Sophia Kerns, Katherine A. Owen, Dana Schwalbe, Amrie C. Grammer, Peter E. Lipsky
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引用次数: 0
摘要
系统性红斑狼疮(SLE)是一种自身免疫性疾病,表现多种多样,包括神经和精神症状。与许多其他疾病相比,系统性红斑狼疮的遗传关联研究因样本量不足和研究能力有限而受到阻碍。多发性硬化症(MS)是一种慢性复发性中枢神经系统(CNS)自身免疫性疾病,也表现出神经和免疫学特征。在此,我们确定了一种利用多发性硬化症的大规模基因组广泛关联研究(GWAS)来确定系统性红斑狼疮新遗传风险位点的方法。统计遗传比较方法包括用于识别疾病病理生理学中遗传重叠的连锁不平衡评分回归(LDSC)和交叉表型关联分析(CPASSOC)、用于识别因果关联的传统双样本和新型基于PPI的泯灭随机化以及贝叶斯共定位,这些方法被应用于在多发性硬化症中进行的关联研究,以促进在较小、较有限的系统性红斑狼疮数据集中进行发现。利用 SNP 对基因映射进行的通路分析确定了由分子通路组成的生物网络,这些分子通路对系统性红斑狼疮的中枢神经系统疾病具有因果影响,同时也确定了可能对这两种病症都有影响的通路,从而为治疗方法的选择提供了重要依据。
Examination of the shared genetic architecture between multiple sclerosis and systemic lupus erythematosus facilitates discovery of novel lupus risk loci
Systemic Lupus Erythematosus (SLE) is an autoimmune disease with heterogeneous manifestations, including neurological and psychiatric symptoms. Genetic association studies in SLE have been hampered by insufficient sample size and limited power compared to many other diseases. Multiple Sclerosis (MS) is a chronic relapsing autoimmune disease of the central nervous system (CNS) that also manifests neurological and immunological features. Here, we identify a method of leveraging large-scale genome wide association studies (GWAS) in MS to identify novel genetic risk loci in SLE. Statistical genetic comparison methods including linkage disequilibrium score regression (LDSC) and cross-phenotype association analysis (CPASSOC) to identify genetic overlap in disease pathophysiology, traditional 2-sample and novel PPI-based mendelian randomization to identify causal associations and Bayesian colocalization were applied to association studies conducted in MS to facilitate discovery in the smaller, more limited datasets available for SLE. Pathway analysis using SNP-to-gene mapping identified biological networks composed of molecular pathways with causal implications for CNS disease in SLE specifically, as well as pathways likely causal of both pathologies, providing key insights for therapeutic selection.
期刊介绍:
Human Genetics is a monthly journal publishing original and timely articles on all aspects of human genetics. The Journal particularly welcomes articles in the areas of Behavioral genetics, Bioinformatics, Cancer genetics and genomics, Cytogenetics, Developmental genetics, Disease association studies, Dysmorphology, ELSI (ethical, legal and social issues), Evolutionary genetics, Gene expression, Gene structure and organization, Genetics of complex diseases and epistatic interactions, Genetic epidemiology, Genome biology, Genome structure and organization, Genotype-phenotype relationships, Human Genomics, Immunogenetics and genomics, Linkage analysis and genetic mapping, Methods in Statistical Genetics, Molecular diagnostics, Mutation detection and analysis, Neurogenetics, Physical mapping and Population Genetics. Articles reporting animal models relevant to human biology or disease are also welcome. Preference will be given to those articles which address clinically relevant questions or which provide new insights into human biology.
Unless reporting entirely novel and unusual aspects of a topic, clinical case reports, cytogenetic case reports, papers on descriptive population genetics, articles dealing with the frequency of polymorphisms or additional mutations within genes in which numerous lesions have already been described, and papers that report meta-analyses of previously published datasets will normally not be accepted.
The Journal typically will not consider for publication manuscripts that report merely the isolation, map position, structure, and tissue expression profile of a gene of unknown function unless the gene is of particular interest or is a candidate gene involved in a human trait or disorder.