Drivers: A Biologically Contextualized, Cross-Inferential View of the Epidemiology of Neurodegenerative Disorders

BACKGROUND Sutherland et al. (2011) suggested that, instead of risk factors for single neurodegenerative disorders (NDDs), there was a need to identify specific "drivers", i.e., risk factors with impact on specific deposits, such as amyloid-β, tau, or α-synuclein, acting across entities. OBJECTIVES AND METHODS Redefining drivers as "neither protein/gene- nor entity-specific features identifiable in the clinical and general epidemiology of conformational NDDs (CNDDs) as potential footprints of templating/spread/transfer mechanisms", we conducted an analysis of the epidemiology of ten CNDDs, searching for patterns. RESULTS We identified seven potential drivers, each of which was shared by at least two CNDDs: 1) an age-at-exposure-related susceptibility to Creutzfeldt-Jakob disease (CJD) and several late-life CNDDs; 2) a relationship between age at onset, survival, and incidence; 3) shared genetic risk factors for CJD and late-life CNNDs; 4) partly shared personal (diagnostic, educational, behavioral, and social risk factors) predating clinical onset of late-life CNDDs; 5) two environmental risk factors, namely, surgery for sporadic CJD and amyotrophic lateral sclerosis, and Bordetella pertussis infection for Parkinson's disease; 6) reticulo-endothelial system stressors or general drivers (andropause or premenopausal estrogen deficiency, APOEɛ4, and vascular risk factors) for late-life CNDDs such as dementia/Alzheimer's disease, type-2 diabetes mellitus, and some sporadic cardiac and vascular degenerative diseases; and 7) a high, invariant incidence ratio of sporadic to genetic forms of mid- and late-life CNDDs, and type-2 diabetes mellitus. CONCLUSION There might be a systematic epidemiologic pattern induced by specific proteins (PrP, TDP-43, SOD1, α-synuclein, amyloid-β, tau, Langerhans islet peptide, and transthyretin) or established combinations of these.