Deep phenotyping of Alzheimer's disease leveraging electronic medical records identifies sex-specific clinical associations.
Deep phenotyping of Alzheimer's disease leveraging electronic medical records identifies sex-specific clinical associations.
复制标题
DOI：
10.1038/s41467-022-28273-0
复制
发表时间：
2022-02-03
影响因子：
16.6
通讯作者：
Sirota M
中科院分区：
文献类型：
--
作者：
Tang AS;Oskotsky T;Havaldar S;Mantyh WG;Bicak M;Solsberg CW;Woldemariam S;Zeng B;Hu Z;Oskotsky B;Dubal D;Allen IE;Glicksberg BS;Sirota M
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.
登录
查看更多内容
DOI：
10.1093/brain/awx224
发表时间：
2017-11-01
期刊：
Brain : a journal of neurology
影响因子：
--
作者：
Chong JSX;Liu S;Loke YM;Hilal S;Ikram MK;Xu X;Tan BY;Venketasubramanian N;Chen CL;Zhou J
通讯作者：
Zhou J
影响因子：
14
作者：
通讯作者：
--
影响因子：
2.5
作者：
AKIYAMA, H;IKEDA, K;MCGEER, PL
通讯作者：
MCGEER, PL
影响因子：
6.6
作者：
Choi, Byung Wook;Kim, Shin;Kim, Hae Won
通讯作者：
Kim, Hae Won
影响因子：
4.2
作者：
Beeri, Michal Schnaider;Schmeidler, James;Haroutunian, Vahram
通讯作者：
Haroutunian, Vahram