PGC-PSTD 血统工作组:将混血儿更好地纳入精神疾病全球监测系统

IF 6.1 2区 医学 Q1 CLINICAL NEUROLOGY European Neuropsychopharmacology Pub Date : 2024-10-01 DOI:10.1016/j.euroneuro.2024.08.016
Marcos Santoro , Jessica Mauer , Adam Maihofer , Nirav Shah , Caroline Nievergelt , Elizabeth Atkinson
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引用次数: 0

摘要

最新的 PGC-PTSD 基因组研究大大增加了非欧洲人群的样本量,其中包括 50,000 多名非洲裔美国人(AA)和 13,000 多名拉丁美洲人(LA)。分析这些样本的困难之一在于它们通常具有很强的混杂性,根据采集地区的不同,混杂模式也不同。PGC-PTSD 祖先工作组致力于开发新工具,以便将混血个体适当纳入 GWAS,并为 LMIC 合作者使用这些工具提供便利。在此之前,我们开发了 Tractor,这是一种针对混血人群的基因发现工具,它使用本地祖先推断(LAI)将这些个体纳入 GWAS 研究,并对其进行良好校准。目前,我们的主要工作之一是全面测试 LAI 的策略,为参数设置和参考面板组成提供指导。为此,我们考虑了不同的混杂模式(AA-2 方式和 LA-3 方式)、人口统计模型、软件设置、基因组数据类型和参考面板,对混杂个体进行了模拟。通过这些模拟,我们确定了最佳实践指南,供研究人员在分析不同人群时使用,以便在不同祖先间得出最高准确度的结果。在我们的测试中,我们发现美洲土著祖先区与欧洲和非洲祖先区相比,准确度明显降低。当误判发生时,LAI 误差率最常出现的方向是在真正的美洲土著地点判定欧洲人祖先,而不是其他误差模式。虽然我们的研究是直接针对实际的拉丁美洲混血人群组成的,但我们所描述的趋势对不同混血人群的当地祖先推断的最佳实践具有广泛的参考价值。在提高 LAI 分析准确性的同时,我们的工作小组还在为 Tractor 开发一个友好的管道,以便其他联盟可以将这种方法应用于大样本量。从未来的角度来看,PGC-PTSD 祖先工作组还将致力于开发用于后 GWAS 方法的新工具,如多基因评分。
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THE PGC-PSTD ANCESTRY WORKING GROUP: IMPROVING THE INCLUSION OF ADMIXED INDIVIDUALS IN PSYCHIATRIC GWAS
The latest PGC-PTSD GWAS achieved a considerable increase in the sample sizes of non-European populations, including more than 50,000 African American (AA) and 13,000 Latin American (LA) individuals. One of the difficulties in analyzing these samples is that they are usually very admixed, with different patterns of admixture according to the region they have been collected. The PGC-PTSD Ancestry working group is focused on developing new tools to allow proper inclusion of admixed individuals in GWAS and to facilitate the use of these tools for LMIC collaborators. Previously, we developed Tractor, a gene discovery tool for admixed populations that uses Local Ancestry Inference (LAI) to allow the well-calibrated inclusion of these individuals in GWAS studies. Currently, one of the primary efforts is to comprehensively test strategies for LAI to provide guidelines for parameter setting and reference panel composition. For this, we have simulated admixed individuals considering different patterns of admixture (AA-2 way and LA-3 way), demographic models, software settings, genomic data types, and reference panels. These simulations allow us to define best practice guidelines for researchers to use when analyzing diverse populations to produce the highest accuracy results across ancestries.
In our tests, we observe that Amerindigenous ancestry tracts suffer from notably reduced accuracy as compared to European and African tracts. When miscalls occur, LAI error rates are most frequently in the direction of calling European ancestry in true Amerindigenous sites than other error modes. Though our investigations are directly responsive to realistic admixed Latin American cohort compositions, the trends we characterize are broadly useful to inform best practice for local ancestry inference across diverse admixed populations. In parallel with this initiative of improving LAI analysis accuracy, our working group is developing a friendly pipeline for Tractor so other consortia can apply this approach for large sample sizes. As a future perspective, the PGC-PTSD ancestry working group will also work on the development of new tools for post GWAS approaches as polygenic scores.
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来源期刊
European Neuropsychopharmacology
European Neuropsychopharmacology 医学-精神病学
CiteScore
10.30
自引率
5.40%
发文量
730
审稿时长
41 days
期刊介绍: European Neuropsychopharmacology is the official publication of the European College of Neuropsychopharmacology (ECNP). In accordance with the mission of the College, the journal focuses on clinical and basic science contributions that advance our understanding of brain function and human behaviour and enable translation into improved treatments and enhanced public health impact in psychiatry. Recent years have been characterized by exciting advances in basic knowledge and available experimental techniques in neuroscience and genomics. However, clinical translation of these findings has not been as rapid. The journal aims to narrow this gap by promoting findings that are expected to have a major impact on both our understanding of the biological bases of mental disorders and the development and improvement of treatments, ideally paving the way for prevention and recovery.
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