Prioritization of risk genes in multiple sclerosis by a refined Bayesian framework followed by tissue-specificity and cell type feature assessment.
Prioritization of risk genes in multiple sclerosis by a refined Bayesian framework followed by tissue-specificity and cell type feature assessment.
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通过完善的贝叶斯框架对多发性硬化症中的风险基因进行优先排序，然后进行组织特异性和细胞类型特征评估。
DOI：
10.1186/s12864-022-08580-y
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发表时间：
2022-05-11
期刊：
影响因子：
4.4
通讯作者：
中科院分区：
文献类型：
--
作者：
多发性硬化症(MS)是一种免疫介导的中枢神经系统衰弱疾病，影响全球200多万人，给家庭和整个社区带来沉重的负担。了解MS的遗传基础有助于破解MS的发病机制，为MS的治疗提供帮助。我们改进了最近开发的贝叶斯框架，集成风险基因选择器(IRIGS)，通过整合迄今最大的GWA(n = 115,803)、各种基因组特征和基因-基因相似性的汇总统计数据，对与MS相关的风险基因进行优先排序。我们通过贝叶斯框架确定了163个MS相关的优先风险基因(MS-PRGenes)。我们通过两样本孟德尔随机化(2SMR)方法，整合了19个组织的基因类型-组织表达(GTEx)和表达数量性状基因座(EQTL)的数据，复制了35个MS-PRGenes。我们证明了MS-PRGenes具有更多实质性的有害影响和疾病风险。此外，单细胞浓缩分析表明，在对照组中，MS-PRGenes在激活的巨噬细胞和小胶质细胞中比未激活的巨噬细胞更富集。生物和药物浓缩分析强调了炎症信号通路。综上所述，我们从不同的基因组、表观基因组、eQTL、单细胞和药物数据中预测和验证了一个高度可信的MS风险基因集。MS-PRGenes可以进一步作为MS Gwas风险基因的基准，用于未来的验证或遗传学研究。网上版载有补充材料，可在10.1186/s12864-022-08580-y查阅。
Multiple sclerosis (MS) is a debilitating immune-mediated disease of the central nervous system that affects over 2 million people worldwide, resulting in a heavy burden to families and entire communities. Understanding the genetic basis underlying MS could help decipher the pathogenesis and shed light on MS treatment. We refined a recently developed Bayesian framework, Integrative Risk Gene Selector (iRIGS), to prioritize risk genes associated with MS by integrating the summary statistics from the largest GWAS to date (n = 115,803), various genomic features, and gene–gene closeness. We identified 163 MS-associated prioritized risk genes (MS-PRGenes) through the Bayesian framework. We replicated 35 MS-PRGenes through two-sample Mendelian randomization (2SMR) approach by integrating data from GWAS and Genotype-Tissue Expression (GTEx) expression quantitative trait loci (eQTL) of 19 tissues. We demonstrated that MS-PRGenes had more substantial deleterious effects and disease risk. Moreover, single-cell enrichment analysis indicated MS-PRGenes were more enriched in activated macrophages and microglia macrophages than non-activated ones in control samples. Biological and drug enrichment analyses highlighted inflammatory signaling pathways. In summary, we predicted and validated a high-confidence MS risk gene set from diverse genomic, epigenomic, eQTL, single-cell, and drug data. The MS-PRGenes could further serve as a benchmark of MS GWAS risk genes for future validation or genetic studies. The online version contains supplementary material available at 10.1186/s12864-022-08580-y.
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影响因子：
64.8
作者：
GTEx Consortium;Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group;Statistical Methods groups—Analysis Working Group;Enhancing GTEx (eGTEx) groups;NIH Common Fund;NIH/NCI;NIH/NHGRI;NIH/NIMH;NIH/NIDA;Biospecimen Collection Source Site—NDRI;Biospecimen Collection Source Site—RPCI;Biospecimen Core Resource—VARI;Brain Bank Repository—University of Miami Brain Endowment Bank;Leidos Biomedical—Project Management;ELSI Study;Genome Browser Data Integration &Visualization—EBI;Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz;Lead analysts:;Laboratory, Data Analysis &Coordinating Center (LDACC):;NIH program management:;Biospecimen collection:;Pathology:;eQTL manuscript working group:;Battle A;Brown CD;Engelhardt BE;Montgomery SB
通讯作者：
Montgomery SB
影响因子：
30.8
作者：
Fulco, Charles P.;Nasser, Joseph;Engreitz, Jesse M.
通讯作者：
Engreitz, Jesse M.
影响因子：
3.4
作者：
Garcia, Catherine R.;Jayswal, Rani;Villano, John L.
通讯作者：
Villano, John L.
影响因子：
3.7
作者：
Dai, Yulin;Pei, Guangsheng;Jia, Peilin
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Jia, Peilin
IQGAP1：对分子木偶功能的洞察力。
影响因子：
3.6
作者：
Abel AM;Schuldt KM;Rajasekaran K;Hwang D;Riese MJ;Rao S;Thakar MS;Malarkannan S
通讯作者：
Malarkannan S