Measuring maternal body composition by biomedical impedance can predict risk for gestational diabetes mellitus: a retrospective study among 22,223 women.

OBJECTIVES: This study aimed to identify which element of body composition measurements taken before 17th week gestation was the strongest risk factor for gestational diabetes mellitus (GDM) in Chinese pregnant women. DESIGN AND SETTING: A retrospective study was performed using data retrieved from the Electronic Medical Record database of Chongqing Health Center for Women and Children (China) from January 2014 to December 2015. PARTICIPANTS: A total of 22,223 women were included with singleton pregnancies and no preexisting diabetes who underwent bioelectrical impedance analysis (BIA) before 17 gestational weeks and 75-g OGTT at 24-28 gestational weeks. RESULTS: The prevalence of GDM from 2014 to 2015 was 27.13% (IADPSG). All indicators of BIA (total body water, fat mass, fat-free mass, percent body fat, muscle mass, visceral fat levels, proteins, bone minerals, basal metabolic rate, lean trunk mass), age, weight and body mass index (BMI) were risk factors that significantly increased the occurrence of GDM (p < .001 for all). Women older than 30 years or with a BMI more than 23, had a significantly higher GDM prevalence (34.89% and 34.77%). After adjusted covariates, visceral fat levels at the third quartile, the ORs of GDM were 1.142 (95% CI 1.032-1.263) in model I and 1.419 (95% CI 1.274-1.581) in model II used the first quartile as reference (p < .05 for both); bone minerals at the third quartile, the ORs of GDM were 1.124 (95% CI 1.020-1.238) in model I and 1.311 (95% CI 1.192-1.442) in model II (p < .05 for both). After adjusted for age, visceral fat levels and bone minerals, OR of GDM for percent body fat more than 28.77% at the third quartile was 1.334 (95% CI 1.201-1.482) in model II (p < .05 for both). CONCLUSIONS: Visceral fat levels, bone minerals and percent body fat were significantly associated with an increased risk of GDM, providing the reference ranges of visceral fat levels, bone minerals and percent body fat as predictive factors for Chinese women to estimate the risk of GDM by BIA during pregnancy.

Using the Metabolome to Understand the Mechanisms Linking Chronic Arsenic Exposure to Microglia Activation, and Learning and Memory Impairment.

The activation of microglia is a hallmark of neuroinflammation and contributes to various neurodegenerative diseases. Chronic inorganic arsenic exposure is associated with impaired cognitive ability and increased risk of neurodegeneration. The present study aimed to investigate whether chronic inorganic arsenic-induced learning and memory impairment was associated with microglial activation, and how organic (DMAV 600 µM, MMAV 0.1 µM) and inorganic arsenic (NaAsO2 0.6 µM) affect the microglia. Male C57BL/6J mice were divided into two groups: a control group and a group exposed to arsenic in their drinking water (50 mg/L NaAsO2 for 24 weeks). The Morris water maze was performed to analyze neuro-behavior and transmission electron microscopy was used to assess alterations in cellular ultra-structures. Hematoxylin-eosin and Nissl staining were used to observe pathological changes in the cerebral cortex and hippocampus. Flow cytometry was used to reveal the polarization of the arsenic-treated microglia phenotype and GC-MS was used to assess metabolomic differences in the in vitro microglia BV-2 cell line model derived from mice. The results showed learning and memory impairments and activation of microglia in the cerebral cortex and dentate gyrus (DG) zone of the hippocampus, in mice chronically exposed to arsenic. Flow cytometry demonstrated that BV-2 cells were activated with the treatment of different arsenic species. The GC-MS data showed three important metabolites to be at different levels according to the different arsenic species used to treat the microglia. These included tyrosine, arachidonic acid, and citric acid. Metabolite pathway analysis showed that a metabolic pathways associated with tyrosine metabolism, the dopaminergic synapse, Parkinson's disease, and the citrate cycle were differentially affected when comparing exposure to organic arsenic and inorganic arsenic. Organic arsenic MMAV was predominantly pro-inflammatory, and inorganic arsenic exposure contributed to energy metabolism disruptions in BV-2 microglia. Our findings provide novel insight into understanding the neurotoxicity mechanisms of chronic arsenic exposure and reveal the changes of the metabolome in response to exposure to different arsenic species in the microglia.