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Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization
MRC Epidemiology Unit, University of Cambridge, School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, United Kingdom; General Medicine Center, Saarland University, Faculty of Medicine, Homburg, Germany.
Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom; Stem Cells and Diabetes Laboratory, Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.
Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.
Department of Genetics, Harvard Medical School, MA, Boston, United States; Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, MA, Boston, United States; Broad Institute of MIT and Harvard, MA, Cambridge, United States.
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2023 (English)In: Wellcome Open Research, E-ISSN 2398-502X, Vol. 8, article id 483Article in journal (Refereed) Published
Abstract [en]

Background: Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways.

Methods: To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses.

Results: Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology.

Conclusions: Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries.

Place, publisher, year, edition, pages
F1000 Research Ltd , 2023. Vol. 8, article id 483
Keywords [en]
effector genes, exome chip, genetic discovery, glycaemic traits, summary statistics resources
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Medical Genetics and Genomics
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URN: urn:nbn:se:umu:diva-230493DOI: 10.12688/wellcomeopenres.18754.1PubMedID: 39280063Scopus ID: 2-s2.0-85204904115OAI: oai:DiVA.org:umu-230493DiVA, id: diva2:1903249
Note

Version 1. Published: 20 Oct 2023, 8:483 https://doi.org/10.12688/wellcomeopenres.18754.1v

Available from: 2024-10-03 Created: 2024-10-03 Last updated: 2025-05-09Bibliographically approved

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Hallmans, GöranRenström, FridaRolandsson, Olov

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