Analysis of omega-3 and omega-6 polyunsaturated fatty acid metabolism by compound-specific isotope analysis in humans
Notice bibliographique
Résumé
Natural variations in the 13C:12C ratio (carbon-13 isotopic abundance [δ13C]) of the food supply have been used to determine the dietary origin and metabolism of fatty acids, especially in the n-3 polyunsaturated fatty acid (PUFA) biosynthesis pathway. However, n-6 PUFA metabolism following linoleic acid (LNA) intake remains under investigated. Here, we sought to use natural variations in the δ13C signature of dietary oils and fatty fish to analyze n-3 and n-6 PUFA metabolism following dietary changes in LNA and eicosapentaenoic acid (EPA) + docosahexaenoic acid (DHA) in adult humans. Participants with migraine (aged 38.6 ± 2.3 y, 93% female, BMI 27.0 ± 1.1 kg/m2) were randomly assigned to one of three dietary groups for 16 weeks: 1) low omega-3, high omega-6 (H6), 2) high omega-3, high omega-6 (H3H6), or 3) high omega-3, low omega-6 (H3). Blood was collected at baseline, 4, 10, and 16 weeks. Plasma PUFA concentrations and δ13C were determined. The H6 intervention exhibited increases in plasma LNA δ13C signature over time; meanwhile, plasma LNA concentrations were unchanged. No changes in plasma arachidonic acid δ13C or concentration were observed. Participants on the H3H6 and H3 interventions demonstrated increases in plasma EPA and DHA concentration over time. Plasma δ13C-EPA increased in total lipids of the H3 group and phospholipids of the H3H6 group compared to baseline. Compound-specific isotope analysis supports a tracer-free technique that can track metabolism of dietary fatty acids in humans, provided that the isotopic signature of the dietary source is sufficiently different from plasma δ13C. Natural variations in the 13C:12C ratio (carbon-13 isotopic abundance [δ13C]) of the food supply have been used to determine the dietary origin and metabolism of fatty acids, especially in the n-3 polyunsaturated fatty acid (PUFA) biosynthesis pathway. However, n-6 PUFA metabolism following linoleic acid (LNA) intake remains under investigated. Here, we sought to use natural variations in the δ13C signature of dietary oils and fatty fish to analyze n-3 and n-6 PUFA metabolism following dietary changes in LNA and eicosapentaenoic acid (EPA) + docosahexaenoic acid (DHA) in adult humans. Participants with migraine (aged 38.6 ± 2.3 y, 93% female, BMI 27.0 ± 1.1 kg/m2) were randomly assigned to one of three dietary groups for 16 weeks: 1) low omega-3, high omega-6 (H6), 2) high omega-3, high omega-6 (H3H6), or 3) high omega-3, low omega-6 (H3). Blood was collected at baseline, 4, 10, and 16 weeks. Plasma PUFA concentrations and δ13C were determined. The H6 intervention exhibited increases in plasma LNA δ13C signature over time; meanwhile, plasma LNA concentrations were unchanged. No changes in plasma arachidonic acid δ13C or concentration were observed. Participants on the H3H6 and H3 interventions demonstrated increases in plasma EPA and DHA concentration over time. Plasma δ13C-EPA increased in total lipids of the H3 group and phospholipids of the H3H6 group compared to baseline. Compound-specific isotope analysis supports a tracer-free technique that can track metabolism of dietary fatty acids in humans, provided that the isotopic signature of the dietary source is sufficiently different from plasma δ13C.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,005 | 0,023 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 tête enseignante, 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 ».