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Zhang J, Zhu Y, Zhang M, Yan J, Zheng Y, Yao L, Li Z, Shao Z, Chen Y. Potassium channels in depression: emerging roles and potential targets. Cell Biosci 2024; 14:136. [PMID: 39529121 PMCID: PMC11555980 DOI: 10.1186/s13578-024-01319-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2024] [Accepted: 10/31/2024] [Indexed: 11/16/2024] Open
Abstract
Potassium ion channels play a fundamental role in regulating cell membrane repolarization, modulating the frequency and shape of action potentials, and maintaining the resting membrane potential. A growing number of studies have indicated that dysfunction in potassium channels associates with the pathogenesis and treatment of depression. However, the involvement of potassium channels in the onset and treatment of depression has not been thoroughly summarized. In this review, we performed a comprehensive analysis of the association between multiple potassium channels and their roles in depression, and compiles the SNP loci of potassium channels associated with depression, as well as antidepressant drugs that target these channels. We discussed the pivotal role of potassium channels in the treatment of depression, provide valuable insights into new therapeutic targets for antidepressant treatment and critical clues to future drug discovery.
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Affiliation(s)
- Jiahao Zhang
- Institute of Acupuncture and Moxibustion, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China
| | - Yao Zhu
- Institute of Acupuncture and Moxibustion, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China
| | - Meng Zhang
- Institute of Acupuncture and Moxibustion, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China
- Shandong Key Laboratory of Innovation and Application Research in Basic Theory of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China
| | - Jinglan Yan
- Institute of Acupuncture and Moxibustion, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China
- Key Laboratory of Traditional Chinese Medicine Classical Theory, Ministry of Education, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China
| | - Yuanjia Zheng
- Institute of Acupuncture and Moxibustion, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China
- Key Laboratory of Traditional Chinese Medicine Classical Theory, Ministry of Education, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China
| | - Lin Yao
- Institute of Acupuncture and Moxibustion, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China
- Shandong Provincial Engineering Research Center for the Prevention and Treatment of Major Brain Diseases with Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China
| | - Ziwei Li
- Institute of Acupuncture and Moxibustion, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China
| | - Zihan Shao
- Institute of Acupuncture and Moxibustion, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China
| | - Yongjun Chen
- Institute of Acupuncture and Moxibustion, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China.
- Shandong Key Laboratory of Innovation and Application Research in Basic Theory of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China.
- Shandong Provincial Engineering Research Center for the Prevention and Treatment of Major Brain Diseases with Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China.
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Singh P, Srivastava A, Guin D, Thakran S, Yadav J, Chandna P, Sood M, Chadda RK, Kukreti R. Genetic Landscape of Major Depressive Disorder: Assessment of Potential Diagnostic and Antidepressant Response Markers. Int J Neuropsychopharmacol 2023; 26:692-738. [PMID: 36655406 PMCID: PMC10586057 DOI: 10.1093/ijnp/pyad001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 01/18/2023] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND The clinical heterogeneity in major depressive disorder (MDD), variable treatment response, and conflicting findings limit the ability of genomics toward the discovery of evidence-based diagnosis and treatment regimen. This study attempts to curate all genetic association findings to evaluate potential variants for clinical translation. METHODS We systematically reviewed all candidates and genome-wide association studies for both MDD susceptibility and antidepressant response, independently, using MEDLINE, particularly to identify replicated findings. These variants were evaluated for functional consequences using different in silico tools and further estimated their diagnostic predictability by calculating positive predictive values. RESULTS A total of 217 significantly associated studies comprising 1200 variants across 545 genes and 128 studies including 921 variants across 412 genes were included with MDD susceptibility and antidepressant response, respectively. Although the majority of associations were confirmed by a single study, we identified 31 and 18 replicated variants (in at least 2 studies) for MDD and antidepressant response. Functional annotation of these 31 variants predicted 20% coding variants as deleterious/damaging and 80.6% variants with regulatory effect. Similarly, the response-related 18 variants revealed 25% coding variant as damaging and 88.2% with substantial regulatory potential. Finally, we could calculate the diagnostic predictability of 19 and 5 variants whose positive predictive values ranges from 0.49 to 0.66 for MDD and 0.36 to 0.66 for response. CONCLUSIONS The replicated variants presented in our data are promising for disease diagnosis and improved response outcomes. Although these quantitative assessment measures are solely directive of available observational evidence, robust homogenous validation studies are required to strengthen these variants for molecular diagnostic application.
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Affiliation(s)
- Priyanka Singh
- Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB), New Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Ankit Srivastava
- Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB), New Delhi, India
- Department of Pharmacology, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, India
| | - Debleena Guin
- Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB), New Delhi, India
- Department of Biotechnology, Delhi Technological University, Shahbad Daulatpur, Delhi, India
| | - Sarita Thakran
- Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB), New Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Jyoti Yadav
- Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB), New Delhi, India
| | - Puneet Chandna
- Indian Society of Colposcopy and Cervical Pathology (ISCCP), Safdarjung Hospital, New Delhi, India
| | - Mamta Sood
- Department of Psychiatry, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India
| | - Rakesh Kumar Chadda
- Department of Psychiatry, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India
| | - Ritushree Kukreti
- Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB), New Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
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Ganekal P, Vastrad B, Kavatagimath S, Vastrad C, Kotrashetti S. Bioinformatics and Next-Generation Data Analysis for Identification of Genes and Molecular Pathways Involved in Subjects with Diabetes and Obesity. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:medicina59020309. [PMID: 36837510 PMCID: PMC9967176 DOI: 10.3390/medicina59020309] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 01/19/2023] [Accepted: 01/29/2023] [Indexed: 02/10/2023]
Abstract
Background and Objectives: A subject with diabetes and obesity is a class of the metabolic disorder. The current investigation aimed to elucidate the potential biomarker and prognostic targets in subjects with diabetes and obesity. Materials and Methods: The next-generation sequencing (NGS) data of GSE132831 was downloaded from Gene Expression Omnibus (GEO) database. Functional enrichment analysis of DEGs was conducted with ToppGene. The protein-protein interactions network, module analysis, target gene-miRNA regulatory network and target gene-TF regulatory network were constructed and analyzed. Furthermore, hub genes were validated by receiver operating characteristic (ROC) analysis. A total of 872 DEGs, including 439 up-regulated genes and 433 down-regulated genes were observed. Results: Second, functional enrichment analysis showed that these DEGs are mainly involved in the axon guidance, neutrophil degranulation, plasma membrane bounded cell projection organization and cell activation. The top ten hub genes (MYH9, FLNA, DCTN1, CLTC, ERBB2, TCF4, VIM, LRRK2, IFI16 and CAV1) could be utilized as potential diagnostic indicators for subjects with diabetes and obesity. The hub genes were validated in subjects with diabetes and obesity. Conclusion: This investigation found effective and reliable molecular biomarkers for diagnosis and prognosis by integrated bioinformatics analysis, suggesting new and key therapeutic targets for subjects with diabetes and obesity.
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Affiliation(s)
- Prashanth Ganekal
- Department of General Medicine, Basaveshwara Medical College, Chitradurga 577501, Karnataka, India
| | - Basavaraj Vastrad
- Department of Pharmaceutical Chemistry, K.L.E. College of Pharmacy, Gadag 582101, Karnataka, India
| | - Satish Kavatagimath
- Department of Pharmacognosy, K.L.E. College of Pharmacy, Belagavi 590010, Karnataka, India
| | - Chanabasayya Vastrad
- Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karnataka, India
- Correspondence: ; Tel.: +91-9480073398
| | - Shivakumar Kotrashetti
- Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karnataka, India
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Norkeviciene A, Gocentiene R, Sestokaite A, Sabaliauskaite R, Dabkeviciene D, Jarmalaite S, Bulotiene G. A Systematic Review of Candidate Genes for Major Depression. Medicina (B Aires) 2022; 58:medicina58020285. [PMID: 35208605 PMCID: PMC8875554 DOI: 10.3390/medicina58020285] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 02/07/2022] [Accepted: 02/09/2022] [Indexed: 11/16/2022] Open
Abstract
Background and Objectives: The aim of this systematic review was to analyse which candidate genes were examined in genetic association studies and their association with major depressive disorder (MDD). Materials and Methods: We searched PUBMED for relevant studies published between 1 July 2012 and 31 March 2019, using combinations of keywords: “major depressive disorder” OR “major depression” AND “gene candidate”, “major depressive disorder” OR “major depression” AND “polymorphism”. Synthesis focused on assessing the likelihood of bias and investigating factors that may explain differences between the results of studies. For selected gene list after literature overview, functional enrichment analysis and gene ontology term enrichment analysis were conducted. Results: 141 studies were included in the qualitative review of gene association studies focusing on MDD. 86 studies declared significant results (p < 0.05) for 172 SNPs in 85 genes. The 13 SNPs associations were confirmed by at least two studies. The 18 genetic polymorphism associations were confirmed in both the previous and this systematic analysis by at least one study. The majority of the studies (68.79 %) did not use or describe power analysis, which may have had an impact over the significance of their results. Almost a third of studies (N = 54) were conducted in Chinese Han population. Conclusion: Unfortunately, there is still insufficient data on the links between genes and depression. Despite the reported genetic associations, most studies were lacking in statistical power analysis, research samples were small, and most gene polymorphisms have been confirmed in only one study. Further genetic research with larger research samples is needed to discern whether the relationship is random or causal. Summations: This systematic review had summarized all reported genetic associations and has highlighted the genetic associations that have been replicated. Limitations: Unfortunately, most gene polymorphisms have been confirmed only once, so further studies are warranted for replicating these genetic associations. In addition, most studies included a small number of MDD cases that could be indicative for false positive. Considering that polymorphism loci and associations with MDD is also vastly dependent on interpersonal variation, extensive studies of gene interaction pathways could provide more answers to the complexity of MDD.
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Affiliation(s)
- Audrone Norkeviciene
- Clinic of Psychiatry, Institute of Clinical Medicine, Faculty of Medicine, Vilnius University, M. K. Ciurlionio Str. 21/27, LT-03101 Vilnius, Lithuania; (A.N.); (R.G.)
| | - Romena Gocentiene
- Clinic of Psychiatry, Institute of Clinical Medicine, Faculty of Medicine, Vilnius University, M. K. Ciurlionio Str. 21/27, LT-03101 Vilnius, Lithuania; (A.N.); (R.G.)
| | - Agne Sestokaite
- National Cancer Institute, Santariskiu Str. 1, LT-08660 Vilnius, Lithuania; (A.S.); (R.S.); (D.D.); (S.J.)
| | - Rasa Sabaliauskaite
- National Cancer Institute, Santariskiu Str. 1, LT-08660 Vilnius, Lithuania; (A.S.); (R.S.); (D.D.); (S.J.)
| | - Daiva Dabkeviciene
- National Cancer Institute, Santariskiu Str. 1, LT-08660 Vilnius, Lithuania; (A.S.); (R.S.); (D.D.); (S.J.)
| | - Sonata Jarmalaite
- National Cancer Institute, Santariskiu Str. 1, LT-08660 Vilnius, Lithuania; (A.S.); (R.S.); (D.D.); (S.J.)
| | - Giedre Bulotiene
- Clinic of Psychiatry, Institute of Clinical Medicine, Faculty of Medicine, Vilnius University, M. K. Ciurlionio Str. 21/27, LT-03101 Vilnius, Lithuania; (A.N.); (R.G.)
- National Cancer Institute, Santariskiu Str. 1, LT-08660 Vilnius, Lithuania; (A.S.); (R.S.); (D.D.); (S.J.)
- Correspondence:
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Harris JJ, Reynell C. How do antidepressants influence the BOLD signal in the developing brain? Dev Cogn Neurosci 2016; 25:45-57. [PMID: 28089656 PMCID: PMC6987820 DOI: 10.1016/j.dcn.2016.12.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Revised: 12/12/2016] [Accepted: 12/12/2016] [Indexed: 11/21/2022] Open
Abstract
Depression is a highly prevalent life-threatening disorder, with its first onset commonly occurring during adolescence. Adolescent depression is increasingly being treated with antidepressants, such as fluoxetine. The use of medication during this sensitive period of physiological and cognitive brain development produces neurobiological changes, some of which may outlast the course of treatment. In this review, we look at how antidepressant treatment in adolescence is likely to alter neurovascular coupling and brain energy use and how these changes, in turn, affect our ability to identify neuronal activity changes between participant groups. BOLD (blood oxygen level dependent) fMRI (functional magnetic resonance imaging), the method most commonly used to record brain activity in humans, is an indirect measure of neuronal activity. This means that between-group comparisons – adolescent versus adult, depressed versus healthy, medicated versus non-medicated – rely upon a stable relationship existing between neuronal activity and the BOLD response across these groups. We use data from animal studies to detail the ways in which fluoxetine may alter this relationship, and explore how these alterations may influence the interpretation of BOLD signal differences between groups that have been treated with fluoxetine and those that have not.
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Affiliation(s)
- Julia J Harris
- Life Sciences Department, Imperial College London, SW7 2AZ, UK; Francis Crick Institute, Midland Road, London, NW1 1AT, UK.
| | - Clare Reynell
- Département de Neurosciences, Université de Montréal, H3C 3J7, Canada.
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Genetic Loci and Novel Discrimination Measures Associated with Blood Pressure Variation in African Americans Living in Tallahassee. PLoS One 2016; 11:e0167700. [PMID: 28002425 PMCID: PMC5176163 DOI: 10.1371/journal.pone.0167700] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2016] [Accepted: 11/18/2016] [Indexed: 02/06/2023] Open
Abstract
Sequencing of the human genome and decades of genetic association and linkage studies have dramatically improved our understanding of the etiology of many diseases. However, the multiple causes of complex diseases are still not well understood, in part because genetic and sociocultural risk factors are not typically investigated concurrently. Hypertension is a leading risk factor for cardiovascular disease and afflicts more African Americans than any other racially defined group in the US. Few genetic loci for hypertension have been replicated across populations, which may reflect population-specific differences in genetic variants and/or inattention to relevant sociocultural factors. Discrimination is a salient sociocultural risk factor for poor health and has been associated with hypertension. Here we use a biocultural approach to study blood pressure (BP) variation in African Americans living in Tallahassee, Florida by genotyping over 30,000 single nucleotide polymorphisms (SNPs) and capturing experiences of discrimination using novel measures of unfair treatment of self and others (n = 157). We perform a joint admixture and genetic association analysis for BP that prioritizes regions of the genome with African ancestry. We only report significant SNPs that were confirmed through our simulation analyses, which were performed to determine the false positive rate. We identify eight significant SNPs in five genes that were previously associated with cardiovascular diseases. When we include measures of unfair treatment and test for interactions between SNPs and unfair treatment, we identify a new class of genes involved in multiple phenotypes including psychosocial distress and mood disorders. Our results suggest that inclusion of culturally relevant stress measures, like unfair treatment in African Americans, may reveal new genes and biological pathways relevant to the etiology of hypertension, and may also improve our understanding of the complexity of gene-environment interactions that underlie complex diseases.
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Dobrowolski SF, Lyons-Weiler J, Spridik K, Vockley J, Skvorak K, Biery A. DNA methylation in the pathophysiology of hyperphenylalaninemia in the PAH(enu2) mouse model of phenylketonuria. Mol Genet Metab 2016; 119:1-7. [PMID: 26822703 PMCID: PMC8958364 DOI: 10.1016/j.ymgme.2016.01.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2015] [Revised: 12/31/2015] [Accepted: 01/01/2016] [Indexed: 12/25/2022]
Abstract
Phenylalanine hydroxylase deficient phenylketonuria (PKU) is the paradigm for a treatable inborn error of metabolism where maintaining plasma phenylalanine (Phe) in the therapeutic range relates to improved clinical outcomes. While Phe is the presumed intoxicating analyte causal in neurologic damage, the mechanism(s) of Phe toxicity has remained elusive. Altered DNA methylation is a recognized response associated with exposure to numerous small molecule toxic agents. Paralleling this effect, we hypothesized that chronic Phe over-exposure in the brain would lead to aberrant DNA methylation with secondary influence upon gene regulation that would ultimately contribute to PKU neuropathology. The PAH(enu2) mouse models human PKU with intrinsic hyperphenylalaninemia, abnormal response to Phe challenge, and neurologic deficit. To examine this hypothesis, we assessed DNA methylation patterns in brain tissues using methylated DNA immunoprecipitation and paired end sequencing in adult PAH(enu2) animals maintained under either continuous dietary Phe restriction or chronic hyperphenylalaninemia. Heterozygous PAH(enu2/WT) litter mates served as controls for normal Phe exposure. Extensive repatterning of DNA methylation was observed in brain tissue of hyperphenylalaninemic animals while Phe restricted animals displayed an attenuated pattern of aberrant DNA methylation. Affected gene coding regions displayed aberrant hypermethylation and hypomethylation. Gene body methylation of noncoding RNA genes was observed and among these microRNA genes were prominent. Of particular note, observed only in hyperphenylalaninemic animals, was hypomethylation of miRNA genes within the imprinted Dlk1-Dio3 locus on chromosome 12. Aberrant methylation of microRNA genes influenced their expression which has secondary effects upon the expression of targeted protein coding genes. Differential hypermethylation of gene promoters was exclusive to hyperphenylalaninemic PAH(enu2) animals. Genes with synaptic involvement were targets of promoter hypermethylation that resulted in down-regulation of their expression. Gene dysregulation secondary to abnormal DNA methylation may be contributing to PKU neuropathology. These results suggest drugs that prevent or correct aberrant DNA methylation may offer a novel therapeutic option to management of neurological symptoms in PKU patients.
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Affiliation(s)
- S F Dobrowolski
- Department of Pathology, Children's Hospital of Pittsburgh, 4401 Penn Avenue, Pittsburgh, PA 15224, United States.
| | - J Lyons-Weiler
- Genomics and Proteomics Core Laboratories, University of Pittsburgh, 3343 Forbes Avenue, Pittsburgh, PA 15260, United States
| | - K Spridik
- Department of Pathology, Children's Hospital of Pittsburgh, 4401 Penn Avenue, Pittsburgh, PA 15224, United States
| | - J Vockley
- Department of Pediatrics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh, 4401 Penn Avenue, Pittsburgh, PA 15224, United States; Department of Human Genetics, University of Pittsburgh Graduate School of Public Health, 4401 Penn Avenue, Pittsburgh, PA 15224, United States
| | - K Skvorak
- Department of Pediatrics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh, 4401 Penn Avenue, Pittsburgh, PA 15224, United States; Department of Human Genetics, University of Pittsburgh Graduate School of Public Health, 4401 Penn Avenue, Pittsburgh, PA 15224, United States
| | - A Biery
- Department of Pathology, Children's Hospital of Pittsburgh, 4401 Penn Avenue, Pittsburgh, PA 15224, United States
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Minelli A, Congiu C, Ventriglia M, Bortolomasi M, Bonvicini C, Abate M, Sartori R, Gainelli G, Gennarelli M. Influence of GRIK4 genetic variants on the electroconvulsive therapy response. Neurosci Lett 2016; 626:94-8. [PMID: 27222927 DOI: 10.1016/j.neulet.2016.05.030] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2016] [Revised: 05/13/2016] [Accepted: 05/16/2016] [Indexed: 01/27/2023]
Abstract
Several lines of evidence have shown the involvement of the glutamatergic system in the function of electroconvulsive therapy (ECT). In particular, patients with treatment resistant depression (TRD) and chronic depression have lower levels of glutamate/glutamine than controls, and ECT can reverse this deficit. Genetic factors might contribute to modulating the mechanisms underlying ECT. This study aimed to evaluate the relationship between three polymorphisms (rs1954787, rs4936554 and rs11218030) of the glutamate receptor ionotropic kainate 4 (GRIK4) gene and responsiveness to ECT treatment in a sample of one hundred individuals, TRD or depressive Bipolar Disorder patients resistant to pharmacological treatments. The results revealed that GRIK4 variants were significantly associated with the response to ECT. In particular, we found that patients carrying the G allele of the GRIK4 rs11218030 had a significantly poorer response to ECT (p=2.71×10(-4)), showing five times the risk of relapse after ECT compared to the AA homozygotes. Analogously, patients carrying the GG rs1954787 genotype and rs4936554A allele carriers presented a double risk of lack of response after ECT (p=0.013 and p=0.040, respectively). In conclusion, the current study provides new evidence, indicating that some GRIK4 variants modulate the response to ECT in patients with depression resistant to treatment, suggesting a role for kainate receptor modulation.
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Affiliation(s)
- Alessandra Minelli
- Department of Molecular and Translational Medicine, Biology and Genetic Division, University of Brescia, Brescia, Italy.
| | - Chiara Congiu
- Department of Molecular and Translational Medicine, Biology and Genetic Division, University of Brescia, Brescia, Italy
| | - Mariacarla Ventriglia
- Department of Neuroscience, Fatebenefratelli Foundation, AFaR Division, Fatebenefratelli Hospital-Isola Tiberina, Rome, Italy
| | | | - Cristian Bonvicini
- Genetic Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Maria Abate
- Psychiatric Hospital "Villa Santa Chiara", Verona, Italy
| | - Riccardo Sartori
- Department of Philosophy, Education, Psychology University of Verona, Verona, Italy
| | | | - Massimo Gennarelli
- Department of Molecular and Translational Medicine, Biology and Genetic Division, University of Brescia, Brescia, Italy; Genetic Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
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