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Construction and Application of Polygenic Risk Scores in Autoimmune Diseases.
Khunsriraksakul, Chachrit; Markus, Havell; Olsen, Nancy J; Carrel, Laura; Jiang, Bibo; Liu, Dajiang J.
Affiliation
  • Khunsriraksakul C; Graduate Program in Bioinformatics and Genomics, Pennsylvania State University College of Medicine, Hershey, PA, United States.
  • Markus H; Institute for Personalized Medicine, Pennsylvania State University College of Medicine, Hershey, PA, United States.
  • Olsen NJ; Graduate Program in Bioinformatics and Genomics, Pennsylvania State University College of Medicine, Hershey, PA, United States.
  • Carrel L; Institute for Personalized Medicine, Pennsylvania State University College of Medicine, Hershey, PA, United States.
  • Jiang B; Department of Medicine, Division of Rheumatology, Pennsylvania State University College of Medicine, Hershey, PA, United States.
  • Liu DJ; Department of Biochemistry and Molecular Biology, Pennsylvania State University College of Medicine, Hershey, PA, United States.
Front Immunol ; 13: 889296, 2022.
Article in En | MEDLINE | ID: mdl-35833142
ABSTRACT
Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with autoimmune diseases and provided unique mechanistic insights and informed novel treatments. These individual genetic variants on their own typically confer a small effect of disease risk with limited predictive power; however, when aggregated (e.g., via polygenic risk score method), they could provide meaningful risk predictions for a myriad of diseases. In this review, we describe the recent advances in GWAS for autoimmune diseases and the practical application of this knowledge to predict an individual's susceptibility/severity for autoimmune diseases such as systemic lupus erythematosus (SLE) via the polygenic risk score method. We provide an overview of methods for deriving different polygenic risk scores and discuss the strategies to integrate additional information from correlated traits and diverse ancestries. We further advocate for the need to integrate clinical features (e.g., anti-nuclear antibody status) with genetic profiling to better identify patients at high risk of disease susceptibility/severity even before clinical signs or symptoms develop. We conclude by discussing future challenges and opportunities of applying polygenic risk score methods in clinical care.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Autoimmune Diseases / Lupus Erythematosus, Systemic Type of study: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Front Immunol Year: 2022 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Autoimmune Diseases / Lupus Erythematosus, Systemic Type of study: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Front Immunol Year: 2022 Document type: Article Affiliation country: