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Hirakawa H, Terao T. The genetic association between bipolar disorder and dementia: a qualitative review. Front Psychiatry 2024; 15:1414776. [PMID: 39228919 PMCID: PMC11368786 DOI: 10.3389/fpsyt.2024.1414776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 08/05/2024] [Indexed: 09/05/2024] Open
Abstract
Bipolar disorder is a chronic disorder characterized by fluctuations in mood state and energy and recurrent episodes of mania/hypomania and depression. Bipolar disorder may be regarded as a neuro-progressive disorder in which repeated mood episodes may lead to cognitive decline and dementia development. In the current review, we employed genome-wide association studies to comprehensively investigate the genetic variants associated with bipolar disorder and dementia. Thirty-nine published manuscripts were identified: 20 on bipolar disorder and 19 on dementia. The results showed that the genes CACNA1C, GABBR2, SCN2A, CTSH, MSRA, and SH3PXD2A were overlapping between patients with bipolar disorder and dementia. In conclusion, the genes CACNA1C, GABBR2, SCN2A, CTSH, MSRA, and SH3PXD2A may be associated with the neuro-progression of bipolar disorder to dementia. Further genetic studies are needed to comprehensively clarify the role of genes in cognitive decline and the development of dementia in patients with bipolar disorder.
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Affiliation(s)
- Hirofumi Hirakawa
- Department of Neuropsychiatry, Oita University Faculty of Medicine, Yufu, Oita, Japan
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Abedini SS, Akhavantabasi S, Liang Y, Heng JIT, Alizadehsani R, Dehzangi I, Bauer DC, Alinejad-Rokny H. A critical review of the impact of candidate copy number variants on autism spectrum disorder. MUTATION RESEARCH. REVIEWS IN MUTATION RESEARCH 2024; 794:108509. [PMID: 38977176 DOI: 10.1016/j.mrrev.2024.108509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 04/14/2024] [Accepted: 07/02/2024] [Indexed: 07/10/2024]
Abstract
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder (NDD) influenced by genetic, epigenetic, and environmental factors. Recent advancements in genomic analysis have shed light on numerous genes associated with ASD, highlighting the significant role of both common and rare genetic mutations, as well as copy number variations (CNVs), single nucleotide polymorphisms (SNPs) and unique de novo variants. These genetic variations disrupt neurodevelopmental pathways, contributing to the disorder's complexity. Notably, CNVs are present in 10 %-20 % of individuals with autism, with 3 %-7 % detectable through cytogenetic methods. While the role of submicroscopic CNVs in ASD has been recently studied, their association with genomic loci and genes has not been thoroughly explored. In this review, we focus on 47 CNV regions linked to ASD, encompassing 1632 genes, including protein-coding genes and long non-coding RNAs (lncRNAs), of which 659 show significant brain expression. Using a list of ASD-associated genes from SFARI, we detect 17 regions harboring at least one known ASD-related protein-coding gene. Of the remaining 30 regions, we identify 24 regions containing at least one protein-coding gene with brain-enriched expression and a nervous system phenotype in mouse mutants, and one lncRNA with both brain-enriched expression and upregulation in iPSC to neuron differentiation. This review not only expands our understanding of the genetic diversity associated with ASD but also underscores the potential of lncRNAs in contributing to its etiology. Additionally, the discovered CNVs will be a valuable resource for future diagnostic, therapeutic, and research endeavors aimed at prioritizing genetic variations in ASD.
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Affiliation(s)
- Seyedeh Sedigheh Abedini
- UNSW BioMedical Machine Learning Lab (BML), The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia; School of Biotechnology & Biomolecular Sciences, UNSW Sydney, Sydney, NSW 2052, Australia
| | - Shiva Akhavantabasi
- Department of Molecular Biology and Genetics, Yeni Yuzyil University, Istanbul, Turkey; Ghiaseddin Jamshid Kashani University, Andisheh University Town, Danesh Blvd, 3441356611, Abyek, Qazvin, Iran
| | - Yuheng Liang
- UNSW BioMedical Machine Learning Lab (BML), The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia
| | - Julian Ik-Tsen Heng
- Curtin Health Innovation Research Institute, Curtin University, Bentley 6845, Australia
| | - Roohallah Alizadehsani
- Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Victoria, Australia
| | - Iman Dehzangi
- Center for Computational and Integrative Biology, Rutgers University, Camden, NJ 08102, USA; Department of Computer Science, Rutgers University, Camden, NJ 08102, USA
| | - Denis C Bauer
- Transformational Bioinformatics, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sydney, Australia; Applied BioSciences, Faculty of Science and Engineering, Macquarie University, Macquarie Park, Australia
| | - Hamid Alinejad-Rokny
- UNSW BioMedical Machine Learning Lab (BML), The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia; Tyree Institute of Health Engineering (IHealthE), UNSW Sydney, Sydney, NSW 2052, Australia.
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Wang Z, Cao H, Cao Y, Song H, Jiang X, Wei C, Yang Z, Li J. Clinical characteristics and cognitive function in bipolar disorder patients with different onset symptom. Front Psychiatry 2023; 14:1253088. [PMID: 37840798 PMCID: PMC10569422 DOI: 10.3389/fpsyt.2023.1253088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 09/01/2023] [Indexed: 10/17/2023] Open
Abstract
Background In recent years, studies on the clinical features and cognitive impairment of patients with different first-episode types of bipolar disorder have received increasing attention. The patients with bipolar disorder may present with different symptoms at first onset. The aim of this study is to assess the cognitive functions of a patient's index episode of bipolar disorder, depression or mania, on risk factors of effecting on cognitive functions. Method One hundred sixty eight patients with bipolar disorder diagnosed for the first time were enrolled in the study. All patients were divided into two groups according to their index episode of bipolar disorder, either depression or mania. Seventy three patients of the cohort had an index episode mania and 95 patients had initial symptoms of depression. Demographic and clinical disease characteristic data of all enrolled patients were collected. Meanwhile, 75 healthy controls were included. Demographic data of controls were collected. The cognitive functions of all patients and controls were detected by continuous performance test (CPT), digital span test (DST) and Wisconsin card sorting test (WCST). The main cognitive functions data were compared among the mania group, depression group and control group. The relevant risk factors affecting cognitive function were analyzed. Results (1) Most patients with bipolar disorder had an index episode depression (56.55% vs. 43.45%). Compared with the depression group, the mania group had later age of onset [(24.01 ± 4.254) vs. (22.25 ± 6.472), t = 2. 122, p = 0.035]. The education level of patient groups was lower than control group (p < 0.001). (2) The healthy control group's DST, WCST and CPT scores were better than the patient groups (All p < 0.05). The mania group's DST (forward, reverse, sum), WCST (total responses, completed classifications, correct responses, incorrect responses, percentage of correct responses, completed the number of responses required for classification, the percentage of conceptualization level, the number of persistent responses, non-persistent errors), CPT (2 digit score, 3 digit score, 4 digit score) was better than the depression group (p < 0.05). (3) In mania group, correlation analysis showed that all CPT parameter, inverse digit span, and the sum of DST was negatively correlated with the education level (All p < 0.05). The CPT-4 digit score was negatively correlated with onset age (p < 0.05). In the WCST, the number of correct responses, the percentage of correct responses and the percentage of conceptualization level were positively correlated with the BRMS score (All p < 0.05). The number of false responses and persistent responses were negatively correlated with the BRMS score (All p < 0.05). The number of persistent errors and percentage of persistent errors was positively correlated with education years (All p < 0.05). In depression group, there was a positive correlation between inverse digit span and the education level (p < 0.05). Conclusion In our study, there were cognitive impairments in attention, memory, and executive function of patients with different onset syndromes of bipolar disorder. Compared with the mania group, the degree of cognitive impairments in bipolar patients with the depressive episode was more severe. The risk factors affecting cognitive impairments included the age of onset, education level, number of hospitalizations and severity of illness.
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Affiliation(s)
- Zhonggang Wang
- Department of Psychiatry, Shandong Daizhuang Hospital, Jining, China
| | - Haiyan Cao
- Institute of Mental Health, Tianjin Anding Hospital, Tianjin, China
| | - Yuying Cao
- Department of Medical Imaging, Affiliated Hospital of Jining Medical University, Jining, China
| | - Haining Song
- Department of Psychiatry, Shandong Daizhuang Hospital, Jining, China
- Department of Psychiatry, Jining Medical University, Jining, China
| | - Xianfei Jiang
- Department of Psychiatry, Shandong Daizhuang Hospital, Jining, China
| | - Chen Wei
- Department of Psychiatry, Shandong Daizhuang Hospital, Jining, China
| | - Zhenzhen Yang
- Department of Psychiatry, Shandong Daizhuang Hospital, Jining, China
| | - Jie Li
- Institute of Mental Health, Tianjin Anding Hospital, Tianjin, China
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Ou YN, Wu BS, Ge YJ, Zhang Y, Jiang YC, Kuo K, Yang L, Tan L, Feng JF, Cheng W, Yu JT. The genetic architecture of human amygdala volumes and their overlap with common brain disorders. Transl Psychiatry 2023; 13:90. [PMID: 36906575 PMCID: PMC10008562 DOI: 10.1038/s41398-023-02387-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 02/26/2023] [Accepted: 02/28/2023] [Indexed: 03/13/2023] Open
Abstract
The amygdala is a crucial interconnecting structure in the brain that performs several regulatory functions, yet its genetic architectures and involvement in brain disorders remain largely unknown. We carried out the first multivariate genome-wide association study (GWAS) of amygdala subfield volumes in 27,866 UK Biobank individuals. The whole amygdala was segmented into nine nuclei groups using Bayesian amygdala segmentation. The post-GWAS analysis allowed us to identify causal genetic variants in phenotypes at the SNP, locus, and gene levels, as well as genetic overlap with brain health-related traits. We further generalized our GWAS in Adolescent Brain Cognitive Development (ABCD) cohort. The multivariate GWAS identified 98 independent significant variants within 32 genomic loci associated (P < 5 × 10-8) with amygdala volume and its nine nuclei. The univariate GWAS identified significant hits for eight of the ten volumes, tagging 14 independent genomic loci. Overall, 13 of the 14 loci identified in the univariate GWAS were replicated in the multivariate GWAS. The generalization in ABCD cohort supported the GWAS results with the 12q23.2 (RNA gene RP11-210L7.1) being discovered. All of these imaging phenotypes are heritable, with heritability ranging from 15% to 27%. Gene-based analyses revealed pathways relating to cell differentiation/development and ion transporter/homeostasis, with the astrocytes found to be significantly enriched. Pleiotropy analyses revealed shared variants with neurological and psychiatric disorders under the conjFDR threshold of 0.05. These findings advance our understanding of the complex genetic architectures of amygdala and their relevance in neurological and psychiatric disorders.
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Affiliation(s)
- Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Bang-Sheng Wu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Yi-Jun Ge
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yi Zhang
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Yu-Chao Jiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Kevin Kuo
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Liu Yang
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.,Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.,Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Wei Cheng
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China. .,Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China. .,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China. .,Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China.
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China.
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Bharadhwaj VS, Mubeen S, Sargsyan A, Jose GM, Geissler S, Hofmann-Apitius M, Domingo-Fernández D, Kodamullil AT. Integrative analysis to identify shared mechanisms between schizophrenia and bipolar disorder and their comorbidities. Prog Neuropsychopharmacol Biol Psychiatry 2023; 122:110688. [PMID: 36462601 DOI: 10.1016/j.pnpbp.2022.110688] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 11/04/2022] [Accepted: 11/27/2022] [Indexed: 12/04/2022]
Abstract
Schizophrenia and bipolar disorder are characterized by highly similar neuropsychological signatures, implying shared neurobiological mechanisms between these two disorders. These disorders also have comorbidities, such as type 2 diabetes mellitus (T2DM). To date, an understanding of the mechanisms that mediate the link between these two disorders remains incomplete. In this work, we identify and investigate shared patterns across multiple schizophrenia, bipolar disorder and T2DM gene expression datasets through multiple strategies. Firstly, we investigate dysregulation patterns at the gene-level and compare our findings against disease-specific knowledge graphs (KGs). Secondly, we analyze the concordance of co-expression patterns across datasets to identify disease-specific as well as common pathways. Thirdly, we examine enriched pathways across datasets and disorders to identify common biological mechanisms between them. Lastly, we investigate the correspondence of shared genetic variants between these two disorders and T2DM as well as the disease-specific KGs. In conclusion, our work reveals several shared candidate genes and pathways, particularly those related to the immune system, such as TNF signaling pathway, IL-17 signaling pathway and NF-kappa B signaling pathway and nervous system, such as dopaminergic synapse and GABAergic synapse, which we propose mediate the link between schizophrenia and bipolar disorder and its shared comorbidity, T2DM.
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Affiliation(s)
- Vinay Srinivas Bharadhwaj
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Sankt Augustin 53757, Germany; Bonn-Aachen International Center for Information Technology (B-IT), University of Bonn, 53115 Bonn, Germany.
| | - Sarah Mubeen
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Sankt Augustin 53757, Germany; Bonn-Aachen International Center for Information Technology (B-IT), University of Bonn, 53115 Bonn, Germany; Fraunhofer Center for Machine Learning, Germany
| | - Astghik Sargsyan
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Sankt Augustin 53757, Germany
| | - Geena Mariya Jose
- Causality Biomodels, Kinfra Hi-Tech Park, Kalamassery, Cochin, Kerala 683503, India
| | | | - Martin Hofmann-Apitius
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Sankt Augustin 53757, Germany; Bonn-Aachen International Center for Information Technology (B-IT), University of Bonn, 53115 Bonn, Germany
| | - Daniel Domingo-Fernández
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Sankt Augustin 53757, Germany; Fraunhofer Center for Machine Learning, Germany; Enveda Biosciences, Boulder, CO, 80301, USA
| | - Alpha Tom Kodamullil
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Sankt Augustin 53757, Germany; Bonn-Aachen International Center for Information Technology (B-IT), University of Bonn, 53115 Bonn, Germany; Causality Biomodels, Kinfra Hi-Tech Park, Kalamassery, Cochin, Kerala 683503, India
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Huang Y, Zhang Z, Lin S, Zhou H, Xu G. Cognitive Impairment Mechanism in Patients with Bipolar Disorder. Neuropsychiatr Dis Treat 2023; 19:361-366. [PMID: 36798654 PMCID: PMC9926924 DOI: 10.2147/ndt.s396424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Accepted: 01/27/2023] [Indexed: 02/12/2023] Open
Abstract
Bipolar disorder (BD) is a common chronic mental disorder usually characterized by manic, hypomanic and depressive episodes. Patients diagnosed with BD have cognitive impairments in both the mood attack and remission stages, that is impairment of attention, memory and executive function. Up till the present moment, the causative mechanisms of cognitive impairment in BD patients remain poorly understood. Several studies have demonstrated that cognitive impairment in patients with bipolar disorder is not associated with a single factor, but with gene polymorphism, brain structural and functional variables, inflammatory and metabolic factors. Herein, we reviewed and summarized the recent reports on cognitive impairment mechanisms in patients with BD. To prevent or alleviate cognitive damage at an early stage, we propose that future research should focus on investigating the pathological mechanism of specific cognitive dimension damage as well as the pathological mechanism network between the damage of each dimension. It is crucial to recognize mechanisms of cognitive impairment for improving the symptoms and prognosis of BD patients, restoring their social function and integration.
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Affiliation(s)
- Yanxiong Huang
- Department of Clinical Psychology, Affiliated Longhua People's Hospital, Southern Medical University (Longhua People's Hospital), Shenzhen, Guangdong, People's Republic of China
| | - Zhilong Zhang
- The First People's Hospital of Huizhou City, Huizhou, Guangdong, People's Republic of China
| | - Shihao Lin
- The Second Clinical College, Guangzhou Medical University, Guangzhou, Guangdong, People's Republic of China
| | - Haobin Zhou
- The First Clinical College, Guangzhou Medical University, Guangzhou, Guangdong, People's Republic of China
| | - Guiyun Xu
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong, People's Republic of China
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Variability in the antioxidant MSRA gene affects the psychopathology of patients with anorexia nervosa. Acta Neuropsychiatr 2021; 33:307-316. [PMID: 34396949 DOI: 10.1017/neu.2021.24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
The objective is to determine whether variability in the MSRA gene, related to obesity and several psychiatric conditions, may be relevant for psychopathological symptoms common in Anorexia Nervosa (AN) and/or for the susceptibility to the disorder. A total of 629 women (233 AN patients and 396 controls) were genotyped for 14 tag-SNPs. Psychometric evaluation was performed with the EDI-2 and SCL-90R questionnaires. Genetic associations were carried out by logistic regression controlling for age and adjusting for multiple comparisons (FDR method). Two tag-SNPs, rs11249969 and rs81442 (with a pairwise r2 value of 0.41), were associated with the global EDI-2 score, which measures EDI-related psychopathology (adjusted FDR-q = 0.02 and 0.04, respectively). Moreover, rs81442 significantly modulated all the scales of the SCL-90R test that evaluates general psychopathology (FDR-q values ranged from 4.1E-04 to 0.011). A sliding-window analysis using adjacent 3-SNP haplotypes revealed a proximal region of the MSRA gene spanning 187.8 Kbp whose variability deeply affected psychopathological symptoms of the AN patients. Depression was the symptom that showed the strongest association with any of the constructed haplotypes (FDR-q = 3.60E-06). No variants were found to be linked to AN risk or anthropometric parameters in patients or controls. Variability in the MSRA gene locus modulates psychopathology often presented by AN patients.
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Das K, Garnica O, Flores J, Dhandayuthapani S. Methionine sulfoxide reductase A (MsrA) modulates cells and protects against Mycoplasma genitalium induced cytotoxicity. Free Radic Biol Med 2020; 152:323-335. [PMID: 32222467 DOI: 10.1016/j.freeradbiomed.2020.03.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Revised: 03/06/2020] [Accepted: 03/23/2020] [Indexed: 12/28/2022]
Abstract
Methionine sulfoxide reductase A (MsrA) is a ubiquitous antioxidant repair enzyme which specifically reduces the oxidized methionine (Met-O) in proteins to methionine (Met). Previous studies have shown that lack of or overexpression of MsrA in cells affects the function of proteins and can lead to altered cellular processes. Interestingly, some pathogenic bacteria secrete and/or carry MsrA on their surface, suggesting some key roles for this enzyme in the modulation of host cellular processes. Therefore, we investigated how exogenously added MsrA affects the ability of the host cells in combating infection by using an in vitroMycoplasma genitalium cytotoxicity model. HeLa cells pretreated with MsrA and infected with M. genitalium showed significantly lower necrosis (cytotoxicity) than untreated cells infected with M. genitalium. Intriguingly, necrotic cell death pathway specific real time RT-PCR revealed that M. genitalium infection upregulates the expression of the TNF gene in HeLa cells and that MsrA pretreatment of the cells downregulates its expression significantly. Consistent with this, enzyme linked immunosorbent assay (ELISA) results showed that HeLa cells pretreated with MsrA secreted reduced levels of TNF-α following M. genitalium infection. Also, our study demonstrates that MsrA treatment of cells affects the phosphorylation status of transcriptional regulators such as NF-кB, JNK and p53 that regulate different cytokines. Further, fluorescent microscopy showed the cellular uptake of exogenously added MsrA fused with red fluorescent protein (MsrA-RFP). Altogether, our results suggest that secreted MsrA may help pathogens to modulate host cellular processes.
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Affiliation(s)
- Kishore Das
- Department of Molecular and Translational Medicine, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center El Paso, El Paso, TX, 79905, USA
| | - Omar Garnica
- Department of Molecular and Translational Medicine, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center El Paso, El Paso, TX, 79905, USA
| | - Javier Flores
- Department of Molecular and Translational Medicine, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center El Paso, El Paso, TX, 79905, USA; Graduate School of Biomedical Sciences, Texas Tech University Health Sciences Center El Paso, El Paso, TX, 79905, USA
| | - Subramanian Dhandayuthapani
- Department of Molecular and Translational Medicine, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center El Paso, El Paso, TX, 79905, USA; Graduate School of Biomedical Sciences, Texas Tech University Health Sciences Center El Paso, El Paso, TX, 79905, USA.
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Reiterer M, Schmidt-Kastner R, Milton SL. Methionine sulfoxide reductase (Msr) dysfunction in human brain disease. Free Radic Res 2019; 53:1144-1154. [PMID: 31775527 DOI: 10.1080/10715762.2019.1662899] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Extensive research has shown that oxidative stress is strongly associated with aging, senescence and several diseases, including neurodegenerative and psychiatric disorders. Oxidative stress is caused by the overproduction of reactive oxygen species (ROS) that can be counteracted by both enzymatic and nonenzymatic antioxidants. One of these antioxidant mechanisms is the widely studied methionine sulfoxide reductase system (Msr). Methionine is one of the most easily oxidized amino acids and Msr can reverse this oxidation and restore protein function, with MsrA and MsrB reducing different stereoisomers. This article focuses on experimental and genetic research performed on Msr and its link to brain diseases. Studies on several model systems as well as genome-wide association studies are compiled to highlight the role of MSRA in schizophrenia, Alzheimer's disease, and Parkinson's disease. Genetic variation of MSRA may also contribute to the risk of psychosis, personality traits, and metabolic factors.
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Affiliation(s)
- Melissa Reiterer
- Charles E. Schmidt College of Science, Florida Atlantic University, Boca Raton, FL, USA
| | | | - Sarah L Milton
- Charles E. Schmidt College of Science, Florida Atlantic University, Boca Raton, FL, USA
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Liu JS, Cui ZJ. Pancreatic Stellate Cells Serve as a Brake Mechanism on Pancreatic Acinar Cell Calcium Signaling Modulated by Methionine Sulfoxide Reductase Expression. Cells 2019; 8:cells8020109. [PMID: 30717164 PMCID: PMC6406918 DOI: 10.3390/cells8020109] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Revised: 01/28/2019] [Accepted: 01/29/2019] [Indexed: 02/06/2023] Open
Abstract
Although methionine sulfoxide reductase (Msr) is known to modulate the activity of multiple functional proteins, the roles of Msr in pancreatic stellate cell physiology have not been reported. In the present work we investigated expression and function of Msr in freshly isolated and cultured rat pancreatic stellate cells. Msr expression was determined by RT-PCR, Western blot and immunocytochemistry. Msr over-expression was achieved by transfection with adenovirus vectors. Pancreatic stellate cells were co-cultured with pancreatic acinar cells AR4-2J in monolayer culture. Pancreatic stellate and acinar cell function was monitored by Fura-2 calcium imaging. Rat pancreatic stellate cells were found to express MsrA, B1, B2, their expressions diminished in culture. Over-expressions of MsrA, B1 or B2 were found to enhance ATP-stimulated calcium increase but decreased reactive oxygen species generation and lipopolysaccharide-elicited IL-1 production. Pancreatic stellate cell-co-culture with AR4-2J blunted cholecystokinin- and acetylcholine-stimulated calcium increases in AR4-2J, depending on acinar/stellate cell ratio, this inhibition was reversed by MsrA, B1 over-expression in stellate cells or by Met supplementation in the co-culture medium. These data suggest that Msr play important roles in pancreatic stellate cell function and the stellate cells may serve as a brake mechanism on pancreatic acinar cell calcium signaling modulated by stellate cell Msr expression.
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Affiliation(s)
- Jin Shuai Liu
- Institute of Cell Biology, Beijing Normal University, Beijing 100875, China.
| | - Zong Jie Cui
- Institute of Cell Biology, Beijing Normal University, Beijing 100875, China.
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Genetic regulation of longevity and age-associated diseases through the methionine sulfoxide reductase system. Biochim Biophys Acta Mol Basis Dis 2018; 1865:1756-1762. [PMID: 30481589 DOI: 10.1016/j.bbadis.2018.11.016] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Revised: 09/25/2018] [Accepted: 11/14/2018] [Indexed: 12/13/2022]
Abstract
Methionine sulfoxide reductase enzymes are a protective system against biological oxidative stress in aerobic organisms. Modifications to this antioxidant system have been shown to impact the lifespan of several model system organisms. In humans, methionine oxidation of critical proteins and deficiencies in the methionine sulfoxide reductase system have been linked to age-related diseases, including cancer and neurodegenerative disease. Substrates for methionine sulfoxide reductases have been reviewed multiple times, and are still an active area of discovery. In contrast, less is known about the genetic regulation of methionine sulfoxide reductases. In this review, we discuss studies on the genetic regulation of the methionine sulfoxide reductase system with relevance to longevity and age-related diseases. A better understanding of genetic regulation for methionine sulfoxide reductases may lead to new therapeutic approaches for age-related diseases in the future.
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Liu Y, Liang Y, Cicek AE, Li Z, Li J, Muhle RA, Krenzer M, Mei Y, Wang Y, Knoblauch N, Morrison J, Zhao S, Jiang Y, Geller E, Ionita-Laza I, Wu J, Xia K, Noonan JP, Sun ZS, He X. A Statistical Framework for Mapping Risk Genes from De Novo Mutations in Whole-Genome-Sequencing Studies. Am J Hum Genet 2018; 102:1031-1047. [PMID: 29754769 PMCID: PMC5992125 DOI: 10.1016/j.ajhg.2018.03.023] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Accepted: 03/22/2018] [Indexed: 10/16/2022] Open
Abstract
Analysis of de novo mutations (DNMs) from sequencing data of nuclear families has identified risk genes for many complex diseases, including multiple neurodevelopmental and psychiatric disorders. Most of these efforts have focused on mutations in protein-coding sequences. Evidence from genome-wide association studies (GWASs) strongly suggests that variants important to human diseases often lie in non-coding regions. Extending DNM-based approaches to non-coding sequences is challenging, however, because the functional significance of non-coding mutations is difficult to predict. We propose a statistical framework for analyzing DNMs from whole-genome sequencing (WGS) data. This method, TADA-Annotations (TADA-A), is a major advance of the TADA method we developed earlier for DNM analysis in coding regions. TADA-A is able to incorporate many functional annotations such as conservation and enhancer marks, to learn from data which annotations are informative of pathogenic mutations, and to combine both coding and non-coding mutations at the gene level to detect risk genes. It also supports meta-analysis of multiple DNM studies, while adjusting for study-specific technical effects. We applied TADA-A to WGS data of ∼300 autism-affected family trios across five studies and discovered several autism risk genes. The software is freely available for all research uses.
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Affiliation(s)
- Yuwen Liu
- Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA
| | - Yanyu Liang
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15123, USA
| | - A Ercument Cicek
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15123, USA; Computer Engineering Department, Bilkent University, Ankara 06800, Turkey
| | - Zhongshan Li
- Institute of Genomic Medicine, Wenzhou Medical University, Wenzhou, Zhejiang 325000, China
| | - Jinchen Li
- Center for Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan 410078, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410078, China
| | | | - Martina Krenzer
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA
| | - Yue Mei
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100000, China
| | - Yan Wang
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100000, China
| | - Nicholas Knoblauch
- Committee on Genetics, Genomics and Systems Biology, The University of Chicago, Chicago, IL 60637, USA
| | - Jean Morrison
- Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA
| | - Siming Zhao
- Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA
| | - Yi Jiang
- Institute of Genomic Medicine, Wenzhou Medical University, Wenzhou, Zhejiang 325000, China; Center for Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan 410078, China
| | - Evan Geller
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA; Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA
| | | | - Jinyu Wu
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100000, China; Institute of Genomic Medicine, Wenzhou Medical University, Wenzhou, Zhejiang 325000, China
| | - Kun Xia
- Center for Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan 410078, China
| | - James P Noonan
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA; Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA
| | - Zhong Sheng Sun
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100000, China; Institute of Genomic Medicine, Wenzhou Medical University, Wenzhou, Zhejiang 325000, China.
| | - Xin He
- Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA.
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Methionine in Proteins: It's Not Just for Protein Initiation Anymore. Neurochem Res 2018; 44:247-257. [PMID: 29327308 DOI: 10.1007/s11064-017-2460-0] [Citation(s) in RCA: 82] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2017] [Revised: 12/19/2017] [Accepted: 12/26/2017] [Indexed: 12/21/2022]
Abstract
Methionine in proteins is often thought to be a generic hydrophobic residue, functionally replaceable with another hydrophobic residue such as valine or leucine. This is not the case, and the reason is that methionine contains sulfur that confers special properties on methionine. The sulfur can be oxidized, converting methionine to methionine sulfoxide, and ubiquitous methionine sulfoxide reductases can reduce the sulfoxide back to methionine. This redox cycle enables methionine residues to provide a catalytically efficient antioxidant defense by reacting with oxidizing species. The cycle also constitutes a reversible post-translational covalent modification analogous to phosphorylation. As with phosphorylation, enzymatically-mediated oxidation and reduction of specific methionine residues functions as a regulatory process in the cell. Methionine residues also form bonds with aromatic residues that contribute significantly to protein stability. Given these important functions, alteration of the methionine-methionine sulfoxide balance in proteins has been correlated with disease processes, including cardiovascular and neurodegenerative diseases. Methionine isn't just for protein initiation.
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Amare AT, Schubert KO, Tekola-Ayele F, Hsu YH, Sangkuhl K, Jenkins G, Whaley RM, Barman P, Batzler A, Altman RB, Arolt V, Brockmöller J, Chen CH, Domschke K, Hall-Flavin DK, Hong CJ, Illi A, Ji Y, Kampman O, Kinoshita T, Leinonen E, Liou YJ, Mushiroda T, Nonen S, Skime MK, Wang L, Kato M, Liu YL, Praphanphoj V, Stingl JC, Bobo WV, Tsai SJ, Kubo M, Klein TE, Weinshilboum RM, Biernacka JM, Baune BT. Association of the Polygenic Scores for Personality Traits and Response to Selective Serotonin Reuptake Inhibitors in Patients with Major Depressive Disorder. Front Psychiatry 2018; 9:65. [PMID: 29559929 PMCID: PMC5845551 DOI: 10.3389/fpsyt.2018.00065] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Accepted: 02/19/2018] [Indexed: 12/31/2022] Open
Abstract
Studies reported a strong genetic correlation between the Big Five personality traits and major depressive disorder (MDD). Moreover, personality traits are thought to be associated with response to antidepressants treatment that might partly be mediated by genetic factors. In this study, we examined whether polygenic scores (PGSs) derived from the Big Five personality traits predict treatment response and remission in patients with MDD who were prescribed selective serotonin reuptake inhibitors (SSRIs). In addition, we performed meta-analyses of genome-wide association studies (GWASs) on these traits to identify genetic variants underpinning the cross-trait polygenic association. The PGS analysis was performed using data from two cohorts: the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS, n = 529) and the International SSRI Pharmacogenomics Consortium (ISPC, n = 865). The cross-trait GWAS meta-analyses were conducted by combining GWAS summary statistics on SSRIs treatment outcome and on the personality traits. The results showed that the PGS for openness and neuroticism were associated with SSRIs treatment outcomes at p < 0.05 across PT thresholds in both cohorts. A significant association was also found between the PGS for conscientiousness and SSRIs treatment response in the PGRN-AMPS sample. In the cross-trait GWAS meta-analyses, we identified eight loci associated with (a) SSRIs response and conscientiousness near YEATS4 gene and (b) SSRI remission and neuroticism eight loci near PRAG1, MSRA, XKR6, ELAVL2, PLXNC1, PLEKHM1, and BRUNOL4 genes. An assessment of a polygenic load for personality traits may assist in conjunction with clinical data to predict whether MDD patients might respond favorably to SSRIs.
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Affiliation(s)
- Azmeraw T Amare
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA, Australia
| | - Klaus Oliver Schubert
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA, Australia.,Northern Adelaide Local Health Network, Mental Health Services, Adelaide, SA, Australia
| | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Intramural Population Health Research, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
| | - Yi-Hsiang Hsu
- HSL Institute for Aging Research, Harvard Medical School, Boston, MA, United States.,Program for Quantitative Genomics, Harvard School of Public Health, Boston, MA, United States.,Broad Institute of MIT and Harvard, Cambridge, MA, United States
| | - Katrin Sangkuhl
- Biomedical Data Science, Stanford University, Stanford, CA, United States
| | - Gregory Jenkins
- Department of Health Sciences Research, Mayo Clinic, Rochester, NY, United States
| | - Ryan M Whaley
- Biomedical Data Science, Stanford University, Stanford, CA, United States
| | - Poulami Barman
- Department of Health Sciences Research, Mayo Clinic, Rochester, NY, United States
| | - Anthony Batzler
- Department of Health Sciences Research, Mayo Clinic, Rochester, NY, United States
| | - Russ B Altman
- Department of Bioengineering, Stanford University, Stanford, CA, United States
| | - Volker Arolt
- Department of Psychiatry and Psychotherapy, University of Muenster, Muenster, Germany
| | - Jürgen Brockmöller
- Department of Clinical Pharmacology, University Göttingen, Göttingen, Germany
| | - Chia-Hui Chen
- Department of Psychiatry, Taipei Medical University-Shuangho Hospital, New Taipei City, Taiwan
| | - Katharina Domschke
- Department of Psychiatry and Psychotherapy, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Daniel K Hall-Flavin
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, NY, United States
| | - Chen-Jee Hong
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Ari Illi
- Department of Psychiatry, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Yuan Ji
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic Rochester, Rochester, MN, United States
| | - Olli Kampman
- Department of Psychiatry, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.,Department of Psychiatry, Seinäjoki Hospital District, Seinäjoki, Finland
| | | | - Esa Leinonen
- Department of Psychiatry, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.,Department of Psychiatry, Tampere University Hospital, Tampere, Finland
| | - Ying-Jay Liou
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | | | - Shinpei Nonen
- Department of Pharmacy, Hyogo University of Health Sciences, Hyogo, Japan
| | - Michelle K Skime
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, NY, United States
| | - Liewei Wang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic Rochester, Rochester, MN, United States
| | - Masaki Kato
- Department of Neuropsychiatry, Kansai Medical University, Osaka, Japan
| | - Yu-Li Liu
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
| | - Verayuth Praphanphoj
- Center for Medical Genetics Research, Rajanukul Institute, Department of Mental Health, Ministry of Public Health Bangkok, Bangkok, Thailand
| | - Julia C Stingl
- Research Division Federal Institute for Drugs and Medical Devices, Bonn, Germany
| | - William V Bobo
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, NY, United States
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Teri E Klein
- Biomedical Data Science, Stanford University, Stanford, CA, United States
| | - Richard M Weinshilboum
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic Rochester, Rochester, MN, United States
| | - Joanna M Biernacka
- Department of Health Sciences Research, Mayo Clinic, Rochester, NY, United States.,Department of Psychiatry and Psychology, Mayo Clinic, Rochester, NY, United States
| | - Bernhard T Baune
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA, Australia
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