Giulia Nicole Baldrighi, Andrea Nova, Claus Thorn Ekstrøm, Maria Luisa Piras, Maria Valeria Saddi, Luisa Bernardinelli, Teresa Fazia
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Given the high prevalence of MS in Sardinia and the unique genetic characteristics of the Sardinian population, including reduced heterogeneity and extended linkage disequilibrium, we designed our study specifically within this population and focused on family-based data to enhance the power for detecting genetic signals, avoiding false discoveries. Genotype imputation found 2537 variants, which were then analyzed using the knockoff Trio method to identify loci associated with MS susceptibility. We found rs756787 (3'UTR of MYO1D) increased disease risk (OR 1.57, 95% CI [1.07-2.29], p = 0.02), while rs56175840 (intronic ASIC2) showed a protective effect (OR 0.17, 95% CI [0.04-0.74], p = 0.02), demonstrating the power of knockoff-based fine mapping in family datasets. Integrating LD-based expression and trait analyses helped reveal how rs756787 correlates with variants affecting genes involved in neurodegeneration and the immune response to Epstein-Barr virus, a known environmental factor implicated in MS pathogenesis. 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引用次数: 0
摘要
遗传易感性在自身免疫性疾病和复杂疾病如多发性硬化症(MS)中起着关键作用。然而,确定导致疾病易感性的特定变异或基因组区域仍然是一项重大挑战。在这项研究中,采用基于家族的精细定位方法分析了142个三联组,旨在确定与MS相关的相关遗传变异。目标基因组区域位于17:30,820,506-32,483,270 bp (Ch37/hg19),其中包括蛋白质编码基因ASIC2,该基因先前与MS和其他神经系统疾病有关,周围基因包含强相关的遗传变异,以捕获来自该区域的更广泛信号。考虑到MS在撒丁岛的高患病率和撒丁岛人群独特的遗传特征,包括减少异质性和扩大连锁不平衡,我们专门在这个人群中设计了我们的研究,并专注于基于家庭的数据,以增强检测遗传信号的能力,避免错误的发现。基因型插入发现2537个变异,然后使用仿制品Trio方法对其进行分析,以确定与MS易感性相关的位点。我们发现rs756787 (MYO1D的3'UTR)增加疾病风险(OR 1.57, 95% CI [1.07-2.29], p = 0.02),而rss56175840(内含子ASIC2)显示保护作用(OR 0.17, 95% CI [0.04-0.74], p = 0.02),证明了基于仿制品的精细定位在家族数据集中的力量。整合基于ld的表达和性状分析有助于揭示rs756787如何与影响神经变性和爱泼斯坦-巴尔病毒免疫反应的基因变异相关,爱泼斯坦-巴尔病毒是一种已知的与MS发病有关的环境因素。我们的研究强调了基于仿制品的精细定位结合表达-性状整合来识别撒丁岛人群中影响MS风险的遗传变异的有效性。
Knockoff-Based Fine Mapping of MS-Associated SNPs in Sardinian Trios.
Genetic predisposition plays a key role in autoimmune and complex diseases such as multiple sclerosis (MS). However, identifying the specific variants or genomic regions responsible for disease susceptibility remains a significant challenge. In this study a family-based fine mapping approach was applied to analyze 142 trios, aiming to identify associated genetic variants linked to MS. The targeted genomic region resides within the 17:30,820,506-32,483,270 bp (Ch37/hg19), which includes the protein-coding gene ASIC2, previously implicated in MS and other neurological conditions, with surrounding genes comprising strongly correlated genetic variants to capture the broader signal from the region. Given the high prevalence of MS in Sardinia and the unique genetic characteristics of the Sardinian population, including reduced heterogeneity and extended linkage disequilibrium, we designed our study specifically within this population and focused on family-based data to enhance the power for detecting genetic signals, avoiding false discoveries. Genotype imputation found 2537 variants, which were then analyzed using the knockoff Trio method to identify loci associated with MS susceptibility. We found rs756787 (3'UTR of MYO1D) increased disease risk (OR 1.57, 95% CI [1.07-2.29], p = 0.02), while rs56175840 (intronic ASIC2) showed a protective effect (OR 0.17, 95% CI [0.04-0.74], p = 0.02), demonstrating the power of knockoff-based fine mapping in family datasets. Integrating LD-based expression and trait analyses helped reveal how rs756787 correlates with variants affecting genes involved in neurodegeneration and the immune response to Epstein-Barr virus, a known environmental factor implicated in MS pathogenesis. Our study highlights the effectiveness of knockoff-based fine mapping combined with expression-trait integration to identify genetic variants influencing MS risk in the Sardinian population.
期刊介绍:
Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses.
Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication.
Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses.
Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods.
Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.