Baldrighi Giulia Nicole, Nova Andrea, Ekstrøm Claus Thorn, Piras Maria Luisa, Saddi Maria Valeria, Bernardinelli Luisa, Fazia Teresa
Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100, Pavia, Italy.
Department of Brain and Behavioral Sciences, University of Pavia, 27100, Pavia, Italy.
Biochem Genet. 2025 Aug 30. doi: 10.1007/s10528-025-11238-5.
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.
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。在本研究中，采用了一种基于家系的精细定位方法来分析142个三联体，旨在识别与MS相关的遗传变异。目标基因组区域位于17:30,820,506 - 32,483,270 bp（Ch37/hg19）内，其中包括蛋白质编码基因ASIC2，该基因先前与MS和其他神经疾病有关，其周围基因包含高度相关的遗传变异，以捕捉该区域更广泛的信号。鉴于撒丁岛MS的高患病率以及撒丁岛人群独特的遗传特征，包括较低的异质性和较长的连锁不平衡，我们专门在该人群中设计了研究，并专注于基于家系的数据，以增强检测遗传信号的能力，避免错误发现。基因型填充发现了2537个变异，然后使用敲除三联体方法进行分析，以识别与MS易感性相关的基因座。我们发现rs756787（MYO1D的3'UTR）增加了疾病风险（OR 1.57，95% CI [1.07 - 2.29]，p = 0.02），而rs56175840（ASIC2内含子）显示出保护作用（OR 0.17，95% CI [0.04 - 0.74]，p = 0.02），证明了基于敲除的精细定位在家系数据集中的效力。整合基于连锁不平衡的表达和性状分析有助于揭示rs756787与影响神经退行性变相关基因以及对爱泼斯坦 - 巴尔病毒免疫反应的变异之间的相关性，爱泼斯坦 - 巴尔病毒是一种已知的与MS发病机制有关的环境因素。我们的研究强调了基于敲除的精细定位与表达 - 性状整合相结合以识别影响撒丁岛人群MS风险的遗传变异的有效性。
