Harnessing the power of diverse populations to empower clinical translation of genome-wide association studies of common human disease

利用不同人群的力量，促进人类常见疾病全基因组关联研究的临床转化

• 批准号: MR/W029626/1
• 负责人: Andrew Morris
• 金额: $ 53.16万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FW029626%2F1
• 关键词: Harnessing; power; diverse; populations; empower

Genome-wide association studies (GWAS) have been successful in identifying changes in our DNA, referred to as genetic variants, that contribute to our risk of developing many common human diseases, including those that have major public health burden, such as cancers, cardiovascular disease, and diabetes. This success offers exciting opportunities to use genetics for a significant positive impact on human health by: (i) improving our understanding of the biology of disease, thereby informing potential novel treatments; and (ii) predicting the future occurrence of disease in an individual, referred to as polygenic risk scores (PRS). However, despite this success, most GWAS have been performed in white populations of European ancestry, in Europe and North America. This bias in GWAS is in stark contrast to the global and racial/ethnic distribution of many diseases and may therefore exacerbate healthcare disparities because genetic findings from white European ancestry individuals are unlikely to be as impactful in other population groups. For example, the genetic variants that cause disease in white European ancestry individuals might not be observed in other population groups. Consequently, PRS derived from white European ancestry GWAS provide less reliable prediction of disease risk into individuals of African, Asian, or mixed ancestry. The concerns over population bias in genetic studies have prompted a recent expansion of GWAS into individuals from more diverse ancestry groups. The overall vision of this proposal is to develop novel statistical methods for the analysis of multi-ancestry GWAS that allow for the genetic differences observed across diverse population groups. These methods will be implemented into user-friendly software tools that will be shared with the wider research community to provide a better understanding of the impact on disease of genetic differences between population groups to reduce healthcare disparities. Improved knowledge of disease biology that is shared across diverse populations will inform treatment development opportunities that will be relevant to everyone. Furthermore, PRS that take account of the ancestry of an individual will provide more accurate prediction of disease risk, irrespective of their genetic background.

全基因组关联研究（GWAS）已成功地识别我们的DNA的变化，称为遗传变异，这有助于我们患上许多常见的人类疾病，包括那些具有重大公共健康负担的人，例如癌症，心血管疾病和糖尿病。这一成功提供了使用遗传学对人类健康产生重大积极影响的激动人心的机会： （ii）预测个人中疾病的未来发生，称为多基因风险评分（PRS）。然而，尽管取得了成功，但大多数GWA都在欧洲和北美的欧洲血统白人人群中进行。 GWAS中的这种偏见与许多疾病的全球和种族/种族分布形成鲜明对比，因此可能加剧医疗保健差异，因为来自白人欧洲血统个体的遗传发现不太可能在其他人群中产生影响。例如，在其他人群群体中可能不会观察到引起欧洲白人血统疾病的遗传变异。因此，源自欧洲白人血统的PRS对非洲，亚洲或混合血统的个体提供了对疾病风险的可靠性较低的预测。遗传研究中人口偏见的担忧促使GWA最近扩展到来自更多样化的祖先的个体。该提案的总体视野是开发新的统计方法，用于分析多功能GWAS，从而允许在不同人群群体中观察到的遗传差异。这些方法将被实施到用户友好的软件工具中，这些软件工具将与更广泛的研究社区共享，以更好地了解对人群群体之间遗传差异疾病的影响，以减少医疗保健差异。在各种各样的人群中共享的疾病生物学知识的提高将为治疗发展机会提供与每个人有关的机会。此外，考虑到个体的血统的PR将提供更准确的疾病风险预测，无论其遗传背景如何。

项目成果

Leveraging information between multiple population groups and traits improves fine-mapping resolution.

• DOI: 10.1038/s41467-023-43159-5
• 发表时间: 2023-11-10
• 期刊: NATURE COMMUNICATIONS
• 影响因子: 16.6
• 作者: Zhou, Feng;Soremekun, Opeyemi;Chikowore, Tinashe;Fatumo, Segun;Barroso, Ines;Morris, Andrew P;Asimit, Jennifer L
• 通讯作者: Asimit, Jennifer L