S100B Maternal Blood Levels in Gestational Diabetes Mellitus Are Birthweight, Gender and Delivery Mode Dependent.
Laura AbellaEbe D'AdamoMariachiara StrozziJoan Sanchez-de-ToledoMiriam Perez-CruzOlga GómezErnesto AbellaMaurizio CassinariRoberto GuaschinoLaura MazzuccoAntonio MaconiStefania TestaCristian ZanelliMarika PerrottaPatacchiola RobertaNeri Costanza RenataGiorgia GasparroniEster VitacolonnaFrancesco ChiarelliDiego GazzoloPublished in: International journal of environmental research and public health (2022)
Gestational Diabetes Mellitus (GDM) is one of the main causes of perinatal mortality/morbidity. Today, a parameter offering useful information on fetal central nervous system (CNS) development/damage is eagerly awaited. We investigated the role of brain-protein S100B in the maternal blood of GDM pregnancies by means of a prospective case-control study in 646 pregnancies (GDM: n = 106; controls: n = 530). Maternal blood samples for S100B measurement were collected at four monitoring time-points from 24 weeks of gestation to term. Data was corrected for gender and delivery mode and correlated with gestational age and weight at birth. Results showed higher ( p < 0.05) S100B from 24 to 32 weeks and at term in GDM fetuses than controls. Higher ( p < 0.05) S100B was observed in GDM male new-borns than in females from 24 to 32 weeks and at term, in GDM cases delivering vaginally than by caesarean section. Finally, S100B positively correlated with gestational age and weight at birth (R = 0.27; R = 0.37, respectively; p < 0.01). The present findings show the usefulness of S100B in CNS to monitor high-risk pregnancies during perinatal standard-of-care procedures. The results suggest that further investigations into its potential role as an early marker of CNS growth/damage in GDM population are needed.
Keyphrases
- gestational age
- birth weight
- preterm birth
- pregnant women
- pregnancy outcomes
- blood brain barrier
- body mass index
- oxidative stress
- physical activity
- palliative care
- weight gain
- healthcare
- cardiovascular events
- high resolution
- cardiovascular disease
- body weight
- health information
- atomic force microscopy
- data analysis
- health insurance
- artificial intelligence