ArticleBMC medical genomics2020
Genetic colocalization atlas points to common regulatory sites and genes for hematopoietic traits and hematopoietic contributions to disease phenotypes.
Article in BMC medical genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review of Mendelian randomization studies on risk of cancer.BMC medicine · 2022Pooled it
- A multi-omics Mendelian randomization study identifies new therapeutic targets for alcohol use disorder and problem drinking.Nature human behaviour · 2025Article
- HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data.Genome biology · 2024Article
- Long-read proteogenomics to connect disease-associated sQTLs to the protein isoform effectors of disease.American journal of human genetics · 2024Article
- Article
- Genetically influenced tobacco and alcohol use behaviors impact erythroid trait variation.PloS one · 2024Article
- Article
- Body mass index and adipose distribution have opposing genetic impacts on human blood traits.eLife · 2022Article
- eQTL Colocalization Analyses Identify NTN4 as a Candidate Breast Cancer Risk Gene.American journal of human genetics · 2020Article
- Mechanistic and Translational Advances Using iPSC-Derived Blood Cells.Journal of Experimental Pathology · 2020Article
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Abstract
backgroundGenetic associations link hematopoietic traits and disease end-points, but most causal variants and genes underlying these relationships are unknown. Here, we used genetic colocalization to nominate loci and genes related to shared genetic signal for hematopoietic, cardiovascular, autoimmune, neuropsychiatric, and cancer phenotypes.
methodsOur aim was to identify colocalization sites for human traits among established genome-wide significant loci. Using genome-wide association study (GWAS) summary statistics, we determined loci where multiple traits colocalized at a false discovery rate < 5%. We then identified quantitative trait loci among colocalization sites to highlight related genes. In addition, we used Mendelian randomization analysis to further investigate certain trait relationships genome-wide.
resultsOur findings recapitulated developmental hematopoietic lineage relationships, identified loci that linked traits with causal genetic relationships, and revealed novel trait associations. Out of 2706 loci with genome-wide significant signal for at least 1 blood trait, we identified 1779 unique sites (66%) with shared genetic signal for 2+ hematologic traits. We could assign some sites to specific developmental cell types during hematopoiesis based on affected traits, including those likely to impact hematopoietic progenitor cells and/or megakaryocyte-erythroid progenitor cells. Through an expanded analysis of 70 human traits, we defined 2+ colocalizing traits at 2123 loci from an analysis of 9852 sites (22%) containing genome-wide significant signal for at least 1 GWAS trait. In addition to variants and genes underlying shared genetic signal between blood traits and disease phenotypes that had been previously related through Mendelian randomization studies, we defined loci and related genes underlying shared signal between eosinophil percentage and eczema. We also identified colocalizing signals in a number of clinically relevant coding mutations, including sites linking PTPN22 with Crohn's disease, NIPA with coronary artery disease and platelet trait variation, and the hemochromatosis gene HFE with altered lipid levels. Finally, we anticipate potential off-target effects on blood traits related novel therapeutic targets, including TRAIL.
conclusionsOur findings provide a road map for gene validation experiments and novel therapeutics related to hematopoietic development, and offer a rationale for pleiotropic interactions between hematopoietic loci and disease end-points.
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