253-OR: Maternal Hyperglycemia Is Associated with Offspring Adiposity through Altered Lipid Metabolism in Type 1 Diabetes Pregnancy
Notice bibliographique
Résumé
Objective: Type 1 diabetes in pregnancy is associated with increased birthweight and adiposity in offspring, which may contribute to increased future cardiometabolic risk. We assessed if the effects of maternal hyperglycemia on adiposity were mediated by altered lipid metabolism in pregnancy. Methods and Outcomes: 200 women in the Continuous Glucose Monitoring (CGM) in Pregnant women with Type 1 diabetes Trial (CONCEPTT) had a livebirth. Liquid chromatography-mass spectrometry of maternal serum (12, 24, 34 wks; n=174) and cord blood (n=93) measured 21metabolites. Anthropometry was performed at birth by trained staff. Statistical Analysis: Linear regression of CGM time above range 12, 24, 34 wks (>140 mg/dl; >7.8 mmol/l) with adjustment for maternal age, BMI, parity, ethnicity, education and intervention (birth gestation for offspring) . Significance limit was p=0.0for unselected analysis of all metabolites, p=0.for subset analysis with skinfolds. Results: Maternal hyperglycemia at 24 and 34 weeks was associated with increased triglycerides containing FA (16:0) , (16:1) , (18:0) and (18:1) in maternal serum, considered biomarkers of de novo lipogenesis. Maternal hyperglycemia was associated with abundant carnitines in cord blood, suggesting increased fetal beta oxidation. Lipogenesis-associated species (maternal serum) and carnitines (cord blood) were associated with offspring skinfold sum, independently of maternal hyperglycemia. However, maternal hyperglycemia retained a strong independent association with skinfold sum despite adjustment for potential lipid mediators. Conclusions: Maternal hyperglycemia is associated with features of de novo lipogenesis in the maternal metabolism and beta oxidation in the offspring. Altered lipid metabolism significantly contributes to offspring adiposity but does not appear to solely mediate the relationship between hyperglycemia and body composition in type 1 diabetes pregnancy. Disclosure C.L.Meek: Research Support; Dexcom, Inc. Z.A.Stewart: None. D.Feig: Advisory Panel; Novo Nordisk, Research Support; Apotex. A.Koulman: None. H.R.Murphy: Advisory Panel; Medtronic. Funding This project was funded by Diabetes UK (PG 2017/2278) . The CONCEPTT trial was funded by Juvenile Diabetes Research Foundation (JDRF) grants #17-2011-533, and grants under the JDRF Canadian Clinical Trial Network, a public-private partnership including JDRF and FedDev Ontario and supported by JDRF #80-2010-585. Medtronic supplied the CGM sensors and CGM systems at reduced cost. The study sponsor/funders were not involved in the design of the study; the collection, analysis, and interpretation of data; writing the report; and did not impose any restrictions regarding the publication of the report.CLM is supported by the Diabetes UK Harry Keen Intermediate Clinical Fellowship (DUK-HKF 17/0005712) and the European Foundation for the Study of Diabetes – Novo Nordisk Foundation Future Leaders’ Award (NNF19SA058974) . HRM conducts independent research supported by the National Institute for Health Research (Career Development Fellowship, CDF-2013-06-035) , and is supported by Tommy’s charity. SF and AK acknowledge funding from the BBSRC (BB/M027252/1) . DSF conducts independent research supported by the Canadian Institute for Health Research.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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) | 0,005 | 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 ».