遺伝子データの多様化で心臓の健康増進を図る(Improving heart health by diversifying genetic data)

ペンシルベニア州立大学の統計学者が、一般に知られていないグループから遺伝データを収集し、複雑なデータを最大限に活用するための統計手法を改良しています。 Penn State statistician helps gather genetic data from underrepresented groups and improve statistical methods to make the most of the complex data.

2023-02-01 ペンシルベニア州立大学(PennState)

<関連情報>

• https://www.psu.edu/news/eberly-college-science/story/improving-heart-health-diversifying-genetic-data/
• https://www.nature.com/articles/s41591-022-01891-3
• https://www.nature.com/articles/s41586-021-04064-3

遺伝的に多様な集団における冠動脈疾患の大規模ゲノムワイド関連研究 Large-scale genome-wide association study of coronary artery disease in genetically diverse populations

Catherine Tcheandjieu, Xiang Zhu, Austin T. Hilliard, Shoa L. Clarke, Valerio Napolioni, Shining Ma, Kyung Min Lee, Huaying Fang, Fei Chen, Yingchang Lu, Noah L. Tsao, Sridharan Raghavan, Satoshi Koyama, Bryan R. Gorman, Marijana Vujkovic, Derek Klarin, Michael G. Levin, Nasa Sinnott-Armstrong, Genevieve L. Wojcik, Mary E. Plomondon, Thomas M. Maddox, Stephen W. Waldo, Alexander G. Bick, Saiju Pyarajan, Regeneron Genetics Center, CARDIoGRAMplusC4D Consortium, Biobank Japan, Million Veteran Program, …Themistocles L. Assimes
Nature Medicine  Published:01 August 2022
DOI:https://doi.org/10.1038/s41591-022-01891-3

Abstract

We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD.

脂質のゲノムワイド関連研究における遺伝的多様性の威力 The power of genetic diversity in genome-wide association studies of lipids

Sarah E. Graham, Shoa L. Clarke, Kuan-Han H. Wu, Stavroula Kanoni, Greg J. M. Zajac, Shweta Ramdas, Ida Surakka, Ioanna Ntalla, Sailaja Vedantam, Thomas W. Winkler, Adam E. Locke, Eirini Marouli, Mi Yeong Hwang, Sohee Han, Akira Narita, Ananyo Choudhury, Amy R. Bentley, Kenneth Ekoru, Anurag Verma, Bhavi Trivedi, Hilary C. Martin, Karen A. Hunt, Qin Hui, Derek Klarin, VA Million Veteran Program, Global Lipids Genetics Consortium*, …Cristen J. Willer
Nature  Published:09 December 2021
DOI:https://doi.org/10.1038/s41586-021-04064-3

Abstract

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use¹. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels², heart disease remains the leading cause of death worldwide³. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS^{4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23} have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns²⁴. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine²⁵, we anticipate that increased diversity of participants will lead to more accurate and equitable²⁶ application of polygenic scores in clinical practice.