Circulating metabolites improve the prediction of renal impairment in patients with type 2 diabetes

Introduction Low glomerular filtration rate (GFR) is a leading cause of reduced lifespan in type 2 diabetes. Unravelling biomarkers capable to identify high-risk patients can help tackle this burden. We investigated the association between 188 serum metabolites and kidney function in type 2 diabetes and then whether the associated metabolites improve two established clinical models for predicting GFR decline in these patients. Research design and methods Two cohorts comprising 849 individuals with type 2 diabetes (discovery and validation samples) and a follow-up study of 575 patients with estimated GFR (eGFR) decline were analyzed. Results Ten metabolites were independently associated with low eGFR in the discovery sample, with nine of them being confirmed also in the validation sample (ORs range 1.3-2.4 per 1SD, p values range 1.9x10(-2)-2.5x10(-9)). Of these, five metabolites were also associated with eGFR decline (ie, tiglylcarnitine, decadienylcarnitine, total dimethylarginine, decenoylcarnitine and kynurenine) (beta range -0.11 to -0.19, p values range 4.8x10(-2) to 3.0x10(-3)). Indeed, tiglylcarnitine and kynurenine, which captured all the information of the other three markers, improved discrimination and reclassification (all p<0.01) of two clinical prediction models of GFR decline in people with diabetes. Conclusions Further studies are needed to validate our findings in larger cohorts of different clinical, environmental and genetic background.

Automated summary

This study investigated the association between 188 serum metabolites and kidney function in type 2 diabetes. Ten metabolites were found to be independently associated with low estimated glomerular filtration rate (eGFR), and five metabolites were associated with eGFR decline. Two of these metabolites improved clinical prediction models for GFR decline in individuals with diabetes.