Genetic regulatory subnetworks and key regulating genes in rat hippocampus perturbed by prenatal malnutrition: implications for major brain disorders.
11 May 2020-Vol. 12, Iss: 9, pp 8434-8458
TL;DR: The findings suggest that three genetic regulatory subnetworks and thirteen key regulating genes in rat hippocampus perturbed by a prenatal nutrition deficiency may be prenatally involved in the etiologies of major brain disorders, including Alzheimer’s disease, autism, and schizophrenia.
Abstract: Objective Many population studies have shown that maternal prenatal nutrition deficiency may increase the risk of neurodevelopmental disorders in their offspring, but its potential transcriptomic effects on brain development are not clear. We aimed to investigate the transcriptional regulatory interactions between genes in particular pathways responding to the prenatal nutritional deficiency and to explore their effects on neurodevelopment and related disorders. Results We identified three modules in rat hippocampus responding to maternal prenatal nutritional deficiency and found 15 key genes (Hmgn1, Ssbp1, LOC684988, Rpl23, Gga1, Rhobtb2, Dhcr24, Atg9a, Dlgap3, Grm5, Scn2b, Furin, Sh3kbp1, Ubqln1, and Unc13a) related to the rat hippocampus developmental dysregulation, of which Hmgn1, Rhobtb2 and Unc13a related to autism, and Dlgap3, Grm5, Furin and Ubqln1 are related to Alzheimer's disease, and schizophrenia. Transcriptional alterations of the hub genes were confirmed except for Atg9a. Additionally, through modeling miRNA-mRNA-transcription factor interactions for the hub genes, we confirmed a transcription factor, Cebpa, is essential to regulate the expression of Rhobtb2. We did not find singificent singals in the prefrontal cortex responding to maternal prenatal nutritional deficiency. Conclusion These findings demonstrated that these genes with the three modules in rat hippocampus involved in synaptic development, neuronal projection, cognitive function, and learning function are significantly enriched hippocampal CA1 pyramidal neurons and suggest that three genetic regulatory subnetworks and thirteen key regulating genes in rat hippocampus perturbed by a prenatal nutrition deficiency. These genes and related subnetworks may be prenatally involved in the etiologies of major brain disorders, including Alzheimer's disease, autism, and schizophrenia. Methods We compared the transcriptomic differences in the hippocampus and prefrontal cortex between 10 rats with prenatal nutritional deficiency and 10 rats with prenatal normal chow feeding by differential analysis and co-expression network analysis. A network-driven integrative analysis with microRNAs and transcription factors was performed to define significant modules and hub genes responding to prenatal nutritional deficiency. Meanwhile, the module preservation test was conducted between the hippocampus and prefrontal cortex. Expression levels of the hub genes were further validated with a quantitative real-time polymerase chain reaction based on additional 40 pairs of rats.
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TL;DR: It is concluded that folic acid supplementation might be a cheap, safe, and effective method of primary prevention of neural-tube defects but that this must be confirmed in a large, multicentre trial.
Abstract: A randomized controlled double-blind trial was undertaken in south Wales to prevent the recurrence of neural-tube defects in women who had had one child with a neural-tube defect. Sixty women were allocated before conception to take 4 mg of folic acid a day before and during early pregnancy and 44 complied with these instructions. Fifty-one women were allocated to placebo treatment. There were no recurrences among the compliant mothers but two among the non-compliers and four among the women in the placebo group. Thus there were no recurrences among those who received supplementation and six among those who did not; this difference is significant (p = 0.04). It is concluded that folic acid supplementation might be a cheap, safe, and effective method of primary prevention of neural-tube defects but that this must be confirmed in a large, multicentre trial.
83 citations
Mayo Clinic1, Erasmus University Rotterdam2, University of California, San Francisco3, University of British Columbia4, University of Western Ontario5, Karolinska Institutet6, German Center for Neurodegenerative Diseases7, University of Tübingen8, University of Rostock9, Ludwig Maximilian University of Munich10, Technische Universität München11, University of Texas Southwestern Medical Center12, King's College London13, University of Cambridge14, Northwestern University15, University of Texas Health Science Center at San Antonio16, University of Arizona17, Columbia University18, Indiana University – Purdue University Indianapolis19, Medical Research Council20, University of Pennsylvania21, University of Manchester22, University of Sydney23, United States Department of Veterans Affairs24, University of Toronto25, University Health Network26, Washington University in St. Louis27, University of Pittsburgh28, University of New South Wales29, Emory University30, University College London31
TL;DR: A possible role for genes functioning within the TBK1-related immune pathway (e.g., DHX58, TRIM21, IRF7) in the genetic etiology of FTLD-TDP is discovered and strongly implicates the immune pathway in FTLD/TDP pathogenesis.
Abstract: Frontotemporal lobar degeneration with neuronal inclusions of the TAR DNA-binding protein 43 (FTLD-TDP) represents the most common pathological subtype of FTLD. We established the international FTLD-TDP whole-genome sequencing consortium to thoroughly characterize the known genetic causes of FTLD-TDP and identify novel genetic risk factors. Through the study of 1131 unrelated Caucasian patients, we estimated that C9orf72 repeat expansions and GRN loss-of-function mutations account for 25.5% and 13.9% of FTLD-TDP patients, respectively. Mutations in TBK1 (1.5%) and other known FTLD genes (1.4%) were rare, and the disease in 57.7% of FTLD-TDP patients was unexplained by the known FTLD genes. To unravel the contribution of common genetic factors to the FTLD-TDP etiology in these patients, we conducted a two-stage association study comprising the analysis of whole-genome sequencing data from 517 FTLD-TDP patients and 838 controls, followed by targeted genotyping of the most associated genomic loci in 119 additional FTLD-TDP patients and 1653 controls. We identified three genome-wide significant FTLD-TDP risk loci: one new locus at chromosome 7q36 within the DPP6 gene led by rs118113626 (p value = 4.82e − 08, OR = 2.12), and two known loci: UNC13A, led by rs1297319 (p value = 1.27e − 08, OR = 1.50) and HLA-DQA2 led by rs17219281 (p value = 3.22e − 08, OR = 1.98). While HLA represents a locus previously implicated in clinical FTLD and related neurodegenerative disorders, the association signal in our study is independent from previously reported associations. Through inspection of our whole-genome sequence data for genes with an excess of rare loss-of-function variants in FTLD-TDP patients (n ≥ 3) as compared to controls (n = 0), we further discovered a possible role for genes functioning within the TBK1-related immune pathway (e.g., DHX58, TRIM21, IRF7) in the genetic etiology of FTLD-TDP. Together, our study based on the largest cohort of unrelated FTLD-TDP patients assembled to date provides a comprehensive view of the genetic landscape of FTLD-TDP, nominates novel FTLD-TDP risk loci, and strongly implicates the immune pathway in FTLD-TDP pathogenesis.
72 citations
TL;DR: In this article, Mendelian randomization (MR) was used to assess how genetically predicted systemic iron status affected T2D risk using a 2-sample MR analysis to obtain a causal estimate.
Abstract: CONTEXT Iron overload is a known risk factor for type 2 diabetes (T2D); however, iron overload and iron deficiency have both been associated with metabolic disorders in observational studies. OBJECTIVE Using mendelian randomization (MR), we assessed how genetically predicted systemic iron status affected T2D risk. METHODS A 2-sample MR analysis was used to obtain a causal estimate. We selected genetic variants strongly associated (P < 5 × 10-8) with 4 biomarkers of systemic iron status from a study involving 48 972 individuals performed by the Genetics of Iron Status consortium and applied these biomarkers to the T2D case-control study (74 124 cases and 824 006 controls) performed by the Diabetes Genetics Replication and Meta-analysis consortium. The simple median, weighted median, MR-Egger, MR analysis using mixture-model, weighted allele scores, and MR based on a Bayesian model averaging approaches were used for the sensitivity analysis. RESULTS Genetically instrumented serum iron (odds ratio [OR]: 1.07; 95% CI, 1.02-1.12), ferritin (OR: 1.19; 95% CI, 1.08-1.32), and transferrin saturation (OR: 1.06; 95% CI, 1.02-1.09) were positively associated with T2D. In contrast, genetically instrumented transferrin, a marker of reduced iron status, was inversely associated with T2D (OR: 0.91; 95% CI, 0.87-0.96). CONCLUSION Genetic evidence supports a causal link between increased systemic iron status and increased T2D risk. Further studies involving various ethnic backgrounds based on individual-level data and studies regarding the underlying mechanism are warranted for reducing the risk of T2D.
63 citations
TL;DR: In this paper, the authors investigated the short-term association between ambient temperature and mental health hospitalizations in Bern, Switzerland, and found that the hospitalization risk increased linearly by 4.0% for every 10°C increase in mean daily temperature.
Abstract: Background Psychiatric disorders constitute a major public health concern that are associated with substantial health and socioeconomic burden. Psychiatric patients may be more vulnerable to high temperatures, which under current climate change projections will most likely increase the burden of this public health concern. Objective This study investigated the short-term association between ambient temperature and mental health hospitalizations in Bern, Switzerland. Methods Daily hospitalizations for mental disorders between 1973 and 2017 were collected from the University Hospital of Psychiatry and Psychotherapy in Bern. Population-weighted daily mean ambient temperatures were derived for the catchment area of the hospital from 2.3-km gridded weather maps. Conditional quasi-Poisson regression with distributed lag linear models were applied to assess the association up to three days after the exposure. Stratified analyses were conducted by age, sex, and subdiagnosis, and by subperiods (1973–1989 and 1990–2017). Additional subanalyses were performed to assess whether larger risks were found during the warm season or were due to heatwaves. Results The study included a total number of 88,996 hospitalizations. Overall, the hospitalization risk increased linearly by 4.0% (95% CI 2.0%, 7.0%) for every 10°C increase in mean daily temperature. No evidence of a nonlinear association or larger risks during the warm season or heatwaves was found. Similar estimates were found across for all sex and age categories, and larger risks were found for hospitalizations related to developmental disorders (29.0%; 95% CI 9.0%, 54.0%), schizophrenia (10.0%; 95% CI 4.0%, 15.0%), and for the later rather than the earlier period (5.0%; 95% CI 2.0%, 8.0% vs. 2.0%; 95% CI -3.0%, 8.0%). Conclusions Our findings suggest that increasing temperatures could negatively affect mental status in psychiatric patients. Specific public health policies are urgently needed to protect this vulnerable population from the effects of climate change.
15 citations
TL;DR: In this article, the authors used the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool to construct a protein-protein interaction (PPI) network, followed by the use of Molecular Complex Detection (MCODE) plug-ins in Cytoscape software to identify hub genes.
Abstract: This investigation seeks to dissect coronary artery disease molecular target candidates along with its underlying molecular mechanisms. Data on patients with CAD across three separate array data sets, GSE66360, GSE19339 and GSE97320 were extracted. The gene expression profiles were obtained by normalizing and removing the differences between the three data sets, and important modules linked to coronary heart disease were identified using weighted gene co-expression network analysis (WGCNA). Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and genomes (KEGG) pathway enrichment analyses were applied in order to identify statistically significant genetic modules with the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool (version 6.8; http://david.abcc.ncifcrf.gov
). The online STRING tool was used to construct a protein–protein interaction (PPI) network, followed by the use of Molecular Complex Detection (MCODE) plug-ins in Cytoscape software to identify hub genes. Two significant modules (green-yellow and magenta) were identified in the CAD samples. Genes in the magenta module were noted to be involved in inflammatory and immune-related pathways, based on GO and KEGG enrichment analyses. After the MCODE analysis, two different MCODE complexes were identified in the magenta module, and four hub genes (ITGAM, degree = 39; CAMP, degree = 37; TYROBP, degree = 28; ICAM1, degree = 18) were uncovered to be critical players in mediating CAD. Independent verification data as well as our RT-qPCR results were highly consistent with the above finding. ITGAM, CAMP, TYROBP and ICAM1 are potential targets in CAD. The underlying mechanism may be related to the transendothelial migration of leukocytes and the immune response.
14 citations
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TL;DR: The hierarchical model of Lonnstedt and Speed (2002) is developed into a practical approach for general microarray experiments with arbitrary numbers of treatments and RNA samples and the moderated t-statistic is shown to follow a t-distribution with augmented degrees of freedom.
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11,864 citations
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5,569 citations
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TL;DR: The authors' data provide clues as to how neurons and astrocytes differ in their ability to dynamically regulate glycolytic flux and lactate generation attributable to unique splicing of PKM2, the gene encoding the glycoleytic enzyme pyruvate kinase.
Abstract: The major cell classes of the brain differ in their developmental processes, metabolism, signaling, and function To better understand the functions and interactions of the cell types that comprise these classes, we acutely purified representative populations of neurons, astrocytes, oligodendrocyte precursor cells, newly formed oligodendrocytes, myelinating oligodendrocytes, microglia, endothelial cells, and pericytes from mouse cerebral cortex We generated a transcriptome database for these eight cell types by RNA sequencing and used a sensitive algorithm to detect alternative splicing events in each cell type Bioinformatic analyses identified thousands of new cell type-enriched genes and splicing isoforms that will provide novel markers for cell identification, tools for genetic manipulation, and insights into the biology of the brain For example, our data provide clues as to how neurons and astrocytes differ in their ability to dynamically regulate glycolytic flux and lactate generation attributable to unique splicing of PKM2, the gene encoding the glycolytic enzyme pyruvate kinase This dataset will provide a powerful new resource for understanding the development and function of the brain To ensure the widespread distribution of these datasets, we have created a user-friendly website (http://webstanfordedu/group/barres_lab/brain_rnaseqhtml) that provides a platform for analyzing and comparing transciption and alternative splicing profiles for various cell classes in the brain
3,891 citations
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