Background and Purpose—Intracranial atherosclerotic disease (ICAD) remains a challenge for stroke primary and secondary prevention. Molecular pathways involved in the development of ICAD from its asymptomatic stages are largely unknown. In our population-based study, we aimed to compare the risk factor and biomarker profiles associated with intracranial and extracranial asymptomatic cerebral atherosclerosis. Methods—The Asymptomatic Intracranial Atherosclerosis (AsIA) study cohort includes a random sample population of 933 white subjects >50 years with a moderate to high vascular risk (based on REGICOR score) and without a history of stroke (64% males; mean age, 66 years). Carotid and intracranial atherosclerosis were screened by cervical and transcranial color-coded Duplex ultrasound, being moderate to severe stenoses confirmed by MR angiography. We registered clinical and anthropometric data and created a biobank with blood samples at baseline. A panel of biomarkers involved in atherothrombogenesis was determined: C-reactive protein, asymmetric-dimethylarginine, resistin, and plasminogen activator inhibitor-1. Insulin resistance was quantified by Homeostasis Model Assessment index. Results—After multinomial regression analyses, male sex, hypertension, smoking, and alcoholic habits were independent risk factors of isolated extracranial atherosclerotic disease. Diabetes and metabolic syndrome conferred a higher risk for ICAD than for extracranial atherosclerotic disease. Moreover, metabolic syndrome and insulin resistance were independent risk factors of moderate to severe ICAD but were not risk factors of moderate to severe extracranial atherosclerotic disease. Regarding biomarkers, asymmetric-dimethylarginine was independently associated with isolated ICAD and resistin with combined ICAD–extracranial atherosclerotic disease. Conclusions—Our findings show distinct clinical and biological profiles in subclinical ICAD and extracranial atherosclerotic disease. Insulin resistance emerged as an important molecular pathway involved in the development of ICAD from its asymptomatic stage.

Patients with diabetes mellitus (DM) have an increased risk of developing heart failure (HF). Further, DM is associated with poor prognosis in patients with HF. Our aim was to determine whether DM has any impact on the predictive value of a multi-biomarker panel in patients with HF. We included 1069 consecutive ambulatory HF patients in the study: age 66.2 ± 12.8 years, 33.5 ± 13.3 left ventricular ejection fraction, 36% diabetic patients. We measured serum concentrations of N-terminal pro-brain natriuretic peptide (NT-proBNP), high-sensitivity troponin T (hs-TnT), ST2, galectin-3, high-sensitivity C reactive protein (hs-CRP), cystatin-C, soluble transferrin receptor (sTfR), and neprilysin and followed patients for 4.9 ± 2.8 years. Primary endpoints were all-cause and cardiovascular death. During follow-up, 534 patients died; 283 died of cardiovascular causes. Diabetic subjects had higher mortality (57.7 vs. 45.6%, p < 0.001). NTproBNP (p = 0.07), hs-TnT (p < 0.001), galectin-3 (p < 0.001), and cystatin-C (p = 0.001) concentrations were higher in diabetic patients, whereas sTfR levels were lower (p = 0.005). There were no interactions between DM and NTproBNP, hs-TnT, galectin-3, hs-CRP, cystatin-C, sTfR, and neprilysin relative to risk prediction for all-cause or cardiovascular death. By contrast, ST2 significantly interacted with DM for all-cause (p = 0.02) and cardiovascular (p = 0.03) death. In diabetic patients, HRs for ST2 were 1.27 (95% CI 1.16–1.40, p < 0.001) and 1.23 (95% CI 1.09–1.39, p = 0.001) for all-cause and cardiovascular death, respectively. In nondiabetic patients, HRs for ST2 were 1.53 (95% CI 1.35–1.73, p < 0.001) and 1.64 (95% CI 1.31–2.05, p < 0.001) for all-cause and cardiovascular death, respectively. The multivariable Cox regression analysis showed that hs-TnT and ST2 were the only markers that were independently associated with both all-cause and cardiovascular mortality in patients with HF and diabetes. Moreover, in these patients, the combination of these two markers significantly increased discrimination as assessed by the area under the curve. Biomarkers used in the general population to predict the clinical course of heart failure are also useful in patients with diabetes. In these patients, among all the biomarkers analysed only hs-TnT and ST2 were independently associated with both all-cause and cardiovascular mortality.