Bidirectional Association between Atrial Fibrillation and Ovarian Cancer: Evidence from the UK Biobank and Mendelian Randomization

Figures

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  Figure 1.. Flowchart of participant selection of the UKB cohort. OCA, ovarian cancer.

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  Figure 2.. Bidirectional associations between AF and ovarian cancer and cumulative risk curves. A, Forest plots illustrating bidirectional associations between AF and ovarian cancer using Cox proportional hazards regression. The associations of ovarian cancer to AF and AF to ovarian cancer were each stratified by the interval between disease onset. P for interaction was statistically significant. All models were adjusted for age, ethnicity, menopause, BMI, body fat mass, use of cholesterol-lowering medication, use of blood pressure–lowering medication, hormone replacement therapy, smoking status, alcohol usage status, history of hypertension, diabetes, heart failure, and myocardial infarction. B, Cumulative risk of ovarian cancer in participants with and without AF. C, Cumulative risk of AF in participants with and without ovarian cancer. Solid lines represent estimated cumulative risk; dashed lines indicate 95% CIs. OCA, ovarian cancer. Bold text denotes statistically significant associations (P < 0.01).

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  Figure 3.. Risk of new-onset AF by ovarian cancer histologic subtype and in subgroups defined by participant characteristics. The figure shows the associations between different histologic subtypes of ovarian cancer (endometrioid, mucinous, and serous) and the risk of developing AF, as estimated by Cox proportional hazards regression models. It also depicts the relationship between ovarian cancer and new-onset AF within various population subgroups, including individuals with hypertension, myocardial infarction, smoking, alcohol use, menopause, and White ethnicity. Values represent numbers or HRs with 95% CIs. Adjusted covariates were the same as in Fig. 2. Bold text denotes statistically significant associations (P < 0.01).

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  Figure 4.. MR analysis of a genetic relationship between AF and ovarian cancers using two different AF-GWAS datasets. This figure demonstrates MR analysis (inverse variance weighted method) of a genetic relationship between AF and ovarian cancers using GWAS datasets (A) ebi-GCST006414 and (B) ebi-GCST006061. *, Result after removing pleiotropic SNPs with the MR-PRESSO method. Values are ORs (95% CIs). Bol text denotes statistically significant associations (P < 0.01).

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  Figure 5.. Prognosis analysis of NUP50 and SYTL2. Kaplan–Meier survival analysis of patients with ovarian cancer based on gene expression levels of (A) SYTL2 and (B) NUP50, as derived from TCGA data. C, RT-qPCR analysis and (D) Western blot of SKOV3 after the knockdown of NUP50 and SYTL2 genes by siRNA. E, CCK-8 assays of SKOV3 transfected with siRNA targeting human NUP50 (si-NUP50) and SYTL2 (si-SYTL2) or control. Representative images are shown. Data are presented as means ± SD. **, P < 0.01; ****, P < 0.0001; n = 5.