The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes

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The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes. / 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; Mexican Biobank.

In: Diabetologia, Vol. 66, 2023, p. 1273-1288.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Huerta-Chagoya, A, Schroeder, P, Mandla, R, Deutsch, AJ, Zhu, W, Petty, L, Yi, X, Cole, JB, Udler, MS, Dornbos, P, Porneala, B, DiCorpo, D, Liu, CT, Li, JH, Szczerbiński, L, Kaur, V, Kim, J, Lu, Y, Martin, A, Eizirik, DL, Marchetti, P, Marselli, L, Chen, L, Srinivasan, S, Todd, J, Flannick, J, Gubitosi-Klug, R, Levitsky, L, Shah, R, Kelsey, M, Burke, B, Dabelea, DM, Divers, J, Marcovina, S, Stalbow, L, Loos, RJF, Darst, BF, Kooperberg, C, Raffield, LM, Haiman, C, Sun, Q, McCormick, JB, Fisher-Hoch, SP, Ordoñez, ML, Meigs, J, Baier, LJ, González-Villalpando, C, González-Villalpando, ME, Orozco, L, García-García, L & Mexican Biobank 2023, 'The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes', Diabetologia, vol. 66, pp. 1273-1288. https://doi.org/10.1007/s00125-023-05912-9

APA

Huerta-Chagoya, A., Schroeder, P., Mandla, R., Deutsch, A. J., Zhu, W., Petty, L., Yi, X., Cole, J. B., Udler, M. S., Dornbos, P., Porneala, B., DiCorpo, D., Liu, C. T., Li, J. H., Szczerbiński, L., Kaur, V., Kim, J., Lu, Y., Martin, A., ... Mexican Biobank (2023). The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes. Diabetologia, 66, 1273-1288. https://doi.org/10.1007/s00125-023-05912-9

Vancouver

Huerta-Chagoya A, Schroeder P, Mandla R, Deutsch AJ, Zhu W, Petty L et al. The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes. Diabetologia. 2023;66:1273-1288. https://doi.org/10.1007/s00125-023-05912-9

Author

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 ; Mexican Biobank. / The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes. In: Diabetologia. 2023 ; Vol. 66. pp. 1273-1288.

Bibtex

@article{c5232ffc52a146e8ba1cd15b43642df3,
title = "The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes",
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: [Figure not available: see fulltext.]",
keywords = "GWAS meta-analysis, Latino population, Polygenic score, TOPMed imputation, Type 2 diabetes",
author = "Alicia Huerta-Chagoya and Philip Schroeder and Ravi Mandla and Deutsch, {Aaron J.} and Wanying Zhu and Lauren Petty and Xiaoyan Yi and Cole, {Joanne B.} and Udler, {Miriam S.} and Peter Dornbos and Bianca Porneala and Daniel DiCorpo and Liu, {Ching Ti} and Li, {Josephine H.} and Lukasz Szczerbi{\'n}ski and Varinderpal Kaur and Joohyun Kim and Yingchang Lu and Alicia Martin and Eizirik, {Decio L.} and Piero Marchetti and Lorella Marselli and Ling Chen and Shylaja Srinivasan and Jennifer Todd and Jason Flannick and Rose Gubitosi-Klug and Lynne Levitsky and Rachana Shah and Megan Kelsey and Brian Burke and Dabelea, {Dana M.} and Jasmin Divers and Santica Marcovina and Lauren Stalbow and Loos, {Ruth J.F.} and Darst, {Burcu F.} and Charles Kooperberg and Raffield, {Laura M.} and Christopher Haiman and Quan Sun and McCormick, {Joseph B.} and Fisher-Hoch, {Susan P.} and Ordo{\~n}ez, {Maria L.} and James Meigs and Baier, {Leslie J.} and Clicerio Gonz{\'a}lez-Villalpando and Gonz{\'a}lez-Villalpando, {Maria Elena} and Lorena Orozco and Lourdes Garc{\'i}a-Garc{\'i}a and {Mexican Biobank}",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s).",
year = "2023",
doi = "10.1007/s00125-023-05912-9",
language = "English",
volume = "66",
pages = "1273--1288",
journal = "Diabetologia",
issn = "0012-186X",
publisher = "Springer",

}

RIS

TY - JOUR

T1 - The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes

AU - Huerta-Chagoya, Alicia

AU - Schroeder, Philip

AU - Mandla, Ravi

AU - Deutsch, Aaron J.

AU - Zhu, Wanying

AU - Petty, Lauren

AU - Yi, Xiaoyan

AU - Cole, Joanne B.

AU - Udler, Miriam S.

AU - Dornbos, Peter

AU - Porneala, Bianca

AU - DiCorpo, Daniel

AU - Liu, Ching Ti

AU - Li, Josephine H.

AU - Szczerbiński, Lukasz

AU - Kaur, Varinderpal

AU - Kim, Joohyun

AU - Lu, Yingchang

AU - Martin, Alicia

AU - Eizirik, Decio L.

AU - Marchetti, Piero

AU - Marselli, Lorella

AU - Chen, Ling

AU - Srinivasan, Shylaja

AU - Todd, Jennifer

AU - Flannick, Jason

AU - Gubitosi-Klug, Rose

AU - Levitsky, Lynne

AU - Shah, Rachana

AU - Kelsey, Megan

AU - Burke, Brian

AU - Dabelea, Dana M.

AU - Divers, Jasmin

AU - Marcovina, Santica

AU - Stalbow, Lauren

AU - Loos, Ruth J.F.

AU - Darst, Burcu F.

AU - Kooperberg, Charles

AU - Raffield, Laura M.

AU - Haiman, Christopher

AU - Sun, Quan

AU - McCormick, Joseph B.

AU - Fisher-Hoch, Susan P.

AU - Ordoñez, Maria L.

AU - Meigs, James

AU - Baier, Leslie J.

AU - González-Villalpando, Clicerio

AU - González-Villalpando, Maria Elena

AU - Orozco, Lorena

AU - García-García, Lourdes

AU - Mexican Biobank

N1 - Publisher Copyright: © 2023, The Author(s).

PY - 2023

Y1 - 2023

N2 - 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: [Figure not available: see fulltext.]

AB - 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: [Figure not available: see fulltext.]

KW - GWAS meta-analysis

KW - Latino population

KW - Polygenic score

KW - TOPMed imputation

KW - Type 2 diabetes

U2 - 10.1007/s00125-023-05912-9

DO - 10.1007/s00125-023-05912-9

M3 - Journal article

C2 - 37148359

AN - SCOPUS:85158950110

VL - 66

SP - 1273

EP - 1288

JO - Diabetologia

JF - Diabetologia

SN - 0012-186X

ER -

ID: 350992820