Anthony Piron, Florian Szymczak, Lise Folon, Daniel J M Crouch, Theodora Papadopoulou, Maria Lytrivi, Yue Tong, Maria Inês Alvelos, Maikel L Colli, Xiaoyan Yi, Marcin L Pekalski, Konstantinos Hatzikotoulas, Alicia Huerta-Chagoya, Henry J Taylor, Matthieu Defrance, John A Todd, Décio L Eizirik, Josep M Mercader, Miriam Cnop
{"title":"Identification of novel type 1 and type 2 diabetes genes by co-localization of human islet eQTL and GWAS variants with colocRedRibbon.","authors":"Anthony Piron, Florian Szymczak, Lise Folon, Daniel J M Crouch, Theodora Papadopoulou, Maria Lytrivi, Yue Tong, Maria Inês Alvelos, Maikel L Colli, Xiaoyan Yi, Marcin L Pekalski, Konstantinos Hatzikotoulas, Alicia Huerta-Chagoya, Henry J Taylor, Matthieu Defrance, John A Todd, Décio L Eizirik, Josep M Mercader, Miriam Cnop","doi":"10.1016/j.xgen.2025.101004","DOIUrl":null,"url":null,"abstract":"<p><p>Over 1,000 genetic variants have been associated with diabetes by genome-wide association studies (GWASs), but for most, their functional impact is unknown; only 7% alter gene expression in pancreatic islets in expression quantitative trait locus (eQTL) studies. To fill this gap, we developed a co-localization pipeline, colocRedRibbon, that prefilters eQTLs by the direction of effect on gene expression and shortlists overlapping eQTL and GWAS variants prior to co-localization. Applying colocRedRibbon to recent diabetes and glycemic trait GWASs, we identified 292 co-localizing gene regions, including 24 co-localizations for type 1 diabetes and 268 for type 2 diabetes and glycemic traits, representing a 4-fold increase. A low-frequency type 2 diabetes protective variant increases islet MYO5C expression, and a type 1 diabetes protective variant increases FUT2 expression. These novel co-localizations advance the understanding of diabetes genetics and its impact on human islet biology. colocRedRibbon has broad applicability to co-localize GWASs and various QTLs.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"101004"},"PeriodicalIF":11.1000,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell genomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.xgen.2025.101004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Over 1,000 genetic variants have been associated with diabetes by genome-wide association studies (GWASs), but for most, their functional impact is unknown; only 7% alter gene expression in pancreatic islets in expression quantitative trait locus (eQTL) studies. To fill this gap, we developed a co-localization pipeline, colocRedRibbon, that prefilters eQTLs by the direction of effect on gene expression and shortlists overlapping eQTL and GWAS variants prior to co-localization. Applying colocRedRibbon to recent diabetes and glycemic trait GWASs, we identified 292 co-localizing gene regions, including 24 co-localizations for type 1 diabetes and 268 for type 2 diabetes and glycemic traits, representing a 4-fold increase. A low-frequency type 2 diabetes protective variant increases islet MYO5C expression, and a type 1 diabetes protective variant increases FUT2 expression. These novel co-localizations advance the understanding of diabetes genetics and its impact on human islet biology. colocRedRibbon has broad applicability to co-localize GWASs and various QTLs.