Raffaella Buzzetti

Chitotriosidase (CHIT), a mammalian chitinase secreted by neutrophils and activated macrophages, is increased in both cardiovascular disease (CVD) and type 2 diabetes (T2D). Arterial stiffness rises early in T2D and increases the risk of CVD. The aim of this study is to evaluate CHIT activity as an early biomarker of arterial stiffness in people with T2D free from overt vascular complications. In this cross-sectional study, arterial stiffness as measured using standard pulse wave velocity (PWV) was evaluated in 174 people with T2D without overt vascular disease. Then, we measured CHIT serum activity with an electrochemiluminescence assay in two subgroups of participants: 35 with the highest (high-PWV) and 40 with the lowest (low-PWV) PWV values. CHIT activity was no different between the low-PVW and high-PWV groups (12.7 [9.6–17.9] vs. 11.4 [8.8–15.0] nmol/mL/h, respectively). Compared with the low-PWV group, the high-PWV participants were older (p < 0.001); had a longer duration of diabetes (p = 0.03); higher ankle–brachial index ABI (p = 0.04), systolic blood pressure (p = 0.002), diastolic blood pressure (p = 0.005), fasting blood glucose (p = 0.008), and HbA1c (p = 0.005); and lower eGFR (p = 0.03) and body mass index (BMI) (p = 0.01). No association was present with sex, duration of diabetes, age, BMI, peripheral blood pressure, laboratory parameters, and glucose-lowering medications or ongoing antihypertensive therapy. Although no association was found, this study provides novel data about the association of CHIT activity with CVD, focusing on a specific outcome (arterial stiffness) in a well-defined population of subjects with T2D without established CVD.

Context Mortality in type 2 diabetes is twice that of the normoglycemic population. Unravelling biomarkers that identify high‐risk patients for referral to the most aggressive and costly prevention strategies is needed. Objective To validate in type 2 diabetes the association with all‐cause mortality of a 14‐metabolite score (14‐MS) previously reported in the general population and whether this score can be used to improve well‐established mortality prediction models. Methods This is a sub‐study consisting of 600 patients from the “Sapienza University Mortality and Morbidity Event Rate” (SUMMER) study in diabetes, a prospective multicentre investigation on all‐cause mortality in patients with type 2 diabetes. Metabolic biomarkers were quantified from serum samples using high‐throughput proton nuclear magnetic resonance metabolomics. Results In type 2 diabetes, the 14–MS showed a significant ( p < 0.0001) association with mortality, which was lower ( p < 0.0001) than that reported in the general population. This difference was mainly due to two metabolites (histidine and ratio of polyunsaturated fatty acids to total fatty acids) with an effect size that was significantly ( p = 0.01) lower in diabetes than in the general population. A parsimonious 12‐MS (i.e. lacking the 2 metabolites mentioned above) improved patient discrimination and classification of two well‐established mortality prediction models ( p < 0.0001 for all measures). Conclusions The metabolomic signature of mortality in the general population is only partially effective in type 2 diabetes. Prediction markers developed and validated in the general population must be revalidated if they are to be used in patients with diabetes.