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本文引用的文献

1
The personal and clinical utility of polygenic risk scores.多基因风险评分的个体和临床效用。
Nat Rev Genet. 2018 Sep;19(9):581-590. doi: 10.1038/s41576-018-0018-x.
2
Polygenic prediction of the phenome, across ancestry, in emerging adulthood.多基因预测表型,跨越血统,在新兴成年期。
Psychol Med. 2018 Aug;48(11):1814-1823. doi: 10.1017/S0033291717003312. Epub 2017 Nov 27.
3
Association Between Schizophrenia-Related Polygenic Liability and the Occurrence and Level of Mood-Incongruent Psychotic Symptoms in Bipolar Disorder.精神分裂症相关多基因易感性与双相情感障碍中情绪不一致性精神病性症状的发生及程度之间的关联
JAMA Psychiatry. 2018 Jan 1;75(1):28-35. doi: 10.1001/jamapsychiatry.2017.3485.
4
Prospects for using risk scores in polygenic medicine.多基因医学中风险评分的应用前景。
Genome Med. 2017 Nov 13;9(1):96. doi: 10.1186/s13073-017-0489-y.
5
A machine-learning heuristic to improve gene score prediction of polygenic traits.一种用于改善多基因性状基因评分预测的机器学习启发式方法。
Sci Rep. 2017 Oct 4;7(1):12665. doi: 10.1038/s41598-017-13056-1.
6
Multi-polygenic score approach to trait prediction.多基因评分法进行特征预测。
Mol Psychiatry. 2018 May;23(5):1368-1374. doi: 10.1038/mp.2017.163. Epub 2017 Aug 8.
7
The Hierarchical Taxonomy of Psychopathology (HiTOP): A dimensional alternative to traditional nosologies.精神病理学的分层分类法(HiTOP):传统分类法的维度替代方案。
J Abnorm Psychol. 2017 May;126(4):454-477. doi: 10.1037/abn0000258. Epub 2017 Mar 23.
8
Polygenic risk scores for schizophrenia and bipolar disorder associate with addiction.精神分裂症和双相情感障碍的多基因风险评分与成瘾相关。
Addict Biol. 2018 Jan;23(1):485-492. doi: 10.1111/adb.12496. Epub 2017 Feb 23.
9
Predicting educational achievement from DNA.从DNA预测学业成就。
Mol Psychiatry. 2017 Feb;22(2):267-272. doi: 10.1038/mp.2016.107. Epub 2016 Jul 19.
10
Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores.连锁不平衡建模提高了多基因风险评分的准确性。
Am J Hum Genet. 2015 Oct 1;97(4):576-92. doi: 10.1016/j.ajhg.2015.09.001.

多基因风险评分与心理健康结局预测。

Polygenic risk scoring and prediction of mental health outcomes.

机构信息

Department of Psychiatry, University of Utah School of Medicine, 201 President's Circle, Salt Lake City, UT 8412, USA.

Department of Psychiatry, University of Utah School of Medicine, 201 President's Circle, Salt Lake City, UT 8412, USA; Virginia Institute for Psychiatric & Behavioral Genetics, Virginia Commonwealth University School of Medicine, 800 E. Leigh St., Biotech One Suite 100, Richmond, VA 23219, USA.

出版信息

Curr Opin Psychol. 2019 Jun;27:77-81. doi: 10.1016/j.copsyc.2018.09.002. Epub 2018 Sep 20.

DOI:10.1016/j.copsyc.2018.09.002
PMID:30339992
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6426686/
Abstract

Psychiatric conditions are highly polygenic, meaning that genetic risk arises from many hundreds or thousands of genetic variants. Psychiatric genomics and psychological science are increasingly using polygenic risk scoring-the integration of all common genetic variant effects into a single risk metric-to model latent risk and to predict mental health outcomes. This review discusses the use of these scores in psychology and psychiatry to date, important methodological considerations, and potential of scoring methods for informing psychological science. Polygenic risk scores can easily be added to environmental and behavioral genetic models of latent risk, making them desirable metrics for use in psychological research.

摘要

精神疾病具有高度的多基因遗传特征,这意味着遗传风险来自数百或数千种常见的遗传变异。精神疾病遗传学和心理学科学越来越多地使用多基因风险评分——将所有常见遗传变异的影响整合到一个单一的风险指标中——来构建潜在风险模型并预测心理健康结果。本综述讨论了迄今为止这些评分在心理学和精神病学中的应用、重要的方法学考虑因素以及评分方法在心理科学中的应用潜力。多基因风险评分可以很容易地添加到潜在风险的环境和行为遗传模型中,因此它们是心理研究中非常理想的指标。