Plasma biomarkers of cognitive decline and Alzheimer's disease and the role of social determinants of health and lifestyle factors in Nigeria

A. PROJECT SUMMARY The increasing prevalence of dementia in Sub-Saharan Africa is attributed to a number of factors such as population aging, longer life expectancy, and population growth. Beyond this, social determinants of health, including poor economic resources and low education and lifestyle factors, have been shown to exacerbate dementia risk. Despite this burden, early dementia diagnosis in Sub-Saharan Africa suffers systemic challenges such as a lack of specialized professionals, limited awareness, lack of region-specific diagnostic tools and criteria, and funding. Historically, diagnostic approaches are invasive, expensive, and limited, especially in resource-constrained settings. However, blood-based biomarkers present a novel, minimally invasive, and cost-effective option to revolutionize dementia diagnosis in Africa. The overall hypothesis of this proposed research is that social determinants of health (SDH), lifestyle factors, and plasma biomarkers can reliably classify and predict mild cognitive impairment (MCI) and Alzheimer’s disease (AD) in Nigeria, enabling the development of a region-specific early diagnostic tool. This current study proposes a two-year cross-sectional and longitudinal study of 264 Nigerians with different cognitive status: Alzheimer’s disease (AD=88 participants), mild cognitive impairment (MCI=88), and healthy controls (HC=88 participants) aged 50 years and above and living in Urban and rural areas of southwest Nigeria. Participants will be followed up for 12 months after the initial baseline data collection. Cognitive assessment will be conducted with tools such as Montreal Cognitive Assessment (MoCA) and Idea tools. Fasting blood samples will be obtained for plasma biomarkers: amyloid-β (Aβ42/40), phosphorylated tau (p-tau181), and neurofilament light chain (NfL)) using ultra-sensitive immunoassays to correlate with cognitive assessments and diagnoses of mild cognitive impairment (MCI) or AD. Validated questionnaires will be employed to obtain data on social determinants of health and lifestyle factors (physical activity, nutrition, sleep, isolation, smoking status and alcohol consumption). Multivariate analyses (using STATA v18) will explore variable interactions with biomarker expression, while ROC curves and regression models will establish diagnostic cut-off values and evaluate the predictive accuracy of biomarkers for cognitive impairment, accounting for the influence of these SDH and lifestyle factors. The anticipated outcome of the study is the validation of plasma biomarkers as reliable markers and predictors of cognitive decline and AD in a Nigerian population and identifying SDH and lifestyle factors that influence biomarker expression, providing a novel dataset in African contexts.