Complex genetic determinants of hypertriglyceridemia
Notice bibliographique
Résumé
Hypertriglyceridemia (HTG) is a common dyslipidemia defined by elevated circulating blood triglyceride (TG) levels. Individuals with HTG are at risk for several health complications, which can include cardiovascular disease and in severe cases, acute pancreatitis. As the extreme manifestation of a physiological quantitative trait, HTG is influenced by genetic and non‐genetic factors. Genetic determinants include both rare single‐nucleotide variants (SNVs) and copy‐number variants (CNVs) in genes involved in TG metabolism, as well as common single‐nucleotide polymorphisms (SNPs) associated with TG levels. Despite understanding the complex genetic nature of HTG, the individual genetic influences on HTG have so far been examined only in a piecemeal manner. Here, we concurrently assessed rare SNVs and CNVs, and the accumulation of common SNPs in 104 Caucasian patients with mild‐to‐moderate HTG (defined as TG ≥3.3 and <10 mmol/L). As a reference “normolipidemic” group, we studied 503 healthy Caucasians from the open‐source 1000 Genomes Project. Patient DNA was subjected to next‐generation sequencing using our custom‐designed LipidSeq panel, which targets 73 genes and 185 SNPs associated with dyslipidemia and other metabolic disorders. We first screened for rare SNVs and CNVs in TG‐associated genes. For rare variants with likely large phenotypic effects, 1.0% of subjects had homozygous SNVs, and 12.5% had heterozygous SNVs or CNVs. In the normolipidemic controls, there were no homozygous SNVs, and 4.0% of subjects had heterozygous SNVs. We then assessed patients for an accumulation of common SNPs using a polygenic risk score. We identified an extreme score (defined as >90 th percentile of the normolipidemic population) in 27.9% of patients, compared to 9.5% of normolipidemic controls. Taken together, 41.3% of mild‐to‐moderate HTG patients had either a rare variant or high polygenic burden, compared to only 13.5% of controls. Compared to normolipidemic controls, mild‐to‐moderate HTG patients are 3.76‐fold (CI 95% 1.83–7.71; P<0.0001) more likely to carry a rare variant, 3.67‐fold (CI 95% 2.8–6.18; P<0.0001) more likely to have a high polygenic burden, and 4.51‐fold (CI 95% 2.83–7.19; P<0.0001) more likely to carry a TG‐related genetic factor, either a rare variant or polygenic burden of SNPs. We thus report the most in‐depth, systematic evaluation of genetic contributors of mild‐to‐moderate HTG to date. Next steps include: 1) identification of novel genetic determinants in patients negative for genetic determinants studied here; and 2) evaluations of genotype differences in clinical outcomes and intervention response. Support or Funding Information JSD is supported by the Canadian Institutes of Health Research (Doctoral Research Award) and the Schulich School of Medicine and Dentistry (Cobban Student Award in Heart and Stroke Research, and Nellie L. Farthing Memorial Fellowship in the Medical Science). RAH is supported by the Jacob J. Wolfe Distinguished Medical Research Chair, the Edith Schulich Vinet Research Chair in Human Genetics, and the Martha G. Blackburn Chair in Cardiovascular Research. RAH has received operating grants from the Canadian Institutes of Health Research, the Heart and Stroke Foundation, and Genome Canada. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».