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The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations
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 disea...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9110787/ https://www.ncbi.nlm.nih.gov/pubmed/35592775 http://dx.doi.org/10.3389/fendo.2022.863893 |
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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. |
author_facet | 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. |
author_sort | Wang, Zhe |
collection | PubMed |
description | 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 (PRS(common)) with a rare variant PRS (PRS(rare)) 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/m(2)), obesity (BMI ≥ 30 kg/m(2)), and extreme obesity (BMI ≥ 40 kg/m(2)). We built PRSs(common) and PRSs(rare) 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 PRS(common) 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 PRS(rare) explained 1.49%, and 2.97% and 3.68%, respectively. The PRS(rare) was associated with an increased risk of obesity and extreme obesity (OR(obesity) = 1.37 per SD(PRS), P (obesity) = 1.7x10(-85); OR(extremeobesity) = 1.55 per SD(PRS), P (extremeobesity) = 3.8x10(-40)), which was attenuated, after adjusting for PRS(common) (OR(obesity) = 1.08 per SD(PRS), P (obesity) = 9.8x10(-6); OR(extremeobesity)= 1.09 per SD(PRS), P (extremeobesity) = 0.02). When PRS(rare) and PRS(common) are combined, the increase in explained variance attributed to PRS(rare) was small (incremental Nagelkerke R(2) = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRS(rare) to PRS(common) provided little improvement to the prediction of obesity (PRS(rare) AUC = 0.591; PRS(common) AUC = 0.708; PRS(combined) AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRS(rare) provides limited improvement over PRS(common) in the prediction of obesity risk, based on these large populations. |
format | Online Article Text |
id | pubmed-9110787 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91107872022-05-18 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. Front Endocrinol (Lausanne) Endocrinology 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 (PRS(common)) with a rare variant PRS (PRS(rare)) 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/m(2)), obesity (BMI ≥ 30 kg/m(2)), and extreme obesity (BMI ≥ 40 kg/m(2)). We built PRSs(common) and PRSs(rare) 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 PRS(common) 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 PRS(rare) explained 1.49%, and 2.97% and 3.68%, respectively. The PRS(rare) was associated with an increased risk of obesity and extreme obesity (OR(obesity) = 1.37 per SD(PRS), P (obesity) = 1.7x10(-85); OR(extremeobesity) = 1.55 per SD(PRS), P (extremeobesity) = 3.8x10(-40)), which was attenuated, after adjusting for PRS(common) (OR(obesity) = 1.08 per SD(PRS), P (obesity) = 9.8x10(-6); OR(extremeobesity)= 1.09 per SD(PRS), P (extremeobesity) = 0.02). When PRS(rare) and PRS(common) are combined, the increase in explained variance attributed to PRS(rare) was small (incremental Nagelkerke R(2) = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRS(rare) to PRS(common) provided little improvement to the prediction of obesity (PRS(rare) AUC = 0.591; PRS(common) AUC = 0.708; PRS(combined) AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRS(rare) provides limited improvement over PRS(common) in the prediction of obesity risk, based on these large populations. Frontiers Media S.A. 2022-05-03 /pmc/articles/PMC9110787/ /pubmed/35592775 http://dx.doi.org/10.3389/fendo.2022.863893 Text en 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 https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology 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 |
title | The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations |
title_full | The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations |
title_fullStr | The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations |
title_full_unstemmed | The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations |
title_short | The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations |
title_sort | value of rare genetic variation in the prediction of common obesity in european ancestry populations |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9110787/ https://www.ncbi.nlm.nih.gov/pubmed/35592775 http://dx.doi.org/10.3389/fendo.2022.863893 |
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