Polymorphisms within the Protein Tyrosine Phosphatase 1B (PTPN1) Gene Promoter: Functional Characterization and Association with Type 2 Diabetes and Related Metabolic Traits
Bibliographic record
Abstract
BACKGROUND: Protein tyrosine phosphatase 1B (PTPN1) dephosphorylates insulin receptors and attenuates insulin signaling. Polymorphisms in the coding sequence of PTPN1 have been variably associated with type 2 diabetes (T2D). We hypothesized that variations within the PTPN1 promoter might contribute to the development of T2D and related metabolic traits. METHODS: We screened 2.0 kb of PTPN1 promoter in 174 T2D patients and 412 controls using PCR and denaturing HPLC. Association analysis was performed between diabetes and related traits and single-nucleotide polymorphism genotypes. We functionally tested 2 variants (-1023C>A and -51delA) by measuring their influence on luciferase activity in HepG2 cells and performing the electrophoretic mobility shift assay (EMSA). RESULTS: One common (-1023C>A) and 6 rare (-51delA, -451A>G, -467T>C, -1045G>A, -1286-3bp-del, and -1291-9bp-del) variants were identified in the PTPN1 promoter. The -1023(C) allele had significant association with T2D that disappeared after we adjusted for established diabetes risk factors. The alleles of -1023C>A and -51delA variants did not show significant effects on the biochemical markers after adjustment for established diabetes risk factors in the nondiabetic and diabetic groups separately. The -51delA variant decreased luciferase gene expression in HepG2 cells by 2-fold. EMSA revealed a weaker binding of -51delA to specific protein family proteins compared with the A allele. The -1023C>A variant had no influence in either experiment. CONCLUSIONS: The PTPN1 promoter variants -1023C>A and -51delA (which appears to be functional) were not associated with T2D or related traits in this study but must be investigated in a larger population to reveal any potential metabolic association.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".