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Record W2101079673 · doi:10.1136/jmg.37.3.186

Age and sex based genetic locus heterogeneity in type 1 diabetes

2000· article· en· W2101079673 on OpenAlexaff
Andrew D. Paterson

Bibliographic record

VenueJournal of Medical Genetics · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsLocus (genetics)GeneticsType 2 diabetesBiologyGenetic heterogeneityEvolutionary biologyDiabetes mellitusEndocrinologyGenePhenotype

Abstract

fetched live from OpenAlex

BACKGROUND: Two genome scans for susceptibility loci for type 1 diabetes using large collections of families have recently been reported. Apart from strong linkage in both studies of the HLA region on chromosome 6p, clear consistent evidence for linkage was not observed at any other loci. One possible explanation for this is a high degree of locus heterogeneity in type 1 diabetes, and we hypothesised that the sex of affected offspring, age of diagnosis, and parental origin of shared alleles may be the bases of heterogeneity at some loci. METHODS: Using data from a genome wide linkage study of 356 affected sib pairs with type 1 diabetes, we performed linkage analyses using parental origin of shared alleles in subgroups based on (1) sex of affected sibs and (2) age of diagnosis. RESULTS: Among the results obtained, we observed that evidence for linkage to IDDM4 on chromosome 11q13 occurred predominantly from opposite sex, rather than same sex sib pairs. At a locus on chromosome 4q, evidence for linkage was observed in sibs where one was diagnosed above the age of 10 years and the other diagnosed below 10 years of age. CONCLUSIONS: We show that heterogeneity tests based on age of diagnosis, sex of affected subject, and parental origin of shared alleles may be helpful in reducing locus heterogeneity in type 1 diabetes. If repeated in other samples, these findings may assist in the mapping of susceptibility loci for type 1 diabetes. Similar analyses can be recommended in other complex diseases.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.633
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.007
GPT teacher head0.246
Teacher spread0.239 · 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 designObservational
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

Citations10
Published2000
Admission routes1
Has abstractyes

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