近日，德国慕尼黑工业大学Na Cai等研究人员合作发现，表型整合可提高基于生物库的重度抑郁障碍基因研究的效率并保留特异性。2023年11月20日，《自然—遗传学》杂志在线发表了这项成果。

研究人员表示，生物库通常包含与重度抑郁障碍（MDD）等疾病相关的多种表型，这些表型具有部分不同的遗传结构。研究者们面临着浅表型（样本量大、特异性/敏感性低）和深表型（样本量小、特异性/敏感性高）之间的复杂权衡，而最佳选择往往并不明确。

研究人员建议整合这些表型，以兼顾每种表型的优点。研究人员使用表型归因法整合了数百种MDD相关表型的信息，从而显著提高了全基因组关联研究（GWAS）的能力和英国生物库中最深度MDD表型LifetimeMDD的多基因风险评分（PRS）预测准确性。研究人员利用一种基于PRS的新的多向性度量方法证明了估算在其遗传结构中保留了特异性。研究人员进一步发现，通过汇总统计进行整合也能提高GWAS能力和PRS预测，但会根据输入情况引入非特异性遗传效应。这项工作提供了一种简单、可扩展的方法，通过整合浅层和深层表型来改进大型生物库中的遗传研究。

附：英文原文

Title: Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder

Author: Dahl, Andrew, Thompson, Michael, An, Ulzee, Krebs, Morten, Appadurai, Vivek, Border, Richard, Bacanu, Silviu-Alin, Werge, Thomas, Flint, Jonathan, Schork, Andrew J., Sankararaman, Sriram, Kendler, Kenneth S., Cai, Na

Issue&Volume: 2023-11-20

Abstract: Biobanks often contain several phenotypes relevant to diseases such as major depressive disorder (MDD), with partly distinct genetic architectures. Researchers face complex tradeoffs between shallow (large sample size, low specificity/sensitivity) and deep (small sample size, high specificity/sensitivity) phenotypes, and the optimal choices are often unclear. Here we propose to integrate these phenotypes to combine the benefits of each. We use phenotype imputation to integrate information across hundreds of MDD-relevant phenotypes, which significantly increases genome-wide association study (GWAS) power and polygenic risk score (PRS) prediction accuracy of the deepest available MDD phenotype in UK Biobank, LifetimeMDD. We demonstrate that imputation preserves specificity in its genetic architecture using a novel PRS-based pleiotropy metric. We further find that integration via summary statistics also enhances GWAS power and PRS predictions, but can introduce nonspecific genetic effects depending on input. Our work provides a simple and scalable approach to improve genetic studies in large biobanks by integrating shallow and deep phenotypes.

DOI: 10.1038/s41588-023-01559-9

Source: https://www.nature.com/articles/s41588-023-01559-9