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Comparative lipidomic profiling in adolescents with obesity and adolescents with type 1 diabetes

2025· article· en· W4406509282 on OpenAlexfundno aff
Antônio García‐Hermoso, Nidia Huerta-Uribe, Míkel Izquierdo, Katherine González‐Ruíz, Jorge Enrique Correa‐Bautista, Robinson Ramírez‐Vélez

Bibliographic record

VenueCurrent Problems in Cardiology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsnot available
FundersUniversidad del RosarioInstituto de Salud Carlos IIIEgg Farmers of Canada
KeywordsMedicineType 2 diabetesObesityProfiling (computer programming)Diabetes mellitusAdolescent ObesityInternal medicineEndocrinologyOverweight

Abstract

fetched live from OpenAlex

• Both adolescents with obesity and those with type 1 diabetes exhibit alterations in lipid profiles, yet direct comparisons are scarce. • The obesity group displayed higher levels of diglycerides, triglycerides, and specific phosphatidylinositols. • Adolescents with type 1 diabetes showed elevated levels of phosphatidylcholines, phosphatidylethanolamines, cholesterol esters, sphingomyelins, and ceramides. • Our comparative lipidomic profiling unveiled significant differences between adolescents with obesity and those with T1D, with key lipid alterations correlating with clinical parameters. Both adolescents with obesity and those with type 1 diabetes (T1D) exhibit alterations in lipid profiles, but direct comparisons are limited. Comparing lipidomic profiles between obese individuals and those with T1D is crucial for identifying specific metabolic markers, informing tailored interventions, and advancing precision medicine strategies for these distinct populations. The aim of the study was to compare lipidomic profiles between adolescents with obesity and those with T1D, and to analyze associations between metabolites and clinical parameters. We included 156 adolescents aged 11–18 years (59.6% girls) from the HEPAFIT ( n =114, obesity) and Diactive-1 Cohort ( n =42, T1D) studies. Clinical measures included anthropometrics, body composition, lipids, liver enzymes, glucose, and HbA1c. Lipidomic analysis of 277 serum/plasma metabolites used UHPLC-MS. Distinct lipid profiles were seen, with higher diglycerides, triglycerides, and certain phosphatidylinositols in the obesity group, while phosphatidylcholines, phosphatidylethanolamines, cholesterol esters, sphingomyelins, and ceramides were elevated in T1D. Triglycerides acyl chain lengths and saturation levels also varied. Multivariate analysis identified seven metabolites –PC(O-18:1/18:1), PC(O-18:1/22:4), PE(O-16:0/18:1), PE(18:2e/22:6), PC(40:1), PC(O-22:1/20:4), and PE(P-18:0/18:1)– significantly associated with clinical parameters. Distinct lipid profiles were observed among adolescents with obesity and T1D in the study, emphasizing the importance of understanding specific metabolite associations with clinical parameters for more precise health management.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.271
Teacher spread0.256 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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