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Record W4410979841 · doi:10.1016/j.jacl.2025.05.021

Heterozygous pathogenic PPARG variants in patients with severe hypertriglyceridemia

2025· article· en· W4410979841 on OpenAlexafffund
Shyann Hang, Zahra Taboun, Adam D. McIntyre, Robert A. Hegele

Bibliographic record

VenueJournal of clinical lipidology · 2025
Typearticle
Languageen
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsUniversity of British ColumbiaWestern University
FundersUltragenyx PharmaceuticalRegeneron PharmaceuticalsSanofiHLS TherapeuticsPfizerAmgen
KeywordsMedicineHypertriglyceridemiaPeroxisome proliferator-activated receptor gammaInternal medicineGeneticsTriglyceridePeroxisome proliferator-activated receptorCholesterol

Abstract

fetched live from OpenAlex

BACKGROUND: Heterozygous pathogenic variants in PPARG cause familial partial lipodystrophy type 3 (FPLD3; Mendelian Inheritance in Man [MIM] #604367), a heritable form of insulin resistance with multiple metabolic disturbances including hypertriglyceridemia. We investigated the prevalence of FPLD3 individuals in our cohort of patients with multifactorial chylomicronemia syndrome (MCS). METHODS: We used our targeted DNA sequencing panel to screen the PPARG gene in 182 clinically diagnosed MCS patients. RESULTS: We found that 3.3% of MCS patients (6/182) had a heterozygous pathogenic PPARG variant, consistent with a diagnosis of FPLD3. The variants were PPARG p.Lys186fs (ClinVar identifier 8132), p.Glu217Lys, p.Pro454fs (ClinVar identifier 436405), p.Met284Ile, p.Ser383Arg, and p.Arg181Trp. None of these patients had previously been diagnosed with FPLD3 and their clinical and biochemical features were otherwise comparable to those of the entire MCS cohort. CONCLUSION: A small but clinically relevant subgroup of individuals with MCS has FPLD3. Clinical features in FPLD3 are subtle but the phenotype can be metabolically severe. Genetic screening of patients with severe hypertriglyceridemia should include assessment of lipodystrophy genes, since management of lipodystrophy patients is distinct from that of typical MCS patients.

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 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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.021
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.344
Teacher spread0.321 · 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 teacher head, 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

Citations1
Published2025
Admission routes2
Has abstractyes

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