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Deep phenotyping of Alzheimer's disease leveraging electronic medical records identifies sex-specific clinical associations.

Alice S TangTomiko T OskotskyShreyas HavaldarWilliam G MantyhMesude BicakCaroline Warly SolsbergSarah R WoldemariamBilly ZengZicheng HuBoris OskotskyDena B DubalIsabel E AllenBenjamin Scott GlicksbergMarina Sirota
Published in: Nature communications (2022)
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.
Keyphrases
  • network analysis
  • high throughput
  • healthcare
  • ejection fraction
  • cognitive decline
  • genome wide
  • newly diagnosed
  • case report
  • gene expression
  • dna methylation
  • single cell