The relationship among GNB3 rs5443, PNPLA3 rs738409, GCKR rs780094 gene polymorphisms, type of maternal gestational weight gain and neonatal outcomes (STROBE-compliant article).


Journal

Medicine
ISSN: 1536-5964
Titre abrégé: Medicine (Baltimore)
Pays: United States
ID NLM: 2985248R

Informations de publication

Date de publication:
Jul 2019
Historique:
entrez: 16 7 2019
pubmed: 16 7 2019
medline: 30 7 2019
Statut: ppublish

Résumé

The gestational weight gain is determined by food habits, environmental and genetic factors.The aims of this paper were to establish relationships between maternal gene polymorphisms (patatin-like phospholipase domain-containing protein 3 rs738409 [PNPLA3 rs738409], glucokinase regulatory protein rs780094 [GCKR rs780094], and guanine nucleotide-binding protein rs5443 [GNB3 rs5443]) and mothers' gestational weight gain, but also neonatal outcomes (birth weight, length, and ponderal index [PI]).We performed a cross-sectional study in a sample of 158 mothers and their product of conception' in an Obstetrics-Gynecology Clinic from Romania. We divided the pregnant women according to the Institute of Medicine recommendations into 3 subgroups: (1) insufficient gestational weight gain; (2) normal gestational weight gain; and (3) excessive gestational weight gain.The gestational weight gain among pregnant women included in this study was classified as insufficient (10.1%), normal (31%), and excessive (58.9%). We found a tendency towards statistical significance for mothers that were overweight or obese before pregnancy to present an excessive gestational weight gain as compared to the normal weight ones. Similarly, we identified a tendency for statistical significance regarding the association between the variant genotype of GNB3 rs5443 and excessive gestational weight gain. We noticed differences that tended to be statistical significant concerning aspartate aminotransferase values between the 3 subgroups, mothers with excessive gestational weight gain having higher values than mothers with normal gestational weight gain (median, IQR: 22.89[17.53; 31.59] for mothers with excessive gestational weight gain versus 22.71[18.58; 27.37] for mothers with normal gestational weight gain). In mothers with excessive gestational weight gain, we found a significant association between the variant genotype of PNPLA3 rs738409 polymorphism and neonatal PI noticing a decrease of this index in case of newborns from mothers carrying the variant genotype.Excessive gestational weight gain was noticed in pregnant women that were obese and overweight before pregnancy. We found a positive association between the variant genotype of GNB3 rs5443 polymorphism and excessive gestational weight gain. Similarly, the presence of variant genotype of PNPLA3 rs738409 in mothers was associated with a lower PI in their newborns. Our study pointed out the most important factors that influence gestational weight gain and related birth outcomes.

Identifiants

pubmed: 31305457
doi: 10.1097/MD.0000000000016414
pii: 00005792-201907120-00070
pmc: PMC6641780
doi:

Substances chimiques

Adaptor Proteins, Signal Transducing 0
GCKR protein, human 0
GNB3 protein, human 0
Membrane Proteins 0
Lipase EC 3.1.1.3
adiponutrin, human EC 3.1.1.3
Heterotrimeric GTP-Binding Proteins EC 3.6.5.1

Types de publication

Journal Article

Langues

eng

Pagination

e16414

Références

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Auteurs

Claudiu Mărginean (C)

Department of Obstetrics and Gynecology.

Cristina Oana Mărginean (CO)

Department of Pediatrics, University of Medicine, Pharmacy, Sciences and Technology Târgu Mureş.

Claudia Bănescu (C)

Genetics Laboratory, Center for Advanced Medical and Pharmaceutical Research, University of Medicine, Pharmacy, Sciences and Technology Târgu Mureş.

Lorena Elena Meliţ (LE)

Department of Pediatrics, University of Medicine, Pharmacy, Sciences and Technology Târgu Mureş.

Florin Tripon (F)

Genetics Laboratory, Center for Advanced Medical and Pharmaceutical Research, University of Medicine, Pharmacy, Sciences and Technology Târgu Mureş.

Mihaela Iancu (M)

Department of Medical Informatics and Biostatistics, Iuliu Haţieganu University of Medicine and Pharmacy Cluj Napoca, Romania.

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