Dima Danai, Breen Gerome
Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK National Institute of Health Research (NIHR) Biomedical Research Centre for Mental Health, South London and Maudsley National Health Service (NHS) Trust, London, UK.
J Psychopharmacol. 2015 Aug;29(8):867-71. doi: 10.1177/0269881115584470. Epub 2015 May 5.
Genetic factors account for up to 80% of the liability for schizophrenia and bipolar disorder. Genome-wide association studies (GWAS) have successfully identified several single nucleotide polymorphisms (SNPs) and genes associated with increased risk for both disorders. Single SNP analyses alone do not address the overall genomic or polygenic architecture of psychiatric disorders as the amount of phenotypic variation explained by each GWAS-supported SNP is small whereas the number of SNPs/regions underlying risk for illness is thought to be very large. The polygenic risk score models the aggregate effect of alleles associated with disease status present in each individual and allows us to utilise the power of large GWAS to be applied robustly in small samples. Here we make the case that risk prediction, intervention and personalised medicine can only benefit with the inclusion of polygenic risk scores in imaging genetics research.
遗传因素在精神分裂症和双相情感障碍的发病因素中占比高达80%。全基因组关联研究（GWAS）已成功识别出多个与这两种疾病风险增加相关的单核苷酸多态性（SNP）和基因。仅单SNP分析无法揭示精神疾病的整体基因组或多基因结构，因为每个GWAS支持的SNP所解释的表型变异量很小，而导致疾病风险的SNP/区域数量被认为非常多。多基因风险评分对每个个体中与疾病状态相关的等位基因的综合效应进行建模，并使我们能够利用大型GWAS的功效，在小样本中稳健应用。在此，我们认为在影像遗传学研究中纳入多基因风险评分，风险预测、干预和个性化医疗才能从中受益。
