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Hum Genet ; 143(5): 703-719, 2024 May.
Article in English | MEDLINE | ID: mdl-38609570

ABSTRACT

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.


Subject(s)
Genetic Predisposition to Disease , Lupus Erythematosus, Systemic , Multiple Sclerosis , Lupus Erythematosus, Systemic/genetics , Lupus Erythematosus, Systemic/metabolism , Lupus Erythematosus, Systemic/physiopathology , Multiple Sclerosis/genetics , Multiple Sclerosis/metabolism , Multiple Sclerosis/physiopathology , Polymorphism, Single Nucleotide , Signal Transduction , Protein Interaction Maps , White People , Linkage Disequilibrium , Correlation of Data , Systems Biology/methods
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