posted on 2024-01-27, 04:40authored byLynette J. Oost, Roderick C. Slieker, Marieke T. Blom, Leen M. ’t Hart, Joost G. J. Hoenderop, Joline W. J. Beulens, Jeroen H. F. de Baaij
Additional file 1: Supplementary Figure S1. Q-Q plots showing the distribution of observed versus expected −log10(pvalues) for Mg2+ in (A) base model - corrected for age, sex and PC1-3 - genomic inflation factor 1.003277, (B) model 1- corrected for age, sex, eGFR, PC1-3 - genomic inflation factor 1.003411, and (C) model 2 - corrected for age, sex, eGFR, HbA1c, PC1-3 - genomic inflation factor 1.005874, in the Hoorn DCS cohort. Supplementary Figure S2. Genome-wide –log10(p-value) plots from association analyses with serum Mg2+ concentration in 3,466 people with type 2 diabetes in the Hoorn, DCS study. (A) Adjusted for age, sex, PC 1-3 and eGFR and (B) Adjusted for age, sex, PC 1-3, eGFR and HbA1c. Genome-wide significance (P<5×10−8) is indicated by the red horizontal line. The blue line presents significance p<10−6. DCS=Diabtetes Care Ssytem, eGFR=estimated glomerular filtration rate, HbAtc=hemoglobin Atc, PC=principal component. Supplementary Table S1. Adjusted models of associations between serum Mg2+ concentrations and the lead regional genome-wide significant SNPs. Supplementary Table S2. Loci that display similar effect sizes and an identical direction of the effect on serum Mg2+ levels in people with type 2 diabetes (DCS cohort) and in a previous study focused on the general population. Supplementary Table S3. Loci associated with genetic variability according to GTEx consortium in skeletal muscle tissue. Supplementary Table S4. Loci associated with genetic variability according to human kidney meQTL and eQTM association analyses. Supplementary Table S5. Traits associated with genetic variability according to the Open GWAS database