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Increasing the resolution and precision of psychiatric genome‐wide association studies by re‐imputing summary statistics using a large, diverse reference panel
American Journal of Medical Genetics Part B: Neuropsychiatric Genetics ( IF 2.8 ) Pub Date : 2021-02-11 , DOI: 10.1002/ajmg.b.32834
Chris Chatzinakos 1, 2 , Donghyung Lee 3 , Na Cai 4 , Vladimir I Vladimirov 5 , Bradley T Webb 5 , Brien P Riley 5 , Jonathan Flint 6 , Kenneth S Kendler 5 , Kerry J Ressler 1 , Nikolaos P Daskalakis 1, 2 , Silviu-Alin Bacanu 5
Affiliation  

Genotype imputation across populations of mixed ancestry is critical for optimal discovery in large‐scale genome‐wide association studies (GWAS). Methods for direct imputation of GWAS summary‐statistics were previously shown to be practically as accurate as summary statistics produced after raw genotype imputation, while incurring orders of magnitude lower computational burden. Given that direct imputation needs a precise estimation of linkage‐disequilibrium (LD) and that most of the methods using a small reference panel for example, ~2,500‐subject coming from the 1000 Genome‐Project, there is a great need for much larger and more diverse reference panels. To accurately estimate the LD needed for an exhaustive analysis of any cosmopolitan cohort, we developed DISTMIX2. DISTMIX2: (a) uses a much larger and more diverse reference panel compared to traditional reference panels, and (b) can estimate weights of ethnic‐mixture based solely on Z‐scores, when allele frequencies are not available. We applied DISTMIX2 to GWAS summary‐statistics from the psychiatric genetic consortium (PGC). DISTMIX2 uncovered signals in numerous new regions, with most of these findings coming from the rarer variants. Rarer variants provide much sharper location for the signals compared with common variants, as the LD for rare variants extends over a lower distance than for common ones. For example, while the original PGC post‐traumatic stress disorder GWAS found only 3 marginal signals for common variants, we now uncover a very strong signal for a rare variant in PKN2, a gene associated with neuronal and hippocampal development. Thus, DISTMIX2 provides a robust and fast (re)imputation approach for most psychiatric GWAS‐studies.

中文翻译:

通过使用大型、多样化的参考面板重新计算汇总统计数据,提高精神病学全基因组关联研究的分辨率和精确度

混合血统人群的基因型估算对于大规模全基因组关联研究 (GWAS) 中的最佳发现至关重要。先前表明,直接插补 GWAS 汇总统计数据的方法实际上与原始基因型插补后生成的汇总统计数据一样准确,同时计算负担降低了几个数量级。鉴于直接插补需要对连锁不平衡 (LD) 进行精确估计,并且大多数方法都使用小型参考面板,例如来自 1000 基因组计划的约 2,500 名受试者,因此非常需要更大和更广泛的参考面板。更多样化的参考面板。为了准确估计对任何国际化队列进行详尽分析所需的 LD,我们开发了 DISTMIX2。DISTMIX2:(a)与传统参考组相比,使用更大、更多样化的参考组,并且(b)当等位基因频率不可用时,可以仅根据 Z 分数估计种族混合的权重。我们将 DISTMIX2 应用到精神病学遗传联盟 (PGC) 的 GWAS 摘要统计中。DISTMIX2 在许多新区域中发现了信号,其中大部分发现来自较罕见的变异。与常见变体相比,稀有变体为信号提供了更清晰的位置,因为罕见变体的 LD 延伸的距离比常见变体更短。例如,虽然最初的 PGC 创伤后应激障碍 GWAS 仅发现了常见变异的 3 个边缘信号,但我们现在发现了PKN2中罕见变异的非常强的信号,PKN2 是一种与神经元和海马发育相关的基因。因此,DISTMIX2 为大多数精神病学 GWAS 研究提供了一种稳健且快速的(重新)插补方法。
更新日期:2021-03-02
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