Association between inflammatory airway disease of horses and exposure to respiratory viruses: a case control study

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Association between inflammatory airway disease of horses and exposure to respiratory viruses: a case control study

Ashley Houtsma1, Daniela Bedenice1, Nicola Pusterla2, Brenna Pugliese1, Samantha Mapes2, Andrew M Hoffman1, Julia Paxson3, Elizabeth Rozanski1, Jean Mukherjee1, Margaret Wigley1 and Melissa R. Mazan1*

Author Affiliations

1 Cummings School of Veterinary Medicine, Tufts University, North Grafton, MA, USA

2 University of California, Davis, Davis, CA, USA

3 The College of the Holy Cross, Worcester, USA

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Multidisciplinary Respiratory Medicine 2015, 10:33  doi:10.1186/s40248-015-0030-3

The electronic version of this article is the complete one and can be found online at:

Received: 9 June 2015
Accepted: 14 September 2015
Published: 3 November 2015

© 2015 Houtsma et al.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.



Inflammatory airway disease (IAD) in horses, similar to asthma in humans, is a common cause of chronic poor respiratory health and exercise intolerance due to airway inflammation and exaggerated airway constrictive responses. Human rhinovirus is an important trigger for the development of asthma; a similar role for viral respiratory disease in equine IAD has not been established yet.


In a case–control study, horses with IAD (n = 24) were compared to control animals from comparable stabling environments (n = 14). Horses were classified using pulmonary function testing and bronchoalveolar lavage. PCR for equine rhinitis virus A and B (ERAV, ERBV), influenza virus (EIV), and herpesviruses 2, 4, and 5 (EHV-2, EHV-4, EHV-5) was performed on nasal swab, buffy coat from whole blood, and cells from BAL fluid (BALF), and serology were performed. Categorical variables were compared between IAD and control using Fisher’s exact test; continuous variables were compared with an independent t-test. For all analyses, a value of P <0.05 was considered significant.


There was a significant association between diagnosis of IAD and history of cough (P = 0.001) and exercise intolerance (P = 0.003) but not between nasal discharge and IAD. Horses with IAD were significantly more likely to have a positive titer to ERAV (68 %) vs. control horses (32 %). Horses with IAD had higher log-transformed titers to ERAV than did controls (2.28 ± 0.18 v.1.50 ± 0.25, P = 0.038). There was a significant association between nasal shedding (positive PCR) of EHV-2 and diagnosis of IAD (P = 0.002).


IAD remains a persistent problem in the equine population and has strong similarities to the human disease, asthma, for which viral infection is an important trigger. The association between viral respiratory infection and development or exacerbation of IAD in this study suggests that viral infection may contribute to IAD susceptibility; there is, therefore, merit in further investigation into the relationship between respiratory virus exposure and development of IAD.


Asthma; Bronchoalveolar lavage; Equine rhinitis virus; Equine herpesvirus-2; Pulmonary function testing


Inflammatory airway disease (IAD) has been identified as a common cause of respiratory abnormalities and poor performance in horses. IAD is characterized by airway inflammation and airway hyperresponsiveness [1] as well as exercise intolerance, variable coughing, nasal discharge, and increased mucus in the airways [2], and affects a large percentage of stabled horses, resulting in chronic poor respiratory health and poor performance [3]–[5]. The pathophysiology of IAD has not been fully elucidated and is thought to be influenced by both environmental and genetic factors [6]. Although exposure to environmental particulates and endotoxin likely plays a large role in the induction of IAD [7], a role for viral infection in lower airway inflammation has been proposed [5]. Humans suffer from a similar disease, asthma, and respiratory viruses have been firmly connected to the induction and exacerbation of asthma [8]. Human rhinovirus (HRV), genus enteroviridae of the family picornaviridae, is the predominant cause of the common cold and is the most common viral cause of exacerbation of wheezing in patients with asthma [9]. Equine rhinitis virus (ERV, until recently classified as a rhinovirus), is also a picornavirus with the A variant (ERAV) in the Apthovirus genus and the B variants (ERBV-1,2,3) in the Erbovirus genus [10], and is similarly a common cause of respiratory infection in horses [11]. The incidence of ERV in certain equine populations is high, with 43 % of Australian racehorses seroconverting to ERAV within 7 months of entering a training barn [10], however, a role for equine rhinitis viruses in poor performance has yet to be proved [12].

Herpesviruses have also been implicated in poor performance in horses: past studies have associated equine herpesvirus-1 (EHV-1) and equine herpesvirus-4 (EHV-4) infection with IAD, but they have only employed serology [13]. More recently, naturally occurring equine herpesvirus-2 (EHV-2) infection confirmed by PCR has been associated with increased numbers of neutrophils in the respiratory secretions [14] and inoculation with EHV-2 has been shown to result in prolonged (3-week) airway inflammation [15]. Our current study evaluates horses which fulfill a case definition of recent onset or exacerbation of IAD (within the past month) versus control horses for evidence of exposure or active infection with common respiratory viruses including ERAV, ERBV, EHV-2, EHV-4, equine herpesvirus-5 (EHV-5), and equine influenza virus (EIV) measured by PCR of bronchoalveolar lavage fluid cell pellets, peripheral blood buffy coat, and nasal swab, and by serologic detection of viral antibodies. We hypothesized that recent infection with equine rhinitis viruses or other respiratory viruses, similar to respiratory viruses and asthma, is associated with exacerbation or induction of equine IAD.


In accordance with the Consensus on IAD by the American College of Veterinary Internal Medicine [6], criteria for horses with IAD included a history compatible with non-infectious inflammatory airway disease, including cough, exercise intolerance/poor performance, or nasal discharge, as well as recent (within 4 weeks) onset or exacerbation of signs. Further inclusion criteria upon diagnostic sampling included inflammatory BALF cytology (PMNs > 5 % OR mast cells > 2 % OR both). Exclusion criteria for IAD horses included a history more suggestive of recurrent airway obstruction (RAO), including obvious respiratory effort at rest and repeatable episodes of respiratory difficulty when exposed to dusty or moldy environments, recent fever (within 4 weeks), or evidence of bacterial infection on BALF cytology. Control horses were included only if they did not present any history or evidence on physical examination of respiratory disease including cough, nasal discharge, or respiratory effort, or fever for any reason within the past 4 weeks. Control horses were also required to have normal BALF cytology and no evidence of airway hyperresponsiveness or airway obstruction. Horses for this study included those presented to the Hospital for Large Animals at the Cummings School of Veterinary Medicine at Tufts University as well as those seen in the field. In order to standardize environmental conditions, horses were only included in the study if they were stabled at night and turned out during the day, and were fed a combination of hay and concentrate. Horses came from barns with a minimum of 2 horses and a maximum of 30 horses. One barn provided 4 horses, 2 of which had IAD and 2 of which were controls. One barn provided 3 controls, and one barn provided 2 controls. All other horses, both IAD and control, were from separate barns. Both IAD and control horses were sampled throughout the year at similar frequencies, although more IAD than control horses were sampled at all times of year. All horses were pleasure horses or lower-level sport horses. We sampled 46 horses, including 26 horses with a history compatible with IAD and 18 horses without an owner or referring veterinarian complaint of suspected respiratory disease. Of the horses with suspected IAD, 2 had a history or signs on physical examination or lung function testing that were compatible with RAO; these horses were excluded but the other 24 were included in this study. Out of the 18 potential control horses, 3 were lost due to positive histamine bronchoprovocation tests, and one due to presence of guttural pouch infection.

Testing overview

Horses first underwent physical examination including use of a rebreathing bag to enhance auscultation; subsequently, baseline lung function testing and histamine bronchoprovocation (HBP) testing or albuterol challenge were performed followed by bronchoalveolar lavage. Pulmonary function testing required from 20 to 45 min depending on the method used and airway responsiveness of the horse (e.g., forced oscillatory mechanics (FOM) is performed more quickly than flowmetric plethysmography (FP, Open Pleth), and histamine bronchoprovocation is truncated in horses with more reactive airways regardless of method used.) Horses with total respiratory system resistance (R RS ) > 1.5 cmH 2 O/l/s were given 5 puffs of albuterol1 via Aerohippus2[16] and lung function was re-measured after 20 min. A positive response was considered a 25 % or greater decrease in R RS . After lung function testing, bronchoalveolar lavage, nasal swab, and blood draw were performed as described below, taking in total approximately 30 min. The entire procedure took from 1–1.5 h for each horse.

Bronchoalveolar lavage and slide preparation

BAL was performed with either a commercial cuffed BAL tube3 or by bronchoscopy, and 2 aliquots of 250 ml warmed saline, as described previously [1]. The 2 samples were pooled, and slides were prepared by cytocentrifugation or by centrifugation followed by making a thin smear with the sediment. In addition, the BAL fluid was kept on ice and processed within 4 hours for PCR identification of selected viruses. BAL slides were stained with modified Wright stain and Toluidine Blue4 , the latter for enumeration of mast cells [17]. Cells were classified by one of the authors (MRM) as percentage of macrophages, lymphocytes, neutrophils (PMN), eosinophils, and mast cells by classifying a minimum of 500 cells (1,000× magnification).

Pulmonary function testing

Each horse underwent baseline pulmonary function testing followed by either histamine bronchoprovocation or albuterol challenge using either flowmetric plethysmography or forced oscillatory mechanics.

Flowmetric plethysmography was performed with a commercial system5 as described previously [16]. Briefly, each horse was sedated (detomidine6 0.01-0.02 mg/kg BW IV), and fitted with an airtight mask, pneumotachograph7 , and 2 respiratory inductance bands placed at the 11th intercostal space and just behind the last rib. The system was calibrated according to the manufacturer’s instructions. Measurement of airway obstruction was calculated by the software by subtracting the flow signal generated by the thoracic and abdominal volume change from the air flow measured by the pneumotachograph at peak expiration, termed the delta flow (DF). Delta flow increases with bronchoconstriction, as the expected airflow through the pneumotachograph is less than the observed volume shift over time as measured by the abdominal and thoracic bands.

Monosinusoidal forced oscillatory mechanics (FOM, 1-3Hz) was performed as previously described [18]. In brief, total respiratory system resistance (R RS ) was measured in sedated horses (0.4–0.6 mg/kg BW xylazine8 IV). Sinusoidal flow (1–3 Hz) was generated using compressed air (75 psi) released through a proportional pneumatic valve9 and superimposed over the horse’s spontaneous breathing frequency via a latex sealed low dead space facemask. Flow at the mask opening was measured with a pneumotachograph and the difference between mask and atmospheric pressures was recorded with a differential pressure transducer10 . Total respiratory impedance and resultant respiratory resistance were calculated as described previously [18].

Histamine bronchoprovocation

Airway hyperresponsiveness was assessed via histamine bronchoprovocation as previously described [2]. In short, after baseline measurements, either total R RS or DF were measured after nebulization with 0.9 % saline11 (as negative control), and incremental concentrations of histamine12 (2,4,8,16 ,and 32 mg/ml). Sensitivity to histamine was determined as the dose (mg/ml) required to elicit a 75 % increase in R RS using FOM or a 50 % increase in DF using flowmetric plethysmography by interpolation of the dose–response curve [19], [20]. For either method, testing was halted if clinical reaction (increased respiratory rate or effort, repeated coughing) was detected in the horse and the histamine dose at which the clinical reaction occurred was considered to be the reactive dose.

Albuterol challenge

In horses with baseline R RS  > 1.5 cmH 2 O/l/s (3 animals), albuterol was given via metered dose inhaler using the Aerohippus (5 puffs, 90 ucg/puff) to elicit bronchodilation. A positive response was considered ≥ 25 % decrease in R RS . No horse tested via flowmetric plethysmography had a DF greater than 3.5 l/s, therefore all underwent HBP [20].

Sample preparation


Collection tubes of whole blood were allowed to clot for 30 min after sampling, and were centrifuged at 3,000 × g for 10 min at 4 C. The serum was separated and stored at −80 °C until submission for serologic testing.


All samples were kept on ice until they were processed. Four collection tubes of BALF were centrifuged at 500xg for 10 min at 4 °C. Cell pellets were isolated and stored in RNAprotect13 , and the nasal swab was placed in viral culture medium14 . Blood in EDTA was centrifuged at 3,000 × g for 10 min at 4 °C, and the buffy coat was removed and stored in RNAprotect. All samples were held at −80 °C until submission for PCR.

Nucleic acid extraction from whole blood, nasal secretions and bronchoalveolar lavage fluid was performed using an automated nucleic acid extraction system15 according to the manufacturer’s recommendations.

Total RNA was purified as follows: 20 ul of each freshly extracted nucleic acid sample containing genomic DNA (gDNA) and total RNA was digested with DNAse for 60 min at follows: 20 ul of each freshly extracted nucleic acid sample (containing genomic DNA (gDNA) and total RNA) was digested with DNAse for 60 min at 37 °C to remove gDNA. DNase was inactivated at 95 °C for 5 min. Complementary DNA (cDNA) from each sample was synthesized using 50 U SuperScript III16 in a 40 ul final volume containing 50 mM Tris–HCl, pH 8.3, 50 mM KCl, 8 mM MgCl2, 0.5 mM dNTPs, 40 U RNAsin, 0.5 mM dithiothreitol (DTT) and 600 ng random hexadeoxyribonucleotide (pd(N)6) primers (random hexamers17 ). The reaction was performed at 50 °C for 60 min. After inactivation at 95 °C for 5 min, the reaction volume was adjusted to 100 ul with nuclease-free water. Whole blood, nasal secretions and bronchoalveolar lavage fluid was assayed for the presence of EIV, EHV-2, EHV-4, EHV-5, ERAV and ERBV using previously reported qPCR assays [21], [22]. To determine the sample quality and efficiency of nucleic acid extraction we analyzed all samples for the presence of the housekeeping gene equine glyceraldehyde-3-phosphate dehydrogenase (eGAPDH), as previously described [23].

Serologic testing

Evidence of viral infection was assessed through serological examination of single blood samples by using serum neutralization tests for EHV-2, EHV-4, ERAV-1, and ERBV-2, and hemagglutination inhibition tests for EIV-A. Because of inability to determine vaccinal vs infectious cause of positive titers for EHV-4 and EIV-A when only one time point was considered, we only analyzed serology for EHV-2, ERAV-1, and ERBV-2, none of which had available vaccines at the time of the study. Serologic testing was not performed for EHV-5. All serologic testing was performed at Cornell Animal Health Diagnostics Center. A positive titer was determined according to guidelines from the Cornell Animal Health Diagnostics Center (personal communication, Dr. Edward Dubovi), as follows: Titers considered consistent with infection or exposure were defined as follows: ≥8 for EHV-2, ≥96 for ERAV, and ≥32 for ERBV.

Statistical analysis

All continuous variables were examined graphically for normality. Non-normally distributed continuous variables are described with median (range), and normally distributed continuous variables are described with mean ± SEM. Continuous variables that were not normally distributed were transformed mathematically prior to analysis, and described with mean ± SEM. Categorical variables were compared between horses with and without IAD using Fisher’s exact test. Continuous variables were compared between horses with and without IAD using independent t-test. For all analyses, a value of P < 0.05 was considered significant. Data analyses were performed using commercial statistical software18 .


A total of 24 horses with a diagnosis of IAD based on the previously mentioned criteria, and 14 asymptomatic control horses were included in the study. The mean age of IAD-affected horses was 16.2 years ± 0.9, and the mean age of the controls was 14.5 years, ± 1.9. Breeds accounting for 15–23 % of horses were Quarterhorse and Warmblood, breeds accounting for 10–13 % of horses were Grade and Morgan, and Standardbred, Draft, Thoroughbred, Appaloosa, and Paso Fino each accounted for 5 % or less. There were no differences between the IAD and CTL populations for age, sex, or breed (Table 1). Horses with evidence of airway inflammation or abnormal lung function were excluded from the control population; accordingly, IAD horses had significantly greater numbers of neutrophils and mast cells in the BALF, and PC 75 R RS /PC 50 DF were significantly lower (Table 1). Only 5/24 IAD horses had elevated percentages of mast cells with normal percentages of neutrophils, 6/24 had elevated percentages of both mast cells and neutrophils, and the remainder, 13/24, had only elevated percentages of neutrophils. The majority of IAD horses had both abnormal BALF cytology and abnormal pulmonary function tests (21/24). The 3/24 IAD horses with normal PFTs had normal PMN percentages on BALF with elevated mast cell percentages. There was a strong association between elevated percentages of BALF neutrophils or mast cells and abnormal lung function (either airway hyperresponsiveness (AWHR) or response to albuterol challenge), P < 0.001. The majority of horses with IAD had an owner complaint of cough (75 %), or exercise intolerance/poor performance (83 %), whereas only a small number had an owner complaint of nasal discharge (17 %). There was a significant association between history of cough (P = 0.001) and exercise intolerance (P = 0.003) and diagnosis of IAD, but not between nasal discharge and IAD (Table 1). There was no association between history of cough or exercise intolerance and PCR-detection of any virus.

Table 1. Descriptive statistics for the study population

Serology was available for 22/24 horses with IAD and 13/14 control horses. There was a high seroprevalence for ERAV (54 %), ERBV (89 %), and EHV-2 (40 %) in the entire population, but horses with IAD more frequently had positive titers to ERAV (68 %) v. control horses (31 %) (P < 0.03) (Table 2). Horses with a diagnosis of IAD had higher log-transformed titers to ERAV than did control horses. (2.28 ± 0.18 v. 1.50 ± 0.25, P = 0.038) (Fig. 1).

Table 2. Seroprevalence for ERAV, ERBV, and EHV2 in the study population

thumbnailFig. 1. Serum neutralizing antibodies to ERAV were measured in 22/24 horses with a diagnosis of IAD and in 13/14 control horses. The antibody titers were log-transformed and expressed as mean ± standard error of the mean. Student’s paired t-test was used and found that ERAV titers in the IAD group were significantly higher than in the CTL group (2.28 ± 0.18 v. 1.50 ± 0.25). *Indicates a significant difference between groups (P = 0.038)

PCR was available for all horses in the study. No sample for any horse was positive for EHV-4 or ERAV. Out of 38 horses tested, only 12 were PCR positive on any sample for any virus, 9/12 of these horses were in the IAD group. Six IAD horses were positive for EHV-2 on nasal swab, but no control horse was positive (Table 3). There was a significant association between nasal shedding (positive PCR) of EHV-2 and diagnosis of IAD (P = 0.002) (Table 3). There were no associations between airway neutrophilia or mastocytosis and positive PCR status or between AWHR and positive PCR status.

Table 3. Respiratory virus and sample site for horses positive on PCR testing


This study was designed to determine if current or recent infection with equine rhinitis virus or other respiratory viruses plays a role in the development or worsening of IAD. In humans, wheezing episodes in early life due to infection with HRV significantly increase the chances of a diagnosis of the similar disease, asthma, at six years of age [24], and infections later in life are associated with worsening of asthma [25]. Herpesviruses are less firmly linked to wheezing episodes in early life in human infants [25], but may be associated with development of other atopic disease through immune dysregulation [26]. Despite the strong association of HRV with asthma, recent data suggest that development of asthma later in life may be dependent on the number of viral respiratory infection episodes rather than the type of virus [27]. In all, the evidence firmly inculpates respiratory virus as an important determinant of development of asthma. In contrast, although researchers and clinicians have long suspected that respiratory viruses are important to the development or exacerbation of IAD in horses [5], [28], [29], there is a paucity of data in the veterinary literature definitively making this link, and this lack was identified in the last ACVIM Consensus Statement on IAD [6].

Our study showed that there was a significant association between diagnosis of IAD and seropositivity to ERAV, with 68 % of horses with IAD versus 31 % of control horses having a titer ≥96 (Table 2). A vaccine for ERAV has only recently been available commercially, and was not available during the study time period; thus, these titers reflect the natural infection status of the horses. Not only did more IAD than CTL horses have positive titers to ERAV, but IAD horses also had significantly higher log-transformed titers for ERAV than did control horses (Fig. 1). Although serology for EHV-2 failed to distinguish IAD from CTL horses (Table 2), and few horses were PCR positive on any sample to any virus (Table 3), nonetheless there was a significant association between EHV-2 shedding (positive nasal swab on PCR) and diagnosis of IAD (Table 3), primarily because the only horses positive on nasal swab for EHV2 had a diagnosis of IAD. Although these associations do not provide any causal relationships, they do provide us some justification for further investigation and discussion.

In considering the serologic evidence for the role of ERAV in the etiology of IAD, it is important to consider what has previously been termed a positive titer and used to report seroprevalences. Our study employed the cut-point of 96 for ERAV using the guidelines of the laboratory in which the serological testing was performed (Edward Dubovi, personal communication), and was concordant with that used in a study in which seropositive horses had titers of ≥100 [30]. In contrast, in other studies, a positive serum-neutralizing titer has been considered >2 [31], and >10 [10] although it was noted that in older horses titers were in the range of >512 . In a recent experimental study, all ponies prior to infection had serum neutralizing titers for ERAV <2, rising to 64 on day 7 after infection [32] whereas in a suspected natural outbreak, titers of 1,024 were seen [33]. Although there is variability in the designation of a positive titer, nonetheless, our cut-point is within the range of those previously reported. In addition, both age and geography seem to be important in determining seroprevalence for ERAV, with titers lower in younger horses and higher in older horses; as our horses were not young, we would expect their titers to be in the higher range [31]. In contrast, the majority of studies finds that seroprevalence to ERBV is high in multiple age groups [34], similar to our findings (Table 2).

There are varying reports of active disease based on virus isolation and PCR for ERVs depending on the methodology used, whereas there is a consensus that HRV is ubiquitous in human populations [35]. Although PCR is more sensitive than virus isolation, in a recent study of over 200 cases of suspected naturally occurring viral respiratory disease only 11 % of those that were negative for ERAV on virus isolation were positive on PCR [36]. Our study, in which no horse was PCR positive for ERAV and only 3/38 horses had nasal secretions positive for ERBV (Table 3), was similar to one recently reported in which no horses with acute respiratory disease had PCR-positive nasal swab, and ERBV was found in the nasal secretions of only 2.7 % of horses [21]. A year-long longitudinal study in young Standardbreds likewise found a small number of horses PCR positive for any respiratory virus on nasal swab [12]. Positive PCR identification of the other respiratory viruses (whether on BALF cell pellet, nasal swab, or buffy coat) was found with relatively low frequency in our study [Table 3]. This low prevalence of PCR positive results likely reflects the variable natural course of disease. Similarly to HRV in humans, ERAV is cleared quickly from the equine respiratory system (within 2 weeks) [11]. Despite this rapid clearance, high antibody titers are still present at 21 to 35 days after infection with ERAV [11], [33]. This is most likely the reason that, in contrast to our expectation that PCR detection of virus would be more effective in providing the link between respiratory viral disease and diagnosis of IAD, instead, due to sample timing, the indirect serologic evidence was more revealing.

In addition to a possible role for rhinitis viruses, our study showed that although only a small subset of horses was positive on nasal swab for EHV-2, this nonetheless was positively associated with a clinical diagnosis of IAD. EHV-2 is a slow-growing cytomegalovirus that has been reported to infect foals early in life and to have a high seroprevalence [37]. Although the pathogenicity of EHV-2 has previously been debated given that it can be recovered from both clinically affected and healthy animals [13], studies have linked its pathogenic potential to a modulation of the host immune response [38]. A recent study demonstrates that field strains of EHV-2 were detected in 50 % of horses tested, and after reactivation of latent infection using systemic corticosteroids, EHV-2 is detectable in the trachea up to 14 days [15]. Although this study and others have failed to show associations between clinical signs or tracheal neutrophils and EHV-2 [39], or indeed between EHV-2 viral load and poor performance [40] a recent study showed that inoculation with equine herpesvirus-2 results in prolonged neutrophilia in BALF despite resolution of other clinical signs, suggesting that the gammaherpesviruses may indeed play a role in the development of airway inflammation in horses [14]. Unlike HRV, there is far less evidence in human medicine for the involvement of herpesviruses in childhood wheeze or indeed development of asthma. Although serologic evidence of cytomegalovirus infection (a betaherpesvirus) was more prevalent in infants with asthma-like bronchial symptoms than in age-matched infants with no wheezing, arguing for cytomegalovirus infection playing some role in these cases [41], in a different study, having more than one herpesvirus infection before the age of three was actually inversely associated with asthma at age seven [42]. In horses, it has been proposed that EHV-2 modifies Il-10 [43], and may thus affect long-term respiratory responses through modulation of the immune response. On the other hand, as EHV2 has been shown to establish latency [44], it may be that the presence of active shedding is secondary to airway inflammation rather than a cause of airway inflammation. It remains to be determined if EHV-2 is one of the many possible insults that, combined, drive the equine respiratory phenotype toward IAD.

There was a relatively small number of horses testing PCR positive for any other viruses, which is likely due, as with ERAV, to the natural course of disease in comparison to the single sampling timeframe of our study. Equine influenza virus has been shown to be shed in nasal secretions of immunized horses for an average of 6–8 days after infection [45], while equine herpesvirus-1\-4 can be shed in nasal secretions for 14–75 days after infection [46], [47] and reactivated latent herpes virus infections are common. [48] A recent study showed that when subclinical viral respiratory disease was detected on nasal swab, horses had not seroconverted yet. [12]. Therefore, it is not surprising that sampling apparently healthy, non-febrile horses at a single time point yielded low numbers of positive PCR identification of respiratory virus. In fact, when the prevalence of respiratory disease in horses in New Zealand was surveyed, although EHV-2 and EHV-4 were among the most common viruses detected upon PCR, these viruses were only detected in horses with evidence of febrile respiratory illness [49]. Thus, selection bias likely also contributed to low EHV detection rates because horses that were PCR positive for a respiratory virus would more likely have a recent history of fever and malaise, and would have been excluded from the study. Nonetheless, it is of interest to clinicians that in a population of horses without history or clinical signs of current viral infection, 8/38 horses were shedding virus, and only one of those horses was in the control group. Further, nasal discharge, which is commonly seen in horses with viral respiratory infections, was not positively associated with PCR-positive virus status or a diagnosis of IAD (Table 1) and only one of the horses that shed virus had nasal discharge. This is in accordance with prior conclusions that subclinical infection with respiratory viruses is common among equine populations [31], [50].

The strong connections that have been established between respiratory viral infection and asthma in humans suggest that this may be a good model for understanding the relationship between similar equine respiratory viruses, airway inflammation and functional pulmonary derangements in horses. Recent studies have shown that there are multiple factors at play in the development of disease: asthmatics presenting to the emergency room, for instance, do not have higher viral loads than non-asthmatics [51], but it may be that a second hit, such as an environment high in dust mites [52], as well as the influences of genetics, diet, age, and immune responses [53], is necessary to precipitate a crisis. Moreover, there appear to be, as a recent study termed it, a panoply of ‘unique cellular immune factors’ that work in concert with HRV to result in wheezing and long-term asthma in children exposed to HRV [53], including a deficiency of the interferon response due to Th2 polarization in atopic individuals and a subsequent maladaptive immune response [53]. Likewise, the development of equine IAD appears to involve multiple different factors, including environment, in addition to the proposed role of respiratory viruses [6], [7]. There is emerging, if somewhat conflicting, evidence that some horses with IAD also have a polarized Th2 response [54], making it tempting to speculate that a maladaptive immune response may likewise contribute to the development of enhanced airway inflammation and hyperresponsiveness in horses with ERAV or other viral respiratory infection.

A recent review implicates changes in airway biology which result in initiation and progression of airway remodeling, disruption of the epithelial barrier, decreased ciliary function, and production of growth factors and metalloproteinases in HRV-associated asthma perturbations [35]. Although both HRV and the similar picornaviruses, ERAV and ERBV, are commonly associated only with relatively mild upper airway symptoms and signs including pharyngitis, nasal discharge, coughing and variable fever, both are able to infect the lower airways as well as the upper airways, causing long-term airway inflammation and potentially ciliary dysfunction with loss of clearance [32], [55], [56]. It is logical, therefore, that HRV causes reduced lung function [57] and AWHR in humans [58]. Despite the relatively quick clearance of HRV from the respiratory system, AWHR to methacholine persists in children from 5–11 weeks after natural infection with HRV [55]. Although a recent study in horses failed to find an overall increase in AWHR in affected ponies, primarily due to pre-existent AWHR in principal and control animals, nonetheless, individual animals did have a heightened response to histamine after infection with ERAV. [32] In our study, chi-square analysis showed a strong association between elevated percentages of BALF neutrophils or mast cells and abnormal lung function (either AWHR or response to albuterol challenge), P < 0.001, and the majority of IAD horses (>90 %) had evidence of abnormal lung function on pulmonary function testing. Our study concords with findings by other workers, where cough was highly associated with a diagnosis of IAD [59], [60]. However, due to our study design excluding horses with abnormal lung function from the control group, we were unable to look for associations across the whole population of horses between PCR or evidence of viral infection and abnormalities on lung function. In contrast to previous studies from our laboratory [1], [2], there was no correlation between AWHR and BALF cell percentages. This may be a reflection of our population: previous studies from our laboratory have had a significant proportion of young racehorses, whereas this study involved primarily middle-aged lower-level sport horses.

Clearly, there are limitations to this study. Although our samples were quickly placed on ice and transferred within 4 hours to the laboratory for appropriate storage, it is possible that samples may have degraded in transit. In addition, we may have had a higher percentage of horses testing positive on PCR if we had swabbed the nasopharynx rather than the nasal passages alone [30]. We were unable to use serology to investigate the relationship between IAD and viruses other than EHV-2, ERAV and ERBV, as we sampled only at one time-point, and we were thus unable to differentiate vaccinal status vs natural exposure. Had we sampled at 4-week intervals to detect rising titers, we might have detected a role for the more commonly diagnosed respiratory viruses in the development of IAD. As discussed above, it has been suggested that cumulative exposures to HRV are critical to the development of the asthmatic phenotype [35]. Although a longitudinal study of young Standardbred racehorses failed to find any associations among seroconversion, single antibody titers, or PCR positivity to rhinitis viruses and poor performance [12], a longitudinal study of respiratory viral disease in older performance horses may be necessary to adequately parse out the connection to development of the IAD phenotype which may develop with time and repeated insult to the respiratory system. Because environment is thought to be one of the most important of the possible repeated insults to the equine respiratory system, we standardized environment as much as possible by ensuring that horses came from very similar environments, namely a combination of stall and turnout, and that they had similar bedding and similar feed. We also ensured that control horses came from multiple different barns, therefore rendering the possibility of infection with respiratory virus more random. Nonetheless, in an ideal experiment, exposure to respiratory virus would be the only intervention made in horses housed in identical environments, thus rendering any outcome more obvious and clear. Moreover, there is a strong heritable component to asthma in children as well as mutations that may enhance viral binding in asthmatic airways [61]; no heritable component has yet been demonstrated for IAD in horses but there is some evidence for genetics to play a role in the more severe disease, RAO [62]. Future investigations into the genetics of IAD will be necessary eventually to determine if genetics and viral respiratory infection work together to create chronic disease.


In conclusion, this study found that a greater percentage of horses with diagnosis of recent onset or exacerbation of IAD defined by appropriate clinical history, BALF cytology and PFTs had positive titers to ERAV than did control horses, and horses with a diagnosis of IAD had higher log-transformed titers to ERAV than controls. In addition, a diagnosis of IAD was associated with nasal shedding of EHV-2 (positive nasal swab PCR). The authors recognize that these findings are associations without having evidence of causation; nonetheless, this study provides an intriguing possible link between viral respiratory disease and exacerbation or onset of IAD. IAD remains a persistent problem in the equine population and has strong similarities to the human disease, asthma, the development or exacerbation of which is strongly associated with viral respiratory disease. Our study suggests that there is merit in further investigation of the role of viral respiratory disease in initiation or exacerbation of IAD in order to better understand disease in both horses and humans.


AWHR: Airway hyperresponsiveness

BAL: Bronchoalveolar lavage

BALF: Bronchoalveolar lavage fluid

DF: Delta flow

FOM: Forced oscillatory mechanics

FP: Flowmetric plethysmography

HRV: Human rhino virus

HBP: Histamine bronchoprovocation

IAD: Inflammatory airway disease

PMN: Polymorphonuclear leukocyte

RAO: Recurrent airway obstruction

R RS : Total respiratory system resistance

Competing interests

The author declares that there is no competing interest.

Authors’ contributions

AH performed pulmonary function testing and bronchoalveolar lavage, and helped draft the manuscript. DB helped to conceive the study, helped in performing pulmonary function testing and bronchoalveolar lavage, and helped to draft the manuscript. NP and SM carried out the PCR analysis. BP and MW helped in performing pulmonary function testing, bronchoalveolar lavage and helped draft the manuscript. AMH helped in pulmonary function testing and edited the manuscript. JP, JM, and ER assisted in study design. MRM conceived of the study, and participated in all data acquisition and manuscript preparation. All authors read and approved the final manuscript.


The work for this study was performed at the Cummings School of Veterinary Medicine, Tufts University. This study was supported by a grant from the Boehringer Ingelheim Advancement in Equine Research Award Program.

End notes

    1. Ventolin HFA, GlaxoSmithKline, Philadelphia, PA

    1. Aerohippus, Trudell Medical International, London, Ontario, Canada.

    1. Bivona Medical Technologies, Gary, IL

    1. Toluidine Blue, Polyscientific, Bayshore, NY

    1. Open Pleth, Ambulatory Monitoring Inc, Ardsley, NY

    1. Dormosedan, Orion Pharma, Espoo, Finland

    1. Fleisch, No 4, OEM Medical, Lenoir, NC

    1. AnaSed, Akorn Inc, Decatur, IL

    1. Proportional valve No. 602 00001, Joucomatic, Rueil, France

    1. DP45-28, Validyne Engineering, Northridge, CA

    1. 0.9 % preservative-free saline, Hospira Inc, Lake Forest, IL

    1. Histamine diphosphate monohydrate, MP Biomed, Solon, OH

    1. RNA protect, QIAGEN

    1. Viral culture medium

    1. CAS-1820 X-tractor Gene, Corbett Life Science

    1. SuperScript III reverse transcriptase, Invitrogen, Grand Island, NY

    1. Random hexamers primers, Invitrogen, Grand Island, NY

  1. SPSS v. 13.0, SPSS Corp, Chicago, IL


  1. Hoffman AM, Mazan MR, Ellenberg S. Association between bronchoalveolar lavage cytologic features and airway reactivity in horses with a history of exercise intolerance. Am J Vet Res. 1998; 59:176-81. PubMed Abstract | Publisher Full Text OpenURL
  2. Bedenice D, Mazan MR, Hoffman AM. Association between cough and cytology of bronchoalveolar lavage fluid and pulmonary function in horses diagnosed with inflammatory airway disease. J Vet Intern Med. 2008; 22:1022-8. PubMed Abstract | Publisher Full Text OpenURL
  3. Robinson NE, Karmaus W, Holcombe SJ, Carr EA, Derksen FJ. Airway inflammation in Michigan pleasure horses: prevalence and risk factors. Equine Vet J. 2006; 38:293-9. PubMed Abstract | Publisher Full Text OpenURL
  4. Wilsher S, Allen WR, Wood JL. Factors associated with failure of thoroughbred horses to train and race. Equine Vet J. 2006; 38:113-8. PubMed Abstract | Publisher Full Text OpenURL
  5. Wood JL, Newton JR, Chanter N, Mumford JA. Association between respiratory disease and bacterial and viral infections in British racehorses. J Clin Microbiol. 2005; 43:120-6. PubMed Abstract | Publisher Full Text OpenURL
  6. Couetil LL, Hoffman AM, Hodgson J, Buechner-Maxwell V, Viel L, Wood JL et al.. Inflammatory airway disease of horses. J Vet Intern Med. 2007; 21:356-61. PubMed Abstract | Publisher Full Text OpenURL
  7. Ivester KM, Couetil LL, Moore GE, Zimmerman NJ, Raskin RE. Environmental exposures and airway inflammation in young thoroughbred horses. J Vet Intern Med. 2014; 28:918-24. PubMed Abstract | Publisher Full Text OpenURL
  8. Khetsuriani N, Kazerouni NN, Erdman DD, Lu X, Redd SC, Anderson LJ et al.. Prevalence of viral respiratory tract infections in children with asthma. J Allergy Clin Immunol. 2007; 119:314-21. PubMed Abstract | Publisher Full Text OpenURL
  9. Fujitsuka A, Tsukagoshi H, Arakawa M, Goto-Sugai K, Ryo A, Okayama Y et al.. A molecular epidemiological study of respiratory viruses detected in Japanese children with acute wheezing illness. BMC Infect Dis. 2011; 11:168. PubMed Abstract | BioMed Central Full Text OpenURL
  10. Black WD, Wilcox RS, Stevenson RA, Hartley CA, Ficorilli NP, Gilkerson JR et al.. Prevalence of serum neutralising antibody to equine rhinitis A virus (ERAV), equine rhinitis B virus 1 (ERBV1) and ERBV2. Vet Microbiol. 2007; 119:65-71. PubMed Abstract | Publisher Full Text OpenURL
  11. Horsington J, Lynch SE, Gilkerson JR, Studdert MJ, Hartley CA. Equine picornaviruses: well known but poorly understood. Vet Microbiol. 2013; 167:78-85. PubMed Abstract | Publisher Full Text OpenURL
  12. Back H, Penell J, Pringle J, Isakson M, Roneus N, Berndtsson LT et al.. A longitudinal study of poor performance and subclinical respiratory viral activity in Standardbred trotters. Vet Rec Open. 2015; 2:e000107. OpenURL
  13. Dynon K, Black WD, Ficorilli N, Hartley CA, Studdert MJ. Detection of viruses in nasal swab samples from horses with acute, febrile, respiratory disease using virus isolation, polymerase chain reaction and serology. Aust Vet J. 2007; 85:46-50. PubMed Abstract | Publisher Full Text OpenURL
  14. Fortier G, van Erck E, Fortier C, Richard E, Pottier D, Pronost S et al.. Herpesviruses in respiratory liquids of horses: putative implication in airway inflammation and association with cytological features. Vet Microbiol. 2009; 139:34-41. PubMed Abstract | Publisher Full Text OpenURL
  15. Fortier G, Richard E, Hue E, Fortier C, Pronost S, Pottier D et al.. Long-lasting airway inflammation associated with equid herpesvirus-2 in experimentally challenged horses. Vet J. 2013; 197:492-5. PubMed Abstract | Publisher Full Text OpenURL
  16. Mazan MR, Lascola K, Bruns SJ, Hoffman AM. Use of a novel one-nostril mask-spacer device to evaluate airway hyperresponsiveness (AHR) in horses after chronic administration of albuterol. Can J Vet Res. 2014; 78:214-20. PubMed Abstract | Publisher Full Text OpenURL
  17. Leclere M, Desnoyers M, Beauchamp G, Lavoie JP. Comparison of four staining methods for detection of mast cells in equine bronchoalveolar lavage fluid. J Vet Intern Med. 2006; 20:377-81. PubMed Abstract | Publisher Full Text OpenURL
  18. Mazan MR, Hoffman AM, Manjerovic N. Comparison of forced oscillation with the conventional method for histamine bronchoprovocation testing in horses. Am J Vet Res. 1999; 60:174-80. PubMed Abstract | Publisher Full Text OpenURL
  19. Nolen-Walston RD, Kuehn H, Boston RC, Mazan MR, Wilkins PA, Bruns S et al.. Reproducibility of airway responsiveness in horses using flowmetric plethysmography and histamine bronchoprovocation. J Vet Intern Med. 2009; 23:631-5. PubMed Abstract | Publisher Full Text OpenURL
  20. Wichtel M, Gomez D, Burton S, Wichtel J, Hoffman A. Relationships between equine airway reactivity measured by flowmetric plethysmography and specific indicators of airway inflammation in horses with suspected inflammatory airway disease. Equine Vet J. 2015;doi:10.1111/evj.12482.
  21. Pusterla N, Mapes S, Wademan C, White A, Hodzic E. Investigation of the role of lesser characterised respiratory viruses associated with upper respiratory tract infections in horses. Vet Rec. 2013; 172:315. PubMed Abstract | Publisher Full Text OpenURL
  22. Pusterla N, Kass PH, Mapes S, Johnson C, Barnett DC, Vaala W et al.. Surveillance programme for important equine infectious respiratory pathogens in the USA. Vet Rec. 2011; 169:12. PubMed Abstract | Publisher Full Text OpenURL
  23. Mapes S, Leutenegger CM, Pusterla N. Nucleic acid extraction methods for detection of EHV-1 from blood and nasopharyngeal secretions. Vet Rec. 2008; 162:857-9. PubMed Abstract | Publisher Full Text OpenURL
  24. Busse WW, Lemanske RF, Gern JE. Role of viral respiratory infections in asthma and asthma exacerbations. Lancet. 2010; 376:826-34. PubMed Abstract | Publisher Full Text OpenURL
  25. Moreno-Valencia Y, Hernandez-Hernandez VA, Romero-Espinoza JA, Coronel-Tellez RH, Castillejos-Lopez M, Hernandez A, et al. Detection and Characterization of respiratory viruses causing Acute Respiratory Illness and Asthma Exacerbation in children during Three Different Season (2011–2014) in Mexico City. Influenza Other Respir Viruses. 2015: doi:10.1111/irv.12346.
  26. Leung DY. New insights into atopic dermatitis: role of skin barrier and immune dysregulation. Allergol Int. 2013; 62:151-61. PubMed Abstract | Publisher Full Text OpenURL
  27. Carlsson CJ, Vissing NH, Sevelsted A, Johnston SL, Bonnelykke K, Bisqaard H. Duration of wheezy episodes in early childhood is independent of the microbial trigger. J Allergy Clin Immunol. 2015: doi:10.1016/j.jaci.2015.05.003.
  28. Mumford JA, Rossdale PD. Virus and its relationship to the “poor performance” syndrome. Equine Vet J. 1980; 12:3-9. PubMed Abstract | Publisher Full Text OpenURL
  29. Christley RM, Rose RJ, Hodgson DR, Reid SW, Evans S, Bailey C et al.. Attitudes of Australian veterinarians about the cause and treatment of lower-respiratory-tract disease in racehorses. Prev Vet Med. 2000; 46:149-59. PubMed Abstract | Publisher Full Text OpenURL
  30. Dunowska M, Wilks CR, Studdert MJ, Meers J. Viruses associated with outbreaks of equine respiratory disease in New Zealand. N Z Vet J. 2002; 50:132-9. PubMed Abstract | Publisher Full Text OpenURL
  31. Kriegshauser G, Deutz A, Kuechler E, Skern T, Lussy H, Nowotny N. Prevalence of neutralizing antibodies to Equine rhinitis A and B virus in horses and man. Vet Microbiol. 2005; 106:293-6. PubMed Abstract | Publisher Full Text OpenURL
  32. Diaz-Mendez A, Hewson J, Shewen P, Nagy E, Viel L. Characteristics of respiratory tract disease in horses inoculated with equine rhinitis A virus. Am J Vet Res. 2014; 75:169-78. PubMed Abstract | Publisher Full Text OpenURL
  33. Diaz-Mendez A, Viel L, Hewson J, Doig P, Carman S, Chambers T et al.. Surveillance of equine respiratory viruses in Ontario. Can J Vet Res. 2010; 74:271-8. PubMed Abstract | Publisher Full Text OpenURL
  34. Dunowska M, Wilks CR, Studdert MJ, Meers J. Equine respiratory viruses in foals in New Zealand. N Z Vet J. 2002; 50:140-7. PubMed Abstract | Publisher Full Text OpenURL
  35. Jamieson KC, Warner SM, Leigh R, et al. Rhinovirus in the pathogenesis and clinical course of asthma. Chest. 2015: doi:. 10. 1378/chest.15-1335 OpenURL
  36. Quinlivan M, Maxwell G, Lyons P, Proud D. Real-time RT-PCR for the detection and quantitative analysis of equine rhinitis viruses. Equine Vet J. 2010; 42:98-104. PubMed Abstract | Publisher Full Text OpenURL
  37. Bell SA, Balasuriya UB, Gardner IA, Barry PA, Wilson WD, Ferarro GL et al.. Temporal detection of equine herpesvirus infections of a cohort of mares and their foals. Vet Microbiol. 2006; 116:249-57. PubMed Abstract | Publisher Full Text OpenURL
  38. Fortier G, van Erck E, Pronost S, Lekeux P, Thiry E. Equine gammaherpesviruses: pathogenesis, epidemiology and diagnosis. Vet J. 2010; 186:148-56. PubMed Abstract | Publisher Full Text OpenURL
  39. Brault SA, Bird BH, Balasuriya UB, MacLachlan NJ. Genetic heterogeneity and variation in viral load during equid herpesvirus-2 infection of foals. Vet Microbiol. 2011; 147:253-61. PubMed Abstract | Publisher Full Text OpenURL
  40. Back H, Ullman K, Treiberg Berndtsson L, Riihimaki M, Penell J, Stahl K et al.. Viral load of equine herpesviruses 2 and 5 in nasal swabs of actively racing Standardbred trotters: Temporal relationship of shedding to clinical findings and poor performance. Vet Microbiol. 2015; 179:142-8. PubMed Abstract | Publisher Full Text OpenURL
  41. Morisawa Y, Maeda A, Sato T, Hisakawa H, Fujieda M, Wakiguchi H. Cytomegalovirus infection and wheezing in infants. Pediatr Int. 2008; 50:654-7. PubMed Abstract | Publisher Full Text OpenURL
  42. Illi S, von Mutius E, Lau S, Bergmann R, Niggemann B, Sommerfeld C et al.. Early childhood infectious diseases and the development of asthma up to school age: a birth cohort study. BMJ. 2001; 322:390-5. PubMed Abstract | Publisher Full Text OpenURL
  43. Telford EA, Watson MS, Aird HC, Perry J, Davison AJ. The DNA sequence of equine herpesvirus 2. J Mol Biol. 1995; 249:520-8. PubMed Abstract | Publisher Full Text OpenURL
  44. Drummer HE, Reubel GH, Studdert MJ. Equine gammaherpesvirus 2 (EHV2) is latent in B lymphocytes. Arch Virol. 1996; 141:495-504. PubMed Abstract | Publisher Full Text OpenURL
  45. Paillot R, Prowse L, Montesso F, Stewart B, Jordon L, Newton JR et al.. Duration of equine influenza virus shedding and infectivity in immunised horses after experimental infection with EIV A/eq2/Richmond/1/07. Vet Microbiol. 2013; 166:22-34. PubMed Abstract | Publisher Full Text OpenURL
  46. van Maanen C. Equine herpesvirus 1 and 4 infections: an update. Vet Q. 2002; 24:58-78. PubMed Abstract | Publisher Full Text OpenURL
  47. Hussey SB, Clark R, Lunn KF, Breathnach C, Soboll G, Whalley JM et al.. Detection and quantification of equine herpesvirus-1 viremia and nasal shedding by real-time polymerase chain reaction. J Vet Diagn Invest. 2006; 18:335-42. PubMed Abstract | Publisher Full Text OpenURL
  48. Lunn DP, Davis-Poynter N, Flaminio MJ, Horohov DW, Osterrieder K, Pusterla N et al.. Equine herpesvirus-1 consensus statement. J Vet Intern Med. 2009; 23:450-61. PubMed Abstract | Publisher Full Text OpenURL
  49. McBrearty KA, Murray A, Dunowska M. A survey of respiratory viruses in New Zealand horses. N Z Vet J. 2013; 61:254-61. PubMed Abstract | Publisher Full Text OpenURL
  50. Chambers TM. A brief introduction to equine influenza and equine influenza viruses. Methods Mol Biol. 2014; 1161:365-70. PubMed Abstract | Publisher Full Text OpenURL
  51. Kennedy JL, Shaker M, McMeen V, Gern J, Carper H, Murphy D et al.. Comparison of viral load in individuals with and without asthma during infections with rhinovirus. Am J Respir Crit Care Med. 2014; 189:532-9. PubMed Abstract | Publisher Full Text OpenURL
  52. Soto-Quiros M, Avila L, Platts-Mills TA, Hunt JF, Erdman DD, Carper H et al.. High titers of IgE antibody to dust mite allergen and risk for wheezing among asthmatic children infected with rhinovirus. J Allergy Clin Immunol. 2012; 129:1499-1505.e5. PubMed Abstract | Publisher Full Text OpenURL
  53. Gern JE. The ABCs of rhinoviruses, wheezing, and asthma. J Virol. 2010; 84:7418-26. PubMed Abstract | Publisher Full Text OpenURL
  54. Beekman L, Tohver T, Leguillette R. Comparison of cytokine mRNA expression in the bronchoalveolar lavage fluid of horses with inflammatory airway disease and bronchoalveolar lavage mastocytosis or neutrophilia using REST software analysis. J Vet Intern Med. 2012; 26:153-61. PubMed Abstract | Publisher Full Text OpenURL
  55. Xepapadaki P, Papadopoulos NG, Bossios A, Manoussakis E, Manousakas T, Saxoni-Papageorgiou P et al.. Duration of postviral airway hyperresponsiveness in children with asthma: effect of atopy. J Allergy Clin Immunol. 2005; 116:299-304. PubMed Abstract | Publisher Full Text OpenURL
  56. Radin JM, Hawksworth AW, Kammerer PE, Balansay M, Raman R, Lindsay SP et al.. Epidemiology of pathogen-specific respiratory infections among three US populations. PLoS One. 2014; 9:e114871. PubMed Abstract | Publisher Full Text OpenURL
  57. Zambrano JC, Carper HT, Rakes GP, Patrie J, Murphy DD, Platts-Mills TA et al.. Experimental rhinovirus challenges in adults with mild asthma: response to infection in relation to IgE. J Allergy Clin Immunol. 2003; 111:1008-16. PubMed Abstract | Publisher Full Text OpenURL
  58. Brooks GD, Buchta KA, Swenson CA, Gern JE, Busse WW. Rhinovirus-induced interferon-gamma and airway responsiveness in asthma. Am J Respir Crit Care Med. 2003; 168:1091-4. PubMed Abstract | Publisher Full Text OpenURL
  59. Dixon PM, Railton DI, McGorum BC. Equine pulmonary disease: a case control study of 300 referred cases. Part 2: Details of animals and of historical and clinical findings. Equine Vet J. 1995; 27:422-7. PubMed Abstract | Publisher Full Text OpenURL
  60. Rettmer H, Hoffman AM, Lanz S, Oertly M, Gerber V. Owner-reported coughing and nasal discharge are associated with clinical findings, arterial oxygen tension, mucus score and bronchoprovocation in horses with recurrent airway obstruction in a field setting. Equine Vet J. 2015; 47:291-5. PubMed Abstract | Publisher Full Text OpenURL
  61. Vijgen L, Van Essche M, Van Ranst M. Absence of the Kilifi mutation in the rhinovirus-binding domain of ICAM-1 in a Caucasian population. Genet Test. 2003; 7:159-61. PubMed Abstract | Publisher Full Text OpenURL
  62. Gerber V, Tessier C, Marti E. Genetics of upper and lower airway diseases in the horse. Equine Vet J. 2014; 47(4):390-7. PubMed Abstract | Publisher Full Text OpenURL

Integrating technology into cognitive behavior therapy for adolescent depression: a pilot study

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Integrating technology into cognitive behavior therapy for adolescent depression: a pilot study

Kenneth A. Kobak1*, James C. Mundt1 and Betsy Kennard2

Author Affiliations

1 Center for Telepsychology, 22 North Harwood, Madison 53717, WI, USA

2 UT Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas 75390, TX, USA

For all author emails, please log on.

Annals of General Psychiatry 2015, 14:37  doi:10.1186/s12991-015-0077-8

The electronic version of this article is the complete one and can be found online at:

Received: 22 May 2015
Accepted: 20 October 2015
Published: 3 November 2015

© 2015 Kobak et al.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.



Rapid advances in information technology and telecommunications have resulted in a dramatic increase in the use of mobile devices and the internet to enhance and facilitate access to treatment. Cognitive behavior therapy (CBT) is an empirically based treatment that is well suited for enhancement by new technologies, particularly with youth. To facilitate the dissemination of this evidence-based treatment, we developed a technology-enhanced CBT intervention for the treatment of adolescent depression consisting of (1) online therapist training (2) in-session use of tablets for teaching clients CBT concepts and skills, and (3) text messaging for between session homework reminders and self-monitoring.


Eighteen licensed clinicians (social workers n = 7, psychologists n = 9) were randomized to have their patients receive either the intervention (CBT) or treatment as usual (TAU). Each clinician treated four adolescents for 12 weeks. Clinicians in the CBT arm completed an online tutorial on CBT treatment of adolescent depression, then received an iPad with access to patient education materials for teaching CBT concepts to patients during sessions. Individualized text messages were integrated into treatment for homework reminders, support, and outcomes measurement. Outcome measures included a 49-item multiple choice test for tutorial effectiveness; the system usability scale (SUS) for user satisfaction; quick inventory of depressive symptomatology–adolescent version (QIDS-A-Pat); and clinician and patient ratings on the therapeutic alliance scale for adolescents (TASA).


A significant increase in knowledge of CBT concepts was found after completing the tutorial, t(8) = 7.02, p < 0.001. Clinician and patient ratings of user satisfaction were high for both the iPad teaching tools, and the text messaging. Ninety-five percent of teens said reviewing their text messages with their therapist was helpful, and all said they would use text messaging in treatment again. Ratings of the therapeutic alliance were higher in the CBT arm t(131) = 4.03, p = 0.001. A significant reduction in depression was found in both groups [t(34) = 8.453, p < 0.001 and t(29) = 6.67, p < 0.001 for CBT and TAU, respectively). Clinical ratings of improvement were greater on all outcome measures for the CBT arm; however, none reached statistical significance. Effect sizes (Cohen’s d) ranged from small (QIDS-A) to large (TASA).


Results support the feasibility of this technology-enhanced CBT intervention as a means of improving CBT treatment of adolescent depression and may help address the critical shortage of therapists trained on empirically based treatments.


Cognitive therapy; Internet; Training; Depressive disorder; Adolescent; Dissemination; Evidence based


The use of technology for the psychological treatment of mental disorders is on a rapid ascent. While the potential ways of using technology to enhance treatment have been discussed for decades [1], [2], the recent explosion in information technology and telecommunications, and the widespread use of mobile devices have resulted in a dramatic increase in the use of both mobile devices and the internet to enhance and facilitate access to treatment. Several review articles have been published summarizing the bourgeoning body of data being generated [3]–[7]. Results have generally been supportive of both efficacy and feasibility, though several issues have been identified, such as confidentiality, privacy, crisis management, technological competence, and ethical issues [3], [8]. As with all innovations, new practice guidelines have been developed to address the unique challenges presented [9]–[11].

Cognitive behavior therapy (CBT) is an empirically based treatment that is uniquely suited to enhancement by new technologies [5], [12]. It is highly structured, typically manualized, follows a sequential progression, emphasizes self-responsibility, self-monitoring and homework, and includes ongoing outcome measurements. A variety of technology-enhanced CBT applications across a range of mental disorders have been reported. These include computer-administered CBT self-treatment (stand alone, no therapist contact), computer-assisted CBT treatment (computer-administered with some clinician guidance or contact), mobile monitoring and communication, psychoeducation, remote live treatment via videoconference, and online therapist training [12]–[18].

The use of technology is particularly well suited for psychological interventions with youth and teens. Nine in ten teens in the USA (93 %) have access to a computer, 78 % have cell phones, and 74 % have mobile access to the internet via a cell phone, tablet or other device [19]. Text messaging has become the preferred mode of communication among teens, with two-thirds reporting they are more likely to use their cell phones to text their friends than to talk with them. Half of teens in the USA send 50 or more texts per day [20]. Mobile phone use by teens cuts across socio-demographic backgrounds, as more US families replace traditional land lines with mobile phones (e.g., 41 % of households have only wireless according to a 2013 survey by the National Center for Health Statistics; among poor households, the figure is 56 %) [21]. Teens in both the USA and abroad have both the technical expertise with these technologies, and a favorable attitude toward their use in mental health care [4], [22]. Three quarters of lifetime mental disorders begin in adolescence and young adulthood, making it a critical target age for prevention and intervention efforts [23]–[25].

Given the compatibility between CBT and new technologies, and the affinity for new technologies by youth, the integration of new technologies into CBT treatment of youth has been rapidly increasing [5], [7]. Applications have been developed for the treatment of a variety of disorders, including simple phobias, social anxiety disorder, generalized anxiety disorder, obsessive–compulsive disorder, encopresis, autism, eating disorders, depression, and substance abuse [26]–[39].

Mobile applications such as text messaging [i.e., short messaging services (SMS)] are particularly well suited for youth and can help clinicians implement CBT treatment more effectively through the use of homework reminders, real-time self-monitoring and between session communication and feedback [17]. Among mental health patients, text messaging is the most popular feature, and a higher percentage of mental health patients text compared to the general population [40], [41]. Self-monitoring in particular has been found to improve treatment outcomes, both by itself and when added to therapy [42], [43] and accounts for a significant portion of the variance in treatment outcomes [44]. Text messaging may help overcome non-compliance (a primary reason for lack of treatment efficacy) by enabling encouragement and support between sessions. Interacting with each adolescent on a daily basis to encourage compliance with homework assignments, evaluate progress, monitor side effects, etc., would be prohibitively expensive if clinicians were required to personally send and receive the messages themselves. Fortunately it is not necessary, given the demonstrated feasibility of automating those functions. There is a large body of literature on the efficacy of text messaging for improving heath behavior and treatment outcomes in other areas of health care (e.g., diabetes, asthma, hypertension, obesity), with positive outcomes in 93 % of the published studies [45]. Text messaging is also used in the treatment of psychiatric and substance use disorders in adults [46], [47]. Data on the use of SMS in the psychological treatment of youth and young adults are beginning to emerge [3], [48]–[52]. Teens have generally reacted favorably to use of SMS technology in treatment and prevention programs, with good compliance rates [22], [53].

In response to the National Institute of Mental Health’s call for research on the use of technology to facilitate the dissemination of evidence-based treatments [54], we developed a technology-enhanced intervention protocol to facilitate CBT treatment of adolescent depression. The program consists of three components, each using technology for a particular purpose: (1) online therapist training, (2) in-session use of tablets for teaching clients CBT concepts and skills, and (3) text messaging for between session homework reminders and self-monitoring. These three components help disseminate training to therapists, help therapists implement CBT with patients more effectively, and improve CBT treatment outcomes, respectively. The goal of this study was to evaluate the feasibility, user satisfaction, and effectiveness of this technology-enhanced approach for treating adolescent depression.



Eighteen licensed clinicians who work with depressed adolescents participated in the study. Clinicians were recruited through advertisements in professional journals and through direct mail (i.e., Psychology today listing of clinicians working with depressed adolescents). Clinicians came from 13 states and various disciplines, including social work (n = 7), clinical or counseling psychology (n = 9), educational psychology (n = 1) and behavioral mental health (n = 1). Fifteen had master’s degrees and three doctoral degrees. The mean age was 44.2 years (range 31–58 years, SD = 8.4), and 56 % (n = 10) were female. Thirteen were Caucasian, four African American, and one was multiracial. Fifteen (83 %) reported some prior exposure to CBT, primarily through group lectures (78 %). None were accredited or formally trained as CBT practitioners. Mean number of years working with adolescents was 12.2 (range 2–20 years, SD = 5.59).


Sixty-five adolescents, aged 12–17 (mean age = 15.4, SD = 1.52) with a DSM-5 mood disorder [major depressive disorder (n = 31), persistent depressive disorder (n = 20), both major and persistent depressive disorders (n = 3), other specified depressive disorder (n = 6), unspecified depressive disorder (n = 5)] and a minimum score of 11 on the quick inventory of depressive symptomatology–adolescent-patient report (QIDS-A-Pat) (mean = 14.5, SD = 3.28, range 10–22) [55] were recruited. Subjects were excluded if they had bipolar disorder, severe conduct disorder, substance dependence, pervasive developmental disorders, thought disorder, severe suicidal/homicidal ideation or behavior requiring inpatient treatment. Diagnoses were determined via clinical interview using a DSM-5 symptom checklist. Non-English speakers and adolescents without daily access to a cell phone were also excluded. Patients represented diverse races and ethnicities, including Caucasian (n = 27), African American (n = 24), American Indian (n = 3), Asian (n = 1), Biracial (n = 5) and other (n = 5). Fifteen percent (n = 10) were Hispanic and two-thirds (n = 43) were female.


Clinicians were randomly assigned to have all their subjects receive either the technology-enhanced CBT intervention arm (CBT), or treatment as usual (TAU). Each clinician recruited four adolescents from their clinical practice who were initiating treatment for depression. Three clinicians dropped out of the study before completing enrollment and were replaced. Clinicians in the CBT arm completed a pre-test on CBT knowledge and then took the online tutorial on CBT treatment for adolescent depression. After completing the tutorial, clinicians took a post-test, then received an iPad containing a link to the online CBT interactive teaching materials and text-messaging system. A brief (1 h) orientation session was held with each clinician to review how to use the iPad for teaching CBT concepts to patients and for setting up text messages. Each patient was treated for 12 weeks, using the skills learned in the tutorial, and the in-session teaching tools. Individualized text messages were integrated into treatment. Clinicians in the TAU arm also recruited patients initiating treatment for depression from their clinical practice, and treated them for 12 weeks using usual care. After completing the study, clinicians in the TAU arm were offered access to the CBT training and intervention tools. Since both patients and therapists were considered research subjects, each signed informed consent statements approved by the Allendale Institutional Review Board. Patient flow and study completion rates by treatment arm are shown in Table 1.

Table 1. Patient recruitment and study completion by treatment arm

Description of the technology-enhanced CBT intervention

Online therapist training tutorial

The online training tutorial was developed as a way to address the critical shortage of clinicians trained in CBT, due in large part to a lack of training available [56], [57]. Putting the training online makes the training more accessible, cost-effective, and obviates the need for travel to one of the limited number of centers that offer CBT training. Trainees are not bound by time limitations, and can work at their own pace and schedule (a recent study found time and cost the strongest predictor of unwillingness to obtain training on empirically based treatments) [57]. The quality of the training is also enhanced using principles of instructional design to deliver multi-modal, interactive learning, both of which have been found to increase knowledge retention [58]. Standardizing the training helps insure the quality of the instruction, which is important as several studies have found that much of the CBT that is being delivered is not being administered properly [59], [60]. The tutorial was modeled after the cognitive behavior therapy manual used in the NIMH funded treatment of adolescents with depression study [61] and consisted of nine modules (overview, theoretical principals of CBT, explaining the nature of depression to Clients and the therapeutic relationship, explaining treatment rationale to clients, mood monitoring, goal setting, behavioral activation, problem solving, and cognitive restructuring). Trainees worked at their own pace, and could email us with any questions. The tutorial took about 5.5 h to complete (see for examples of tutorial content). Animations, graphical illustrations, interactive exercises, and video illustrations of an expert clinician (Dr. Kennard) applying the techniques were used as teaching tools. Session agendas and a treatment protocol were provided to assist clinicians in treatment implementation.

Online interactive patient educational materials

The second component consisted of online instructional materials to help clinicians explain CBT concepts to patients. Patient understanding of treatment rationale and treatment concepts is a critical part of effective treatment, as the more sense a treatment makes to a client, the more likely they are to comply with it [62], [63]. In CBT, there is a collaborative relationship between the therapist and client, with the client seen as both capable of, and responsible for, change. To empower clients with the skills necessary for change, it is critical that both (the client and the depressed adolescents parents) have an basic understanding of the nature of depression, the CBT treatment rationale, and, CBT concepts and skills, such as mood monitoring, identifying and challenging automatic thoughts, and activity scheduling. Therapists typically teach this using a combination of verbal instruction and paper and pencil forms. We created a series of online, interactive education materials to (1) help novice CBT therapists structure sessions, (2) insure that the concepts are covered thoroughly and accurately, (3) engage and involve the youth and personalize the material, and (4) create personalized goals and homework assignments. For example, in teaching clients about automatic thoughts, the therapist first displays a hypothetical scenario on the tablet PC (in our case, an iPad), to teach the relationship between thoughts, emotions, and behaviors. The teen then generates two or three possible thoughts they might have in that situation and the different feelings associated with those thoughts. Once the concept is understood, i.e., that different thoughts lead to different feelings, the therapist goes through the process again using a situation from the client’s real life. Finally, homework is collaboratively set up, e.g., to monitor one’s mood and thinking at specific intervals during the day. In another example, the client may be learning problem-solving skills. In this case, the tablet plays a pre-recorded scenario of a typical teen problem, after which the client goes through the problem-solving process using the tablet. Finally, the process is repeated with a real-life problem the client has, followed by setting up problem-solving practice between sessions.

Interactive text messaging

The third part of the intervention consists of text messages the client receives between sessions to remind them of their homework goals, and to record results of homework practice (see for an illustration). These are set up as the final step in the patient education process previously described. Typically, the client would receive two texts each day: a reminder text call in the morning and a text later in the day to record results. For example, if the goal was to increase pleasant activities, the morning text would say “remember to do at least one pleasant activity today’. Do you remember the activity you were going to do?” If they said no, they would receive a text back reminding them what the activity was. In the evening, they would receive a text asking them if they did the pleasant activity, get a reinforcing message if they did, and a text back asking them to describe what they did and how it affected their mood. If they did not do the activity, they would receive a text back saying “Making yourself do something when you do not feel like it is hard. Sometimes just doing something nice helps you feel better” followed by “Tell me what kept you from doing the activity today. We can talk about it next session.” A report of all texts sent and received is sent to the therapist for review with the client at their next session, as a way to process together how the homework went and to troubleshoot problems and reinforce learning. Timing and frequency of texts are determined collaboratively by the therapist and teen. For example, the teen may say that 9 pm is the best time to receive evening texts, as that is when he has some down time. Or a therapist may want to increase or decrease the frequency of mood monitoring, depending on the clinical status of the teen. Examples of texts are shown in Table 2.

Table 2. Examples of text messages and response options by therapeutic module

Outcome measures

Online tutorial

Effectiveness of the online tutorial in improving clinician’s knowledge of CBT concepts was evaluated using a 49-item multiple choice pre- and post-test covering the tutorial content. The test had good internal consistency reliability (coefficient alpha = 0.821). Technical feasibility of the tutorial was evaluated with the system usability scale (SUS) [64], [65]. The SUS is a reliable, well-validated 10-item scale designed to evaluate the usability and user satisfaction with web-based applications and other technologies. The SUS has good internal consistency reliability (coefficient alpha: r = 0.86 in our sample) in assessing usability across diverse types of user interfaces (e.g., web, interactive voice response, cell phone, etc.) It provides quantitative feedback on a 0–100 scale. In a cross-validation study of the SUS using an anchored adjective scale, systems with “Good” usability had mean score of 71.4. [66] This criterion was used for successful system design in the current study. In addition to the SUS, ratings were also obtained on whether the stated learning objectives of the tutorial were met, and a set of questions evaluating satisfaction with the clinical content of the tutorial.

Online teaching materials and text messaging

Technical feasibility with the online teaching materials and text-messaging system was evaluated with the SUS. Open-ended feedback was also solicited on user satisfaction with the system from both clinicians and patients.

Clinical outcomes

Clinical outcome measures were obtained at the end of 6 and 12 weeks of treatment. The primary clinical outcome measure was pre-to-post treatment changes in patient ratings of depression on the quick inventory of depressive symptomatology–adolescent version (QIDS-A-Pat) [55]. Secondary outcomes included clinician global ratings of improvement (CGI-I) and severity (CGI-S) [67], and clinician and patient ratings on the therapeutic alliance scale for adolescents (TASA) [68].

Statistical analyses

Categorical and ordinal variables, such as gender and percent responders were tested by Chi-square tests of distributional independence. Interval and ratio level measurements, such as age, and depression severity scores were compared with two-tailed, between group t tests for equivalence of means. When the sample size in each of two groups is 32, a 0.05 level Chi-square test will have power of 0.7–0.97 to distinguish between the groups when the proportions in the two categories are characterized by effect sizes of 0.1 to 0.25. Samples of 32 per group have statistical power of 0.50–0.88 to detect moderate to large mean differences (effect sizes of 0.5–0.8) in two group t tests using two-sided alphas of 0.05. The sample size estimate was based on the QIDS-A-Pat.


Clinicians and patients

There were no significant differences between clinicians randomized to CBT and TAU in terms of age [t(16) = 0.42, p = 0.678), gender (X 2 (1) = 1.90, p = 0.168], or years’ experience [t(16) = 0.10, p = 916]. There were also no significant differences between patients in the CBT and TAU arms on age [t(63) = 0.076, p = 0.940], gender (X 2 (1) = 0.94, p = 0.432), or baseline depression severity (QIDS-A-Pat) [t(63) = 0.27, p = 0.787).

Online tutorial

Increase in didactic knowledge

We examined changes in scores on the 49-item pre-and post-tests of knowledge of CBT concepts covered in the tutorial. A significant increase was found in the number of correct items from the pre-test (24.4, SD = 4.42) to the post-test (33.9, SD = 5.11), t(8) = 7.02, p < 0.001.

Learning objectives

Twenty-three learning objectives were identified a priori as learning goals for the online tutorial (Table 3). After completing the tutorial, 97 % of the learning objectives were rated as met. The mean rating of how much they learned as a result of taking the tutorial was 4.4 (rated on a 1–5 scale (1 = very little and 5 = a great deal).

Table 3. Learning objectives: CBT tutorial

User satisfaction: technical aspects

The means score on the SUS for the online tutorial was 78.4 (SD = 20.44) (Table 4). This corresponds to a score of good user satisfaction on the SUS. Mean global rating of user-friendliness (rated scale range from 1 (worst imaginable) to 7 (best imaginable)) was 5.6, which is halfway between “good” and “excellent”.

Table 4. System usability scale scores for the online tutorial and teaching/text system

User satisfaction: clinical content

Descriptive statistics were obtained on user satisfaction with the online tutorial (Table 5). All that subjects agreed or strongly agreed that the material was presented in an interesting manner, was clearly presented and easy to understand, and was useful and relevant to treating adolescent depression. All would recommend the online tutorial to others.

Table 5. Mean satisfaction ratings on tutorial scale clinical content

Online teaching materials and text messaging

User satisfaction: clinicians

The means score on the SUS for the online CBT teaching materials and text-messaging system was 84.4 (SD = 13.80). This corresponds to a score between good and excellent. Ratings on individual SUS items are presented in Table 6. The mean rating for all items was between “agree” and “strongly agree”. Clinicians found the system ‘user friendly’ in terms of understanding how to utilize the system for teaching CBT skills, setting up text messages, and receiving text reports.

Table 6. Mean ratings on system usability scale items: online teaching materials and text messaging

User satisfaction: patients

Feedback was also solicited from adolescents on how helpful the teaching and text message system was. Eighty-five percent of patients felt the teaching materials presented on the iPad during sessions were helpful in learning new skills, 90 % felt the text messages between sessions were helpful, and 95 % said reviewing their text message responses on their homework and mood at the next session with their therapist were helpful. All patients said they would be willing to use text messaging again to communicate their feelings to their clinician between sessions.

Clinical outcomes

Both treatment groups significantly improved with treatment, with mean improvements on the QIDS-A of 6.09 (SD = 4.26) and 5.73 (SD = 4.71) for the CBT and TAU groups [t(34) = 8.453, p < 0.001 and t(29) = 6.67, p < 0.001 respectively]. Clinical outcome measures comparing the CBT and TAU groups are presented in Table 7. Therapist ratings of the therapeutic alliance (TASA) were significantly higher in the CBT intervention arm than in the TAU arm, t(131) = 4.03, p = 0.001. Measures of symptomatic improvement were greater on all other outcome measures for the CBT arm; however, none reached statistical significance. Effect sizes (Cohen’s d) [69] ranged from small (QIDS-A) to large (TASA).

Table 7. Clinical outcome measures: CBT vs. TAU

Text messaging

A total of 9,613 text messages requiring a response were sent. Of these, 3658 (38.1 %) were responded to. The correlation between improvement on the QIDS-A and percent of texts responded to was not significant (r = 0.165, p = 0.343).

Dropout rate

Seven subjects dropped out prior to week 12 in the TAU arm, compared to 4 subjects in the CBT arm.


Results of this study provide support for the feasibility of this technology-enhanced CBT Intervention as a means of improving CBT treatment of adolescent depression. User satisfaction, a critical component of feasibility, was high for both adolescents and therapists on all components. The program was successful in increasing therapists’ knowledge of CBT concepts and principles. Teens found the online teaching tools useful for learning CBT concepts and skills. They also found the text messaging between sessions helpful, particularly for reviewing work done between sessions with their therapist. All teens indicated they would be willing to use the system again. Rather than put a barrier between the teen and the therapist, the technology improved the therapeutic bond, a critical factor in treatment outcomes. Improving the therapeutic relationship may help to keep teens in treatment, a critical factor for successful outcomes.

From a system delivery perspective, the use of this technology-enhanced intervention is designed to augment rather than replace existing one to one clinician care. As such it is not a low intensity intervention (i.e., an intervention designed to limit therapist time) [70]—and keeps the same number and lengths of session as usual. This approach contrasts recent “stepped-care” models of treatment, which start with the least restrictive treatment with minimal therapist support. Future research can examine the use of this (and similar) technologies within a stepped-care model. This could include examining factors such as length of treatment, use of online self-help combined with therapist and non-therapist support, both with and without text-messaging augmentation.

Effect sizes on the clinical outcomes in the current study were small to medium. According to Cohen, a small effect size is one in which there is a real effect, but can only be seen through careful study. The current study used community clinicians (vs. academic research centers) to see how well the intervention works in a sample of community therapists that not had formal training in CBT. Taken in this light, small effects are encouraging. As the training continues to be evaluated and refined, the impact of additional follow-up training, or live applied training may further improve results. Prior studies with remote CBT training found the addition of live remote observation through a videoconference of trainees conducting CBT, with immediate feedback in real time significantly improved clinical skills [16]. The addition of this applied training component may have improved clinical outcomes. A follow-up study is underway to examine the impact of the addition of live training on post-training treatment outcomes with community patients.

The current program utilized technology to integrate three components as part of a single intervention: therapist training, client education, and treatment implementation and outcomes. As the use of technology continues to be adopted and integrated into clinical treatment, more empirical evidence will help shed light on which components are useful and under what circumstances. At a minimum, the current intervention helps address the critical shortage of training on empirically based treatments. The potential ways in which technology such as text messaging and use of interactive educational tools can enhance treatment are at the start of a new era of clinical research. New possibilities are rapidly emerging, and to some extent, are outpacing our ability to empirically evaluate these new innovations [71]. Some recent data suggest that the explosion of mental health apps has resulted apps of poor quality, or apps that do not reflect clinical practice guidelines or evidence-based practices [72], [73]. However, while presenting many challenges, they also present exciting opportunities. Continued research should continue to generate empirical data to help guide both clinical practice as well as future research in this area.


In the current study, a technology-enhanced CBT Intervention was effective in improving symptoms of depression in adolescents. User satisfaction with the technology was high for both therapists and patients. The therapeutic alliance was stronger in the cohort receiving the technology-enhanced intervention. Effect sizes comparing clinical outcomes between CBT and TAU were small.

Authors’ contributions

JCM and KAK were responsible for developing study design, instrument development, data analysis, and manuscript development. BK provided oversight of clinical content of tutorial, provided input into study design, and manuscript development. All authors read and approved the final manuscript.


The authors would like to acknowledge the contribution of Tracy Reyes for project management, general support, critical review, and subject recruitment, Alison Deep for managing and developing the technology utilized in text messaging and online teaching tools, Rich DeVuono for filming vignettes and photography, and Hal Stokes and Illumnia for tutorial development.

Study funding

This study was supported in part by a Grant from the National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, under Small Business Innovation Research (SBIR) Grant Number R44MH086152.

Competing interests

KAK, JCM, and BK have a proprietary interest in the computer-assisted technology that is under study in the manuscript, and will receive royalties on sales of the program.


  1. Greist JH, Klein MH, Van Cura LJ: A computer interview for psychiatric patient target symptoms.

    Arch Gen Psychiatry 1973, 29(2):247-253. PubMed Abstract | Publisher Full Text OpenURL

  2. Greist JH: Clinical computing: computers and psychiatry.

    Psychiatri Serv 1995, 46(10):989-991. Publisher Full Text OpenURL

  3. Seko Y, et al.: Youth mental health interventions via mobile Phones: a scoping review.

    Cyberpsychol Behav Soc Netw. 2014, 17:591-602. PubMed Abstract | Publisher Full Text OpenURL

  4. Boydell KM, et al.: Using technology to deliver mental health services to children and youth: a scoping review.

    J Can Acad Child Adolesc Psychiatry 2014, 23(2):87-99. PubMed Abstract | Publisher Full Text OpenURL

  5. Berry RR, Lai B: The emerging role of technology in cognitive-behavioral therapy for anxious youth: a review.

    J Rationale-Emotive Cogn Behav Ther 2014, 32:57-66. Publisher Full Text OpenURL

  6. Boschen MJ: Mobile telephones and psychotherapy: II a review of empirical research.

    Behav Therapist 2009, 32:175-181. OpenURL

  7. Slone NC, Reese RJ, McClellan MJ: Telepsychology outcome research with children and adolescents: a review of the literature.

    Psychol Serv 2012, 9(3):272-292. PubMed Abstract | Publisher Full Text OpenURL

  8. Luxton DD, et al.: mHealth for mental health: integrating smartpohone technology in behavioral healthcare.

    Prof Psychol Res Pract 2011, 42(6):505-512. Publisher Full Text OpenURL

  9. Doarn CR, Merrell RC: Standards and guidelines for telemedicine—an evolution.

    Telemed J E Health 2014, 20(3):187-188. PubMed Abstract | Publisher Full Text OpenURL

  10. Turvey C, et al.: ATA practice guidelines for video-based online mental health services.

    Telemed J E Health 2013, 19(9):722-730. PubMed Abstract | Publisher Full Text OpenURL

  11. Joint Task Force for the Development of Telepsychology, Guidelines for Psychologists: Guidelines for the practice of telepsychology

    Am Psychol 2013, 68(9):791-800. Publisher Full Text OpenURL

  12. Boschen MJ, Casy LM: The use of mobile telephones as adjuncts to cognitive behavioral psychotherapy.

    Prof Psychol Res Pract 2008, 39(5):546-552. Publisher Full Text OpenURL

  13. Donker T, et al.: Smartphones for smarter delivery of mental health programs: a systematic review.

    J Med Internet Res 2013, 15(11):e247. PubMed Abstract | Publisher Full Text OpenURL

  14. Kaltenthaler E, et al.: Computerised cognitive-behavioural therapy for depression: systematic review.

    Br J Psychiatry 2008, 193(3):181-184. PubMed Abstract | Publisher Full Text OpenURL

  15. Spek V, et al.: Internet-based cognitive behaviour therapy for symptoms of depression and anxiety: a meta-analysis.

    Psychol Med 2007, 37(3):319-328. PubMed Abstract | Publisher Full Text OpenURL

  16. Kobak KA, et al.: Web-based therapist training on cognitive behavior therapy for anxiety disorders: a pilot study.

    Psychotherapy (Chic) 2013, 50(2):235-247. Publisher Full Text OpenURL

  17. Aguilera A, Muench F: There’s an app for that: the information technology applications for cognitive behavioral practitioners.

    Behav Ther 2012, 35(4):65-73. OpenURL

  18. Roy-Byrne P, et al.: Delivery of evidence-based treatment for multiple anxiety disorders in primary care: a randomized controlled trial.

    JAMA 2010, 303(19):1921-1928. PubMed Abstract | Publisher Full Text OpenURL

  19. Madden M, et al. Teens and technology 2013. In: Pew Research Center’s Internet & American Life Project. Washington, DC: Pew Research Center; 2013. Accessed 31 Oct 2015.
  20. Lenhart A, et al.: Teens and mobile phones, P.I.A.L. project, editor. Pew Research Center, Washington; 2010. OpenURL
  21. Blumberg SJ. Wireless substitution: early release of estimates from the National health interview survey, July–December 2013. Washington, DC: National Center for Health Statistics, U.S. Department of Health and Human Services; 2014. Accessed 30 Oct 2015.
  22. Whittaker R, et al.: MEMO–a mobile phone depression prevention intervention for adolescents: development process and postprogram findings on acceptability from a randomized controlled trial.

    J Med Internet Res 2012, 14(1):e13. PubMed Abstract | Publisher Full Text OpenURL

  23. Kessler RC, et al.: Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey replication.

    Arch Gen Psychiatry 2005, 62(6):593-602. PubMed Abstract | Publisher Full Text OpenURL

  24. Kessler RC, et al.: Lifetime prevalence and age-of-onset distributions of mental disorders in the World Health Organization’s World Mental Health Survey Initiative.

    World Psychiatry 2007, 6(3):168-176. PubMed Abstract | Publisher Full Text OpenURL

  25. Kessler RC, et al.: Age of onset of mental disorders: a review of recent literature.

    Curr Opin Psychiatry 2007, 20(4):359-364. PubMed Abstract | Publisher Full Text OpenURL

  26. Nelson EL, Barnard M, Cain S: Treating childhood depression over videoconferencing.

    Telemed J E Health 2003, 9(1):49-55. PubMed Abstract | Publisher Full Text OpenURL

  27. Dewis LM, et al.: Computer-aided vicarious exposure versus live graded exposure for spider phobia in children.

    J Behav Ther Exp Psychiatry 2001, 32(1):17-27. PubMed Abstract | Publisher Full Text OpenURL

  28. Gladstone T, et al.: Understanding adolescent response to a technology-based depression prevention program.

    J Clin Child Adolesc Psychol 2014, 43(1):102-114. PubMed Abstract | Publisher Full Text OpenURL

  29. Merry SN, et al.: The effectiveness of SPARX, a computerised self help intervention for adolescents seeking help for depression: randomised controlled non-inferiority trial.

    BMJ 2012, 344:e2598. PubMed Abstract | Publisher Full Text OpenURL

  30. Sarver NW, Beidel DC, Spitalnick JS: The feasibility and acceptability of virtual environments in the treatment of childhood social anxiety disorder.

    J Clin Child Adolesc Psychol 2014, 43(1):63-73. PubMed Abstract | Publisher Full Text OpenURL

  31. Ritterband LM, et al.: An Internet intervention as adjunctive therapy for pediatric encopresis.

    J Consult Clin Psychol 2003, 71(5):910-917. PubMed Abstract | Publisher Full Text OpenURL

  32. Silver M, Oakes P: Evaluation of a new computer intervention to teach people with autism or Asperger syndrome to recognize and predict emotions in others.

    Autism 2001, 5(3):299-316. PubMed Abstract | Publisher Full Text OpenURL

  33. Wuthrich VM, et al.: A randomized controlled trial of the Cool Teens CD-ROM computerized program for adolescent anxiety.

    J Am Acad Child Adolesc Psychiatry 2012, 51(3):261-270. PubMed Abstract | Publisher Full Text OpenURL

  34. Comer JS, et al.: A pilot feasibility evaluation of the CALM Program for anxiety disorders in early childhood.

    J Anxiety Disord 2012, 26(1):40-49. PubMed Abstract | Publisher Full Text OpenURL

  35. Comer JS, et al.: Internet-delivered, family-based treatment for early-onset OCD: a preliminary case series.

    J Clin Child Adolesc Psychol 2014, 43(1):74-87. PubMed Abstract | Publisher Full Text OpenURL

  36. Pretorius N, et al.: Cognitive-behavioural therapy for adolescents with bulimic symptomatology: the acceptability and effectiveness of internet-based delivery.

    Behav Res Ther 2009, 47(9):729-736. PubMed Abstract | Publisher Full Text OpenURL

  37. Gulec H, et al. A randomized controlled trial of an internet-based posttreatment care for patients with eating disorders. Telemed J E Health. 2014.
  38. Hoek W, et al.: Effects of Internet-based guided self-help problem-solving therapy for adolescents with depression and anxiety: a randomized controlled trial.

    PLoS One 2012, 7(8):e43485. PubMed Abstract | Publisher Full Text OpenURL

  39. Schwinn TM, Schinke SP, Di Noia J: Preventing drug abuse among adolescent girls: outcome data from an internet-based intervention.

    Prev Sci 2010, 11(1):24-32. PubMed Abstract | Publisher Full Text OpenURL

  40. Campbell B, et al.: Cell phone ownership and use among mental health outpatients.

    Pers Ubiquit Comput 2015, 19:367-378. Publisher Full Text OpenURL

  41. Khazaal Y, et al.: Internet use by patients with psychiatric disorders in search for general and medical informations.

    Psychiatr Q 2008, 79(4):301-309. PubMed Abstract | Publisher Full Text OpenURL

  42. Kazantzis N: Power to detect homework effects in psychotherapy outcome research.

    J Consult Clin Psychol 2000, 68(1):166-170. PubMed Abstract | Publisher Full Text OpenURL

  43. Kazdin AE: Reactive self-monitoring: the effects of response desirability, goal setting, and feedback.

    J Consult Clin Psychol 1974, 42(5):704-716. PubMed Abstract | Publisher Full Text OpenURL

  44. Michie S, et al.: Effective techniques in healthy eating and physical activity interventions: a meta-regression.

    Health Psychol 2009, 28(6):690-701. PubMed Abstract | Publisher Full Text OpenURL

  45. Fjeldsoe BS, Marshall AL, Miller YD: Behavior change interventions delivered by mobile telephone short-message service.

    Am J Prev Med 2009, 36(2):165-173. PubMed Abstract | Publisher Full Text OpenURL

  46. Agyapong VI, et al.: Supportive text messaging for depression and comorbid alcohol use disorder: single-blind randomised trial.

    J Affect Disord 2012, 141(2–3):168-176. PubMed Abstract | Publisher Full Text OpenURL

  47. Free C, et al.: Smoking cessation support delivered via mobile phone text messaging (txt2stop): a single-blind, randomised trial.

    Lancet 2011, 378(9785):49-55. PubMed Abstract | Publisher Full Text OpenURL

  48. Matthews M, et al.: Mobile phone mood charting for adolescents.

    Br J Guid Couns 2008, 36(2):113-129. Publisher Full Text OpenURL

  49. Suffoletto B, et al. A text message alcohol intervention for young adult emergency department patients: a randomized clinical trial. Ann Emerg Med. 2014.
  50. Bauer S, et al.: Technology-enhanced maintenance of treatment gains in eating disorders: efficacy of an intervention delivered via text messaging.

    J Consult Clin Psychol 2012, 80(4):700-706. PubMed Abstract | Publisher Full Text OpenURL

  51. Furber GV, et al.: How adolescents use SMS (short message service) to micro-coordinate contact with youth mental health outreach services.

    J Adolesc Health 2011, 48(1):113-115. PubMed Abstract | Publisher Full Text OpenURL

  52. Branson CE, Clemmey P, Mukherjee P: Text message reminders to improve outpatient therapy attendance among adolescents: a pilot study.

    Psychol Serv 2013, 10(3):298-303. PubMed Abstract | Publisher Full Text OpenURL

  53. Kauer SD, et al.: Investigating the utility of mobile phones for collecting data about adolescent alcohol use and related mood, stress and coping behaviours: lessons and recommendations.

    Drug Alcohol Rev 2009, 28(1):25-30. PubMed Abstract | Publisher Full Text OpenURL

  54. U.S. Department of Health and Human Services. PHS 2011-2, Omnibus Solicitation of the National Institutes of Health, Centers for Disease Control and Prevention, Food and Drug Aadministration, and Administration for Children and Families for Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) Grant applications. Washington, DC. 2011. Accessed 30 Oct 2015.
  55. Moore HK, et al.: A pilot study of an electronic, adolescent version of the quick inventory of depressive symptomatology.

    J Clin Psychiatry 2007, 68(9):1436-1440. PubMed Abstract | Publisher Full Text OpenURL

  56. Shafran R, et al.: Mind the gap: improving the dissemination of CBT.

    Behav Res Ther 2009, 47(11):902-909. PubMed Abstract | Publisher Full Text OpenURL

  57. Stewart RE, Chambless DL, Baron J: Theoretical and practical barriers to practitioners’ willingness to seek training in empirically supported treatments.

    J Clin Psychol 2012, 68(1):8-23. PubMed Abstract | Publisher Full Text OpenURL

  58. Gardner H: Multiple intelligences: the theory in practice. Basic Books, New York; 1993. OpenURL
  59. Kessler RC, Merikangas KR, Wang PS: Prevalence, comorbidity, and service utilization for mood disorders in the United States at the beginning of the twenty-first century.

    Annu Rev Clin Psychol 2007, 3:137-158. PubMed Abstract | Publisher Full Text OpenURL

  60. Stobie B, et al.: Contents may vary: a pilot study of treatment histories of OCD patients.

    Behav Cogni Psychother 2007, 35:273-282. Publisher Full Text OpenURL

  61. Curry JF, et al.: Treatment for Adolescents with Depression Study (TADS) cognitive behavior therapy manual. Duke University Medical Center, Durham; 2005. OpenURL
  62. Street RL Jr, et al.: How does communication heal? Pathways linking clinician-patient communication to health outcomes.

    Patient Educ Couns 2009, 74(3):295-301. PubMed Abstract | Publisher Full Text OpenURL

  63. Raue PJ, et al.: Patients’ depression treatment preferences and initiation, adherence, and outcome: a randomized primary care study.

    Psychiatr Serv 2009, 60(3):337-343. PubMed Abstract | Publisher Full Text OpenURL

  64. Brooke J, et al.: SUS: a ‘quick and dirty’ usability scale. In Usability evaluation in industry. Edited by Jordan PW. Taylor and Francis, London; 1996:189-194. OpenURL
  65. Bangor A, Kortum P, Miller J: The System Usability Scale (SUS): an Empirical evaluation.

    Int J Human-Computer Interact 2008, 24(6):574-592. Publisher Full Text OpenURL

  66. Bangor A, Kortum P, Miller J: Determining what individual SUS scores mean: adding an adjective rating scale.

    J Usability Stud 2009, 4(3):114-123. OpenURL

  67. Guy W. ECDEU assessment manual for psychopharmacology, revised. Rockville MD: National Institute of Mental Health, US Department of Health, Education, and Welfare publication ADM; 1976. p. 76–338.
  68. Shirk SR, et al.: Alliance and outcome in cognitive-behavioral therapy for adolescent depression.

    J Clin Child Adolesc Psychol 2008, 37(3):631-639. PubMed Abstract | Publisher Full Text OpenURL

  69. Statistical power analysis for the behavioral sciences, 2nd. Erlbaum, Hillside; 1988. OpenURL
  70. Bennett-Levy J, et al.: The Oxford guide to low intensity CBT interventions. Oxford University Press, Oxford; 2010. OpenURL
  71. Jones DJ: Future directions in the design, development, and investigation of technology as a service delivery vehicle.

    J Clin Child Adolesc Psychol 2014, 43(1):128-142. PubMed Abstract | Publisher Full Text OpenURL

  72. Abroms LC, et al.: A content analysis of popular smartphone apps for smoking cessation.

    Am J Prev Med 2013, 45(6):732-736. PubMed Abstract | Publisher Full Text OpenURL

  73. Van Singer M, Chatton A, Khazaal Y: Quality of Smartphone Apps Related to Panic Disorder.

    Front Psychiatry 2015, 6:96. PubMed Abstract | Publisher Full Text OpenURL

Prevalence of chronic kidney disease among the high risk population in South-Western Ghana; a cross sectional study

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Prevalence of chronic kidney disease among the high risk population in South-Western Ghana; a cross sectional study

Richard KD Ephraim1*, Sylvester Biekpe1, Samuel A. Sakyi23, Prince Adoba1, Hope Agbodjakey1 and Enoch O. Antoh2

Author Affiliations

1 Department of Medical Laboratory Technology, School of Allied Health Sciences, University of Cape Coast, Cape Coast, Ghana

2 Department of Molecular Medicine, School of Medical Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

3 Noguchi Memorial Institute for Medical Research, Legon, Ghana

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Canadian Journal of Kidney Health and Disease 2015, 2:40  doi:10.1186/s40697-015-0076-3

The electronic version of this article is the complete one and can be found online at:

Received: 29 April 2014
Accepted: 28 August 2015
Published: 3 November 2015

© 2015 Ephraim et al.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.



Chronic Kidney Disease (CKD) is a major global health problem. CKD is one of the most common complications of diabetes mellitus and hypertension and carries a risk of cardiovascular morbidity and mortality and progression to end-stage kidney disease.


This study sought to use the 2012 Kidney Disease Improving Global Outcomes (KDIGO) definitions to establish the prevalence and risk factors for CKD among a high risk population in the Sekondi-Takoradi metropolis.


Cross sectional study.


Effia-Nkwanta regional and the Takoradi Government hospitals in South Western Ghana.


Two hundred eight consecutive adults with diabetes, hypertension or both.


Serum creatinine and urine albumin-creatinine ratio respectively. The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) was used to estimate glomerular filtration rate (GFR).


CKD was classified according to KDIGO.


The prevalence of CKD was 30 %: 27 % in patients with diabetes, 22 % in patients with hypertension only and 74 % in patients with both diabetes and hypertension. GFR category G3a CKD was most prevalent stage (9 %). Albuminuria was highest among people with diabetes (39 %).


A convenience sample of patients attending clinics.


CKD was prevalent in these high-risk patients.



L’insuffisance rénale chronique (IRC) est un problème majeur de santé globale. Elle se révèle l’une des plus fréquentes complications du diabète sucré et de l’hypertension. De plus, l’IRC pose un risque accru pour les patients de souffrir, voire de mourir de cardiopathie, ou alors de voir leur état progresser vers l’insuffisance rénale terminale.

Objectifs de l’étude

L’étude a cherché à établir la prévalence et les facteurs de risque de l’IRC dans la population prédisposée de la métropole de Sekondi-Takoradi (Ghana) en utilisant les définitions proposées par « Kidney Disease Improving Global Outcomes » (KDIGO) en 2012.

Type d’étude

Il s’agit d’une étude transversale.

Contexte de l’étude

L’étude a été effectuée sur des patients de l’hôpital régional Effia-Nkwanta et de l’hôpital gouvernemental de Takoradi, dans le sud-ouest du Ghana.


L’étude était constituée d’une cohorte de 208 adultes atteints de diabète, d’hypertension ou d’une comorbidité.


Le rapport albumine-créatinine dans l’urine ainsi que le taux de créatinine sérique ont été mesurés, puis le débit de filtration glomérulaire (GFR) a été déterminé à l’aide de l’équation du « Chronic Kidney Disease Epidemiology Collaboration » (CKD-EPI).


L’IRC a été déterminée selon les critères de KDIGO.


À la suite de cette étude, la prévalence d’IRC a été établie à 30 % parmi les patients de la cohorte. Elle s’établissait à 27 % chez les patients atteints de diabète seulement, 22 % chez les patients atteints d’hypertension seulement et de 74 % chez les patients présentant à la fois du diabète et de l’hypertension. Le stade d’IRC (9 %) le plus prévalent était de catégorie G3a. La prévalence d’albuminurie était plus élevée chez les patients diabétiques (39 %).

Limites de l’étude

Il s’agit d’un échantillon de commodité formé de patients fréquentant les deux cliniques mentionnées plus haut.


La prévalence d’insuffisance rénale chronique était plus élevée chez ce groupe de patients considérés à haut risque.


Chronic Kidney Disease (CKD) is defined as abnormalities of kidney structure or function, present for more than 3 months, with implications for health [1], [2]. It is characterized by either decreased glomerular filtration rate (GFR) or albuminuria, or both, and carries a risk of cardiovascular morbidity and mortality and progression to end-stage renal disease (ESRD) [3]. Chronic kidney disease is thought to be prevalent in sub-Saharan Africa and to be a major public health problem [4]. Resources for recognition and management aiming at reduction in progression are limited, and resources for the treatment of ESRD severely limited [4].

Chronic kidney disease (CKD) is one of the most common complications of diabetes mellitus [5] and hypertension [5]. Screening for CKD is not routinely performed in many diabetic clinics in sub-Saharan Africa because of limited human resource, diagnostic facilities and the cost of the tests [5]–[7].

Several studies within sub-Saharan Africa have examined the prevalence of CKD in people at high risk, including those with diabetes and hypertension. Janmohamed et al., [7] recorded 84 % prevalence in adult outpatients with diabetes in Tanzania, and Osafo et al. [8] showed a CKD prevalence of 47 % among Ghanaian patients, mainly from the Greater Accra region, with hypertension. In addition, Sumaili et al., [9] recorded 44 % prevalence in patients with hypertension, 39 % in those with diabetes; 16 % in people with obesity and 12 % in those who had human immunodeficiency virus (HIV) or acquired immunodeficiency syndrome (AIDS). We used the 2012 guidelines of the kidney disease improving global outcomes (KDIGO) to classify CKD among patients with diabetes, hypertension and both and also identified the associated risk factors for CKD in the Sekondi-Takoradi metropolis in south western Ghana.


Study design and study site

A cross-sectional study was conducted at the outpatient diabetes and hypertension clinics of the Effia-Nkwanta Regional hospital (ERH) and the Takoradi Government Hospital (TGH) in the Sekondi-Takoradi metropolis between December 2012 and May 2013. These serve as the major healthcare facilities in the metropolis providing primary, secondary and tertiary healthcare services for a population of 445,000. The healthcare system is accessible to those who contribute or pay the minimum of GH 20.0 yearly premium, equivalent to about three times the daily minimum wage of GH 6.0; about 66 % of the population is covered. In Ghana, patients with diabetes or hypertension receive specialized care in teaching, regional or municipal hospitals since they are the only facilities with the capacity to diagnose and manage this condition. Sekondi-Takoradi is the administrative capital of the Western Region. It has a land area of 385 km 2 and is located in the South-Western part of Ghana and about 242 km west of Accra, the capital city of Ghana.

Inclusion and exclusion criteria

We enrolled eligible adult (>18 years) outpatients receiving medical care at the diabetes and hypertension clinics of the hospitals during the study period. Patients diagnosed with high blood pressure or on anti-hypertensive drugs, diabetes or both hypertension and diabetes were included in this study. We excluded patients with other kidney diseases (such as glomerulonephritis, vasculitis, kidney infection, connective tissue disease or adult polycystic kidney disease), those undergoing peritoneal or hemodialysis, and those with inflammatory bowel disease or rheumatoid arthritis. We also excluded people with known hepatitis B or C and HIV/AIDS.

Patient screening, recruitment and data collection

We screened 382 consecutive patients with diabetes, hypertension or both who visited the outpatient department of the two hospitals for routine evaluation. Diabetes was defined as a diagnosis of diabetes or taking a hypoglycaemic drug, and hypertension as a diagnosis of hypertension or taking an anti-hypertensive drug. Information on age, gender, fasting blood glucose, body mass index (BMI), systolic blood pressure and diastolic blood pressure, medication used, duration on medication, and duration of diabetes was obtained using a pre-tested questionnaire and the patient medical records.

Measurement of blood pressure

Trained personnel used a mercury sphygmomanometer (ACCOSON, England) with a standard or a large cuff, appropriate to the patient’s size, to measure blood pressure after patients rested for 5 min, in accordance with recommendations of the American Heart Association Council on High Blood Pressure Research [10]. We report mean values of duplicate measurements.

Body mass index (BMI)

Height (nearest centimetre) and weight (nearest 0.1 kg), without shoes and in light clothing were measured. Participants were weighed on a bathroom scale (Zhongshan Camry Electronic Co. Ltd, Guangdong, China) and their height measured with a wall-mounted ruler. BMI was calculated by dividing weight (kg) by height squared (m 2 ), and categorized according to WHO criteria into normal weight (BMI 18.5–24.9), underweight (<18.5), overweight (25.0–29.9), obese (30.0–39.9) [11].

Blood sample collection and processing

A 4 ml venous blood sample was collected from each participant and 1 and 3 ml were dispensed into a fluoride oxalate tube and a serum gel separator tube respectively. After centrifugation at 1500 g for 3 min, the plasma and serum were stored in cryovials at −80 °C until assays were performed.

Biochemical analysis

Plasma fasting blood sugar (FBS), serum urea and creatinine were estimated using automated chemistry analyzer (Selectra JR). Estimated glomerular filtration rate (eGFR) was calculated using the CKD-EPI equation using the coefficients for black ethnicity in all [12].

Urine sample collection and processing

Urine protein was quantitatively estimated using the method of [13]. Estimation of urine creatinine was done using automated analyzer (ENVOY500/BT 3000 chemistry analyzer. Urine protein-creatinine ratio (uPCR) was calculated by the following formula: uPCR (mg/mmol = urine protein (mg/dl)/urine creatinine (mmol/dl). The urine protein/creatinine ratio (uPCR) was reported as mg/mmol. Resources were not available to measure albuminuria. The relationship between uACR and uPCR is not a simple one, so we did not attempt to convert between the two [14]. Instead we report uPCR in uACR categories, recognizing that this leads to overestimation of the proportions of patients with problems.

Statistical analysis

Analysis was performed using Graphpad prism version 5.0 (GraphPad software, San Diego California USA, Two-sample Student’s t test and chi-squared or Fisher’s exact test, as appropriate, and one-way analysis of variance (ANOVA) were used to compare groups. A P-value ≤0.05 was considered statistically significant.

Ethical considerations

The study was approved by the University of Cape Coast institutional review board (UCC/IRB) and the committee of ethics of TGH and ERH. Written informed consent was obtained from all participants.


Study procedures including collection of clinical data and the laboratory tests were funded by the authors.


We screened 382 consecutive patients, of whom 76 were less than 18 years, and 67 declined to participate: of the 239 consenting participants, 208 provided both blood and urine samples (i.e., 87 % with complete data) and are the subject of this report. Mean age was 60 and 71 % were female (Table 1); blood pressure was higher in participants with known hypertension. The distribution of body weight did not vary with diagnosis (diabetes, hypertension or both) (Table 1). Figures 1 and 2 report the types of medication used by participants and the types of medications used by hypertensives and diabetics respectively.

Table 1. Demographic, clinical and biochemical characteristics of study participants stratified by clinical conditions

thumbnailFig. 1. Types of medications used by participants

thumbnailFig. 2. Medications used by participants with diabetes and hypertension

Overall, 13 of 208 participants (6.2 %) had GFR less than 30, and 50 (24 %) had eGFR less than 60 mL/min/1.73 m 2 (Table 2); 4 of 40 participants (10 %) had uPCR > 30 mg/mmol, and 43 (96 %) had uPCR 3–30 mg/mmol. GFR less than 30 mL/min/1.73 m 2 and uPCR > 3 were more prevalent in those with both diabetes and hypertension than in patients with just one diagnosis (Table 3). Age and gender were similar across eGFR categories, but patients with the lowest eGFR had the highest systolic and diastolic blood pressures, and systolic blood pressure was above 140 in 17 and 26 % respectively of those in eGFR categories 3a and 3b, and in 36 % of those in eGFR category 4 (eGFR less than 30 mL/min/1.73 m 2 ).

Table 2. Prevalence of albuminuria, estimated glomerular filtration rate (eGFR) and stages of CKD stratified by clinical conditions

Table 3. Prevalence of albuminuria and estimated glomerular filtration rate (eGFR) stratified by clinical conditions

Table 3 show the distribution of patients by GFR and albuminuria categories, for those with hypertension, diabetes and both diabetes and hypertension. Overall, 30 % of participants fell into the category defined by KDIGO as ‘very high risk’: 23 % of patients with hypertension, 27 % of patients with diabetes and 74 % of those with both diabetes and hypertension.

Multivariable predictors of the presence of CKD were diagnosis category and duration on medication, both with odds ratios around 10, but not age, gender or BMI (Table 4).

Table 4. Multivariable associations of clinical variables with CKD in high-risk population


We identified a prevalence of CKD in patients with hypertension of 22 % and in patients with diabetes of 27 %. In patients with both hypertension and diabetes, the prevalence was 74 %, and 26 % had category G4 CKD. Clinical factors associated with a greater risk of CKD were the presence of both hypertension and diabetes, and duration on medication (antidiabetic and antihypertensive).

Osafo and colleagues [8] reported a 47 % prevalence of CKD among patients with hypertension in Ghana, in a multicenter study conducted predominantly among people with hypertension in the Greater Accra area (known for a high prevalence of hypertension). This is higher than the overall prevalence of 30 % among our study participants, and 22 % in people with hypertension. The difference may, in part, be owing to our having used the CKD-Epi [12] equation rather the MDRD equation, which was used in the study by Osafo and colleagues. MDRD is known to overestimate the prevalence of CKD compared with CKD-Epi, and this has also been shown by Kitiyakara and colleagues in their study of the high risk population in South East Asia [15]. In all patients with diabetes (with or without hypertension) we observed a prevalence of 48 %, which is lower than the 80 % prevalence observed among African adults with diabetes in a cross-sectional study conducted in Tanzania by Janmohamed and colleagues [7]. Again this is not directly comparable, with differences arising from their use of Cockroft-Gault equation to calculate the eGFR (which overestimates true GFR and underestimates prevalence); and urine albumin concentration as a measure of proteinuria (which is the recommended method of assessing proteinuria; our use of uPCR overestimates prevalence) but both these differences would result in a tendency for our prevalence by our methods to be higher than by their methods; so it may be that true differences exist. However, neither study used IDMS calibrated creatinine measurement and the direction of biases resulting from this limitation cannot be assessed.

Osafo and colleagues [8] observed a 51 % prevalence of CKD in patients with coexistent diabetes and hypertension, based on data from 712 participants in a multicenter study in Accra, Ghana, and we observed 74 % prevalence of CKD in our participants. Since their use of the MDRD formula would have biased their findings towards a greater incidence of CKD, it is possible that the prevalence is truly higher in this group in Ghana.

Good blood pressure control and ACE inhibitors are known to have a reno-protective effect, particularly in people with albuminuria [16]. In our study, 30 % overall, 11.1 % of people with diabetes and hypertension, 9.2 % of people with albuminuria and hypertension received ACE inhibitor therapy. We are unable to determine from our study to what extent this relatively low prevalence represents true contraindications or previous adverse effects, or whether this is a possible missed treatment opportunity that results from the economic costs of the drug (most of which are borne by the patients) or a reluctance on the part of physicians to prescribe ACE inhibitors without access to repeated monitoring of renal function (laboratory tests are paid for by the patient).

Our study has several limitations. First our findings cannot be generalized to other low income and low resource countries because it was not community based and was conducted within a population at risk of developing CKD with genetic and cultural differences. Further, there may be differences in the practices that lead to a patient being identified as having hypertension or diabetes, and differences in access to treatments for, and monitoring of those conditions. The study was conducted in the Sekondi-Takoradi metropolis. It is likely that there would be significant variation in prevalence rates in other urban and rural towns in the Western region and across Ghana as a whole. This study is also limited by the small sample size, use of the single measurement of serum creatinine (whereas to truly fulfill definitions of CKD, two measurements at least 3 months apart are needed), and by our lack of standardization of serum creatinine to isotope mass dilution spectrophotometry (IMDS). Third, although the CKD-EPI eGFR equation has been used in previous studies in this population [8], [18], [19] it has not been validated for use in the black Ghanaian population. Strengths of our study are the consecutive sampling and completeness of data collection.


CKD was detected among 30 % of this high-risk population. Further research is needed into optimal approaches to screening and treatment, including research on the effects of lowering economic barriers to known effective treatments. This is particularly important in resource-constrained practice settings such as ours, because the impact of the development of end-stage renal disease when dialysis cannot be provided is so much greater.

Competing interests

The authors declare that there is no conflict of interest associated with this manuscript.

Authors’ contributions

RKDE, SB, SAS and HA were involved in conception of the idea and study design and data analysis. RKDE, SB, PA and EOA were involved in recruitment of participants, data collection and compilation. RKDE, SB, SAS and EOA were involved in laboratory work, literature search and drafting of the manuscript. RKDE, PA and HA were involved in revision and final approval of the manuscript. All authors read and approved the final manuscript.


The authors appreciate the contributions Mr. Samuel K. Danquah and the staff and management of the Effia Nkwanta Regional Hospital (ENRH) and the Takoradi Government Hospital (TGH) especially the Laboratory Department in making this work a success. We also appreciate the contributions of the humble people of the Sekondi-Takoradi metropolis for availing themselves for this research.


  1. Stevens PE, Levin A. Evaluation and management of chronic kidney disease: synopsis of the kidney disease: improving global outcomes 2012 clinical practice guideline. Ann Intern Med. 2013;158(11):825–30.
  2. Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl. 2013;3:1–150.
  3. Hallan SI, Dahl K, Oien CM, Grootendorst DC, Aasberg A, Holmen J et al.. Screening strategies for chronic kidney disease in the general population: follow-up of cross sectional health survey. BMJ. 2006; 333(7577):1047. PubMed Abstract | Publisher Full Text OpenURL
  4. Naicker S. End-stage renal disease in sub-Saharan Africa. Ethn Dis. 2009; 19(1 Suppl 1):S1-13-15. OpenURL
  5. Gill GV, Mbanya JC, Ramaiya KL, Tesfaye S. A sub-Saharan African perspective of diabetes. Diabetologia. 2009; 52(1):8-16. PubMed Abstract | Publisher Full Text OpenURL
  6. Perico N, Remuzzi G. Chronic kidney disease in sub-Saharan Africa: a public health priority. Lancet Glob Health. 2014; 2(3):e124-5. PubMed Abstract | Publisher Full Text OpenURL
  7. Janmohamed MN, Kalluvya SE, Mueller A, Kabangila R, Smart LR, Downs JA et al.. Prevalence of chronic kidney disease in diabetic adult out-patients in Tanzania. BMC Nephrol. 2013; 14:183. PubMed Abstract | BioMed Central Full Text OpenURL
  8. Osafo C, Mate-Kole M, Affram K, Adu D. Prevalence of chronic kidney disease in hypertensive patients in Ghana. Ren Fail. 2011; 33(4):388-92. PubMed Abstract | Publisher Full Text OpenURL
  9. Sumaili EK, Cohen EP, Zinga CV, Krzesinski JM, Pakasa NM, Nseka NM. High prevalence of undiagnosed chronic kidney disease among at-risk population in Kinshasa, the Democratic Republic of Congo. BMC Nephrol. 2009; 10:18. PubMed Abstract | BioMed Central Full Text OpenURL
  10. Pickering TG, Hall JE, Appel LJ, Falkner BE, Graves J, Hill MN, Jones DW, Kurtz T, Sheps SG, Roccella EJ: Recommendations for blood pressure measurement in humans and experimental animals: Part 1: blood pressure measurement in humans: a statement for professionals from the Subcommittee of Professional and Public Education of the American Heart Association Council on High Blood Pressure Research. Hypertension 2005;45(1):142–161.
  11. Physical status: the use and interpretation of anthropometry, Report of a WHO expert committee. Technical report series. WHO, Geneva; 1995. OpenURL
  12. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, Feldman HI et al.. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009; 150(9):604-12. PubMed Abstract | Publisher Full Text OpenURL
  13. Pesce MA, Strande CS. A new micromethod for determination of protein in cerebrospinal fluid and urine. Clin. Chem. 1973; 19:1265-1267. PubMed Abstract | Publisher Full Text OpenURL
  14. Johnson DW, Jones GR, Mathew TH, Ludlow MJ, Chadban SJ, Usherwood T et al.. Chronic kidney disease and measurement of albuminuria or proteinuria: a position statement. Med J Aust. 2012; 197(4):224-5. OpenURL
  15. Kitiyakara C, Yamwong S, Vathesatogkit P, Chittamma A, Cheepudomwit S, Vanavanan S et al.. The impact of different GFR estimating equations on the prevalence of CKD and risk groups in a Southeast Asian cohort using the new KDIGO guidelines. BMC Nephrol. 2012; 13:1. PubMed Abstract | BioMed Central Full Text OpenURL
  16. Baltatzi M, Savopoulos C, Hatzitolios A: Role of angiotensin converting enzyme inhibitors and angiotensin receptor blockers in hypertension of chronic kidney disease and renoprotection. Study results. Hippokratia 2011, 15(Suppl 1):27–32
  17. van der Meer V, Wielders HPM, Grootendorst DC, de Kanter JS, Sijpkens YWJ, Assendelft WJJ et al.. Chronic kidney disease in patients with diabetes mellitus type 2 or hypertension in general practice. Br J Gen Pract. 2010; 60:884-90. PubMed Abstract | Publisher Full Text OpenURL
  18. Owiredu W, Ephraim R, Amidu N, Eghan Jnr BA, Quaye L. Predictive performance of renal function equations among Ghanaians presenting with chronic kidney disease. J Med Sci. 2008; 8:491-7. Publisher Full Text OpenURL
  19. Eastwood JB, Kerry SM, Plange-Rhule J, Micah FB, Antwi S, Boa FG et al.. Assessment of GFR by four methods in adults in Ashanti, Ghana: the need for an eGFR equation for lean African populations. Nephrol Dial Transplant. 2010; 25(7):2178-87. PubMed Abstract | Publisher Full Text OpenURL

The effectiveness of interventions to improve uptake and retention of HIV-infected pregnant and breastfeeding women and their infants in prevention of mother-to-child transmission care programs in low- and middle-income countries: protocol for a systematic review and meta-analysis

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The effectiveness of interventions to improve uptake and retention of HIV-infected pregnant and breastfeeding women and their infants in prevention of mother-to-child transmission care programs in low- and middle-income countries: protocol for a systematic review and meta-analysis

Lisa M. Puchalski Ritchie123, Monique van Lettow45*, Mina C. Hosseinipour67, Nora E. Rosenberg67, Sam Phiri8, Megan Landes39, Fabian Cataldo4, Sharon E. Straus12 and For the PURE consortium

Author Affiliations

1 Department of Medicine, University of Toronto, Toronto, ON, Canada

2 Li Ka Shing Knowledge Institute, St. Michaels Hospital, University of Toronto, Toronto, ON, Canada

3 University Health Network, Toronto, ON, Canada

4 Dignitas International, Zomba, Malawi

5 Dalla Lana School of Public Health, University of Toronto, Toronto, Canada

6 Division of Infectious Diseases, University of North Carolina, Chapel Hill, NC, USA

7 University of North Carolina Project, Lilongwe, Malawi

8 Lighthouse Trust, Lilongwe, Malawi

9 Department of Family and Community Medicine, University of Toronto, Toronto, ON, Canada

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Systematic Reviews 2015, 4:144  doi:10.1186/s13643-015-0136-x

The electronic version of this article is the complete one and can be found online at:

Received: 5 June 2015
Accepted: 15 October 2015
Published: 3 November 2015

© 2015 Puchalski Ritchie et al.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.



Despite recent improvements, uptake and retention of mothers and infants in prevention of mother-to-child transmission (PMTCT) services remain well below target levels in many low- and middle-income countries (LMICs). Identification of effective interventions to support uptake and retention is the first step towards improvement. We aim to complete a systematic review and meta-analysis to evaluate the effectiveness of interventions at the patient, provider or health system level in improving uptake and retention of HIV-infected mothers and their infants in PMTCT services in LMICs.


We will include studies comparing usual care or no intervention to any type of intervention to improve uptake and retention of HIV-infected pregnant or breastfeeding women and their children from birth to 2 years of age attending PMTCT services in LMICs. We will include randomized controlled trials (RCTs), cluster RCTs, non-randomized controlled trials, and interrupted time series. The primary outcomes of interest are percentage of HIV-infected women receiving/initiated on anti-retroviral prophylaxis or treatment, percentage of infants receiving/initiated on anti-retroviral prophylaxis, and percentage of women and infants completing the anti-retroviral regimen/retained in PMTCT care. The following databases will be searched from inception: Ovid MEDLINE and EMBASE, The WHO Global Health Library, CAB abstracts, EBM Reviews, CINAHL, HealthSTAR and Web of Science databases, Scopus, PsychINFO, POPLINE, Sociological Abstracts, ERIC, AIDS Education Global Information System, NLM Gateway, LILACS, Google Scholar, British Library Catalogue, DARE, ProQuest Dissertation & Theses, the New York Academy of Grey Literature, Open Grey, The Cochrane Library, WHO International Clinical Trials Registry, Controlled Clinical Trials, and Reference lists of included articles will be hand searched and study authors and content experts contacted to inquire about eligible unpublished or in progress studies. Screening, data abstraction, and risk of bias appraisal using the Cochrane Effective Practice and Organization of Care criteria will be conducted independently by two team members. Results will be synthesized narratively and a meta-analysis conducted using the DerSimonian Laird random effects method if appropriate based on assessment of clinical and statistical heterogeneity.


Our findings will be useful to PMTCT implementers, policy makers, and implementation researchers working in LMICs.

Systematic review registration

PROSPERO CRD42015020829


HIV; Prevention of mother-to-child transmission; Interventions; Retention; Uptake


Although the incidence of pediatric HIV acquisition is falling, over 240,000 children were newly infected with HIV in 2013, primarily through mother-to-child transmission [1]. Prevention of mother-to-child transmission (PMTCT) therapeutic regimens have been proven to reduce the risk of mother-to-child transmission from 20–45 % to 2 % in non-breastfeeding populations and 5 % or less in breastfeeding populations [2]. However, despite recent improvements in PMTCT clinical service coverage in low- and middle-income countries (LMICs) from 10 % in 2004 to 67 % in 2013, uptake and retention of mothers and newborns in PMTCT clinical services remain well below target levels in many LMICs [1], [2]. PMTCT services begin with maternal HIV testing and counseling and for HIV-infected women include the following: initiation and maintenance of pregnant and nursing women and their infants on PMTCT medication regimens for the duration of treatment as defined by the specific regimen employed; and completion of appropriate infant HIV testing. As a result of the 2010–2015 PMTCT strategic vision, the World Health Organization (WHO) has called for renewed commitment and effort towards achieving universal PMTCT coverage. The identification of interventions to support PMTCT uptake and retention is the first step towards improvement.

To date, two systematic reviews have been published that specifically evaluated the effectiveness of interventions to improve PMTCT coverage. Both were limited to specific interventions—male involvement [3] and integration of services [4] —and found too few studies meeting inclusion criteria to assess or make recommendations regarding effectiveness. A third systematic review indentified nine completed studies and five ongoing trials which examined initiation of antiretroviral (ARV) treatment in pregnant women [5]. While the authors report several promising interventions for improving ARV initiation, the quality of evidence was insufficient to support recommendations. In addition, results for ARV initiation in pregnant women were not independently examined, and maternal retention in PMTCT care and exposed infant care were not assessed. However, in our preliminary search, we identified a number of additional interventions including integration of HIV and antenatal care, peer-based programs, and community health worker programs [6]–[8] that have been evaluated to improve PMTCT uptake and retention in LMICs.

Given the paucity of synthesized evidence to date, we propose to complete a systematic review to identify what interventions are effective in improving uptake and retention of HIV-infected mothers and their infants in PMTCT services in LMICs. While we anticipate a relatively small number of evaluations of any given intervention type, which may preclude meta-analysis, a narrative synthesis of the evidence to date is urgently needed to inform LMIC PMTCT program development and policy. With the exception of Option B+ (lifelong triple ARV therapy for all HIV+ pregnant and breastfeeding women, regardless of clinical stage or CD4 count) recommended by WHO in April 2012 for which evidence is not yet available, the effectiveness of PMTCT regimens is well established and will therefore not be included in the present search [9].



A preliminary systematic review protocol was developed based on the Cochrane Handbook [10]. The protocol was revised with input from the PURE Malawi Consortium, a research partnership of governmental, non-governmental, and academic organizations working to improve PMTCT programming in Malawi. The final protocol was registered with the PROSPERO database (CRD42015020829, available at:, with reporting of the protocol guided by the PRISMA-P [11].

Eligibility criteria

We will include studies of HIV-infected pregnant and breastfeeding women and their children from birth to 2 years of age or termination of breastfeeding in LMICs. For the purpose of this review, we will utilize the EPOC filter to identify low- and middle-income countries [12] updated using the most recent World Bank World Country and Lending group classification [13] to define LMICs. Based on the unique challenges facing PMTCT health services in LMICs and intended use of the findings of this review to inform PMTCT service development in Malawi and other LMICs, we chose to limit the review to studies conducted in LMICs. Studies conducted only in high-income countries or where LMIC results cannot be separated will not be eligible for inclusion.

We will include studies comparing usual care or no intervention to any type of intervention (including patient, provider, or health system level interventions) to improve uptake and retention of HIV-infected pregnant or breastfeeding women and their children from birth to 2 years of age in PMTCT services. Patient level interventions are those focused on the patient and may include patient education programs, peer support programs, or efforts to improve patient support through engagement of partners or family members. Provider level interventions may include provider training, incentive programs, or tools to improve care provided. Health system level interventions may include restructuring of services and task shifting or other mechanisms to address human resource shortages.

The primary outcomes of interest are percentage of HIV-infected women receiving or initiated on ARV prophylaxis or treatment, percentage of infants born to HIV-infected mothers receiving or initiated on ARV prophylaxis, and percentage of women and infants retained in PMTCT care/completing the ARV regimen as defined by the PMTCT regimen utilized. Secondary outcomes of interest include the following: percentage of infants completing post-exposure HIV testing at 4–6 weeks after birth and percentage of infants completing post-exposure HIV testing at 6 weeks following termination of breastfeeding for all infants with known HIV exposure as recommend by the WHO [14]; percentage of HIV-exposed infants testing positive for HIV; and adverse events including negative impact(s) on resources/delivery and/or effectiveness of other health care programs (including economic impact), major (e.g., heart defects, neural tube defects, major limb malformations, hypospadias) or minor (e.g., syndactyly, cutis aplasia, accessory digit) congenital malformations, small for gestational age, premature delivery, still birth, and infant death within the first 2 years of life).

We will include controlled experimental studies (randomized controlled trials, cluster randomized controlled trials, non-randomized controlled trials) and controlled quasi-experimental studies (interrupted time series). We chose to include non-randomized controlled trials and quasi-experimental designs based on the results of our scoping searches, in which we found few randomized controlled trials that evaluated interventions to improve uptake and retention of HIV-infected women and their children in PMTCT services conducted in LMICs. Language of publication will be restricted to the language spoken by the study team and includes English only. No restrictions will be placed on publication status, study time frame, or duration of follow-up.

Information sources and literature search

Our search strategy was developed in consultation with an experienced information specialist and peer reviewed by two additional information specialists with expertise in systematic reviews using the Peer Review of Electronic Search Strategies checklist [15].

We will search the following electronic databases from inception to June 2015 using medical subject headings (MeSH) and text words related to HIV, pregnancy, breastfeeding, mother-to-child transmission, interventions, treatment uptake and retention, and low- and middle-income countries, using MEDLINE (OVID interface, 1946 to July Week 4 onwards), EMBASE (OVID interface, 1974 onward), The WHO Global Health Library (, CAB abstracts (OVID interface, 1973 onward), EBM Reviews (OVID interface, 1991 onward), CINAHL (EBSCOhost Research Databases interface, 19,814 onward), HealthSTAR (OVID interface, 1966 onward) and Web of Science databases (Thompson Reuters interface, 1975 onward), Scopus (Elsevier Interface, 1823 onward), PsychINFO (OVID interface, 1806 onward), POPLINE (, 1970 onward), Sociological Abstracts (Proquest interface, 1953 onward), ERIC (EBSCOhost Research Databases interface, 1966 onward), AIDS Education Global Information System (, NLM Gateway (, LILACS (, Google Scholar (, British Library Catalogue (, DARE (LexisNexis Academic interface, 2010 onward), ProQuest Dissertation & Theses (Proquest Interface, 1637 onward), the New York Academy of Grey Literature (, OpenGrey (, The Cochrane Library (, WHO International Clinical Trials Registry (, Controlled Clinical Trials (, and ( In addition, we will search reference lists of included articles and will contact experts in the field to inquire about eligible unpublished or in progress studies. Low- and middle-income countries will be searched utilizing the EPOC LMIC filter [12], updated based on the most recent World Bank LMIC list [13], see Additional file 1 for full MEDLINE search strategy. We will employ the Cochrane highly sensitive search strategy for identifying randomized trials in OVID MEDLINE: sensitivity and precision maximizing version [16], with the following two changes: Random* was used in place of randomized or randomly and trials ti was not used as an isolated term.

Study selection process

All titles and abstracts identified by the database search will be entered into a reference manager and duplicates removed manually into the duplicate folder, with companion papers for the same study retained for further evaluation at the full article phase of the review. Citations will be screened in two phases, level 1 (titles and abstracts) and level 2 (full-text review). A screening checklist will be developed and pilot tested by the reviewers on a random sample of 50 citations for each screening phase. Inter-rater agreement will be calculated for the pilot test and the form revised and re-piloted if percent agreement is <90 %. Once adequate agreement has been achieved, two team members will independently screen citations using the screening checklist. Differences at each stage will be resolved by consensus and if necessary through discussion with a third team member who is a content expert. Reference lists of included studies will be reviewed independently by the same two team members and again differences resolved through consensus and if necessary consultation with a third team member. A review log will be maintained in order to provide a record of resolution of discrepancies, decisions regarding studies described in >1 report, and reasons for exclusion.

Data abstraction and management

Data abstraction forms will be developed and pilot tested. Two team members will independently abstract directly into excel spreadsheets, corresponding to outcome tables, with additional space for comments and reasons for exclusion. Inter-rater reliability will be measured for data abstraction on a sample of excluded and included articles (approximately 10 %), and if percent agreement is found to be below 90 %, abstraction is conducted by a third team member. All discrepancies will be reviewed and consensus reached through discussion.

Data abstraction will be based on the PICOST [17] format including population, intervention, comparator, context, outcomes, study DESIGN, and time frame. Population characteristics to be abstracted include maternal age, number of children, marital status, place of residence (rural/urban), level of education, primary language, first infant HIV testing (4–6 weeks), and at end of study. Study characteristics of interest include study design, country and geographical location within country (rural/urban), setting (home, hospital or health center clinic, maternity ward), detailed description of intervention and comparator (usual care/no intervention), number of participants per group at study baseline and follow-up, duration of intervention and follow-up period, source of data (self-report, clinical records, pill counting), and publication status. Outcome data to be abstracted include percentage of HIV-infected women and their infants receiving or initiating PMTCT treatment, retained in or completing PMTCT as defined by the PMTCT regimen(s) used. Where data necessary for analysis are missing, corresponding authors will be contacted.

Although improved in recent years, examples of cluster trails inappropriately analyzed (without adjustment for cluster randomization) may be found among older trials. Data on appropriateness of analysis will be abstracted and reported as part of the review findings.

Methodological quality/risk of bias appraisal

Risk of bias assessment will be conducted using the Cochrane Effective Practice and Organization of Care (EPOC) criteria for assessing risk of bias [18]. Categories of bias assessed by this tool for randomized controlled trials, and non-randomized controlled trails include: allocation concealment, measurement of baseline characteristics and outcomes, management of incomplete data, blinding of outcome assessment, protection against contamination, selective reporting, and other categories of bias [18]. Categories of bias assessed by this tool for interrupted time series and repeated measures studies include independence of intervention from other changes, pre-specification of the intervention effect shape, effect of data collection on the intervention, allocation concealment, management of incomplete data, selective reporting, and other sources of bias [18]. Two team members will independently assess the studies for risk of bias at both study and outcome levels with disagreement resolved by consensus and discussion with a third team member if necessary. Studies will not be excluded based on risk of bias assessment, but the information will be used in the analysis and reporting of findings. Risk of bias will be categorized as low, high, or unclear risk of bias, using the EPOC-suggested risk of bias criteria [18]. We have elected not to use GRADE for this review given that the review findings are urgently needed to inform PMCTC program development and policy and that the need to build capacity in the use of grade across the team which would significantly prolong the review timeline.

Risk of publication bias will be examined using funnel plots. For studies in which selected reporting bias is suspected, planned outcomes will be reviewed for registered trials and authors contacted for missing outcomes and for unregistered trials, and risk of selected reporting bias rated as unclear if response not received within 8 weeks of our initial email request.

Evidence synthesis

A flow diagram will be utilized to visually present the results of the search strategy and reasons for exclusion of articles. Included articles will be synthesized and reported narratively and in tabular form to provide an overview of findings, assessment of bias and its potential impact on reported findings, and strengths and weaknesses of included studies. Summary statistics for continuous outcomes will be expressed as mean difference and standardized mean difference with 95 % CIs, for outcomes reported using the same and different scales, respectively. Summary statistics for dichotomous data will be expressed as risk ratio with 95 % CI.

If meta-analysis is possible, it will be conducted using the DerSimonian Laird random effects method. Summary statistics will be expressed as risk ratios with 95 % confidence interval. Clinical heterogeneity will be determined based on patient, intervention, and outcome characteristics of included studies. Statistical heterogeneity will be determined visually and the impact of heterogeneity assessed using the I 2 test, with I 2 of 75 % considered significant. Given the time constraints for this review, re-analysis for unit of analysis errors will not be conducted and cluster trials with unit of analysis errors will be excluded from the primary meta-analysis, and their impact assessed with sensitivity analysis comparing meta-analysis with and without studies with unit of analysis errors included. Interventions at the patient, provider, and health system level will be reported separately and analyzed separately if possible to do so.


The findings of this review will have significant implications for PMTCT program development and policy in LMICs. If high-quality evidence of intervention effectiveness is identified, this will provide important guidance to ongoing efforts to address low rates of uptake and retention of HIV-infected mothers and their infants in PMTCT services in LMICs. If high-quality evidence is not identified, findings of the systematic review may identify gaps in evidence and promising interventions providing direction for future intervention research.

To ensure our findings reach audiences who may benefit from the review findings, we plan to disseminate the results through publication in open access peer-reviewed journals, presentations at relevant international conferences, and direct communication within the professional networks of PURE consortium members.


ARV: anti-retroviral

EPOC: Effective Practice and Organization of Care

HIV: human immunodeficiency virus

LMIC: low- and middle-income country

MeSH: medical subject headings

PMTCT: prevention of mother-to-child transmission

WHO: World Health Organization

Competing interests

LPR was funded by a KT Canada Strategic Training Initiative in Health Research Fellowship award in 2014. SS is funded by a Tier 1 Canada Research Chair in Knowledge Translation and Quality of Care. The authors have declared that no competing interests exist. The authors alone are responsible for the writing and content of the paper.

Authors’ contributions

LPR and MvL conceived the study. LPR and SS were responsible for developing the search strategy. LPR was responsible for preparing and registering the protocol and for manuscript preparation. LPR, MvL, and SS were responsible for finalizing the protocol. MCH, NER, SP, ML, and FC provided content expertise and assisted with preparation of the protocol and manuscript. All authors provided critical revision of the protocol and manuscript. All authors read and approved the final manuscript.

Additional file

Additional file 1:. Ovid MEDLINE search strategy. (DOC 39 kb)

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We thank Melanie Anderson for her assistance with developing the search strategy and Elise Cogo and Becky Skidmore for peer reviewing our MEDLINE search strategy.


  1. World Health Organization, 2014. Global update on the health sector reponse to HIV, 2014. Accessed March 2015.
  2. World Health Organization, 2010. PMTCT strategic vision 2010–2015: preventing mother-to-child transmission of HIV to reach the UNGASS and Millennium Development Goals. Accessed March 2015.
  3. Brusamento S, Ghanotakis E, Tudor Car L, van-Velthoven MHMMT, Majeed A, Car J. Male involvement for increasing the effectiveness of prevention of mother-to-child HIV transmission (PMTCT) programmes (Review). The Cochrane library, 2012, issue 10. accessible at. http://www. OpenURL
  4. Tudor Car L, van-Velthoven MHMMT, Brusamento S, Elmoniry H, Car J, Majeed A, Atun R. Integrating prevention of mother-to-child HIV transmission (PMTCT) programmes with other health services for preventing HIV infection and improving HIV outcomes in developing countries (Review). The Cochrane library, 2011, issue 6. accessible at. http://www. OpenURL
  5. Govindasamy D, Meghij J, Negussi EK, Baggaley RC, Ford N, Kranzer K. Interventions to improve or facilitate linkage to or retention in pre-ART (HIV) care and initiation of ART in low- and middle income settings—a systematic review. J Int AIDS Soc. 2014; 17:19032. PubMed Abstract | Publisher Full Text OpenURL
  6. Turan JM, Onono M, Steinfeld RL, Shade SB, Owuor K, Washington S et al.. Implementation and operational research: effects of antenatal care and HIV treatment integration on elements of the PMTCT cascade: results from the SHAIP cluster-randomized controlled trial in Kenya. J Acquir Immune Defic Syndr. 2015; 69(5):e172-e181. PubMed Abstract | Publisher Full Text OpenURL
  7. Decroo T, Telfer B, Biot M et al.. Distribution of antiretroviral treatment through self-forming groups of patients in Tete Province. Mozambique J Acquir Immune Defic Syndr. 2011; 56:e39-e44. PubMed Abstract | Publisher Full Text OpenURL
  8. Kim MH, Ahmed S, Buck WC et al.. The Tingathe programme: a pilot intervention using community health workers to create a continuum of care in the prevention of mother to child transmission of HIV (PMTCT) cascade of services in Malawi. J Int AIDS Soc. 2012; 15(suppl 2):17389. PubMed Abstract | Publisher Full Text OpenURL
  9. Teasdale C, Marais B, Abrams E. HIV: prevention of mother-to-child transmission. Clin Evid. 2011; 01:909. OpenURL
  10. Higgins JPT, Green S (editors). Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]. The Cochrane Collaboration, 2011. Available from Accessed January 2015.
  11. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew P, Stewart L A, and PRISMA-P Group. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews 2015, 4:1 doi:10.1186/2046-4053-4-1
  12. EPOC filter to identify Low and middle income countries Accessed March 2015.
  13. The world bank data: Country and lending groups Accessed January 2015.
  14. World Health Organizaiton (2010). WHO recommendations on the diagnosis of HIV infection in infants and children., accessed march 2015.
  15. Sampson M, McGowan J, Cogo E, Grimshaw J, Moher D, Lefebvre C. An evidence-based practice guideline for the peer review of electronic search strategies. J Clin Epidemiol. 2009; 62(9):944-952. PubMed Abstract | Publisher Full Text OpenURL
  16. Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]. The Cochrane Collaboration, 2011. The Cochrane Highly Sensitive Search Strategies for identifying randomized trials in MEDLINE (section6.4.11.1, 2008 revision). Available from Accessed January 2015.
  17. Stone PW. Popping the (PICO) question in research and evidence-based practice. Appl Nurs Res. 2002; 15(3):197-198. PubMed Abstract | Publisher Full Text OpenURL
  18. Effective Practice and Organisation of Care (EPOC). EPOC Resources for review authors. Oslo: Norwegian Knowledge Centre for the Health Services; 2013. Available at: Accessed January 2015.

Increased circulating follicular helper T cells with decreased programmed death-1 in chronic renal allograft rejection

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Increased circulating follicular helper T cells with decreased programmed death-1 in chronic renal allograft rejection

Jian Shi1, Fengbao Luo1, Qianqian Shi1, Xianlin Xu1, Xiaozhou He1* and Ying Xia2*

Author Affiliations

1 Third Clinical College of Soochow University, Changzhou, Jiangsu, China

2 The University of Texas Medical School at Houston, Houston, TX, USA

For all author emails, please log on.

BMC Nephrology 2015, 16:182  doi:10.1186/s12882-015-0172-8

The electronic version of this article is the complete one and can be found online at:

Received: 26 May 2015
Accepted: 19 October 2015
Published: 3 November 2015

© 2015 Shi et al.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.



Chronic antibody-mediated rejection is a major issue that affects long-term renal allograft survival. Since follicular helper T (Tfh) cells promote the development of antigen-specific B cells in alloimmune responses, we investigated the potential roles of Tfh cells, B cells and their alloimmune-regulating molecules in the pathogenesis of chronic renal allograft rejection in this study.


The frequency of Tfh, B cells and the levels of their alloimmune-regulating molecules including chemokine receptor type 5 (CXCR5), inducible T cell co-stimulator (ICOS), programmed death-1 (PD-1), ICOSL, PDL-1 and interleukin-21 (IL-21), of peripheral blood were comparatively measured in 42 primary renal allograft recipients within 1–3 years after transplantation. Among them, 24 patients had definite chronic rejection, while other 18 patients had normal renal function.


Tfh-cell ratio was significantly increased with PD-1 down-regulation in the patients with chronic renal allograft rejection, while B cells and the alloimmune-regulating molecules studied did not show any appreciable change in parallel.


The patients with chronic renal allograft rejection have a characteristic increase in circulating Tfh cells with a decrease in PD-1 expression. These pathological changes may be a therapeutic target for the treatment of chronic renal allograft rejection and can be useful as a clinical index for monitoring conditions of renal transplant.


Chronic renal allograft rejection; Tfh cells; PD-1


Renal transplantation remains an effective treatment for end-stage renal dysfunction [1], facilitating a return to normal health and prolonging life. However, antibody-mediated rejection is a major issue that affects long-term renal allograft survival. Despite the rapid development of new immunosuppressive drugs for attenuating acute rejection, improving the long-term survival of grafts is still a challenge mainly because of chronic allograft rejection. The features of chronic renal allograft rejection are hypertension, proteinuria, progressive deterioration of graft function, peritubular capillary C4d deposition, presence of donor-specific antibodies (DSA) and morphological changes with transplant vasculopathy, glomerulopathy, fibrosis and lymphocyte infiltration. However, the causes leading to chronic rejection are complex and not well understood yet [2].

Allograft rejection is characterized by an increase in activated CD4+ T-lymphocytes, especially regulatory and cytotoxic T cells, leading to an imbalance of immune responses in the transplant recipients [3], [4]. Functionally, CD4+ T helper cells that interact with antigen-specific B cells are required for the production of alloantibodies [5]. Among them, Tfh cells, a recently defined subset of CD4+ T cells, play a particular role in mediating B cell-driven allogeneic responses. Tfh cells can migrate into germinal centers and promote B-cell activation and differentiation into immunoglobulin-producing plasmablasts or plasma cells [5]. They can express PD-1, CXCR5, ICOS, IL-21 and the transcription factor B-cell lymphoma 6 (Bcl-6) [6], [7], thereby displaying their regulatory functions.

Circulating Tfh cells, peripheral counterparts of conventional Tfh cells, express PD-1, CXCR5, ICOS and IL-21, but not Bcl-6 [5]–[7]. They play an important role in human humoral immunity through these functional molecules. Their abnormal activities are critically involved in the onset of several human diseases such as autoimmune disorders, cancer and infective diseases [7]–[10]. Therefore, an alteration in circulating Tfh cells may be correlated with disease conditions and might be used as a biomarker of certain diseases [11]–[13]. Moreover, recent clinical studies have shown that peripheral Tfh cells in the kidney transplant recipients with acute rejection can regulate B-cell alloreactivity and the number of these Tfh cells alters the immunization status and DSA levels [14]. However, their function and relevance to chronic renal allograft rejection are not known yet.

This study was conducted to explore the potential association between circulating Tfh cells and chronic rejection in kidney transplant recipients. The outcome results may provide a useful hint for clinical prediction of renal status after transplantation and for a potential new therapy for chronic allograft rejection.


This study was approved by the Institutional Ethics Committee of Third Affiliated Hospital of Soochow University, Jiangsu Province, China. Written-informed consent was obtained from all participants of the study.


The patients with primary renal transplantation for 1–3 years were enrolled from October 2013 to December 2014. Totally 42 recipients were studied in this work, including 24 patients with chronic rejection (CR group) and 18 patients with normal renal function as the normal control (NC group). All of them received the treatment with cyclosporine A, methylprednisolone and mycophenolate mofetil or azathioprine after the renal transplantation. The diagnosis for chronic allograft rejection was confirmed by renal biopsy, biochemical measurements and immunological assays, including DSA as described in other studies [15]–[18]. In specific,the diagnostic criteria included 1) clinical evidence of slowly deteriorating graft function; 2) biopsy evidence and diffuse deposition of C4d; and 3) the presence of circulating DSA at the time of biopsy. Their peripheral blood samples were collected in a standard way by the clinical laboratory of the hospital. All the subjects had no infective disease when sampling blood.

Surface staining and flow cytometry analysis

The whole blood was subjected to flow cytometry detection by a BD bioscience FACSCantoII cytometer with FACSDiva software for measuring the frequency of circulating Tfh cells and B cells as well as the expression of their surface markers. The following conjugated monoclonal antibodies were used to stain the cells: CD4-FITC, CXCR5-APC, ICOS-PE, PD-1-PE, CD19-PE-Cy5.5, ICOSL-PE and PDL-1-APC. The cells were incubated with the antibodies for 30 min at room temperature in the dark. Totally 50,000 lymphocytes were acquired in each sample. Data were analyzed using Flow Jo software 7.6.1.

Enzyme-linked immunosorbent assay (ELISA)

The levels of serum IL-21 were quantified by using the human IL-21 ELISA kit (eBioscience) according to the manufacturer’s instructions. The concentration in each individual sample was calculated according to the standard curve.

Statistical analyses

All experimental data were analyzed by Graph Prism version 5.0. The results were expressed as mean ± SD and subjected to t test for statistical comparisons between the NC and CR groups. If a p-value was found to be less than 0.05, the result would be considered statistically significant.



The general information of the renal transplant recipients was summarized in Table 1. Gender and age were similar between CR and NC groups. The mean serum creatinine (sCr) and blood urea nitrogen (BUN) were almost three-fold higher in the CR patients than those of NC group (p < 0.001).

Table 1. General information of the renal transplant patients

Increased circulating Tfh cells in the CR patients

To determine if chronic rejection was associated with an alteration in circulating Tfh cells in the renal transplantation recipients, we first evaluated the frequency of CD4 + CXCR5+ Tfh cells through flow cytometry. As shown in Fig. 1, the percentage of CD4 + CXCR5+ Tfh cells among total CD4+ T cells was significantly increased in the CR group as compared to that of the NC group (35.3 ± 8.5 % vs.19.0 ± 5.0, P < 0.001).

thumbnailFig. 1. Frequency of Tfh cells in the patients with renal allograft. a, representative contour plots of the ratio of Tfh cells in the NC and CR groups, b, mean values of the frequency of Tfh cells in the two groups. ***, P < 0.001. Note a significant increase in Tfh cells in the CR group compared to that of the control group

Differential changes in PD-1, CXCR5, ICOS, and IL-21 of Tfh cells in the CR patients

We further detected the changes of PD-1, CXCR5 and ICOS in the high frequency of Tfh cells and found that PD-1 was significantly down-regulated in these Tfh cells (Fig. 2a). In sharp contrast, there were no significant changes in CXCR5 and ICOS in the CR group as compared to the NC group (Fig. 2b and c).

thumbnailFig. 2. Comparative changes in PD-1, CXCR5 and ICOS expression on Tfh-cell surfaces. a,PD-1. b, CXCR5. c, ICOS. * P < 0.05. Note a significant decrease in PD-1 expression with no appreciable changes in CXCR5 and ICOS expression in the CR patients as compared to the NC group

IL-21 is a biological hallmark of Tfh cells because this immune cytokine is produced by Tfh cells and is involved in mediating Tfh-B-cell interaction [6]. Therefore, we further measured the concentration of IL-21 in the serum of the CR patients (Fig. 3). Similarly as the changes in CXCR5 and ICOS, serum IL-21 did not show any significant change in the CR patients as compared to that of the control group (406.9 ± 123.9 pg/ml vs. 449.1 ± 101.7 pg/ml, P > 0.05).

thumbnailFig. 3. The level of serum IL-21 in renal allograft patients. Note that there was no statistic difference in the IL-21 level between the CR and NC groups

No changes in circulating B cells, PDL-1 and ICOSL in the CR patients

Since B cells are key players in the graft rejection [19], we further determined the frequency of total B cells and compared their change with that of Tfh cells. The ratio of B lymphocytes was not significantly different between CR and NC groups (Fig. 4), unlike Tfh cells. Because PDL-1-expressing B cells interact with PD-1+ Tfh cells to regulate the maturation and survival of B cells [20], we next detected the expression of PDL-1 in B cells. Unlike the change in the PD-1 of Tfh cells, PDL-1 did not decrease in B cells at all in the CR group (Fig. 5a). Also, ICOSL had no significant change in the CR patients (Fig. 5b).

thumbnailFig. 4. The frequency of B cells. Note that there was no significant difference between two groups

thumbnailFig. 5. The expression of PDL-1 and ICOSL in B cells. Note that there were no appreciable differences in both PDL-1 (a) and ICOSL (b) between two groups

All these results suggest that the increase in circulating Tfh cells with PD-1 down-regulation is a specific and characteristic change in the CR patients.


We have made a novel finding in this work, i.e., a major increase in circulating Tfh cells with a significant decrease in PD-1 in the patients with chronic renal allograft rejection. In sharp contrast, B cells and the alloimmune-regulating molecules such as CXCR5, ICOS, ICOSL, PDL-1 and IL-21 did not show any appreciable change in parallel.

Tfh cells display multiple features for their helper functions in secondary lymphoid organs or tissues with inflammation [21]. They migrate into B cell follicles of germinal centers [22] and thereby help B cells generate antibodies for humoral immunity [3], [6], [23]. In fact, Tfh cells, as an immune regulator, are critically involved in the pathological processes of many immune diseases [8]. In renal allograft rejection, the germinal center reactions are dependent on Tfh, while B cells are indispensable for the immune attack to the newly transplanted kidney [24].

Tfh cells express PD-1 [6], while B cells produce PDL-1, an endogenous ligand of PD-1 [19]. The PD-1/PDL-1 signaling has been shown to play an important role in regulating immune functions and affecting the activation of regulatory T cells, cytotoxic T cells and Dendritic cells [25]. Such signaling also influences the generation and differentiation of Tfh and B cells themselves [26]. Recent evidence suggests that blocking the PD-1 signaling induces an up-regulation of Tfh generation and differentiation, which may directly lead to autoimmune encephalomyelitis [27]. In contrast, stimulating this pathway can prolong the survival of the patients after cardiac allograft transplantation [28]. More recently, PD-1 ligands are found to protect the kidneys from ischemia reperfusion injury [29]. In fact, PDL-1, the endogenous ligand of PD-1, has been demonstrated as a required factor for peripheral transplantation tolerance and protection aganist chronic allograft rejection [30].

Taken together, PD-1 signaling is a key regulator for attenuating the Tfh cells and down-regulating the overreaction of humoral immunity against the transplanted kidneys. Therefore, the novel finding of the present study strongly suggests that the deficiency of PD-1 expression causes the increase in Tfh cells, thereby leading to an overreaction of humoral immunity against the allergenic organ, which may be a major reason for chronic allograft rejection.

Tfh and B cells also express many other immune-regulating molecules such as CXCR5, ICOS, ICOSL, and IL-21 [6], [19], [26]. All these molecules are actively involved in the regulation of immune function [26]. For example, an increase in the expression of CXCR5 can enable Tfh cells to migrate into germinal centers [21]. On the other hand, ICOS, another surface receptor like PD-1, also mediate the generation, development and function of Tfh cells by activating ICOS/ICOSL signaling [31], [32]. Moreover, IL-21,a pro-inflammatory cytokine secreted by Tfh cells,has an important role in Tfh cell differentiation, B cell proliferation [33], and the expression of PD-1 [34] and CXCR5 [26]. However, all of these immune regulators did not shown any change in the patients with chronic allograft rejection. We are therefore confident that the deficient PD-1 expression with increased circulating Tfh cells is a specific and characteristic change in chronic allograft rejection.

In the lymph nodes, CD4+ CXCR5+ Tfh cells are more effective in helping B cells than their peripheral counterparts [7]. Humoral response in the lymph nodes can be suppressed by anti-CD40 mAb via regulating Tfh cells [23]. In the transplanted kidneys with acute rejection, infiltrated Tfh cells have been found to participate in the antibody-mediated rejection [14]. However, little is known about the role of these special Tfh cells in the transplanted kidneys with chronic rejection. We speculate that the increase in circulating Tfh cells with a decrease in PD-1 expression might, at least partially, contributes to the genesis of the renal chronic rejection by migrating and infiltrating into germinal centers of renal allografts and lymphoid organs. We will further clarify this issue in our future work.

In addition, pre-existent DSA storing before renal transplantation and de-novo DSA developing after renal transplantation are associated with antibody-mediated rejection and allograft failure [35]. However, recent studies have shown that despite the numbers of circulating Tfh cells were higher in the patients with pre-existent DSA than those without pre-existent DSA, the levels of circulating Tfh cells were not different among the patients with or without de-novo DSA [35], [36]. Therefore, the relationship between the frequency of circulating Tfh cells and the level of DSA in renal allograft rejection is not clear yet and needs more investigations.


Our first data show that decreased PD-1 expression may contribute to the increase in circulating Tfh cells in the patients with chronic renal allograft rejection. This finding provides a potential hint for a new target for the treatment of chronic rejection. Moreover, a dynamic change in the expression of PD-1 and the number of circulating Tfh cells may be used as an index for monitoring chronic allograft rejection after kidney transplantation as.


Tfh: Follicular helper T cells

CXCR5: Chemokine receptor type 5

ICOS: Inducible T cell co-stimulator

PD-1: Programmed death-1

ICOSL: Inducible T cell co-stimulator ligand

PDL-1: Programmed death-1 ligand

IL-21: Interleukin-21

Bcl-6: Transcription factor B-cell lymphoma 6

CR: Chronic rejection

NC: Normal control

ELISA: Enzyme-linked immunosorbent assay

sCr: Serum creatinine

BUN: Blood urea nitrogen

DSA: Donor-specific antibodies.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

JS, XX, XH and YX conceived and designed the experiments. JS, FL and QS performed the experiments. JS analyzed the data. XH provided research reagents. JS and YX wrote the paper. All authors read and approved the final manuscript.


This work was supported by the National Natural Science Foundation of China (Grant No.81273267) . YX was partially supported by NIH (AT-004422).


  1. Nankivell BJ, Alexander SI. Rejection of the kidney allograft. N Engl J Med. 2010; 363:1451-62. PubMed Abstract | Publisher Full Text OpenURL
  2. Halloran PF. Call for revolution: a new approach to describing allograft deterioration. Am J Transplant. 2002; 2:195-200. PubMed Abstract | Publisher Full Text OpenURL
  3. Giaretta F, Bussolino S, Beltramo S, Fop F, Rossetti M, Messina M et al.. Different regulatory and cytotoxic CD4+ T lymphocyte profiles in renal transplants with antibody-mediated chronic rejection or long-term good graft function. Transpl Immunol. 2013; 28:48-56. PubMed Abstract | Publisher Full Text OpenURL
  4. Nankivell BJ, Chapman JR. Chronic allograft nephropathy: current concepts and future directions. Transplantation. 2006; 81:643-54. PubMed Abstract | Publisher Full Text OpenURL
  5. Morita R, Schmitt N, Bentebibel SE, Ranganathan R, Bourdery L, Zurawski G et al.. Human blood CXCR5(+)CD4(+) T cells are counterparts of T follicular cells and contain specific subsets that differentially support antibody secretion. Immunity. 2011; 34:108-21. PubMed Abstract | Publisher Full Text OpenURL
  6. Crotty S. Follicular helper CD4 T cells (TFH). Annu Rev Immunol. 2011; 29:621-63. PubMed Abstract | Publisher Full Text OpenURL
  7. Tangye SG, Ma CS, Brink R, Deenick EK. The good, the bad and the ugly – TFH cells in human health and disease. Nat Rev Immunol. 2013; 13:412-26. PubMed Abstract | Publisher Full Text OpenURL
  8. King C, Tangye SG, Mackay CR. T follicular helper (TFH) cells in normal and dysregulated immune responses. Annu Rev Immunol. 2008; 26:741-66. PubMed Abstract | Publisher Full Text OpenURL
  9. Shi W, Li X, Cha Z, Sun S, Wang L, Jiao S et al.. Dysregulation of circulating follicular helper T cells in nonsmall cell lung cancer. DNA Cell Biol. 2014; 33:355-60. PubMed Abstract | Publisher Full Text OpenURL
  10. Slight SR, Rangel-Moreno J, Gopal R, Lin Y, Fallert-Junecko BA, Mehra S et al.. CXCR5(+) T helper cells mediate protective immunity against tuberculosis. J Clin Invest. 2013; 123:712-26. PubMed Abstract | Publisher Full Text OpenURL
  11. Bentebibel SE, Lopez S, Obermoser G, Schmitt N, Mueller C, Harrod C et al.. Induction of ICOS + CXCR3 + CXCR5+ TH cells correlates with antibody responses to influenza vaccination. Sci Transl Med. 2013; 5:176ra132. Publisher Full Text OpenURL
  12. Locci M, Havenar-Daughton C, Landais E, Wu J, Kroenke MA, Arlehamn CL et al.. Human circulating PD-1 + CXCR3-CXCR5+ memory Tfh cells are highly functional and correlate with broadly neutralizing HIV antibody responses. Immunity. 2013; 39:758-69. PubMed Abstract | Publisher Full Text OpenURL
  13. Pallikkuth S, Parmigiani A, Silva SY, George VK, Fischl M, Pahwa R et al.. Impaired peripheral blood T-follicular helper cell function in HIV-infected nonresponders to the 2009 H1N1/09 vaccine. Blood. 2012; 120:985-93. PubMed Abstract | Publisher Full Text OpenURL
  14. Carla CB, Gretchen NG, Karin B. T Follicular Helper Cells in Transplantation: The Target to Attenuate Antibody-Mediated Allogeneic Responses? Curr Transpl Rep. 2014; 1:166-72. Publisher Full Text OpenURL
  15. Rascio F, Pontrelli P, Accetturo M, Oranger A, Gigante M, Castellano G et al.. A type I interferon signature characterizes chronic antibody-mediated rejection in kidney transplantation. J Pathol. 2015; 237(1):72-84. PubMed Abstract | Publisher Full Text OpenURL
  16. Hong YA, Kin HG, Choi SR, Sun IO, Park HS, Chung BH et al.. Effectiveness of Rituximab and Intravenous Immunoglobulin Therapy in Renal Transplant Recipients with Chronic Active Antibody-Mediated Rejection. Transplant Proc. 2012; 44:182-4. PubMed Abstract | Publisher Full Text OpenURL
  17. Chow KM, Szeto CC, Lai FM, Luk CC, Kwan BC, Leung CB et al.. Functional and histological improvement after everolimus rescue of chronic allograft dysfunction in renal transplant recipients. Ther Clin Risk Manag. 2015; 11:829-35. PubMed Abstract | Publisher Full Text OpenURL
  18. Kim MG, Kim YJ, Kwon HY, Park HC, Koo TY, Jeong JC et al.. Outcomes of combination therapy for chronic antibody-mediated rejection in renal transplantation. Nephrology(Carlton). 2013; 18:820-6. Publisher Full Text OpenURL
  19. Nouel A, Simon Q, Jamin C, Pers JO, Hillion S. Regulatory B cells: an exciting target for future therapeutics in transplantation. Front Immunol. 2014; 5:11. PubMed Abstract | Publisher Full Text OpenURL
  20. Good-Jacobson KL, Szumilas CG, Chen L, Sharpe AH, Tomayko MM, Shlomchik MJ. PD-1 regulates germinal center B cell survival and the formation and affinity of long-lived plasma cells. Nat Immunol. 2010; 11:535-42. PubMed Abstract | Publisher Full Text OpenURL
  21. Schmitt N, Bentebibel SE, Ueno H. Phenotype and functions of memory Tfh cells in human blood. Trends Immunol. 2014; 35:436-42. PubMed Abstract | Publisher Full Text OpenURL
  22. Schaerli P, Willimann K, Lang AB, Lipp M, Loetscher P, Moser B. CXC chemokine receptor 5 expression defines follicular homing T cells with B cell helper function. J Exp Med. 2000; 192:1553-62. PubMed Abstract | Publisher Full Text OpenURL
  23. McHeyzer-Williams LJ, Pelletier N, Mark L, Fazilleau N, McHeyzer-Williams MG. Follicular helper T cells as cognate regulators of B cell immunity. Curr Opin Immunol. 2009; 21:266-73. PubMed Abstract | Publisher Full Text OpenURL
  24. Kim EJ, Kwun, Gibby AC, Hong JJ, Farris AB, Iwakoshi NN et al.. Costimulation blockade alters germinal center responses and prevents antibody-mediated rejection. Am J Transplant. 2014; 14:59-69. PubMed Abstract | Publisher Full Text OpenURL
  25. Tsang JY, Li D, Ho D, Peng J, Xu A, Lamb J et al.. Novel immunomodulatory effects of adiponectin on dendritic cell functions. Int Immunopharmacol. 2011; 11:604-9. PubMed Abstract | Publisher Full Text OpenURL
  26. Park HJ, Kim DH, Lim SH, Kim WJ, Youn J, Choi YS et al.. Insights into the role of follicular helper T cells in autoimmunity. Immune Netw. 2014; 14:21-9. PubMed Abstract | Publisher Full Text OpenURL
  27. Ansari MJ, Salama AD, Chitnis T, Smith RN, Yagita H, Akiba H et al.. The programmed death-1 (PD-1) pathway regulates autoimmune diabetes in nonobese diabetic (NOD) mice. J Exp Med. 2003; 198:63-9. PubMed Abstract | Publisher Full Text OpenURL
  28. Ozkaynak E, Wang L, Goodearl A, McDonald K, Qin S, O’Keefe T et al.. Programmed death-1 targeting can promote allograft survival. J Immunol. 2002; 169:6546-53. PubMed Abstract | Publisher Full Text OpenURL
  29. Jaworska K, Ratajczak J, Huang L, Whalen K, Yang M, Stevens BK, et al. Both PD-1 Ligands Protect the Kidney from Ischemia Reperfusion Injury. J Immunol. 2015;194(1):325–33.
  30. Tanaka K, Albin MJ, Yuan X, Yamaura K, Habicht A, Murayama T et al.. PDL1 is required for peripheral transplantation tolerance and protection from chronic allograft rejection. J Immunol. 2007; 179:5204-10. PubMed Abstract | Publisher Full Text OpenURL
  31. Gigoux M, Shang J, Pak Y, Xu M, Choe J, Mak TW et al.. Inducible costimulator promotes helper T-cell differentiation through phosphoinositide 3-kinase. Proc Natl Acad Sci. 2009; 106:20371-6. PubMed Abstract | Publisher Full Text OpenURL
  32. Hams E, McCarron MJ, Amu S, Yagita H, Azuma M, Chen L et al.. Blockade of B7-H1 (programmed death ligand 1) enhances humoral immunity by positively regulating the generation of T follicular helper cells. J Immunol. 2011; 186:5648-55. PubMed Abstract | Publisher Full Text OpenURL
  33. Nurieva RI, Chung Y, Hwang D, Yang XO, Kang HS, Ma L et al.. Generation of T follicular helper cells is mediated by interleukin-21 but independent of T helper 1, 2, or 17 cell lineages. Immunity. 2008; 29:138-49. PubMed Abstract | Publisher Full Text OpenURL
  34. Jacob J, Przylepa J, Miller C, Kelsoe G. In situ studies of the primary immune response to (4-hydroxy-3-nitrophenyl)acetyl. III. The kinetics of V region mutation and selection in germinal center B cells. J Exp Med. 1993; 178:1293-307. PubMed Abstract | Publisher Full Text OpenURL
  35. de Graav GN, Dieterich M, Hesselink DA, Boer K, Clahsen-van Groningen MC, Kraaijeveld R et al.. Follicular T helper cells and humoral reactivity in kidney transplant patients. Clin Exp Immunol. 2015; 180:329-40. PubMed Abstract | Publisher Full Text OpenURL
  36. Lee PC, Zhu L, Terasaki PI, Everly MJ. HLA-specific antibodies developed in the first year posttransplant are predictive of chronic rejection and renal graft loss. Transplantation. 2009; 8:568-74. Publisher Full Text OpenURL