Biomarkers reflecting insulin resistance increase the risk of aortic stenosis in a population-based study of 10,144 Finnish men

Abstract

Aims: To investigate a comprehensive panel of biomarkers and risk of aortic stenosis (AS) in a prospective population-based study. Methods: Anthropometric, metabolic, and inflammatory biomarkers were measured in the Metabolic Syndrome in the Men Study of 10,144 Finnish men without AS at baseline. Cases of AS were identified from the medical records. Cox regression analysis was used to identify variables predicting AS over a follow-up time of 10.8 years. Principal component (PC) analysis was applied to the biomarkers that predicted AS. Cox regression analysis was used to investigate the resulting PCs as AS predictors. Results: AS was diagnosed in 116 men (1.1%), with a median age of 62 years. In Cox regression analyses, fasting, 30 min, and 120 min plasma insulin, and proinsulin, with hazard ratios (HR) ranging from 1.38 (1.12-1.69, p = 2.1E-3) to 1.44 (1.23-1.68, p = 4.0E-6), Matsuda index [HR 0.68 (0.56-0.82, p = 6.9E-5)], and serum C-peptide [HR 1.47 (1.22-1.77, p = 5.0E-5)] were associated with incident AS, in addition to age, systolic blood pressure, BMI, waist circumference, waist/hip ratio, height, body fat mass, fat-free mass, and hs-CRP, and remained significant after adjustments, or if diabetic subjects were excluded. PC 1, consisting of fasting plasma insulin, C-peptide, Matsuda index, waist/hip ratio, and urine albumin excretion, and PC 2, consisting of age, body fat mass, and systolic blood pressure, were significantly associated with AS [HRs 1.37(1.09-1.73) and 1.77 (1.45-2.17), respectively]. Conclusion: Biomarkers reflecting insulin resistance are risk factors for AS, a novel finding indicating that insulin resistance is important in the pathogenesis of AS.