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Record W4304187454 · doi:10.3389/fendo.2022.934706

Integrative analysis reveals novel associations between DNA methylation and the serum metabolome of adolescents with type 2 diabetes: A cross-sectional study

2022· article· en· W4304187454 on OpenAlexafffund
Prasoon Agarwal, Brandy Wicklow, Allison Dart, Nikho A. Hizon, Elizabeth Sellers, Jonathan McGavock, Charlotte P.J. Talbot, Mario Fonseca, Wayne Wenzhong Xu, James Davie, Meaghan J. Jones, Animesh Acharjee, Vernon W. Dolinsky

Bibliographic record

VenueFrontiers in Endocrinology · 2022
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsResearch Institute in Oncology and HematologyUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
FundersCanadian Institutes of Health ResearchSurgical Reconstruction and Microbiology Research CentreNational Institute for Health and Care ResearchManitoba Medical Service FoundationResearch Manitoba
KeywordsType 2 diabetesDNA methylationMetabolomeEpigeneticsDifferentially methylated regionsBiologyTCF7L2EndocrinologyMethylationCohortInternal medicineDiabetes mellitusMedicineBioinformaticsMetabolomicsGeneGeneticsGene expressionGenotype

Abstract

fetched live from OpenAlex

Objective Rates of type 2 diabetes (T2D) among adolescents are on the rise. Epigenetic changes could be associated with the metabolic alterations in adolescents with T2D. Methods We performed a cross sectional integrated analysis of DNA methylation data from peripheral blood mononuclear cells with serum metabolomic data from First Nation adolescents with T2D and controls participating in the Improving Renal Complications in Adolescents with type 2 diabetes through Research (iCARE) cohort study, to explore the molecular changes in adolescents with T2D. Results Our analysis showed that 43 serum metabolites and 36 differentially methylated regions (DMR) were associated with T2D. Several DMRs were located near the transcriptional start site of genes with established roles in metabolic disease and associated with altered serum metabolites (e.g. glucose, leucine, and gamma-glutamylisoleucine). These included the free fatty acid receptor-1 (FFAR1 ), upstream transcription factor-2 ( USF2 ), and tumor necrosis factor-related protein-9 ( C1QTNF9 ), among others. Conclusions We identified DMRs and metabolites that merit further investigation to determine their significance in controlling gene expression and metabolism which could define T2D risk in adolescents.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.025
GPT teacher head0.314
Teacher spread0.289 · 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

Citations18
Published2022
Admission routes2
Has abstractyes

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