Single-nucleotide Polymorphism and Haplotypes of TNIP1 Associated with Systemic Lupus Erythematosus in a Chinese Han Population
Bibliographic record
Abstract
OBJECTIVE: To determine the association of systemic lupus erythematosus (SLE) with single-nucleotide polymorphisms (SNP) in the TNIP1 gene and compare the expression of this gene in cases and controls from a Chinese Han population in this replication study. METHODS: Matrix-assisted laser desorption ionization time-of-flight mass spectrometry was used to genotype 19 SNP in TNIP1 in Chinese Han patients with SLE (n = 341) and controls (n = 356). Genotypes were analyzed by codominant, dominant, and recessive models. Analysis of allele frequencies and linkage disequilibrium was also performed. Western blotting and qRT-PCR were used to measure the expression of these genes in peripheral blood mononuclear cells of SLE cases and controls. RESULTS: Seven SNP loci were significantly associated with SLE in our population (p < 0.05 for all comparisons). Two TNIP1 gene haplotypes (ATTGCGC and GTCCTAT) were associated with SLE (p = 0.0246 and p = 0.0024, respectively). Western blotting and qRT-PCR results provide evidence that patients with SLE had significantly reduced expression of TNIP1/ABIN-1 relative to controls. CONCLUSION: Analysis of SNP in the TNIP1 gene and expression of this gene in peripheral blood lymphocytes indicated these SNP were associated with the occurrence of SLE in Han Chinese patients. Future studies should examine the roles of these SNP in the pathogenesis of SLE.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".