Association Study of <i>IRS1</i> Gene Polymorphisms with Type 2 Diabetes in South Indians
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The insulin receptor substrate-1 (IRS1) gene is a candidate gene for type 2 diabetes. The aim of this study was to investigate the association of the IRS1 gene polymorphisms Gly972Arg and Ala513Pro with type 2 diabetes in an Asian Indian population in south India. METHODS: A total of 2,148 subjects (1,187 normal glucose-tolerant [NGT] and 961 type 2 diabetes subjects) were randomly selected from the Chennai Urban Rural Epidemiology Study. The IRS1 gene polymorphisms Gly972Arg and Ala513Pro were genotyped in these subjects using polymerase chain reaction-restriction fragment length polymorphism, and a few variants were confirmed by direct sequencing. RESULTS: The frequency of the "A" allele of the Gly972Arg(G→A) single nucleotide polymorphism was similar between the NGT and diabetes subjects (2%). There was no significant difference in the genotypic frequency between the NGT and type 2 diabetes group (P = 0.25). When the study subjects were stratified based on body mass index (BMI) as per World Health Organization Asia Pacific guidelines as nonobese (BMI <25 kg/m(2)) and obese (BMI ≥25 kg/m(2)), neither the allelic frequency (nonobese, P = 0.44; obese, P = 0.37) nor the genotypic frequency (nonobese, P = 0.29; obese, P = 0.35) was significantly different between the NGT and type 2 diabetes groups. The Ala513Pro polymorphism was first genotyped in 500 NGT and 500 type 2 diabetes subjects. None of these subjects carried the Ala513Pro or the Pro513Pro genotype. Hence, the Ala513Pro polymorphism was not genotyped further. CONCLUSION: The IRS1 gene variants Gly972Arg and Ala513Pro are not associated with type 2 diabetes in this south Indian population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.000 | 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".