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Meta-analysis of genome-wide association studies reveals genetic overlap between Hodgkin lymphoma and multiple sclerosis

Background : Based on epidemiological commonalities, multiple sclerosis (MS) and Hodgkin lymphoma (HL), two clinically distinct conditions, have long been suspected to be aetiologically related. MS and HL occur in roughly the same age groups, both are associated with Epstein-Barr virus infection and...

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Detalles Bibliográficos
Autores principales: Khankhanian, Pouya, Cozen, Wendy, Himmelstein, Daniel S, Madireddy, Lohith, Din, Lennox, van den Berg, Anke, Matsushita, Takuya, Glaser, Sally L, Moré, Jayaji M, Smedby, Karin E., Baranzini, Sergio E, Mack, Thomas M, Lizée, Antoine, de Sanjosé, Silvia, Gourraud, Pierre-Antoine, Nieters, Alexandra, Hauser, Stephen L, Cocco, Pierluigi, Maynadié, Marc, Foretová, Lenka, Staines, Anthony, Delahaye-Sourdeix, Manon, Li, Dalin, Bhatia, Smita, Melbye, Mads, Onel, Kenan, Jarrett, Ruth, McKay, James D, Oksenberg, Jorge R, Hjalgrim, Henrik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5005944/
https://www.ncbi.nlm.nih.gov/pubmed/26971321
http://dx.doi.org/10.1093/ije/dyv364
Descripción
Sumario:Background : Based on epidemiological commonalities, multiple sclerosis (MS) and Hodgkin lymphoma (HL), two clinically distinct conditions, have long been suspected to be aetiologically related. MS and HL occur in roughly the same age groups, both are associated with Epstein-Barr virus infection and ultraviolet (UV) light exposure, and they cluster mutually in families (though not in individuals). We speculated if in addition to sharing environmental risk factors, MS and HL were also genetically related. Using data from genome-wide association studies (GWAS) of 1816 HL patients, 9772 MS patients and 25 255 controls, we therefore investigated the genetic overlap between the two diseases. Methods: From among a common denominator of 404 K single nucleotide polymorphisms (SNPs) studied, we identified SNPs and human leukocyte antigen (HLA) alleles independently associated with both diseases. Next, we assessed the cumulative genome-wide effect of MS-associated SNPs on HL and of HL-associated SNPs on MS. To provide an interpretational frame of reference, we used data from published GWAS to create a genetic network of diseases within which we analysed proximity of HL and MS to autoimmune diseases and haematological and non-haematological malignancies. Results: SNP analyses revealed genome-wide overlap between HL and MS, most prominently in the HLA region. Polygenic HL risk scores explained 4.44% of HL risk (Nagelkerke R (2) ), but also 2.36% of MS risk. Conversely, polygenic MS risk scores explained 8.08% of MS risk and 1.94% of HL risk. In the genetic disease network, HL was closer to autoimmune diseases than to solid cancers. Conclusions: HL displays considerable genetic overlap with MS and other autoimmune diseases.