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

ABSTRACT: 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.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.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.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.

SUBMITTER: de Pedro-Cuesta J

PROVIDER: S-EPMC4927850 | biostudies-other | 2016

REPOSITORIES: biostudies-other

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

de Pedro-Cuesta Jesús J Martínez-Martín Pablo P Rábano Alberto A Alcalde-Cabero Enrique E José García López Fernando F Almazán-Isla Javier J Ruiz-Tovar María M Medrano Maria-José MJ Avellanal Fuencisla F Calero Olga O Calero Miguel M

Journal of Alzheimer's disease : JAD 20160101 4

<h4>Background</h4>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.<h4>Objectives and methods</h4>Redefining drivers as "neither protein/gene- nor entity-specific features identifiable in the clinical and general epidemiology of conformational NDDs (CNDDs) as potential f ...[more]

PMID: 26923014

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Project description:BackgroundThe purpose of this study was to identify incidence and survival patterns in conformational neurodegenerative disorders (CNDDs).MethodsWe identified 2563 reports on the incidence of eight conditions representing sporadic, acquired and genetic, protein-associated, i.e., conformational, NDD groups and age-related macular degeneration (AMD). We selected 245 papers for full-text examination and application of quality criteria. Additionally, data-collection was completed with detailed information from British, Swedish, and Spanish registries on Creutzfeldt-Jakob disease (CJD) forms, amyotrophic lateral sclerosis (ALS), and sporadic rapidly progressing neurodegenerative dementia (sRPNDd). For each condition, age-specific incidence curves, age-adjusted figures, and reported or calculated median survival were plotted and examined.FindingsBased on 51 valid reported and seven new incidence data sets, nine out of eleven conditions shared specific features. Age-adjusted incidence per million person-years increased from ≤1.5 for sRPNDd, different CJD forms and Huntington's disease (HD), to 1589 and 2589 for AMD and Alzheimer's disease (AD) respectively. Age-specific profiles varied from (a) symmetrical, inverted V-shaped curves for low incidences to (b) those increasing with age for late-life sporadic CNDDs and for sRPNDd, with (c) a suggested, intermediate, non-symmetrical inverted V-shape for fronto-temporal dementia and Parkinson's disease. Frequently, peak age-specific incidences from 20-24 to ≥90 years increased with age at onset and survival. Distinct patterns were seen: for HD, with a low incidence, levelling off at middle age, and long median survival, 20 years; and for sRPNDd which displayed the lowest incidence, increasing with age, and a short median disease duration.InterpretationThese results call for a unified population view of NDDs, with an age-at-onset-related pattern for acquired and sporadic CNDDs. The pattern linking age at onset to incidence magnitude and survival might be explained by differential pathophysiological mechanisms associated with specific misfolded protein deposits.

Dataset Information

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

Publications

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

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