Summary characteristics for each GWAS used to derive external weights in polygenic scores.

Summary characteristics for each GWAS used to derive external weights in polygenic scores.</p

Study exclusion criteria.

*CVD = stroke, atrial fibrillation, coronary heart disease or risk factor type 2 diabetes. **Participants can be missing more than one variable, so the total excluded is less than the sum of the missing data of all traits.</p

Additional file 2 of The relationships between women’s reproductive factors: a Mendelian randomisation analysis

Additional file 2: Table S1 Relationships where bi-directional MR was performed due to unclear temporal ordering. Table S2 Relationships investigated. Table S3 Replication consortia and studies. Table S4 Genetic correlation results. Table S5 Primary analysis (IVW). Table S6 Negative control results. Table S7 Heterogeneity for primary analysis. Table S8 Additional MR methods in relation to primary analysis. Table S9 Egger intercept test for the primary analysis. Table S10 I-squared statistics. Table S11 MR PRESSO Global test for primary analysis. Table S12 MR PRESSO Outlier correction for primary analysis. Table S13 Steiger results for the primary analysis. Table S14 Steiger: SNPs found to be in the incorrect intended for the primary analysis direction. Table S15 Steiger filtered MR results for the primary analysis. Table S16 Split sample SNPs, R2, F stats and number of overlapping SNPs. Table S17 Split sample GWAS overlapping SNPs between samples. Table S18 IVW UKBB split sample results. Table S19 UKBB meta-analysed split sample results. Table S20 Replication SNPs, R2 and F stats. Table S21 IVW UKBB and replication results. Table S22 MRlap number of SNPs. Table S23 MRlap observed and corrected results. Table S24 MVMR findings adjusted for childhood body size (UK Biobank)

Descriptive statistics of study sample, stratified by sex.

Descriptive statistics of study sample, stratified by sex.</p

Additional file 1 of The relationships between women’s reproductive factors: a Mendelian randomisation analysis

Additional file 1: Figure S1. Forest plots showing effect estimates of additional MR methods for relationships identified in the primary MR analysis. Panels A-P refer to the relationships assessed using MR, and MR methods used is shown on the y axis

S1 File -

Cardiovascular disease (CVD) is influenced by genetic and environmental factors. Childhood maltreatment is associated with CVD and may modify genetic susceptibility to cardiovascular risk factors. We used genetic and phenotypic data from 100,833 White British UK Biobank participants (57% female; mean age = 55.9 years). We regressed nine cardiovascular risk factors/diseases (alcohol consumption, body mass index [BMI], low-density lipoprotein cholesterol, lifetime smoking behaviour, systolic blood pressure, atrial fibrillation, coronary heart disease, type 2 diabetes, and stroke) on their respective polygenic scores (PGS) and self-reported exposure to childhood maltreatment. Effect modification was tested on the additive and multiplicative scales by including a product term (PGS*maltreatment) in regression models. On the additive scale, childhood maltreatment accentuated the effect of genetic susceptibility to higher BMI (Peffect modification: 0.003). Individuals not exposed to childhood maltreatment had an increase in BMI of 0.12 SD (95% CI: 0.11, 0.13) per SD increase in BMI PGS, compared to 0.17 SD (95% CI: 0.14, 0.19) in those exposed to all types of childhood maltreatment. On the multiplicative scale, similar results were obtained for BMI though these did not withstand to Bonferroni correction. There was little evidence of effect modification by childhood maltreatment in relation to other outcomes, or of sex-specific effect modification. Our study suggests the effects of genetic susceptibility to a higher BMI may be moderately accentuated in individuals exposed to childhood maltreatment. However, gene*environment interactions are likely not a major contributor to the excess CVD burden experienced by childhood maltreatment victims.</div

Additional file 2 of Establishing the relationships between adiposity and reproductive factors: a multivariable Mendelian randomization analysis

Additional file 2: Table S1. Relationships explored in the univariable analysis. Table S2. Relationships explored in the multivariable analysis with adjustments. Table S3. Replication consortia and information. Table S4. Multivariable mendelian randomization instrument strength and SNP overlap. Table S5. Univariable mendelian randomization findings – IVW method. Table S6. Multivariable mendelian randomization findings - IVW method. Table S7. Steiger filtering. Table S8. Univariable mendelian randomization analyses – heterogeneity test. Table S9. Univariable mendelian randomization analyses - additional MR methods. Table S10. Univariable mendelian randomization analyses – Egger intercept test. Table S11. Univariable mendelian randomization analyses- MR PRESSO. Table S12. Univariable mendelian randomization analyses- MRlap. Table S13. Multivariable mendelian randomization analyses – heterogeneity test. Table S14. Multivariable mendelian randomization with minimised Q statistic findings. Table S15. Multivariable mendelian randomization analysis of childhood body size on reproductive factors - steiger filtered SNPs removed. Table S16. Replication multivariable mendelian randomization instrument strength. Table S17. Replication univariable mendelian randomization findings - IVW method. Table S18. Replication multivariable mendelian randomization findings - IVW method

Additional file 1 of Establishing the relationships between adiposity and reproductive factors: a multivariable Mendelian randomization analysis

Additional file 1. Further details

STROBE statement—checklist of items that should be included in reports of observational studies.

STROBE statement—checklist of items that should be included in reports of observational studies.</p

Effect modification by exposure to childhood maltreatment on genetic predisposition to cardiovascular risk factors and disease on the additive scale at P<5x10^-8.

Analyses were adjusted for age, sex and 40 genetic principal components. Traits are grouped according to whether they are binary or continuous. BMI = body mass index; LDL-C = low-density lipoprotein cholesterol; SBP = systolic blood pressure; PGS = polygenic score.</p