Rare Variants in Triglycerides-Related Genes Increase Pancreatitis Risk in Multifactorial Chylomicronemia Syndrome
Bibliographic record
Abstract
CONTEXT: Severe hypertriglyceridemia (fasting triglycerides [TG] concentration ≥10 mmol/L) can be caused by multifactorial chylomicronemia syndrome (MCS) or familial chylomicronemia syndrome (FCS). Both conditions are associated with an increased risk of acute pancreatitis. The clinical differences between MCS patients with or without a rare variant in TG-related genes have never been studied. OBJECTIVE: To compare the clinical and biochemical characteristics of FCS, positive-MCS patients, and negative-MCS patients, as well as to investigate the predictors of acute pancreatitis in MCS patients. METHODS: All patients referred at the clinic for severe hypertriglyceridemia underwent genetic testing for the 5 canonical genes involved in TG metabolism (LPL, APOC2, GPIHBP1, APOA5, and LMF1) using next-generation sequencing. RESULTS: A total of 53 variant negative-MCS, 22 variant positive-MCS and 28 FCS subjects were included in this retrospective cross-sectional study. A significant difference was observed in the prevalence of pancreatitis (9%, 41%, and 61%) and multiple pancreatitis (6%, 23%, and 46%) in the negative-MCS, the positive-MCS, and the FCS groups, respectively (P < 0.0001). Predictors of pancreatitis among MCS subjects included the presence of a rare variant, lower apolipoprotein B, as well as higher gamma-glutamyl transferase, maximal TG value, and fructose consumption. CONCLUSION: We observed that the MCS individuals who carried a rare variant have an intermediate phenotype between FCS and negative-MCS subjects. Since novel molecules such as the antisense oligonucleotide against APOC3 mRNA showed high efficacy in reducing TG levels in patients with multifactorial chylomicronemia, identification of higher-risk MCS patients who would benefit from additional treatment is essential.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".