Browsing by Author "Li, Yun"

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    EndoPRS: Incorporating Endophenotype Information to Improve Polygenic Risk Scores for Clinical Endpoints
    (medRxiv, 2024-05-24) Kharitonova, Elena V.; Sun, Quan; Ockerman, Frank; Chen, Brian; Zhou, Laura Y.; Cao, Hongyuan; Mathias, Rasika A.; Auer, Paul L.; Ober, Carole; Raffield, Laura M.; Reiner, Alexander P.; Cox, Nancy J.; Kelada, Samir; Tao, Ran; Li, Yun; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public Health
    Polygenic risk score (PRS) prediction of complex diseases can be improved by leveraging related phenotypes. This has motivated the development of several multi-trait PRS methods that jointly model information from genetically correlated traits. However, these methods do not account for vertical pleiotropy between traits, in which one trait acts as a mediator for another. Here, we introduce endoPRS, a weighted lasso model that incorporates information from relevant endophenotypes to improve disease risk prediction without making assumptions about the genetic architecture underlying the endophenotype-disease relationship. Through extensive simulation analysis, we demonstrate the robustness of endoPRS in a variety of complex genetic frameworks. We also apply endoPRS to predict the risk of childhood onset asthma in UK Biobank by leveraging a paired GWAS of eosinophil count, a relevant endophenotype. We find that endoPRS significantly improves prediction compared to many existing PRS methods, including multi-trait PRS methods, MTAG and wMT-BLUP, which suggests advantages of endoPRS in real-life clinical settings.
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    A Multiancestral Genome-Wide Exome Array Study of Alzheimer Disease, Frontotemporal Dementia, and Progressive Supranuclear Palsy
    (2015-04) Chen, Jason A.; Wang, Qing; Davis-Turak, Jeremy; Li, Yun; Karydas, Anna M.; Hsu, Sandy C.; Sears, Renee L.; Chatzopoulou, Doxa; Huang, Alden Y.; Wojta, Kevin J.; Klein, Eric; Lee, Jason; Beekly, Duane L.; Boxer, Adam; Faber, Kelley M.; Haase, Claudia M.; Miller, Josh; Poon, Wayne W.; Rosen, Ami; Rosen, Howard; Sapozhnikova, Anna; Shapira, Jill; Varpetian, Arousiak; Foroud, Tatiana M.; Levenson, Robert W.; Levey, Allan I.; Kukull, Walter A.; Mendez, Mario F.; Ringman, John; Chui, Helena; Cotman, Carl; DeCarli, Charles; Miller, Bruce L.; Geschwind, Daniel H.; Coppola, Giovanni; Department of Medical and Molecular Genetics, IU School of Medicine
    Importance Previous studies have indicated a heritable component of the etiology of neurodegenerative diseases such as Alzheimer disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP). However, few have examined the contribution of low-frequency coding variants on a genome-wide level. Objective To identify low-frequency coding variants that affect susceptibility to AD, FTD, and PSP. Design, Setting, and Participants We used the Illumina HumanExome BeadChip array to genotype a large number of variants (most of which are low-frequency coding variants) in a cohort of patients with neurodegenerative disease (224 with AD, 168 with FTD, and 48 with PSP) and in 224 control individuals without dementia enrolled between 2005-2012 from multiple centers participating in the Genetic Investigation in Frontotemporal Dementia and Alzheimer’s Disease (GIFT) Study. An additional multiancestral replication cohort of 240 patients with AD and 240 controls without dementia was used to validate suggestive findings. Variant-level association testing and gene-based testing were performed. Main Outcomes and Measures Statistical association of genetic variants with clinical diagnosis of AD, FTD, and PSP. Results Genetic variants typed by the exome array explained 44%, 53%, and 57% of the total phenotypic variance of AD, FTD, and PSP, respectively. An association with the known AD gene ABCA7 was replicated in several ancestries (discovery P = .0049, European P = .041, African American P = .043, and Asian P = .027), suggesting that exonic variants within this gene modify AD susceptibility. In addition, 2 suggestive candidate genes, DYSF (P = 5.53 × 10−5) and PAXIP1 (P = 2.26 × 10−4), were highlighted in patients with AD and differentially expressed in AD brain. Corroborating evidence from other exome array studies and gene expression data points toward potential involvement of these genes in the pathogenesis of AD. Conclusions and Relevance Low-frequency coding variants with intermediate effect size may account for a significant fraction of the genetic susceptibility to AD and FTD. Furthermore, we found evidence that coding variants in the known susceptibility gene ABCA7, as well as candidate genes DYSF and PAXIP1, confer risk for AD.