复旦大学沈夏研究团队提出了一种改进的局部遗传相关分析框架。2025年3月10日，国际知名学术期刊《自然—遗传学》发表了这一成果。

在这里，小组将高清晰度似然（HDL）方法扩展到一个局部版本，HDL- l，它在小的，近似独立的连锁不平衡块中进行遗传相关分析。HDL-L允许对遗传方差和协方差进行更细粒度的估计。模拟结果表明，与LAVA相比，HDL-L提供了更一致的遗传力估计和更有效的遗传相关性估计。HDL-L在不同参数设置下进行的广泛模拟中展示了机器人的性能。在对来自UK Biobank的30种表型的分析中，HDL-L确定了109种显著的局部遗传相关性，并显示出显著的计算优势。HDL-L被证明是一个强大的工具，可以揭示复杂人类特征背后的详细基因景观，同时提供准确性和计算效率。

据介绍，遗传相关是复杂性状联合遗传模型中的一个关键参数，但通常是在全球基因组尺度上进行估计的。了解局部遗传相关性可以更详细地了解复杂性状的共享遗传结构。然而，最先进的工具，局部遗传相关分析，熔岩，是容易错误的推断。

附：英文原文

Title: An enhanced framework for local genetic correlation analysis

Author: Li, Yuying, Pawitan, Yudi, Shen, Xia

Issue&Volume: 2025-03-10

Abstract: Genetic correlation is a key parameter in the joint genetic model of complex traits, but it is usually estimated on a global genomic scale. Understanding local genetic correlations provides more detailed insight into the shared genetic architecture of complex traits. However, a state-of-the-art tool for local genetic correlation analysis, LAVA, is prone to false inference. Here we extend the high-definition likelihood (HDL) method to a local version, HDL-L, which performs genetic correlation analysis in small, approximately independent linkage disequilibrium blocks. HDL-L allows a more granular estimation of genetic variances and covariances. Simulations show that HDL-L offers more consistent heritability estimates and more efficient genetic correlation estimates compared with LAVA. HDL-L demonstrated robust performance across a wide range of simulations conducted under varying parameter settings. In the analysis of 30 phenotypes from the UK Biobank, HDL-L identified 109 significant local genetic correlations and showed a notable computational advantage. HDL-L proves to be a powerful tool for uncovering the detailed genetic landscape that underlies complex human traits, offering both accuracy and computational efficiency.

DOI: 10.1038/s41588-025-02123-3

Source: https://www.nature.com/articles/s41588-025-02123-3