Addition of inflammation-related biomarkers to the CAIDE model for risk prediction of all-cause dementia, Alzheimer’s disease and vascular dementia in a prospective study

Abstract

Abstract Background It is of interest whether inflammatory biomarkers can improve dementia prediction models, such as the widely used Cardiovascular Risk Factors, Aging and Dementia (CAIDE) model. Methods The Olink Target 96 Inflammation panel was assessed in a nested case-cohort design within a large, population-based German cohort study (n = 9940; age-range: 50–75 years). All study participants who developed dementia over 20 years of follow-up and had complete CAIDE variable data (n = 562, including 173 Alzheimer’s disease (AD) and 199 vascular dementia (VD) cases) as well as n = 1,356 controls were selected for measurements. 69 inflammation-related biomarkers were eligible for use. LASSO logistic regression and bootstrapping were utilized to select relevant biomarkers and determine areas under the curve (AUCs). Results The CAIDE model 2 (including Apolipoprotein E (APOE) ε4 carrier status) predicted all-cause dementia, AD, and VD better than CAIDE model 1 (without APOE ε4) with AUCs of 0.725, 0.752 and 0.707, respectively. Although 20, 7, and 4 inflammation-related biomarkers were selected by LASSO regression to improve CAIDE model 2, the AUCs did not increase markedly. CAIDE models 1 and 2 generally performed better in mid-life (50–64 years) than in late-life (65–75 years) sub-samples of our cohort, but again, inflammation-related biomarkers did not improve their predictive abilities. Conclusions Despite a lack of improvement in dementia risk prediction, the selected inflammation-related biomarkers were significantly associated with dementia outcomes and may serve as a starting point to further elucidate the pathogenesis of dementia.

Keywords

• Inflammation
• Risk prediction
• Cohort study
• Dementia
• Alzheimer’s disease
• Vascular dementia