Inference of Causal Relationships Between Genetic Risk Factors for Cardiometabolic Phenotypes and Female‐Specific Health Conditions
Authors: 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 , Abecasis Goncalo , Baras Aris , Cantor Michael , Coppola Giovanni , Deubler Andrew , Economides Aris , Karalis Katia , Lotta Luca A. , Overton John D. , Reid Jeffrey G. , Siminovitch Katherine , Shuldiner Alan , Beechert Christina , Forsythe Caitlin , Fuller Erin D. , Gu Zhenhua , Lattari Michael , Lopez Alexander , Overton John D. , Padilla Maria Sotiropoulos , Pradhan Manasi , Manoochehri Kia , Schleicher Thomas D. , Widom Louis , Wolf Sarah E. , Ulloa Ricardo H. , Averitt Amelia , Banerjee Nilanjana , Cantor Michael , Li Dadong , Malhotra Sameer , Sharma Deepika , Staples Jeffrey , Bai Xiaodong , Balasubramanian Suganthi , Bao Suying , Boutkov Boris , Chen Siying , Eom Gisu , Habegger Lukas , Hawes Alicia , Khalid Shareef , Krasheninina Olga , Lanche Rouel , Mansfield Adam J. , Maxwell Evan K. , Mitra George , Nafde Mona , O’Keeffe Sean , Orelus Max , Panea Razvan , Polanco Tommy , Rasool Ayesha , Reid Jeffrey G. , Salerno William , Staples Jeffrey C. , Sun Kathie , Abecasis Goncalo , Backman Joshua , Damask Amy , Dobbyn Lee , Ferreira Manuel Allen Revez , Ghosh Arkopravo , Gillies Christopher , Gurski Lauren , Jorgenson Eric , Kang Hyun Min , Kessler Michael , Kosmicki Jack , Li Alexander , Lin Nan , Liu Daren , Locke Adam , Marchini Jonathan , Marcketta Anthony , Mbatchou Joelle , Moscati Arden , Paulding Charles , Sidore Carlo , Stahl Eli , Watanabe Kyoko , Ye Bin , Zhang Blair , Ziyatdinov Andrey , Ayer Ariane , Guvenek Aysegul , Hindy George , Coppola Giovanni , Freudenberg Jan , Bovijn Jonas , Siminovitch Katherine , Praveen Kavita , Lotta Luca A. , Kapoor Manav , Haas Mary , Riaz Moeen , Verweij Niek , Sosina Olukayode , Akbari Parsa , Nakka Priyanka , Gelfman Sahar , Gokhale Sujit , De Tanima , Rajagopal Veera , Shuldiner Alan , Ye Bin , Tzoneva Gannie , Rodriguez‐Flores Juan , Chim Shek Man , Donato Valerio , Economides Aris , Fernandez Daniel , Gatta Giusy Della , Di Gioia Alessandro , Howell Kristen , Karalis Katia , Khrimian Lori , Kim Minhee , Martinez Hector , Miloscio Lawrence , Nunez Sheilyn , Pavlopoulos Elias , Persaud Trikaldarshi , Chen Esteban , Jones Marcus B. , LeBlanc Michelle G. , Mighty Jason , Mitnaul Lyndon J. , Nishtala Nirupama , Rana Nadia 
Published: February 2023

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.