Biology subjects

Joehanes, R.

Publications and source records attributed to Joehanes, R..

4 recordsLinked to original sources

bioRxiv2026

eQTM (expression quantitative trait methylation) Atlas: a comprehensive resource of over 11 million DNA methylation-gene expression associations through across 11 tissues and 4 diseases

MotivationEpigenome-wide association studies (EWAS) have identified numerous DNA methylation (DNAm) CpG sites associated with complex traits and diseases, but interpretation of those CpG sites remains challenging because in EWAS, CpGs are mostly linked to nearby genes based only on genomic proximity. Expression quantitative trait methylation (eQTM) analyses connect DNAm CpGs with statistically associated gene expression levels. However, a comprehensive, searchable resource integrating eQTMs across diverse tissues and disease contexts has been lacking. ResultsWe developed the eQTM Atlas, a web-based resource that manually curates more than 11 million DNAm-gene expression associations from eight cohorts, covering 11 tissue types, four broad disease contexts, 173,886 unique CpG probes and 20,231 unique genes. The Atlas supports gene- or CpG-searches by tissue or disease type and finding associated CpG or genes, visualization of cis- and trans-eQTMs through genome browser, heatmap interfaces across various tissues, and cohort-level data downloads. By integrating eQTM results with EWAS resources, the eQTM Atlas enables users to connect disease- or trait-associated CpGs to statistically associated genes rather than relying solely on proximity-based gene annotation, supporting functional interpretation of EWAS findings and generation of disease-specific regulatory hypotheses. Availability and implementationThe eQTM Atlas is freely available at https://shiny.crc.pitt.edu/eqtm_browser/. The web interface is implemented in R Shiny and hosted through the University of Pittsburgh Center for Research Computing (CRC). Source code is available at https://github.com/ads303/eQTM-Atlas.

genetics↗

bioRxiv2026

Genetic Impacts on Variability of Body Fat Distribution Uncover Gene-Environment and Gene-Gene Interactions

Body fat distribution is a strong predictor of cardiometabolic disease risk. Gene-environment and gene-gene interactions can affect body fat distribution, resulting in differential phenotypic variance across genotype groups that can be detected through variance quantitative trait loci (vQTLs). Using UK Biobank MRI data in conjunction with genetic data, we explored evidence for vQTLs for body fat distribution phenotypes aiming to uncover potential genetic interactions. We identified three vQTLs for liver fat distribution, including rs738408 (PNPLA3), rs4293458 (APOE), and rs58542926 (TM6SF2), and one vQTL region (FTO) for abdominal subcutaneous adipose tissue. To dissect putative gene-environment and gene-gene interactions underlying these signals, we identified multiple vQTL-environment interactions and one epistatic effect (rs58542926*rs429358) for liver fat. The vQTLs and interaction results were validated in multiple UK Biobank and external replication cohort datasets (Framingham Heart Study, All of Us, and TwinsUK), showing replication of the three liver vQTLs with the greatest reproducibility for vQTL rs738408. Our findings uncover vQTLs and underlying interaction effects on body fat distribution, especially liver fat, that may be useful for the development of precision medicine approaches.

genetics↗

bioRxiv2025

A Mammalian Genomic Signature Shaped by Single Nucleotide Variants Controlling Transcriptome Integrity and Diversity

BackgroundMany functional features of mammalian genomic sequences remain poorly defined, especially how sequence motifs and genetic variants within non-coding regions (NCRs) regulate transcriptome integrity and diversity. We have shown that G-tracts unusually positioned between the polypyrimidine tract and 3' AG repress usage of the AG and are enriched at cryptic splice sites in cancer cells but their broader role across the extensive NCRs of mammalian genomes is unknown. ResultsHere, we identify a widely evolved genomic signature, G-tract-AG motifs consisting of guanine tracts closely upstream of AG dinucleotides, which is significantly associated with single-nucleotide variants (SNVs) identified in genome-wide association studies, particularly within NCRs. Approximately 9,000 such G-tracts within human genes are disrupted by variants of the cis-splicing quantitative trait loci in the Genotype-Tissue Expression project. Functionally, G-tracts repress splicing at the adjacent 3' AG, primarily by stalling the second transesterification step. Disruption of G-tracts by SNVs relieves this repression, enabling splicing and generating novel transcript isoforms. These G-tract-disrupting SNVs are in cis across the majority of protein-coding genes and are among thousands of rare variants causing genetic diseases. ConclusionsG-tract-AG signatures are widespread bipartite motifs with dual functions: G-tracts repress AG usage to safeguard transcriptome integrity, while SNV-induced disruption releases AGs for splicing to promote transcriptome diversity. Our findings provide mechanistic insights into the regulation of transcriptome integrity and diversity by a mammalian genomic signature, particularly for NCR SNVs associated with diverse traits and a new framework for their functional annotation.

genetics↗

bioRxiv2017

GWAS of epigenetic ageing rates in blood reveals a critical role for TERT

DNA methylation age is an accurate biomarker of chronological age and predicts lifespan, but its underlying molecular mechanisms are unknown. In this genome-wide association study of 9,907 individuals, we found gene variants mapping to five loci associated with intrinsic epigenetic age acceleration (IEAA) and gene variants in 3 loci associated extrinsic epigenetic age acceleration (EEAA). Mendelian randomization analysis suggested causal influences of menarche and menopause on IEAA and lipid levels on IEAA and EEAA. Variants associated with longer leukocyte telomere length (LTL) in the telomerase reverse transcriptase gene (TERT) locus at 5p15.33 confer higher IEAA (P<2.7x10-11). Causal modelling indicates TERT-specific and independent effects on LTL and IEAA. Experimental hTERT expression in primary human fibroblasts engenders a linear increase in DNA methylation age with cell population doubling number. Together, these findings indicate a critical role for hTERT in regulating the DNA methylation clock, in addition to its established role of compensating for cell replication-dependent telomere shortening.

genetics↗