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Zou ZL, Ye Y, Zhou B, Zhang Y. Identification and characterization of noncoding RNAs-associated competing endogenous RNA networks in major depressive disorder. World J Psychiatry 2023; 13:36-49. [PMID: 36925948 PMCID: PMC10011943 DOI: 10.5498/wjp.v13.i2.36] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 12/06/2022] [Accepted: 01/23/2023] [Indexed: 02/17/2023] Open
Abstract
BACKGROUND Major depressive disorder (MDD) is a common and serious mental illness. Many novel genes in MDD have been characterized by high-throughput methods such as microarrays or sequencing. Recently, noncoding RNAs (ncRNAs) were suggested to be involved in the complicated environmental-genetic regulatory network of MDD occurrence; however, the interplay among RNA species, including protein-coding RNAs and ncRNAs, in MDD remains unclear.
AIM To investigate the RNA expression datasets downloaded from a public database and construct a network based on differentially expressed long noncoding RNA (lncRNAs), microRNAs (miRNAs), and mRNAs between MDD and controls.
METHODS Gene expression data were searched in NCBI Gene Expression Omnibus using the search term “major depressive disorder.” Six array datasets from humans were related to the search term: GSE19738, GSE32280, GSE38206, GSE52790, GSE76826, and GSE81152. These datasets were processed for initial assessment and subjected to quality control and differential expression analysis. Differentially expressed lncRNAs, miRNAs, and mRNAs were determined, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed, and protein-protein interaction network was generated. The results were analyzed for their association with MDD.
RESULTS After analysis, 3 miRNAs, 12 lncRNAs, and 33 mRNAs were identified in the competing endogenous RNA network. Two of these miRNAs were earlier shown to be involved in psychiatric disorders, and differentially expressed mRNAs were found to be highly enriched in pathways related to neurogenesis and neuroplasticity as per Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. The expression of hub gene fatty acid 2-hydroxylase was enriched, and the encoded protein was found to be involved in myelin formation, indicating that neurological development and signal transduction are involved in MDD pathogenesis.
CONCLUSION The present study presents candidate ncRNAs involved in the neurogenesis and neuroplasticity pathways related to MDD.
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Affiliation(s)
- Zhi-Li Zou
- Department of Psychosomatic, Sichuan Academy of Medical Science & Sichuan Provincial People’s Hospital, Chengdu 610072, Sichuan Province, China
| | - Yu Ye
- Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu 611130, Sichuan Province, China
| | - Bo Zhou
- Department of Psychosomatic, Sichuan Academy of Medical Science & Sichuan Provincial People’s Hospital, Chengdu 610072, Sichuan Province, China
| | - Yuan Zhang
- Personalized Drug Therapy Key Laboratory of Sichuan Province, Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, Chengdu 610072, Sichuan Province, China
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Olsen AL, Feany MB. Glial α-synuclein promotes neurodegeneration characterized by a distinct transcriptional program in vivo. Glia 2019; 67:1933-1957. [PMID: 31267577 DOI: 10.1002/glia.23671] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 04/29/2019] [Accepted: 06/18/2019] [Indexed: 12/15/2022]
Abstract
α-Synucleinopathies are neurodegenerative diseases that are characterized pathologically by α-synuclein inclusions in neurons and glia. The pathologic contribution of glial α-synuclein in these diseases is not well understood. Glial α-synuclein may be of particular importance in multiple system atrophy (MSA), which is defined pathologically by glial cytoplasmic α-synuclein inclusions. We have previously described Drosophila models of neuronal α-synucleinopathy, which recapitulate key features of the human disorders. We have now expanded our model to express human α-synuclein in glia. We demonstrate that expression of α-synuclein in glia alone results in α-synuclein aggregation, death of dopaminergic neurons, impaired locomotor function, and autonomic dysfunction. Furthermore, co-expression of α-synuclein in both neurons and glia worsens these phenotypes as compared to expression of α-synuclein in neurons alone. We identify unique transcriptomic signatures induced by glial as opposed to neuronal α-synuclein. These results suggest that glial α-synuclein may contribute to the burden of pathology in the α-synucleinopathies through a cell type-specific transcriptional program. This new Drosophila model system enables further mechanistic studies dissecting the contribution of glial and neuronal α-synuclein in vivo, potentially shedding light on mechanisms of disease that are especially relevant in MSA but also the α-synucleinopathies more broadly.
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Affiliation(s)
- Abby L Olsen
- Department of Neurology, Brigham and Women's Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Mel B Feany
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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Shu L, Meng Q, Diamante G, Tsai B, Chen YW, Mikhail A, Luk H, Ritz B, Allard P, Yang X. Prenatal Bisphenol A Exposure in Mice Induces Multitissue Multiomics Disruptions Linking to Cardiometabolic Disorders. Endocrinology 2019; 160:409-429. [PMID: 30566610 PMCID: PMC6349005 DOI: 10.1210/en.2018-00817] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2018] [Accepted: 12/13/2018] [Indexed: 12/21/2022]
Abstract
The health impacts of endocrine-disrupting chemicals (EDCs) remain debated, and their tissue and molecular targets are poorly understood. In this study, we leveraged systems biology approaches to assess the target tissues, molecular pathways, and gene regulatory networks associated with prenatal exposure to the model EDC bisphenol A (BPA). Prenatal BPA exposure at 5 mg/kg/d, a dose below most reported no-observed-adverse-effect levels, led to tens to thousands of transcriptomic and methylomic alterations in the adipose, hypothalamus, and liver tissues in male offspring in mice, with cross-tissue perturbations in lipid metabolism as well as tissue-specific alterations in histone subunits, glucose metabolism, and extracellular matrix. Network modeling prioritized main molecular targets of BPA, including Pparg, Hnf4a, Esr1, Srebf1, and Fasn as well as numerous less studied targets such as Cyp51 and long noncoding RNAs across tissues, Fa2h in hypothalamus, and Nfya in adipose tissue. Lastly, integrative analyses identified the association of BPA molecular signatures with cardiometabolic phenotypes in mouse and human. Our multitissue, multiomics investigation provides strong evidence that BPA perturbs diverse molecular networks in central and peripheral tissues and offers insights into the molecular targets that link BPA to human cardiometabolic disorders.
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Affiliation(s)
- Le Shu
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, California
- Molecular, Cellular, and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, Los Angeles, California
| | - Qingying Meng
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, California
| | - Graciel Diamante
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, California
| | - Brandon Tsai
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, California
| | - Yen-Wei Chen
- Molecular Toxicology Interdepartmental Program, University of California, Los Angeles, Los Angeles, California
| | - Andrew Mikhail
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, California
| | - Helen Luk
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, California
| | - Beate Ritz
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California
- Institute for Society and Genetics, University of California, Los Angeles, Los Angeles, California
| | - Patrick Allard
- Molecular Toxicology Interdepartmental Program, University of California, Los Angeles, Los Angeles, California
- Institute for Society and Genetics, University of California, Los Angeles, Los Angeles, California
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, California
- Molecular, Cellular, and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, Los Angeles, California
- Molecular Toxicology Interdepartmental Program, University of California, Los Angeles, Los Angeles, California
- Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, Los Angeles, California
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Czysz AH, South C, Gadad BS, Arning E, Soyombo A, Bottiglieri T, Trivedi MH. Can targeted metabolomics predict depression recovery? Results from the CO-MED trial. Transl Psychiatry 2019; 9:11. [PMID: 30664617 PMCID: PMC6341111 DOI: 10.1038/s41398-018-0349-6] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 07/02/2018] [Accepted: 07/14/2018] [Indexed: 12/18/2022] Open
Abstract
Metabolomics is a developing and promising tool for exploring molecular pathways underlying symptoms of depression and predicting depression recovery. The AbsoluteIDQ™ p180 kit was used to investigate whether plasma metabolites (sphingomyelins, lysophosphatidylcholines, phosphatidylcholines, and acylcarnitines) from a subset of participants in the Combining Medications to Enhance Depression Outcomes (CO-MED) trial could act as predictors or biologic correlates of depression recovery. Participants in this trial were assigned to one of three pharmacological treatment arms: escitalopram monotherapy, bupropion-escitalopram combination, or venlafaxine-mirtazapine combination. Plasma was collected at baseline in 159 participants and again 12 weeks later at study exit in 83 of these participants. Metabolite concentrations were measured and combined with clinical and sociodemographic variables using the hierarchical lasso to simultaneously model whether specific metabolites are particularly informative of depressive recovery. Increased baseline concentrations of phosphatidylcholine C38:1 showed poorer outcome based on change in the Quick Inventory of Depressive Symptoms (QIDS). In contrast, an increased ratio of hydroxylated sphingomyelins relative to non-hydroxylated sphingomyelins at baseline and a change from baseline to exit suggested a better reduction of symptoms as measured by QIDS score. All metabolite-based models performed superior to models only using clinical and sociodemographic variables, suggesting that metabolomics may be a valuable tool for predicting antidepressant outcomes.
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Affiliation(s)
- Andrew H. Czysz
- 0000 0000 9482 7121grid.267313.2Department of Psychiatry, University of Texas Southwestern, Dallas, TX 75390 USA
| | - Charles South
- 0000 0000 9482 7121grid.267313.2Department of Psychiatry, University of Texas Southwestern, Dallas, TX 75390 USA
| | - Bharathi S. Gadad
- 0000 0000 9482 7121grid.267313.2Department of Psychiatry, University of Texas Southwestern, Dallas, TX 75390 USA
| | - Erland Arning
- 0000 0004 4685 2620grid.486749.0Center of Metabolomics, Institute of Metabolic Disease, Baylor Scott and White Research Institute, 3812 Elm Street, Dallas, TX 75226 USA
| | - Abigail Soyombo
- 0000 0000 9482 7121grid.267313.2Department of Psychiatry, University of Texas Southwestern, Dallas, TX 75390 USA
| | - Teodoro Bottiglieri
- 0000 0004 4685 2620grid.486749.0Center of Metabolomics, Institute of Metabolic Disease, Baylor Scott and White Research Institute, 3812 Elm Street, Dallas, TX 75226 USA
| | - Madhukar H. Trivedi
- 0000 0000 9482 7121grid.267313.2Department of Psychiatry, University of Texas Southwestern, Dallas, TX 75390 USA
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Bettencourt C, Forabosco P, Wiethoff S, Heidari M, Johnstone DM, Botía JA, Collingwood JF, Hardy J, Milward EA, Ryten M, Houlden H. Gene co-expression networks shed light into diseases of brain iron accumulation. Neurobiol Dis 2016; 87:59-68. [PMID: 26707700 PMCID: PMC4731015 DOI: 10.1016/j.nbd.2015.12.004] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Revised: 11/18/2015] [Accepted: 12/14/2015] [Indexed: 12/21/2022] Open
Abstract
Aberrant brain iron deposition is observed in both common and rare neurodegenerative disorders, including those categorized as Neurodegeneration with Brain Iron Accumulation (NBIA), which are characterized by focal iron accumulation in the basal ganglia. Two NBIA genes are directly involved in iron metabolism, but whether other NBIA-related genes also regulate iron homeostasis in the human brain, and whether aberrant iron deposition contributes to neurodegenerative processes remains largely unknown. This study aims to expand our understanding of these iron overload diseases and identify relationships between known NBIA genes and their main interacting partners by using a systems biology approach. We used whole-transcriptome gene expression data from human brain samples originating from 101 neuropathologically normal individuals (10 brain regions) to generate weighted gene co-expression networks and cluster the 10 known NBIA genes in an unsupervised manner. We investigated NBIA-enriched networks for relevant cell types and pathways, and whether they are disrupted by iron loading in NBIA diseased tissue and in an in vivo mouse model. We identified two basal ganglia gene co-expression modules significantly enriched for NBIA genes, which resemble neuronal and oligodendrocytic signatures. These NBIA gene networks are enriched for iron-related genes, and implicate synapse and lipid metabolism related pathways. Our data also indicates that these networks are disrupted by excessive brain iron loading. We identified multiple cell types in the origin of NBIA disorders. We also found unforeseen links between NBIA networks and iron-related processes, and demonstrate convergent pathways connecting NBIAs and phenotypically overlapping diseases. Our results are of further relevance for these diseases by providing candidates for new causative genes and possible points for therapeutic intervention.
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Affiliation(s)
- Conceição Bettencourt
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK; Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK.
| | - Paola Forabosco
- Istituto di Ricerca Genetica e Biomedica CNR, Cagliari, Italy
| | - Sarah Wiethoff
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK; Center for Neurology and Hertie Institute for Clinical Brain Research, Eberhard-Karls-University, Tübingen, Germany
| | - Moones Heidari
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia; Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, The University of Newcastle, Callaghan, NSW, Australia
| | - Daniel M Johnstone
- Bosch Institute and Discipline of Physiology, University of Sydney, NSW, Australia
| | - Juan A Botía
- Department of Medical and Molecular Genetics, King's College London, London, UK
| | | | - John Hardy
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Elizabeth A Milward
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia; Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, The University of Newcastle, Callaghan, NSW, Australia
| | - Mina Ryten
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK; Department of Medical and Molecular Genetics, King's College London, London, UK
| | - Henry Houlden
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
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