Affiliations: [a]
Endocrinology Institute, Gertner Institute, Sheba Medical Center, Ramat-Gan, Israel
| [b]
Epidemiology Department, Sackler School of Medicine, Herceg Institute of Aging, Tel Aviv University, Tel Aviv, Israel
| [c]
Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Canada
| [d]
Thrombosis and Atherosclerosis Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
| [e] Sanofi-Aventis Deutschland GmbH, R&D, Translational Medicine & Early Development, Biomarkers & Clinical Bioanalyses, Frankfurt am Main, Germany
Correspondence:
[*]
Correspondence to: Tali Cukierman-Yaffe, MD, MSc, Epidemiology Department, Sackler School of Medicine, Herceg Institute of Aging, Tel Aviv University, 6 Tritsh St, Tel-Aviv, Israel. Tel.: +972523824704; E-mail: [email protected].
Abstract: Background:Diabetes and cardiovascular disease increase the risk of incident cognitive dysfunction. Identification of novel biochemical markers for cognitive dysfunction may identify people at the highest risk while yielding insights regarding the pathophysiology of cognitive dysfunction. Objective:To identify cardiovascular biomarkers in serum that are independent predictors of cognitive dysfunction in individuals with dysglycemia. Methods:This analysis was conducted in 8,365 participants in the Outcome Reduction with an Initial Glargine Intervention (ORIGIN) trial whose stored serum was analyzed for 238 cardio-metabolic biomarkers and completed a baseline Mini-Mental State Examination (MMSE). Fine and Gray sub distribution hazard models accounting for the competing risk of death accounting for clinical risk factors and the baseline MMSE were used to identify biomarkers that predicted incident cognitive dysfunction (MMSE < 24 or dementia) using forward selection with an inclusion p-value < 0.0002 to account for multiplicity. Results:During a median follow-up period of 6.2 years, 939 individuals developed cognitive dysfunction. After accounting for 17 clinical risk factors, glargine allocation, and the baseline MMSE, three biomarkers (α-2 Macroglobulin, HR 1.19; 95% CI 1.12, 1.27; Macrophage Inflammatory Protein 1α, HR 1.11; 95% CI 1.06, 1.16; and Growth Hormone, HR 0.91; 95% CI 0.87, 0.96) independently predicted incident cognitive dysfunction (p < 0.0002). Addition of these biomarkers to a model that included clinical risk factors, however, did not improve the ability to predict cognitive dysfunction. Conclusion:Addition of independent biomarkers to clinical risk factors for cognitive dysfunction in people with dysglycemia did not predict incident cognitive dysfunction better than clinical risk factors alone.
