挪威奥斯陆大学Oleksandr Frei课题组利用包涵生物特异性基因集的GSA-MiXeR，改进了复杂性状遗传功能的定位。这一研究成果于2024年6月3日发表在国际学术期刊《自然-遗传学》上。

研究人员开发了用于基因组分析（GSA）的GSA-MiXeR分析工具，该工具拟合了单个基因的遗传率模型，考虑了变异间的连锁不平衡，并允许量化小基因组的分区遗传率和折合富集度。研究通过大量的模拟和敏感性分析对该方法进行了验证。

与标准的GSA方法相比，GSA-MiXeR在对包括精神分裂症在内的各种复杂性状和疾病分析时，优先选择了具有更高生物学特异性的基因集，这与精神分裂症的电压门控钙通道功能和多巴胺能信号转导有关。这类生物相关基因集通常只有不到十个基因，该方法能深入揭示复杂疾病的病理生物学，有利于发现潜在的药物靶点。

据了解，尽管全基因组关联研究在发现与人类复杂性状和疾病相关的基因组位点方面取得了突破性进展，但对这些研究结果进行生物学解释仍然具有挑战性。

附：英文原文

Title: Improved functional mapping of complex trait heritability with GSA-MiXeR implicates biologically specific gene sets

Author: Frei, Oleksandr, Hindley, Guy, Shadrin, Alexey A., van der Meer, Dennis, Akdeniz, Bayram C., Hagen, Espen, Cheng, Weiqiu, OConnell, Kevin S., Bahrami, Shahram, Parker, Nadine, Smeland, Olav B., Holland, Dominic, de Leeuw, Christiaan, Posthuma, Danielle, Andreassen, Ole A., Dale, Anders M.

Issue&Volume: 2024-06-03

Abstract: While genome-wide association studies are increasingly successful in discovering genomic loci associated with complex human traits and disorders, the biological interpretation of these findings remains challenging. Here we developed the GSA-MiXeR analytical tool for gene set analysis (GSA), which fits a model for the heritability of individual genes, accounting for linkage disequilibrium across variants and allowing the quantification of partitioned heritability and fold enrichment for small gene sets. We validated the method using extensive simulations and sensitivity analyses. When applied to a diverse selection of complex traits and disorders, including schizophrenia, GSA-MiXeR prioritizes gene sets with greater biological specificity compared to standard GSA approaches, implicating voltage-gated calcium channel function and dopaminergic signaling for schizophrenia. Such biologically relevant gene sets, often with fewer than ten genes, are more likely to provide insights into the pathobiology of complex diseases and highlight potential drug targets.

DOI: 10.1038/s41588-024-01771-1

Source: https://www.nature.com/articles/s41588-024-01771-1