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Record W1995716751 · doi:10.1186/1471-2350-12-95

Genetic polymorphisms of innate immunity-related inflammatory pathways and their association with factors related to type 2 diabetes

2011· article· en· W1995716751 on OpenAlex
Paul Arora, Bibiana García‐Bailo, Zari Dastani, Darren R. Brenner, André Villegas, Suneil Malik, Timothy D. Spector, Brent Richards, Ahmed El‐Sohemy, Mohamed A. Karmali, Alaa Badawi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBMC Medical Genetics · 2011
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsMcGill UniversityPublic Health OntarioUniversity of TorontoPublic Health Agency of Canada
FundersBiotechnology and Biological Sciences Research CouncilFonds de Recherche du Québec - SantéVersus ArthritisDirectorate for Biological SciencesNational Institute for Health and Care ResearchJewish General HospitalPublic Health AgencyEuropean CommissionKing's College LondonCanadian Institutes of Health ResearchPublic Health Agency of CanadaWellcome Trust
KeywordsHuman geneticsBiologyInnate immune systemGeneticsImmunologyType 1 diabetesImmunityGenetic associationDiabetes mellitusComputational biologyGenotypeGeneSingle-nucleotide polymorphismImmune system

Abstract

fetched live from OpenAlex

BACKGROUND: Type 2 diabetes mellitus (T2DM) has been linked to a state of pre-clinical chronic inflammation resulting from abnormalities in the innate immune pathway. Serum levels of pro-inflammatory cytokines and acute-phase proteins, collectively known as 'inflammatory network', are elevated in the pre-, or early, stages of T2DM and increase with disease progression. Genetic variation can affect the innate immune response to certain environmental factors, and may, therefore, determine an individual's lifetime risk of disease. METHODS: We conducted a cross-sectional study in 6,720 subjects from the Twins UK Registry to evaluate the association between 18 single nucleotide polymorphisms (SNPs) in five genes (TLR4, IL1A, IL6, TNFA, and CRP) along the innate immunity-related inflammatory pathway and biomarkers of predisposition to T2DM [fasting insulin and glucose, HDL- and LDL- cholesterols, triglycerides (TGs), amyloid-A, sensitive C-reactive protein (sCRP) and vitamin D binding protein (VDBP) and body mass index (BMI)]. RESULTS: Of 18 the SNPs examined for their association with nine metabolic phenotypes of interest, six were significantly associated with five metabolic phenotypes (Bonferroni correction, P ≤ 0.0027). Fasting insulin was associated with SNPs in IL6 and TNFA, serum HDL-C with variants of TNFA and CRP and serum sCRP level with SNPs in CRP. Cross-correlation analysis among the different metabolic factors related to risk of T2DM showed several significant associations. For example, BMI was directly correlated with glucose (r = 0.11), insulin (r = 0.15), sCRP (r = 0.23), LDL-C (r = 0.067) and TGs (r = 0.18) but inversely with HDL-C (r = -0.14). sCRP was also positively correlated (P < 0.0001) with insulin (r = 0.17), amyloid-A (r = 0.39), TGs (r = 0.26), and VDBP (r = 0.36) but inversely with HDL-C (r = -0.12). CONCLUSION: Genetic variants in the innate immunity pathway and its related inflammatory cascade is associated with some metabolic risk factors for T2DM; an observation that may provide a rationale for further studying their role as biomarkers for disease early risk prediction.

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.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.017
GPT teacher head0.220
Teacher spread0.203 · 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