Suppr超能文献

美国的人口结构和药物基因组学风险分层。

Population structure and pharmacogenomic risk stratification in the United States.

机构信息

School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA.

PanAmerican Bioinformatics Institute, Cali, Colombia.

出版信息

BMC Biol. 2020 Oct 13;18(1):140. doi: 10.1186/s12915-020-00875-4.

Abstract

BACKGROUND

Pharmacogenomic (PGx) variants mediate how individuals respond to medication, and response differences among racial/ethnic groups have been attributed to patterns of PGx diversity. We hypothesized that genetic ancestry (GA) would provide higher resolution for stratifying PGx risk, since it serves as a more reliable surrogate for genetic diversity than self-identified race/ethnicity (SIRE), which includes a substantial social component. We analyzed a cohort of 8628 individuals from the United States (US), for whom we had both SIRE information and whole genome genotypes, with a focus on the three largest SIRE groups in the US: White, Black (African-American), and Hispanic (Latino). Our approach to the question of PGx risk stratification entailed the integration of two distinct methodologies: population genetics and evidence-based medicine. This integrated approach allowed us to consider the clinical implications for the observed patterns of PGx variation found within and between population groups.

RESULTS

Whole genome genotypes were used to characterize individuals' continental ancestry fractions-European, African, and Native American-and individuals were grouped according to their GA profiles. SIRE and GA groups were found to be highly concordant. Continental ancestry predicts individuals' SIRE with > 96% accuracy, and accordingly, GA provides only a marginal increase in resolution for PGx risk stratification. In light of the concordance between SIRE and GA, taken together with the fact that information on SIRE is readily available to clinicians, we evaluated PGx variation between SIRE groups to explore the potential clinical utility of race and ethnicity. PGx variants are highly diverged compared to the genomic background; 82 variants show significant frequency differences among SIRE groups, and genome-wide patterns of PGx variation are almost entirely concordant with SIRE. The vast majority of PGx variation is found within rather than between groups, a well-established fact for almost all genetic variants, which is often taken to argue against the clinical utility of population stratification. Nevertheless, analysis of highly differentiated PGx variants illustrates how SIRE partitions PGx variation based on groups' characteristic ancestry patterns. These cases underscore the extent to which SIRE carries clinically valuable information for stratifying PGx risk among populations, albeit with less utility for predicting individual-level PGx alleles (genotypes), supporting the concept of population pharmacogenomics.

CONCLUSIONS

Perhaps most interestingly, we show that individuals who identify as Black or Hispanic stand to gain far more from the consideration of race/ethnicity in treatment decisions than individuals from the majority White population.

摘要

背景

药物基因组学(PGx)变体介导个体对药物的反应,而不同种族/民族之间的反应差异归因于 PGx 多样性的模式。我们假设遗传血统(GA)将为分层 PGx 风险提供更高的分辨率,因为它是遗传多样性的更可靠替代,而自我认同的种族/民族(SIRE)则包含了大量的社会成分。我们分析了来自美国(US)的 8628 个人的队列,他们既有 SIRE 信息又有全基因组基因型,重点关注美国的三个最大的 SIRE 群体:白种人、黑种人(非裔美国人)和西班牙裔(拉丁裔)。我们对 PGx 风险分层问题的方法涉及两种截然不同的方法:群体遗传学和循证医学。这种综合方法使我们能够考虑到在人群内部和人群之间观察到的 PGx 变异模式的临床意义。

结果

全基因组基因型用于描述个体的大陆血统分数 - 欧洲、非洲和美洲原住民 - 并根据个体的 GA 特征对其进行分组。发现 SIRE 和 GA 群体高度一致。大陆血统以 > 96%的准确率预测个体的 SIRE,因此,GA 对 PGx 风险分层的分辨率只有微小的提高。鉴于 SIRE 和 GA 之间的一致性,再加上 SIRE 信息对临床医生来说是现成的,我们评估了 SIRE 组之间的 PGx 变异,以探索种族和民族的潜在临床效用。PGx 变体与基因组背景相比高度分化;82 个变体在 SIRE 组之间显示出显著的频率差异,全基因组的 PGx 变异模式几乎完全与 SIRE 一致。绝大多数 PGx 变异发生在群体内部,而不是群体之间,这是几乎所有遗传变体的既定事实,这通常被认为反对人群分层的临床效用。然而,对高度分化的 PGx 变体的分析说明了 SIRE 如何根据群体的特征血统模式来划分 PGx 变异。这些情况突出表明,尽管 SIRE 对预测个体水平的 PGx 等位基因(基因型)的效用较低,但它为人群中 PGx 风险分层提供了有临床价值的信息,支持群体药物基因组学的概念。

结论

也许最有趣的是,我们表明,自认为是黑人或西班牙裔的人在治疗决策中考虑种族/民族比来自多数白人人口的人获益更多。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/261c/7557099/c6bcced59e2a/12915_2020_875_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验