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Record W2094911048 · doi:10.1136/jmg.2003.014092

Functional dimorphism of two hAgRP promoter SNPs in linkage disequilibrium

2004· article· en· W2094911048 on OpenAlexafffund
Fulu Bai

Bibliographic record

VenueJournal of Medical Genetics · 2004
Typearticle
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsToronto General HospitalToronto Western HospitalUniversity of TorontoOntario Institute for Cancer Research
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsLinkage disequilibriumSingle-nucleotide polymorphismSNPAlleleBiologyMelanocortinGeneticsEndocrinologyInternal medicineReceptorGenotypeGeneMedicine

Abstract

fetched live from OpenAlex

The agouti related protein (AgRP) exerts its anabolic effects on food intake by antagonising the alpha-melanocyte stimulating hormone (alpha-MSH) at its receptors, melanocortin receptors 3 and 4 (MC3R and MC4R). A single nucleotide polymorphism (SNP) in the promoter of the human AgRP (hAgRP), -38C>T, was associated with low body fatness. The -38T allele that was associated with low body fatness also resulted in lower promoter activity. Here we report a novel SNP, -3019G>A, again in the promoter of hAgRP, which is in complete linkage disequilibrium (LD) with the -38C>T SNP (linked alleles: -3019A/-38T and -3019G/-38C). Functional analyses in a human adrenal and two mouse hypothalamus cell lines showed that the -3019A allele had significantly higher promoter activity. Hence, the two linked alleles (-3019A and -38T) had opposite effects on promoter function and yet they were both associated with low body fatness. The region encompassing the -38C>T SNP had approximately 1000-fold higher activity than the region encompassing the -3019G>A SNP, potentially determining the net functional effect between these two SNPs.

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)0.001
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 score0.231
Threshold uncertainty score0.391

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.036
GPT teacher head0.294
Teacher spread0.258 · 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

Citations23
Published2004
Admission routes2
Has abstractyes

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