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Record W2589693885 · doi:10.1161/hyp.66.suppl_1.p181

Abstract P181: Circulating Second-messenger Glycerophosphocholines and Cardiovascular Risk Factors in a Population-based Sample of Adolescents

2015· article· en· W2589693885 on OpenAlexaffabout
Simon Czajkowski, Michał Abrahamowicz, Gabriel Leonard, Michel Perron, Louis Richer, Suzanne Veillette, Daniel Gaudet, Yun Wang, Hongbin Xu, Graeme Taylor, Tomáš Paus, Steffany A. L. Bennett, Zdenka Pausová

Bibliographic record

VenueHypertension · 2015
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsUniversity of OttawaUniversité de MontréalMcGill UniversityUniversité du Québec à ChicoutimiUniversity of Toronto
Fundersnot available
KeywordsInsulin resistanceInternal medicinePopulationEndocrinologyMedicineBody mass indexBlood pressureInflammationMetabolic syndromeSystemic inflammationDiseaseLipidomicsInsulinDiabetes mellitusBiologyBioinformatics

Abstract

fetched live from OpenAlex

Circulating second-messenger glycerophosphocholines (smGPCs), including lysophosphatidylcholines and platelet-activating factors, are low-abundance plasma phospholipids that modulate atherosclerosis and inflammation and, in turn, the risk for cardiovascular disease (CVD). Although CVD is a slow-progressing disease culminating in middle-to-late adulthood, its initial stages may be seen already in adolescence. Here, we investigated whether circulating smGPCs are associated with classical CVD risk factors - excess body fat, elevated BP, insulin resistance and low-grade inflammation - during adolescence. We studied a population-based sample of 1029 adolescents (52% females, 12-18 years), as part of the Saguenay Youth Study. We used targeted serum lipidomics (LC-ESI-MS) to identify and quantify circulating smGPCs within the 440-640 Da range. In all participants, we also measured: (i) visceral fat with MRI and total body fat with bioimpedance; (ii) blood pressure (BP) beat-by-beat for five minutes under standard clinical conditions; and (iii and iv) fasting serum insulin (as an index of insulin resistance) and CRP (as an index of low-grade inflammation). We identified a total of 81 smGPCs that varied by the length and saturation of their fatty acyl residues and the type of linkage these residues are attached to the glycerol backbone. Over 30 of them were associated with multiple CVD risk factors (p<6x10 -4 ). Most of these associations were inverse and involved ‘medium’ mass smGPCs. Positive associations were also seen and these involved ‘low’ or ‘high’ mass smGPCs. Most strongly inversely associated smGPCs were: (i) PC(20:6/0:0) and PC(O-18:6/2:0), which were associated with total body fat (p<3x10 -14 ) and CRP (p<8x10 -36 ); and (ii) PC(16:0/2:0), which was associated with visceral fat (p=2x10 -18 ) and BP (p<1x10 -5 ). The most strongly positively associated smGPC was PC(14:1/0:0), which was associated with visceral fat (p=8x10 -8 ) and fasting insulin (p=2x10 -24 ). Thus, specific circulating smGPCs are strongly associated with multiple CVD risk factors in adolescence; some of these associations may be ‘protective’ whereas others ‘adverse’. Circulating smGPCs may serve as novel biomarkers of early risk for CVD.

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 score0.006
Threshold uncertainty score0.012

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 head0.031
GPT teacher head0.248
Teacher spread0.217 · 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

Citations0
Published2015
Admission routes2
Has abstractyes

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