{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T16:35:14Z","timestamp":1777394114053,"version":"3.51.4"},"reference-count":176,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2016,2,25]],"date-time":"2016-02-25T00:00:00Z","timestamp":1456358400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Alzheimer\u2019s Disease"],"published-print":{"date-parts":[[2016,4,12]]},"abstract":"<jats:sec specific-use=\"heading-level-1\">\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>\n                      Sutherland et al. (2011) suggested that, instead of risk factors for single neurodegenerative disorders (NDDs), there was a need to identify specific \u201cdrivers\u201d, i.e., risk factors with impact on specific deposits, such as amyloid-\u03b2, tau, or\n                      <jats:italic>\u03b1<\/jats:italic>\n                      -synuclein, acting across entities.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec specific-use=\"heading-level-1\">\n                    <jats:title>Objectives and Methods:<\/jats:title>\n                    <jats:p>Redefining drivers as \u201cneither 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\u201d, we conducted an analysis of the epidemiology of ten CNDDs, searching for patterns.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec specific-use=\"heading-level-1\">\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>\n                      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\n                      <jats:italic>Bordetella pertussis<\/jats:italic>\n                      infection for Parkinson\u2019s disease; 6) reticulo-endothelial system stressors or general drivers (andropause or premenopausal estrogen deficiency,\n                      <jats:italic>APOE<\/jats:italic>\n                      <jats:italic>\u025b<\/jats:italic>\n                      4, and vascular risk factors) for late-life CNDDs such as dementia\/Alzheimer\u2019s 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.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec specific-use=\"heading-level-1\">\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>\n                      There might be a systematic epidemiologic pattern induced by specific proteins (PrP, TDP-43, SOD1,\n                      <jats:italic>\u03b1<\/jats:italic>\n                      -synuclein, amyloid-\u03b2, tau, Langerhans islet peptide, and transthyretin) or established combinations of these.\n                    <\/jats:p>\n        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