Possible association of CD3 and CD4 polymorphisms with insulin-dependent diabetes mellitus (IDDM)

Ghabanbasani, M. Zamani; Buyse, Inge M.; Legius, Eric; Decorte, Ronny; Marynen, Peter; Bouillon, Roger; Cassiman, Jean‐Jacques

doi:10.1111/j.1365-2249.1994.tb06119.x

Cited by 12 publications

(6 citation statements)

References 23 publications

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“…The individual alleles however showed no association. This finding contrasts with the observation that a similar association was not found in IDDM but in IDDM the CD4*A4/A4 genotype showed association (Zamani Ghabanbasani et al 1994a) .…”

Section: Discussioncontrasting

confidence: 87%

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Increased and decreased relative risk for noninsulin‐dependent diabetes mellitus conferred by HLA class II and by CD4 alleles

et al. 1995

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Non‐insulin‐dependent diabetes mellitus has been recognized to be heterogeneous in etiology, with multiple subgroups. Several genes or chromosomal regions have been implicated in the development of the disease. In this study the association of HLA class II alleles and genotypes and the association of CD4 and CD3 polymorphisms were assessed in a large number of Belgian non‐insulin‐dependent diabetes mellitus patients. Furthermore, the importance of the DQα***Arg52/DQαlArg52 and the DQβlAsp57/DQβlAsp57 genotypes and the combination of both genotypes were examined. Our results show that in the HLA class II genes only the DQαlArg52+/DQαlArg52+ genotype was significantly associated with non‐insulin‐dependent diabetes mellitus compared with controls (p=0.011, RR=2.02). We also observed that the frequency of the CD4*A4/*A8 genotype and the CD4*A7 allele was significantly increased and decreased respectively in non‐insulin‐dependent diabetes mellitus patients as compared with the controls (p=0.018, RR=2.16 and p=0.0003, RR=0.49 respectively). These results therefore suggest that HLA class II and CD4 genes might independently contribute to the susceptibility for non‐insulin‐dependent diabetes mellitus and that these alleles and genotypes might identify subgroups of patients with different susceptibilities.

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Section: Discussioncontrasting

confidence: 87%

“…In a study of insulin-dependent diabetes mellitus patients we previously found a significant association with particular CD3 and CD4 alleles (Zamani Ghabanbasani et al 1994a). In the present study the association of HLA class I1 DQAI, DQB1, DRB1, DRB3, DRB4, DRB5 and DPB1, as well as CD4 and CD3 polymorphisms were assessed in a large number of NIDDM patients.…”

mentioning

confidence: 96%

Increased and decreased relative risk for noninsulin‐dependent diabetes mellitus conferred by HLA class II and by CD4 alleles

et al. 1995

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“…Subnetwork A ( Figure 5A) and B ( Figure 5B) included quite a number of previously reported T2D-related genes: Tcf4 and Dcc [32]; Cd3d [33], Uts2r [34] and Map2k1 [35]. Subnetwork C ( Figure 5C) was the largest reversed DCL-organized module and it contained an interesting four-gene-circuit (including Arpc5l, Tra1, Mcm3ap, and Hspe1) of consistent negative-topositive correlation reversal.…”

Section: Re-analyzing a T2d Dataset From The Perspective Of Differentmentioning

confidence: 74%

RSEM: Accurate Transcript Quantification from RNA-Seq Data With or Without a Reference Genome

2014

Bioinformatics

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Background: Differential coexpression analysis (DCEA) is increasingly used for investigating the global transcriptional mechanisms underlying phenotypic changes. Current DCEA methods mostly adopt a gene connectivity-based strategy to estimate differential coexpression, which is characterized by comparing the numbers of gene neighbors in different coexpression networks. Although it simplifies the calculation, this strategy mixes up the identities of different coexpression neighbors of a gene, and fails to differentiate significant differential coexpression changes from those trivial ones. Especially, the correlation-reversal is easily missed although it probably indicates remarkable biological significance. Results: We developed two link-based quantitative methods, DCp and DCe, to identify differentially coexpressed genes and gene pairs (links). Bearing the uniqueness of exploiting the quantitative coexpression change of each gene pair in the coexpression networks, both methods proved to be superior to currently popular methods in simulation studies. Re-mining of a publicly available type 2 diabetes (T2D) expression dataset from the perspective of differential coexpression analysis led to additional discoveries than those from differential expression analysis. Conclusions: This work pointed out the critical weakness of current popular DCEA methods, and proposed two link-based DCEA algorithms that will make contribution to the development of DCEA and help extend it to a broader spectrum.

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“…Although CD4 rs11064392 has not been investigated for its functional significance, another linked variant in promoter ( CD4 − 181C > G (rs2855534); D’=1.0 and r 2 =0.38 with rs11064392: calculated using HapMap data) was reported to affect stimulated promoter activity in vitro [21]. In addition, SNPs other than rs11064392 or a pyrimidine-rich pentanucleotide repeat polymorphism (CD4-1188 (TTTTC)) in enhancer/promoter region have been reported to be associated with autoimmune diseases (i.e., rheumatoid arthritis, systemic lupus erythematosus, and vitiligo) [22,23], multiple sclerosis that is a T-cell mediated disease of the central nervous system [24], and insulin-dependent diabetes mellitus (IDDM) [25]. It is also noteworthy that recent reports have shown that a non-synonymous SNP ( CD4 Trp240Arg), common among individuals of African descent but non-polymorphic among Caucasian, influence human immunodeficiency virus (HIV-1) infection risk [26,27].…”

Section: Discussionmentioning

confidence: 99%

Common single nucleotide polymorphisms in immunoregulatory genes and multiple myeloma risk among women in Connecticut

et al. 2010

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In light of the relationship between immune system dysregulation and multiple myeloma (MM) risk, we investigated whether genetic variation in 92 immune function genes among 77 gene regions are associated with MM susceptibility in a population-based case-control study (108 cases and 482 controls) conducted among Caucasian women in Connecticut. Tagging single-nucleotide polymorphisms (SNPs; N 5 870) were selected using a pairwise linkage-disequilibrium based algorithm. Odds ratios (ORs) and 95% confidence intervals (CIs) for SNP genotypes were estimated using unconditional logistic regression. Tests of association for gene regions were conducted using the minP test. We applied the false discovery rate (FDR) method to the minP test results as a means of controlling for multiple comparisons. The CD4 gene region located on 12p13-q13 (minP 5 0.0009), had an FDR value <0.1. In this region, a total of six tag SNPs in two genes (CD4 and LAG3) were significantly associated with MM risk (P trend <0.05), with the strongest association observed for the CD4 variant rs11064392 (OR AG/GG 5 2.53, 95% CI 5 1.59-4.02). Our findings suggest that genetic variation in CD4 may influence susceptibility to MM. Additional studies are needed to replicate these findings and, more generally, to explore the manner in which genes and receptors may influence the pathogenesis of this poorly understood malignancy. Am. J. Hematol. 85:560-563, 2010. V

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Possible association of CD3 and CD4 polymorphisms with insulin-dependent diabetes mellitus (IDDM)

Cited by 12 publications

References 23 publications

Increased and decreased relative risk for noninsulin‐dependent diabetes mellitus conferred by HLA class II and by CD4 alleles

Increased and decreased relative risk for noninsulin‐dependent diabetes mellitus conferred by HLA class II and by CD4 alleles

RSEM: Accurate Transcript Quantification from RNA-Seq Data With or Without a Reference Genome

Common single nucleotide polymorphisms in immunoregulatory genes and multiple myeloma risk among women in Connecticut

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