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Record W4292805223 · doi:10.1016/j.isci.2022.104992

Genetic association and Mendelian randomization for hypothyroidism highlight immune molecular mechanisms

2022· article· en· W4292805223 on OpenAlexaff
Samuel Mathieu, Mewen Briend, Erik Abner, Christian Couture, Zhonglin Li, Yohan Bossé, Sébastien Thériault, Tõnu Esko, Benoît J. Arsenault, Patrick Mathieu

Bibliographic record

VenueiScience · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMendelian randomizationGenome-wide association studyCandidate geneGenetic associationBiologyGeneGeneticsBioinformaticsSingle-nucleotide polymorphismGenotype

Abstract

fetched live from OpenAlex

We carried out a genome-wide association analysis including 51,194 cases of hypothyroidism and 443,383 controls. In total, 139 risk loci were associated to hypothyroidism with genes involved in lymphocyte function. Candidate genes associated with hypothyroidism were identified by using molecular quantitative trait loci, colocalization, and enhancer-promoter chromatin looping. Mendelian randomization (MR) identified 42 blood expressed genes and circulating proteins as candidate causal molecules in hypothyroidism. Drug-gene interaction analysis provided evidence that immune checkpoint and tyrosine kinase inhibitors used in cancer therapy increase the risk of hypothyroidism. Hence, integrative mapping and MR support that expression of genes and proteins enriched in lymphocyte function are associated with the risk of hypothyroidism and provide genetic evidence for drug-induced hypothyroidism and identify actionable potential drug targets.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.220
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), 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

Citations31
Published2022
Admission routes1
Has abstractyes

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