A Polygenic and Phenotypic Risk Prediction for Polycystic Ovary Syndrome Evaluated by Phenome-Wide Association Studies.

As many as 75% of patients with polycystic ovary syndrome (PCOS) are estimated to be unidentified in clinical practice. Utilizing polygenic risk prediction, we aim to identify the phenome-wide comorbidity patterns characteristic of PCOS to improve accurate diagnosis and preventive treatment. Leveraging the electronic health records (EHRs) of 124 852 individuals, we developed a PCOS risk prediction algorithm by combining polygenic risk scores (PRS) with PCOS component phenotypes into a polygenic and phenotypic risk score (PPRS). We evaluated its predictive capability across different ancestries and perform a PRS-based phenome-wide association study (PheWAS) to assess the phenomic expression of the heightened risk of PCOS. The integrated polygenic prediction improved the average performance (pseudo-R2) for PCOS detection by 0.228 (61.5-fold), 0.224 (58.8-fold), 0.211 (57.0-fold) over the null model across European, African, and multi-ancestry participants respectively. The subsequent PRS-powered PheWAS identified a high level of shared biology between PCOS and a range of metabolic and endocrine outcomes, especially with obesity and diabetes: "morbid obesity", "type 2 diabetes", "hypercholesterolemia", "disorders of lipid metabolism", "hypertension", and "sleep apnea" reaching phenome-wide significance. Our study has expanded the methodological utility of PRS in patient stratification and risk prediction, especially in a multifactorial condition like PCOS, across different genetic origins. By utilizing the individual genome-phenome data available from the EHR, our approach also demonstrates that polygenic prediction by PRS can provide valuable opportunities to discover the pleiotropic phenomic network associated with PCOS pathogenesis.

Joo YY ，Actkins K ，Pacheco JA ，Basile AO ，Carroll R ，Crosslin DR ，Day F ，Denny JC ，Velez Edwards DR ，Hakonarson H ，Harley JB ，Hebbring SJ ，Ho K ，Jarvik GP ，Jones M ，Karaderi T ，Mentch FD ，Meun C ，Namjou B ，Pendergrass S ，Ritchie MD ，Stanaway IB ，Urbanek M ，Walunas TL ，Smith M ，Chisholm RL ，Kho AN ，Davis L ，Hayes MG ，International PCOS Consortium ... -  《-》

Sex modifies the effect of genetic risk scores for polycystic ovary syndrome on metabolic phenotypes.

Females with polycystic ovary syndrome (PCOS), the most common endocrine disorder in women, have an increased risk of developing cardiometabolic disorders such as insulin resistance, obesity, and type 2 diabetes (T2D). While only diagnosable in females, males with a family history of PCOS can also exhibit a poor cardiometabolic profile. Therefore, we aimed to elucidate the role of sex in the cardiometabolic comorbidities observed in PCOS by conducting bidirectional genetic risk score analyses in both sexes. We first conducted a phenome-wide association study (PheWAS) using PCOS polygenic risk scores (PCOSPRS) to identify potential pleiotropic effects of PCOSPRS across 1,380 medical conditions recorded in the Vanderbilt University Medical Center electronic health record (EHR) database, in females and males. After adjusting for age and genetic ancestry, we found that European (EUR)-ancestry males with higher PCOSPRS were significantly more likely to develop hypertensive diseases than females at the same level of genetic risk. We performed the same analysis in an African (AFR)-ancestry population, but observed no significant associations, likely due to poor trans-ancestry performance of the PRS. Based on observed significant associations in the EUR-ancestry population, we then tested whether the PRS for comorbid conditions (e.g., T2D, body mass index (BMI), hypertension, etc.) also increased the odds of a PCOS diagnosis. Only BMIPRS and T2DPRS were significantly associated with a PCOS diagnosis in EUR-ancestry females. We then further adjusted the T2DPRS for measured BMI and BMIresidual (regressed on the BMIPRS and enriched for the environmental contribution to BMI). Results demonstrated that genetically regulated BMI primarily accounted for the relationship between T2DPRS and PCOS. Overall, our findings show that the genetic architecture of PCOS has distinct sex differences in associations with genetically correlated cardiometabolic traits. It is possible that the cardiometabolic comorbidities observed in PCOS are primarily explained by their shared genetic risk factors, which can be further influenced by biological variables including sex and BMI.

Actkins KV ，Jean-Pierre G ，Aldrich MC ，Velez Edwards DR ，Davis LK ... -  《-》

Clinical and genetic contributions to medical comorbidity in bipolar disorder: a study using electronic health records-linked biobank data.

Bipolar disorder is a chronic and complex polygenic disease with high rates of comorbidity. However, the independent contribution of either diagnosis or genetic risk of bipolar disorder to the medical comorbidity profile of individuals with the disease remains unresolved. Here, we conducted a multi-step phenome-wide association study (PheWAS) of bipolar disorder using phenomes derived from the electronic health records of participants enrolled in the Mayo Clinic Biobank and the Mayo Clinic Bipolar Disorder Biobank. First, we explored the conditions associated with a diagnosis of bipolar disorder by conducting a phenotype-based PheWAS followed by LASSO-penalized regression to account for correlations within the phenome. Then, we explored the conditions associated with bipolar disorder polygenic risk score (BD-PRS) using a PRS-based PheWAS with a sequential exclusion approach to account for the possibility that diagnosis, instead of genetic risk, may drive such associations. 53,386 participants (58.7% women) with a mean age at analysis of 67.8 years (SD = 15.6) were included. A bipolar disorder diagnosis (n = 1479) was associated with higher rates of psychiatric conditions, injuries and poisonings, endocrine/metabolic and neurological conditions, viral hepatitis C, and asthma. BD-PRS was associated with psychiatric comorbidities but, in contrast, had no positive associations with general medical conditions. While our findings warrant confirmation with longitudinal-prospective studies, the limited associations between bipolar disorder genetics and medical conditions suggest that shared environmental effects or environmental consequences of diagnosis may have a greater impact on the general medical comorbidity profile of individuals with bipolar disorder than its genetic risk.

Sanchez-Ruiz JA ，Coombes BJ ，Pazdernik VM ，Melhuish Beaupre LM ，Jenkins GD ，Pendegraft RS ，Batzler A ，Ozerdem A ，McElroy SL ，Gardea-Resendez MA ，Cuellar-Barboza AB ，Prieto ML ，Frye MA ，Biernacka JM ... -  《-》

Prospective associations of adolescent obesity phenotypes with self-reported polycystic ovary syndrome diagnosis in young adulthood.

Are empirically derived adolescent overweight/obesity phenotypes differentially associated with polycystic ovary syndrome (PCOS) in young adulthood? Self-reported PCOS diagnosis risk in young adulthood varied by empirically derived adolescent overweight/obesity phenotypes, with the highest risk observed among those in the 'mothers with obesity' and 'early puberty' phenotypes. Overweight and obesity during puberty are postulated to promote the development of PCOS. Much of the prior literature in this area is cross-sectional and defines weight status based solely on BMI, yet emerging research suggests that not all people with overweight/obesity have the same risk for chronic health conditions, including PCOS. Data came from 4838 female participants in the Growing Up Today Study (GUTS), an ongoing prospective cohort study in the USA that has followed children aged 9-14 into young adulthood (ages 31-37, with 16 waves of data collection between 1996 and 2019). We previously used latent class analysis to empirically derive obesity phenotypes among 2038 female participants aged 14-19 years with overweight/obesity in the sample, as determined by participants' self-reported height and weight status. Indicators in the latent class analysis were participants' maternal weight status, disordered eating behaviors, body image and weight concerns, depressive symptoms and pubertal timing. The derived obesity phenotypes included 'mothers with obesity', 'early puberty', 'high weight concerns', and 'mixed'. Among these participants and female participants without adolescent overweight/obesity, we used logistic regression with generalized estimating equations to examine associations of adolescent obesity phenotypes with self-reported PCOS diagnosis after age 19. Analyses were adjusted for potential confounders. Participants in all four obesity phenotypes were more likely than participants without overweight/obesity to report a PCOS diagnosis ('mothers with obesity' phenotype: odds ratio (OR) = 4.50, 95% CI = 2.61, 7.77; 'early puberty' phenotype: OR = 2.51, 95% CI = 1.59, 3.97; 'high weight concerns' phenotype: OR = 2.01, 95% CI = 1.24, 3.24; 'mixed' phenotype: OR = 1.94, 95% CI = 1.33, 2.82). Individuals in the 'mothers with obesity' phenotype had a significantly greater risk of PCOS diagnosis compared to those in the 'mixed' and 'high weight concerns' phenotypes (P < 0.05). Participants self-reported PCOS diagnosis, which may underestimate new-onset PCOS and limit our ability to establish a temporal order between overweight/obesity and PCOS development. Residual confounding may also explain some of the observed associations in our analysis. Despite the fact that participants were from all regions across the USA, the results may not be generalizable to non-White and socioeconomically diverse populations. Among females, the risk of PCOS in young adulthood varied by distinct adolescent obesity phenotypes. Those in the 'mothers with obesity' and 'early puberty' phenotypes had higher risks of PCOS, which suggests a potential underlying biological component. It may be beneficial to tailor PCOS surveillance according to these high-risk adolescent obesity phenotypes. This project was funded by research grants from the National Institutes of Health (R01 DK127585, U01 HL145386, and U01 CA176726). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The authors have no competing interests to disclose. N/A.

Reich LA ，St Fleur RG ，Gjelsvik A ，Field AE ，Ziobrowski HN ... -  《-》

Polygenic risk scores for cardiometabolic traits demonstrate importance of ancestry for predictive precision medicine.

Kember RL ，Verma SS ，Verma A ，Xiao B ，Lucas A ，Kripke CM ，Judy R ，Chen J ，Damrauer SM ，Rader DJ ，Ritchie MD ... -  《-》