Epigenetic Aging and Treatment Response to Semaglutide in the SLIM LIVER Study

Epigenetic Aging and Treatment Response to Semaglutide in the SLIM LIVER Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Epigenetic Aging and Treatment Response to Semaglutide in the SLIM LIVER Study Michael Corley, Alina Pang, Douglas Kitch, Amy Kantor, Fred Sattler, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7697256/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Apr, 2026 Read the published version in npj Aging → Version 1 posted 15 You are reading this latest preprint version Abstract Background: Semaglutide, a glucagon-like peptide-1 receptor agonist (GLP-1 RA), improves metabolic health and reduces liver fat in people with HIV (PWH) and metabolic dysfunction-associated steatotic liver disease (MASLD). Whether changes in epigenetic aging biomarkers reflect these clinical benefits remains unknown. Methods: We conducted a post hoc analysis of the SLIM LIVER study (ACTG A5371), a 24-week, single-arm trial of semaglutide (1.0 mg weekly) in PWH and MASLD. Epigenetic aging was assessed at baseline and 24 weeks using DNA methylation–based epigenetic clocks: DunedinPACE (pace of aging), PCGrimAge (mortality risk), and PCDNAmTL (methylation-derived telomere length). Participants were stratified by change in epigenetic markers (decrease vs. increase); clinical responses were compared across anthropometric, metabolic, and physical function outcomes. Results: We observed a stable pace of aging was maintained over 24 weeks (n=41) with a median change of DunedinPACE of +0.018 (IQR: –0.023 to +0.053), PCDNAmTL (median –0.006 kb; IQR: –0.073 to +0.054), and PCGrimAge (median +0.54 years; IQR: –0.33 to +1.26). Seventeen (41.5%) showed a decrease in DunedinPACE with significantly greater reductions in liver fat ( p = 0.024) and improved gait speed ( p = 0.081), corresponding to a ~0.8 day (minimum, –0.0048) to ~19.5 days (maximum, –0.116) deceleration. Participants with increased PCDNAmTL (n=20) similarly demonstrated significantly greater improvements in gait speed ( p = 0.012). No significant clinical associations were observed with changes in PCGrimAge. Conclusions: These findings provide preliminary evidence that semaglutide may modulate epigenetic age biomarkers, with DunedinPACE and PCDNAmTL tracking improvements in hepatic and physical function. Integration of epigenetic biomarkers into future trials may enhance gerotherapeutic precision by identifying individuals most likely to benefit from GLP-1RA therapy and by enabling minimally invasive monitoring of biological aging. Trial Registration: ClinicalTrials.gov ID: NCT04216589 Health sciences/Biomarkers Health sciences/Diseases Health sciences/Medical research Epigenetics HIV Aging Semaglutide GLP-1 DNA methylation Epigenetic clock geroscience liver MASLD Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION Glucagon-like peptide-1 receptor agonists (GLP-1 RAs), such as semaglutide, have emerged as a transformative class of therapeutics that promote weight loss, improve glycemic control, and provide systemic benefits across multiple organ systems 1 – 4 . Beyond their established role in diabetes management, GLP-1 RAs have demonstrated cardiovascular protection, potential neuroprotective effects, and improvement in inflammation and endothelial function, positioning them as promising therapeutic agents for the geroscience field 1 – 3 , 5 , 6 . The properties of GLP-1 RAs are particularly relevant for metabolic dysfunction–associated steatotic liver disease (MASLD), a leading comorbidity in people with HIV (PWH) characterized by excess intrahepatic triglyceride (IHTG) accumulation, insulin resistance, oxidative stress, and systemic inflammation 7 . While lifestyle-induced weight loss remains the cornerstone of MASLD management 8 , semaglutide 9 has shown efficacy in reducing hepatic steatosis and improving broader metabolic parameters and physical function 10 , 11 . Such benefits may be especially important for PWH, who frequently experience an accelerated aging phenotype driven by chronic immune activation and metabolic dysregulation 12 . Recent advances in epigenetic biomarker research have enabled the quantification of biological aging through DNA methylation-based "epigenetic clocks" 13 . These clocks serve as minimally invasive proxies of biological aging and have been linked to metabolic traits such as body mass index, visceral adiposity, insulin resistance, and liver disease severity 14 – 16 . In PWH, epigenetic age acceleration (EAA) is frequently observed, with estimates ranging from 3 to 7 years above chronological age 17 – 19 . Recent evidence suggests that EAA may also reflect liver disease progression. In a study of 325 individuals with MASLD, advanced fibrosis was associated with a 5% faster pace of aging, as measured by DunedinPACE, and a 10% reduction in telomere length, captured by DNAmTL, compared to those without fibrosis 16 . Similarly, in a separate study of individuals with biopsy-confirmed non-alcoholic steatohepatitis (NASH), EAA measured by the Horvath clock correlated with hepatic collagen content, though not fibrosis stage, and revealed differentially methylated CpG sites enriched in developmental and transcriptional regulatory pathways 15 . These findings underscore the potential of epigenetic aging measures as biomarkers of liver disease severity and therapeutic responsiveness. However, it remains unclear whether longitudinal changes in epigenetic biomarkers track with clinical improvements in response to interventions such as GLP-1 RA therapy. To address this, we conducted a post hoc epigenetic analysis of participants from the SLIM LIVER study (Advancing Clinical Therapeutics Globally for HIV/AIDS and Other Infections (ACTG) A5371; NCT04216589), an open-label, single arm, Phase 2 clinical trial of semaglutide in PWH with MASLD. In the parent study, 24 weeks of low-dose semaglutide (1 mg subcutaneously weekly) significantly reduced IHTG by 31.3%, improved insulin sensitivity (approximately 1.5-unit decrease in Homeostatic Model Assessment of Insulin Resistance (HOMA-IR)), and lowered triglyceride levels by 27 mg/dL 11 . A secondary analysis also revealed preserved or improved physical function, with a significant reduction in the prevalence of slow gait speed (< 1 m/s) despite modest muscle loss 10 . We hypothesized that within-individual changes in epigenetic aging biomarkers DunedinPACE, PCGrimAge, and DNAm telomere length (PCDNAmTL) over 24 weeks of semaglutide treatment would be associated with improvements in hepatic fat, metabolic markers, and physical function. This exploratory analysis aimed to assess the extent to which biological aging is modifiable in response to semaglutide and whether such changes are associated with therapeutic benefit in PWH with MASLD. 1. METHODS 1.1. Trial Population The SLIM LIVER study ([ACTG] protocol A5371; NCT04216589) was a Phase 2b, single-arm, open-label, 24-week, pilot study designed to evaluate the effect of semaglutide on IHTG and metabolic health among PWH and MASLD 11 . Participants were enrolled from nine ACTG-affiliated clinical research sites between February 2021 and September 2022​. Eligible participants were aged ≥ 18 years, living with HIV on stable antiretroviral therapy (ART) with suppressed HIV-1 RNA ( 3.0) or pre-diabetes (fasting glucose 100–125 mg/dL or hemoglobin A1c (HbA1c ) 5.7–6.4%). Exclusion criteria included previous GLP-1 RA use within 24 weeks, diabetes mellitus, significant alcohol use, and other causes of liver disease. Physical function was measured at baseline and week 24 by assessing the time to rise from a chair 5 and 10 times and 4-meter gait speed, where gait speed was calculated as the average of 2 measurements at usual pace. Slow gait speed was defined as walking < 1 m/sec. Each site obtained institutional review board approval, and all participants provided written informed consent​. 1.2. SLIM LIVER Epigenetic Sub-study Participant Selection We evaluated the longitudinal changes in epigenetic age estimates at two time points, at baseline and after 24 weeks of low-dose semaglutide, for 41 participants enrolled with available peripheral blood mononuclear cells (PBMCs). 1.3. DNA Methylation Profiling and Epigenetic Age DNA was isolated from PBMCs using a Zymo Research Quick-DNA microprep kit. 500 ng of DNA was treated with bisulfite using the EZ DNA Methylation kit from Zymo Research, following the manufacturer's instructions. The bisulfite-treated DNA samples were randomly assigned to a well on the Infinium HumanMethylationEPIC BeadChip, which was then amplified, hybridized, stained, washed, and imaged with the Illumina iScan SQ instrument to obtain raw image intensities. To pre-process the DNA methylation data, we used the minfi pipeline 20 , and low quality samples were identified using the qcfilter() function from the ENmix package 21 , using default parameters. A total of 82 samples (41 baseline and 41 follow up), representing 100% of the original samples, passed the quality assurance and quality control (p < 0.05) and were deemed to be high quality samples. Our focus was on the second-generation principal component-derived epigenetic clock, PCGrimAge 22 , 23 , a measure of biological aging that incorporates DNA methylation-based estimates of biomarkers associated with age-related mortality risk, the third-generation clock, DunedinPACE 24 , a measure of the pace of aging crucial for understanding the impact of interventions on epigenetic aging, and Lu’s telomere length predictor based on 140 CpGs 25 . Epigenetic clocks were calculated according to published methods 19 from processed DNA methylation data. To enhance the reliability of GrimAge and DNAmTL estimates, we utilized its principal-component versions using the custom R script available via GitHub ( https://github.com/MorganLevineLab/PC-Clocks ) 23 . The pace of aging clock, DunedinPACE, was calculated using the PACEProjector function from the DunedinPACE package available via GitHub ( https://github.com/danbelsky/DunedinPACE ). 1.4. Statistical Analysis This post hoc analysis assessed whether changes in epigenetic aging markers over 24 weeks of semaglutide treatment were associated with differential responses across hepatic, metabolic, and physical function domains. Descriptive statistics were reported as medians with interquartile ranges (IQRs) for continuous variables and frequencies with percentages for categorical variables. Participants were stratified into “decreased” vs. “increased” epigenetic age change groups based on directionality of change in three biomarkers: DunedinPACE, PCGrimAge, and PCDNAmTL. Directionality (increase vs. decrease) was assessed separately for DunedinPACE, PCGrimAge, and PCDNAmTL. Group comparisons for percent changes in clinical measures (e.g., IHTG, HOMA-IR, HbA1c, BMI, physical function) were conducted using the Kruskal-Wallis test. For epigenetic biomarkers, changes from baseline to week 24 were analyzed using Wilcoxon signed-rank tests for within-group comparisons. 2. RESULTS 3.1. SLIM LIVER Epigenetic Substudy Characteristics. Characteristics of the overall SLIM LIVER cohort have been previously described 11 . Forty one of 51 enrolled participants had evaluable samples at both time points for our post hoc epigenetic analysis (Table 1 ). The median age was 52 years (interquartile range [IQR]: 42–58). Obesity and central adiposity were common (by design), with a median body mass index (BMI) of 35 kg/m² (IQR: 31–39) and median waist circumference of 114 cm (IQR: 107–124). All participants were on suppressive ART with HIV-1 RNA levels below 50 copies/mL, and the median CD4 + T-cell count was 701 cells/mm³ (IQR: 586–869). Metabolic parameters reflected elevated cardiometabolic risk, with a median HOMA-IR of 3.8 (IQR: 2.8–6.1) and fasting glucose of 98 mg/dL (IQR: 93–107). Median fasting triglycerides were 116 mg/dL (IQR: 95–183), and alanine aminotransferase (ALT) was elevated in 53% of participants. ART regimens were predominantly integrase strand transfer inhibitor (INSTI)-based (82%), with smaller proportions on non-nucleoside reverse transcriptase inhibitor (NNRTI; 22%)- or protease inhibitor (PI; 4%)-based regimens. 3.2. Baseline PCGrimAge, DunedinPACE, and PCDNAmTL and changes over 24 weeks of semaglutide At baseline, PCGrimAge, an epigenetic biomarker trained to predict mortality risk, indicated a biological age of 60.0 years (median; range: 34.3–70.6). The median PCGrimAge acceleration reflecting the difference between epigenetic and chronological age was 7.5 years (IQR: 5.1–9.4), suggesting elevated age-related mortality risk within the cohort for 40 of the 41 participants profiled. The DunedinPACE score, which quantifies the rate of aging (with 1.0 representing the normative pace), had a median value of 0.95 (IQR: 0.88–1.00). Twenty two percent (9 of 41 participants) had a DunedinPACE score calculated at greater than 1.0 at baseline, indicating an accelerated pace of aging for these individuals. PCDNAmTL, a methylation-derived estimate of telomere length, showed a median value of 6.90 units (IQR: 6.80–7.16), reflecting relatively uniform telomere-associated aging across participants. Over 24 weeks of semaglutide, participants maintained a stable pace of aging, with a median DunedinPACE change of + 0.018 (IQR: − 0.023 to + 0.053), stable PCDNAmTL (median − 0.006 kb; IQR: − 0.073 to + 0.054), and minimal change in PCGrimAge (median + 0.54 years; IQR: − 0.33 to + 1.26). 3.3. Changes in Epigenetic Age Markers Are Associated with Hepatic and Functional Outcomes following 24 weeks of semaglutide A total of 17 participants (9 male, 8 female; 41.5%) experienced a decrease in DunedinPACE with semaglutide, indicating a slower pace of aging from baseline. 14 participants (8 male, 6 female; 34.1%) demonstrated a decrease in PCGrimAge, indicating a reduction in epigenetic mortality risk, and 20 participants (11 male, 9 female; 48.8%) showed an increase in predicted DNA methylation-based telomere length (PCDNAmTL) (Fig. 1 A - F). We examined whether changes in epigenetic aging over the 24 weeks were associated with differential responses to semaglutide treatment across key clinical domains, including anthropometry, metabolic biomarkers, and physical function. Participants were grouped based on direction of change (Increased vs. Decreased) for DunedinPACE, PCGrimAge, and PCDNAmTL. Participants with a decrease in DunedinPACE showed a significantly greater percent reduction in IHTG ( p = 0.024) compared to those with increased DunedinPACE (Fig. 2 ). No significant differences were observed for BMI ( p = 0.63) or weight ( p = 0.63) (Fig. 2 ). When stratified by PCGrimAge or PCDNAmTL change groups, no significant group differences were observed for any anthropometric outcome (all p > 0.35), including IHTG ( p = 0.88 for PCGrimAge, p = 0.36 for PCDNAmTL), suggesting this association may be specific to DunedinPACE (Fig. 2 ). There were no statistically significant differences in metabolic biomarkers by change group for DunedinPACE, PCGrimAge, or PCDNAmTL. This included HOMA-IR ( p = 0.94 for DunedinPACE, p = 0.78 for PCDNAmTL), fasting glucose, triglycerides, high-density lipoprotein (HDL), and low-density lipoprotein LDL (all p > 0.14), indicating that semaglutide-induced improvements in these markers occurred broadly and were not contingent on three epigenetic age dynamics assessed (Fig. 3 ). However, a trend toward greater reduction in HbA1c was observed among participants with increased PCDNAmTL ( p = 0.072), suggesting a possible relationship between telomere attrition and glycemic improvement (Fig. 3 ). For physical function, no significant differences were found in 5-time or 10-time chair rise time by DunedinPACE, PCGrimAge or PCDNAmTL group (all p > 0.50) (Fig. 4 ). A non-significant trend toward improved gait speed was observed among those with decreased DunedinPACE ( p = 0.083) and a significant improvement in gait speed was observed among participants with increased PCDNAmTL ( p = 0.012) (Fig. 4 ), suggesting that preservation or elongation of telomere length may be linked to better maintenance of physical function following semaglutide treatment. 3. DISCUSSION In this pilot post hoc epigenetic analysis of the SLIM LIVER trial, we evaluated whether changes in epigenetic aging biomarkers, specifically DunedinPACE, PCGrimAge and PCDNAmTL, were associated with anthropometric, metabolic, and physical function changes over 24 weeks of semaglutide treatment in PWH and MASLD. Our findings suggest that a less accelerated pace of aging, as captured by DunedinPACE, may be selectively associated with greater liver fat reduction following semaglutide treatment. While PCGrimAge change was not linked to anthropometric or metabolic outcomes, an increase in telomere length (PCDNAmTL) was significantly associated with improved gait speed, indicating that epigenetic telomere preservation may parallel enhancements in physical function. Conversely, participants with increased PCDNAmTL trended toward greater reductions in HbA1c, hinting at a possible link between semaglutide glycemic improvement and telomere biology. These findings suggest a potential relationship between semaglutide-related changes in specific epigenetic aging biomarkers and improvements in liver fat and physical function. These results merit further investigation of this association in larger cohorts and independent studies to validate the utility of epigenetic age biomarkers as indicators of therapeutic response in GLP-1RA therapy. The observed reduction in liver fat among select individuals with slowing DunedinPACE may reflect improved metabolic flexibility and hepatic lipid mobilization in reponse to semaglutide. DunedinPACE, is a third-generation DNA methylation-based biomarker that quantifies the pace of biological aging by integrating longitudinal physiological, cellular, and molecular data across multiple organ systems 24 . Unlike first generation epigenetic clocks, it captures short-term changes in systemic function and has been shown to respond to behavioral and pharmacologic interventions 26 , 27 . Our findings are consistent with prior work demonstrating associations between accelerated DunedinPACE and liver fibrosis severity, insulin resistance, and cardiometabolic risk 16 . The lack of similar associations with body weight or BMI following semaglutide treatment in this study suggests that DunedinPACE may be more sensitive to underlying shifts in tissue-specific metabolic health such as intrahepatic lipid dynamics than to gross anthropometric changes alone. These findings support further exploration of DunedinPACE as a potential biomarker for semaglutide-related improvements in metabolic aging beyond weight loss alone. Interestingly, we did not observe significant group differences in glycemic or lipid parameters when stratified by epigenetic age change following semaglutide. Improvements in HOMA-IR, fasting glucose, and triglycerides were seen broadly across the cohort following semaglutide 11 , regardless of whether DunedinPACE or PCGrimAge declined over the study period. These findings suggest that semaglutide’s core metabolic benefits may operate, at least in part, through mechanisms independent of its impact on the three DNA methylation-based epigenetic measures assessed. Alternatively, the lack of association may reflect limited power to detect domain-specific effects given the modest sample size. Importantly, while semaglutide has demonstrated robust metabolic efficacy, its potential as a multi-system gerotherapeutic is only beginning to be explored 28 . Emerging data suggest that GLP-1 RAs may influence aging biology in other organ systems such as the brain, cardiovascular system, and kidneys via effects on inflammation, oxidative stress, and cellular senescence 29 . The SLIM LIVER study provides supporting preliminary evidence that semaglutide may also modulate biological aging trajectories in the liver and musculoskeletal system, as reflected by links to liver fat reduction and gait speed improvement. Future work incorporating broader multi-organ epigenetic and transcriptomic profiling may clarify how GLP-1 RAs influence systemic aging biology beyond metabolic control alone. We also observed a modest trend toward improved walking speed among participants who exhibited a reduction in DunedinPACE. Although this association did not reach statistical significance, the directionality is biologically plausible and consistent with prior studies linking accelerated epigenetic aging to frailty, slower gait speed, and functional decline in older adults 30 , 31 . The absence of group differences in chair rise times may be due to skeletal muscle effects, task variability, or limited power. Taken together, these findings suggest that semaglutide-associated slowing of biological aging may contribute to preserved or enhanced mobility. Future studies in borader populations, more granular functional assessments, and extended follow-up durations are needed to fully characterize the relationship between changes in epigenetic aging markers and physical performance trajectories. In addition to DunedinPACE and PCGrimAge, we evaluated changes in methylation-derived telomere length (PCDNAmTL). While changes in PCDNAmTL were not associated with differences in hepatic or anthropometric outcomes, we observed a trend toward greater HbA1c reduction among participants with telomere increases, potentially linking glycemic improvement to telomere biology 32 . In addition, participants with increased PCDNAmTL indicating preserved or elongated telomeres demonstrated a significant improvement in walking speed, suggesting a possible protective effect of telomere maintenance on physical function. In the SLIM LIVER study we found the prevalence of slow gait speed (< 1 m/sec) decreased from 63% to 46% (P = .029) 10 . These findings align with prior evidence linking longer telomeres to better mobility, mitochondrial integrity, and muscle performance in aging populations 33 . Although exploratory, the directionality of these associations suggests that different dimensions of epigenetic aging may differentially track metabolic versus functional responsiveness to treatment. Larger studies are needed to validate these relationships and clarify whether PCDNAmTL may serve as a prognostic marker for physical resilience in the context of semaglutide. An important consideration in interpreting these results is the use of a relatively low semaglutide dose (1.0 mg weekly) and a 24-week treatment duration, which may have attenuated the magnitude of clinical effects compared to trials using higher doses over longer periods. For example, phase 3 trials such as the STEP and ESSENCE programs have demonstrated greater reductions in liver fat, weight, and glycemic indices with weekly 2.4 mg dosing over 48 to 72 weeks 1 , 3 , 6 . However, for anti-aging applications, prolonged tolerability and safety are critical, and lower, sustained dosing regimens may be more appropriate for long-term use. As such, while higher doses could potentially amplify clinical and epigenetic responses, the current design may reflect a more pragmatic framework for gerotherapeutic implementation. Future studies should explore dose–response effects, compare acute versus chronic trajectories of epigenetic change, and evaluate the durability of biological aging modifications with extended follow-up in target populations, including PWH. Taken together, our findings provide preliminary evidence that semaglutide may influence biological aging trajectories in a subset of individuals, particularly through deceleration of the pace of aging as measured by DunedinPACE. This slowing was selectively associated with greater reductions in liver fat, suggesting that epigenetic aging dynamics may reflect or contribute to organ-specific treatment responsiveness. Given the disproportionate burden of metabolic dysfunction in PWH and the expanding therapeutic role of GLP-1RA in liver disease, these results highlight the importance of integrating biological aging metrics into future interventional studies. Epigenetic clocks such as DunedinPACE and DNAmTL may serve as minimally invasive biomarkers to stratify risk, monitor longitudinal response, and guide personalized approaches aimed at improving both metabolic and functional health outcomes. Declarations AUTHORS’ CONTRIBUTIONS Conceptualization (MJC, AL, KME); data curation, formal analysis, visualization, and methodology (AJC, APP, DWK, AK); funding acquisition (JEL, KME); investigation (all authors); project administration (MJC, JEL, KME); writing – original draft (MJC, APP); writing – review and editing (all authors). MJC had full access to and verified all the data in the study. All authors had final responsibility for the decision to submit for publication. ACKNOWLEDGEMENTS The study investigators thank the study participants, site staff, and study-associated personnel for their ongoing participation in the trial. In addition, we thank the following: the ACTG for clinical site support; ACTG Clinical Trials Specialists (Christina Vernon, Katharine Bergstrom) for protocol development and implementation support; the data management center, Frontier Science Foundation, for data support; the Center for Biostatistics in AIDS Research for statistical support; and the Community Advisory Board for input for the community. NIH GRANTS POLICY STATEMENT The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Institutes of Health; or the U.S. Department of Health and Human Services. FUNDING: This manuscript is the result of funding in whole or in part by the National Institutes of Health and is subject to the NIH Public Access Policy. This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under [UM1 AI068634, UM1 AI068636, UM1 AI106701] with additional funding provided by McGovern School of Medicine at UTHealth. Additional support was provided by National Institute of Allergy and Infectious Diseases [K24 AI120834 to TTB] and the National Institute on Aging under [K24 AG082527 to KME]. COMPETING INTERESTS: MJ Corley serves as a scientific advisor for TruDiagnostic. APS Pang declares no disclosures. KM Erlandson has received research funding from the NIH/NIA in support of the present manuscript; outside of the current work, she has received research funding from Gilead Sciences and has consulted for Gilead Sciences, Merck, and ViiV Pharmaceuticals, all paid to her institution. TT Brown has served as a consultant to Merck, ViiV Healthcare, EMD Serono, and Jannsen. PFB-Z is the Division of AIDS medical officer for the study; however, his views are personal and do not represent the NIH/NIAID's views. DATA AVAILABILITY [ The data from this study was submitted to the NCBI Gene Expression Omnibus (GEO) http://www.ncbi.nlm.nih.gov/geo/ References Sanyal, A. J. et al. Phase 3 trial of semaglutide in metabolic dysfunction-associated steatohepatitis. N. Engl. J. Med. (2025) doi:10.1056/NEJMoa2413258. Marso, S. P. et al. Semaglutide and cardiovascular outcomes in patients with type 2 diabetes. The New England journal of medicine vol. 375 1834–1844 (2016). Davies, M. et al. Semaglutide 2·4 mg once a week in adults with overweight or obesity, and type 2 diabetes (STEP 2): a randomised, double-blind, double-dummy, placebo-controlled, phase 3 trial. Lancet 397 , 971–984 (2021). Drucker, D. J. Expanding applications of therapies based on GLP1. Nat. Rev. Endocrinol. 21 , 65–66 (2025). De Giorgi, R. et al. An analysis on the role of glucagon-like peptide-1 receptor agonists in cognitive and mental health disorders. Nat. Ment. Health 3 , 354–373 (2025). Wilding, J. P. H. et al. Once-weekly semaglutide in adults with overweight or obesity. N. Engl. J. Med. 384 , 989–1002 (2021). Hsu, C. L. & Loomba, R. From NAFLD to MASLD: implications of the new nomenclature for preclinical and clinical research. Nat. Metab. 6 , 600–602 (2024). Rajewski, P. et al. Dietary interventions and physical activity as crucial factors in the prevention and treatment of metabolic dysfunction-associated steatotic liver disease. Biomedicines 13 , (2025). Kuo, C.-C. et al. Semaglutide versus other GLP-1 receptor agonists in patients with MASLD. Hepatol. Commun. 9 , e0747 (2025). Ditzenberger, G. L. et al. Effects of Semaglutide on Muscle Structure and Function in the SLIM LIVER Study. Clin. Infect. Dis. (2024) doi:10.1093/cid/ciae384. Lake, J. E. et al. The Effect of Open-Label Semaglutide on Metabolic Dysfunction-Associated Steatotic Liver Disease in People With HIV. Ann. Intern. Med. (2024) doi:10.7326/M23-3354. Deeks, S. G. Immune dysfunction, inflammation, and accelerated aging in patients on antiretroviral therapy. Top. HIV Med. 17 , 118–123 (2009). Teschendorff, A. E. & Horvath, S. Epigenetic ageing clocks: statistical methods and emerging computational challenges. Nat. Rev. Genet. (2025) doi:10.1038/s41576-024-00807-w. Horvath, S. et al. Obesity accelerates epigenetic aging of human liver. Proc. Natl. Acad. Sci. U. S. A. 111 , 15538–15543 (2014). Loomba, R. et al. DNA methylation signatures reflect aging in patients with nonalcoholic steatohepatitis. JCI Insight 3 , e96685 (2018). Wang, H. et al. Association between advanced fibrosis and epigenetic age acceleration among individuals with MASLD. J. Gastroenterol. 60 , 306–314 (2025). Horvath, S. & Levine, A. J. HIV-1 Infection Accelerates Age According to the Epigenetic Clock. J. Infect. Dis. 212 , 1563–1573 (2015). Corley, M. J. et al. Effect of Pitavastatin on Epigenetic Aging Biomarkers in People With HIV: Pilot Substudy of the REPRIEVE Trial. Clinical Infectious Diseases ciaf247 (2025). Johnston, C. D. et al. Sex differences in epigenetic ageing for older people living with HIV. EBioMedicine 113 , 105588 (2025). Aryee, M. J. et al. Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics 30 , 1363–1369 (2014). Xu, Z., Niu, L., Li, L. & Taylor, J. A. ENmix: a novel background correction method for Illumina HumanMethylation450 BeadChip. Nucleic Acids Res. 44 , e20 (2016). Lu, A. T. et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging 11 , 303–327 (2019). Higgins-Chen, A. T. et al. A computational solution for bolstering reliability of epigenetic clocks: Implications for clinical trials and longitudinal tracking. Nat Aging 2 , 644–661 (2022). Belsky, D. W. et al. DunedinPACE, a DNA methylation biomarker of the pace of aging. Elife 11 , (2022). Lu, A. T. et al. DNA methylation-based estimator of telomere length. Aging 11 , 5895–5923 (2019). Dwaraka, V. B. et al. Unveiling the epigenetic impact of vegan vs. omnivorous diets on aging: insights from the Twins Nutrition Study (TwiNS). BMC Med. 22 , 301 (2024). Bischoff-Ferrari, H. A. et al. Individual and additive effects of vitamin D, omega-3 and exercise on DNA methylation clocks of biological aging in older adults from the DO-HEALTH trial. Nat. Aging 5 , 376–385 (2025). Scheltens, P. et al. Baseline characteristics from evoke and evoke+: Two phase 3 randomized placebo-controlled trials of oral semaglutide in patients with early Alzheimer’s disease (P11-9.013). Neurology 102 , 3350 (2024). Drucker, D. J. GLP-1-based therapies for diabetes, obesity and beyond. Nat. Rev. Drug Discov. 1–20 (2025). Mak, J. K. L. et al. Temporal dynamics of epigenetic aging and frailty from midlife to old age. J. Gerontol. A Biol. Sci. Med. Sci. 79 , glad251 (2024). Phyo, A. Z. Z. et al. Epigenetic age acceleration and the risk of frailty, and persistent activities of daily living (ADL) disability. Age Ageing 53 , afae127 (2024). Cheng, F. et al. Shortened leukocyte telomere length is associated with glycemic progression in type 2 diabetes: A prospective and Mendelian randomization analysis. Diabetes Care 45 , 701–709 (2022). Dempsey, P. C. et al. Investigation of a UK biobank cohort reveals causal associations of self-reported walking pace with telomere length. Commun. Biol. 5 , 381 (2022). Table 1 Table 1: Baseline Participant Characteristics Baseline Characteristic Groups All participants (N = 41) IHTG% Change Mean (SD) Overall -28.8 (27.3) Age (years) 52 (41.0, 57.5) 50 23 (56%) -32.2 (26.5) Natal sex Male 25 (61%) -24.1 (30.0) Female 16 (39%) -36.2 (21.3) Race White 30 (73%) Black 16 (39%) Multiple 1 (2%) American Indian/ Alaska Native 1 (2%) Unknown 3 (7%) Ethnicity Not Hispanic or Latino 31 (61%) Hispanic or Latino 20 (39%) HIV-1 RNA (copies/mL) <20 30 (73%) -27.3 (27.8) <50 11 (27%) -33.0 (26.9) CD4 count (cells/mm³) 701 (606, 848) <500 5 (12%) -31.5 (34.5) ≥500 36 (78%) -28.4 (26.8) CD4/CD8 ratio (cells/mm³) 1.21 (0.714, 1.72) <1 12 (29%) -33.1 (26.0) ≥1 29 (71%) -27.0 (28.1) Additional Declarations Competing interest reported. MJ Corley serves as a scientific advisor for TruDiagnostic. APS Pang declares no disclosures. KM Erlandson has received research funding from the NIH/NIA in support of the present manuscript; outside of the current work, she has received research funding from Gilead Sciences and has consulted for Gilead Sciences, Merck, and ViiV Pharmaceuticals, all paid to her institution. TT Brown has served as a consultant to Merck, ViiV Healthcare, EMD Serono, and Jannsen. PFB-Z is the Division of AIDS medical officer for the study; however, his views are personal and do not represent the NIH/NIAID's views. Cite Share Download PDF Status: Published Journal Publication published 21 Apr, 2026 Read the published version in npj Aging → Version 1 posted Editorial decision: Revision requested 22 Oct, 2025 Reviews received at journal 21 Oct, 2025 Reviewers agreed at journal 21 Oct, 2025 Reviews received at journal 21 Oct, 2025 Reviews received at journal 19 Oct, 2025 Reviews received at journal 14 Oct, 2025 Reviewers agreed at journal 14 Oct, 2025 Reviewers agreed at journal 13 Oct, 2025 Reviewers agreed at journal 13 Oct, 2025 Reviewers agreed at journal 13 Oct, 2025 Reviewers agreed at journal 13 Oct, 2025 Reviewers invited by journal 08 Oct, 2025 Editor assigned by journal 07 Oct, 2025 Submission checks completed at journal 28 Sep, 2025 First submitted to journal 23 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7697256","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":521935892,"identity":"cfbdc9b9-e3fb-4bd0-a699-0cbf1e9bae69","order_by":0,"name":"Michael Corley","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYFCCA0BcwMDALwGkH4B5DAxANjMBLQYMDJIzgHRCAlFaGCBaDG4Qq0W38fDDxxUGNombbzcf/JD44w6DwfHjD28wVFgnNuDQYnbgmLHhGYO0xG13jiVLJCQ8YzA4k2NswXAmHY+WM2ySDQaHE7fdyDEAajkMdCEPmwRj22FCWv4nbp6R//kHRAv7MwnGfwS1HEjcIJHDBrWFwUyCsQGfFqBfGgySjWfcSDOzSEg7zCMJ8kvCsXRjnFpuHH74sKHCTrZ/RvLjGx9sDsvxgULsQ421LC4tDBIHwJQjTAEPmEzApRwE+CFq7fGpGQWjYBSMghEOAISCZWLCjrmAAAAAAElFTkSuQmCC","orcid":"","institution":"University of California, San Diego","correspondingAuthor":true,"prefix":"","firstName":"Michael","middleName":"","lastName":"Corley","suffix":""},{"id":521935895,"identity":"14f648b9-bdbf-4b42-b60c-9db7bb8052a1","order_by":1,"name":"Alina Pang","email":"","orcid":"","institution":"University of California, San Diego","correspondingAuthor":false,"prefix":"","firstName":"Alina","middleName":"","lastName":"Pang","suffix":""},{"id":521935898,"identity":"2f933e1a-a3d9-42cb-8af1-d5a288bc912a","order_by":2,"name":"Douglas Kitch","email":"","orcid":"","institution":"Harvard T.H. Chan School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Douglas","middleName":"","lastName":"Kitch","suffix":""},{"id":521935899,"identity":"cf432ba3-8d7e-4f15-9e64-e85b399c2b76","order_by":3,"name":"Amy Kantor","email":"","orcid":"","institution":"Harvard T.H. Chan School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Amy","middleName":"","lastName":"Kantor","suffix":""},{"id":521935901,"identity":"9bedcc56-6f3b-4b22-a732-ad01c59f0baf","order_by":4,"name":"Fred Sattler","email":"","orcid":"","institution":"University of Southern California Keck School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Fred","middleName":"","lastName":"Sattler","suffix":""},{"id":521935903,"identity":"48c83c7f-237a-4701-a02f-07e038a402e5","order_by":5,"name":"Pablo Belaunzaran-Zamudio","email":"","orcid":"","institution":"National Institute of Allergy and Infectious Diseases (contractor)","correspondingAuthor":false,"prefix":"","firstName":"Pablo","middleName":"","lastName":"Belaunzaran-Zamudio","suffix":""},{"id":521935904,"identity":"20775905-282a-419c-90ad-da7a1cc3860c","order_by":6,"name":"Todd Brown","email":"","orcid":"","institution":"John Hopkins University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Todd","middleName":"","lastName":"Brown","suffix":""},{"id":521935905,"identity":"c34b3b8e-29a3-4653-92b9-ff82f8b27f4a","order_by":7,"name":"Alan Landay","email":"","orcid":"","institution":"University of Texas Medical Branch","correspondingAuthor":false,"prefix":"","firstName":"Alan","middleName":"","lastName":"Landay","suffix":""},{"id":521935906,"identity":"fdf5b7ad-9384-421c-ab51-6b6281ccf62a","order_by":8,"name":"Jordan Lake","email":"","orcid":"","institution":"UTHealth Houston","correspondingAuthor":false,"prefix":"","firstName":"Jordan","middleName":"","lastName":"Lake","suffix":""},{"id":521935907,"identity":"03e4b0d2-3176-4d2e-bdd6-1758de96885f","order_by":9,"name":"Kristine Erlandson","email":"","orcid":"","institution":"University of Colorado- Anschutz Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Kristine","middleName":"","lastName":"Erlandson","suffix":""}],"badges":[],"createdAt":"2025-09-23 19:08:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7697256/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7697256/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41514-026-00383-9","type":"published","date":"2026-04-21T15:58:48+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":92574892,"identity":"646e9c5f-f135-4dfc-bc84-6423505c09d0","added_by":"auto","created_at":"2025-10-01 08:14:15","extension":"tiff","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":894122,"visible":true,"origin":"","legend":"","description":"","filename":"Fig3Sema.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/f85e8f717d0c52f0fa1e4609.tiff"},{"id":92577180,"identity":"ca23c7c6-f92e-4b59-a933-3e485e7340f1","added_by":"auto","created_at":"2025-10-01 08:38:16","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2266511,"visible":true,"origin":"","legend":"","description":"","filename":"CorleyetalSLIMLIVERFINAL.docx","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/72c8e6fc8cf7579b5e790400.docx"},{"id":92574897,"identity":"0d019fb4-eeeb-4fa1-b810-dbdaf875ac68","added_by":"auto","created_at":"2025-10-01 08:14:15","extension":"tiff","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":328642,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1Sema.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/5e19d7412c7ceccd5dbbeb15.tiff"},{"id":92574902,"identity":"a8825aca-12f8-49ab-8b11-95fbd075c9bd","added_by":"auto","created_at":"2025-10-01 08:14:15","extension":"tiff","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":423254,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2Sema.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/aac58c3b51d0817525db7011.tiff"},{"id":92574904,"identity":"d909ba46-6e8e-4503-9072-fec1234b3da8","added_by":"auto","created_at":"2025-10-01 08:14:15","extension":"tiff","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":431658,"visible":true,"origin":"","legend":"","description":"","filename":"Figure4Sema.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/0e82e42dfde1111234e17c8d.tiff"},{"id":92574896,"identity":"672fea5a-4a71-42b3-a757-3826ba08f207","added_by":"auto","created_at":"2025-10-01 08:14:15","extension":"json","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":12351,"visible":true,"origin":"","legend":"","description":"","filename":"376d98f724064fc8ba60bc3c3dc68cf5.json","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/064615e0f56a80728e75d0ab.json"},{"id":92576727,"identity":"e6fbfd1d-3d5d-4bcf-8486-7f3b6c539aed","added_by":"auto","created_at":"2025-10-01 08:30:15","extension":"xml","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":101787,"visible":true,"origin":"","legend":"","description":"","filename":"376d98f724064fc8ba60bc3c3dc68cf51enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/6735f074a59602dac560bc2b.xml"},{"id":92574900,"identity":"73f1883e-6706-4f9d-b1bd-163c7c6d0ef8","added_by":"auto","created_at":"2025-10-01 08:14:15","extension":"tiff","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":894122,"visible":true,"origin":"","legend":"","description":"","filename":"Fig3Sema.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/707a3df4c89b8ff1525b8cd1.tiff"},{"id":92576728,"identity":"e3e1fcbb-4b95-4c71-89ab-428ed46209ee","added_by":"auto","created_at":"2025-10-01 08:30:15","extension":"tiff","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":328642,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1Sema.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/34ece2844e95581ab9947e27.tiff"},{"id":92575505,"identity":"63120ce3-0c26-471b-a35e-514f23c780be","added_by":"auto","created_at":"2025-10-01 08:22:16","extension":"tiff","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":423254,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2Sema.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/f2b8612cbc31aba8ea1228ca.tiff"},{"id":92575499,"identity":"0dd1fa82-2fd5-415e-938c-4184be07460b","added_by":"auto","created_at":"2025-10-01 08:22:15","extension":"tiff","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":431658,"visible":true,"origin":"","legend":"","description":"","filename":"Figure4Sema.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/2c6520c6d43f038018a7e5ee.tiff"},{"id":92576729,"identity":"ff5a4fa2-5137-4c18-8ac6-2950b1057329","added_by":"auto","created_at":"2025-10-01 08:30:15","extension":"jpeg","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":328642,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1Sema.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/ce474e467d817cc9108d3b8f.jpeg"},{"id":92574913,"identity":"adfce677-8ce8-49ce-a28e-675e9cd082a0","added_by":"auto","created_at":"2025-10-01 08:14:15","extension":"jpeg","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":423254,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2Sema.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/4831a181f5bfb039cf21f3ee.jpeg"},{"id":92574907,"identity":"bf615116-3f42-4680-bb33-dc4a10c0fbf0","added_by":"auto","created_at":"2025-10-01 08:14:15","extension":"jpeg","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":894122,"visible":true,"origin":"","legend":"","description":"","filename":"Fig3Sema.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/08f9d71afee27e5a94bcfe02.jpeg"},{"id":92574920,"identity":"21ecfa52-560f-4860-9549-ac850465d642","added_by":"auto","created_at":"2025-10-01 08:14:16","extension":"jpeg","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":431658,"visible":true,"origin":"","legend":"","description":"","filename":"Figure4Sema.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/f726841816c71fd0011ea4e7.jpeg"},{"id":92574912,"identity":"1a4d14cc-74c7-405c-94ca-1fa53bc59e25","added_by":"auto","created_at":"2025-10-01 08:14:15","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":199969,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig3Sema.png","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/425b05244c063e853d7cba10.png"},{"id":92574917,"identity":"cbb8d246-07c5-4eca-a686-eef3a785555a","added_by":"auto","created_at":"2025-10-01 08:14:16","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":126710,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure1Sema.png","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/1bb294350dba0b4de806c98b.png"},{"id":92574918,"identity":"694402f3-6813-4e9e-b716-a727ed27997d","added_by":"auto","created_at":"2025-10-01 08:14:16","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":90942,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2Sema.png","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/0790656a062c2634ce93f6e1.png"},{"id":92574905,"identity":"57294b8f-17cd-48e4-b273-b5c075b7934f","added_by":"auto","created_at":"2025-10-01 08:14:15","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":85569,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure4Sema.png","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/38944dc6f5091ad326cbb999.png"},{"id":92574921,"identity":"0e060e16-f334-4dfa-94f3-46dbfed52d6e","added_by":"auto","created_at":"2025-10-01 08:14:16","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":126710,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure1Sema.png","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/03e8a1584fba95360c4cb689.png"},{"id":92574906,"identity":"a6f7c6a2-9916-466a-be08-c63e461dac0b","added_by":"auto","created_at":"2025-10-01 08:14:15","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":90942,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/5e9f13807e52a129a85c3eeb.png"},{"id":92574915,"identity":"5b70b7de-dd4e-4bab-ac14-b2b293fb9f72","added_by":"auto","created_at":"2025-10-01 08:14:16","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":199969,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/abb0b3722ad373b6445a5deb.png"},{"id":92574919,"identity":"e8c120c9-a40d-4ae8-ad52-e5cbac6257e3","added_by":"auto","created_at":"2025-10-01 08:14:16","extension":"png","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":85569,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/3e725d3fe44f68b48e95baa4.png"},{"id":92574914,"identity":"72f85d06-83ac-42f3-a4bc-8277b95c3a45","added_by":"auto","created_at":"2025-10-01 08:14:15","extension":"xml","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":95065,"visible":true,"origin":"","legend":"","description":"","filename":"376d98f724064fc8ba60bc3c3dc68cf51structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/d6a3de3241a08a14723e2010.xml"},{"id":92575503,"identity":"1b3634da-0630-41d8-a981-759a56178250","added_by":"auto","created_at":"2025-10-01 08:22:16","extension":"html","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":114032,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/58bc98af4b870c8f7cc8ba6c.html"},{"id":92575496,"identity":"8a8a00ba-a1a8-4cb9-8faf-193fb590e612","added_by":"auto","created_at":"2025-10-01 08:22:15","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":812549,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChanges in epigenetic aging biomarkers before and after 24 weeks of semaglutide treatment in people with HIV and MASLD with participant grouping by direction of epigenetic change.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A–B) DunedinPACE, a measure of the pace of aging (1.0 = normative rate), decreased following treatment with 17 participants (41.5%) demonstrating a reduction (panel A) indicating a slower pace of aging and 24 participants demonstrating an increase (panel B).\u003cbr\u003e\n(C–D) PCGrimAge, an epigenetic estimate of biological age and mortality risk, also declined with 14 participants (34.1%) showing reductions in predicted age (panel C) and 27 participants (65.8%) showing an increase (panel D).\u003cbr\u003e\n(E–F) PCDNAmTL, a methylation-derived estimate of telomere length (in kilobases) increased in 20 participants (48.8%) showing predicted telomere elongation (panel E) and 21 (51.2%) participants showing decrease (panel F).\u003c/p\u003e\n\u003cp\u003eCircles indicate participants with beneficial changes (slower pace of aging, reduced epigenetic age, or longer DNAm telomere length), while triangles indicate participants with changes in the opposite direction over the 24-week period. Data are shown as paired values with lines connecting participants.These groupings were used to examine whether directional shifts in epigenetic aging over the 24-week period were associated with differential clinical responses to semaglutide, including outcomes related to anthropometry, metabolic biomarkers, and physical function.\u003c/p\u003e","description":"","filename":"Figure1Sema.tiff.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/e9768fd1188eb1b6a9708816.jpg"},{"id":92575497,"identity":"aa39aead-a1fb-4d00-a108-a4539e82f689","added_by":"auto","created_at":"2025-10-01 08:22:15","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1018767,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferences in 24-week changes in IHTG and anthropometric percent following low-dose (1mg) weekly semaglutide by Epigenetic Age Group.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBoxplots display the percent change in intrahepatic triglycerides (IHTG; panels A–C), body mass index (BMI; panels D–F), and body weight (panels G–I) stratified by 24 week group changes in three epigenetic aging measures: DunedinPACE, PCGrimAge, and PCDNAmTL. Each panel shows median, interquartile range, and range of percent changes. Statistical comparisons were conducted using the Mann-Whitney nonparametric test, with p-values annotated above each panel.\u003c/p\u003e","description":"","filename":"Figure2Sema.tiff.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/f3ca89e2f90e88e927fb633c.jpg"},{"id":92574894,"identity":"05140a6c-0630-499b-b20c-1aebba7c81e4","added_by":"auto","created_at":"2025-10-01 08:14:15","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2076232,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGroup differences in lipids and glucose homeostasis percent changes following semaglutide by epigenetic age change.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBoxplots display the percent change in insulin resistance (HOMA-IR; panels A, G, M), glucose (panels B, H, N), HDL cholesterol (panels C, I, O), LDL cholesterol (panels D, J, P), triglycerides (panels E, K, Q), and HbA1c (panels F, L, R), stratified by 24-week group changes in DunedinPACE (panels A–F), PCGrimAge (panels G–L), and PCDNAmTL (panels M–R). Each panel shows median, interquartile range, and range of percent changes. Statistical comparisons were conducted using the Mann–Whitney nonparametric test, with \u003cem\u003ep\u003c/em\u003e-values annotated above each panel.\u003c/p\u003e","description":"","filename":"Fig3Sema.tiff.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/334329df7870590d07eadd38.jpg"},{"id":92575498,"identity":"2850f2d5-7ad0-40d3-afe9-acfb90919c6d","added_by":"auto","created_at":"2025-10-01 08:22:15","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1031236,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGroup differences in physical function percent changes following semaglutide by epigenetic age change.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBoxplots display the percent change in physical performance outcomes, including time to complete 10 chair stands (Chair10; panels A–C), time to complete 5 chair stands (Chair5; panels D–F) (% increase indicates slower time to complete), and walking speed (panels G–I) (% increase indicates faster time to complete), stratified by 24-week group changes in three epigenetic aging measures: DunedinPACE, PCGrimAge, and PCDNAmTL. Each panel shows median, interquartile range, and range of percent changes. Statistical comparisons were conducted using the Mann–Whitney nonparametric test, with \u003cem\u003ep\u003c/em\u003e-values annotated above each panel.\u003c/p\u003e","description":"","filename":"Figure4Sema.tiff.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/2977fdd08b8fe68a2618624a.jpg"},{"id":107929296,"identity":"7168a916-143f-4564-bfe6-e216bdf13a70","added_by":"auto","created_at":"2026-04-27 16:14:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5277538,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7697256/v1/1728e881-856c-4ea5-a039-21f33eba295e.pdf"}],"financialInterests":"Competing interest reported. MJ Corley serves as a scientific advisor for TruDiagnostic. \nAPS Pang declares no disclosures.\nKM Erlandson has received research funding from the NIH/NIA in support of the present manuscript; outside of the current work, she has received research funding from Gilead Sciences and has consulted for Gilead Sciences, Merck, and ViiV Pharmaceuticals, all paid to her institution.\nTT Brown has served as a consultant to Merck, ViiV Healthcare, EMD Serono, and Jannsen. \nPFB-Z is the Division of AIDS medical officer for the study; however, his views are personal and do not represent the NIH/NIAID's views.","formattedTitle":"Epigenetic Aging and Treatment Response to Semaglutide in the SLIM LIVER Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eGlucagon-like peptide-1 receptor agonists (GLP-1 RAs), such as semaglutide, have emerged as a transformative class of therapeutics that promote weight loss, improve glycemic control, and provide systemic benefits across multiple organ systems\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Beyond their established role in diabetes management, GLP-1 RAs have demonstrated cardiovascular protection, potential neuroprotective effects, and improvement in inflammation and endothelial function, positioning them as promising therapeutic agents for the geroscience field\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. The properties of GLP-1 RAs are particularly relevant for metabolic dysfunction\u0026ndash;associated steatotic liver disease (MASLD), a leading comorbidity in people with HIV (PWH) characterized by excess intrahepatic triglyceride (IHTG) accumulation, insulin resistance, oxidative stress, and systemic inflammation\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. While lifestyle-induced weight loss remains the cornerstone of MASLD management\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, semaglutide\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e has shown efficacy in reducing hepatic steatosis and improving broader metabolic parameters and physical function\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Such benefits may be especially important for PWH, who frequently experience an accelerated aging phenotype driven by chronic immune activation and metabolic dysregulation\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eRecent advances in epigenetic biomarker research have enabled the quantification of biological aging through DNA methylation-based \"epigenetic clocks\"\u003csup\u003e13\u003c/sup\u003e. These clocks serve as minimally invasive proxies of biological aging and have been linked to metabolic traits such as body mass index, visceral adiposity, insulin resistance, and liver disease severity\u003csup\u003e\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. In PWH, epigenetic age acceleration (EAA) is frequently observed, with estimates ranging from 3 to 7 years above chronological age\u003csup\u003e\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Recent evidence suggests that EAA may also reflect liver disease progression. In a study of 325 individuals with MASLD, advanced fibrosis was associated with a 5% faster pace of aging, as measured by DunedinPACE, and a 10% reduction in telomere length, captured by DNAmTL, compared to those without fibrosis\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Similarly, in a separate study of individuals with biopsy-confirmed non-alcoholic steatohepatitis (NASH), EAA measured by the Horvath clock correlated with hepatic collagen content, though not fibrosis stage, and revealed differentially methylated CpG sites enriched in developmental and transcriptional regulatory pathways\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. These findings underscore the potential of epigenetic aging measures as biomarkers of liver disease severity and therapeutic responsiveness. However, it remains unclear whether longitudinal changes in epigenetic biomarkers track with clinical improvements in response to interventions such as GLP-1 RA therapy.\u003c/p\u003e\u003cp\u003e To address this, we conducted a post hoc epigenetic analysis of participants from the SLIM LIVER study (Advancing Clinical Therapeutics Globally for HIV/AIDS and Other Infections (ACTG) A5371; NCT04216589), an open-label, single arm, Phase 2 clinical trial of semaglutide in PWH with MASLD. In the parent study, 24 weeks of low-dose semaglutide (1 mg subcutaneously weekly) significantly reduced IHTG by 31.3%, improved insulin sensitivity (approximately 1.5-unit decrease in Homeostatic Model Assessment of Insulin Resistance (HOMA-IR)), and lowered triglyceride levels by 27 mg/dL\u003csup\u003e11\u003c/sup\u003e. A secondary analysis also revealed preserved or improved physical function, with a significant reduction in the prevalence of slow gait speed (\u0026lt;\u0026thinsp;1 m/s) despite modest muscle loss\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. We hypothesized that within-individual changes in epigenetic aging biomarkers DunedinPACE, PCGrimAge, and DNAm telomere length (PCDNAmTL) over 24 weeks of semaglutide treatment would be associated with improvements in hepatic fat, metabolic markers, and physical function. This exploratory analysis aimed to assess the extent to which biological aging is modifiable in response to semaglutide and whether such changes are associated with therapeutic benefit in PWH with MASLD.\u003c/p\u003e"},{"header":"1. METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e1.1. Trial Population\u003c/h2\u003e\u003cp\u003eThe SLIM LIVER study ([ACTG] protocol A5371; NCT04216589) was a Phase 2b, single-arm, open-label, 24-week, pilot study designed to evaluate the effect of semaglutide on IHTG and metabolic health among PWH and MASLD\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Participants were enrolled from nine ACTG-affiliated clinical research sites between February 2021 and September 2022​. Eligible participants were aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years, living with HIV on stable antiretroviral therapy (ART) with suppressed HIV-1 RNA (\u0026lt;\u0026thinsp;50 copies/mL), had\u0026thinsp;\u0026ge;\u0026thinsp;5% IHTG as quantified by magnetic resonance imaging proton-density fat fraction (MRI-PDFF), and demonstrated central adiposity and either insulin resistance (HOMA-IR\u0026thinsp;\u0026gt;\u0026thinsp;3.0) or pre-diabetes (fasting glucose 100\u0026ndash;125 mg/dL or hemoglobin A1c (HbA1c ) 5.7\u0026ndash;6.4%). Exclusion criteria included previous GLP-1 RA use within 24 weeks, diabetes mellitus, significant alcohol use, and other causes of liver disease. Physical function was measured at baseline and week 24 by assessing the time to rise from a chair 5 and 10 times and 4-meter gait speed, where gait speed was calculated as the average of 2 measurements at usual pace. Slow gait speed was defined as walking\u0026thinsp;\u0026lt;\u0026thinsp;1 m/sec. Each site obtained institutional review board approval, and all participants provided written informed consent​.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e1.2. SLIM LIVER Epigenetic Sub-study Participant Selection\u003c/h2\u003e\u003cp\u003eWe evaluated the longitudinal changes in epigenetic age estimates at two time points, at baseline and after 24 weeks of low-dose semaglutide, for 41 participants enrolled with available peripheral blood mononuclear cells (PBMCs).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e1.3. DNA Methylation Profiling and Epigenetic Age\u003c/h2\u003e\u003cp\u003eDNA was isolated from PBMCs using a Zymo Research Quick-DNA microprep kit. 500 ng of DNA was treated with bisulfite using the EZ DNA Methylation kit from Zymo Research, following the manufacturer's instructions. The bisulfite-treated DNA samples were randomly assigned to a well on the Infinium HumanMethylationEPIC BeadChip, which was then amplified, hybridized, stained, washed, and imaged with the Illumina iScan SQ instrument to obtain raw image intensities. To pre-process the DNA methylation data, we used the \u003cem\u003eminfi\u003c/em\u003e pipeline\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, and low quality samples were identified using the \u003cem\u003eqcfilter()\u003c/em\u003e function from the ENmix package\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, using default parameters. A total of 82 samples (41 baseline and 41 follow up), representing 100% of the original samples, passed the quality assurance and quality control (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and were deemed to be high quality samples. Our focus was on the second-generation principal component-derived epigenetic clock, PCGrimAge\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, a measure of biological aging that incorporates DNA methylation-based estimates of biomarkers associated with age-related mortality risk, the third-generation clock, DunedinPACE\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, a measure of the pace of aging crucial for understanding the impact of interventions on epigenetic aging, and Lu\u0026rsquo;s telomere length predictor based on 140 CpGs \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Epigenetic clocks were calculated according to published methods\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e from processed DNA methylation data. To enhance the reliability of GrimAge and DNAmTL estimates, we utilized its principal-component versions using the custom R script available via GitHub (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/MorganLevineLab/PC-Clocks\u003c/span\u003e\u003cspan address=\"https://github.com/MorganLevineLab/PC-Clocks\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003csup\u003e23\u003c/sup\u003e. The pace of aging clock, DunedinPACE, was calculated using the \u003cem\u003ePACEProjector\u003c/em\u003e function from the DunedinPACE package available via GitHub (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/danbelsky/DunedinPACE\u003c/span\u003e\u003cspan address=\"https://github.com/danbelsky/DunedinPACE\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e1.4. Statistical Analysis\u003c/h2\u003e\u003cp\u003eThis post hoc analysis assessed whether changes in epigenetic aging markers over 24 weeks of semaglutide treatment were associated with differential responses across hepatic, metabolic, and physical function domains. Descriptive statistics were reported as medians with interquartile ranges (IQRs) for continuous variables and frequencies with percentages for categorical variables. Participants were stratified into \u0026ldquo;decreased\u0026rdquo; vs. \u0026ldquo;increased\u0026rdquo; epigenetic age change groups based on directionality of change in three biomarkers: DunedinPACE, PCGrimAge, and PCDNAmTL. Directionality (increase vs. decrease) was assessed separately for DunedinPACE, PCGrimAge, and PCDNAmTL. Group comparisons for percent changes in clinical measures (e.g., IHTG, HOMA-IR, HbA1c, BMI, physical function) were conducted using the Kruskal-Wallis test. For epigenetic biomarkers, changes from baseline to week 24 were analyzed using Wilcoxon signed-rank tests for within-group comparisons.\u003c/p\u003e\u003c/div\u003e"},{"header":"2. RESULTS","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1. SLIM LIVER Epigenetic Substudy Characteristics.\u003c/h2\u003e\u003cp\u003eCharacteristics of the overall SLIM LIVER cohort have been previously described\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Forty one of 51 enrolled participants had evaluable samples at both time points for our post hoc epigenetic analysis (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The median age was 52 years (interquartile range [IQR]: 42\u0026ndash;58). Obesity and central adiposity were common (by design), with a median body mass index (BMI) of 35 kg/m\u0026sup2; (IQR: 31\u0026ndash;39) and median waist circumference of 114 cm (IQR: 107\u0026ndash;124). All participants were on suppressive ART with HIV-1 RNA levels below 50 copies/mL, and the median CD4\u0026thinsp;+\u0026thinsp;T-cell count was 701 cells/mm\u0026sup3; (IQR: 586\u0026ndash;869). Metabolic parameters reflected elevated cardiometabolic risk, with a median HOMA-IR of 3.8 (IQR: 2.8\u0026ndash;6.1) and fasting glucose of 98 mg/dL (IQR: 93\u0026ndash;107). Median fasting triglycerides were 116 mg/dL (IQR: 95\u0026ndash;183), and alanine aminotransferase (ALT) was elevated in 53% of participants. ART regimens were predominantly integrase strand transfer inhibitor (INSTI)-based (82%), with smaller proportions on non-nucleoside reverse transcriptase inhibitor (NNRTI; 22%)- or protease inhibitor (PI; 4%)-based regimens.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Baseline PCGrimAge, DunedinPACE, and PCDNAmTL and changes over 24 weeks of semaglutide\u003c/h2\u003e\u003cp\u003eAt baseline, PCGrimAge, an epigenetic biomarker trained to predict mortality risk, indicated a biological age of 60.0 years (median; range: 34.3\u0026ndash;70.6). The median PCGrimAge acceleration reflecting the difference between epigenetic and chronological age was 7.5 years (IQR: 5.1\u0026ndash;9.4), suggesting elevated age-related mortality risk within the cohort for 40 of the 41 participants profiled. The DunedinPACE score, which quantifies the rate of aging (with 1.0 representing the normative pace), had a median value of 0.95 (IQR: 0.88\u0026ndash;1.00). Twenty two percent (9 of 41 participants) had a DunedinPACE score calculated at greater than 1.0 at baseline, indicating an accelerated pace of aging for these individuals. PCDNAmTL, a methylation-derived estimate of telomere length, showed a median value of 6.90 units (IQR: 6.80\u0026ndash;7.16), reflecting relatively uniform telomere-associated aging across participants. Over 24 weeks of semaglutide, participants maintained a stable pace of aging, with a median DunedinPACE change of +\u0026thinsp;0.018 (IQR: \u0026minus;\u0026thinsp;0.023 to +\u0026thinsp;0.053), stable PCDNAmTL (median \u0026minus;\u0026thinsp;0.006 kb; IQR: \u0026minus;\u0026thinsp;0.073 to +\u0026thinsp;0.054), and minimal change in PCGrimAge (median\u0026thinsp;+\u0026thinsp;0.54 years; IQR: \u0026minus;\u0026thinsp;0.33 to +\u0026thinsp;1.26).\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.3. Changes in Epigenetic Age Markers Are Associated with Hepatic and Functional Outcomes following 24 weeks of semaglutide\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 17 participants (9 male, 8 female; 41.5%) experienced a decrease in DunedinPACE with semaglutide, indicating a slower pace of aging from baseline. 14 participants (8 male, 6 female; 34.1%) demonstrated a decrease in PCGrimAge, indicating a reduction in epigenetic mortality risk, and 20 participants (11 male, 9 female; 48.8%) showed an increase in predicted DNA methylation-based telomere length (PCDNAmTL) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA - F).\u003c/p\u003e\u003cp\u003eWe examined whether changes in epigenetic aging over the 24 weeks were associated with differential responses to semaglutide treatment across key clinical domains, including anthropometry, metabolic biomarkers, and physical function. Participants were grouped based on direction of change (Increased vs. Decreased) for DunedinPACE, PCGrimAge, and PCDNAmTL. Participants with a decrease in DunedinPACE showed a significantly greater percent reduction in IHTG (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024) compared to those with increased DunedinPACE (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). No significant differences were observed for BMI (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.63) or weight (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.63) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). When stratified by PCGrimAge or PCDNAmTL change groups, no significant group differences were observed for any anthropometric outcome (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.35), including IHTG (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.88 for PCGrimAge, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.36 for PCDNAmTL), suggesting this association may be specific to DunedinPACE (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThere were no statistically significant differences in metabolic biomarkers by change group for DunedinPACE, PCGrimAge, or PCDNAmTL. This included HOMA-IR (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.94 for DunedinPACE, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.78 for PCDNAmTL), fasting glucose, triglycerides, high-density lipoprotein (HDL), and low-density lipoprotein LDL (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.14), indicating that semaglutide-induced improvements in these markers occurred broadly and were not contingent on three epigenetic age dynamics assessed (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). However, a trend toward greater reduction in HbA1c was observed among participants with increased PCDNAmTL (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.072), suggesting a possible relationship between telomere attrition and glycemic improvement (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFor physical function, no significant differences were found in 5-time or 10-time chair rise time by DunedinPACE, PCGrimAge or PCDNAmTL group (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.50) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). A non-significant trend toward improved gait speed was observed among those with decreased DunedinPACE (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.083) and a significant improvement in gait speed was observed among participants with increased PCDNAmTL (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), suggesting that preservation or elongation of telomere length may be linked to better maintenance of physical function following semaglutide treatment.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. DISCUSSION","content":"\u003cp\u003eIn this pilot post hoc epigenetic analysis of the SLIM LIVER trial, we evaluated whether changes in epigenetic aging biomarkers, specifically DunedinPACE, PCGrimAge and PCDNAmTL, were associated with anthropometric, metabolic, and physical function changes over 24 weeks of semaglutide treatment in PWH and MASLD. Our findings suggest that a less accelerated pace of aging, as captured by DunedinPACE, may be selectively associated with greater liver fat reduction following semaglutide treatment. While PCGrimAge change was not linked to anthropometric or metabolic outcomes, an increase in telomere length (PCDNAmTL) was significantly associated with improved gait speed, indicating that epigenetic telomere preservation may parallel enhancements in physical function. Conversely, participants with increased PCDNAmTL trended toward greater reductions in HbA1c, hinting at a possible link between semaglutide glycemic improvement and telomere biology. These findings suggest a potential relationship between semaglutide-related changes in specific epigenetic aging biomarkers and improvements in liver fat and physical function. These results merit further investigation of this association in larger cohorts and independent studies to validate the utility of epigenetic age biomarkers as indicators of therapeutic response in GLP-1RA therapy.\u003c/p\u003e\u003cp\u003eThe observed reduction in liver fat among select individuals with slowing DunedinPACE may reflect improved metabolic flexibility and hepatic lipid mobilization in reponse to semaglutide. DunedinPACE, is a third-generation DNA methylation-based biomarker that quantifies the pace of biological aging by integrating longitudinal physiological, cellular, and molecular data across multiple organ systems\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Unlike first generation epigenetic clocks, it captures short-term changes in systemic function and has been shown to respond to behavioral and pharmacologic interventions\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Our findings are consistent with prior work demonstrating associations between accelerated DunedinPACE and liver fibrosis severity, insulin resistance, and cardiometabolic risk\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The lack of similar associations with body weight or BMI following semaglutide treatment in this study suggests that DunedinPACE may be more sensitive to underlying shifts in tissue-specific metabolic health such as intrahepatic lipid dynamics than to gross anthropometric changes alone. These findings support further exploration of DunedinPACE as a potential biomarker for semaglutide-related improvements in metabolic aging beyond weight loss alone.\u003c/p\u003e\u003cp\u003eInterestingly, we did not observe significant group differences in glycemic or lipid parameters when stratified by epigenetic age change following semaglutide. Improvements in HOMA-IR, fasting glucose, and triglycerides were seen broadly across the cohort following semaglutide\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, regardless of whether DunedinPACE or PCGrimAge declined over the study period. These findings suggest that semaglutide\u0026rsquo;s core metabolic benefits may operate, at least in part, through mechanisms independent of its impact on the three DNA methylation-based epigenetic measures assessed. Alternatively, the lack of association may reflect limited power to detect domain-specific effects given the modest sample size. Importantly, while semaglutide has demonstrated robust metabolic efficacy, its potential as a multi-system gerotherapeutic is only beginning to be explored\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Emerging data suggest that GLP-1 RAs may influence aging biology in other organ systems such as the brain, cardiovascular system, and kidneys via effects on inflammation, oxidative stress, and cellular senescence\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. The SLIM LIVER study provides supporting preliminary evidence that semaglutide may also modulate biological aging trajectories in the liver and musculoskeletal system, as reflected by links to liver fat reduction and gait speed improvement. Future work incorporating broader multi-organ epigenetic and transcriptomic profiling may clarify how GLP-1 RAs influence systemic aging biology beyond metabolic control alone.\u003c/p\u003e\u003cp\u003eWe also observed a modest trend toward improved walking speed among participants who exhibited a reduction in DunedinPACE. Although this association did not reach statistical significance, the directionality is biologically plausible and consistent with prior studies linking accelerated epigenetic aging to frailty, slower gait speed, and functional decline in older adults\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The absence of group differences in chair rise times may be due to skeletal muscle effects, task variability, or limited power. Taken together, these findings suggest that semaglutide-associated slowing of biological aging may contribute to preserved or enhanced mobility. Future studies in borader populations, more granular functional assessments, and extended follow-up durations are needed to fully characterize the relationship between changes in epigenetic aging markers and physical performance trajectories.\u003c/p\u003e\u003cp\u003eIn addition to DunedinPACE and PCGrimAge, we evaluated changes in methylation-derived telomere length (PCDNAmTL). While changes in PCDNAmTL were not associated with differences in hepatic or anthropometric outcomes, we observed a trend toward greater HbA1c reduction among participants with telomere increases, potentially linking glycemic improvement to telomere biology\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. In addition, participants with increased PCDNAmTL indicating preserved or elongated telomeres demonstrated a significant improvement in walking speed, suggesting a possible protective effect of telomere maintenance on physical function. In the SLIM LIVER study we found the prevalence of slow gait speed (\u0026lt;\u0026thinsp;1 m/sec) decreased from 63% to 46% (P\u0026thinsp;=\u0026thinsp;.029)\u003csup\u003e10\u003c/sup\u003e. These findings align with prior evidence linking longer telomeres to better mobility, mitochondrial integrity, and muscle performance in aging populations\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Although exploratory, the directionality of these associations suggests that different dimensions of epigenetic aging may differentially track metabolic versus functional responsiveness to treatment. Larger studies are needed to validate these relationships and clarify whether PCDNAmTL may serve as a prognostic marker for physical resilience in the context of semaglutide.\u003c/p\u003e\u003cp\u003eAn important consideration in interpreting these results is the use of a relatively low semaglutide dose (1.0 mg weekly) and a 24-week treatment duration, which may have attenuated the magnitude of clinical effects compared to trials using higher doses over longer periods. For example, phase 3 trials such as the STEP and ESSENCE programs have demonstrated greater reductions in liver fat, weight, and glycemic indices with weekly 2.4 mg dosing over 48 to 72 weeks\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. However, for anti-aging applications, prolonged tolerability and safety are critical, and lower, sustained dosing regimens may be more appropriate for long-term use. As such, while higher doses could potentially amplify clinical and epigenetic responses, the current design may reflect a more pragmatic framework for gerotherapeutic implementation. Future studies should explore dose\u0026ndash;response effects, compare acute versus chronic trajectories of epigenetic change, and evaluate the durability of biological aging modifications with extended follow-up in target populations, including PWH.\u003c/p\u003e\u003cp\u003eTaken together, our findings provide preliminary evidence that semaglutide may influence biological aging trajectories in a subset of individuals, particularly through deceleration of the pace of aging as measured by DunedinPACE. This slowing was selectively associated with greater reductions in liver fat, suggesting that epigenetic aging dynamics may reflect or contribute to organ-specific treatment responsiveness. Given the disproportionate burden of metabolic dysfunction in PWH and the expanding therapeutic role of GLP-1RA in liver disease, these results highlight the importance of integrating biological aging metrics into future interventional studies. Epigenetic clocks such as DunedinPACE and DNAmTL may serve as minimally invasive biomarkers to stratify risk, monitor longitudinal response, and guide personalized approaches aimed at improving both metabolic and functional health outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAUTHORS’ CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization (MJC, AL, KME); data curation, formal analysis, visualization, and methodology (AJC, APP, DWK, AK); funding acquisition (JEL, KME); investigation (all authors); project administration (MJC, JEL, KME); writing – original draft (MJC, APP); writing – review and editing (all authors). MJC had full access to and verified all the data in the study. All authors had final responsibility for the decision to submit for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study investigators thank the study participants, site staff, and study-associated personnel for their ongoing participation in the trial. In addition, we thank the following: the ACTG for clinical site support; ACTG Clinical Trials Specialists (Christina Vernon, Katharine Bergstrom) for protocol development and implementation support; the data management center, Frontier Science Foundation, for data support; the Center for Biostatistics in AIDS Research for statistical support; and the Community Advisory Board for input for the community.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNIH GRANTS POLICY STATEMENT\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Institutes of Health; or the U.S. Department of Health and Human Services.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eThis manuscript is the result of funding in whole or in part by the National Institutes of Health and is subject to the NIH Public Access Policy.\u0026nbsp;\u003c/u\u003eThis work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under [UM1 AI068634, UM1 AI068636, UM1 AI106701] with additional funding provided by McGovern School of Medicine at UTHealth. Additional support was provided by National Institute of Allergy and Infectious Diseases [K24 AI120834 to TTB] and the National Institute on Aging under [K24 AG082527 to KME].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCOMPETING INTERESTS:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMJ Corley serves as a scientific advisor for TruDiagnostic.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAPS Pang declares no disclosures.\u003c/p\u003e\n\u003cp\u003eKM Erlandson has received research funding from the NIH/NIA in support of the present manuscript; outside of the current work, she has received research funding from Gilead Sciences and has consulted for Gilead Sciences, Merck, and ViiV Pharmaceuticals, all paid to her institution.\u003c/p\u003e\n\u003cp\u003eTT Brown has served as a consultant to Merck, ViiV Healthcare, EMD Serono, and Jannsen.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePFB-Z is the Division of AIDS medical officer for the study; however, his views are personal and do not represent the NIH/NIAID's views.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e[\u003c/strong\u003eThe data from this study was submitted to the NCBI Gene Expression Omnibus (GEO) http://www.ncbi.nlm.nih.gov/geo/ \u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSanyal, A. J. \u003cem\u003eet al.\u003c/em\u003e Phase 3 trial of semaglutide in metabolic dysfunction-associated steatohepatitis. \u003cem\u003eN. Engl. J. Med.\u003c/em\u003e (2025) doi:10.1056/NEJMoa2413258.\u003c/li\u003e\n\u003cli\u003eMarso, S. P. \u003cem\u003eet al.\u003c/em\u003e Semaglutide and cardiovascular outcomes in patients with type 2 diabetes. \u003cem\u003eThe New England journal of medicine\u003c/em\u003e vol. 375 1834\u0026ndash;1844 (2016).\u003c/li\u003e\n\u003cli\u003eDavies, M. \u003cem\u003eet al.\u003c/em\u003e Semaglutide 2\u0026middot;4 mg once a week in adults with overweight or obesity, and type 2 diabetes (STEP 2): a randomised, double-blind, double-dummy, placebo-controlled, phase 3 trial. \u003cem\u003eLancet\u003c/em\u003e \u003cstrong\u003e397\u003c/strong\u003e, 971\u0026ndash;984 (2021).\u003c/li\u003e\n\u003cli\u003eDrucker, D. J. Expanding applications of therapies based on GLP1. \u003cem\u003eNat. Rev. Endocrinol.\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 65\u0026ndash;66 (2025).\u003c/li\u003e\n\u003cli\u003eDe Giorgi, R. \u003cem\u003eet al.\u003c/em\u003e An analysis on the role of glucagon-like peptide-1 receptor agonists in cognitive and mental health disorders. \u003cem\u003eNat. Ment. Health\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, 354\u0026ndash;373 (2025).\u003c/li\u003e\n\u003cli\u003eWilding, J. P. H. \u003cem\u003eet al.\u003c/em\u003e Once-weekly semaglutide in adults with overweight or obesity. \u003cem\u003eN. Engl. J. Med.\u003c/em\u003e \u003cstrong\u003e384\u003c/strong\u003e, 989\u0026ndash;1002 (2021).\u003c/li\u003e\n\u003cli\u003eHsu, C. L. \u0026amp; Loomba, R. From NAFLD to MASLD: implications of the new nomenclature for preclinical and clinical research. \u003cem\u003eNat. Metab.\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 600\u0026ndash;602 (2024).\u003c/li\u003e\n\u003cli\u003eRajewski, P. \u003cem\u003eet al.\u003c/em\u003e Dietary interventions and physical activity as crucial factors in the prevention and treatment of metabolic dysfunction-associated steatotic liver disease. \u003cem\u003eBiomedicines\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, (2025).\u003c/li\u003e\n\u003cli\u003eKuo, C.-C. \u003cem\u003eet al.\u003c/em\u003e Semaglutide versus other GLP-1 receptor agonists in patients with MASLD. \u003cem\u003eHepatol. Commun.\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, e0747 (2025).\u003c/li\u003e\n\u003cli\u003eDitzenberger, G. L. \u003cem\u003eet al.\u003c/em\u003e Effects of Semaglutide on Muscle Structure and Function in the SLIM LIVER Study. \u003cem\u003eClin. Infect. Dis.\u003c/em\u003e (2024) doi:10.1093/cid/ciae384.\u003c/li\u003e\n\u003cli\u003eLake, J. E. \u003cem\u003eet al.\u003c/em\u003e The Effect of Open-Label Semaglutide on Metabolic Dysfunction-Associated Steatotic Liver Disease in People With HIV. \u003cem\u003eAnn. Intern. Med.\u003c/em\u003e (2024) doi:10.7326/M23-3354.\u003c/li\u003e\n\u003cli\u003eDeeks, S. G. Immune dysfunction, inflammation, and accelerated aging in patients on antiretroviral therapy. \u003cem\u003eTop. HIV Med.\u003c/em\u003e \u003cstrong\u003e17\u003c/strong\u003e, 118\u0026ndash;123 (2009).\u003c/li\u003e\n\u003cli\u003eTeschendorff, A. E. \u0026amp; Horvath, S. Epigenetic ageing clocks: statistical methods and emerging computational challenges. \u003cem\u003eNat. Rev. Genet.\u003c/em\u003e (2025) doi:10.1038/s41576-024-00807-w.\u003c/li\u003e\n\u003cli\u003eHorvath, S. \u003cem\u003eet al.\u003c/em\u003e Obesity accelerates epigenetic aging of human liver. \u003cem\u003eProc. Natl. Acad. Sci. U. S. A.\u003c/em\u003e \u003cstrong\u003e111\u003c/strong\u003e, 15538\u0026ndash;15543 (2014).\u003c/li\u003e\n\u003cli\u003eLoomba, R. \u003cem\u003eet al.\u003c/em\u003e DNA methylation signatures reflect aging in patients with nonalcoholic steatohepatitis. \u003cem\u003eJCI Insight\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, e96685 (2018).\u003c/li\u003e\n\u003cli\u003eWang, H. \u003cem\u003eet al.\u003c/em\u003e Association between advanced fibrosis and epigenetic age acceleration among individuals with MASLD. \u003cem\u003eJ. Gastroenterol.\u003c/em\u003e \u003cstrong\u003e60\u003c/strong\u003e, 306\u0026ndash;314 (2025).\u003c/li\u003e\n\u003cli\u003eHorvath, S. \u0026amp; Levine, A. J. HIV-1 Infection Accelerates Age According to the Epigenetic Clock. \u003cem\u003eJ. Infect. Dis.\u003c/em\u003e \u003cstrong\u003e212\u003c/strong\u003e, 1563\u0026ndash;1573 (2015).\u003c/li\u003e\n\u003cli\u003eCorley, M. J. \u003cem\u003eet al.\u003c/em\u003e Effect of Pitavastatin on Epigenetic Aging Biomarkers in People With HIV: Pilot Substudy of the REPRIEVE Trial. \u003cem\u003eClinical Infectious Diseases\u003c/em\u003e ciaf247 (2025).\u003c/li\u003e\n\u003cli\u003eJohnston, C. D. \u003cem\u003eet al.\u003c/em\u003e Sex differences in epigenetic ageing for older people living with HIV. \u003cem\u003eEBioMedicine\u003c/em\u003e \u003cstrong\u003e113\u003c/strong\u003e, 105588 (2025).\u003c/li\u003e\n\u003cli\u003eAryee, M. J. \u003cem\u003eet al.\u003c/em\u003e Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. \u003cem\u003eBioinformatics\u003c/em\u003e \u003cstrong\u003e30\u003c/strong\u003e, 1363\u0026ndash;1369 (2014).\u003c/li\u003e\n\u003cli\u003eXu, Z., Niu, L., Li, L. \u0026amp; Taylor, J. A. ENmix: a novel background correction method for Illumina HumanMethylation450 BeadChip. \u003cem\u003eNucleic Acids Res.\u003c/em\u003e \u003cstrong\u003e44\u003c/strong\u003e, e20 (2016).\u003c/li\u003e\n\u003cli\u003eLu, A. T. \u003cem\u003eet al.\u003c/em\u003e DNA methylation GrimAge strongly predicts lifespan and healthspan. \u003cem\u003eAging \u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 303\u0026ndash;327 (2019).\u003c/li\u003e\n\u003cli\u003eHiggins-Chen, A. T. \u003cem\u003eet al.\u003c/em\u003e A computational solution for bolstering reliability of epigenetic clocks: Implications for clinical trials and longitudinal tracking. \u003cem\u003eNat Aging\u003c/em\u003e \u003cstrong\u003e2\u003c/strong\u003e, 644\u0026ndash;661 (2022).\u003c/li\u003e\n\u003cli\u003eBelsky, D. W. \u003cem\u003eet al.\u003c/em\u003e DunedinPACE, a DNA methylation biomarker of the pace of aging. \u003cem\u003eElife\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, (2022).\u003c/li\u003e\n\u003cli\u003eLu, A. T. \u003cem\u003eet al.\u003c/em\u003e DNA methylation-based estimator of telomere length. \u003cem\u003eAging \u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 5895\u0026ndash;5923 (2019).\u003c/li\u003e\n\u003cli\u003eDwaraka, V. B. \u003cem\u003eet al.\u003c/em\u003e Unveiling the epigenetic impact of vegan vs. omnivorous diets on aging: insights from the Twins Nutrition Study (TwiNS). \u003cem\u003eBMC Med.\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 301 (2024).\u003c/li\u003e\n\u003cli\u003eBischoff-Ferrari, H. A. \u003cem\u003eet al.\u003c/em\u003e Individual and additive effects of vitamin D, omega-3 and exercise on DNA methylation clocks of biological aging in older adults from the DO-HEALTH trial. \u003cem\u003eNat. Aging\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 376\u0026ndash;385 (2025).\u003c/li\u003e\n\u003cli\u003eScheltens, P. \u003cem\u003eet al.\u003c/em\u003e Baseline characteristics from evoke and evoke+: Two phase 3 randomized placebo-controlled trials of oral semaglutide in patients with early Alzheimer\u0026rsquo;s disease (P11-9.013). \u003cem\u003eNeurology\u003c/em\u003e \u003cstrong\u003e102\u003c/strong\u003e, 3350 (2024).\u003c/li\u003e\n\u003cli\u003eDrucker, D. J. GLP-1-based therapies for diabetes, obesity and beyond. \u003cem\u003eNat. Rev. Drug Discov.\u003c/em\u003e 1\u0026ndash;20 (2025).\u003c/li\u003e\n\u003cli\u003eMak, J. K. L. \u003cem\u003eet al.\u003c/em\u003e Temporal dynamics of epigenetic aging and frailty from midlife to old age. \u003cem\u003eJ. Gerontol. A Biol. Sci. Med. Sci.\u003c/em\u003e \u003cstrong\u003e79\u003c/strong\u003e, glad251 (2024).\u003c/li\u003e\n\u003cli\u003ePhyo, A. Z. Z. \u003cem\u003eet al.\u003c/em\u003e Epigenetic age acceleration and the risk of frailty, and persistent activities of daily living (ADL) disability. \u003cem\u003eAge Ageing\u003c/em\u003e \u003cstrong\u003e53\u003c/strong\u003e, afae127 (2024).\u003c/li\u003e\n\u003cli\u003eCheng, F. \u003cem\u003eet al.\u003c/em\u003e Shortened leukocyte telomere length is associated with glycemic progression in type 2 diabetes: A prospective and Mendelian randomization analysis. \u003cem\u003eDiabetes Care\u003c/em\u003e \u003cstrong\u003e45\u003c/strong\u003e, 701\u0026ndash;709 (2022).\u003c/li\u003e\n\u003cli\u003eDempsey, P. C. \u003cem\u003eet al.\u003c/em\u003e Investigation of a UK biobank cohort reveals causal associations of self-reported walking pace with telomere length. \u003cem\u003eCommun. Biol.\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 381 (2022).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003e\u003cstrong\u003eTable 1: Baseline Participant Characteristics\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"913\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 316px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline Characteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll participants\u003cbr\u003e\u0026nbsp;(N = 41)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 249px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIHTG% Change\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean (SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 316px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 249px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-28.8 (27.3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 316px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e52 (41.0, 57.5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 249px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;50\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18 (44%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 249px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-24.4 (28.5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;50\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e23 (56%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 249px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-32.2 (26.5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 316px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNatal sex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25 (61%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 249px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-24.1 (30.0)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16 (39%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 249px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-36.2 (21.3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eWhite\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e30 (73%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBlack\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e16 (39%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMultiple\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e1 (2%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAmerican Indian/ Alaska Native\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e1 (2%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eUnknown\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e3 (7%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eNot Hispanic or Latino\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e31 (61%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHispanic or Latino\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e20 (39%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 316px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHIV-1 RNA (copies/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;20\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e30 (73%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 249px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-27.3 (27.8)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;50\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11 (27%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 249px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-33.0 (26.9)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 316px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCD4 count (cells/mm\u0026sup3;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e701 (606, 848)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 249px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;500\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5 (12%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 249px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-31.5 (34.5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;500\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e36 (78%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 249px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-28.4 (26.8)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 316px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCD4/CD8 ratio (cells/mm\u0026sup3;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.21 (0.714, 1.72)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 249px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12 (29%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 249px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-33.1 (26.0)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e29 (71%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 249px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-27.0 (28.1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-aging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Aging](https://www.nature.com/npjamd/)","snPcode":"41514","submissionUrl":"https://submission.springernature.com/new-submission/41514/3","title":"npj Aging","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Epigenetics, HIV, Aging, Semaglutide, GLP-1, DNA methylation, Epigenetic clock, geroscience, liver, MASLD","lastPublishedDoi":"10.21203/rs.3.rs-7697256/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7697256/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eSemaglutide, a glucagon-like peptide-1 receptor agonist (GLP-1 RA), improves metabolic health and reduces liver fat in people with HIV (PWH) and metabolic dysfunction-associated steatotic liver disease (MASLD). Whether changes in epigenetic aging biomarkers reflect these clinical benefits remains unknown.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe conducted a post hoc analysis of the SLIM LIVER study (ACTG A5371), a 24-week, single-arm trial of semaglutide (1.0 mg weekly) in PWH and MASLD. Epigenetic aging was assessed at baseline and 24 weeks using DNA methylation–based epigenetic clocks: DunedinPACE (pace of aging), PCGrimAge (mortality risk), and PCDNAmTL (methylation-derived telomere length). Participants were stratified by change in epigenetic markers (decrease vs. increase); clinical responses were compared across anthropometric, metabolic, and physical function outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eWe observed a stable pace of aging was maintained over 24 weeks (n=41) with a median change of DunedinPACE of +0.018 (IQR: –0.023 to +0.053), PCDNAmTL (median –0.006 kb; IQR: –0.073 to +0.054), and PCGrimAge (median +0.54 years; IQR: –0.33 to +1.26). Seventeen (41.5%) showed a decrease in DunedinPACE with significantly greater reductions in liver fat (\u003cem\u003ep\u003c/em\u003e = 0.024) and improved gait speed (\u003cem\u003ep\u003c/em\u003e = 0.081), corresponding to a ~0.8 day (minimum, –0.0048) to ~19.5 days (maximum, –0.116) deceleration. Participants with increased PCDNAmTL (n=20) similarly demonstrated significantly greater improvements in gait speed (\u003cem\u003ep\u003c/em\u003e= 0.012). No significant clinical associations were observed with changes in PCGrimAge.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThese findings provide preliminary evidence that semaglutide may modulate epigenetic age biomarkers, with DunedinPACE and PCDNAmTL tracking improvements in hepatic and physical function. Integration of epigenetic biomarkers into future trials may enhance gerotherapeutic precision by identifying individuals most likely to benefit from GLP-1RA therapy and by enabling minimally invasive monitoring of biological aging.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial Registration: \u003c/strong\u003eClinicalTrials.gov ID: NCT04216589\u003c/p\u003e","manuscriptTitle":"Epigenetic Aging and Treatment Response to Semaglutide in the SLIM LIVER Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-01 08:14:10","doi":"10.21203/rs.3.rs-7697256/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-22T13:46:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-21T14:34:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"180786513261075701377654593734403902937","date":"2025-10-21T10:28:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-21T04:50:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-19T13:16:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-14T14:47:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"55054650136673066826144029272603282020","date":"2025-10-14T09:29:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"203049180460197449276449621032441764551","date":"2025-10-13T16:07:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"196939269657640413070577961254753220775","date":"2025-10-13T14:35:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"201722246362335001238194218238281196420","date":"2025-10-13T13:53:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"205583160686217215320726867649306805969","date":"2025-10-13T07:09:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-08T15:43:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-07T14:34:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-29T03:32:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Aging","date":"2025-09-23T18:55:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-aging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Aging](https://www.nature.com/npjamd/)","snPcode":"41514","submissionUrl":"https://submission.springernature.com/new-submission/41514/3","title":"npj Aging","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2010a55b-d9e6-45ae-a1de-a7a58cf12278","owner":[],"postedDate":"October 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":55470082,"name":"Health sciences/Biomarkers"},{"id":55470083,"name":"Health sciences/Diseases"},{"id":55470084,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-04-27T16:13:06+00:00","versionOfRecord":{"articleIdentity":"rs-7697256","link":"https://doi.org/10.1038/s41514-026-00383-9","journal":{"identity":"npj-aging","isVorOnly":false,"title":"npj Aging"},"publishedOn":"2026-04-21 15:58:48","publishedOnDateReadable":"April 21st, 2026"},"versionCreatedAt":"2025-10-01 08:14:10","video":"","vorDoi":"10.1038/s41514-026-00383-9","vorDoiUrl":"https://doi.org/10.1038/s41514-026-00383-9","workflowStages":[]},"version":"v1","identity":"rs-7697256","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7697256","identity":"rs-7697256","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}