So-Armah et al. BMC Gastroenterology (2020) 20:1 https://doi.org/10.1186/s12876-019-1136-4 RESEARCH ARTICLE Open Access Liver fibrosis and accelerated immune dysfunction (immunosenescence) among HIV-infected Russians with heavy alcohol consumption - an observational cross- sectional study Kaku So-Armah1* , Matthew Freiberg2*, Debbie Cheng3, Joseph K. Lim4, Natalia Gnatienko5, Gregory Patts6, Margaret Doyle7, Daniel Fuster8, Dmitry Lioznov9, Evgeny Krupitsky10 and Jeffrey Samet11 Abstract Background: The multifactorial mechanisms driving negative health outcomes among risky drinkers with HIV may include immunosenescence. Immunosenescence, aging of the immune system, may be accentuated in HIV and leads to poor outcomes. The liver regulates innate immunity and adaptive immune tolerance. HIV-infected people have high prevalence of liver-related comorbidities. We hypothesize that advanced liver fibrosis/cirrhosis is associated with alterations in T-cell subsets consistent with immunosenescence. Methods: ART-naïve people with HIV with a recent history of heavy drinking were recruited into a clinical trial of zinc supplementation. Flow cytometry was used to characterize T-cell subsets. The two primary dependent variables were CD8+ and CD4+ T-cells expressing CD28-CD57+ (senescent cell phenotype). Secondary dependent variables were CD8+ and CD4+ T-cells expressing CD45RO + CD45RA- (memory phenotype), CD45RO-CD45RA+ (naïve phenotype), and the naïve phenotype to memory phenotype T-cell ratio (lower ratios associated with immunosenescence). Advanced liver fibrosis/cirrhosis was defined as FIB-4 > 3.25, APRI≥1.5, or Fibroscan measurement ≥10.5 kPa. Analyses were conducted using multiple linear regression adjusted for potential confounders. Results: Mean age was 34 years; 25% female; 88% hepatitis C. Those with advanced liver fibrosis/cirrhosis (N = 25) had higher HIV-1 RNA and more hepatitis C. Advanced liver fibrosis/cirrhosis was not significantly associated with primary or secondary outcomes in adjusted analyses. Conclusions: Advanced liver fibrosis/cirrhosis was not significantly associated with these senescent T-cell phenotypes in this exploratory study of recent drinkers with HIV. Future studies should assess whether liver fibrosis among those with HIV viral suppression and more advanced, longstanding liver disease is associated with changes in these and other potentially senescent T-cell subsets. Keywords: HIV, Liver fibrosis, Immune senescence, Russia, Alcohol * Correspondence: kaku@bu.edu; matthew.s.freiberg@vanderbilt.edu 1 Department of Medicine, Boston University School of Medicine, 801 Massachusetts Avenue, Crosstown Building, 2nd Floor, Boston, MA 02118, USA 2 Department of Medicine, Vanderbilt University School of Medicine; Nashville Veterans Affairs Medical Center, Tennessee Valley Healthcare System, Nashville, TN, USA Full list of author information is available at the end of the article © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), 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 (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. So-Armah et al. BMC Gastroenterology (2020) 20:1 Page 2 of 8 Background ARCH and ZINC who had available liver fibrosis data Heavy alcohol use is more prevalent among people living and T-cell phenotypes at baseline (N = 130). with human immunodeficiency virus/acquired immuno- deficiency syndrome (PLWHA) than among uninfected Main independent variable people [1] and is associated with liver disease and multiple The main exposure variable was advanced liver fibrosis/ negative health outcomes [2]. Alcohol related liver injury cirrhosis defined as having any of the following: FIB-4 among PLWHA is compounded by high prevalence of score > 3.25, APRI score ≥ 1.5 or Fibroscan result ≥10.5 liver-related comorbidities occurring among PLWHA kPa [10, 11]. The FIB-4 score is calculated as the prod- such as viral hepatitis. The multifactorial mechanisms uct of age (years) and aspartate aminotransferase (AST, driving negative health outcomes among PLWHA who U/L) divided by the product of platelet count (109/L) are risky drinkers are still being elucidated [3–7]. and the square root of alanine aminotransferase (ALT, The liver plays a critical role in metabolic detoxifica- U/L). The resulting score was categorized as ≤3.25 (no tion and immune regulation [8]. It receives blood from advanced fibrosis/cirrhosis) or > 3.25 (advanced fibrosis/ the hepatic arteries and the portal venous system. Blood cirrhosis). The APRI score is calculated as AST divided from the portal venous system contains nutrients, meta- by platelet count and categorized such that scores bolic products as well as toxins and antigens. Thus, the greater than or equal to 1.5 reflect advanced fibrosis/cir- liver must balance immune activation from antigen ex- rhosis. By design in the ZINC HIV trial, participants posure with preventing damage to hepatocytes and sur- with FIB-4 in the indeterminate range (i.e., 1.45 to 3.25) rounding tissues from the antigenic response. received Fibroscan imaging. Fibroscan enables ultra- We hypothesize that fibrotic or cirrhotic livers of sound measurement of liver stiffness, which correlates PLWHA have diminished capability to maintain this bal- with liver fibrosis. These data were used to confirm ad- ance, resulting in chronic immune activation and ultim- equate separation of liver fibrosis exposure groups ately, premature immune exhaustion (immunosenescence). among the subset of participants on whom Fibroscan The objective of this study is therefore to explore the asso- imaging was done. ciation between advanced liver fibrosis/cirrhosis and alter- ations in T-cell subsets among ART-naïve HIV-infected Outcome variable Russians with heavy alcohol consumption. We analyzed CD8+ and CD4+ T-cell phenotypes con- sistent with immunosenescence, the aging related de- Methods cline of adaptive immune function. Immunosenescence Participants is characterized by accumulation of CD28-CD57+ T- Study participants were from the Russia ARCH (Alcohol cells, decrease in naïve lymphocytes, and increase in Research Collaboration on HIV/AIDS) and ZINC HIV memory lymphocytes that are oligoclonally expanded, (Zinc for INflammation and Chronic disease in HIV) resistant to apoptosis and functionally incompetent [12, studies. Russia ARCH is a longitudinal cohort of 13]. The two primary outcomes were the percentage of PLWHA with varying levels of alcohol consumption. CD8+ and CD4+ T-cells expressing the CD28-CD57+ ZINC HIV is a randomized double-blinded placebo con- phenotype. T-cells that lose CD28 (CD28-) or gain trolled clinical trial (ClinicalTrials.gov identifier: CD57 (CD57+) expression have undergone chronic anti- NCT01614626). The aim of ZINC HIV is to determine genic stimulation, multiple rounds of antigen-specific the efficacy of long-term zinc supplementation com- replication, and have decreased ability to replicate fur- pared to placebo among PLWHA on outcomes related ther. These T-cell subsets are cytotoxic or immunosup- to mortality risk, cardiovascular disease risk, microbial pressive, and poorly regulated [14]. The CD28-CD57+ translocation, inflammation and HIV disease progression phenotype is associated with alcoholism [15], intracellu- [9]. Participants in the ZINC HIV trial were antiretro- lar infections like HIV, [16, 17] and diseases of aging like viral therapy naïve at enrollment and reported heavy cancer [14]. Six secondary outcomes were evaluated: drinking within the 30 days prior to enrollment. Heavy CD8+ and CD4+ T-cells expressing CD45RO + drinking was defined according to National Institutes on CD45RA- (memory phenotype), CD45RO-CD45RA+ Alcohol Abuse and Alcoholism (NIAAA) risky drinking (naïve phenotype), or naïve:memory T-cell ratio (lower criteria as > 4 standard drinks in a day (or > 14 standard ratios associated with immunosenescence). Skewed out- drinks/week) for men and > 3/ day (or > 7/week) for comes were natural log-transformed to better approxi- women. The first 250 participants in Russia ARCH had mate a normal distribution. T-cell phenotyping by flow cytometry. All ZINC partici- Flow cytometry and T-cell quantification have been pants had liver enzymes and platelets measured and previously described [18]. Briefly, heparin anticoagulated Fibroscan imaging performed. The current study focuses whole blood was processed within 4 h of collection at on the overlapping subset of participants in both Russia the St. Petersburg Pasteur Institute Central Clinical So-Armah et al. BMC Gastroenterology (2020) 20:1 Page 3 of 8 Diagnostic Laboratory. All reagents were from BD Bio- Confirmatory analyses were performed using median re- sciences. Whole blood was labeled with FITC anti-CD8, gression models, which are more robust to departures PE anti-CD45RO, PeCy5 anti-CD45RA and APC-H7 from normality and the presence of outliers than linear anti-CD4, or FITC anti-CD8, PE anti-CD57, PeCy5 anti- regression models [23, 24]. Additional exploratory ana- CD28 and APC-H7 anti CD4 or appropriate isotypes. lyses were conducted evaluating FIB-4 as a continuous Samples were incubated, red blood cells were lysed, cells variable. As an initial step, generalized additive models were washed, and samples were fixed in paraformalde- (GAMs) were used to assess the form of the relationship hyde. Flow cytometry was performed on a BD FACS between FIB-4 and outcomes and whether the linearity Cantos that has been calibrated daily and compensation assumption was appropriate. Based on the GAMs, linear was set using single color controls. Flow data was ana- or piecewise linear regression models were then used to lyzed with BD FACS DIVA software. Lymphocytes were evaluate whether FIB-4 was associated with CD4 + gated based on their forward and side scatter. CD4+ and CD28-CD57+ and CD8 + CD28-CD57+ T-cell subsets. CD8+ cells are reported as a percent of gated lympho- For example, in the analyses of the association between cytes. All other subsets are a percent of either CD4+ or FIB-4 and CD8 + CD28-CD57+ T-cells, the GAM sug- CD8+ cells. gested separate slopes at a FIB-4 value of approximately 2.7. We therefore subsequently fit a piecewise linear re- Covariates gression model estimating separate slopes for those with This study used covariate data obtained from the follow- FIB-4 less than or equal to 2.7 versus those above this ing instruments: 30 Day Timeline Follow Back for alco- threshold and tested each slope separately. Analyses hol use, [19] Fagerström Test for Nicotine Dependence, were performed with SAS 9.3 statistical software. The [20] survey of co-morbidities adapted from the Veterans datasets used and/or analyzed during the current study Aging Cohort Study patient questionnaire [21] and HIV are available from the corresponding author on reason- Risk Behavior Survey (RBS) [22]. Past 30-day heavy able request. drinking was based on Timeline Followback for alcohol use and categorized per NIAAA risky drinking criteria. HIV RNA was quantified using a polymerase chain Results reaction-based diagnostic (AmpliSens® HIVMonitor- Among the 130 participants included in the current FRT, Amplisens, Moscow, Russia). Hepatitis C status study, 25 (19%) were categorized as having evidence of was based on an antibody test. Past 30-day injection advanced liver fibrosis/cirrhosis (Table 1). The partici- drug use, current smoking and prior exposure to poten- pants were all Caucasian, predominantly younger men tially chronic infections (hepatitis B, tuberculosis, herpes (mean age 34 years) with high prevalence of heavy drink- zoster) were based on self-report. Covariates were poten- ing (90%), hepatitis C antibody positivity (85%) and tial confounders selected a priori based on the literature mean time since HIV diagnosis of 7 years. Mean log10 and clinical knowledge. HIV-1 RNA copies/mL was 4.5. Those with advanced liver fibrosis/cirrhosis had more prevalent hepatitis C Statistical analysis co-infection. Among those with Fibroscan data, median For descriptive purposes, we compared participant char- Fibroscan scores were higher among those with evidence acteristics at baseline by FIB-4 category (no/moderate fi- of liver fibrosis compared to those without (8.0 vs. 6.2) brosis vs. advanced fibrosis/cirrhosis) using t-tests, (p < 0.05 for comparisons by liver fibrosis category). Wilcoxon rank sum, chi-square or Fisher’s exact tests as In unadjusted analyses, the proportions of senescent, appropriate. Primary and secondary outcomes were memory and naïve CD8+ and CD4+ T-cells were similar compared between the FIB-4 categories of interest using by liver fibrosis category (Tables 2, 3, 4, and 5; p > 0.05). multiple linear regression adjusted for potential con- All associations remained non-significant after adjust- founders. Regression models were adjusted for age, sex, ment for possible confounders (Tables 4 and 5). In HIV-1 RNA, injection drug use in the prior 30 days, adjusted analyses of the two primary outcomes, the pro- current smoking, time since HIV diagnosis, hepatitis C, portion of CD8 + CD28-CD57+ T-cells was lower among and exposure to chronic infections (hepatitis B, tubercu- those with advanced liver fibrosis/cirrhosis, but the dif- losis, herpes zoster). CD8+ and CD4+ naïve to memory ference was not statistically significant (adjusted mean ratios and CD4 + CD28-CD57+ T-cell subsets were nat- difference [95% confidence interval, CI]: − 0.36 [− 7.35, ural log-transformed to improve normality and back- 6.63]. CD4 + CD28-CD57+ T-cells proportion was simi- transformed for ease of interpretation. For back trans- lar for the two groups (adjusted ratio of means [95% CI]: formed T-cell subsets, measures of effect are reported as 1.00 [0.48, 2.07]). For this and other back transformed a ratio of means for comparisons between those with ad- T-cell subsets, the ratio of means is interpreted as fol- vanced fibrosis/cirrhosis compared to those without. lows: mean proportion of T-cell subset in the advanced So-Armah et al. BMC Gastroenterology (2020) 20:1 Page 4 of 8 Table 1 Baseline characteristics of study population by liver fibrosis status among ART-naïve people living with HIV/AIDS (PLWHA) with recent heavy alcohol use Overall No advanced Advanced p-value fibrosis/cirrhosis fibrosis/cirrhosis N 130 105 25 – Mean age (SD)/years 33.5 (6.0) 33.6 (6.2) 33.1 (4.9) 0.74 Female sex 33 (25%) 26 (25%) 7 (28%) 0.74 Heavy drinkinga 118 (91%) 95 (90%) 23 (92%) 0.81 Injected drugs use (past 30 days) 46 (35%) 38 (36%) 8 (32%) 0.69 Current regular smoker 111 (85%) 87 (83%) 24 (96%) 0.09 Self-reported history of hepatitis B 43 (33%) 34 (32%) 9 (36%) 0.73 Self-reported history of herpes zoster 28 (22%) 20 (19%) 8 (32%) 0.16 Self-reported history of tuberculosis 16 (12%) 11 (11%) 5 (20%) 0.19 Hepatitis C antibody positive 114 (88%) 89 (85%) 25 (100%) 0.04 Mean years since first positive HIV test (SD) 6.8 (5.0) 6.7 (4.9) 7.3 (5.4) 0.54 Mean platelet count (SD) 211 (74) 226 (65) 148 (75) < 0.01 Mean ALT (SD)/Units per liter 52 (74) 38 (40) 109 (136) < 0.01 Mean AST (SD)/Units per liter 65 (65) 45 (22) 148 (107) < 0.01 Median FIB-4 (25th, 75th) 1.3 [0.9, 2.1] 1.1 [0.9, 1.5] 3.4 [2.3, 6.6] < 0.01 Median APRI (25th, 75th) 0.6 [0.4, 1.0] 0.5 [0.3, 0.8] 2.4 [1.5, 4.2] < 0.01 Median Fibroscan (25th, 75th); N = 33 (9 determined to have advanced fibrosis/cirrhosis) 6.4 [5.3, 8.4] 6.2 [5.0, 7.2] 8.0 [7.6, 13.6] < 0.01 Mean Log10 HVL (SD) /copies/mL 4.5 (1.1) 4.5 (1.0) 4.6 (1.3) 0.85 a heavy drinking (> 4 standard drinks in a day (or > 14 standard drinks/week) for men and > 3/ day (or > 7/week) for women) Data are N(%) unless otherwise specified. liver fibrosis/cirrhosis group compared to the group CD8 + CD28-CD57+ T-cells. Although the observed without advanced liver fibrosis/cirrhosis. slope for FIB-4 was positive at lower levels of FIB-4 and negative for higher levels of FIB-4, neither reached stat- istical significance (Table 6). For the outcome CD4 + In secondary analyses, the ratio of naïve:memory CD28-CD57+ T-cells, a linear model was fit based on CD8+ T-cells was higher for those with advanced the GAM, and no significant association was observed liver fibrosis/cirrhosis (adjusted ratio of means [95% for FIB-4. CI]: 1.32 [0.88, 1.97]). The ratio of naïve:memory CD4+ T-cells was similar for the two groups (ad- justed ratio of means [95% CI]: 1.00 [0.66, 1.52]). Discussion Confirmatory analysis with median regression for In this exploratory study of ART-naïve PLWHA with CD4 + CD28-CD57+ T-cells yielded results consistent heavy drinking, those with advanced liver fibrosis/cirrho- with the primary analyses. sis appeared to have lower prevalence of CD8+ T-cell In exploratory analyses of FIB-4 as a continuous vari- phenotypes suggestive of immunosenescence (i.e. lower able, a piecewise linear model was fit for the outcome proportions CD8 + CD28-CD57+, higher naïve:memory Table 2 Distribution of CD8+ T-cell subsets reflecting immunosenesence by liver fibrosis status among art-naïve PLWHA with recent heavy alcohol use T-cell subsets as a proportion of CD8+ T- Mean (SD) unless otherwise stated p-value cells Overall No advanced fibrosis/cirrhosis Advanced fibrosis/cirrhosis CD8 + CD28-CD57+ 35.6 (15.7) 35.4 (15.5) 36.1 (16.7) 0.85 CD8+ memory 34.4 (13.8) 34.9 (13.7) 32.3 (14.4) 0.40 CD8+ naive 38.7 (15.0) 39.3 (14.0) 36.4 (18.6) 0.44 CD8 naïve:memory ratio median (25th, 75th) 1.56 (0.99, 2.40) 1.54 (0.95, 2.30) 1.82 (1.17, 3.00) 0.26 So-Armah et al. BMC Gastroenterology (2020) 20:1 Page 5 of 8 Table 3 Distribution of CD4+ T-cell subsets reflecting immunosenesence by liver fibrosis status among art-naïve PLWHA with recent heavy alcohol use T-cell subsets as a proportion Mean (SD) unless otherwise stated p-value of CD4+ T-cells Overall No advanced fibrosis/cirrhosis Advanced fibrosis/cirrhosis CD4 + CD28-CD57+ 2.25 (0.40, 6.40) 2.40 (0.40, 6.10) 1.40 (0.40, 6.60) 0.59 (25th, 75th) CD4+ memory 54.3 (16.3) 53.7 (15.1) 56.6 (20.7) 0.42 CD4+ naive 38.7 (15.0) 39.3 (14.0) 36.4 (18.6) 0.39 CD4+ naïve:memory ratiomedian 0.70 (0.48, 1.07) 0.75 (0.48, 1.13) 0.59 (0.47, 1.06) 0.81 (25th, 75th) CD8+ T-cell ratio). However, these differences did not Markers of immunosenescence in that study were in- reach statistical significance. creased in cirrhosis patients compared to healthy con- To our knowledge, no published studies have assessed trols (i.e., higher proportion of CD8 + CD45RO + CD57+ these T-cell subpopulations by liver fibrosis status T-cells) and in cirrhotic patients with ascites compared among HIV infected people. A prior study described to healthy controls (i.e., lower proportion of CD28+ T- similar memory (CD45RO+) T-cell proportions among cells) [25]. Others have reported evidence of immunose- HIV uninfected patients with cirrhosis compared to nescence (i.e., lower CD8 + CD28+ T-cell proportions) healthy controls, which is consistent with our results. among HIV uninfected people with cirrhosis who Table 4 a) Unadjusted and b)adjusted association between liver fibrosis status and CD8+ T-cell subsets reflecting immunosenesence among art-naïve PLWHA with recent heavy alcohol use a) CD8+ CD28- CD57+ CD8+ Memory CD8+ Naïve (as % of CD8+) CD8+ Naïve:Memory ratio (as % of CD8+) (as % of CD8+) Unadjusted Mean P-value Unadjusted Mean P-value Unadjusted Mean P-value Unadjusted Ratio of P-value Difference (95% CI) Difference (95% CI) Difference (95% CI) Meansa (95% CI) No advanced 1 (referent group) 1 (referent group) 1 (referent group) 1 (referent group) fibrosis/ cirrhosis Advanced 0.67 (−6.15, 7.48) 0.85 −2.61 (−8.59, 3.36) 0.39 2.48 (−3.78, 8.73) 0.44 1.24 (0.84, 1.90) 0.25 fibrosis/ cirrhosis b) CD8+ CD28- CD57+ (as CD8+ Memory (as %CD8+) CD8+ Naïve (as%CD8+) CD8+ Naïve:Memory ratio %CD8+) Adjusted Mean P-value Adjusted Mean P-value Adjusted Mean P-value Adjusted Mean P-value Difference (95% CI) Difference (95% CI) Difference (95% CI) Difference (95% CI) No advanced 1 (referent group) 1 (referent group) 1 (referent group) 1 (referent group) fibrosis/ cirrhosis Advanced fibrosis/ −0.36 (−7.35, 6.63) 0.92 −3.16 (−8.90, 2.57) 0.28 3.07 (−2.97, 9.11) 0.32 1.32 (0.88, 1.97) 0.18 cirrhosis (adjusted) Age/years −0.07 (− 0.39, 0.53) 0.77 − 0.15 (− 0.53, 0.23) 0.45 0.01 (− 0.39, 0.41) 0.96 1.00 (0.97, 1.03) 0.96 Female sex −0.53 (−6.93, 5.87) 0.87 −3.12 (− 8.37, 2.13) 0.24 2.76 (−2.76, 8.29) 0.33 1.23 (0.85, 1.78) 0.27 Log10(HIV-1 RNA copies/ −0.18 (−2.70, 2.34) 0.89 2.94 (0.87, 5.01) < 0.01 −2.38 (−4.55, − 0.20) 0.03 0.91 (0.79, 1.05) 0.20 mL) Heavy drinking −0.15 (−9.45, 9.16) 0.98 −6.68 (−14.32, 0.95) 0.09 8.27 (0.23, 16.30) 0.04 1.47 (0.86, 2.51) 0.16 Injection drug use 3.26 (−3.08, 9.60) 0.31 −1.10 (−6.31, 4.10) 0.68 2.95 (−2.53, 8.42) 0.29 1.26 (0.87, 1.81) 0.22 Current smoking −0.17 (−8.51, 8.18) 0.97 5.31 (−1.53, 12.16) 0.13 −5.58 (− 12.79, 1.63) 0.13 0.74 (0.46, 1.20) 0.23 Years since HIV −0.16 (− 0.72, 0.41) 0.59 − 0.24 (− 0.70, 0.22) 0.31 0.65 (0.16, 1.14) < 0.01 1.03 (1.00, 1.07) 0.07 diagnosis Hepatitis C 6.67 (−2.29, 15.63) 0.14 1.5 (−5.84, 8.86) 0.69 −2.93 (−10.7, 4.81) 0.46 0.89 (0.53, 1.48) 0.65 Hepatitis B −3.41 (−9.68, 2.86) 0.29 4.72 (−0.42, 9.87) 0.07 −5.55 (−11.0, − 0.13) 0.04 0.67 (0.47, 0.97) 0.03 Shingles 1.70 (−5.02, 8.43) 0.62 3.04 (−2.48, 8.55) 0.28 −1.64 (−7.44, 4.17) 0.58 0.85 (0.58, 1.25) 0.41 Tuberculosis 2.43 (−6.07, 10.93) 0.58 −8.60 (−15.57, − 1.62) 0.02 6.07 (− 1.27, 13.41) 0.11 1.46 (0.89, 2.37) 0.13 a Result after back transformation from natural log scale So-Armah et al. BMC Gastroenterology (2020) 20:1 Page 6 of 8 Table 5 a) Unadjusted and b) adjusted association between liver fibrosis status and CD4+ T-cell subsets reflecting immunosenesence among art-naïve PLWHA with recent heavy alcohol use a) CD4+ CD28- CD57+ CD4+ Memory CD4+ Naïve CD4+ Naïve:Memory ratio (as % of CD4+) (as % of CD4+) (as % of CD4+) Unadjusted Mean P-value Unadjusted Mean P-value Unadjusted Mean P-value Unadjusted Mean P-value Differencea (95% CI) Difference (95% CI) Difference (95% CI) Differencea (95% CI) No advanced 1 (referent group) 1 (referent group) 1 (referent group) 1 (referent group) fibrosis/ cirrhosis Advanced fibrosis/ 0.81 (0.39, 1.70) 0.58 2.95 (−4.09, 10.0) 0.41 −3.83 (−9.28, 1.61) 0.17 0.95 (0.63, 1.44) 0.81 cirrhosis b) CD4+ CD28- CD57+ CD4+ Memory CD4+ Naïve CD4+ Naïve:Memory ratio/ (as % of CD4+) (as % of CD4+) (as % of CD4+) CD4+ Adjusted Mean P-value Adjusted Mean P-value Adjusted Mean P-value Adjusted Mean P-value Differencea (95% CI) Difference Difference (95% CI) Differencea (95% CI) (95% CI) No advanced 1 (referent group) 1 (referent group) 1 (referent group) 1 (referent group) fibrosis/ cirrhosis Advanced fibrosis/ 1.00 (0.48, 2.07) 1.00 2.15 (−4.89, 9.19) 0.55 −3.38 (−8.67, 1.91) 0.21 1.00 (0.66, 1.52) 0.99 cirrhosis Age/years 1.05 (1.00, 1.10) 0.07 0.32 (−0.15, 0.79) 0.18 −0.37 (− 0.79, 0.04) 0.08 0.98 (0.96, 1.01) 0.22 Female sex 0.89 (0.46, 1.73) 0.73 −2.42 (−8.86, 4.02) 0.46 2.97 (− 2.62, 8.57) 0.30 1.14 (0.78, 1.67) 0.49 Log10(HIV-1 RNA) 0.91 (0.70, 1.18) 0.49 0.79 (−1.75, 3.33) 0.54 −0.59 (− 2.58, 1.41) 0.56 1.00 (0.86, 1.17) 0.96 Heavy drinking 0.91 (0.34, 2.39) 0.84 −4.87 (−14.23, 4.50) 0.31 5.36 (−2.71, 13.43) 0.19 1.27 (0.73, 2.21) 0.40 Injection drug use 1.09 (0.56, 2.11) 0.80 −3.11 (−9.50, 3.27) 0.34 3.53 (−1.9, 8.96) 0.20 1.16 (0.80, 1.69) 0.43 Current smoking 0.80 (0.34, 1.91) 0.62 1.75 (−6.65, 10.15) 0.68 −2.3 (−9.75, 5.16) 0.55 0.92 (0.56, 1.51) 0.73 Years since HIV 0.98 (0.93, 1.04) 0.55 −0.06 (− 0.63, 0.51) 0.83 0.11 (− 0.38, 0.6) 0.66 1.00 (0.97, 1.04) 0.83 diagnosis Hepatitis C 0.37 (0.14, 0.93) 0.04 −2.57 (−11.59, 6.45) 0.58 3.49 (−4.52, 11.5) 0.39 1.14 (0.67, 1.94) 0.63 Hepatitis B 0.62 (0.32, 1.19) 0.15 5.69 (−0.62, 12.01) 0.08 −5.04 (−10.39, 0.3) 0.06 0.74 (0.51, 1.07) 0.11 Shingles 1.41 (0.70, 2.84) 0.34 6.13 (−0.63, 12.90) 0.08 −5.51 (−11.32, 0.31) 0.06 0.71 (0.47, 1.05) 0.09 Tuberculosis 0.93 (0.38, 2.24) 0.86 1.45 (−7.10, 10.01) 0.74 −3.64 (−10.84, 3.56) 0.32 0.82 (0.50, 1.37) 0.46 a Represents the ratio of means after back transformation from natural log scale consumed > 90 g/day of ethanol in prior 5 years com- liver. Many of the participants in the prior studies where pared to healthy controls consuming 10-15 g/day ethanol differences in T-cell subsets were observed had biopsy [26]. These findings may differ from ours because: 1) confirmed cirrhosis and/or ascites. It is possible that a our study was conducted among PLWHA; 2) we investi- much greater degree and chronicity of liver fibrosis or gated different subsets of T-cells representing immuno- cirrhosis than was present in our cohort, is required be- senescence; and 3) we had few people with cirrhosis and fore differences demonstrating senescence in T-cell sub- did not have data about ascites. sets will be observed. If this were to be true, it would HIV and viral hepatitis have each been shown to be asso- suggest that subclinical measures of liver fibrosis as used ciated with markers of cellular immunosenescence. Since all in this study may not be able to identify if the liver is participants in the current study were ART-naïve PLWHA losing its ability to regulate immune activation and and most were hepatitis C co-infected, it is plausible that the maintain immune tolerance. Alternatively, it could also effects of HIV and hepatitis C infection on the T-cell subsets suggest that a longer duration of liver fibrosis may be re- we assessed may be masking a potential effect of liver fibro- quired before subclinical measures of liver fibrosis can sis on these cell populations. Evidence for this is provided by provide information about senescence. the associations we observed linking HIV-1 RNA and hepa- Our exploratory analyses suggest the importance of titis C co-infection with CD8+ and CD4+ T-cell subsets re- considering non-linear associations between liver disease spectively. Future studies should repeat these analyses and T-cell subsets consistent with immunosenescence. among HIV infected people with suppressed viremia. While FIB-4 of 3.25 is an important clinical threshold Another potential reason these results do not confirm for advanced fibrosis/cirrhosis, there is ambiguity in our hypothesis involves the regenerative capability of the interpreting FIB-4 between 1.45 and 3.25. Our analyses So-Armah et al. BMC Gastroenterology (2020) 20:1 Page 7 of 8 Table 6 Association between liver fibrosis status (continuous fibrosis was only available for a subset of our partici- measure) and a) CD8+ T-cell b) CD4+ T-cell subsets reflecting pants. In this subset however, Fibroscan data suggest we immunosenesence among art-naïve PLWHA with recent heavy achieved good separation of the liver fibrosis exposure alcohol use groups we defined. Several of our covariates were self- a) CD8+ CD28- CD57+ (as % of CD8+) reported, without information on duration of co-morbid Adjusted Mean Difference (95% CI) P-value conditions, and subject to reporting bias. However, the Log(FIB-4) ≤ 1 6.2 (− 0.70, 13.18) 0.08 several potential confounders (e.g. alcohol, HIV viremia, Log(FIB-4) > 1 −5.54 (− 13.6, 2.47) 0.17 hepatitis C status) were measured using validated instru- ments and/or objective laboratory data. This study was Age/years −0.06 (− 0.58, 0.45) 0.80 likely underpowered to detect the associations of interest Female sex −0.83 (−7.68, 6.01) 0.81 and as such should be considered exploratory and hypoth- Log10(HIV-1 RNA) −0.45 (− 3.15, 2.25) 0.74 esis generating. Post hoc power calculations based on the Heavy drinking 1.24 (−8.99, 11.47) 0.81 observed standard deviations in each group indicate we Injection drug use 3.54 (−3.12, 10.20) 0.30 had approximately 80% power to detect a minimum dif- Current smoking −0.55 (−9.53, 8.43) 0.90 ference in CD8 + CD28-CD57+ T-cell proportions of 10, a substantially larger mean difference than the 0.7 observed Years since HIV diagnosis −0.08 (− 0.68, 0.52) 0.79 in this study. As with all observational studies, there is a Hepatitis C 4.32 (−5.33, 13.97) 0.38 possibility of unmeasured confounding. Hepatitis B −3.69 (− 10.34, 2.97) 0.27 Shingles 0.32 (−6.82, 7.46) 0.93 Conclusions Tuberculosis 3.11 (−5.82, 12.04) 0.49 We did not detect a significant association between ad- vanced liver fibrosis/cirrhosis and the senescent T-cell b) CD4+ CD28- CD57+ (as% of CD4+) phenotypes assessed in this sample of ART-naïve HIV- Adjusted Mean Difference (95% CI) P-value infected Russians with heavy alcohol consumption. Log(FIB-4) 0.99 (0.64, 1.54) 0.97 Acknowledgements Not applicable. Age/years 1.05 (0.99, 1.10) 0.09 Female sex 0.83 (0.41, 1.71) 0.62 Authors’ contributions Authors made substantial contributions to the conception OR design of the Log10(HIV-1 RNA) 0.90 (0.68, 1.20) 0.48 work (KS, MF, JS); OR the acquisition (KS, MF, DC, GP, DL, EK, JS), analysis (DC, Heavy drinking 1.07 (0.37, 3.14) 0.90 GP, MD) OR interpretation of data; OR have drafted the work or substantively revised it (all authors) AND approved the submitted version (and any Injection drug use 1.09 (0.54, 2.19) 0.81 substantially modified version that involves the author’s contribution to the Current smoking 0.89 (0.35, 2.27) 0.80 study) (all authors); AND agreed both to be personally accountable for the author’s own contributions and to ensure that questions related to the Years since HIV diagnosis 0.99 (0.93, 1.05) 0.68 accuracy or integrity of any part of the work, even ones in which the author Hepatitis C 0.34 (0.13, 0.93) 0.04 was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature (all authors). All authors have read Hepatitis B 0.62 (0.31, 1.24) 0.18 and approved the manuscript in its current state. Shingles 1.34 (0.63, 2.81) 0.44 Funding Tuberculosis 0.92 (0.36, 2.36) 0.87 This work was supported by the National Institute on Alcohol Abuse and Alcoholism at the National Institutes of Health: Grant numbers: U01AA020780, U24AA020778, U24AA020779, U01AA021989-03S1. KS was supported by grant K01 HL1314701 from the National Heart, Lung, and Blood suggest that the relationship between FIB-4 and CD8+ Institute. Funding bodies did not have a role in study design, or collection, T-cells with senescent characteristics could potentially analysis and interpretation of data, or manuscript writing. vary within this indeterminate range. Future studies link- Availability of data and materials ing liver disease and T-cell dysfunction should examine The datasets used and/or analyzed during the current study are available this further and account for the possibility of non-linear from the corresponding author on reasonable request. associations. Ethics approval and consent to participate Limitations to this work that warrant discussion. Cur- All participants provided written informed consent. The study was approved rently, more detailed markers of immunosenescence and by Institutional Review Boards of Boston University Medical Campus and First memory and naïve T-cell phenotypes available than were St. Petersburg Pavlov State Medical University. readily available at the time of our flow cytometry test- Consent for publication ing between 2013 and 2015. Our analysis only examined Not applicable. T-cell phenotypes as percentages of CD4 or CD8, where Competing interests an absolute count, which was unavailable, might yield Debbie Cheng serves on Data Safety Monitoring Boards for Janssen Research different conclusions. Imaging confirmation of liver & Development. So-Armah et al. BMC Gastroenterology (2020) 20:1 Page 8 of 8 Author details 16. Vivar N, Thang PH, Atlas A, Chiodi F, Rethi B. Potential role of CD8+CD28- T 1 Department of Medicine, Boston University School of Medicine, 801 lymphocytes in immune activation during HIV-1 infection. AIDS. 2008;22(9): Massachusetts Avenue, Crosstown Building, 2nd Floor, Boston, MA 02118, 1083–6. USA. 2Department of Medicine, Vanderbilt University School of Medicine; 17. Brenchley JM, Karandikar NJ, Betts MR, Ambrozak DR, Hill BJ, Crotty LE, Nashville Veterans Affairs Medical Center, Tennessee Valley Healthcare Casazza JP, Kuruppu J, Migueles SA, Connors M, et al. Expression of CD57 System, Nashville, TN, USA. 3Department of Biostatistics, Boston University defines replicative senescence and antigen-induced apoptotic death of School of Public Health, Boston, MA, USA. 4Department of Internal Medicine, CD8+ T cells. Blood. 2003;101(7):2711–20. Yale University School of Medicine, New Haven, CT, USA. 5Department of 18. So-Armah KA, Edelman EJ, Cheng DM, Doyle MF, Patts GJ, Gnatienko N, Medicine, Boston Medical Center, Boston, MA, USA. 6Department of Krupitsky EM, Samet JH, Freiberg MS. Effects of heavy drinking on T-cell Biostatistics and Data Coordinating Center, Boston University School of phenotypes consistent with Immunosenescence in untreated HIV infection. Public Health, Boston, MA, USA. 7Department of Pathology and Laboratory Alcohol Clin Exp Res. 2016;40(8):1737–43. Medicine, University of Vermont, Burlington, VT, USA. 8Department of Internal 19. Sobell MB, Sobell LC, Klajner F, Pavan D, Basian E. The reliability of a Medicine, Hospital Universitari Germans Trias i Pujol, Universitat Autònoma timeline method for assessing normal drinker college students' recent de Barcelona, Badalona, Spain. 9Department of Infectious Diseases and drinking history: utility for alcohol research. Addict Behav. 1986;11(2):149–61. Epidemiology, Smorodintsev Research Institute of Influenza, First Pavlov State 20. Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom KO. The Fagerstrom Medical University, St. Petersburg, Russia. 10First Pavlov State Medical test for nicotine dependence: a revision of the Fagerstrom tolerance University, V. M. Bekhterev National Research Medical Center for Psychiatry questionnaire. Br J Addict. 1991;86(9):1119–27. and Neurology, St. Petersburg, Russia. 11Department of Medicine, Boston 21. Justice AC, Dombrowski E, Conigliaro J, Fultz SL, Gibson D, Madenwald Medical Center, Boston University School of Medicine, Boston, MA, USA. T, Goulet J, Simberkoff M, Butt AA, Rimland D, et al. Veterans aging cohort study (VACS): overview and description. Med Care. 2006;44(8 Received: 25 January 2019 Accepted: 5 December 2019 Suppl 2):S13–24. 22. Darke S, Hall W, Heather N, Ward J, Wodak A. The reliability and validity of a scale to measure HIV risk-taking behaviour among intravenous drug users. AIDS. 1991;5(2):181–5. References 23. Hao L, Naiman DQ. Quantile regression. Thousand Oaks: Sage Publications; 1. Galvan FH, Bing EG, Fleishman JA, London AS, Caetano R, Burnam MA, 2007. Longshore D, Morton SC, Orlando M, Shapiro M. The prevalence of alcohol 24. Koenker R. Quantile regression. Cambridge, New York: Cambridge University consumption and heavy drinking among people with HIV in the United Press; 2005. States: results from the HIV cost and services utilization study. J Stud 25. Marquez M, Fernandez-Gutierrez C, Montes-de-Oca M, Blanco MJ, Brun F, Alcohol. 2002;63(2):179–86. Rodriguez-Ramos C, Giron-Gonzalez JA. Chronic antigenic stimuli as a 2. Williams EC, Hahn JA, Saitz R, Bryant K, Lira MC, Samet JH. Alcohol use possible explanation for the immunodepression caused by liver cirrhosis. and human immunodeficiency virus (HIV) infection: current knowledge, Clin Exp Immunol. 2009;158(2):219–29. implications, and future directions. Alcohol Clin Exp Res. 2016;40(10): 26. Laso FJ, Iglesias-Osma C, Ciudad J, Lopez A, Pastor I, Torres E, Orfao A. 2056–72. Alcoholic liver cirrhosis is associated with a decreased expression of the 3. Samet JH, Cheng DM, Libman H, Nunes DP, Alperen JK, Saitz R. Alcohol CD28 costimulatory molecule, a lower ability of T cells to bind exogenous consumption and HIV disease progression. J Acquir Immune Defic Syndr. IL-2, and increased soluble CD8 levels. Cytometry. 2000;42(5):290–5. 2007;46(2):194–9. 4. Braithwaite RS, Bryant KJ. Influence of alcohol consumption on adherence Publisher’s Note to and toxicity of antiretroviral therapy and survival. Alcohol Res Health. Springer Nature remains neutral with regard to jurisdictional claims in 2010;33(3):280–7. published maps and institutional affiliations. 5. Malbergier A, Amaral RA, Cardoso LD. Alcohol dependence and CD4 cell count: is there a relationship? AIDS Care. 2015;27(1):54–8. 6. Hahn JA, Samet JH. Alcohol and HIV disease progression: weighing the evidence. Curr HIV/AIDS Rep. 2010;7(4):226–33. 7. Hahn JA, Cheng DM, Emenyonu NI, Lloyd-Travaglini C, Fatch R, Shade SB, Ngabirano C, Adong J, Bryant K, Muyindike WR, et al. Alcohol use and HIV disease progression in an antiretroviral naive cohort. J Acquir Immune Defic Syndr. 2018;77(5):492–501. 8. Li F, Tian Z. The liver works as a school to educate regulatory immune cells. Cell Mol Immunol. 2013;10(4):292–302. 9. Gnatienko N, Freiberg MS, Blokhina E, Yaroslavtseva T, Bridden C, Cheng DM, Chaisson CE, Lioznov D, Bendiks S, Koerbel G, et al. Design of a randomized controlled trial of zinc supplementation to improve markers of mortality and HIV disease progression in HIV-positive drinkers in St. Petersburg, Russia. HIV Clin Trials. 2018;19:1–11. 10. Klibansky DA, Mehta SH, Curry M, Nasser I, Challies T, Afdhal NH. Transient elastography for predicting clinical outcomes in patients with chronic liver disease. J Viral Hepat. 2012;19(2):e184–93. 11. Chou R, Wasson N. Blood tests to diagnose fibrosis or cirrhosis in patients with chronic hepatitis C virus infection: a systematic review. Ann Intern Med. 2013;158(11):807–20. 12. Weng NP. Aging of the immune system: how much can the adaptive immune system adapt? Immunity. 2006;24(5):495–9. 13. Dock JN, Effros RB. Role of CD8 T cell replicative senescence in human aging and in HIV-mediated Immunosenescence. Aging Dis. 2011;2(5): 382–97. 14. Strioga M, Pasukoniene V, Characiejus D. CD8+ CD28- and CD8+ CD57+ T cells and their role in health and disease. Immunology. 2011;134(1):17–32. 15. Cook RT, Ballas ZK, Waldschmidt TJ, Vandersteen D, LaBrecque DR, Cook BL. Modulation of T-cell adhesion markers, and the CD45R and CD57 antigens in human alcoholics. Alcohol Clin Exp Res. 1995;19(3):555–63.