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Inference of Causal Relationships Between Genetic Risk Factors for Cardiometabolic Phenotypes and Female‐Specific Health Conditions

BACKGROUND: Cardiometabolic diseases are highly comorbid, but their relationship with female‐specific or overwhelmingly female‐predominant health conditions (breast cancer, endometriosis, pregnancy complications) is understudied. This study aimed to estimate the cross‐trait genetic overlap and influ...

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Autores principales: Xiao, Brenda, Velez Edwards, Digna R., Lucas, Anastasia, Drivas, Theodore, Gray, Kathryn, Keating, Brendan, Weng, Chunhua, Jarvik, Gail P., Hakonarson, Hakon, Kottyan, Leah, Elhadad, Noemie, Wei, Wei‐Qi, Luo, Yuan, Kim, Dokyoon, Ritchie, Marylyn, Verma, Shefali Setia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10111435/
https://www.ncbi.nlm.nih.gov/pubmed/36846987
http://dx.doi.org/10.1161/JAHA.121.026561
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author Xiao, Brenda
Velez Edwards, Digna R.
Lucas, Anastasia
Drivas, Theodore
Gray, Kathryn
Keating, Brendan
Weng, Chunhua
Jarvik, Gail P.
Hakonarson, Hakon
Kottyan, Leah
Elhadad, Noemie
Wei, Wei‐Qi
Luo, Yuan
Kim, Dokyoon
Ritchie, Marylyn
Verma, Shefali Setia
author_facet Xiao, Brenda
Velez Edwards, Digna R.
Lucas, Anastasia
Drivas, Theodore
Gray, Kathryn
Keating, Brendan
Weng, Chunhua
Jarvik, Gail P.
Hakonarson, Hakon
Kottyan, Leah
Elhadad, Noemie
Wei, Wei‐Qi
Luo, Yuan
Kim, Dokyoon
Ritchie, Marylyn
Verma, Shefali Setia
author_sort Xiao, Brenda
collection PubMed
description BACKGROUND: Cardiometabolic diseases are highly comorbid, but their relationship with female‐specific or overwhelmingly female‐predominant health conditions (breast cancer, endometriosis, pregnancy complications) is understudied. This study aimed to estimate the cross‐trait genetic overlap and influence of genetic burden of cardiometabolic traits on health conditions unique to women. METHODS AND RESULTS: Using electronic health record data from 71 008 ancestrally diverse women, we examined relationships between 23 obstetrical/gynecological conditions and 4 cardiometabolic phenotypes (body mass index, coronary artery disease, type 2 diabetes, and hypertension) by performing 4 analyses: (1) cross‐trait genetic correlation analyses to compare genetic architecture, (2) polygenic risk score–based association tests to characterize shared genetic effects on disease risk, (3) Mendelian randomization for significant associations to assess cross‐trait causal relationships, and (4) chronology analyses to visualize the timeline of events unique to groups of women with high and low genetic burden for cardiometabolic traits and highlight the disease prevalence in risk groups by age. We observed 27 significant associations between cardiometabolic polygenic scores and obstetrical/gynecological conditions (body mass index and endometrial cancer, body mass index and polycystic ovarian syndrome, type 2 diabetes and gestational diabetes, type 2 diabetes and polycystic ovarian syndrome). Mendelian randomization analysis provided additional evidence of independent causal effects. We also identified an inverse association between coronary artery disease and breast cancer. High cardiometabolic polygenic scores were associated with early development of polycystic ovarian syndrome and gestational hypertension. CONCLUSIONS: We conclude that polygenic susceptibility to cardiometabolic traits is associated with elevated risk of certain female‐specific health conditions.
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spelling pubmed-101114352023-04-19 Inference of Causal Relationships Between Genetic Risk Factors for Cardiometabolic Phenotypes and Female‐Specific Health Conditions Xiao, Brenda Velez Edwards, Digna R. Lucas, Anastasia Drivas, Theodore Gray, Kathryn Keating, Brendan Weng, Chunhua Jarvik, Gail P. Hakonarson, Hakon Kottyan, Leah Elhadad, Noemie Wei, Wei‐Qi Luo, Yuan Kim, Dokyoon Ritchie, Marylyn Verma, Shefali Setia J Am Heart Assoc JAHA Spotlight: Go Red for Women BACKGROUND: Cardiometabolic diseases are highly comorbid, but their relationship with female‐specific or overwhelmingly female‐predominant health conditions (breast cancer, endometriosis, pregnancy complications) is understudied. This study aimed to estimate the cross‐trait genetic overlap and influence of genetic burden of cardiometabolic traits on health conditions unique to women. METHODS AND RESULTS: Using electronic health record data from 71 008 ancestrally diverse women, we examined relationships between 23 obstetrical/gynecological conditions and 4 cardiometabolic phenotypes (body mass index, coronary artery disease, type 2 diabetes, and hypertension) by performing 4 analyses: (1) cross‐trait genetic correlation analyses to compare genetic architecture, (2) polygenic risk score–based association tests to characterize shared genetic effects on disease risk, (3) Mendelian randomization for significant associations to assess cross‐trait causal relationships, and (4) chronology analyses to visualize the timeline of events unique to groups of women with high and low genetic burden for cardiometabolic traits and highlight the disease prevalence in risk groups by age. We observed 27 significant associations between cardiometabolic polygenic scores and obstetrical/gynecological conditions (body mass index and endometrial cancer, body mass index and polycystic ovarian syndrome, type 2 diabetes and gestational diabetes, type 2 diabetes and polycystic ovarian syndrome). Mendelian randomization analysis provided additional evidence of independent causal effects. We also identified an inverse association between coronary artery disease and breast cancer. High cardiometabolic polygenic scores were associated with early development of polycystic ovarian syndrome and gestational hypertension. CONCLUSIONS: We conclude that polygenic susceptibility to cardiometabolic traits is associated with elevated risk of certain female‐specific health conditions. John Wiley and Sons Inc. 2023-02-27 /pmc/articles/PMC10111435/ /pubmed/36846987 http://dx.doi.org/10.1161/JAHA.121.026561 Text en © 2023 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle JAHA Spotlight: Go Red for Women
Xiao, Brenda
Velez Edwards, Digna R.
Lucas, Anastasia
Drivas, Theodore
Gray, Kathryn
Keating, Brendan
Weng, Chunhua
Jarvik, Gail P.
Hakonarson, Hakon
Kottyan, Leah
Elhadad, Noemie
Wei, Wei‐Qi
Luo, Yuan
Kim, Dokyoon
Ritchie, Marylyn
Verma, Shefali Setia
Inference of Causal Relationships Between Genetic Risk Factors for Cardiometabolic Phenotypes and Female‐Specific Health Conditions
title Inference of Causal Relationships Between Genetic Risk Factors for Cardiometabolic Phenotypes and Female‐Specific Health Conditions
title_full Inference of Causal Relationships Between Genetic Risk Factors for Cardiometabolic Phenotypes and Female‐Specific Health Conditions
title_fullStr Inference of Causal Relationships Between Genetic Risk Factors for Cardiometabolic Phenotypes and Female‐Specific Health Conditions
title_full_unstemmed Inference of Causal Relationships Between Genetic Risk Factors for Cardiometabolic Phenotypes and Female‐Specific Health Conditions
title_short Inference of Causal Relationships Between Genetic Risk Factors for Cardiometabolic Phenotypes and Female‐Specific Health Conditions
title_sort inference of causal relationships between genetic risk factors for cardiometabolic phenotypes and female‐specific health conditions
topic JAHA Spotlight: Go Red for Women
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10111435/
https://www.ncbi.nlm.nih.gov/pubmed/36846987
http://dx.doi.org/10.1161/JAHA.121.026561
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