The Effect of BMI and Type 2 Diabetes on Socioeconomic Status: A Two-Sample Multivariable Mendelian Randomization Study

Data

For the associations between SNPs and socioeconomic outcomes, we used publicly available summary-level data from a GWAS of UK Biobank data (12,13), including 464,708 individuals of European ancestry. Our outcomes were household income, defined as the average total household income before tax, and regional deprivation, defined using the Townsend deprivation index (14) (Supplementary Material 1). Regarding the exposures, we used summary-level data on the associations between SNPs and BMI or T2D from published meta-analyses of GWAS (10,11), excluding UK Biobank participants, because independency of data of the SNP-exposure and SNP-outcome association is a key prerequisite (先决条件) for the validity of the two-sample MR approach (9) (Supplementary Materials 1 and 2).

Statistical Analysis

First, we performed a univariable MR analysis, testing the single effects of BMI and diabetes on the outcomes (8). Second, we estimated two-sample multivariable MR analysis of the effects of BMI and diabetes on the outcomes, using the set of overlapping SNPs as instruments (10,11). We estimated the effects using the inverse-variance weighted (IVW)method (9). Furthermore, we tested their robustness (稳健性) against other estimation methods, including median-based (基于中值的方法), MR Egger, and MR-robust adjusted profile score (RAPS) methods (Supplementary Materials 1 and 3). Moreover, we tested the sensitivity of the results by excluding other potentially pleiotropic SNPs (Supplementary Material 4). In both the univariable and the multivariable analyses, we tested the effects of two exposures on two outcomes. We therefore assumed a conservative Bonferroni-corrected P value for statistical significance of 0.05/4 5 0.0125.

See you tomorrow