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Record W3197580402 · doi:10.1161/jaha.120.019890

Spectrum of Apolipoprotein AI and Apolipoprotein AII Proteoforms and Their Associations With Indices of Cardiometabolic Health: The CARDIA Study

2021· article· en· W3197580402 on OpenAlexaff
John T. Wilkins, Henrique S. Seckler, Jonathan S. Rink, Philip D. Compton, Luca Fornelli, C. Shad Thaxton, Richard D. LeDuc, David R. Jacobs, Peter F. Doubleday, Allan D. Sniderman, Donald M. Lloyd‐Jones, Neil L. Kelleher

Bibliographic record

VenueJournal of the American Heart Association · 2021
Typearticle
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsMcGill University Health Centre
FundersNational Center for Advancing Translational SciencesNational Institute of General Medical SciencesNational Heart, Lung, and Blood Institute
KeywordsMedicineApolipoprotein BBody mass indexMetabolic syndromeInternal medicineCholesterolObesityEndocrinology

Abstract

fetched live from OpenAlex

Background ApoAI (apolipoproteins AI) and apoAII (apolipoprotein AII) are structural and functional proteins of high-density lipoproteins (HDL) which undergo post-translational modifications at specific residues, creating distinct proteoforms. While specific post-translational modifications have been reported to alter apolipoprotein function, the full spectrum of apoAI and apoAII proteoforms and their associations with cardiometabolic phenotype remains unknown. Herein, we comprehensively characterize apoAI and apoAII proteoforms detectable in serum and their post-translational modifications and quantify their associations with cardiometabolic health indices. Methods and Results Using top-down proteomics (mass-spectrometric analysis of intact proteins), we analyzed paired serum samples from 150 CARDIA (Coronary Artery Risk Development in Young Adults) study participants from year 20 and 25 exams. Measuring 15 apoAI and 9 apoAII proteoforms, 6 of which carried novel post-translational modifications, we quantified associations between percent proteoform abundance and key cardiometabolic indices. Canonical (unmodified) apoAI had inverse associations with HDL cholesterol and HDL-cholesterol efflux, and positive associations with obesity indices (body mass index, waist circumference), and triglycerides, whereas glycated apoAI showed positive associations with serum glucose and diabetes mellitus. Fatty-acid‒modified ApoAI proteoforms had positive associations with HDL cholesterol and efflux, and inverse associations with obesity indices and triglycerides. Truncated and dimerized proteoforms of apoAII were associated with HDL cholesterol (positively) and obesity indices (inversely). Several proteoforms had no significant associations with phenotype. Conclusions Associations between apoAI and AII and cardiometabolic indices are proteoform-specific. These results provide "proof-of-concept" that precise chemical characterization of human apolipoproteins will yield improved insights into the complex pathways through which proteins signify and mediate health and disease.

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)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.261
Teacher spread0.252 · 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

Citations29
Published2021
Admission routes1
Has abstractyes

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