medRxivGenetic & Genomic MedicinePreprint
Type 2 diabetes genetics in 125,000 admixed adults from Mexico City
Jason TorresiD, Jaime Berumen-CamposiD, Diego J. Aguilar-RamireziD, Eirini TrichiaiD, Francisco Martin Barajas-OlmosiD, Humberto Garcia‐OrtíziD, Sam MorrisiD, Michael TurneriD, Elizabeth BarreraiD, Tianshu Liu, Consuelo D. Quinto-CortésiD, Lauren E. PettyiD, Lourdes García‐GarcíaiD, Marı́a Teresa Tusié-LunaiD, Carlos A Aguilar-Salinas, Amanda Yoon-Yee ChongiD, Paulina BacaiD, Fernando RivasiD, Fiona BraggiD, Louisa GnatiuciD, Michael HilliD, Lisa HollandiD, Alejandra Vergara-LopeiD, Rachel L. WadeiD, J. Michael GazianoiD, , Roberto Tapia‐ConyeriD
Abstract
Type 2 diabetes (T2D) is a highly heritable, polygenic disease with over 600 loci identified through genome-wide association studies (GWAS). However, despite possessing unique genetic variation shaped by demographic history and admixture, Latin American populations remain markedly underrepresented in global genomic research. To address this gap, we conducted genome- and exome-wide analyses of 19,431 T2D cases and 105,611 controls from the Mexico City Prospective Study (MCPS). We identified 86 independent GWAS associations, including 21 novel signals, 15 of which replicated in external cohorts. Risk alleles at novel loci were enriched in individuals with Indigenous American ancestry. Exome analyses revealed rare and ultra-rare missense variants with substantial risk effects at HNF1A and GCK, as well as a protein-damaging variant in SLC30A8 that reduced T2D risk by 45% in carriers. Integrative analyses indicate that T2D genetic architecture in Mexico is predominantly driven by common regulatory variation acting in the endocrine pancreas. Polygenic risk scores strongly stratified T2D risk and transferred to Indigenous Mexican populations. These findings demonstrate the power of large-scale genetic discovery in diverse populations to refine disease architecture and identify loci with potential therapeutic relevance.
- organism: human
- assay: whole-exome sequencing
- assay: whole-genome sequencing
- research focus: GWAS / association mapping
- research focus: fine-mapping
- approach: statistical model
- Citations
- 0
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