3011 Pathophysiological link between renal and cardiovascular disease in patients with type 2 diabetes mellitus: preliminary results from a proteomic study

Abstract Background and Aims Diabetic kidney disease (DKD) affects nearly 40% of people with diabetes and is the leading cause of chronic kidney disease (CKD). A high prevalence of cardiovascular disease (CVD) is known in this population. Indeed, DKD and CVD are often related and lead to worse outcomes in type 2 diabetes mellitus (T2D), i.e. cardiac fibrosis and CV events are frequently described in patients with DKD. However, specific associations and accurate prediction biomarkers for DKD and CVD progression in T2D are still lacking as various proteins may play a multi-mechanistic role. Lipocalin-2 (LCN2) is involved in several pathophysiological processes (inflammation, renal disease and cardiometabolic complications in CKD). Its leukocyte-chemoattractant effect has shown to reduce CVD in experimental models of cardiomyopathy when suppressed. Excess LCN2 in CKD is a determinant of disease progression, but also a potent mediator of cardiac injury in CKD. Insulin-like growth factor binding proteins (IGFBPs) also play an important role in cell homeostasis by regulating cell transcription, migration, and apoptosis. IGFBP-3 down-regulation has demonstrated to be a predictor of rapid renal progression in T2DM. On the other hand, IGFBP-6 increases when GFR drops, being involved in the pathophysiological process of CKD as an apoptosis-inducing protein In this context, a proteomic-based approach would optimise the clinical utility of multiple plasma biomarkers. The aim was to identify proteins associated with DKD, cardiac fibrosis (estimated by the PICP biomarker) and the presence of a new CV event. Method A prospective cohort of 91 T2D patients, with a minimum follow-up of 3 years (mean: 4 years) was analysed. We evaluated the association between rates of change in GFR and PICP during follow-up (fold-change: end/initial) and their interaction with the development of a composite of cardiovascular (CV) events: CV death, stroke, ischaemic heart disease, atrial fibrillation, valvular heart disease and CV-related hospitalisation. In addition, ninety-two proteins were quantified in serum samples using a multiplex proximity extension assay with high-throughput protein detection technology (Olink proteomics, Cardiometabolic panel). Associations between variations in these proteins and changes in PICP and eGFR (all expressed as fold change from baseline) were assessed using linear regression analyses adjusted for their respective baseline values. All analyses were adjus