Premium
Interaction analysis of the CBLB and CTLA4 genes in type 1 diabetes
Author(s) -
Payne Felicity,
Cooper Jason D.,
Walker Neil M.,
Lam Alex C.,
Smink Luc J.,
Nutland Sarah,
Stevens Helen E.,
Hutchings Jayne,
Todd John A.
Publication year - 2007
Publication title -
journal of leukocyte biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.819
H-Index - 191
eISSN - 1938-3673
pISSN - 0741-5400
DOI - 10.1189/jlb.0906577
Subject(s) - biology , gene , type (biology) , type 2 diabetes , type 1 diabetes , genetics , microbiology and biotechnology , diabetes mellitus , endocrinology , ecology
Gene‐gene interaction analyses have been suggested as a potential strategy to help identify common disease susceptibility genes. Recently, evidence of a statistical interaction between polymorphisms in two negative immunoregulatory genes, CBLB and CTLA4 , has been reported in type 1 diabetes (T1D). This study, in 480 Danish families, reported an association between T1D and a synonymous coding SNP in exon 12 of the CBLB gene (rs3772534 G>A; minor allele frequency, MAF=0.24; derived relative risk, RR for G allele=1.78; P =0.046). Furthermore, evidence of a statistical interaction with the known T1D susceptibility‐associated CTLA4 polymorphism rs3087243 (laboratory name CT60, G>A) was reported ( P <0.0001), such that the CBLB SNP rs3772534 G allele was overtransmitted to offspring with the CTLA4 rs3087243 G/G genotype. We have, therefore, attempted to obtain additional support for this finding in both large family and case‐control collections. In a primary analysis, no evidence for an association of the CBLB SNP rs3772534 with disease was found in either sample set (2162 parent‐child trios, P =0.33; 3453 cases and 3655 controls, P =0.69). In the case‐only statistical interaction analysis between rs3772534 and rs3087243, there was also no support for an effect (1994 T1D affected offspring, and 3215 cases, P =0.92). These data highlight the need for large, well‐characterized populations, offering the possibility of obtaining additional support for initial observations owing to the low prior probability of identifying reproducible evidence of gene‐gene interactions in the analysis of common disease‐associated variants in human populations.