Phenome-Wide Association Study of Polygenic Risk Score for Alzheimer’s Disease in Electronic Health Records

Frontiers in Aging Neuroscience

Michael Broudy¹  Clara Magyar¹  Ruth Jhnson¹  Maryam Ariannejad¹  Sriram Sankraraman¹  Eleazar Eskin¹  Ariff Muhamed¹  Brian L. Hill¹  Sheila Minton¹  Tony Dang¹  Brunilda Balliu¹  Eran Halperin¹  Ankur Jain¹  Yael Berkovich¹  Chris Denny¹  Paul Tung¹  Clara Lajonchere¹  Jae-Hoon Sul¹  Alec Chiu¹  Akos Rudas¹  Ghouse Mohammed¹  Angela M. Badillo¹  Nadav Rakocz¹  Vu Vu¹  Bogdan Pasaniuc¹  Michael A. Pfeffer¹  Ailsa Zheng¹  Timothy J. Sanders¹  UCLA Precision Health Data Discovery Repository Working Group¹  Rey Salonga¹  Yi Ding¹  Anna L. Antonio¹  Vivek Katakwar¹  UCLA Precision Health ATLAS Working Group¹  Pabba Pavan¹  Mingzhou Fu²  Timothy S. Chang³ 

[1] ;Medical Informatics Home Area, Department of Bioinformatics, University of California, Los Angeles, Los Angeles, CA, United States;Movement Disorders Program, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States;

关键词: Alzheimer’s disease;    polygenic risk score;    phenome-wide association study;    electronic health record;    Mendelian randomization;   

DOI  :  10.3389/fnagi.2022.800375

来源: DOAJ

【 摘 要 】

Alzheimer’s disease (AD) is the most common form of dementia and a growing public health burden in the United States. Significant progress has been made in identifying genetic risk for AD, but limited studies have investigated how AD genetic risk may be associated with other disease conditions in an unbiased fashion. In this study, we conducted a phenome-wide association study (PheWAS) by genetic ancestry groups within a large academic health system using the polygenic risk score (PRS) for AD. PRS was calculated using LDpred2 with genome-wide association study (GWAS) summary statistics. Phenotypes were extracted from electronic health record (EHR) diagnosis codes and mapped to more clinically meaningful phecodes. Logistic regression with Firth’s bias correction was used for PRS phenotype analyses. Mendelian randomization was used to examine causality in significant PheWAS associations. Our results showed a strong association between AD PRS and AD phenotype in European ancestry (OR = 1.26, 95% CI: 1.13, 1.40). Among a total of 1,515 PheWAS tests within the European sample, we observed strong associations of AD PRS with AD and related phenotypes, which include mild cognitive impairment (MCI), memory loss, and dementias. We observed a phenome-wide significant association between AD PRS and gouty arthropathy (OR = 0.90, adjusted p = 0.05). Further causal inference tests with Mendelian randomization showed that gout was not causally associated with AD. We concluded that genetic predisposition of AD was negatively associated with gout, but gout was not a causal risk factor for AD. Our study evaluated AD PRS in a real-world EHR setting and provided evidence that AD PRS may help to identify individuals who are genetically at risk of AD and other related phenotypes. We identified non-neurodegenerative diseases associated with AD PRS, which is essential to understand the genetic architecture of AD and potential side effects of drugs targeting genetic risk factors of AD. Together, these findings expand our understanding of AD genetic and clinical risk factors, which provide a framework for continued research in aging with the growing number of real-world EHR linked with genetic data.

【 授权许可】

Unknown