Improved understanding of the pathophysiology causing diabetic kidney disease (DKD) is imperative. The aim of this study was to uncover associations between serum metabolites and renal outcomes. Non-targeted serum metabolomics analyses were performed in samples from 637 persons with type 1 diabetes using two-dimensional gas chromatography coupled to time-of-flight mass-spectrometry. Longitudinal data at follow-up (median 5.5 years) on renal events were obtained from national Danish health registries. A composite renal endpoint ( = 123) consisted of estimated glomerular filtration rate (eGFR) decline from baseline (≥30%), progression to end-stage renal disease and all-cause mortality. Metabolites with significant associations ( < 0.05) in any of the cross-sectional analyses with eGFR and albuminuria were analyzed for specific and composite endpoints. Adjustments included traditional cardiovascular risk factors and correction for multiple testing. A data-driven partial correlation analysis revealed a dense fabric of co-regulated metabolites and clinical variables dominated by eGFR. Ribonic acid and myo-inositol were inversely associated with eGFR, positively associated with macroalbuminuria ( < 0.02) and longitudinally associated with higher risk of eGFR decline ≥30% (HR 2.2-2.7, CI [1.3-4.3], < 0.001). Ribonic acid was associated with a combined renal endpoint (HR 1.8, CI [1.3-2.3], = 0.001). The hydroxy butyrate 3,4-dihydroxybutanoic acid was cross-sectionally associated with micro- and macroalbuminuria, urinary albumin excretion rate and inversely associated with eGFR ( < 0.04) while branched chain amino acids were associated with eGFR and lower risk of the combined renal endpoint ( < 0.02). Alterations in serum metabolites, particularly polyols and amino acids, were associated with renal endpoints in type 1 diabetes highlighting molecular pathways associated with progression of kidney disease. External validation is needed to further assess their roles and potentials as future therapeutic targets.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6883958PMC
http://dx.doi.org/10.3389/fendo.2019.00818DOI Listing

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