1. The power of TOPMed imputation for the discovery of Latino enriched rare variants associated with type 2 diabetes
- Author
-
Alicia Huerta-Chagoya, Philip Schroeder, Ravi Mandla, Aaron J. Deutsch, Wanying Zhu, Lauren Petty, Xiaoyan Yi, Joanne B. Cole, Miriam S. Udler, Peter Dornbos, Bianca Porneala, Daniel DiCorpo, Ching-Ti Liu, Josephine H. Li, Lukasz Szczerbiński, Varinderpal Kaur, Joohyun Kim, Yingchang Lu, Alicia Martin, Decio L. Eizirik, Piero Marchetti, Lorella Marselli, Ling Chen, Shylaja Srinivasan, Jennifer Todd, Jason Flannick, Rose Gubitosi-Klug, Lynne Levitsky, Rachana Shah, Megan Kelsey, Brian Burke, Dana M. Dabelea, Jasmin Divers, Santica Marcovina, Lauren Stalbow, Ruth J.F. Loos, Burcu F. Darst, Charles Kooperberg, Laura M. Raffield, Christopher Haiman, Quan Sun, Joseph B. McCormick, Susan P. Fisher-Hoch, Maria L. Ordoñez, James Meigs, Leslie J. Baier, Clicerio González-Villalpando, Maria Elena González-Villalpando, Lorena Orozco, Andrés Moreno, Carlos A. Aguilar-Salinas, Teresa Tusié, Josée Dupuis, Maggie C.Y. Ng, Alisa Manning, Heather M. Highland, Miriam Cnop, Robert Hanson, Jennifer Below, Jose C. Florez, Aaron Leong, and Josep M. Mercader
- Abstract
HypothesisThe prevalence of type 2 diabetes is higher in Latino populations compared with other major ancestry groups. Not only has the Latino population been systematically underrepresented in large-scale genetic analyses, but previous studies relied on the imputation of ungenotyped variants based on the 1000 Genomes (1000G) imputation reference panel, which results in suboptimal capture of low-frequency or Latino-enriched variants. The NHLBI Trans-Omics for Precision Medicine (TOPMed) reference panel represents a unique opportunity to analyze rare genetic variations in the Latino population.MethodsWe evaluate the TOPMed imputation performance using genotyping array and whole-exome sequence data in 6 Latino cohorts. To evaluate the ability of TOPMed imputation of increasing the identified loci, we performed a Latino type 2 diabetes GWAS meta-analysis in 8,150 type 2 diabetes cases and 10,735 controls and replicated the results in 6 additional cohorts including whole-genome sequence data from the All of Us cohort.ResultsWe show that, compared to imputation with 1000G, the TOPMed panel improves the identification of rare and low-frequency variants. We identified 26 distinct signals including a novel genome-wide significant variant (minor allele frequency 1.6%, OR=2.0, P=3.4×10−9) near ORC5. A Latino-tailored polygenic score constructed from our data and GWAS data from East Asian and European populations improves the prediction accuracy in a Latino target dataset, explaining up to 7.6% of the type 2 diabetes risk variance.ConclusionsOur results demonstrate the utility of TOPMed imputation for identifying low-frequency variation in understudied populations, leading to the discovery of novel disease associations and the improvement of polygenic scores.
- Published
- 2022
- Full Text
- View/download PDF