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Record W4387309596 · doi:10.3389/fendo.2023.1222101

Plasma IGFBP-2 levels reveal heterogeneity in hepatic fat content in adults with excess visceral adiposity

2023· article· en· W4387309596 on OpenAlexafffund
Chloé Rauzier, Dominic Chartrand, Natalie Alméras, Isabelle Lemieux, Éric Larose, Patrick Mathieu, Philippe Pîbarot, Benoı̂t Lamarche, Caroline Rhéaume, Paul Poirier, Jean‐Pierre Després, Frédéric Picard

Bibliographic record

VenueFrontiers in Endocrinology · 2023
Typearticle
Languageen
FieldMedicine
TopicGrowth Hormone and Insulin-like Growth Factors
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchInstitut universitaire de cardiologie et de pneumologie de Québec, Université Laval
KeywordsInternal medicineEndocrinologyMedicineIntra-Abdominal FatBiomarkerAsymptomaticObesityInsulin resistanceVisceral fatBiology

Abstract

fetched live from OpenAlex

Lay summary Obesity is frequently accompanied by a fatty liver. However, some individuals with high abdominal fat levels nevertheless have low levels of liver fat. Reasons for such discordant phenotypes are unclear. In this paper, we report that among asymptomatic individuals with high levels of visceral fat, low concentrations of IGFBP-2 in the circulation were associated with significantly higher hepatic fat content compared to those with high IGFBP-2 levels. We conclude that quantification of plasma IGFBP-2 concentrations may be useful to identify the early risk for liver fat accumulation in apparently healthy individuals without cardiovascular symptoms. Aim/hypothesis Although excess visceral adiposity (VAT) is generally associated with increased liver fat (LF), recent evidence has revealed heterogeneity in LF content among adults with visceral obesity, potentially contributing to specific differences in cardiometabolic outcomes. Reasons for such discordant VAT-LF phenotypes are largely unknown. The present study aimed at assessing whether circulating levels of insulin growth-factor binding protein-2 (IGFBP-2) could be a useful biomarker in the identification of heterogenous and discordant VAT-LF phenotypes. Methods A sample of 308 middle-aged Caucasian apparently healthy men and women without cardiovascular symptoms were studied for the present cross-sectional analyses. Fasting plasma glucose and lipid levels were assessed and an oral glucose tolerance test was performed. Hepatic fat fraction (HFF) was measured using magnetic resonance spectroscopy whereas VAT was assessed by magnetic resonance imaging. Plasma IGFBP-2 levels were quantified by ELISA. Participants were then classified on the basis of median VAT (81 mL) and IGFBP-2 levels (233 ng/mL). Results Individuals with high levels of VAT were characterized by higher waist circumference, lower insulin sensitivity, as well as by higher plasma triglyceride and lower HDL-cholesterol levels. Plasma IGFBP-2 levels were inversely correlated with HFF (r = -0.39, p < 0.0001). Among men and women with high levels of VAT, those with low levels of IGFBP-2 had significantly higher HFF (7.5 ± 0.7%), compared to participants with high IGFBP-2 concentrations (3.2 ± 0.5%, p < 0.0001). Conclusion In the presence of excess VAT, high IGFBP-2 concentrations are associated with low levels of LF. Although additional studies will be necessary to establish causality and further clarify the clinical implications of these observations, these findings are concordant with a novel function of IGFBP-2 in modulating susceptibility to non-alcoholic fatty liver disease (NAFLD) in the presence of visceral obesity.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.263
Teacher spread0.228 · 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

Citations4
Published2023
Admission routes2
Has abstractyes

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