Table 1.
Female-only, European ancestry GWASs retrieved from the IEU Open GWAS project to be included as exposures (anthropometric markers) and the outcome (PCOS) in two-sample Mendelian randomization analyses.
Table 2.
Results from two-sample Mendelian randomization analyses on the causality of anthropometric markers associated with polycystic ovarian syndrome.
Fig 1.
Scatter plot illustrating the distribution of individual ratio estimates of weight with polycystic ovarian syndrome as the outcome.
Trend lines from the four different two-sample Mendelian randomization methods employed indicating the positive causal associations, are also included in each scatter plot.
Fig 2.
Scatter plot illustrating the distribution of individual ratio estimates of body mass index with polycystic ovarian syndrome as the outcome.
Trend lines from the four different two-sample Mendelian randomization methods employed indicating the positive causal associations, are also included in each scatter plot.
Fig 3.
Scatter plot illustrating the distribution of individual ratio estimates of waist circumference with polycystic ovarian syndrome as the outcome.
Trend lines from the four different two-sample Mendelian randomization methods employed indicating the positive causal associations, are also included in each scatter plot.
Fig 4.
Scatter plot illustrating the distribution of individual ratio estimates of hip circumference with polycystic ovarian syndrome as the outcome.
Trend lines from the four different two-sample Mendelian randomization methods employed indicating the positive causal associations, are also included in each scatter plot.
Fig 5.
Forest plot of weight, against polycystic ovarian syndrome as the outcome.
Effects of individual SNPs and pooled estimates from MR-Egger- and inverse variance weighted methods are visualized.
Fig 6.
Forest plot of body mass index, against polycystic ovarian syndrome as the outcome.
Effects of individual SNPs and pooled estimates from MR-Egger- and inverse variance weighted methods are visualized.
Fig 7.
Forest plot of waist circumference, against polycystic ovarian syndrome as the outcome.
Effects of individual SNPs and pooled estimates from MR-Egger- and inverse variance weighted methods are visualized.
Fig 8.
Forest plot of hip circumference, against polycystic ovarian syndrome as the outcome. Effects of individual SNPs and pooled estimates from MR-Egger- and inverse variance weighted methods are visualized.
Fig 9.
Leave-one-out sensitivity analysis plot of weight, against polycystic ovarian syndrome as the outcome.
A given dark point indicates the effect measure from inverse variance weighted Mendelian randomization analysis excluding that specific SNP. The red lines indicate pooled analyses encompassing all SNPs via IVW-MR method (drawn for comparison).
Fig 10.
Leave-one-out sensitivity analysis plot of body mass index, against polycystic ovarian syndrome as the outcome.
A given dark point indicates the effect measure from inverse variance weighted Mendelian randomization analysis excluding that specific SNP. The red lines indicate pooled analyses encompassing all SNPs via IVW-MR method (drawn for comparison).
Fig 11.
Leave-one-out sensitivity analysis plot of waist circumference, against polycystic ovarian syndrome as the outcome.
A given dark point indicates the effect measure from inverse variance weighted Mendelian randomization analysis excluding that specific SNP. The red lines indicate pooled analyses encompassing all SNPs via IVW-MR method (drawn for comparison).
Fig 12.
Leave-one-out sensitivity analysis plot of hip circumference, against polycystic ovarian syndrome as the outcome.
A given dark point indicates the effect measure from inverse variance weighted Mendelian randomization analysis excluding that specific SNP. The red lines indicate pooled analyses encompassing all SNPs via IVW-MR method (drawn for comparison).
Fig 13.
Funnel plot of weight as the exposure, against polycystic ovarian syndrome as the outcome.
Fig 14.
Funnel plot of body mass index as the exposure, against polycystic ovarian syndrome as the outcome.
Fig 15.
Funnel plot of waist circumference as the exposure, against polycystic ovarian syndrome as the outcome.
Fig 16.
Funnel plot of hip circumference as the exposure, against polycystic ovarian syndrome as the outcome.
Table 3.
Heterogeneity statistics of two-sample Mendelian randomization analyses.
Fig 17.
Radial plot of weight as the exposure.
No significant outliers were detected.
Fig 18.
Radial plot of body mass index as the exposure.
No significant outliers were detected.
Fig 19.
Radial plot of waist circumference as the exposure.
No significant outliers were detected.
Fig 20.
Radial plot of hip circumference as the exposure.
No significant outliers were detected.
Table 4.
Horizontal pleiotropy statistics of two-sample Mendelian randomization analyses.
Table 5.
Genetic variants (SNPs) and nearest genes/transcriptional start sites (TSSs) underlying the significant causal associations.
Table 6.
Findings from multivariable Mendelian randomization analyses with multiple anthropometric markers as exposures and polycystic ovarian syndrome as the outcome.