The etiology and pathophysiology of schizophrenia remain unknown. A parallel transcriptomics, proteomics and metabolomics approach was employed on human brain tissue to explore the molecular disease signatures. Almost half the altered proteins identified by proteomics were associated with mitochondrial function and oxidative stress responses. This was mirrored by transcriptional and metabolite perturbations. Cluster analysis of transcriptional alterations showed that genes related to energy metabolism and oxidative stress differentiated almost 90% of schizophrenia patients from controls, while confounding drug effects could be ruled out. We propose that oxidative stress and the ensuing cellular adaptations are linked to the schizophrenia disease process and hope that this new disease concept may advance the approach to treatment, diagnosis and disease prevention of schizophrenia and related syndromes.
Transcript changes and altered pathways in schizophrenia prefrontal cortex. (a) Mitochondria are the most affected cellular components at the transcript level in schizophrenia. Cellular localization of the significantly altered genes (both up-and downregulated) that passed RMA and filtering procedures were analyzed and visualized using GO Surfer (http://biosun1.harvard.edu/complab/gosurfer/). Branches and nodes represent pathways containing greater than five genes. Significantly altered 'cellular components' (Po0.05) are highlighted in red and their categories are indicated. (b) Metabolic categories found to be most significantly altered at the transcript level. EASE (http://david.niaid.nih.gov/david/ease.htm) was used for pathway analysis of microarray results and to determine significantly up-and/or downregulated GO biological processes and KEGG metabolic pathways. (c) Hierarchical clustering tree of schizophrenia (vertical blue lines) and controls (vertical gray lines) microarray chips on the basis of 59 significantly altered genes related to energy metabolism and oxidative stress. Drug-naive schizophrenia patients are denoted by ** (n ¼ 7), while minimally treated patients are marked by * (o6000 lifetime fluphenazine units; n ¼ 4). Note that the schizophrenia group appears to fall into two subclusters with respect to lowered transcript expression as indicated by the prominent blue shading. For more information on this topic, please see the article by Prabakaran et al on pp 684-697.
The mechanisms by which trisomy 21 leads to the characteristic Down syndrome (DS) phenotype are unclear. We used whole genome microarrays to characterize for the first time the transcriptome of human adult brain tissue (dorsolateral prefrontal cortex) from seven DS subjects and eight controls. These data were coanalyzed with a publicly available dataset from fetal DS tissue and functional profiling was performed to identify the biological processes central to DS and those that may be related to late onset pathologies, particularly Alzheimer disease neuropathology. A total of 685 probe sets were differentially expressed between adult DS and control brains at a stringent significance threshold (adjusted p value (q) < 0.005), 70% of these being up-regulated in DS. Over 25% of genes on chromosome 21 were differentially expressed in comparison to a median of 4.4% for all chromosomes. The unique profile of up-regulation on chromosome 21, consistent with primary dosage effects, was accompanied by widespread transcriptional disruption. The critical Alzheimer disease gene, APP, located on chromosome 21, was not found to be up-regulated in adult brain by microarray or QPCR analysis. However, numerous other genes functionally linked to APP processing were dysregulated. Functional profiling of genes dysregulated in both fetal and adult datasets identified categories including development (notably Notch signaling and Dlx family genes), lipid transport, and cellular proliferation. In the adult brain these processes were concomitant with cytoskeletal regulation and vesicle trafficking categories, and increased immune response and oxidative stress response, which are likely linked to the development of Alzheimer pathology in individuals with DS.
IntroductionMammary gland development during the pregnancy cycle is characterized by successive phases of cell growth, differentiation, high metabolic activity and apoptosis. At the ultrastructural level this includes dramatic changes in tissue architecture, involving ductal epithelial branching and morphogenesis, invasion of tissue compartments, vascularization and subsequent organized remodelling. These events are highly reproducible and strictly controlled at the transcriptional level by circulating hormones and locally derived factors [1]. Thus, many transcription factors have been shown either to directly affect this developmental program or to exhibit altered activity at specific stages in the pregnancy cycle [1]. CAM = cell adhesion molecule; C/ebp = CAAT-enhancer binding protein; IGF = insulin-like growth factor; IL = interleukin; LIF = leukaemia inhibitory factor; LPS = lipopolysaccharide; NF-κB = nuclear factor-κB; Stat = signal transducer and activator of transcription. Breast Cancer ResearchVol 6 No 2 Clarkson et al. Research articleGene expression profiling of mammary gland development reveals putative roles for death receptors and immune mediators in post-lactational regression Richard AbstractIntroduction In order to gain a better understanding of the molecular processes that underlie apoptosis and tissue regression in mammary gland, we undertook a large-scale analysis of transcriptional changes during the mouse mammary pregnancy cycle, with emphasis on the transition from lactation to involution.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.