The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations

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The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations. / Wang, Zhe; Choi, Shing Wan; Chami, Nathalie; Boerwinkle, Eric; Fornage, Myriam; Redline, Susan; Bis, Joshua C.; Brody, Jennifer A.; Psaty, Bruce M.; Kim, Wonji; McDonald, Merry Lynn N.; Regan, Elizabeth A.; Silverman, Edwin K.; Liu, Ching Ti; Vasan, Ramachandran S.; Kalyani, Rita R.; Mathias, Rasika A.; Yanek, Lisa R.; Arnett, Donna K.; Justice, Anne E.; North, Kari E.; Kaplan, Robert; Heckbert, Susan R; de Andrade, Mariza; Guo, Xiuqing; Lange, Leslie A.; Rich, Stephen S; Rotter, Jerome I.; Ellinor, Patrick T.; Lubitz, Steven A.; Blangero, John; Shoemaker, M. Benjamin; Darbar, Dawood; Gladwin, Mark T.; Albert, Christine M.; Chasman, Daniel I.; Jackson, Rebecca D.; Kooperberg, Charles; Reiner, Alexander P.; O’Reilly, Paul F.; Loos, Ruth J.F.

In: Frontiers in Endocrinology, Vol. 13, 863893, 2022.

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

Harvard

Wang, Z, Choi, SW, Chami, N, Boerwinkle, E, Fornage, M, Redline, S, Bis, JC, Brody, JA, Psaty, BM, Kim, W, McDonald, MLN, Regan, EA, Silverman, EK, Liu, CT, Vasan, RS, Kalyani, RR, Mathias, RA, Yanek, LR, Arnett, DK, Justice, AE, North, KE, Kaplan, R, Heckbert, SR, de Andrade, M, Guo, X, Lange, LA, Rich, SS, Rotter, JI, Ellinor, PT, Lubitz, SA, Blangero, J, Shoemaker, MB, Darbar, D, Gladwin, MT, Albert, CM, Chasman, DI, Jackson, RD, Kooperberg, C, Reiner, AP, O’Reilly, PF & Loos, RJF 2022, 'The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations', Frontiers in Endocrinology, vol. 13, 863893. https://doi.org/10.3389/fendo.2022.863893

APA

Wang, Z., Choi, S. W., Chami, N., Boerwinkle, E., Fornage, M., Redline, S., Bis, J. C., Brody, J. A., Psaty, B. M., Kim, W., McDonald, M. L. N., Regan, E. A., Silverman, E. K., Liu, C. T., Vasan, R. S., Kalyani, R. R., Mathias, R. A., Yanek, L. R., Arnett, D. K., ... Loos, R. J. F. (2022). The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations. Frontiers in Endocrinology, 13, [863893]. https://doi.org/10.3389/fendo.2022.863893

Vancouver

Wang Z, Choi SW, Chami N, Boerwinkle E, Fornage M, Redline S et al. The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations. Frontiers in Endocrinology. 2022;13. 863893. https://doi.org/10.3389/fendo.2022.863893

Author

Wang, Zhe ; Choi, Shing Wan ; Chami, Nathalie ; Boerwinkle, Eric ; Fornage, Myriam ; Redline, Susan ; Bis, Joshua C. ; Brody, Jennifer A. ; Psaty, Bruce M. ; Kim, Wonji ; McDonald, Merry Lynn N. ; Regan, Elizabeth A. ; Silverman, Edwin K. ; Liu, Ching Ti ; Vasan, Ramachandran S. ; Kalyani, Rita R. ; Mathias, Rasika A. ; Yanek, Lisa R. ; Arnett, Donna K. ; Justice, Anne E. ; North, Kari E. ; Kaplan, Robert ; Heckbert, Susan R ; de Andrade, Mariza ; Guo, Xiuqing ; Lange, Leslie A. ; Rich, Stephen S ; Rotter, Jerome I. ; Ellinor, Patrick T. ; Lubitz, Steven A. ; Blangero, John ; Shoemaker, M. Benjamin ; Darbar, Dawood ; Gladwin, Mark T. ; Albert, Christine M. ; Chasman, Daniel I. ; Jackson, Rebecca D. ; Kooperberg, Charles ; Reiner, Alexander P. ; O’Reilly, Paul F. ; Loos, Ruth J.F. / The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations. In: Frontiers in Endocrinology. 2022 ; Vol. 13.

Bibtex

@article{d8e4ba010a2846f19e2c6f98dd112592,
title = "The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations",
abstract = "Polygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) ≥1%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRScommon) with a rare variant PRS (PRSrare) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m2), obesity (BMI ≥ 30 kg/m2), and extreme obesity (BMI ≥ 40 kg/m2). We built PRSscommon and PRSsrare using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRScommon explained 10.1% of variation in BMI, and 18.3% and 22.5% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRSrare explained 1.49%, and 2.97% and 3.68%, respectively. The PRSrare was associated with an increased risk of obesity and extreme obesity (ORobesity = 1.37 per SDPRS, Pobesity = 1.7x10-85; ORextremeobesity = 1.55 per SDPRS, Pextremeobesity = 3.8x10-40), which was attenuated, after adjusting for PRScommon (ORobesity = 1.08 per SDPRS, Pobesity = 9.8x10-6; ORextremeobesity= 1.09 per SDPRS, Pextremeobesity = 0.02). When PRSrare and PRScommon are combined, the increase in explained variance attributed to PRSrare was small (incremental Nagelkerke R2 = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRSrare to PRScommon provided little improvement to the prediction of obesity (PRSrare AUC = 0.591; PRScommon AUC = 0.708; PRScombined AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRSrare provides limited improvement over PRScommon in the prediction of obesity risk, based on these large populations.",
keywords = "BMI - body mass index, burden score, C+T, lassosum, obesity risk, polygenic risk score, PRS-CS, rare variants",
author = "Zhe Wang and Choi, {Shing Wan} and Nathalie Chami and Eric Boerwinkle and Myriam Fornage and Susan Redline and Bis, {Joshua C.} and Brody, {Jennifer A.} and Psaty, {Bruce M.} and Wonji Kim and McDonald, {Merry Lynn N.} and Regan, {Elizabeth A.} and Silverman, {Edwin K.} and Liu, {Ching Ti} and Vasan, {Ramachandran S.} and Kalyani, {Rita R.} and Mathias, {Rasika A.} and Yanek, {Lisa R.} and Arnett, {Donna K.} and Justice, {Anne E.} and North, {Kari E.} and Robert Kaplan and Susan R Heckbert and {de Andrade}, Mariza and Xiuqing Guo and Lange, {Leslie A.} and Stephen S Rich and Rotter, {Jerome I.} and Ellinor, {Patrick T.} and Lubitz, {Steven A.} and John Blangero and Shoemaker, {M. Benjamin} and Dawood Darbar and Gladwin, {Mark T.} and Albert, {Christine M.} and Chasman, {Daniel I.} and Jackson, {Rebecca D.} and Charles Kooperberg and Reiner, {Alexander P.} and O{\textquoteright}Reilly, {Paul F.} and Loos, {Ruth J.F.}",
note = "Publisher Copyright: Copyright {\textcopyright} 2022 Wang, Choi, Chami, Boerwinkle, Fornage, Redline, Bis, Brody, Psaty, Kim, McDonald, Regan, Silverman, Liu, Vasan, Kalyani, Mathias, Yanek, Arnett, Justice, North, Kaplan, Heckbert, de Andrade, Guo, Lange, Rich, Rotter, Ellinor, Lubitz, Blangero, Shoemaker, Darbar, Gladwin, Albert, Chasman, Jackson, Kooperberg, Reiner, O{\textquoteright}Reilly and Loos.",
year = "2022",
doi = "10.3389/fendo.2022.863893",
language = "English",
volume = "13",
journal = "Frontiers in Endocrinology",
issn = "1664-2392",
publisher = "Frontiers Media S.A.",

}

RIS

TY - JOUR

T1 - The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations

AU - Wang, Zhe

AU - Choi, Shing Wan

AU - Chami, Nathalie

AU - Boerwinkle, Eric

AU - Fornage, Myriam

AU - Redline, Susan

AU - Bis, Joshua C.

AU - Brody, Jennifer A.

AU - Psaty, Bruce M.

AU - Kim, Wonji

AU - McDonald, Merry Lynn N.

AU - Regan, Elizabeth A.

AU - Silverman, Edwin K.

AU - Liu, Ching Ti

AU - Vasan, Ramachandran S.

AU - Kalyani, Rita R.

AU - Mathias, Rasika A.

AU - Yanek, Lisa R.

AU - Arnett, Donna K.

AU - Justice, Anne E.

AU - North, Kari E.

AU - Kaplan, Robert

AU - Heckbert, Susan R

AU - de Andrade, Mariza

AU - Guo, Xiuqing

AU - Lange, Leslie A.

AU - Rich, Stephen S

AU - Rotter, Jerome I.

AU - Ellinor, Patrick T.

AU - Lubitz, Steven A.

AU - Blangero, John

AU - Shoemaker, M. Benjamin

AU - Darbar, Dawood

AU - Gladwin, Mark T.

AU - Albert, Christine M.

AU - Chasman, Daniel I.

AU - Jackson, Rebecca D.

AU - Kooperberg, Charles

AU - Reiner, Alexander P.

AU - O’Reilly, Paul F.

AU - Loos, Ruth J.F.

N1 - Publisher Copyright: Copyright © 2022 Wang, Choi, Chami, Boerwinkle, Fornage, Redline, Bis, Brody, Psaty, Kim, McDonald, Regan, Silverman, Liu, Vasan, Kalyani, Mathias, Yanek, Arnett, Justice, North, Kaplan, Heckbert, de Andrade, Guo, Lange, Rich, Rotter, Ellinor, Lubitz, Blangero, Shoemaker, Darbar, Gladwin, Albert, Chasman, Jackson, Kooperberg, Reiner, O’Reilly and Loos.

PY - 2022

Y1 - 2022

N2 - Polygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) ≥1%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRScommon) with a rare variant PRS (PRSrare) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m2), obesity (BMI ≥ 30 kg/m2), and extreme obesity (BMI ≥ 40 kg/m2). We built PRSscommon and PRSsrare using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRScommon explained 10.1% of variation in BMI, and 18.3% and 22.5% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRSrare explained 1.49%, and 2.97% and 3.68%, respectively. The PRSrare was associated with an increased risk of obesity and extreme obesity (ORobesity = 1.37 per SDPRS, Pobesity = 1.7x10-85; ORextremeobesity = 1.55 per SDPRS, Pextremeobesity = 3.8x10-40), which was attenuated, after adjusting for PRScommon (ORobesity = 1.08 per SDPRS, Pobesity = 9.8x10-6; ORextremeobesity= 1.09 per SDPRS, Pextremeobesity = 0.02). When PRSrare and PRScommon are combined, the increase in explained variance attributed to PRSrare was small (incremental Nagelkerke R2 = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRSrare to PRScommon provided little improvement to the prediction of obesity (PRSrare AUC = 0.591; PRScommon AUC = 0.708; PRScombined AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRSrare provides limited improvement over PRScommon in the prediction of obesity risk, based on these large populations.

AB - Polygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) ≥1%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRScommon) with a rare variant PRS (PRSrare) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m2), obesity (BMI ≥ 30 kg/m2), and extreme obesity (BMI ≥ 40 kg/m2). We built PRSscommon and PRSsrare using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRScommon explained 10.1% of variation in BMI, and 18.3% and 22.5% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRSrare explained 1.49%, and 2.97% and 3.68%, respectively. The PRSrare was associated with an increased risk of obesity and extreme obesity (ORobesity = 1.37 per SDPRS, Pobesity = 1.7x10-85; ORextremeobesity = 1.55 per SDPRS, Pextremeobesity = 3.8x10-40), which was attenuated, after adjusting for PRScommon (ORobesity = 1.08 per SDPRS, Pobesity = 9.8x10-6; ORextremeobesity= 1.09 per SDPRS, Pextremeobesity = 0.02). When PRSrare and PRScommon are combined, the increase in explained variance attributed to PRSrare was small (incremental Nagelkerke R2 = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRSrare to PRScommon provided little improvement to the prediction of obesity (PRSrare AUC = 0.591; PRScommon AUC = 0.708; PRScombined AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRSrare provides limited improvement over PRScommon in the prediction of obesity risk, based on these large populations.

KW - BMI - body mass index

KW - burden score

KW - C+T

KW - lassosum

KW - obesity risk

KW - polygenic risk score

KW - PRS-CS

KW - rare variants

U2 - 10.3389/fendo.2022.863893

DO - 10.3389/fendo.2022.863893

M3 - Journal article

C2 - 35592775

AN - SCOPUS:85130368867

VL - 13

JO - Frontiers in Endocrinology

JF - Frontiers in Endocrinology

SN - 1664-2392

M1 - 863893

ER -

ID: 313648604