title: Autonomic Nervous System Dysfunctions as a Basis for a Predictive Model of Risk of Neurological Disorders in Subjects with Prior History of Traumatic Brain Injury: Implications in Alzheimer's Disease.
abstract: Autonomic dysfunction is very common in patients with dementia, and its presence might also help in differential diagnosis among dementia subtypes. Various central nervous system structures affected in Alzheimer's disease (AD) are also implicated in the central autonomic nervous system (ANS) regulation. For example, deficits in central cholinergic function in AD could likely lead to autonomic dysfunction. We recently developed a simple, readily applicable evaluation for monitoring ANS disturbances in response to traumatic brain injury (TBI). This ability to monitor TBI allows for the possible detection and targeted prevention of long-term, detrimental brain responses caused by TBI that lead to neurodegenerative diseases such as AD. We randomly selected and extracted de-identified medical record information from subjects who have been assessed using the ANS evaluation protocol. Using machine learning strategies in the analysis of information from individual as well as a combination of ANS evaluation protocol components, we identified a novel prediction model that is effective in correctly segregating between cases with or without a documented history of TBI exposure. Results from our study support the hypothesis that trauma-induced ANS dysfunctions may contribute to clinical TBI features. Because autonomic dysfunction is very common in AD patients it is possible that TBI may also contribute to AD and/or other forms of dementia through these novel mechanisms. This study provides a novel prediction model to physiologically assess the likelihood of subjects with prior history of TBI to develop clinical TBI complications, such as AD.
authors.affiliation: Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.|Geriatric Research, Education & Clinical Center, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA.
authors.forename: Lap
authors.initials: L
authors.lastname: Ho
authors.affiliation: PATCH Chiropractic, Philadelphia, PA, USA.
authors.forename: Marc
authors.initials: M
authors.lastname: Legere
authors.affiliation: AccuraScience, Johnston, IA, USA.
authors.forename: Tongbin
authors.initials: T
authors.lastname: Li
authors.affiliation: Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
authors.forename: Samara
authors.initials: S
authors.lastname: Levine
authors.affiliation: Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
authors.forename: Ke
authors.initials: K
authors.lastname: Hao
authors.affiliation: Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
authors.forename: Breanna
authors.initials: B
authors.lastname: Valcarcel
authors.affiliation: Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.|Geriatric Research, Education & Clinical Center, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA.
authors.forename: Giulio M
authors.initials: GM
authors.lastname: Pasinetti
mesh_terms: D001342:Autonomic Nervous System Diseases / Q000209:etiology*; D000070642:Brain Injuries, Traumatic / Q000150:complications*; D016009:Chi-Square Distribution; D005260:Female; D005684:Gait / Q000502:physiology; D006801:Humans; D008297:Male; D008954:Models, Biological; D009422:Nervous System Diseases / Q000150:complications / Q000175:diagnosis / Q000209:etiology; D011237:Predictive Value of Tests; D060388:Support Vector Machine
keywords: Alzheimer’s disease; autonomic nervous system; biomarker; neurodegenerative disorders; risk factor; traumatic brain injury