👤 Peter I Benke

This study aims to explore the association between plasma metabolites and chronic kidney disease progression in individuals with type 2 diabetes. We performed a comprehensive metabolomic analysis in a prospective cohort study of 5144 multi-ancestral individuals with type 2 diabetes in Singapore, using eGFR slope as the primary outcome of kidney function decline. In addition, we performed genome-wide association studies on metabolites to assess how these metabolites could be genetically influenced by metabolite quantitative trait loci and performed colocalisation analysis to identify genes affecting both metabolites and kidney function. Elevated levels of 61 lipids with long unsaturated fatty acid chains such as phosphatidylethanolamines, triacylglycerols, diacylglycerols, ceramides and deoxysphingolipids were prospectively associated with more rapid kidney function decline. In addition, elevated levels of seven amino acids and three lipids in the plasma were associated with a slower decline in eGFR. We also identified 15 metabolite quantitative trait loci associated with these metabolites, within which variants near TM6SF2, APOE and CPS1 could affect both metabolite levels and kidney functions. Our study identified plasma metabolites associated with prospective renal function decline, offering insights into the underlying mechanism by which the metabolite abnormalities due to fatty acid oversupply might reflect impaired β-oxidation and associate with future chronic kidney disease progression in individuals with diabetes. Show less

Long QT Syndrome, Marfan Syndrome, hypertrophic and dilated cardiomyopathy are caused by mutations in large, multi-exon genes that are principally expressed in cardiovascular tissues. Genetic testing for these disorders is labor-intensive and expensive. We sought to develop a more rapid, comprehensive, and cost-effective approach. Paired whole blood samples were collected into tubes with or without an RNA-preserving solution, and harvested for whole blood RNA or leukocyte DNA, respectively. Large overlapping cDNA fragments from KCNQ1 and KCNH2 (Long QT Syndrome), MYBPC3 (hypertrophic and dilated cardiomyopathy), or FBN1 (Marfan Syndrome) were amplified from RNA and directly sequenced. Variants were confirmed in leukocyte DNA. All 4 transcripts were amplified and sequenced from whole blood mRNA. Six known and 2 novel mutations were first identified from RNA of 10 probands, and later confirmed in genomic DNA, at considerable savings in time and cost. In one patient with MFS, RNA sequencing directly identified a splicing mutation. Results from RNA and DNA were concordant for single nucleotide polymorphisms at the same loci. Taking advantage of new whole blood RNA stabilization methods, we have designed a cost-effective, comprehensive method for mutation detection that should significantly facilitate clinical genetic testing in four lethal cardiovascular disorders. Show less