Birthweight, Childhood Body Mass Index, Height and Growth, and Risk of Polycystic Ovary Syndrome

Fetal genome predicted birth weight and polycystic ovary syndrome in later life: a Mendelian randomization study

Associations between lower birth weight and higher polycystic ovary syndrome (PCOS) risk have been reported in previous observational studies, however, the causal relationship is still unknown. Based on decomposed fetal and maternal genetic effects on birth weight (n  =  406,063), we conducted a two-sample Mendelian randomization (MR) analysis to assess potential causal relationships between fetal genome predicted birth weight and PCOS risk using a large-scale genome-wide association study (GWAS) including 4,138 PCOS cases and 20,129 controls. To further eliminate the maternally transmitted or non-transmitted effects on fetal growth, we performed a secondary MR analysis by utilizing genetic instruments after excluding maternally transmitted or non-transmitted variants, which were identified in another birth weight GWAS (n = 63,365 parent-offspring trios from Icelandic birth register). Linkage disequilibrium score regression (LDSR) analysis was conducted to estimate the genetic correlation. We found little evidence to support a causal effect of fetal genome determined birth weight on the risk of developing PCOS (primary MR analysis, OR: 0.86, 95% CI: 0.52 to 1.43; secondary MR analysis, OR: 0.86, 95% CI: 0.54 to 1.39). In addition, a marginally significant genetic correlation (rg = -0.14, se = 0.07) between birth weight and PCOS was revealed via LDSR analysis. Our findings indicated that observed associations between birth weight and future PCOS risk are more likely to be attributable to genetic pleiotropy driven by the fetal genome rather than a causal mechanism.

Association Between Self-Reported Polycystic Ovary Syndrome with Chronic Diseases Among Emiratis: A Cross-Sectional Analysis from the UAE Healthy Future Study

Purpose

This study aimed to assess the prevalence of self-reported polycystic ovary syndrome (PCOS) among Emiratis and examine bi-directional associations of PCOS with self-reported chronic diseases, namely: diabetes, asthma, high cholesterol, and high blood pressure.

Patients and Methods

A cross-sectional analysis was performed using the UAE Healthy Future Study (UAEHFS) data collected from February 2016 to April 2022 involving 1040 Emirati women aged 25-67 years from recruitment centers in the United Arab Emirates (UAE). The bi-directional associations between self-reported PCOS and self-reported chronic diseases were evaluated by establishing temporality based on reported age-at-diagnoses. Firstly, the associations between PCOS (diagnosed at ≥25 years) and chronic diseases (diagnosed at <25 years) were examined, followed by PCOS (diagnosed at <25 years) and chronic diseases (diagnosed at ≥25 years). Finally, a Poisson regression under unadjusted and age-and-body mass index (BMI) adjusted models was performed to obtain the risk ratio (RR) and its 95% confidence interval (CI).

Results

The prevalence of PCOS in this study was 25.9%. Those with asthma and high cholesterol diagnosed at <25 years had increased risks of PCOS diagnosed at ≥25 years (RR = 1.79, 95% CI: 1.17-2.76 for asthma; and RR = 1.61, 95% CI: 1.01-2.59 for high cholesterol), compared to those respective healthier counterparts, after adjusting for age and BMI. No significant association was observed between PCOS diagnosed at <25 years and respective chronic diseases diagnosed at ≥25 years.

Conclusion

PCOS prevalence among Emirati women was high. Asthma and high cholesterol in earlier life were associated with PCOS in later life. Understanding how chronic disease conditions and PCOS are associated in bi-directional ways may improve the surveillance of chronic disease conditions among women with PCOS and may also contribute to more targeted PCOS prevention strategies.

Genomic correlation, shared loci, and causal relationship between obesity and polycystic ovary syndrome: a large-scale genome-wide cross-trait analysis

BACKGROUND

The comorbidity between polycystic ovary syndrome (PCOS) and obesity has long been observed in clinical settings, but their shared genetic basis remains unclear.

METHODS

Leveraging summary statistics of large-scale GWAS(s) conducted in European-ancestry populations on body mass index (adult BMI, Nfemale=434,794; childhood BMI, N=39,620), waist-to-hip ratio (WHR, Nfemale=381,152), WHR adjusted for BMI (WHRadjBMI, Nfemale=379,501), and PCOS (Ncase=10,074, Ncontrol=103,164), we performed a large-scale genome-wide cross-trait analysis to quantify overall and local genetic correlation, to identify shared loci, and to infer causal relationship.

RESULTS

We found positive genetic correlations between PCOS and adult BMI (rg=0.47, P=2.19×10-16), childhood BMI (rg=0.31, P=6.72×10-5), and WHR (rg=0.32, P=1.34×10-10), all withstanding Bonferroni correction. A suggestive significant genetic correlation was found between PCOS and WHRadjBMI (rg=0.09, P=0.04). Partitioning the whole genome into 1703 nearly independent regions, we observed a significant local genetic correlation for adult BMI and PCOS at chromosome 18: 57630483-59020751. We identified 16 shared loci underlying PCOS and obesity-related traits via cross-trait meta-analysis including 9 loci shared between BMI and PCOS (adult BMI and PCOS: 5 loci; childhood BMI and PCOS: 4 loci), 6 loci shared between WHR and PCOS, and 5 loci shared between WHRadjBMI and PCOS. Mendelian randomization (MR) supported the causal roles of both adult BMI (OR=2.92, 95% CI=2.33-3.67) and childhood BMI (OR=2.76, 95% CI=2.09-3.66) in PCOS, but not WHR (OR=1.19, 95% CI=0.93-1.52) or WHRadjBMI (OR=1.03, 95% CI=0.87-1.22). Genetic predisposition to PCOS did not seem to influence the risk of obesity-related traits.

CONCLUSIONS

Our cross-trait analysis suggests a shared genetic basis underlying obesity and PCOS and provides novel insights into the biological mechanisms underlying these complex traits. Our work informs public health intervention by confirming the important role of weight management in PCOS prevention.