Introduction
Frailty is a clinical syndrome with multiple causes and contributors, resulting in enhanced vulnerability to stressors and increased risk of adverse outcomes. Several operational definitions are used; the frailty phenotype, operationalized by Fried et al. is characterized by unintentional weight loss, diminished gait speed and grip strength, exhaustion and low energy expenditure [1] frailty phenotype has been associated with increased mortality and morbidity in the general population [1,2] [1]
A higher frailty phenotype prevalence in HIV -infected compared with HIV -uninfected populations has been observed [3–7] frailty , immunodeficiency [3,4,6,8,9] [3,4,7] frailty in the general population [2,10–12] HIV infection and frailty [13,14] abdominal obesity , may be involved in the pathophysiology of frailty in the general population [15–17] HIV infection by itself as well as exposure to antiretroviral therapy (ART) may contribute to body composition changes, and thereby to the development of frailty in the context of HIV [18]
Within the AGEh IV Cohort Study we systematically assessed the frailty phenotype in HIV type 1 (HIV -1)-infected individuals aged at least 45, and concurrently in HIV -uninfected individuals with a similar demographic and behavioral background. We compared the prevalence of frailty and prefrailty and investigated whether HIV was independently associated with prefrailty and frailty . Additionally we explored the role of comorbidities, markers of inflammation and body composition, and HIV -disease and ART-related factors as possible mediators in the relation between HIV , prefrailty and frailty .
Methods and materials
Study population
Between 2010 and 2012, 597 HIV -1-infected individuals, aged at least 45, were enrolled into the AGEh IV Cohort Study at the HIV outpatient clinic of the Academic Medical Center, Amsterdam, the Netherlands. Five hundred and fifty-one HIV -uninfected individuals, aged at least 45, were recruited from the sexual health clinic and the Amsterdam Cohort Studies on HIV /AIDS at the Amsterdam Public Health Service, as a comparable control group with a similar geographical, socio-demographic and behavioral background. Participants undergo a biennial standardized screening for age-associated comorbidities and organ dysfunction. Details concerning study procedures have previously been published [19]
Detailed information concerning HIV infection and ART history was obtained from the HIV Monitoring Foundation registry [20]
Written informed consent was obtained from all participants; the study was approved by the local ethics review board (ClinicalTrials.gov identifier NCT01466582).
Definitions
The frailty phenotype, as modified by Önen, was assessed in all participants in a standardized manner [1,21] frailty , presence of 1–2 was defined as prefrailty and absence of all five factors was considered nonfrail. Self-reported unintentional weight loss (1) was considered present if exceeding 4.5 kg in the last year or 2.3 kg in the last 6 months. Low physical activity (2) was considered present if participant answered ‘yes, limited a lot’ when asked whether their health limits vigorous activities such as running, lifting heavy objects, participating in strenuous sports. Exhaustion (3) was present if participant answered “occasionally” or “most of the time” to either one of the following statements: During the last week, how often have you felt that (a) everything you did was an effort, or (b) you could not ‘get going’ [two questions from the Center for Epidemiologic Studies Depression (CES-D) scale]. Maximum grip strength (4) was assessed using Jamar handheld dynamometer (Jamar Plus+ Digital Hand Dynamometer, Jamar, USA), the mean value of three consecutive measurements of the dominant hand was used for analysis. Study participants with pain in the dominant hand, or a missing hand, were excluded from grip strength assessment. Participants were asked to walk a distance of 4.57 m (15 ft) at their own usual pace (5). The average of two consecutive measurements was used. Individuals were excluded from walking speed assessment if walking was painful, if they needed a support device, if they were unable to walk or if one of the legs was missing or incomplete. The cohort, including both HIV -uninfected and HIV -infected individuals, was stratified using the strata as previously described by Fried [1] https://links.lww.com/QAD/A795 frailty criteria were present. Individuals with two missing criteria were classified as frail if at least three frailty criteria were present and missing if otherwise.
The number of age-associated noncommunicable comorbidities (AANCC) was categorized in zero, one, two or at least three comorbidities. Conditions included were hypertension, diabetes mellitus, chronic kidney disease, chronic obstructive pulmonary disease, osteoporosis, myocardial infarction, angina pectoris, peripheral arterial disease, ischemic cerebrovascular disease and non-AIDS/AIDS associated cancer, according to previously reported criteria [19] et al. [22] https://links.lww.com/QAD/A795
Presence of depressive symptoms was assessed using the CES-D scale, excluding two questions that are used in the definition of frailty . Depressive symptoms were stratified in three categories, using both the classical cut-off value for major depression (score ≥16) and a more stringent cut-off (score ≥25) [23]
Statistical analysis
Statistical analysis was performed using STATA version 12. Characteristics and prevalence of prefrailty and frailty were compared between study groups using χ 2 , Student's t , and (Cuzick's extension of) Wilcoxon's rank-sum tests where appropriate. All reported P -values are two-sided.
After testing the proportionality of odds across categories nonfrail, prefrail and frail, using a likelihood ratio test, a multivariable ordered logistic regression model was constructed. The independent association between HIV infection and the three frailty categories (nonfrail, prefrail and frail) was investigated. The resulting odds ratio (OR) represents the ratio of the odds for being prefrail compared with nonfrail and for being frail compared with prefrail (the OR for being classified in a higher frailty category). All models were adjusted for age, sex and race/ethnicity. Behavioral factors (heavy alcohol intake, intravenous drug use, and smoking) and the presence of chronic viral hepatitis were explored as potential confounders. The presence of comorbidities, depression, metabolic syndrome, as well as markers of body composition (waist- and hip-circumference, BMI), inflammation and immune activation [high sensitivity C-reactive protein (hsCRP), D-dimer, soluble (s)CD163 and sCD14] were investigated as potentially lying on the causal pathway by analyzing whether their addition to the model attenuated the relation between HIV -status and (pre)frailty at least 10%. A bidirectional elimination approach was used, the entry criterion being a P -value <0.05 and the exit criterion a P -value >0.1. Statistical interactions between HIV -status and explored covariates were investigated as well.
HIV - and ART-associated factors were explored in a multivariable model including only HIV -infected individuals.
Results
Frailty assessment was performed in 594 HIV -infected and 550 uninfected individuals. Seventy-three HIV -infected and 29 uninfected individuals were excluded from this analysis, due to missing values for grip strength and walking speed assessment (n = 24 and n = 11) or incomplete questionnaire data (n = 49 and n = 18). Individuals with incomplete data were more often women (22.7 vs. 12.8%, P = 0.004) and slightly but not significantly younger (51.3 vs. 52.6 years, P = 0.55). Individuals without an available questionnaire were borderline significantly more often frail (13.3 vs. 6.7%) and prefrail (45.3 vs. 43.5%), P trend = 0.07.
The 521 HIV -infected and 513 uninfected individuals included in this analysis were comparable regarding age and sex. HIV -infected individuals were more often of black race/ethnicity (12.7 vs. 5.5%, P < 0.001), had slightly lower median BMI (24.2 vs. 24.5 kg/m2 , P = 0.02), higher median waist (93.5 vs. 90.7 cm, P = 0.01) and lower median hip-circumference (96.6 vs. 99.0 cm, P < 0.001) and were more often smokers (32.4 vs. 24.5%, P = 0.005). HIV -infected individuals were more often diagnosed with AANCC and more often had depression (Table 1 ). Median known duration of HIV infection was 12.0 years. About 94.4% of HIV -infected patients were currently on combination (c)ART, of whom 93.3% had undetectable HIV -1 RNA (<200 c/ml) in the year prior to enrollment (Table 2 ).
Table 1: Characteristics of HIV -infected and HIV -uninfected participants.
Table 2: HIV and ART-related characteristics of HIV -infected participants.
Frailty HIV -infected individuals were more likely to be frail (10.6 vs. 2.7%) and prefrail (50.7 vs. 36.3%) than HIV -uninfected individuals (P trend < 0.001); this was true for all age-categories (Fig. 1 ). All five individual frailty criteria were more often present in HIV -infected than in HIV -uninfected individuals (Fig. 2 ). We observed no significant differences in the distribution of criteria contributing to a prefrail or frail state in HIV -infected compared with uninfected individuals.
Fig. 1: Prevalence of frailty by age, in HIV -uninfected (HIV –) and HIV -infected (HIV +) individuals.
Fig. 2: Prevalence of frailty criteria.
In unadjusted ordered logistic regression, the OR for a higher frailty category for HIV -infected status was 2.60 [95% confidence interval (CI) 2.04–3.32, P < 0.001]. After adjusting for age, sex, black race/ethnicity, smoking and chronic hepatitis C virus (HCV) (co)infection in multivariable regression, HIV -infected status remained significantly associated with a higher OR (ORadjusted 2.39, 95%CI 1.85–3.09, P < 0.0001). Heavy alcohol intake [≥3/≥5 units/day (women/men)], intravenous drug use, and chronic hepatitis B virus (HBV) (co)infection were not significantly associated with a higher OR for frailty and prefrailty nor did they attenuate the OR of HIV -infected status.
The OR of HIV -infected status was slightly attenuated after depression and AANCC were introduced in the model (ORadjusted 2.16, 95%CI 1.66–2.83, P < 0.001). The metabolic syndrome was not independently associated with a higher frailty category, nor was a waist-circumference above the cut-off or a higher hip-circumference. However, a higher waist-to-hip ratio (WHR) was independently associated with a higher frailty category, and adjustment for the WHR significantly attenuated the OR of HIV -infected status (ORadjusted 1.93, 95%CI 1.46–2.55, P < 0.001). After introducing the WHR into the model, the number of AANCC was no longer statistically significantly associated with a higher frailty category, and therefore excluded from the model. Introduction of BMI attenuated the OR of being HIV -infected further (ORadjusted 1.74, 95%CI 1.31–2.32, P < 0.001). A statistically significant interaction was observed between BMI and HIV -status; compared with having a BMI of 20–25, 25–30 or at least 30 kg/m2 , a BMI less than 20 kg/m2 was associated with falling in a higher frailty category in HIV -infected (OR 6.14, 95%CI 3.10–12.18, P < 0.001), but not in HIV -uninfected individuals (OR 0.67, 95%CI 0.21–2.19, P = 0.51) (Pinteraction = 0.001).
sCD14, sCD163, D-dimer and hsCRP were not independently associated with a higher frailty category nor did they attenuate the OR of HIV -infected status significantly.
There were no significant interactions between HIV -infected status and age or any other covariate. The final model is shown in Table 3 .
Table 3: Multivariable ordinal logistic regression model, with prefrailty and frailty as outcome.
Sensitivity analyses
We repeated the model from Table 3 , excluding several subgroups of HIV -infected individuals, to explore whether the observed association between HIV and a higher frailty category was caused by a certain subgroup within the HIV -infected cohort. When those HIV -infected individuals who were ART experienced before start of cART were excluded, HIV -infected status remained significantly associated with a higher frailty category (ORadjusted 1.49, 95%CI 1.10–2.02, P = 0.009). The relation between WHR and frailty category remained statistically significant as well (OR 1.54, 95%CI 1.23–1.92, P < 0.001). Similarly, HIV -infected status remained statistically significantly associated with a higher frailty category when individuals with a history of AIDS, or with a nadir CD4+ T-cell count (CD4+ cell count) less than 100 cells/μl were excluded.
HIV -related determinants of frailty We explored HIV - and ART-related variables in the multivariable model including only HIV -infected individuals, adjusting for age, sex, black race/ethnicity, HCV coinfection, smoking and depression. The duration of having had a CD4+ cell count less than 200 (OR 1.14/year, 95%CI 1.00–1.30, P = 0.04) as well as the cumulative duration of exposure to protease inhibitors (OR 1.05/year, 95%CI 1.01–1.10, P = 0.01) were independently associated with a higher OR for a higher frailty category. Exposure to any other type of ART, including dideoxynucleoside analogues (D-drugs), stavudine in particular or mono- and dual ART were not independently associated with a higher OR for a higher frailty category, nor were the nadir or current CD4+ cell count, having a detectable viral load in the year prior to enrollment, the known duration of HIV -1-infection or a history of AIDS.
However, following adjustment for current BMI less than 20 kg/m2 and WHR as well as nadir BMI less than 20 kg/m2 , the ORs of both protease inhibitor exposure and time spent with a CD4+ cell count less than 200 were slightly attenuated and no longer statistically significant (OR for a CD4+ cell count <200 1.09/year, 95%CI 0.95–1.24, P = 0.21 and OR for the duration of protease inhibitor exposure 1.03/year, 95%CI 0.99–1.08, P = 0.14).
A current BMI less than 20 kg/m2 (OR 2.83, 95%CI 1.26–6.37, P = 0.01), a nadir BMI less than 20 kg/m2 (OR 2.51, 95%CI 1.46–4.31, P = 0.001) and a higher WHR (OR 1.79 per 0.1 higher, 95%CI 1.32–2.41, P < 0.001) were most strongly associated with a higher frailty category in the multivariable model.
Further adjustment for the number of diagnosed AANCC and hsCRP, D-dimer, sCD163 and sCD14 levels did not significantly affect these associations.
Discussion
We investigated the frailty phenotype in a population of middle-aged HIV -infected individuals, predominantly with undetectable HIV viral load on cART, and similar HIV -uninfected controls. Depression, low BMI and higher WHR were strongly associated with a higher frailty category, but none of the investigated factors could fully explain the observed association between HIV infection, prefrailty, and frailty . Markers of inflammation and immune activation were not associated with a higher frailty category. Currently having a low BMI (<20 kg/m2 ) was significantly associated with a higher OR for a higher frailty category in the HIV -infected, but not in the HIV -uninfected group. Within the HIV -infected group, longer time spent with a CD4+ cell count less than 200 and longer protease inhibitor exposure were associated with a higher OR for a higher frailty category, but this was no longer statistically significant after adjusting for low current and nadir BMI (<20 kg/m2 ) and WHR.
The higher prevalence of frailty and prefrailty in HIV -infected compared with uninfected individuals we observed confirms earlier studies [3–7] HIV -infected individuals were on long-term cART, enabling us to investigate (determinants of) frailty in treated HIV in more detail. Furthermore, inclusion of a highly comparable control group and collection of detailed information on demographics, behavior, comorbidities, body composition and HIV - and ART-history, enabled us to further explore the pathogenesis of frailty in HIV -infected individuals.
In the general as well as in the HIV -infected population markers of inflammation have been associated with frailty [2,11,14] HIV infection is associated with a pro-inflammatory state [24] frailty . We confirmed HIV -infected participants to have higher levels of markers of inflammation and immune activation, but these were not independently associated with frailty . However, our information was limited to the current levels of a selection of inflammatory markers. Interleukin-6, a marker previously associated with frailty [2,14] frailty .
Depression may be a consequence of as well as a contributor to frailty [25] frailty and depression, adjusting for depression is likely an overadjustment. Furthermore, even though depression was more common in the HIV -infected group, adjusting for its presence only moderately affected the association between HIV and (pre)frailty (<10%). This indicates that in our HIV -infected population the higher prevalence of frailty cannot be solely explained by the higher prevalence of depression.
Chronic HCV infection was independently associated with (pre)frailty . This is consistent with a study associating HCV infection with an increased risk for frailty incidence in HIV -infected and uninfected individuals [7] HIV infection. However, the number of HCV-infected study participants was small. Whether the effect of HCV infection differs according to HIV serostatus therefore deserves further study in a population with a higher prevalence of chronic HCV (co)infection.
Obesity, specifically abdominal obesity , has been recognized as risk factors for the development of frailty in the general population [15,16,26] [15] HIV -infected people, but without controls, showed an association between a high BMI, abdominal obesity and frailty [17] aging HIV -infected population abdominal obesity may partly be due to normal physiological aging and partly from body composition changes due to exposure to HIV and ART, including current regimens [18,27,28] frailty than abdominal obesity , as indicated by waist-circumference, or generalized obesity as indicated by the BMI. Furthermore, a higher WHR appeared to mediate the relation between HIV -infected status and frailty . This suggests that not only abdominal fat accumulation (of which high waist-circumference is an accepted surrogate), but also peripheral lipoatrophy (which may result in a reduced hip-circumference) may contribute to the development of frailty in the context of treated HIV infection. Alternatively, the lower hip-circumference may be related to muscle loss or sarcopenia, an important contributor to frailty [1]
In the HIV -infected but not uninfected participants, a current BMI less than 20 kg/m2 was strongly associated with a higher frailty category. Low BMI has been associated with frailty previously in the general population [15] HIV -patients [5,21] HIV -uninfected group may partially result from the relatively low proportion of individuals with an extremely low BMI in our cohort and partially from the different meaning of a low BMI in HIV -infected individuals. In the HIV -infected population a low BMI may be a persistent consequence of advanced HIV -disease and related weight loss, whereas in HIV -uninfected individuals a relatively low BMI may be an expression of a lean healthy build. An additional argument in support of this hypothesis is the observed association between nadir BMI and a higher frailty category in the HIV -infected group, even in individuals with a currently normal BMI (possibly having recovered after cART initiation).
Several studies have demonstrated associations between markers of current HIV -disease severity, such as clinical AIDS and immunodeficiency, and frailty [4,8] HIV -infected individuals were not currently on cART, and the majority had a CD4+ cell count above 500. Therefore, the statistical power to detect differences according to current HIV -disease status was limited. We did, however, observe an association between the duration of time spent with a CD4+ cell count less than 200, and a higher frailty category. This association was attenuated after we adjusted for covariates related to current and historically low BMI, possibly indicating that the observed association is rather a consequence of HIV -disease-related weight loss than of immunodeficiency itself. A previous study found a lower nadir CD4+ cell count in frail compared with nonfrail individuals [21] frailty in HIV -infected individuals.
This study is subject to several limitations. Due to the observational character, it is impossible to draw definite conclusions on the associations between use of specific types of ART and frailty ; we can only speculate and form hypotheses to be confirmed in longitudinal studies and randomized controlled trials. One previous study has reported frailty to be associated with current protease inhibitor exposure; however, this analysis was unadjusted [21] frailty by adding WHR to the model, may suggest some mechanistic role for protease inhibitor-associated body composition changes, either lipohypertrophy or lipoatrophy or both. We used adaptations of two of the Fried phenotype criteria; we classified slow walking speed and low grip strength by the per stratum lowest quintile of the study population rather than using the predefined cut-offs based on per stratum lowest quintiles in a population of elderly individuals from the original paper by Fried et al. [1] frailty according to our definition is not directly comparable to that used in some other cohorts; however, as our objective was to compare HIV -infected and HIV -uninfected individuals within the same cohort this does not affect our results. Populations of HIV -infected individuals generally are younger than the population the frailty phenotype has been developed in; the clinical consequences of frailty in this relatively young population are largely unknown. Few studies have prospectively investigated consequences of frailty in HIV infection, but these were conducted in specific populations, limiting the generalizability of their results. A study among intravenous drug users found frailty to be associated with mortality [6] frailty phenotype was associated with AIDS and mortality among ART-naive HIV -infected individuals [29] HIV -infected and HIV -uninfected veterans [30] frailty defined as the number of accumulated deficits predicted mortality and multimorbidity in HIV -infected individuals [31] h IV Cohort Study will provide more information on the prognostic value of the frailty phenotype in these middle-aged HIV -infected and HIV -uninfected individuals.
In conclusion, the higher prevalence of frailty and prefrailty in HIV -infected participants of the AGEh IV Cohort Study could not be explained by comorbid conditions, depression or levels of inflammation. Exposure to severe immunodeficiency and being underweight appear to play a role in the pathophysiology of frailty in the context of HIV . Therefore, frailty may in part be a long-term consequence of having experienced advanced HIV -disease. As this can be avoided by timely initiation of cART, one may expect individuals who are diagnosed and treated earlier in infection to be less affected by frailty . The higher waist- and lower hip-circumference in HIV -infected study participants may partly have resulted from body composition changes due to exposure to HIV or ART, also in more recently infected individuals and those treated with modern cART. The observed association between greater WHR and a higher frailty category, which in part explained the association between HIV -infection and frailty , thus suggests that body composition changes may also have contributed to the onset of frailty .
Acknowledgements
We thank Yolanda Ruijs-Tiggelman, Lia Veenenberg-Benschop, Tieme Woudstra, Sima Zaheri, and Mariska Hillebregt at the HIV Monitoring Foundation for their contributions to data management. We thank Aafien Henderiks and Hans-Erik Nobel for their advice on logistics and organization at the Academic Medical Center. We thank Rosan van Zoest, Barbara Elsenga, Aafien Henderiks, Jane Berkel, Sandra Moll, and Marjolein Martens for running the study programme and capturing our data with such care and passion.
We thank all HIV -physicians and HIV -nurses at the Academic Medical Center and all Public Health Service Amsterdam personnel for their efforts to include the HIV -infected and uninfected participants into the AGEh IV Cohort Study.
We thank all study participants without whom this research would not be possible.
AGEhIV Cohort Study Group members:
Scientific oversight and coordination: P. Reiss (principal investigator), F.W.N.M. Wit, M. van der Valk, J. Schouten, K.W. Kooij, R.A. van Zoest, B.C. Elsenga (Academic Medical Center (AMC), Department of Global Health and Amsterdam Institute for Global Health and Development (AIGHD)). M. Prins (co-principal investigator), I.G. Stolte, M. Martens, S. Moll, J. Berkel, L. Möller, G.R. Visser, C. Welling (Public Health Service Amsterdam, Infectious Diseases Research Cluster).
Data management: S. Zaheri, M.M.J. Hillebregt, L.A.J. Gras, Y.M.C. Ruijs, D.P. Benschop, P. Reiss (HIV Monitoring Foundation).
Central laboratory support: N.A. Kootstra, A.M. Harskamp-Holwerda, I. Maurer, M.M. Mangas Ruiz, A.F. Girigorie, E. van Leeuwen (AMC, Laboratory for Viral Immune Pathogenesis and Department of Experimental Immunology).
Project management and administrative support: F.R. Janssen, M. Heidenrijk, J.H.N. Schrijver, W. Zikkenheiner (AIGHD), M. Wezel, C.S.M. Jansen-Kok (AMC).
Participating HIV physicians and nurses: S.E. Geerlings, M.H. Godfried, A. Goorhuis, J.W.R. Hovius, J.T.M. van der Meer, F.J.B. Nellen, T. van der Poll, J.M. Prins, P. Reiss, M. van der Valk, W.J. Wiersinga, F.W.N.M. Wit; J. van Eden, A. Henderiks, A.M.H. van Hes, M. Mutschelknauss , H.E. Nobel, F.J.J. Pijnappel, A.M. Westerman (AMC, Division of Infectious Diseases).
Others collaborators: J. de Jong, P.G. Postema (AMC, Department of Cardiology); P.H.L.T. Bisschop, M.J.M. Serlie (AMC, Division of Endocrinology and Metabolism); P. Lips (Free University Medical Center Amsterdam); E. Dekker (AMC, Department of Gastroenterology); S.E.J.A. de Rooij (AMC, Division of Geriatric Medicine); J.M.R. Willemsen, L. Vogt (AMC, Division of Nephrology); J. Schouten, P. Portegies, B.A. Schmand, G.J. Geurtsen, J.A. ter Stege, M. Klein Twennaar (AMC, Department of Neurology); B.L.F. van Eck-Smit, M. de Jong (AMC, Department of Nuclear medicine); D.J. Richel (retired) (AMC, Division of Clinical Oncology); F.D. Verbraak, N. Demirkaya (AMC, Department of Ophthalmology); I. Visser, H.G. Ruhé (AMC, Department of Psychiatry); P.T. Nieuwkerk (AMC, Department of Medical Psychology); R.P. van Steenwijk, E. Dijkers (AMC, Department of Pulmonary medicine); C.B.L.M. Majoie, M.W.A. Caan, T. Su (AMC, Department of Radiology); H.W. van Lunsen, M.A.F. Nievaard (AMC, Department of Gynaecology); B.J.H. van den Born, E.S.G. Stroes, (AMC, Division of Vascular Medicine); W.M.C. Mulder (HIV Vereniging Nederland).
Authors’ contributions: P.R. conceived the study and together with F.W., J.S., I.S., M.P. and M.V. contributed to study design. K.K., J.S. and I.S. contributed to study coordination and data collection. K.K. and F.W. conducted the statistical analysis. K.K., F.W., J.S., M.V., J.F. and P.R. contributed to data interpretation. K.K. drafted the manuscript. All authors critically reviewed and revised the manuscript, and approved the final version submitted for publication.
This work was supported by The Netherlands Organisation for Health Research and Development (ZonMW) (grant nr 300020007) and AIDS Fonds (grant nr 2009063). Additional unrestricted scientific grants were received from Gilead Sciences; ViiV Healthcare, Janssen Pharmaceutica N.V.; Bristol-Myers Squibb; and Merck&Co.
None of these funding bodies had a role in the design or conduct of the study, the analysis and interpretation of the results, or the decision to publish.
Conflicts of interest
K.K. has received travel grants from Gilead Sciences and ViiV Healthcare, and was a speaker at an event sponsored by Gilead Sciences for which her institution received remuneration.
F.W. has received travel grants from Gilead Sciences, ViiV Healthcare, Boehringer Ingelheim, AbbVie and Bristol-Myers Squibb.
J.S. has received travel grants from Gilead Sciences, ViiV Healthcare and Boehringer Ingelheim.
M.V. has received consultancies fees from AbbVie, Bristol-Myers Squibb, Gilead Sciences, Johnson and Johnson; received nonfinancial support by MSD.
M.G. has received travel grants from Gilead Sciences, ViiV Healthcare and AbbVie and was a speaker at events sponsored by Bristol-Myers Squibb.
J.F. has received consultancy fees from Theratechnologies Inc., payment for lectures from ViiV Healthcare and Merck & Co and travel grants from ViiV Healthcare and Merck & Co.
P.R. through his institution has received independent scientific grant support from Gilead Sciences, Janssen Pharmaceuticals Inc, Merck & Co, Bristol-Myers Squibb and ViiV Healthcare; he has served on scientific advisory board for Gilead Sciences; he serves on data safety monitoring committee for Janssen Pharmaceuticals Inc; chaired a scientific symposium by ViiV Healthcare, for which his institution has received remuneration.
For the remaining authors no conflicts of interest were declared
This work has been presented in part at the 12th International Symposium on Neurobiology and Neuroendocrinology of Aging , Bregenz, Austria, August 2014 and the 8th Netherlands Conference on HIV Pathogenesis, Epidemiology, Prevention and Treatment, Amsterdam, The Netherlands, November 2014.
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