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

Abstract

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.

Genetic overlap between autoimmune diseases and non‐Hodgkin lymphoma subtypes

“…The mean proximity between NHLs and ADs was compared to the mean proximity between NHLs and solid cancers with the Fisher test. Similarly, the mean proximity between NHL and solid cancers was compared to the mean proximity between NHL and all other diseases (Khankhanian et al, 2016;Himmelstein et al, 2015). Figure 1 gives an overview of study design and data analysis.…”

“…In this regard, the current understanding of environmental risk factors possibly shared by ADs and NHLs, such as smoking, offers no convincing explanation for their mutual clustering (Cerhan et al, 2017;Deane et al, 2010;Kang et al, 2010;Belbasis, Bellou, Evangelou, Ioannidis, & Tzoulaki, 2015;Smedby & Ponzoni, 2017;Ekström et al, 2003;Bernatsky et al, 2013). Further, meta-analyses of genome-wide association studies (GWAS) suggested genetic overlap between SLE and diffuse large B-cell lymphoma (DLBCL; Bernatsky et al, 2017), and between multiple sclerosis (MS) and Hodgkin lymphoma (Khankhanian et al, 2016) as a partial explanation of the accumulation of those two diseases among relatives.…”

Genome-wide association study implicates immune dysfunction in the development of Hodgkin lymphoma

“…In addition to analyzing data from these 3 GWAS, we made use of preprocessed association test statistics for HL risk from a meta-analysis of 3 additional GWAS (USC-IARC-UC-GWAS) comprising 1816 HL cases and 7879 control individuals, 12,25,26 and an analysis of 432 HL cases and 337 208 unaffected individuals 13 from the UK Biobank, accessed through the Global Biobank Engine.…”

“…We analyzed summary level GWAS data generated on HL cases and controls of European ancestry 11 from 3 sources (supplemental Tables 1-4): 2 GWAS of UK cases and controls and 1 GWAS of German cases and controls, totaling 3077 cases and 14 546 control patients (Discovery GWAS) 11 ; the Stanford Global Biobank Engine, an analysis of 432 HL cases from the UK Biobank 13 ; and a meta-analysis of 3 published HL GWAS totaling 1816 HL cases and 7879 control patients (USC-IARC-UC-GWAS). 12,25,26 In a meta-analysis of data from the 7 studies, we identified new genome-wide significant associations for HL ( Figure 1; Table 1) at 6p21.31 (rs649775; P 5 2.11 3 10 210 , marking ITPR3-UQCC2-IP6K3), 6q23.3 (rs1002658; P 5 2.97 3 10 28 , marking OLIG3-TNFAIP3), 11q23.1 (rs7111520; P 5 1.44 3 10 211 , marking POU2AF1), 16p11.2 (rs6565176; P 5 4.00 3 10 28 , marking MAPK3-CORO1A), and 20q13.13 (rs2425752; P 5 2.01 3 10 28 , marking NCOA5-CD40). In addition, we identified a promising association at 1p13.2 (rs2476601; P 5 4.20 3 10 27 , marking PTPN22).…”

Viruses and endogenous retroviruses in multiple sclerosis: From correlation to causation

“…22 It is also mechanistically intriguing how EBV plays a role in both cancer-a disorder of cellular proliferation-and MS-a disease characterized by neuronal cell death; however, recent reports of a genetic overlap between the EBV-related Hodgkin lymphoma and MS could shed some light on this. 53,54 In parallel, dogma that EBV cannot possibly be found in glial cells or neurons, the host immune response must remain the focus of studies, 53 or that EBV latency status underpins virus-mediated pathogenesis 24 should be re-examined in the light of recent observations that EBV can cause lytic infection in human primary neurons. 55 To summarize, in the context of discordance between the high rates of EBV infection vs low rates of MS worldwide, EBV is likely to be necessary but not sufficient to cause MS. 19 Future studies on shared polygenic risk from genomewide association studies on MS cases with those with markers of increased EBV levels (eg EBNA-1 56 ) are likely to shed further light on such host-pathogen interactions.…”