Acute myeloid leukemia (AML) is a complex hematologic malignancy with multiple disease subgroups defined by somatic mutations and heterogeneous outcomes. Although genome-wide association studies (GWAS Show more
Acute myeloid leukemia (AML) is a complex hematologic malignancy with multiple disease subgroups defined by somatic mutations and heterogeneous outcomes. Although genome-wide association studies (GWAS) have identified a small number of common genetic variants influencing AML risk, the heritable component of this disease outside of familial susceptibility remains largely undefined. Here, we perform a meta-analysis of 4 published GWAS plus 2 new GWAS, totaling 4710 AML cases and 12 938 controls. We identify a new genome-wide significant risk locus for pan-AML at 2p23.3 (rs4665765; P = 1.35 × 10-8; EFR3B, POMC, DNMT3A, and DNAJC27), which also significantly associates with patient survival (P = 6.09 × 10-3). Our analysis also identifies 3 new genome-wide significant risk loci for disease subgroups, including AML with deletions of chromosome 5 and/or 7 at 1q23.3 (rs12078864; P = 7.0 × 10-10; DUSP23) and cytogenetically complex AML at 2q33.3 (rs12988876; P = 3.28 × 10-8; PARD3B) and 2p21 (rs79918355; P = 1.60 × 10-9; EPCAM). We also investigated loci previously associated with the risk of clonal hematopoiesis (CH) or CH of indeterminate potential and identified several variants associated with the risk of AML. Our results further inform on AML etiology and demonstrate the existence of disease subgroup specific risk loci. Show less
Metformin is used as a first-line oral treatment for type 2 diabetes (T2D). However, the underlying mechanism is not fully understood. Here, we aimed to comprehensively investigate the pleiotropic eff Show more
Metformin is used as a first-line oral treatment for type 2 diabetes (T2D). However, the underlying mechanism is not fully understood. Here, we aimed to comprehensively investigate the pleiotropic effects of metformin. We analyzed both metabolomic and genomic data of the population-based KORA cohort. To evaluate the effect of metformin treatment on metabolite concentrations, we quantified 131 metabolites in fasting serum samples and used multivariable linear regression models in three independent cross-sectional studies (n = 151 patients with T2D treated with metformin [mt-T2D]). Additionally, we used linear mixed-effect models to study the longitudinal KORA samples (n = 912) and performed mediation analyses to investigate the effects of metformin intake on blood lipid profiles. We combined genotyping data with the identified metformin-associated metabolites in KORA individuals (n = 1,809) and explored the underlying pathways. We found significantly lower (P < 5.0E-06) concentrations of three metabolites (acyl-alkyl phosphatidylcholines [PCs]) when comparing mt-T2D with four control groups who were not using glucose-lowering oral medication. These findings were controlled for conventional risk factors of T2D and replicated in two independent studies. Furthermore, we observed that the levels of these metabolites decreased significantly in patients after they started metformin treatment during 7 years' follow-up. The reduction of these metabolites was also associated with a lowered blood level of LDL cholesterol (LDL-C). Variations of these three metabolites were significantly associated with 17 genes (including FADS1 and FADS2) and controlled by AMPK, a metformin target. Our results indicate that metformin intake activates AMPK and consequently suppresses FADS, which leads to reduced levels of the three acyl-alkyl PCs and LDL-C. Our findings suggest potential beneficial effects of metformin in the prevention of cardiovascular disease. Show less