Modeling of horizontal pleiotropy identifies possible causal gene expression in systemic lupus erythematosus.

Frontiers in lupus Pub Date : 2023-01-01 Epub Date: 2023-10-03 DOI:10.3389/flupu.2023.1234578
Iouri Chepelev, Isaac T W Harley, John B Harley
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Abstract

Background: Systemic lupus erythematosus (SLE) is a chronic autoimmune condition with complex causes involving genetic and environmental factors. While genome-wide association studies (GWASs) have identified genetic loci associated with SLE, the functional genomic elements responsible for disease development remain largely unknown. Mendelian Randomization (MR) is an instrumental variable approach to causal inference based on data from observational studies, where genetic variants are employed as instrumental variables (IVs).

Methods: This study utilized a two-step strategy to identify causal genes for SLE. In the first step, the classical MR method was employed, assuming the absence of horizontal pleiotropy, to estimate the causal effect of gene expression on SLE. In the second step, advanced probabilistic MR methods (PMR-Egger, MRAID, and MR-MtRobin) were applied to the genes identified in the first step, considering horizontal pleiotropy, to filter out false positives. PMR-Egger and MRAID analyses utilized whole blood expression quantitative trait loci (eQTL) and SLE GWAS summary data, while MR-MtRobin analysis used an independent eQTL dataset from multiple immune cell types along with the same SLE GWAS data.

Results: The initial MR analysis identified 142 genes, including 43 outside of chromosome 6. Subsequently, applying the advanced MR methods reduced the number of genes with significant causal effects on SLE to 66. PMR-Egger, MRAID, and MR-MtRobin, respectively, identified 13, 7, and 16 non-chromosome 6 genes with significant causal effects. All methods identified expression of PHRF1 gene as causal for SLE. A comprehensive literature review was conducted to enhance understanding of the functional roles and mechanisms of the identified genes in SLE development.

Conclusions: The findings from the three MR methods exhibited overlapping genes with causal effects on SLE, demonstrating consistent results. However, each method also uncovered unique genes due to different modelling assumptions and technical factors, highlighting the complementary nature of the approaches. Importantly, MRAID demonstrated a reduced percentage of causal genes from the Major Histocompatibility complex (MHC) region on chromosome 6, indicating its potential in minimizing false positive findings. This study contributes to unraveling the mechanisms underlying SLE by employing advanced probabilistic MR methods to identify causal genes, thereby enhancing our understanding of SLE pathogenesis.

水平多效性建模确定了系统性红斑狼疮中可能的致病基因表达。
背景:系统性红斑狼疮(SLE)是一种慢性自身免疫性疾病,病因复杂,涉及遗传和环境因素。虽然全基因组关联研究(GWAS)已经确定了与SLE相关的遗传基因座,但负责疾病发展的功能基因组元件在很大程度上仍然未知。孟德尔随机化(MR)是一种基于观察性研究数据进行因果推断的工具变量方法,其中遗传变异被用作工具变量。方法:本研究采用两步策略来识别SLE的因果基因。在第一步中,假设不存在水平多效性,采用经典的MR方法来估计基因表达对SLE的因果影响。在第二步中,考虑到水平多效性,将先进的概率MR方法(PMR-Egger、MRAID和MR-MtRobin)应用于第一步中鉴定的基因,以过滤假阳性。PMR-Egger和MRAID分析使用全血表达定量性状基因座(eQTL)和SLE GWAS汇总数据,而MR-MtRobin分析使用来自多种免疫细胞类型的独立eQTL数据集以及相同的SLE GWAS数据。结果:初步MR分析鉴定出142个基因,其中43个位于6号染色体外。随后,应用先进的MR方法将对SLE具有显著因果影响的基因数量减少到66个。PMR-Egger、MRAID和MR-MtRobin分别鉴定了13个、7个和16个具有显著因果效应的非6号染色体基因。所有方法都确定PHRF1基因的表达是SLE的病因。进行了一项全面的文献综述,以增进对已鉴定基因在SLE发展中的功能作用和机制的理解。结论:三种MR方法的结果显示出对SLE具有因果影响的基因重叠,结果一致。然而,由于不同的建模假设和技术因素,每种方法都发现了独特的基因,突出了这些方法的互补性。重要的是,MRAID证明了来自6号染色体主要组织相容性复合体(MHC)区域的致病基因的百分比降低,这表明它有可能最大限度地减少假阳性结果。本研究通过采用先进的概率MR方法来识别致病基因,从而有助于揭示SLE的发病机制,从而增强我们对SLE发病机制的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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