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Record W2137505372 · doi:10.2337/diabetes.53.3.870

Analysis of the Type 2 Diabetes-Associated Single Nucleotide Polymorphisms in the Genes <i>IRS1</i>, <i>KCNJ11</i>, and <i>PPARG2</i> in Type 1 Diabetes

2004· article· en· W2137505372 on OpenAlexaff
Christina Eftychi, Joanna M. M. Howson, Bryan J. Barratt, Adrian Vella, Felicity Payne, Deborah J. Smyth, Rebecca C.J. Twells, Neil Walker, Helen Rance, Eva Tuomilehto‐Wolf, Jaakko Tuomilehto, Dag E. Undlien, Kjersti S. Rønningen, Cristian Guja, Constantin Ionescu-Tı̂irgovişte, David A. Savage, John A. Todd

Bibliographic record

VenueDiabetes · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsNutrasource
FundersWellcome Trust
KeywordsSingle-nucleotide polymorphismType 2 diabetesInternal medicineIRS1Diabetes mellitusEndocrinologyPeroxisome proliferator-activated receptor gammaGenetic associationPolymorphism (computer science)MedicineGeneGeneticsBiologyGenotypeReceptorInsulin receptorPeroxisome proliferator-activated receptorInsulin resistance

Abstract

fetched live from OpenAlex

It has been proposed that type 1 and 2 diabetes might share common pathophysiological pathways and, to some extent, genetic background. However, to date there has been no convincing data to establish a molecular genetic link between them. We have genotyped three single nucleotide polymorphisms associated with type 2 diabetes in a large type 1 diabetic family collection of European descent: Gly972Arg in the insulin receptor substrate 1 (IRS1) gene, Glu23Lys in the potassium inwardly-rectifying channel gene (KCNJ11), and Pro12Ala in the peroxisome proliferative-activated receptor gamma2 gene (PPARG2). We were unable to confirm a recently published association of the IRS1 Gly972Arg variant with type 1 diabetes. Moreover, KCNJ11 Glu23Lys showed no association with type 1 diabetes (P > 0.05). However, the PPARG2 Pro12Ala variant showed evidence of association (RR 1.15, 95% CI 1.04-1.28, P = 0.008). Additional studies need to be conducted to confirm this result.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score0.804

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.212
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations43
Published2004
Admission routes1
Has abstractyes

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