Polygenic scores for psychiatric disorders in a diverse postmortem brain tissue cohort.

Polygenic scores for psychiatric disorders in a diverse postmortem brain tissue cohort.
复制标题

DOI:
10.1038/s41386-022-01524-w
复制
发表时间:
2023-04
影响因子:
7.6
通讯作者:
Marenco, Stefano
Marenco, Stefano
中科院分区:
医学1区
文献类型:
--
作者:
Duncan, Laramie;Shen, Hanyang;Schulmann, Anton;Li, Tayden;Kolachana, Bhaskar;Mandal, Ajeet;Feng, Ningping;Auluck, Pavan;Marenco, Stefano

文献摘要

参考文献

相似文献

由于“组学技术”的发展,人类死后组织研究的新时代已经出现,这些技术可以以前所未有的细节测量基因、蛋白质和空间参数。此外,新的可能是构建多基因评分,遗传风险的个体水平指标(也称为多基因风险评分/PRS),基于全基因组关联研究,GWAS的能力。在这里,我们报告临床,教育,和大脑基因表达相关的多基因得分在祖先不同的样本从人脑收集核心(HBCC)。对来自1418名供体的基因型进行质量控制过滤,插补,并用于构建多基因评分。精神分裂症的多基因评分预测了欧洲血统供体(p = 4.7 × 10−8,17.2%)和非洲血统供体(p = 1.6 × 10−5,解释了10.4%的表型方差)的精神分裂症状态。在其他精神疾病(抑郁症、双相情感障碍、物质使用障碍、焦虑症)以及身高、体重指数和受教育年限方面,也观察到欧洲血统样本中解释的这种较高变异模式。对于223个样本的子集,背外侧前额叶皮层(DLPFC)的基因表达可通过CommonMind联盟获得。在这个亚组中,精神分裂症多基因评分也预测了精神分裂症的总基因表达评分(欧洲血统:p = 0.0032,非洲血统:p = 0.15)。总体而言,多基因评分在血统多样的样本中表现如预期,考虑到使用欧洲血统样本的历史偏倚和表型间多基因评分的可变预测能力。这里报道的转录组学结果表明,遗传性精神分裂症的遗传风险影响基因表达,即使在成年期。对于未来的研究,这些和额外的多基因评分可用于分析,并选择样本,使用死后组织从人脑收集核心。
A new era of human postmortem tissue research has emerged thanks to the development of ‘omics technologies that measure genes, proteins, and spatial parameters in unprecedented detail. Also newly possible is the ability to construct polygenic scores, individual-level metrics of genetic risk (also known as polygenic risk scores/PRS), based on genome-wide association studies, GWAS. Here, we report on clinical, educational, and brain gene expression correlates of polygenic scores in ancestrally diverse samples from the Human Brain Collection Core (HBCC). Genotypes from 1418 donors were subjected to quality control filters, imputed, and used to construct polygenic scores. Polygenic scores for schizophrenia predicted schizophrenia status in donors of European ancestry (p = 4.7 × 10−8, 17.2%) and in donors with African ancestry (p = 1.6 × 10−5, 10.4% of phenotypic variance explained). This pattern of higher variance explained among European ancestry samples was also observed for other psychiatric disorders (depression, bipolar disorder, substance use disorders, anxiety disorders) and for height, body mass index, and years of education. For a subset of 223 samples, gene expression from dorsolateral prefrontal cortex (DLPFC) was available through the CommonMind Consortium. In this subgroup, schizophrenia polygenic scores also predicted an aggregate gene expression score for schizophrenia (European ancestry: p = 0.0032, African ancestry: p = 0.15). Overall, polygenic scores performed as expected in ancestrally diverse samples, given historical biases toward use of European ancestry samples and variable predictive power of polygenic scores across phenotypes. The transcriptomic results reported here suggest that inherited schizophrenia genetic risk influences gene expression, even in adulthood. For future research, these and additional polygenic scores are being made available for analyses, and for selecting samples, using postmortem tissue from the Human Brain Collection Core.
基因发现和多基因预测,从基因组全基因组协会的教育程度研究中,有110万个人。
DOI: 10.1038/s41588-018-0147-3
发表时间: 2018-07-23
期刊: Nature genetics
影响因子: 30.8
作者:
Lee JJ;Wedow R;Okbay A;Kong E;Maghzian O;Zacher M;Nguyen-Viet TA;Bowers P;Sidorenko J;Karlsson Linnér R;Fontana MA;Kundu T;Lee C;Li H;Li R;Royer R;Timshel PN;Walters RK;Willoughby EA;Yengo L;23andMe Research Team;COGENT (Cognitive Genomics Consortium);Social Science Genetic Association Consortium;Alver M;Bao Y;Clark DW;Day FR;Furlotte NA;Joshi PK;Kemper KE;Kleinman A;Langenberg C;Mägi R;Trampush JW;Verma SS;Wu Y;Lam M;Zhao JH;Zheng Z;Boardman JD;Campbell H;Freese J;Harris KM;Hayward C;Herd P;Kumari M;Lencz T;Luan J;Malhotra AK;Metspalu A;Milani L;Ong KK;Perry JRB;Porteous DJ;Ritchie MD;Smart MC;Smith BH;Tung JY;Wareham NJ;Wilson JF;Beauchamp JP;Conley DC;Esko T;Lehrer SF;Magnusson PKE;Oskarsson S;Pers TH;Robinson MR;Thom K;Watson C;Chabris CF;Meyer MN;Laibson DI;Yang J;Johannesson M;Koellinger PD;Turley P;Visscher PM;Benjamin DJ;Cesarini D
通讯作者: Cesarini D
DOI: 10.1038/ng.3656
发表时间: 2016-10
期刊: NATURE GENETICS
影响因子: 30.8
作者:
Das, Sayantan;Forer, Lukas;Schoenherr, Sebastian;Sidore, Carlo;Locke, Adam E.;Kwong, Alan;Vrieze, Scott I.;Chew, Emily Y.;Levy, Shawn;McGue, Matt;Schlessinger, David;Stambolian, Dwight;Loh, Po-Ru;Iacono, William G.;Swaroop, Anand;Scott, Laura J.;Cucca, Francesco;Kronenberg, Florian;Boehnke, Michael;Abecasis, Goncalo R.;Fuchsberger, Christian
通讯作者: Fuchsberger, Christian
DOI: 10.1038/s41593-018-0187-0
发表时间: 2018-08
影响因子: 25
作者:
Girdhar K;Hoffman GE;Jiang Y;Brown L;Kundakovic M;Hauberg ME;Francoeur NJ;Wang YC;Shah H;Kavanagh DH;Zharovsky E;Jacobov R;Wiseman JR;Park R;Johnson JS;Kassim BS;Sloofman L;Mattei E;Weng Z;Sieberts SK;Peters MA;Harris BT;Lipska BK;Sklar P;Roussos P;Akbarian S
通讯作者: Akbarian S
DOI: 10.1186/s13742-015-0047-8
发表时间: 2015
期刊: GigaScience
影响因子: 9.2
作者:
Chang CC;Chow CC;Tellier LC;Vattikuti S;Purcell SM;Lee JJ
通讯作者: Lee JJ
DOI: 10.1002/gepi.21896
发表时间: 2015-05
影响因子: 2.1
作者:
Conomos MP;Miller MB;Thornton TA
通讯作者: Thornton TA