It is found that socioeconomic adversity influences not only inflammatory pathways but also distinct biological aging processes, including metabolomic aging, and that socioeconomic adversity influences not only inflammatory pathways but also distinct biological aging processes.
Abstract
Objectives: We tested how multi-level socioeconomic disadvantage relates to biological aging and systemic inflammation in women and men from the population-based Canadian Longitudinal Study on Aging (CLSA). Methods: We examined cross-sectional data from 8,516 CLSA participants with baseline measures on systemic inflammatory biomarkers (C-reactive protein, interleukin-6, and tumoral necrosis factor-) and biological aging (metabolomic and six DNA methylation [DNAm] age estimates). Plasma samples underwent metabolomic profiling by Metabolon, Inc. Metabolomic age was estimated separately in males and females using sex-stratified models based on age-correlated metabolite levels. DNAm data generated using the Illumina Infinium MethylationEPIC v1.0 array were used to estimate DNAm age across six established models, including Horvath, Hannum, PhenoAge, GrimAge, GrimAge2, and DunedinPACE. We used log-transformed metabolite levels to calculate metabolomic age by sex. We linked education, income, material and social deprivation to biomarkers of systemic inflammation and biological aging stratified by sex using generalized linear models. Multivariable models were adjusted by age, major behavioral risk factors, and chronic conditions. Results: Participants were aged on average of 62.6 years of age, and approximately 50% were females. In multivariable linear adjusted models, we found that in comparison to those earning [≥]$100K a year, women earning less <$20K were on average 1.14 (95%CI: 0.46, 1.82) year older with respect to metabolomic age; those earning [≥]$20K & <$50K were on average 0.90 (95%CI: 0.26, 1.53) years older; and those earning [≥]$50K & <$100K were on average 0.70 (95%CI: 0.05, 1.34) years older. We did not observe this dose response among men. A similar dose-response association was observed for interleukin-6 in both men and women. Discussion: These findings suggest that socioeconomic adversity influences not only inflammatory pathways but also distinct biological aging processes, including metabolomic aging.
BACKGROUND
Inflammation is a key driver of age-related disease and has been associated with social conditions. We examined how cumulative community-level social and structural disadvantage is associated with inflammatory proteomic profiles in older Black adults.
METHODS
We employed data from the Minority Aging Research Study and the Rush Clinical Core, including the Social Vulnerability Index (SVI; global score and four domains) and 92 plasma inflammatory proteins (Olink® Target-96 Inflammation). Cross-sectional associations between each SVI metric and inflammatory proteins (principal component (PC)-derived global proteomic profile and protein-specific) were assessed using multivariable linear models (demographic, behavioral, and individual-level socioeconomic factors adjusted), with additional sex-by-SVI interaction terms. In a secondary analysis, we replaced SVI with the Index of Concentration at the Extremes (ICE) for household income (ICEincome).
RESULTS
A total of 580 participants (mean (SD) age of 74.9 (6.50) years; 79.7% women) had global SVI and proteomics assessed. Lower household composition (SVIHHC) was associated with the primary global proteomic profile, represented by the 1st proteomic PC (beta = -0.429, p-value = 0.019). A secondary exploratory analysis using the first five proteomic PCs showed that higher minority status/language (SVIMSL) and socioeconomic status (SVISES) were associated with an inflammatory proteomic profile (SVIMSL-PC3: beta=0.160, p-value = 0.048; SVISES-PC2: beta = 0.286, p-value = 0.012). In protein-specific analyses, no SVI-protein associations were found. We found an SVIHHC-by-sex interaction for interleukin-10 receptor alpha (IL-10RA; beta = -0.258, p-value = 5.01×10-4), and among men, SVIMSL was associated with Sirtuin 2 (beta = -0.397, p-value = 8.51×10-04) and STAM binding protein (beta = -0.304, p-value = 9.87×10-04). ICEincome was inversely associated with the global proteomic profile (beta = -0.233, p-value = 0.051), and an ICEincome-by-sex interaction was found for IL-10RA (beta=0.279, p-value = 4.66×10-04).
CONCLUSIONS
By analyzing associations between community-level factors and inflammation-related proteins, our study provides new molecular insights into how social context may relate to biological risk, identifies proteomic patterns that could inform the development of community-level interventions, and underscores the utility of integrating multi-omics approaches to investigate biological pathways relevant to health disparities research.
Anat Yaskolka Meir, H. Adeola, S. Tasaki et al.· BMC Medicine· 0 citations
BACKGROUND
Global population aging underscores the urgent need for biomarkers quantifying biological aging trajectories. While DNA methylation-derived pace of aging (DunedinPoAm) measures individual differences, its generalizability across diverse populations and mechanistic links to systemic inflammation remain underexplored. This study aimed to systematically examine the longitudinal associations between the DunedinPoAm and all‑cause mortality in a multiethnic cohort, and to quantify the extent to which systemic inflammatory biomarkers mediate these associations using causal mediation analysis.
METHODS
For this cohort study, information on a nationally representative cohort of 21,004 U.S. adults was extracted from the National Health and Nutrition Examination Survey (NHANES) conducted from 1999 to 2002, along with the NHANES Linked Mortality File, which ascertained mortality through December 31, 2019. The exposures were Pace of aging (DunedinPoAm) and inflammation. The survival outcome measured was all-cause mortality. We employed Cox proportional hazards models, Kaplan-Meier survival curves, restricted cubic splines, and Bayesian mediation frameworks to evaluate mortality risk, explore non-linear dose-response relationships, and investigate inflammatory mediation.
RESULTS
Data were analyzed from 2,532 participants, with a mean follow-up duration of 18.5 ± 1.29 years. Higher DunedinPoAm quartiles exhibited graded mortality risks (Q4 vs. Q1: HR = 2.50, 95% CI 1.84-3.38), which persisted after multivariable adjustment. Restricted cubic splines revealed a non-linear association (P for overall < 0.001; P for nonlinearity < 0.001), indicating the presence of threshold effects. Systemic inflammation mediated 2.33-23.5% of the mortality risk associated with DunedinPoAm, driven by CD4 + T cells, B cells, CRP and comprehensive inflammatory indices. A significant interaction with diabetes (P for interaction = 0.026) underscored metabolic dysregulation as a vulnerability factor.
CONCLUSION
DunedinPoAm predicts all-cause mortality in a non-linearly manner across multiethnic populations, partially mediated by pathways associated with inflammaging. The observed diabetes-specific interactions and threshold effects indicate the potential for precision approaches targeting high-risk subgroups. These findings support the integration of DunedinPoAm into gerotherapeutic trials and public health strategies aimed at addressing disparities in aging.
Jihua Feng, Yuting Liang, Jie Zhou et al.· Clinical Epigenetics· 0 citations
Type 2 diabetes mellitus (T2DM) is an aging-related disease with greater incidence in older African Americans (AAs) than whites, but studies on racial disparity in epigenetic aging pathways are scarce; specifically, socio-biological aging processes are not well characterized. We investigated biological aging acceleration (aging accel) with development of T2DM and additionally, insulin resistance (IR) of nondiabetic women at baseline in cross-section. We estimated the extent to which social adversity explained AAs' greater aging accel and, together with accelerated aging, mediated their greater burden of glucometabolic outcomes. Clinical and social determinants of health (SDOH) variables and genome-wide DNA methylation data were extracted from the Women's Health Initiative with > 1,500 postmenopausal non-diabetic women. Diabetic outcome was followed for a mean of 19 years, and baseline IR was measured using fasting serum samples. Aging accel metrics were calculated with Levine's clock, and mediation effects of SDOH and aging accel was estimated via Multiple Mediation analyses. Greater aging accel was observed in T2DM, albeit with only univariate significance and IR and in AAs rather than whites. SDOH was associated with greater aging accel, but its impact on greater accelerated aging in AAs varied and in combination, was minimal. Although aging accel has greater influence than SDOH on the racial difference in glucometabolic outcomes, these parameters jointly mediated to only a limited extent T2DM/IR pathways by race. Our mediation findings are exploratory and hypothesis-generating and thus, our results warrant validation studies to better understand socio-glucometabolic pathways shared by epigenetic aging processes and to inform early risk stratification among at-risk older women for disease prevention and reduced racial health inequity.
An LE8-derived DNAm score was associated with lower cIMT across the life course and, to a lesser extent, across generations, suggesting that blood DNAm reflects cumulative cardiovascular health and vascular burden and may complement conventional cardiovascular risk assessment.
B. Mishra, E. Raitoharju, L.-P. LyytikaÌinen et al.· medRxiv· 0 citations
Background: Chronic liver disease (CLD) represents a substantial global health challenge, with significant morbidity and mortality worldwide. Biological aging may be involved in CLD-related outcomes, but the associations of diverse DNA methylation (DNAm) aging algorithms with CLD phenotypes and long-term mortality remain incompletely characterized. Methods: Using a US nationally representative cohort, we analyzed 12 DNAm aging algorithms in 2522 adults aged ≥50. CLD was classified into viral, alcohol-related, metabolic syndrome (MetS)-related liver disease, or uncharacterized groups. Advanced fibrosis was defined by AST-to-platelet ratio index ≥0.7. Associations of algorithms with CLD and all-cause mortality (followed through 2019) were assessed using multivariable-adjusted regression and logistic regression models and Cox models, accounting for complex sampling. Results: Among participants with CLD, DNAm aging algorithms showed only nominal associations with APRI-defined advanced fibrosis. GrimAgeMortAcc, GrimAge2MortAcc, HannumAgeAcc, PhenoAgeAcc, DunedinPoAm, and HorvathTelo were significantly associated with all-cause mortality. GrimAge-based measures and PhenoAgeAcc showed the strongest associations with all-cause mortality across CLD-related phenotypes (HRs ranged from 1.31 to 1.82). HorvathTelo was inversely associated with mortality risk (HR = 0.71, 95% CI: 0.62–0.82). Conclusions: DNAm aging algorithms, particularly GrimAge-based measures, are strongly associated with long-term all-cause mortality among individuals with CLD-related phenotypes. Although associations with fibrosis-related outcomes varied according to fibrosis definitions, DNAm aging algorithms may provide additional biological information for mortality risk stratification among individuals with CLD-related phenotypes.