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GWAS of random glucose in 476,326 individuals provide insights into diabetes pathophysiology, complications and treatment stratification

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posted on 2025-08-01, 17:31 authored by V Lagou, L Jiang, A Ulrich, L Zudina, KSG González, Z Balkhiyarova, A Faggian, JG Maina, S Chen, PV Todorov, S Sharapov, A David, L Marullo, R Mägi, R-M Rujan, E Ahlqvist, G Thorleifsson, Η Gao, Ε Εvangelou, B Benyamin, RA Scott, A Isaacs, JH Zhao, SM Willems, T Johnson, C Gieger, H Grallert, C Meisinger, M Müller-Nurasyid, RJ Strawbridge, A Goel, D Rybin, E Albrecht, AU Jackson, HM Stringham, IR Corrêa, E Farber-Eger, V Steinthorsdottir, AG Uitterlinden, PB Munroe, MJ Brown, J Schmidberger, O Holmen, B Thorand, K Hveem, T Wilsgaard, KL Mohlke, Z Wang, A Shmeliov, M den Hoed, RJF Loos, W Kratzer, M Haenle, W Koenig, BO Boehm, TM Tan, A Tomas, V Salem, I Barroso, J Tuomilehto, M Boehnke, JC Florez, A Hamsten, H Watkins, I Njølstad, H-E Wichmann, MJ Caulfield, K-T Khaw, CM van Duijn, A Hofman, NJ Wareham, C Langenberg, JB Whitfield, NG Martin, G Montgomery, C Scapoli, I Tzoulaki, P Elliott, U Thorsteinsdottir, K Stefansson, EL Brittain, MI McCarthy, P Froguel, PM Sexton, D Wootten, L Groop, J Dupuis, JB Meigs, G Deganutti, A Demirkan, TH Pers, CA Reynolds, YS Aulchenko, MA Kaakinen, B Jones, I Prokopenko
Conventional measurements of fasting and postprandial blood glucose levels investigated in genome-wide association studies (GWAS) cannot capture the effects of DNA variability on ‘around the clock’ glucoregulatory processes. Here we show that GWAS meta-analysis of glucose measurements under nonstandardized conditions (random glucose (RG)) in 476,326 individuals of diverse ancestries and without diabetes enables locus discovery and innovative pathophysiological observations. We discovered 120 RG loci represented by 150 distinct signals, including 13 with sex-dimorphic effects, two cross-ancestry and seven rare frequency signals. Of these, 44 loci are new for glycemic traits. Regulatory, glycosylation and metagenomic annotations highlight ileum and colon tissues, indicating an underappreciated role of the gastrointestinal tract in controlling blood glucose. Functional follow-up and molecular dynamics simulations of lower frequency coding variants in glucagon-like peptide-1 receptor (GLP1R), a type 2 diabetes treatment target, reveal that optimal selection of GLP-1R agonist therapy will benefit from tailored genetic stratification. We also provide evidence from Mendelian randomization that lung function is modulated by blood glucose and that pulmonary dysfunction is a diabetes complication. Our investigation yields new insights into the biology of glucose regulation, diabetes complications and pathways for treatment stratification.

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© The Author(s) 2023. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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This is the final version. Available on open access from Nature Research via the DOI in this record Data availability: Meta-analysis summary statistics for the GWAS presented in this manuscript are available on the MAGIC website (magicinvestigators.org) and through the NHGRI-EBI GWAS Catalog (https://www.ebi.ac.uk/gwas/downloads/summary-statistics, GCP ID: GCP000666; with study accession codes for Europeans-only meta-analysis: GCST90271557; cross-ancestry meta-analysis: GCST90271558; and sex-dimorphic meta-analysis: GCST90271559). UK Biobank individual-level data can be obtained through a data access application available at https://www.ukbiobank.ac.uk/. In this study, we made use of data made available by: 1000 Genomes project (https://www.genome.gov/27528684/1000-genomes-project); SNPsnap (https://data.broadinstitute.org/mpg/snpsnap/index.html); Tabula Muris (https://www.czbiohub.org/tabula-muris/); GTEx Consortium (https://gtexportal.org/home/); microbiome GWAS (https://mibiogen.gcc.rug.nl/); Human Gut Microbiome Atlas (https://www.microbiomeatlas.org); eQTLGen Consortium (https://www.eqtlgen.org/); TIGER expression data (http://tiger.bsc.es/) and LDHub database (http://ldsc.broadinstitute.org/ldhub/).

Journal

Nature Genetics

Pagination

1448-1461

Publisher

Nature Research

Version

  • Version of Record

Language

en

FCD date

2023-09-11T10:14:10Z

FOA date

2023-09-11T10:16:25Z

Citation

Vol. 55(9), pp. 1448-1461

Department

  • Clinical and Biomedical Sciences

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