Identification of novel type 1 and type 2 diabetes genes by co-localization of human islet eQTL and GWAS variants with colocRedRibbon.
| Citation | Piron, Anthony, et al. “Identification of Novel Type 1 and Type 2 Diabetes Genes by Co-Localization of Human Islet EQTL and GWAS Variants With ColocRedRibbon”. 2025. Cell Genomics, vol. 5, no. 11, 2025, p. 101004. |
| Center | Boston Area |
| Author | 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, Type Diabetes Global Genomics Initiative 2, Matthieu Defrance, John A Todd, Décio L Eizirik, Josep M Mercader, Miriam Cnop |
| Keywords | GWAS, co-localization, colocRedRibbon, diabetes, eQTL, Genetics, glycemic traits, insulin, meQTL, multi-ancestry, pQTL, pancreatic islets, β cells |
| 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. |
| Year of Publication |
2025
|
| Journal |
Cell genomics
|
| Volume |
5
|
| Issue |
11
|
| Number of Pages |
101004
|
| Date Published |
11/2025
|
| ISSN Number |
2666-979X
|
| DOI |
10.1016/j.xgen.2025.101004
|
| Alternate Journal |
Cell Genom
|
| PMCID |
PMC12648100
|
| PMID |
40961947
|
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