美国马萨诸塞州综合医院Hilary K. Finucane、Ran Cui和耶鲁大学Zhou Fan小组合作的最新研究提出，通过建模无限小效应来改进精细绘图。相关论文于2023年11月30日发表于国际学术期刊《自然—遗传学》杂志上。

研究人员引入了复制失败率（RFR），其是通过下采样评估精细绘图一致性的指标。SuSiE、FINEMAP和COJO-ABF显示出较高的RFR，表明它们的输出可能存在假阳性结果。模拟显示，非稀疏遗传结构会导致校准错误，而估算噪声、因果变异体的非均匀分布和质量控制过滤器的影响则微乎其微。

研究人员研发了SuSiE-inf和FINEMAP-inf，这是一种在较大-较小因果效应背景下模拟无限小效应的精细映射方法。该方法在校准、RFR、功能富集、竞争性召回和计算效率方面都有改进。值得注意的是，与SuSiE和FINEMAP相比，该方法的后效应大小明显提高了多基因风险评分的准确性。该研究工作改进了复杂性状的因果变异识别，并且因果变异识别是人类遗传学的一个基本问题。

据悉，精细绘图旨在确定产生表型的因果遗传变异。贝叶斯精细作图算法（如SuSiE、FINEMAP、ABF和COJO-ABF）应用广泛，但利用真实数据评估后验概率校准仍然具有挑战性，因为真实数据中可能存在模型错误，而且真正的因果变异是未知的。

附：英文原文

Title: Improving fine-mapping by modeling infinitesimal effects

Author: Cui, Ran, Elzur, Roy A., Kanai, Masahiro, Ulirsch, Jacob C., Weissbrod, Omer, Daly, Mark J., Neale, Benjamin M., Fan, Zhou, Finucane, Hilary K.

Issue&Volume: 2023-11-30

Abstract: Fine-mapping aims to identify causal genetic variants for phenotypes. Bayesian fine-mapping algorithms (for example, SuSiE, FINEMAP, ABF and COJO-ABF) are widely used, but assessing posterior probability calibration remains challenging in real data, where model misspecification probably exists, and true causal variants are unknown. We introduce replication failure rate (RFR), a metric to assess fine-mapping consistency by downsampling. SuSiE, FINEMAP and COJO-ABF show high RFR, indicating potential overconfidence in their output. Simulations reveal that nonsparse genetic architecture can lead to miscalibration, while imputation noise, nonuniform distribution of causal variants and quality control filters have minimal impact. Here we present SuSiE-inf and FINEMAP-inf, fine-mapping methods modeling infinitesimal effects alongside fewer larger causal effects. Our methods show improved calibration, RFR and functional enrichment, competitive recall and computational efficiency. Notably, using our methods’ posterior effect sizes substantially increases polygenic risk score accuracy over SuSiE and FINEMAP. Our work improves causal variant identification for complex traits, a fundamental goal of human genetics.

DOI: 10.1038/s41588-023-01597-3

Source: https://www.nature.com/articles/s41588-023-01597-3