Biomedical subjects

Jerome I Rotter

Publications and source records attributed to Jerome I Rotter.

At least 19 recordsLinked to original sources

PubMed2026

Longitudinal Repeated Protein Measurements in a Multiethnic Cohort Identify Novel Diabetes Biomarkers That Reveal Unique Disease Pathways.

There is up to a fourfold increase in diabetes biomarkers identified with longitudinal repeated versus single time point proteomic measurements. The increase in biomarkers identified with longitudinal repeated measurements is supported by a similar proportion being nominated as causal for type 2 diabetes with Mendelian randomization. Proteins unique to the longitudinal repeated analyses highlighted biological pathways (e.g., posttranslational protein modification and cellular structure and cycle regulation) that were distinct from pathways enriched among the shared proteins (e.g., small-molecule metabolic and catabolic processes). Longitudinal protein measurements identify additional novel disease biomarkers and disparate biological pathways compared with single measurement analyses.

Journal Article↗

PubMed2026

Addition of CAD polygenic risk score to coronary artery calcium score enhances prediction of MACE.

BACKGROUND: Coronary heart disease (CHD) is prevalent in the United States, highlighting the need for accurate risk prediction to inform primary prevention strategies. While multivariate risk models like the Framingham Risk Score and ACC/AHA Pooled Cohort Equations are commonly utilized, novel risk markers, such as the coronary artery calcium score (CACS) and polygenic risk score (PRS), are increasingly gaining recognition. OBJECTIVES: This study aimed to compare the diagnostic utility of CACS and CAD PRS, both individually and in combination, for predicting major adverse cardiovascular events (MACE). METHODS: We conducted a retrospective analysis of a cohort comprising 1,380 predominantly Caucasian participants from the Sanford Health System. CAD PRS was constructed using genetic variants, while CACS was assessed via cardiac computed tomography (CT). Statistical analyses evaluated the relationship between each modality and MACE. RESULTS: Both CAD PRS and CACS were significantly associated with future MACE. Following the adjustment for covariates, the area under the curve (AUC) for both the CACS and PRS models was comparable, indicating similar predictive capabilities for MACE. However, the combination of CAD PRS with CACS significantly enhanced predictive accuracy, outperforming either modality alone. CONCLUSIONS: This study underscores the value of integrating CACS and CAD PRS in predicting MACE. The synergistic effect of CAD PRS combined with CACS markedly improves predictive power. Further research and prospective studies are necessary to validate these findings and assess their clinical implications. Investigating the interactions between PRS and CACS will be crucial for refining cardiovascular risk prediction and optimizing prevention strategies.

cardiac genetics↗

PubMed2026

Plasma proteomics and coronary artery calcium score: synergistic, concordant and contrasting predictions of cardiovascular outcomes in The Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Coronary artery calcium (CAC) scores inform subclinical atherosclerotic cardiovascular disease (ASCVD) burden, helping guide preventative treatments. However, prediction of cardiovascular (CV) events by CAC is largely limited to ASCVD outcomes. This study investigated whether a previously validated proteomic test for predicting a broad composite of four-year CV events could enhance the prognostic utility of CAC. METHODS: We used a 27-protein CV risk score (Prot-CVR), derived from ~5,000 SomaScan™ Assay plasma protein measurements, to predict four-year risk of a composite CV and mortality outcome (myocardial infarction, stroke/TIA, heart failure hospitalization, death) in 2,122 participants with ≥1 CV risk factors from the Multi-Ethnic Study of Atherosclerosis (MESA) observational cohort at exam 5 and compared predictions to CAC Agatston scores. Discriminatory performance was assessed using C-Index and 4-year area under the curve (AUC). Cox Proportional Hazard (CoxPH) ratios were calculated for the composite outcome, ASCVD outcome (myocardial infarction, resuscitated cardiac arrest, stroke, coronary heart disease death), and individual events. Changes in Prot-CVR and CAC scores from baseline to MESA exam 5 (+10-years) in CV event versus event-free participants were assessed using 2-tailed paired t-tests. CoxPH regression models of CV event status distributed by Prot-CVR, CAC, and relevant co-variates were evaluated for performance relative to individual models. RESULTS: Individual Prot-CVR and CAC models predicting the composite outcome had comparable 4-year AUCs, but Prot-CVR had a higher C-index (0.68 (0.65-0.70) versus 0.63 (0.60-0.65), p=0.001) and greater hazard ratios for the composite outcome (p<0.001), death (p<0.001), and heart failure (p=0.015). A combined CoxPH model of Prot-CVR + CAC + Age had a higher 4-year AUC (0.72, p<0.05) and C-Index (0.71, p<0.05) than Prot-CVR or CAC alone. Both Prot-CVR and CAC scores detected an increase in risk prior to an approaching CV event in ~10-year sensitivity-to-change analysis. For 49.6% of MESA population with CAC=0 at baseline, Prot-CVR was greater in composite event versus event free participants at 4 years (0.23 versus 0.15, p=0.006) and full follow-up (0.18 versus 0.13, p<0.001). CONCLUSION: Protein testing complements CAC for CV risk assessment although the improvement is modest. Prot-CVR may resolve which patients with CAC=0 are at heightened CV risk.

Journal Article↗

PubMed2026

Human Immunodeficiency Virus-Associated Proteomic Signature of Myocardial Fibrosis and Incident Heart Failure.

BACKGROUND: People with human immunodeficiency virus (HIV) (PWH) are at higher risk of myocardial fibrosis and subsequent heart failure (HF) compared to people without HIV (PWOH). Mechanisms underlying this risk and its specificity to PWH are unclear. METHODS: We measured 2594 proteins in plasma obtained concurrently with cardiovascular magnetic resonance imaging among 342 PWH and PWOH. We estimated associations with HIV serostatus and myocardial fibrosis (elevated extracellular volume fraction [ECV] ≥30% among women, ≥28% among men) using multivariable regression. Among an independent community-based cohort, we estimated associations between the identified signature and time to incident HF. RESULTS: Mean age of participants was 55 (standard deviation [SD], 6) years, 25% were female, 61% were PWH (88% on antiretroviral therapy, 74% with undetectable HIV RNA), and 52% had elevated ECV. We identified 39 proteins and 1 cluster of 42 proteins that were higher among PWH versus PWOH and positively associated with elevated ECV, independent of risk factors (false discovery rate <0.05). Among an independent cohort of 3223 PWOH (mean age, 68 [SD, 9] years; 52% female; 118 incident HF cases over a mean of 9.8 [SD, 1.4] years), we found that this protein cluster and 34 of 39 individual proteins were associated with time to incident HF. This signature was statistically enriched for T-cell activation, tumor necrosis factor signaling, ephrin signaling, and tissue maintenance and repair. CONCLUSIONS: We identified an HIV-related proteomic signature associated with myocardial fibrosis regardless of HIV serostatus and that predicted incident HF among the general population. Our results identify several novel associations related to specific immune processes that may contribute to risk of myocardial fibrosis and subsequent HF among both PWH and PWOH.

Humans↗

PubMed2026

Multi-omic signatures of genetic mechanisms inform on type 2 diabetes biology and patient heterogeneity.

Type 2 diabetes (T2D) is a heterogeneous disease shaped by genetic pathways related to insulin resistance and β-cell dysfunction, but how this heterogeneity is reflected molecularly remains unclear. We integrated partitioned polygenic scores (pPS) with proteomic and metabolomic profiling to define molecular signatures of T2D and their clinical relevance. We analyzed UK Biobank participants with genomic, proteomic, and metabolomic data. In a disease-free training subset, we used LASSO regression to identify multi-omic signatures associated with each pPS by jointly modeling proteins and metabolites. In an independent testing set, we constructed multi-omic scores and examined their associations with clinical traits and diabetes-related outcomes. Mediation analyses were used to investigate putative causal pathways. Key findings were evaluated in the Multi-Ethnic Study of Atherosclerosis (MESA). We identified distinct multi-omic signatures that capture the molecular architecture of T2D genetic risk across physiological subtypes. Compared with genetic scores alone, multi-omic pPS showed larger effect sizes and better disease discrimination. These scores recapitulated subtype-specific physiology and were associated with T2D risk. The Beta-Cell 2 multi-omic score showed marked stratification for insulin use, which was replicated in MESA, where it also predicted future insulin use. Mediation analyses implicated lipoprotein remodeling and fatty acid metabolism in the Lipodystrophy 1 cluster, accounting for 30-45% of the total effect of pPS on T2D risk. Integrating process-specific genetic risk with circulating multi-omic profiles reveals biologically distinct endotypes of T2D and supports a framework for improved patient stratification and risk assessment.

Journal Article↗

PubMed2026

Estimating population structure using epigenome-wide methylation data.

Population stratification is one of the source of inflation in epigenome-wide association studies (EWAS) when not properly accounted for. To address this, we developed methylation population scores (MPSs) to predict genetic principal components (GPCs) using a feature selection approach. We used multi-ethnic DNA methylation data from Illumina EPIC arrays across five cohorts, including MESA (n = 929), CARDIA (n = 1123), JHS (n = 1365), ARIC (n = 2338), and HCHS/SOL (n = 1475), randomly splitting participants into training (85%) and test (15%) sets. Within each cohort, associations between GPCs and CpG sites were estimated using linear regression adjusting for age, sex, smoking and alcohol use, race/ethnicity, body mass index, and cell type proportions, followed by meta-analysis and selection of CpGs with FDR <0.05. We then applied a two-stage weighted least squares Lasso regression to construct MPSs, adjusting for the aforementioned covariates. In the test dataset, MPSs showed strong correlation with GPCs, with R² ranging from 0.27 (MPS7 vs. GPC7) to 0.98 (MPS1 vs. GPC1). Visualization demonstrated that MPSs recapitulated the pattern shown by GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups and outperformed methylation-based principal components constructed using alternative published methods. Additionally, MPSs showed comparable performance to GPCs in reducing inflation in EWAS. Overall, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations, and provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent.

Humans↗

PubMed2026

Genetic evidence for causality of late chronotype on metabolic syndrome in East Asians and Europeans.

CONTEXT: The impact of chronotype-defined as an individuals' inherent preference of sleep timing-and its genetic determinants on metabolic syndrome (MetS) has been less studied. OBJECTIVE: This study investigated the causal relationship between late chronotype and MetS using Mendelian randomization (MR) analysis, based on data from the Taiwan Biobank (TWB) and parallel analyses in the UK Biobank (UKB). METHODS: A total of 36,845 participants from TWB served as the discovery cohort, and 235,639 participants from UKB served as the replication cohort. Late chronotype was defined in TWB as a preference for bedtime after midnight, and in UKB as self-report as being an 'evening' person. The association between late chronotype and MetS, along with its components, was evaluated in TWB, and validated in UKB. Genome-wide association analyses for late chronotype were first conducted in TWB and then meta-analyzed with UKB. Polygenic risk scores (PRS) for late chronotype were constructed and tested for association with MetS. Causality between late chronotype and MetS was examined using one-sample MR analysis in TWB and validated in UKB. RESULTS: Late chronotype was significantly associated with MetS, as well as with central obesity, hyperglycemia, and hypertriglyceridemia, in both TWB and UKB (all P < 0.0083, considering Bonferroni correction). The constructed PRS of late chronotype also showed significant associations with MetS and several of its components (several P < 0.0083, considering Bonferroni correction). Findings from the one-sample MR analysis indicated a potential causal effect of late chronotype on MetS. CONCLUSIONS: This study provides evidence of a robust association between late chronotype and MetS across populations of diverse ancestry, including Taiwanese and European.

Humans↗

PubMed2026

Polygenic Risk Scores for Incident Dementia in the Multi-Ethnic Study of Atherosclerosis.

Over 75 Alzheimer's disease (AD) and dementia-associated variants have been identified through genome-wide association studies, but the utility of polygenic risk scores (PRS) for predicting AD and dementia in diverse and admixed populations remains unclear. We compared how PRS approaches differing in p-value thresholds, variant weights, and source ancestry perform in predicting dementia in 6338 African American, Chinese, Hispanic, and White individuals from the Multi-Ethnic Study of Atherosclerosis. We tested clumping and thresholding (C+T) methods with varying parameters against Bayesian approaches (PRS-CS, PRS-CSx). We compared the ability of each method to predict incident dementia in all participants and in groups stratified by self-reported race/ethnicity. We additionally analyzed performance across groups stratified by estimated proportion of non-Finnish European (NFE)-like ancestry. Including more variants does not improve performance. We found comparable associations between dementia and PRS when comparing a C+T method with only 15 SNPs and PRS derived from Bayesian models that include > 800,000 SNPs (HR5e-08 = 1.18, 95% CI: 1.08-1.28; HRCSx = 1.17, 95% CI: 1.07-1.27). The p < 5e-08 C+T method was more strongly associated with incident dementia in populations genetically dissimilar from the source data (HRlowNFE_5e-08 = 1.27, 95% CI: 1.08-1.50; HRlowNFE_CSx = 1.12, 95% CI: 0.94-1.33). More selective PRS models using genome-wide significant SNPs may be preferable for dementia prediction in diverse populations.

Aged↗

PubMed2025

Impact of AGT rs5050(T>G) variants on associations between estradiol and angiotensinogen levels: Multi-Ethnic Study of Atherosclerosis (MESA).

AIMS: Angiotensinogen plays an essential role in maintaining circulatory homeostasis. AGT rs5050(T > G) has been identified as a regulator of the transcription of AGT mRNA, with differential expression between sexes. We sought to determine if rs5050(T > G), an estrogen response element, modifies the relationship between estrogen and angiotensinogen levels. METHODS: rs5050(T > G) was genotyped, and plasma angiotensinogen levels were measured in 4,831 MESA participants, including postmenopausal women, on hormone therapy (n = 709) or not (n = 1,551), and 2,581 men. Linear regression models were employed to determine the associations of angiotensinogen with rs5050(T > G) allele dosage; and to evaluate whether rs5050(T > G) modifies the association between estradiol and angiotensinogen, with a main effect term and interaction term between rs5050(T > G)*estradiol. Estimated marginal means (EMMs) were used to further evaluate the effect of estradiol on angiotensinogen across different rs5050 alleles (T > G). RESULTS: rs5050TT had the highest median levels of angiotensinogen, followed by TG and GG. Adjusted main effect model showed positive associations between estradiol and angiotensinogen, with each rs5050T allele associated with 0.329 SD higher log-angiotensinogen levels (CI 95% 0.293, 0.365). The interaction rs5050(T > G)*estradiol was not significant, with EMMs exhibiting overlapping slope confidence intervals across genotypes. The proportion of the variance in angiotensinogen explained by modeling increases from 47.9% to 51.6% when including rs5050(T > G) or interation rs5050(T > G)*estradiol in the model. CONCLUSIONS: rs5050(T > G) is associated with circulating angiotensinogen levels, but rs5050(T > G) alleles do not influence the relationship between estradiol and angiotensinogen. This suggests that estrogen's effect on angiotensinogen regulation occurs independently of rs5050(T > G), despite its location within an estrogen-responsive element.

Angiotensinogen↗

PubMed2025

Proteome-wide association study of prostate cancer risk across populations.

There is insufficient understanding of the molecular basis of prostate cancer (PCa) across different populations. We perform a large-scale proteome-wide association study (PWAS) to identify proteins with genetically regulated expression in plasma to be associated with PCa risk across populations. We develop genetic prediction models for expression of 1578, 1993, 1218, and 1390 proteins for African (n = 450), European (n = 758), Asian (n = 289), and Hispanic/Latino (n = 474) males, respectively, and evaluate associations of genetically regulated protein expression with PCa risk in 19,391 PCa cases and 61,608 controls of African population, 122,188 cases and 604,640 controls of European population, 10,809 cases and 95,790 controls of Asian population, and 3931 cases and 26,405 controls of Hispanic/Latino population. We identify three, four, 15, and 73 PCa-associated proteins in African, Hispanic/Latino, Asian, and European populations, respectively, and 83 in trans-population meta-analysis. There are both pan-population and population-specific associations. Our findings provide valuable insights into etiology of PCa.

Humans↗

PubMed2025

Insulinemic and inflammatory dietary patterns and colorectal cancer risk: a dietary data harmonization study of one million participants in the Consortium of Metabolomics Studies (COMETS).

BACKGROUND: Inflammatory and insulinemic dietary patterns have been associated with colorectal cancer (CRC) risk, but generalizability across diverse populations with heterogeneous food supplies and dietary behaviors has not been established. OBJECTIVES: We harmonized disparate dietary and covariate data on a large scale to compute the reverse Empirical Dietary Index for Hyperinsulinemia (rEDIH), reverse Empirical Dietary Inflammatory Pattern (rEDIP), and Healthy Eating Index (HEI)-2015 scores, and tested their associations with CRC risk. METHODS: We leveraged data among 501,892 women and 407,390 men from 6 cohorts across the United States (NIH-AARP, Multi-Ethnic Study of Atherosclerosis, Prostate, Lung, Colorectal, and Ovarian, SCCS) and Europe (EPIC, ATBC) with varying sociodemographic characteristics, participating in the Consortium of Metabolomics Studies. We harmonized nomenclature and nutritional information of >800 unique food items across cohorts. We used multivariable-adjusted Cox regression, adjusting for demographic, clinical, and lifestyle factors, to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between the dietary indices and CRC risk per cohort, then meta-analyzed the estimates. RESULTS: During a median follow-up of 14.9 y, 16,525 incident CRC cases were diagnosed. Participants in the highest quintile of rEDIH (low-insulinemic diet) had an 18% reduced risk of CRC (HR: 0.82; 95% CI: 0.78, 0.86) compared with those in the lowest quintile. For the same comparison, similar risk reductions were observed for rEDIP (anti-inflammatory diet) (HR: 0.84; 95% CI: 0.80, 0.89) and HEI-2015 (overall dietary quality) (HR: 0.80; 95% CI: 0.76, 0.85). Heterogeneity between cohorts in the meta-analyzed estimates was low for rEDIH (I2 = 22.3%) compared with rEDIP (I2 = 62.5%) and HEI-2015 (I2=83.9%). CONCLUSIONS: Using carefully harmonized data from nearly 1 million individuals in the United States and Europe, we observed significant CRC risk reduction with habitual intake of low-insulinemic and anti-inflammatory dietary patterns, comparable with higher overall dietary quality. Study findings underscore the utility of these dietary patterns for global cancer prevention efforts.

Humans↗

PubMed2025

Admixture-mapping analysis reveals genetic determinants of the human plasma proteome.

Protein profiling and genetic findings can be integrated to define the genetic architecture of the circulating proteome in chronic diseases. Most self-identified African American (AA) individuals have both African and European genetic ancestry. Admixture mapping can detect genomic association regions in which causal variants exist with substantial differences in allele frequency or effect sizes between genetic ancestries. We performed admixture mapping of the circulating proteome in 1,989 participants from the Jackson Heart Study (JHS), investigating the relation of local African ancestry within genomic regions with levels of circulating proteins. We conditioned protein-local ancestry association models on variants previously found to be associated with those proteins in genome-wide association studies (GWASs). We replicated findings in 196 AA participants from the Multi-Ethnic Study of Atherosclerosis (MESA). 62 proteins were associated with local African ancestry. 21 of 62 remained statistically significant after conditioning on protein-associated variants observed in previous GWASs. 48 of 54 available protein-local ancestry associations were replicated in the MESA. Proteins associated with local African ancestry included chemokines, factors associated with vascular biology and inflammation, and other biologically interesting proteins. Admixture associations unexplained by previously reported protein-associated variants in conditional analysis suggest the existence of causal variants missed by standard GWAS techniques.

Aged↗

PubMed2025

Sleep-disordered breathing subtypes and future diet quality in the Multi-Ethnic Study of Atherosclerosis.

OBJECTIVES: Sleep-disordered breathing (SDB) and diet quality impact cardiometabolic disease, but few studies have examined if SDB influences diet quality. This study estimated the association between SDB subtypes (with and without sleepiness) and future diet quality in the Multi-Ethnic Study of Atherosclerosis. METHODS: Probable SDB was characterized by self-reported physician-diagnosed sleep apnea (PDSA) or habitual snoring and subtyped by presence or absence of sleepiness. A food frequency questionnaire measured diet 1.6 years before, and 7.8 years after SDB assessment. Diet quality was measured with the Alternate Healthy Eating Index-2010 (AHEI). Mean differences in AHEI at follow-up by SDB subtypes were estimated with multivariable linear regression adjusting for baseline AHEI, demographic, and lifestyle factors. RESULTS: Among 3294 participants (mean age 62 years, 51% women), 29.5% had SDB. When grouped by sleepiness, 20.6% had SDB without, and 8.9% had SDB with, sleepiness. Adjusting for baseline diet and potential confounders, those with SDB had lower follow-up AHEI scores compared with unaffected individuals (mean AHEI difference [95% CI]: -1.02 [-1.69, -0.35]). Upon stratifying by sleepiness, both groups had lower AHEI scores at follow-up compared with unaffected individuals, and the difference was greater for those with sleepiness (mean score difference [95% CI]: -0.8 [-1.56, -0.04], without sleepiness; -1.52 [-2.59, -0.45], with sleepiness). The difference between those with and without sleepiness was not statistically significant. CONCLUSIONS: In a multi-ethnic cohort, SDB was associated with lower diet quality after 7.8 years and this association was larger among participants with SDB with sleepiness.

Humans↗

PubMed2025

Genetic architecture and analysis practices of circulating metabolites in the NHLBI Trans-Omics for Precision Medicine Program.

Circulating metabolite levels partly reflect the state of human health and diseases and can be impacted by genetic determinants. Hundreds of loci associated with circulating metabolites have been identified; however, most findings focus on predominantly European ancestry or single-study analyses. Leveraging the rich metabolomics resources generated by the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) Program, we harmonized and accessibly cataloged 1,729 circulating metabolites among 25,058 ancestrally diverse samples. From our comparison of multiple methods, we provided a set of reasonable strategies for outlier and imputation handling to process metabolite data and show that inverse normalization by study and half-minimum imputation provide mostly similar results for pooled or meta-analysis. Following the practical analysis framework, we further performed a genome-wide association analysis on 1,135 selected metabolites using whole-genome sequencing data from 16,359 individuals passing the quality-control filters and discovered 1,775 independent loci associated with 667 metabolites. Among 160 unreported locus-metabolite pairs, we identified associations with loci locating within previously implicated metabolite-associated genes, as well as associations with loci locating in genes such as GAB3 and VSIG4 (located on the X chromosome) that may play a role in metabolic regulation. In the sex-stratified analysis, we revealed 85 independent locus-metabolite pairs with evidence of sexual dimorphism, which were located in well-known metabolic genes such as FADS2, D2HGDH, SUGP1, and UGT2B17, strongly supporting the importance of exploring sex difference in the human metabolome. Taken together, our study depicted the genetic contribution to circulating metabolite levels, providing additional insight into the understanding of human health.

Humans↗

PubMed2025

Genetic Variants Associated With the Biochemical Response to Vitamin D3 in the Multi-Ethnic Study of Atherosclerosis.

CONTEXT: The response to treatment with vitamin D varies between patients. OBJECTIVE: To identify genetic variants associated with the biochemical response to vitamin D3 supplementation. DESIGN: Randomized placebo-controlled trial conducted between 2017 and 2019. SETTING: The trial was nested in an ongoing community-based cohort study, the Multi-Ethnic Study of Atherosclerosis. INTERVENTION: 2000 International Units of vitamin D3 or placebo daily for 16 weeks. PARTICIPANTS: The analytic sample included 427 participants assigned to vitamin D3 (mean age, 73 years; 54% females) and was 36% White, 33% Black, 18% Hispanic, and 14% Chinese. MAIN OUTCOME MEASURES: The biochemical response to vitamin D3 included changes in serum concentrations of 1,25-dihydroxyvitamin D3 [1,25(OH)2D3], PTH, and 25-hydroxyvitamin D3 [25(OH)D3]. RESULTS: In genome-wide analyses, single nucleotide polymorphisms in 8 regions of the genome had significant association (P < 5E-08) with 1 of the traits (2 with change in 1,25(OH)2D3, 1 with change in PTH, and 5 with change in 25(OH)D3). rs16867276 within an intergenic region on 2q31 was associated with change in serum 1,25(OH)2D3 (+8.37 pg/mL difference per effect allele; P = 4.93E-08) and was the only locus that achieved genome-wide significance in transethnic meta-analysis. rs114044709 adjacent to FAM20A, which encodes a protein required for biomineralization, was associated with change in PTH among Black participants (+20.32 pg/mL difference per effect allele; P = 1.34E-08). In candidate analyses, single nucleotide polymorphisms within SULT2A1 and CYP24A1 had significant association (P < .05÷36 = .0014) with the changes in 1,25(OH)2D3 and PTH, respectively. CONCLUSION: Our results reveal potential new pathways of vitamin D regulation that require replication in other vitamin D trials.

Humans↗

PubMed2025

Whole genome sequence analysis of low-density lipoprotein cholesterol across 246 K individuals.

BACKGROUND: Rare genetic variation provided by whole genome sequence datasets has been relatively less explored for its contributions to human traits. Meta-analysis of sequencing data offers advantages by integrating larger sample sizes from diverse cohorts, thereby increasing the likelihood of discovering novel insights into complex traits. Furthermore, emerging methods in genome-wide rare variant association testing further improve power and interpretability. RESULTS: Here, we conduct the largest meta-analysis of whole genome sequencing for low-density lipoprotein cholesterol (LDL-C), a therapeutic target for coronary artery disease, analyzing data from 246 K participants and integrating 1.23B variants from the UK Biobank and the Trans-Omics for Precision Medicine (TOPMed) program. We identify numerous rare coding and non-coding gene associations related to LDL-C, with replication across 86 K participants in All of Us. Our findings are based on single-variant analyses, rare coding and non-coding variant aggregation tests, and sliding window approaches. Through this comprehensive analysis, we identify 704 novel single-variant associations, 25 novel rare coding variant aggregates, 28 novel rare non-coding variant aggregates, and one novel sliding window aggregate. CONCLUSIONS: This study provides a meta-analysis framework for large-scale whole genome sequence association analyses from diverse population groups, yielding novel rare non-coding variant associations.

Humans↗

PubMed2025

Estimating population structure using epigenome-wide methylation data.

INTRODUCTION: In epigenome-wide association analysis (EWAS), unaddressed population stratification often leads to inflation. We aimed to compute methylation population scores (MPSs) that predict genetic principal components (GPCs) using a feature selection and regression approach. METHODS: We used multi-ethnic methylation data (Illumina 450K/EPIC array) from unrelated MESA (n=929), CARDIA (n=1123), JHS (n=1365), ARIC (n=2338), and HCHS/SOL (n=1475) individuals, randomly assigning 85% of participants from each cohort to a training dataset and the remaining 15% to a test dataset. First, we estimated the associations of GPCs with each available CpG methylation site using linear regression within each cohort, adjusting for age, sex, smoking status, race/ethnic background (as a proxy for background information associated with lifestyle and other environmental exposures that may impact methylation), alcohol use status, body mass index, and cell type proportions. We meta-analyzed the associations across cohorts and selected CpG sites with association FDR-adjusted q-value <0.05. We next aggregated individuallevel data across the cohort-specific training datasets, and applied two-stage weighted least squares Lasso regression, with the GPCs as the outcomes and the selected CpG sites as penalized predictors, adjusting for the aforementioned covariates. The developed MPSs are the weighted sum of selected CpG sites from the Lasso. To evaluate the developed MPSs, we constructed them in the test dataset, and compared them with GPCs, and with MPSs constructed based on a previously-published paper. Comparison was based on correlation analysis and data visualization. We demonstrate the use of the MPSs in EWAS. RESULTS: In the test dataset, the MPSs were highly correlated with GPCs, with correlation decreasing, though not monotonically, for later components. Specifically, MPS1 and GPC1 had R2= 0.99, while MPS7 and GPC7 had R2=0.27 (the lowest observed correlation). In data visualization, MPSs had similar patterns as GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups, while outperforming MPC constructed using alternative published methods. MPSs showed comparable performance to GPCs in reducing some of the inflation in EWAS. CONCLUSIONS: Methylation-based population scores provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent. Unlike previous methods based on unsupervised methylation PCA, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations. The weights for each GPCs derived in our study can be applied to generate MPSs in other studies.

Journal Article↗

PubMed2025

Biological Age, PNPLA3, and Risk of Metabolic Dysfunction-associated Steatotic Liver Disease.

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Journal Article↗