The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes
Authors: Huerta-Chagoya Alicia , Schroeder Philip , Mandla Ravi , Deutsch Aaron J. , Zhu Wanying , Petty Lauren , Yi Xiaoyan , Cole Joanne B. , Udler Miriam S. , Dornbos Peter , Porneala Bianca , DiCorpo Daniel , Liu Ching-Ti , Li Josephine H. , Szczerbiński Lukasz , Kaur Varinderpal , Kim Joohyun , Lu Yingchang , Martin Alicia , Eizirik Decio L. , Marchetti Piero , Marselli Lorella , Chen Ling , Srinivasan Shylaja , Todd Jennifer , Flannick Jason , Gubitosi-Klug Rose , Levitsky Lynne , Shah Rachana , Kelsey Megan , Burke Brian , Dabelea Dana M. , Divers Jasmin , Marcovina Santica , Stalbow Lauren , Loos Ruth J. F. , Darst Burcu F. , Kooperberg Charles , Raffield Laura M. , Haiman Christopher , Sun Quan , McCormick Joseph B. , Fisher-Hoch Susan P. , Ordoñez Maria L. , Meigs James , Baier Leslie J. , González-Villalpando Clicerio , González-Villalpando Maria Elena , Orozco Lorena , García-García Lourdes , Moreno-Estrada Andrés ,   Mexican Biobank, Aguilar-Salinas Carlos A. , Tusié Teresa , Dupuis Josée , Ng Maggie C. Y. , Manning Alisa , Highland Heather M. , Cnop Miriam , Hanson Robert , Below Jennifer , Florez Jose C. , Leong Aaron , Mercader Josep M. 
Published: May 2023

Abstract
Aims/hypothesis
The Latino population has been systematically underrepresented in large-scale genetic analyses, and previous studies have relied on the imputation of ungenotyped variants based on the 1000 Genomes (1000G) imputation panel, which results in suboptimal capture of low-frequency or Latino-enriched variants. The National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) released the largest multi-ancestry genotype reference panel representing a unique opportunity to analyse rare genetic variations in the Latino population. We hypothesise that a more comprehensive analysis of low/rare variation using the TOPMed panel would improve our knowledge of the genetics of type 2 diabetes in the Latino population.

Methods
We evaluated the TOPMed imputation performance using genotyping array and whole-exome sequence data in six Latino cohorts. To evaluate the ability of TOPMed imputation to increase the number of identified loci, we performed a Latino type 2 diabetes genome-wide association study (GWAS) meta-analysis in 8150 individuals with type 2 diabetes and 10,735 control individuals and replicated the results in six additional cohorts including whole-genome sequence data from the All of Us cohort.

Results
Compared with imputation with 1000G, the TOPMed panel improved the identification of rare and low-frequency variants. We identified 26 genome-wide significant signals including a novel variant (minor allele frequency 1.7%; OR 1.37, p=3.4 × 10−9). A Latino-tailored polygenic score constructed from our data and GWAS data from East Asian and European populations improved the prediction accuracy in a Latino target dataset, explaining up to 7.6% of the type 2 diabetes risk variance.

Conclusions/interpretation
Our results demonstrate the utility of TOPMed imputation for identifying low-frequency variants in understudied populations, leading to the discovery of novel disease associations and the improvement of polygenic scores.

Data availability
Full summary statistics are available through the Common Metabolic Diseases Knowledge Portal (https://t2d.hugeamp.org/downloads.html) and through the GWAS catalog (https://www.ebi.ac.uk/gwas/, accession ID: GCST90255648). Polygenic score (PS) weights for each ancestry are available via the PGS catalog (https://www.pgscatalog.org, publication ID: PGP000445, scores IDs: PGS003443, PGS003444 and PGS003445).

Graphical abstract