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Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects.一项对41321名受试者的全基因组研究:拷贝数变异对精神分裂症的影响
Nat Genet. 2017 Jan;49(1):27-35. doi: 10.1038/ng.3725. Epub 2016 Nov 21.
2
Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia.4877名精神分裂症患者中极罕见的蛋白质改变变体负担增加。
Nat Neurosci. 2016 Nov;19(11):1433-1441. doi: 10.1038/nn.4402. Epub 2016 Oct 3.
3
Whole-genome sequencing in multiplex families with psychoses reveals mutations in the SHANK2 and SMARCA1 genes segregating with illness.对患有精神病的多个家族进行全基因组测序,发现SHANK2和SMARCA1基因中的突变与疾病共分离。
Mol Psychiatry. 2016 Dec;21(12):1690-1695. doi: 10.1038/mp.2016.24. Epub 2016 Mar 22.
4
Rare loss-of-function variants in SETD1A are associated with schizophrenia and developmental disorders.SETD1A基因中罕见的功能丧失变异与精神分裂症和发育障碍有关。
Nat Neurosci. 2016 Apr;19(4):571-7. doi: 10.1038/nn.4267. Epub 2016 Mar 14.
5
Exome arrays capture polygenic rare variant contributions to schizophrenia.外显子组芯片捕获了多基因罕见变异对精神分裂症的影响。
Hum Mol Genet. 2016 Mar 1;25(5):1001-7. doi: 10.1093/hmg/ddv620. Epub 2016 Jan 5.
6
Contrasting genetic architectures of schizophrenia and other complex diseases using fast variance-components analysis.使用快速方差成分分析对比精神分裂症和其他复杂疾病的遗传结构。
Nat Genet. 2015 Dec;47(12):1385-92. doi: 10.1038/ng.3431. Epub 2015 Nov 2.
7
Identity-by-descent mapping in a Scandinavian multiple sclerosis cohort.斯堪的纳维亚多发性硬化症队列中的同源性映射
Eur J Hum Genet. 2015 May;23(5):688-92. doi: 10.1038/ejhg.2014.155. Epub 2014 Aug 27.
8
Biological insights from 108 schizophrenia-associated genetic loci.108 个精神分裂症相关遗传位点的生物学见解。
Nature. 2014 Jul 24;511(7510):421-7. doi: 10.1038/nature13595. Epub 2014 Jul 22.
9
De novo mutations in schizophrenia implicate chromatin remodeling and support a genetic overlap with autism and intellectual disability.精神分裂症中的从头突变提示染色质重塑,并支持与自闭症和智力障碍的遗传重叠。
Mol Psychiatry. 2014 Jun;19(6):652-8. doi: 10.1038/mp.2014.29. Epub 2014 Apr 29.
10
An evaluation of copy number variation detection tools from whole-exome sequencing data.基于全外显子组测序数据的拷贝数变异检测工具评估
Hum Mutat. 2014 Jul;35(7):899-907. doi: 10.1002/humu.22537. Epub 2014 May 1.

基于人群的同源定位作图结合外显子组测序检测精神分裂症的罕见风险变异。

Population-based identity-by-descent mapping combined with exome sequencing to detect rare risk variants for schizophrenia.

机构信息

Neuropsychiatric Genetics Research Group, Institute of Molecular Medicine and Discipline of Psychiatry, Trinity College Dublin, Dublin, Ireland.

School of Biotechnology, Dublin City University, Dublin, Ireland.

出版信息

Am J Med Genet B Neuropsychiatr Genet. 2019 Apr;180(3):223-231. doi: 10.1002/ajmg.b.32716. Epub 2019 Feb 23.

DOI:10.1002/ajmg.b.32716
PMID:30801977
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8863274/
Abstract

Genome-wide association studies (GWASs) are highly effective at identifying common risk variants for schizophrenia. Rare risk variants are also important contributors to schizophrenia etiology but, with the exception of large copy number variants, are difficult to detect with GWAS. Exome and genome sequencing, which have accelerated the study of rare variants, are expensive so alternative methods are needed to aid detection of rare variants. Here we re-analyze an Irish schizophrenia GWAS dataset (n = 3,473) by performing identity-by-descent (IBD) mapping followed by exome sequencing of individuals identified as sharing risk haplotypes to search for rare risk variants in coding regions. We identified 45 rare haplotypes (>1 cM) that were significantly more common in cases than controls. By exome sequencing 105 haplotype carriers, we investigated these haplotypes for functional coding variants that could be tested for association in independent GWAS samples. We identified one rare missense variant in PCNT but did not find statistical support for an association with schizophrenia in a replication analysis. However, IBD mapping can prioritize both individual samples and genomic regions for follow-up analysis but genome rather than exome sequencing may be more effective at detecting risk variants on rare haplotypes.

摘要

全基因组关联研究(GWAS)在识别精神分裂症的常见风险变异方面非常有效。罕见风险变异也是精神分裂症病因的重要贡献者,但除了大片段拷贝数变异外,GWAS 很难检测到这些变异。外显子组和基因组测序加速了对罕见变异的研究,但这些方法昂贵,因此需要替代方法来帮助检测罕见变异。在这里,我们通过对被鉴定为共享风险单倍型的个体进行亲缘关系(IBD)作图和外显子组测序,对一个爱尔兰精神分裂症 GWAS 数据集(n=3473)进行了重新分析,以搜索编码区域中的罕见风险变异。我们确定了 45 个罕见单倍型(>1 cM),这些单倍型在病例中比对照组更为常见。通过对 105 个单倍型携带者进行外显子组测序,我们研究了这些单倍型中的功能编码变异,这些变异可以在独立的 GWAS 样本中进行关联测试。我们在 PCNT 中发现了一个罕见的错义变异,但在复制分析中没有发现与精神分裂症关联的统计学支持。然而,IBD 作图可以优先对个体样本和基因组区域进行后续分析,但在检测罕见单倍型上,全基因组测序可能比外显子组测序更有效。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/766a/8863274/6b8820994b4e/nihms-1778948-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/766a/8863274/6b8820994b4e/nihms-1778948-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/766a/8863274/6b8820994b4e/nihms-1778948-f0001.jpg