Biomedical subjects

Colleen M Sitlani

Publications and source records attributed to Colleen M Sitlani.

5 recordsLinked to original sources

PubMed2026

Proteomic pathways mediating low socioeconomic status and cardiovascular events in older adults in CHS and ARIC.

BACKGROUND AND AIMS: Many studies have linked socioeconomic status (SES) and cardiovascular outcomes, yet the biologic mechanisms mediating these associations are only partially understood. The objective of this study was to identify molecular mediators of the association of low SES with coronary heart disease (CHD) and stroke. METHODS: This research was conducted in 2942 Black and White adults in the Cardiovascular Health Study (mean age 76.2 years) and 10,689 Black and White adults in the Atherosclerosis Risk in Communities Study (mean age 60.0 years). We used factor analysis to create a composite measure of low educational attainment, low-income, and blue-collar occupation. Approximately 5000 proteins were measured with an aptamer-based method, and CHD and stroke events were adjudicated. Results were stratified by race, which was conceptualized as a social factor. RESULTS: Low SES was associated with 44 and 262 proteins, in Black and White adults, respectively. No protein met the Bonferroni adjusted threshold for statistically significantly mediation among Black participants. Among White participants, 23 proteins mediated the association between SES adversity and CHD and 5 mediated the association between SES adversity and stroke. The strongest mediating associations for CHD included PTPRS, SCG3, and MMP12. The strongest mediating associations for stroke included NCAN, FAM20B, and APLP1. SPARCL1 and CDCP1 remained the strongest mediators of the association between SES adversity and CHD, after adjusting for potential confounders and traditional cardiovascular risk factors. CONCLUSION: We identified several biomarkers that characterize the biologic risk of SES adversity on CHD and stroke.

Aged↗

PubMed2026

Rethinking immune studies: population-level immune variations and the path forward.

Shifts in immune cell proportions underlie disease progression and immunotherapy response, positioning them as promising diagnostic biomarkers and therapeutic targets. However, these shifts also occur naturally across the lifespan and vary with demographic factors such as age and sex, which may complicate their interpretation and clinical utility. While demographic associations have been explored previously, there have been mixed results likely due to small sample sizes and cross-cohort population-specific differences. To address these limitations, we conducted a meta-analysis across 3 large, diverse cohort studies to evaluate associations between 20 immune cell subtypes, 3 informative cell ratios, and a range of sociodemographic variables such as age, sex, self-identified race and ethnicity (SIRE), and socioeconomic status. We find consistent and significant associations across all sociodemographic dimensions. Cytomegalovirus (CMV)-a key driver of immune senescence-emerged as a major contributor to variation in immune composition and CMV antibody levels were higher among women, individuals of lower socioeconomic status, and marginalized racial and ethnic groups. In addition, male sex showed similar patterns of association with immune profiles as aging, whereas race did not. These findings underscore the need to account for diverse sociodemographic factors in immunology study design and participant recruitment to avoid population-specific biases and ensure broadly generalizable results.

Humans↗

PubMed2026

Large-Scale Proteomic Profiling of Incident Heart Failure and Its Subtypes in Older Adults.

BACKGROUND: Heart failure (HF) and its main subtypes, heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF), impose an enormous health burden on elders. Assessment of the circulating proteome to illuminate pathogenesis could open new opportunities for treatment. METHODS: We conducted a plasma proteomics screen of incident HF and its subtypes in 2 older population-based cohorts, the CHS (Cardiovascular Health Study) and the AGES-RS (Aging, Gene/Environment Susceptibility-Reykjavik Study). The 2 studies used SomaLogic platforms, with 4404 aptamers in common. Multivariable Cox models were fit to evaluate individual-protein associations with HF, HFpEF, and HFrEF separately in each cohort, and study-specific associations were combined by fixed-effects meta-analysis. Replication was performed in the ARIC (Atherosclerosis Risk in Communities) cohort. Two-sample Mendelian randomization of HF and its subtypes, along with colocalization analysis, was performed to support causal inference. RESULTS: Among 8599 participants, 1590 experienced incident HF (536 HFpEF, 471 HFrEF). There were 119 proteins associated with HF, 15 proteins with HFpEF, and 11 proteins with HFrEF, at Bonferroni-corrected significance. Among these, 9 have never previously been identified for cardiovascular diseases, and another 61 represent new associations with incident HF or its subtypes. Of these 70 proteins, 55 of the 66 available replicated externally. Mendelian randomization analysis revealed 7 proteins genetically associated with HF at nominal significance; 2 were separately associated with HFpEF, and another 2 with HFrEF. Seven of these 9 proteins (NPDC1 [neural proliferation differentiation and control protein 1], APOF [apolipoprotein F], LMAN2 [lectin, mannose-binding 2], ADIPOQ [adiponectin], CD14 [cluster of differentiation 14], ARHGAP1 [Rho GTPase-activating protein 1], C9 [complement 9]) showed new, possibly causal associations, although we did not detect evidence for colocalization. CONCLUSIONS: In this large-scale proteomic study involving 3 longitudinal cohorts of older adults, we identified and replicated 55 novel protein markers of HF or its subtypes, and 7 new, possibly causal proteins. These proteins may enhance risk prediction, improve understanding of pathobiology, and help prioritize targets for therapeutic development of these foremost disorders in elders.

Humans↗

PubMed2026

Plasma proteomics and incident coronary heart disease.

BACKGROUND: Systematic profiling of plasma proteins in population studies offers a complementary approach to discovery of novel risk factors and may provide new insights into the causes of coronary heart disease. METHODS: To explore relationships between the circulating proteome and coronary heart disease (CHD), we evaluated associations of 4780 plasma proteins with incident CHD in the Cardiovascular Health Study (CHS, N=2856, 575 CHD events) and replicated significant associations in the Atherosclerosis Risk in Communities Study (ARIC, N = 10456; 1375 events). RESULTS: We find that 11 proteins significantly associate with incident CHD after adjusting for risk factors; and eight significantly replicated in ARIC. Several proteins correlate with carotid intimal medial thickness and CHD associations are attenuated in participants without subclinical atherosclerosis. Macrophage metalloelastase (MMP12) is the strongest observed association (Hazard Ratio, 1.31; 95% Confidence Interval, 1.19-1.44). Mendelian randomization (MR) identifies a causal relationship between higher MMP12 and lower CHD (Odds Ratio, OR 0.94) and ischemic stroke (OR 0.90) risk, while reverse MR found that genetic propensity to CHD increased MMP12. Taken together, multivariable MR confirms a direct protective effect of higher plasma MMP12 on CHD risk and a genetic effect of atherosclerosis and CHD on elevating MMP12. CONCLUSIONS: Proteomic analyses reveal associations with incident CHD and genomic evidence suggests that therapeutic MMP12 inhibition may confer adverse cardiovascular effects.

Journal Article↗

PubMed2025

Genome-wide gene-sleep interaction study identifies novel lipid loci in 732,564 participants.

BACKGROUND AND AIMS: Deviations from the population mean in sleep duration have been associated with increased risk for developing dyslipidemia and atherosclerotic cardiovascular disease, but the mechanism of effect is poorly characterized. We performed large-scale genome-wide gene-sleep interaction analyses of lipid levels to identify genetic variants underpinning the biomolecular pathways of sleep-associated lipid disturbances and to suggest possible druggable targets. METHODS: We collected data from 55 cohorts with a combined sample size of 732,564 participants (87 % European ancestry) with data on lipid traits (high-density lipoprotein [HDL-c] and low-density lipoprotein [LDL-c] cholesterol and triglycerides [TG]). Short (STST) and long (LTST) total sleep time were defined by the extreme 20 % of the age- and sex-standardized values within each cohort. Based on cohort-level summary statistics data, we performed meta-analyses for one-degree of freedom tests of interaction and two-degree of freedom joint tests of the SNP-main and -interaction effect on lipid levels. RESULTS: The one-degree of freedom variant-sleep interaction test identified 10 novel loci (Pint<5.0e-9), and we additionally identify 7 loci within the two-degree of freedom analyses (Pjoint<5.0e-9 in combination with Pint<6.6e-6). Multiple loci, including those mapped to APSH (target for aspartic and succinic acid) and SLC8A1 showed biological plausibility and druggability potential based on literature. CONCLUSIONS: Collectively, the 17 (9 with short and 8 with long sleep) loci provided evidence into the biomolecular mechanisms underlying sleep-associated lipid changes, including potential involvement of the vitamin D receptor pathway. Collectively, these findings may contribute developing novel interventions for treating dyslipidemia in people with sleep disturbances.

Humans↗