Serum ceramides in early pregnancy as predictors of gestational diabetes.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
15 08 2023
15 08 2023
Historique:
received:
03
05
2023
accepted:
07
08
2023
medline:
17
8
2023
pubmed:
16
8
2023
entrez:
15
8
2023
Statut:
epublish
Résumé
Ceramides contribute to the development of type 2 diabetes but it is uncertain whether they predict gestational diabetes (GDM). In this multicentre case-control study including 1040 women with GDM and 958 non-diabetic controls, early pregnancy (mean 10.7 gestational weeks) concentrations of four ceramides-Cer(d18:1/16:0), Cer(d18:1/18:0), Cer(d18:1/24:0) and Cer(d18:1/24:1)-were determined by a validated mass-spectrometric method from biobanked serum samples. Traditional lipids including total cholesterol, LDL, HDL and triglycerides were measured. Logistic and linear regression and the LASSO logistic regression were used to analyse lipids and clinical risk factors in the prediction of GDM. The concentrations of four targeted ceramides and total cholesterol, LDL and triglycerides were higher and HDL was lower among women with subsequent GDM than among controls. After adjustments, Cer(d18:1/24:0), triglycerides and LDL were independent predictors of GDM, women in their highest quartile had 1.44-fold (95% CI 1.07-1.95), 2.17-fold (95% CI 1.57-3.00) and 1.63-fold (95% CI 1.19-2.24) odds for GDM when compared to their lowest quartiles, respectively. In the LASSO regression modelling ceramides did not appear to markedly improve the predictive performance for GDM alongside with clinical risk factors and triglycerides. However, their adverse alterations highlight the extent of metabolic disturbances involved in GDM.
Identifiants
pubmed: 37582815
doi: 10.1038/s41598-023-40224-3
pii: 10.1038/s41598-023-40224-3
pmc: PMC10427660
doi:
Substances chimiques
Cholesterol, LDL
0
Ceramides
0
Triglycerides
0
Types de publication
Multicenter Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
13274Investigateurs
Risto Kaaja
(R)
Mika Gissler
(M)
Anneli Pouta
(A)
Informations de copyright
© 2023. Springer Nature Limited.
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