Body Mass Index and Polycystic Ovary Syndrome: A 2-Sample Bidirectional Mendelian Randomization Study
Abstract Background Observational studies have shown a link between elevated body mass index (BMI) and the risk of polycystic ovary syndrome (PCOS). While Mendelian randomization (MR) studies in Europeans have suggested a causal role of increased BMI in PCOS, whether the same role is suggested in As...
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creator | Zhao, Yalin Xu, Yuping Wang, Xiaomeng Xu, Lin Chen, Jianhua Gao, Chengwen Wu, Chuanhong Pan, Dun Zhang, Qian Zhou, Juan Chen, Ruirui Wang, Zhuo Zhao, Han You, Li Cao, Yunxia Li, Zhiqiang Shi, Yongyong |
description | Abstract
Background
Observational studies have shown a link between elevated body mass index (BMI) and the risk of polycystic ovary syndrome (PCOS). While Mendelian randomization (MR) studies in Europeans have suggested a causal role of increased BMI in PCOS, whether the same role is suggested in Asians has yet to be investigated. We used MR studies to infer causal effects using genetic data from East Asian populations.
Methods and Findings
We performed a 2-sample bidirectional MR analysis using summary statistics from genome-wide association studies (GWAS) of BMI (with up to 173 430 individuals) and PCOS (4386 cases and 8017 controls) in East Asian populations. Seventy-eight single nucleotide polymorphisms (SNPs) correlated with BMI were selected as genetic instrumental variables to estimate the causal effect of BMI on PCOS using the inverse-variance weighted (IVW) method. To test the reliability of the results, further sensitivity analyses included MR–Egger regression, weighted median estimates, and leave-one-out analysis. The IVW analysis indicated a significant association between high BMI and the risk of PCOS (odds ratio per standard deviation higher BMI, 2.208; 95% confidence interval 1.537 to 3.168, P = 1.77 × 10–5). In contrast, the genetic risk of PCOS had no significant effect on BMI.
Conclusions
The results of our bidirectional MR study showed that an increase in BMI causes PCOS, while PCOS does not cause an increased BMI. This study provides further genetic support for a link between BMI and PCOS. Further research is needed to interpret the potential mechanisms of this association. |
doi_str_mv | 10.1210/clinem/dgaa125 |
format | Article |
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Background
Observational studies have shown a link between elevated body mass index (BMI) and the risk of polycystic ovary syndrome (PCOS). While Mendelian randomization (MR) studies in Europeans have suggested a causal role of increased BMI in PCOS, whether the same role is suggested in Asians has yet to be investigated. We used MR studies to infer causal effects using genetic data from East Asian populations.
Methods and Findings
We performed a 2-sample bidirectional MR analysis using summary statistics from genome-wide association studies (GWAS) of BMI (with up to 173 430 individuals) and PCOS (4386 cases and 8017 controls) in East Asian populations. Seventy-eight single nucleotide polymorphisms (SNPs) correlated with BMI were selected as genetic instrumental variables to estimate the causal effect of BMI on PCOS using the inverse-variance weighted (IVW) method. To test the reliability of the results, further sensitivity analyses included MR–Egger regression, weighted median estimates, and leave-one-out analysis. The IVW analysis indicated a significant association between high BMI and the risk of PCOS (odds ratio per standard deviation higher BMI, 2.208; 95% confidence interval 1.537 to 3.168, P = 1.77 × 10–5). In contrast, the genetic risk of PCOS had no significant effect on BMI.
Conclusions
The results of our bidirectional MR study showed that an increase in BMI causes PCOS, while PCOS does not cause an increased BMI. This study provides further genetic support for a link between BMI and PCOS. Further research is needed to interpret the potential mechanisms of this association.</description><identifier>ISSN: 0021-972X</identifier><identifier>EISSN: 1945-7197</identifier><identifier>DOI: 10.1210/clinem/dgaa125</identifier><identifier>PMID: 32163573</identifier><language>eng</language><publisher>US: Oxford University Press</publisher><subject>Biomarkers - analysis ; Body Mass Index ; Care and treatment ; Development and progression ; Female ; Genetic aspects ; Genome-Wide Association Study ; Genomes ; Health aspects ; Humans ; Mendelian Randomization Analysis - statistics & numerical data ; Polycystic ovary syndrome ; Polycystic Ovary Syndrome - genetics ; Polycystic Ovary Syndrome - pathology ; Polymorphism, Single Nucleotide ; Prognosis ; Sensitivity analysis ; Single nucleotide polymorphisms ; Single-nucleotide polymorphism ; Statistical analysis ; Stein-Leventhal syndrome</subject><ispartof>The journal of clinical endocrinology and metabolism, 2020-06, Vol.105 (6), p.1778-1784</ispartof><rights>Endocrine Society 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com 2020</rights><rights>Copyright © Oxford University Press 2015</rights><rights>Endocrine Society 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.</rights><rights>COPYRIGHT 2020 Oxford University Press</rights><rights>Endocrine Society 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5075-391438218780bad5200825acd9ac34dd1a1b60ef41a45c1ac258da90c1f686623</citedby><cites>FETCH-LOGICAL-c5075-391438218780bad5200825acd9ac34dd1a1b60ef41a45c1ac258da90c1f686623</cites><orcidid>0000-0001-6485-0221</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2405346324?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,21388,21389,27924,27925,33530,33531,33744,33745,43659,43805,64385,64387,64389,72469,73123,73128,73129,73131</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32163573$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhao, Yalin</creatorcontrib><creatorcontrib>Xu, Yuping</creatorcontrib><creatorcontrib>Wang, Xiaomeng</creatorcontrib><creatorcontrib>Xu, Lin</creatorcontrib><creatorcontrib>Chen, Jianhua</creatorcontrib><creatorcontrib>Gao, Chengwen</creatorcontrib><creatorcontrib>Wu, Chuanhong</creatorcontrib><creatorcontrib>Pan, Dun</creatorcontrib><creatorcontrib>Zhang, Qian</creatorcontrib><creatorcontrib>Zhou, Juan</creatorcontrib><creatorcontrib>Chen, Ruirui</creatorcontrib><creatorcontrib>Wang, Zhuo</creatorcontrib><creatorcontrib>Zhao, Han</creatorcontrib><creatorcontrib>You, Li</creatorcontrib><creatorcontrib>Cao, Yunxia</creatorcontrib><creatorcontrib>Li, Zhiqiang</creatorcontrib><creatorcontrib>Shi, Yongyong</creatorcontrib><title>Body Mass Index and Polycystic Ovary Syndrome: A 2-Sample Bidirectional Mendelian Randomization Study</title><title>The journal of clinical endocrinology and metabolism</title><addtitle>J Clin Endocrinol Metab</addtitle><description>Abstract
Background
Observational studies have shown a link between elevated body mass index (BMI) and the risk of polycystic ovary syndrome (PCOS). While Mendelian randomization (MR) studies in Europeans have suggested a causal role of increased BMI in PCOS, whether the same role is suggested in Asians has yet to be investigated. We used MR studies to infer causal effects using genetic data from East Asian populations.
Methods and Findings
We performed a 2-sample bidirectional MR analysis using summary statistics from genome-wide association studies (GWAS) of BMI (with up to 173 430 individuals) and PCOS (4386 cases and 8017 controls) in East Asian populations. Seventy-eight single nucleotide polymorphisms (SNPs) correlated with BMI were selected as genetic instrumental variables to estimate the causal effect of BMI on PCOS using the inverse-variance weighted (IVW) method. To test the reliability of the results, further sensitivity analyses included MR–Egger regression, weighted median estimates, and leave-one-out analysis. The IVW analysis indicated a significant association between high BMI and the risk of PCOS (odds ratio per standard deviation higher BMI, 2.208; 95% confidence interval 1.537 to 3.168, P = 1.77 × 10–5). In contrast, the genetic risk of PCOS had no significant effect on BMI.
Conclusions
The results of our bidirectional MR study showed that an increase in BMI causes PCOS, while PCOS does not cause an increased BMI. This study provides further genetic support for a link between BMI and PCOS. Further research is needed to interpret the potential mechanisms of this association.</description><subject>Biomarkers - analysis</subject><subject>Body Mass Index</subject><subject>Care and treatment</subject><subject>Development and progression</subject><subject>Female</subject><subject>Genetic aspects</subject><subject>Genome-Wide Association Study</subject><subject>Genomes</subject><subject>Health aspects</subject><subject>Humans</subject><subject>Mendelian Randomization Analysis - statistics & numerical data</subject><subject>Polycystic ovary syndrome</subject><subject>Polycystic Ovary Syndrome - genetics</subject><subject>Polycystic Ovary Syndrome - pathology</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Prognosis</subject><subject>Sensitivity analysis</subject><subject>Single nucleotide polymorphisms</subject><subject>Single-nucleotide polymorphism</subject><subject>Statistical analysis</subject><subject>Stein-Leventhal syndrome</subject><issn>0021-972X</issn><issn>1945-7197</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNqFkd1rFDEUxYModq2--igBX_Rh2nzOh2_b4kehpeIq-DbcTe60qZnJmsxYx7_eLLsqSEXyEMj9ncO5OYQ85eyIC86OjXcD9sf2CoALfY8seKN0UfGmuk8WjAleNJX4fEAepXTDGFdKy4fkQApeSl3JBcGTYGd6ASnRs8HidwqDpe-Dn82cRmfo5TeIM13Ng42hx1d0SUWxgn7jkZ446yKa0YUBPL3ALPcOBvohW4Te_YDthK7Gyc6PyYMOfMIn-_uQfHrz-uPpu-L88u3Z6fK8MJpVupANV7IWvK5qtgarBWO10GBsA0YqaznwdcmwUxyUNhyM0LWFhhnelXVZCnlIXux8NzF8nTCNbe-SQe9hwDClVsiqkko3ss7o87_QmzDFvEmmFNNSlVKoP9QVeGzd0IUxgtmatstSNnXDhCwzdXQHlY_F3pkwYOfy-10CE0NKEbt2E12ff7rlrN322u56bfe9ZsGzfdpp3aP9jf8qMgNiB9wGP2JMX_x0i7G9RvDj9b9dX-5EYdr8L8FPdLy9Mw</recordid><startdate>202006</startdate><enddate>202006</enddate><creator>Zhao, Yalin</creator><creator>Xu, Yuping</creator><creator>Wang, Xiaomeng</creator><creator>Xu, Lin</creator><creator>Chen, Jianhua</creator><creator>Gao, Chengwen</creator><creator>Wu, Chuanhong</creator><creator>Pan, Dun</creator><creator>Zhang, Qian</creator><creator>Zhou, Juan</creator><creator>Chen, Ruirui</creator><creator>Wang, Zhuo</creator><creator>Zhao, Han</creator><creator>You, Li</creator><creator>Cao, Yunxia</creator><creator>Li, Zhiqiang</creator><creator>Shi, Yongyong</creator><general>Oxford University Press</general><general>Copyright Oxford University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QP</scope><scope>7T5</scope><scope>7TM</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-6485-0221</orcidid></search><sort><creationdate>202006</creationdate><title>Body Mass Index and Polycystic Ovary Syndrome: A 2-Sample Bidirectional Mendelian Randomization Study</title><author>Zhao, Yalin ; Xu, Yuping ; Wang, Xiaomeng ; Xu, Lin ; Chen, Jianhua ; Gao, Chengwen ; Wu, Chuanhong ; Pan, Dun ; Zhang, Qian ; Zhou, Juan ; Chen, Ruirui ; Wang, Zhuo ; Zhao, Han ; You, Li ; Cao, Yunxia ; Li, Zhiqiang ; Shi, Yongyong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5075-391438218780bad5200825acd9ac34dd1a1b60ef41a45c1ac258da90c1f686623</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Biomarkers - analysis</topic><topic>Body Mass Index</topic><topic>Care and treatment</topic><topic>Development and progression</topic><topic>Female</topic><topic>Genetic aspects</topic><topic>Genome-Wide Association Study</topic><topic>Genomes</topic><topic>Health aspects</topic><topic>Humans</topic><topic>Mendelian Randomization Analysis - statistics & numerical data</topic><topic>Polycystic ovary syndrome</topic><topic>Polycystic Ovary Syndrome - genetics</topic><topic>Polycystic Ovary Syndrome - pathology</topic><topic>Polymorphism, Single Nucleotide</topic><topic>Prognosis</topic><topic>Sensitivity analysis</topic><topic>Single nucleotide polymorphisms</topic><topic>Single-nucleotide polymorphism</topic><topic>Statistical analysis</topic><topic>Stein-Leventhal syndrome</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhao, Yalin</creatorcontrib><creatorcontrib>Xu, Yuping</creatorcontrib><creatorcontrib>Wang, Xiaomeng</creatorcontrib><creatorcontrib>Xu, Lin</creatorcontrib><creatorcontrib>Chen, Jianhua</creatorcontrib><creatorcontrib>Gao, Chengwen</creatorcontrib><creatorcontrib>Wu, Chuanhong</creatorcontrib><creatorcontrib>Pan, Dun</creatorcontrib><creatorcontrib>Zhang, Qian</creatorcontrib><creatorcontrib>Zhou, Juan</creatorcontrib><creatorcontrib>Chen, Ruirui</creatorcontrib><creatorcontrib>Wang, Zhuo</creatorcontrib><creatorcontrib>Zhao, Han</creatorcontrib><creatorcontrib>You, Li</creatorcontrib><creatorcontrib>Cao, Yunxia</creatorcontrib><creatorcontrib>Li, Zhiqiang</creatorcontrib><creatorcontrib>Shi, Yongyong</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Immunology Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>The journal of clinical endocrinology and metabolism</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhao, Yalin</au><au>Xu, Yuping</au><au>Wang, Xiaomeng</au><au>Xu, Lin</au><au>Chen, Jianhua</au><au>Gao, Chengwen</au><au>Wu, Chuanhong</au><au>Pan, Dun</au><au>Zhang, Qian</au><au>Zhou, Juan</au><au>Chen, Ruirui</au><au>Wang, Zhuo</au><au>Zhao, Han</au><au>You, Li</au><au>Cao, Yunxia</au><au>Li, Zhiqiang</au><au>Shi, Yongyong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Body Mass Index and Polycystic Ovary Syndrome: A 2-Sample Bidirectional Mendelian Randomization Study</atitle><jtitle>The journal of clinical endocrinology and metabolism</jtitle><addtitle>J Clin Endocrinol Metab</addtitle><date>2020-06</date><risdate>2020</risdate><volume>105</volume><issue>6</issue><spage>1778</spage><epage>1784</epage><pages>1778-1784</pages><issn>0021-972X</issn><eissn>1945-7197</eissn><abstract>Abstract
Background
Observational studies have shown a link between elevated body mass index (BMI) and the risk of polycystic ovary syndrome (PCOS). While Mendelian randomization (MR) studies in Europeans have suggested a causal role of increased BMI in PCOS, whether the same role is suggested in Asians has yet to be investigated. We used MR studies to infer causal effects using genetic data from East Asian populations.
Methods and Findings
We performed a 2-sample bidirectional MR analysis using summary statistics from genome-wide association studies (GWAS) of BMI (with up to 173 430 individuals) and PCOS (4386 cases and 8017 controls) in East Asian populations. Seventy-eight single nucleotide polymorphisms (SNPs) correlated with BMI were selected as genetic instrumental variables to estimate the causal effect of BMI on PCOS using the inverse-variance weighted (IVW) method. To test the reliability of the results, further sensitivity analyses included MR–Egger regression, weighted median estimates, and leave-one-out analysis. The IVW analysis indicated a significant association between high BMI and the risk of PCOS (odds ratio per standard deviation higher BMI, 2.208; 95% confidence interval 1.537 to 3.168, P = 1.77 × 10–5). In contrast, the genetic risk of PCOS had no significant effect on BMI.
Conclusions
The results of our bidirectional MR study showed that an increase in BMI causes PCOS, while PCOS does not cause an increased BMI. This study provides further genetic support for a link between BMI and PCOS. Further research is needed to interpret the potential mechanisms of this association.</abstract><cop>US</cop><pub>Oxford University Press</pub><pmid>32163573</pmid><doi>10.1210/clinem/dgaa125</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0001-6485-0221</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Biomarkers - analysis Body Mass Index Care and treatment Development and progression Female Genetic aspects Genome-Wide Association Study Genomes Health aspects Humans Mendelian Randomization Analysis - statistics & numerical data Polycystic ovary syndrome Polycystic Ovary Syndrome - genetics Polycystic Ovary Syndrome - pathology Polymorphism, Single Nucleotide Prognosis Sensitivity analysis Single nucleotide polymorphisms Single-nucleotide polymorphism Statistical analysis Stein-Leventhal syndrome |
title | Body Mass Index and Polycystic Ovary Syndrome: A 2-Sample Bidirectional Mendelian Randomization Study |
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