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Record W3034907335 · doi:10.1210/jendso/bvaa056

Dissection of Clinical and Gene Expression Signatures of Familial versus Multifactorial Chylomicronemia

2020· article· en· W3034907335 on OpenAlex
Karine Tremblay, Daniel Gaudet, Étienne Khoury, Diane Brisson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Endocrine Society · 2020
Typearticle
Languageen
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsGeneticsGeneBioinformaticsMedicineBiologyComputational biology

Abstract

fetched live from OpenAlex

Abstract Familial chylomicronemia syndrome (FCS) is a rare disorder associated with chylomicronemia (CM) and an increased risk of pancreatitis. Most individuals with CM do not have FCS but exhibit multifactorial CM (MCM), which differs from FCS in terms of risk and disease management. This study aimed to investigate clinical and gene expression profiles of FCS and MCM patients. Anthropometrics, clinical, and biochemical variables were analyzed in 57 FCS and 353 MCM patients. Gene expression analyses were performed in a subsample of 19 FCS, 28 MCM, and 15 normolipidemic controls. Receiver operating characteristic (ROC) curve analyses were performed to analyze the capacity of variables to discriminate FCS from MCM. Sustained fasting triglycerides ≥20 mmol/L (>15 mmol/L with eruptive xanthomas), history of pancreatitis, poor response to fibrates, diagnosis of CM at childhood, body mass index <22 kg/m2, and delipidated apolipoprotein B or glycerol levels <0.9 g/L and <0.05 mmol/L, respectively, had an area under the ROC curve ≥0.7. Gene expression analyses identified 142 probes differentially expressed in FCS and 32 in MCM compared with controls. Among them, 13 probes are shared between FCS and MCM; 63 are specific to FCS and 2 to MCM. Most FCS-specific or shared biomarkers are involved in inflammatory, immune, circadian, postprandial metabolism, signaling, docking systems, or receptor-mediated clearance mechanisms. This study reveals differential signatures of FCS and MCM. It opens the door to the identification of key mechanisms of CM expression and potential targets for the development of new treatments.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.210

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.037
GPT teacher head0.336
Teacher spread0.299 · 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