Causal genes and variants within genome-wide association study (GWAS) loci can be identified by integrating GWAS statistics with expression quantitative trait loci (eQTL) and determining which variants underlie both GWAS and eQTL signals. Most analyses, however, consider only the marginal eQTL signal, rather than dissect this signal into multiple conditionally independent signals for each gene. Here we show that analyzing conditional eQTL signatures, which could be important under specific cellular or temporal contexts, leads to improved fine mapping of GWAS associations. Using genotypes and gene expression levels from post-mortem human brain samples (n = 467) reported by the CommonMind Consortium (CMC), we find that conditional eQTL are widespread; 63% of genes with primary eQTL also have conditional eQTL. In addition, genomic features associated with conditional eQTL are consistent with context-specific (e.g., tissue-, cell type-, or developmental time point-specific) regulation of gene expression. Integrating the 2014 Psychiatric Genomics Consortium schizophrenia (SCZ) GWAS and CMC primary and conditional eQTL data reveals 40 loci with strong evidence for co-localization (posterior probability > 0.8), including six loci with co-localization of conditional eQTL. Our co-localization analyses support previously reported genes, identify novel genes associated with schizophrenia risk, and provide specific hypotheses for their functional follow-up.
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http://dx.doi.org/10.1016/j.ajhg.2018.04.011 | DOI Listing |
Cell Genom
January 2025
Curriculum in Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, NC 27599, USA; Thurston Arthritis Research Center, University of North Carolina, Chapel Hill, NC 27599, USA; Curriculum in Genetics and Molecular Biology, University of North Carolina, Chapel Hill, NC 27599, USA; Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, NC 27599, USA. Electronic address:
Osteoarthritis (OA) poses a significant healthcare burden with limited treatment options. While genome-wide association studies (GWASs) have identified over 100 OA-associated loci, translating these findings into therapeutic targets remains challenging. To address this gap, we mapped gene expression, chromatin accessibility, and 3D chromatin structure in primary human articular chondrocytes in both resting and OA-mimicking conditions.
View Article and Find Full Text PDFAtheroscler Plus
December 2024
College of Acumox and Tuina, Guizhou University of Traditional Chinese Medicine, Guiyang, China.
Background: Coronary atherosclerosis (CAS) is a complex chronic inflammatory disease with significant genetic and environmental contributions. While genome-wide association studies (GWAS) have pinpointed many risk loci, over 75 % are in non-coding regions, complicating functional analysis and understanding gene-disease mechanisms.
Methods: We conducted a cross-tissue transcriptome-wide association study (TWAS) using data from the GWAS Catalog (16,041 cases, 440,307 controls) and the Genotype-Tissue Expression (GTEx) v8 eQTL dataset.
Am J Hum Genet
September 2024
Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA. Electronic address:
Understanding the molecular mechanisms of complex traits is essential for developing targeted interventions. We analyzed liver expression quantitative-trait locus (eQTL) meta-analysis data on 1,183 participants to identify conditionally distinct signals. We found 9,013 eQTL signals for 6,564 genes; 23% of eGenes had two signals, and 6% had three or more signals.
View Article and Find Full Text PDFbioRxiv
October 2024
Curriculum in Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, NC 27599, USA.
Osteoarthritis (OA) poses a significant healthcare burden with limited treatment options. While genome-wide association studies (GWAS) have identified over 100 OA-associated loci, translating these findings into therapeutic targets remains challenging. Integrating expression quantitative trait loci (eQTL), 3D chromatin structure, and other genomic approaches with OA GWAS data offers a promising approach to elucidate disease mechanisms; however, comprehensive eQTL maps in OA-relevant tissues and conditions remain scarce.
View Article and Find Full Text PDFNat Commun
April 2024
Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA.
Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV.
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