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Deep phenotyping of Alzheimer’s disease leveraging electronic medical records identifies sex-specific clinical associations
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Deep phenotyping of Alzheimer’s disease leveraging electronic medical records identifies sex-specific clinical associations
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Journal Article
Deep phenotyping of Alzheimer’s disease leveraging electronic medical records identifies sex-specific clinical associations
2022
Overview
Alzheimer’s Disease (AD) is a neurodegenerative disorder that is still not fully understood. Sex modifies AD vulnerability, but the reasons for this are largely unknown. We utilize two independent electronic medical record (EMR) systems across 44,288 patients to perform deep clinical phenotyping and network analysis to gain insight into clinical characteristics and sex-specific clinical associations in AD. Embeddings and network representation of patient diagnoses demonstrate greater comorbidity interactions in AD in comparison to matched controls. Enrichment analysis identifies multiple known and new diagnostic, medication, and lab result associations across the whole cohort and in a sex-stratified analysis. With this data-driven method of phenotyping, we can represent AD complexity and generate hypotheses of clinical factors that can be followed-up for further diagnostic and predictive analyses, mechanistic understanding, or drug repurposing and therapeutic approaches.
Sex modifies Alzheimer’s Disease vulnerability, but the reasons for this are largely unknown. Here, the authors utilize two independent electronic medical record systems to perform deep clinical phenotyping and network analysis to gain insight into clinical characteristics and sex-specific clinical associations.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
/ Aged
/ Alzheimer Disease - diagnosis
/ Alzheimer Disease - drug therapy
/ Alzheimer Disease - epidemiology
/ Databases, Factual - statistics & numerical data
/ Electronic Health Records - statistics & numerical data
/ Female
/ Humanities and Social Sciences
/ Humans
/ Male
/ Mental Disorders - epidemiology
/ Musculoskeletal Diseases - epidemiology
/ Nervous System Diseases - epidemiology
/ Patients
/ Science
/ Sex
