Polygenic Risk Scores in Clinical Psychology: Bridging Genomic Risk to Individual Differences.
Polygenic Risk Scores in Clinical Psychology: Bridging Genomic Risk to Individual Differences.
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DOI：
10.1146/annurev-clinpsy-050817-084847
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发表时间：
2018-05-07
影响因子：
18.4
通讯作者：
Agrawal A
中科院分区：
文献类型：
--
作者：
Bogdan R;Baranger DAA;Agrawal A
跨精神病表型的全基因组关联研究（GWAS）表明，常见的遗传变异通常会带来风险，其效应大小较小（OR<1.1），可增加多基因风险。从大型发现GWAS导出的汇总统计量可用于在独立的目标数据集中生成多基因风险评分（PRS），以检查多基因疾病易感性的相关性（例如，精神分裂症的遗传易感性是否能预测认知）。PRS的直观吸引力和普遍性导致了其广泛使用和对多基因责任机制的新见解。然而，目前，当跨性状应用时，它们占小的影响（小于3%的方差），并且对于临床治疗相对无意义，并且单独地，不能提供对分子机制的洞察。需要更大的GWAS来提高其精度和集成各种数据源的新方法（例如，GWAS的多性状分析）可以改进当前PRS的效用。
Genomewide association studies (GWAS) across psychiatric phenotypes have shown that common genetic variants generally confer risk with small effect sizes (OR<1.1) that additively contribute to polygenic risk. Summary statistics derived from large discovery GWAS can be used to generate polygenic risk scores (PRS) in independent, target datasets to examine correlates of polygenic disorder liability (e.g., does genetic liability to schizophrenia predict cognition). The intuitive appeal and generalizability of PRS have led to their widespread use and new insight into mechanisms of polygenic liability. However, presently, when applied across traits they account for small effects (less than 3% of variance) and are relatively uninformative for clinical treatment and, in isolation, provide no insight into molecular mechanisms. Larger GWAS are needed to increase their precision and novel approaches integrating various data sources (e.g., multi-trait analysis of GWAS) may improve the utility of current PRS.
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DOI：
10.1002/ajmg.b.32558
发表时间：
2017-10
期刊：
American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics
影响因子：
--
作者：
Coleman JRI;Lester KJ;Keers R;Munafò MR;Breen G;Eley TC
通讯作者：
Eley TC
影响因子：
25
作者：
Breen G;Li Q;Roth BL;O'Donnell P;Didriksen M;Dolmetsch R;O'Reilly PF;Gaspar HA;Manji H;Huebel C;Kelsoe JR;Malhotra D;Bertolino A;Posthuma D;Sklar P;Kapur S;Sullivan PF;Collier DA;Edenberg HJ
通讯作者：
Edenberg HJ
影响因子：
30.8
作者：
Bulik-Sullivan, Brendan K.;Loh, Po-Ru;Finucane, Hilary K.;Ripke, Stephan;Yang, Jian;Patterson, Nick;Daly, Mark J.;Price, Alkes L.;Neale, Benjamin M.
通讯作者：
Neale, Benjamin M.
影响因子：
64.5
作者：
Boyle EA;Li YI;Pritchard JK
通讯作者：
Pritchard JK
影响因子：
4.7
作者：
Bierut LJ;Johnson EO;Saccone NL
通讯作者：
Saccone NL