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Record W4214825972 · doi:10.2337/db21-1046

Connecting Genomics and Proteomics to Identify Protein Biomarkers for Adult and Youth-Onset Type 2 Diabetes: A Two-Sample Mendelian Randomization Study

2022· article· en· W4214825972 on OpenAlexaff
Faegheh Ghanbari, Nahid Yazdanpanah, Mojgan Yazdanpanah, J. Brent Richards, Despoina Manousaki

Bibliographic record

VenueDiabetes · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsMcGill UniversityJewish General HospitalUniversité de Montréal
Fundersnot available
KeywordsMendelian randomizationGenomicsProteomicsComputational biologyGeneticsMendelian inheritanceBiologyType 2 diabetesBioinformaticsMedicineDiabetes mellitusGeneEndocrinologyGenomeGenetic variantsGenotype

Abstract

fetched live from OpenAlex

Type 2 diabetes shows an increasing prevalence in both adults and children. Identification of biomarkers for both youth and adult-onset type 2 diabetes is crucial for development of screening tools or drug targets. In this study, using two-sample Mendelian randomization (MR), we identified 22 circulating proteins causally linked to adult type 2 diabetes and 11 proteins with suggestive evidence for association with youth-onset type 2 diabetes. Among these, colocalization analysis further supported a role in type 2 diabetes for C-type mannose receptor 2 (MR odds ratio [OR] 0.85 [95% CI 0.79-0.92] per genetically predicted SD increase in protein level), MANS domain containing 4 (MR OR 0.90 [95% CI 0.88-0.92]), sodium/potassium-transporting ATPase subunit β2 (MR OR 1.10 [95% CI 1.06-1.15]), endoplasmic reticulum oxidoreductase 1β (MR OR 1.09 [95% CI 1.05-1.14]), spermatogenesis-associated protein 20 (MR OR 1.12 [95% CI 1.06-1.18]), haptoglobin (MR OR 0.96 [95% CI 0.94-0.98]), and α1-3-N-acetylgalactosaminyltransferase and α1-3-galactosyltransferase (MR OR 1.04 [95% CI 1.03-1.05]). Our findings support a causal role in type 2 diabetes for a set of circulating proteins, which represent promising type 2 diabetes 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 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)0.002
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 score0.200
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.015
GPT teacher head0.278
Teacher spread0.263 · 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
Published2022
Admission routes1
Has abstractyes

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