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

2023; Wiley; Volume: 12; Issue: 5 Linguagem: Inglês

10.1161/jaha.121.026561

2047-9980

Brenda Xiao, Digna R. Velez Edwards, Anastasia Lucas, Theodore G. Drivas, Kathryn J. Gray, Brendan J. Keating, Chunhua Weng, Gail P. Jarvik, Hákon Hákonarson, Leah C. Kottyan, Noémie Elhadad, Wei‐Qi Wei, Yuan Luo, Dokyoon Kim, Marylyn D. Ritchie, Shefali S. Verma, Gonçalo R. Abecasis, Aris Baras, Michael Cantor, Giovanni Coppola, Andrew Deubler, Aris N. Economides, Katia Karalis, Luca A. Lotta, John D. Overton, Jeffrey G. Reid, Katherine Siminovitch, Alan R. Shuldiner, Christina Beechert, Caitlin Forsythe, Erin D. Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, John D. Overton, Maria Sotiropoulos Padilla, Manasi Pradhan, Kia Manoochehri, Thomas D. Schleicher, Louis Widom, Sarah E. Wolf, Ricardo H. Ulloa, Amelia Averitt, Nilanjana Banerjee, Michael Cantor, Dadong Li, Sameer Malhotra, Deepika Sharma, Jeffrey Staples, Xiaodong Bai, Suganthi Balasubramanian, Suying Bao, Boris Boutkov, Siying Chen, Gisu Eom, Lukas Habegger, Alicia Hawes, Shareef Khalid, Olga Krasheninina, Rouel Lanche, Adam J. Mansfield, Evan K. Maxwell, George Mitra, Mona Nafde, Sean O’Keeffe, Max Orelus, Razvan Panea, Tommy Polanco, Ayesha Rasool, Jeffrey G. Reid, William Salerno, Jeffrey Staples, Kathie Sun, Gonçalo R. Abecasis, Joshua Backman, Amy Damask, Lee Dobbyn, Manuel Allen Revez Ferreira, Arkopravo Ghosh, Christopher E. Gillies, Lauren Gurski, Eric Jorgenson, Hyun Min Kang, Michael D. Kessler, Jack A. Kosmicki, Alexander Li, Nan Lin, Daren Liu, Adam E. Locke, Jonathan Marchini, Anthony Marcketta, Joelle Mbatchou, Arden Moscati, Charles Paulding, Carlo Sidore, Eli A. Stahl, Kyoko Watanabe, Bin Ye, Blair Zhang, Andrey Ziyatdinov, Ariane Ayer, Ayşegül Güvenek, George Hindy, Giovanni Coppola, Jan Freudenberg, Jonas Bovijn, Katherine Siminovitch, Kavita Praveen, Luca A. Lotta, Manav Kapoor, Mary E. Haas, Moeen Riaz, Niek Verweij, Olukayode Sosina, Parsa Akbari, Priyanka Nakka, Sahar Gelfman, Sujit Gokhale, Tanima De, Veera M. Rajagopal, Alan R. Shuldiner, Bin Ye, Gannie Tzoneva, Juan L. Rodriguez‐Flores, Shek Man Chim, Valerio Donato, Aris N. Economides, Daniel Fernández, Giusy Della Gatta, Alessandro Di Gioia, Kristen E. Howell, Katia Karalis, Lori Khrimian, Minhee Kim, Héctor R. Martínez, Lawrence Miloscio, Sheilyn Nunez, Elias Pavlopoulos, Trikaldarshi Persaud, Esteban Chen, Marcus B. Jones, Michelle G. LeBlanc, Jason Mighty, Lyndon J. Mitnaul, Nirupama Nishtala, Nadia A. Rana,

BRCA gene mutations in cancer

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.