1.
Assessing the causal association of glycine with risk of cardio-metabolic diseases.
Wittemans, LBL, Lotta, LA, Oliver-Williams, C, Stewart, ID, Surendran, P, Karthikeyan, S, Day, FR, Koulman, A, Imamura, F, Zeng, L, et al
Nature communications. 2019;(1):1060
Abstract
Circulating levels of glycine have previously been associated with lower incidence of coronary heart disease (CHD) and type 2 diabetes (T2D) but it remains uncertain if glycine plays an aetiological role. We present a meta-analysis of genome-wide association studies for glycine in 80,003 participants and investigate the causality and potential mechanisms of the association between glycine and cardio-metabolic diseases using genetic approaches. We identify 27 genetic loci, of which 22 have not previously been reported for glycine. We show that glycine is genetically associated with lower CHD risk and find that this may be partly driven by blood pressure. Evidence for a genetic association of glycine with T2D is weaker, but we find a strong inverse genetic effect of hyperinsulinaemia on glycine. Our findings strengthen evidence for a protective effect of glycine on CHD and show that the glycine-T2D association may be driven by a glycine-lowering effect of insulin resistance.
2.
Pathway analysis of genome-wide association studies on uric acid concentrations.
Lee, YH, Song, GG
Human immunology. 2012;(8):805-10
Abstract
OBJECTIVE The aims of this study were to identify the candidate causal single nucleotide polymorphisms (SNPs) and candidate causal mechanisms influencing uric acid level and to generate hypotheses for the SNP to gene to pathways that influence uric acid concentrations. METHODS Meta-analysis data of 954 SNPs with genome-wide significance in 14 genome-wide association studies (GWASs) comprising 28,141 individuals of European ancestry was subjected to ICSNPathway (Identify candidate Causal SNPs and Pathways) analysis to establish associations between pathways and uric acid concentrations. RESULTS ICSNPathway analysis identified 14 candidate causal SNPs, five genes, and two candidate causal pathways, which provided two hypothetical biologic mechanisms: (1) rs2728121 (regulatory region) to polycystic kidney disease 2 (PKD2) to ion transmembrane transporter activity; (2) rs942377, rs3799346, rs3799344, rs2762353, rs13197601, rs3757131, rs1165215, rs1165196 to SLC17A1 to ion transmembrane transporter activity and secondary active transmembrane transporter activity. SLC17A1, SLC17A3, SLC17A4, SLC22A11, and SLC2A9 were involved in both pathways, and PKD2 and SLC16A9 in one pathway. CONCLUSION By applying ICSNPathway analysis to GWAS data on uric acid levels, 14 SNPs, five genes, and two pathways involving the PKD2, SLC17A1, SLC17A3, SLC17A4, and SLC2A9 genes were identified that might contribute to the condition in Europeans.