Construction and Application of Polygenic Risk Scores in Autoimmune Diseases.
Construction and Application of Polygenic Risk Scores in Autoimmune Diseases.
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DOI：
10.3389/fimmu.2022.889296
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发表时间：
2022
影响因子：
7.3
通讯作者：
中科院分区：
文献类型：
--
作者：
全基因组关联研究（GWAS）已经确定了数百种与自身免疫性疾病相关的遗传变异，并提供了独特的机制见解和新的治疗方法。这些个体遗传变异本身通常对疾病风险的影响很小，预测能力有限；然而，当汇总（例如，通过多基因风险评分方法）时，它们可以为无数疾病提供有意义的风险预测。在这篇综述中，我们描述了GWAS在自身免疫性疾病中的最新进展，以及这些知识在通过多基因风险评分方法预测个体对自身免疫性疾病（如系统性红斑狼疮（SLE））的易感性/严重程度方面的实际应用。我们概述了获得不同多基因风险评分的方法，并讨论了整合来自相关性状和不同祖先的额外信息的策略。我们进一步提倡将临床特征（如抗核抗体状态）与基因谱结合起来，以便在临床体征或症状出现之前更好地识别疾病易感性/严重程度高风险的患者。最后，我们讨论了在临床护理中应用多基因风险评分方法的未来挑战和机遇。
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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影响因子：
5.1
作者：
Billi AC;Kahlenberg JM;Gudjonsson JE
通讯作者：
Gudjonsson JE
影响因子：
30.8
作者：
Barrett, Jeffrey C.;Clayton, David G.;Concannon, Patrick;Akolkar, Beena;Cooper, Jason D.;Erlich, Henry A.;Julier, Cecile;Morahan, Grant;Nerup, Jorn;Nierras, Concepcion;Plagnol, Vincent;Pociot, Flemming;Schuilenburg, Helen;Smyth, Deborah J.;Stevens, Helen;Todd, John A.;Walker, Neil M.;Rich, Stephen S.
通讯作者：
Rich, Stephen S.
DOI：
10.1093/bioinformatics/btu848
发表时间：
2015-05-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Euesden J;Lewis CM;O'Reilly PF
通讯作者：
O'Reilly PF
影响因子：
14.9
作者：
Buniello, Annalisa;MacArthur, Jacqueline A. L.;Parkinson, Helen
通讯作者：
Parkinson, Helen
影响因子：
29.4
作者：
COTTONE, M;ROSSELLI, M;PAGLIARO, L
通讯作者：
PAGLIARO, L