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.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117 Int+J+Epidemiol
2016 ; 45
(3
): 728-40
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Meta-analysis of genome-wide association studies reveals genetic overlap between
Hodgkin lymphoma and multiple sclerosis
#MMPMID26971321
Khankhanian P
; Cozen W
; Himmelstein DS
; Madireddy L
; Din L
; van den Berg A
; Matsushita T
; Glaser SL
; Moré JM
; Smedby KE
; Baranzini SE
; Mack TM
; Lizée A
; de Sanjosé S
; Gourraud PA
; Nieters A
; Hauser SL
; Cocco P
; Maynadié M
; Foretová L
; Staines A
; Delahaye-Sourdeix M
; Li D
; Bhatia S
; Melbye M
; Onel K
; Jarrett R
; McKay JD
; Oksenberg JR
; Hjalgrim H
Int J Epidemiol
2016[Jun]; 45
(3
): 728-40
PMID26971321
show ga
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.