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      Maternal Obesity Affects Fetal Neurodevelopmental and Metabolic Gene Expression: A Pilot Study

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          Abstract

          Objective

          One in three pregnant women in the United States is obese. Their offspring are at increased risk for neurodevelopmental and metabolic morbidity. Underlying molecular mechanisms are poorly understood. We performed a global gene expression analysis of mid-trimester amniotic fluid cell-free fetal RNA in obese versus lean pregnant women.

          Methods

          This prospective pilot study included eight obese (BMI≥30) and eight lean (BMI<25) women undergoing clinically indicated mid-trimester genetic amniocentesis. Subjects were matched for gestational age and fetal sex. Fetuses with abnormal karyotype or structural anomalies were excluded. Cell-free fetal RNA was extracted from amniotic fluid and hybridized to whole genome expression arrays. Genes significantly differentially regulated in 8/8 obese-lean pairs were identified using paired t-tests with the Benjamini-Hochberg correction (false discovery rate of <0.05). Biological interpretation was performed with Ingenuity Pathway Analysis and the BioGPS gene expression atlas.

          Results

          In fetuses of obese pregnant women, 205 genes were significantly differentially regulated. Apolipoprotein D, a gene highly expressed in the central nervous system and integral to lipid regulation, was the most up-regulated gene (9-fold). Apoptotic cell death was significantly down-regulated, particularly within nervous system pathways involving the cerebral cortex. Activation of the transcriptional regulators estrogen receptor, FOS, and STAT3 was predicted in fetuses of obese women, suggesting a pro-estrogenic, pro-inflammatory milieu.

          Conclusion

          Maternal obesity affects fetal neurodevelopmental and metabolic gene expression as early as the second trimester. These findings may have implications for postnatal neurodevelopmental and metabolic abnormalities described in the offspring of obese women.

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          Most cited references58

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          Adenocarcinoma of the vagina. Association of maternal stilbestrol therapy with tumor appearance in young women.

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            Maternal metabolic conditions and risk for autism and other neurodevelopmental disorders.

            We examined whether metabolic conditions (MCs) during pregnancy (diabetes, hypertension, and obesity) are associated with autism spectrum disorder (ASD), developmental delays (DD), or impairments in specific domains of development in the offspring. Children aged 2 to 5 years (517 ASD, 172 DD, and 315 controls) were enrolled in the CHARGE (Childhood Autism Risks from Genetics and the Environment) study, a population-based, case-control investigation between January 2003 and June 2010. Eligible children were born in California, had parents who spoke English or Spanish, and were living with a biological parent in selected regions of California. Children's diagnoses were confirmed by using standardized assessments. Information regarding maternal conditions was ascertained from medical records or structured interview with the mother. All MCs were more prevalent among case mothers compared with controls. Collectively, these conditions were associated with a higher likelihood of ASD and DD relative to controls (odds ratio: 1.61 [95% confidence interval: 1.10-2.37; odds ratio: 2.35 [95% confidence interval: 1.43-3.88], respectively). Among ASD cases, children of women with diabetes had Mullen Scales of Early Learning (MSEL) expressive language scores 0.4 SD lower than children of mothers without MCs (P < .01). Among children without ASD, those exposed to any MC scored lower on all MSEL and Vineland Adaptive Behavior Scales (VABS) subscales and composites by at least 0.4 SD (P < .01 for each subscale/composite). Maternal MCs may be broadly associated with neurodevelopmental problems in children. With obesity rising steadily, these results appear to raise serious public health concerns.
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              Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling.

              Organs and organelles represent core biological systems in mammals, but the diversity in protein composition remains unclear. Here, we combine subcellular fractionation with exhaustive tandem mass spectrometry-based shotgun sequencing to examine the protein content of four major organellar compartments (cytosol, membranes [microsomes], mitochondria, and nuclei) in six organs (brain, heart, kidney, liver, lung, and placenta) of the laboratory mouse, Mus musculus. Using rigorous statistical filtering and machine-learning methods, the subcellular localization of 3274 of the 4768 proteins identified was determined with high confidence, including 1503 previously uncharacterized factors, while tissue selectivity was evaluated by comparison to previously reported mRNA expression patterns. This molecular compendium, fully accessible via a searchable web-browser interface, serves as a reliable reference of the expressed tissue and organelle proteomes of a leading model mammal.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                18 February 2014
                : 9
                : 2
                : e88661
                Affiliations
                [1 ]Mother Infant Research Institute, Tufts Medical Center, Boston, Massachusetts, United States of America
                [2 ]Department of Computer Science, Tufts University, Medford, Massachusetts, United States of America
                [3 ]Department of Pathology and Laboratory Medicine, Tufts Medical Center, Boston, Massachusetts, United States of America
                Virgen Macarena University Hospital, School of Medicine, University of Seville, Spain
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: AGE NLV DWB. Performed the experiments: AGE NLV. Analyzed the data: AGE HCW DWB. Contributed reagents/materials/analysis tools: AGE NLV LH JMC DWB. Wrote the paper: AGE LH DWB. Revised the manuscript critically for important intellectual content: AGE NLV LH HCW JMC DWB.

                [¤a]

                Current address: Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of North Carolina-Chapel Hill, NC, United States of America

                [¤b]

                Current address: Department of Perinatal Medicine, Mercy Hospital for Women, Heidelberg, VIC, Australia

                Article
                PONE-D-13-43087
                10.1371/journal.pone.0088661
                3928248
                24558408
                4aad036f-acd1-4d07-bb4f-6e7136cf5816
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 21 October 2013
                : 11 January 2014
                Page count
                Pages: 11
                Funding
                This research was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) awards R01 HD42053-10 and R01 HD058880. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Genetics
                Genetics of disease
                Molecular genetics
                Genomics
                Genome analysis tools
                Transcriptomes
                Systems biology
                Medicine
                Nutrition
                Obesity
                Obstetrics and gynecology
                Management of high-risk pregnancies
                Pregnancy

                Uncategorized
                Uncategorized

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