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The sodium-dependent glucose cotransporter SLC5A11 as an autoimmune modifier gene in SLE.

Tissue Antigens. 2008 Feb;71(2):114-26. Epub 2007 Dec 06
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摘要


Genetic studies in several human autoimmune diseases suggest that the pericentromeric region of chromosome 16 might harbor an autoimmune modifier gene. We hypothesized that the sodium-dependent glucose cotransporter gene SLC5A11 is such a gene, and so might interact with immune-related genes. Herein, this hypothesis was tested in a genetic evaluation of the multiple gene effect in systemic lupus erythematosus (SLE). We used the case-control candidate gene association approach. Eight immune-related genes involved in inflammation and autoantibody generation and clear-up [interleukin 1 receptor antagonist (IL1RN), interleukin 1-beta (IL1-beta), tumor necrosis factor-alpha (TNF-alpha), lymphotoxin-alpha (LTA), tumor necrosis factor ligand superfamily, member 6 (TNFSF6), programmed cell death 1 (PDCD1), C2, and complement component 4 (C4)] were selected for study. Frequency of each candidate's genotype and allele between case and control were compared. Results were stratified by reanalyzing genotype data with relevant symptoms. Finally, improved computational data mining was used to analyze the phenotypes in a large data set. In the frequency analysis, only IL1-beta was significantly associated with SLE. Stratification analysis showed a significant association with SLE symptoms between SLC5A11 and the other immune-related genes, with the exceptions of TNFSF6 and C4. SLC5A11 was significantly associated with low C4 (as was TNF-alpha), anti-Smith antibody (anti-Sm) (as was C2), serositis, and alopecia. Finally, SLC5A11 interacted with PDCD1, TNF-alpha, LTA, and C4. After our study, we concluded that SLC5A11 is involved with some immune effects and interacts with immune-related gene(s), consistent with its function as an autoimmune modifier gene. Furthermore, SLC5A11 might induce apoptosis through the TNF-alpha, PDCD1 pathway. The present genotype-phenotype mapping approach should be applicable to genetic study of other complex diseases.

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