Structural Analysis of Pathogenic Missense Mutations in GABRA2 and Identification of a Novel De Novo Variant in the Desensitization Gate
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A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Expression Profiling of Ion Channel Genes Predicts Clinical Outcome in Breast Cancer
UCSF UC San Francisco Previously Published Works Title Expression profiling of ion channel genes predicts clinical outcome in breast cancer Permalink https://escholarship.org/uc/item/1zq9j4nw Journal Molecular Cancer, 12(1) ISSN 1476-4598 Authors Ko, Jae-Hong Ko, Eun A Gu, Wanjun et al. Publication Date 2013-09-22 DOI http://dx.doi.org/10.1186/1476-4598-12-106 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Ko et al. Molecular Cancer 2013, 12:106 http://www.molecular-cancer.com/content/12/1/106 RESEARCH Open Access Expression profiling of ion channel genes predicts clinical outcome in breast cancer Jae-Hong Ko1, Eun A Ko2, Wanjun Gu3, Inja Lim1, Hyoweon Bang1* and Tong Zhou4,5* Abstract Background: Ion channels play a critical role in a wide variety of biological processes, including the development of human cancer. However, the overall impact of ion channels on tumorigenicity in breast cancer remains controversial. Methods: We conduct microarray meta-analysis on 280 ion channel genes. We identify candidate ion channels that are implicated in breast cancer based on gene expression profiling. We test the relationship between the expression of ion channel genes and p53 mutation status, ER status, and histological tumor grade in the discovery cohort. A molecular signature consisting of ion channel genes (IC30) is identified by Spearman’s rank correlation test conducted between tumor grade and gene expression. A risk scoring system is developed based on IC30. We test the prognostic power of IC30 in the discovery and seven validation cohorts by both Cox proportional hazard regression and log-rank test. -
Supplementary Material
Supplementary Material Table S1: Significant downregulated KEGGs pathways identified by DAVID following exposure to five cinnamon- based phenylpropanoids (p < 0.05). p-value Term: Genes (Benjamini) Cytokine-cytokine receptor interaction: FASLG, TNFSF14, CXCL11, IL11, FLT3LG, CCL3L1, CCL3L3, CXCR6, XCR1, 2.43 × 105 RTEL1, CSF2RA, TNFRSF17, TNFRSF14, CCNL2, VEGFB, AMH, TNFRSF10B, INHBE, IFNB1, CCR3, VEGFA, CCR2, IL12A, CCL1, CCL3, CXCL5, TNFRSF25, CCR1, CSF1, CX3CL1, CCL7, CCL24, TNFRSF1B, IL12RB1, CCL21, FIGF, EPO, IL4, IL18R1, FLT1, TGFBR1, EDA2R, HGF, TNFSF8, KDR, LEP, GH2, CCL13, EPOR, XCL1, IFNA16, XCL2 Neuroactive ligand-receptor interaction: OPRM1, THRA, GRIK1, DRD2, GRIK2, TACR2, TACR1, GABRB1, LPAR4, 9.68 × 105 GRIK5, FPR1, PRSS1, GNRHR, FPR2, EDNRA, AGTR2, LTB4R, PRSS2, CNR1, S1PR4, CALCRL, TAAR5, GABRE, PTGER1, GABRG3, C5AR1, PTGER3, PTGER4, GABRA6, GABRA5, GRM1, PLG, LEP, CRHR1, GH2, GRM3, SSTR2, Chlorogenic acid Chlorogenic CHRM3, GRIA1, MC2R, P2RX2, TBXA2R, GHSR, HTR2C, TSHR, LHB, GLP1R, OPRD1 Hematopoietic cell lineage: IL4, CR1, CD8B, CSF1, FCER2, GYPA, ITGA2, IL11, GP9, FLT3LG, CD38, CD19, DNTT, 9.29 × 104 GP1BB, CD22, EPOR, CSF2RA, CD14, THPO, EPO, HLA-DRA, ITGA2B Cytokine-cytokine receptor interaction: IL6ST, IL21R, IL19, TNFSF15, CXCR3, IL15, CXCL11, TGFB1, IL11, FLT3LG, CXCL10, CCR10, XCR1, RTEL1, CSF2RA, IL21, CCNL2, VEGFB, CCR8, AMH, TNFRSF10C, IFNB1, PDGFRA, EDA, CXCL5, TNFRSF25, CSF1, IFNW1, CNTFR, CX3CL1, CCL5, TNFRSF4, CCL4, CCL27, CCL24, CCL25, CCL23, IFNA6, IFNA5, FIGF, EPO, AMHR2, IL2RA, FLT4, TGFBR2, EDA2R, -
Ion Channels
UC Davis UC Davis Previously Published Works Title THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: Ion channels. Permalink https://escholarship.org/uc/item/1442g5hg Journal British journal of pharmacology, 176 Suppl 1(S1) ISSN 0007-1188 Authors Alexander, Stephen PH Mathie, Alistair Peters, John A et al. Publication Date 2019-12-01 DOI 10.1111/bph.14749 License https://creativecommons.org/licenses/by/4.0/ 4.0 Peer reviewed eScholarship.org Powered by the California Digital Library University of California S.P.H. Alexander et al. The Concise Guide to PHARMACOLOGY 2019/20: Ion channels. British Journal of Pharmacology (2019) 176, S142–S228 THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: Ion channels Stephen PH Alexander1 , Alistair Mathie2 ,JohnAPeters3 , Emma L Veale2 , Jörg Striessnig4 , Eamonn Kelly5, Jane F Armstrong6 , Elena Faccenda6 ,SimonDHarding6 ,AdamJPawson6 , Joanna L Sharman6 , Christopher Southan6 , Jamie A Davies6 and CGTP Collaborators 1School of Life Sciences, University of Nottingham Medical School, Nottingham, NG7 2UH, UK 2Medway School of Pharmacy, The Universities of Greenwich and Kent at Medway, Anson Building, Central Avenue, Chatham Maritime, Chatham, Kent, ME4 4TB, UK 3Neuroscience Division, Medical Education Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK 4Pharmacology and Toxicology, Institute of Pharmacy, University of Innsbruck, A-6020 Innsbruck, Austria 5School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, BS8 1TD, UK 6Centre for Discovery Brain Science, University of Edinburgh, Edinburgh, EH8 9XD, UK Abstract The Concise Guide to PHARMACOLOGY 2019/20 is the fourth in this series of biennial publications. The Concise Guide provides concise overviews of the key properties of nearly 1800 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. -
Structural Analysis of Pathogenic Missense Mutations in GABRA2 and Identification of a Novel De Novo Variant in the Desensitization Gate
Received: 22 October 2019 | Revised: 29 November 2019 | Accepted: 10 December 2019 DOI: 10.1002/mgg3.1106 ORIGINAL ARTICLE Structural analysis of pathogenic missense mutations in GABRA2 and identification of a novel de novo variant in the desensitization gate Alba Sanchis-Juan1,2 | Marcia A. Hasenahuer3,4 | James A. Baker3 | Amy McTague5 | Katy Barwick5 | Manju A. Kurian5 | Sofia T. Duarte6 | NIHR BioResource | Keren J. Carss1,2 | Janet Thornton3 | F. Lucy Raymond2,4 1Department of Haematology, University of Cambridge, NHS Blood and Transplant Abstract Centre, Cambridge, UK Background: Cys-loop receptors control neuronal excitability in the brain and their 2NIHR BioResource, Cambridge dysfunction results in numerous neurological disorders. Recently, six missense vari- University Hospitals NHS Foundation ants in GABRA2, a member of this family, have been associated with early infantile Trust, Cambridge Biomedical Campus, Cambridge, UK epileptic encephalopathy (EIEE). We identified a novel de novo missense variant 3European Molecular Biology Laboratory, in GABRA2 in a patient with EIEE and performed protein structural analysis of the European Bioinformatics Institute, seven variants. Wellcome Genome Campus, Hinxton, . Cambridge, UK Methods: The novel variant was identified by trio whole-genome sequencing We 4Department of Medical Genetics, performed protein structural analysis of the seven variants, and compared them to Cambridge Institute for Medical Research, previously reported pathogenic mutations at equivalent positions in other Cys-loop University of Cambridge, Cambridge, UK receptors. Additionally, we studied the distribution of disease-associated variants in 5Developmental Neurosciences, Great the transmembrane helices of these proteins. Ormond Street Institute of Child Health, University College London, London, UK Results: The seven variants are in the transmembrane domain, either close to the de- 6Hospital Dona Estefânia, Centro Hospitalar sensitization gate, the activation gate, or in inter-subunit interfaces. -
Novel Missense Mutations in the Glycine Receptor Β Subunit Gene (GLRB) in Startle Disease
*Manuscript Click here to view linked References Novel missense mutations in the glycine receptor β subunit gene (GLRB) in startle disease Victoria M. Jamesa,bº, Anna Bodecº, Seo-Kyung Chungd,e, Jennifer L. Gilla, Maartje Nielsenf, Frances M. Cowang, Mihailo Vujicg, Rhys H. Thomasd,e, Mark I. Reesd,e, Kirsten Harveya, Angelo Keramidasc, Maya Topfb, Ieke Ginjaarf, Joseph W. Lynchc,i and Robert J. Harveya* aDepartment of Pharmacology, UCL School of Pharmacy, 29-39 Brunswick Square, London WC1N 1AX, United Kingdom; bInstitute for Structural and Molecular Biology, Department of Biological Sciences, Birkbeck College, London WC1E 7HX, United Kingdom; cQueensland Brain Institute, The University of Queensland, Brisbane, QLD 4072 Australia; dInstitute of Life Science, College of Medicine, Swansea University, Swansea SA2 8PP, United Kingdom; eWales Epilepsy Research Network, College of Medicine, Swansea University, Swansea SA2 8PP, United Kingdom; fCenter for Human and Clinical Genetics, Leiden University Medical Center, Einthovenweg 20, 2333 ZC Leiden, The Netherlands; gDepartment of Paediatrics, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London W12 0HS, United Kingdom; hDepartment of Clinical Genetics, Sahlgrenska University Hospital, SE- 41345, Gothenburg, Sweden; iSchool of Biomedical Sciences, The University of Queensland, Brisbane, QLD 4072, Australia. Short title: GlyR β subunit mutations in startle disease ºThese authors contributed equally to this work *Corresponding author: Robert J Harvey, Department of Pharmacology, UCL School of Pharmacy, 29-39 Brunswick Square, London WC1N 1AX, UK. Telephone: +44 207 753 5930; E-mail: [email protected] 1 Abstract Startle disease is a rare, potentially fatal neuromotor disorder characterized by exaggerated startle reflexes and hypertonia in response to sudden unexpected auditory, visual or tactile stimuli. -
Systematic Elucidation of Neuron-Astrocyte Interaction in Models of Amyotrophic Lateral Sclerosis Using Multi-Modal Integrated Bioinformatics Workflow
ARTICLE https://doi.org/10.1038/s41467-020-19177-y OPEN Systematic elucidation of neuron-astrocyte interaction in models of amyotrophic lateral sclerosis using multi-modal integrated bioinformatics workflow Vartika Mishra et al.# 1234567890():,; Cell-to-cell communications are critical determinants of pathophysiological phenotypes, but methodologies for their systematic elucidation are lacking. Herein, we propose an approach for the Systematic Elucidation and Assessment of Regulatory Cell-to-cell Interaction Net- works (SEARCHIN) to identify ligand-mediated interactions between distinct cellular com- partments. To test this approach, we selected a model of amyotrophic lateral sclerosis (ALS), in which astrocytes expressing mutant superoxide dismutase-1 (mutSOD1) kill wild-type motor neurons (MNs) by an unknown mechanism. Our integrative analysis that combines proteomics and regulatory network analysis infers the interaction between astrocyte-released amyloid precursor protein (APP) and death receptor-6 (DR6) on MNs as the top predicted ligand-receptor pair. The inferred deleterious role of APP and DR6 is confirmed in vitro in models of ALS. Moreover, the DR6 knockdown in MNs of transgenic mutSOD1 mice attenuates the ALS-like phenotype. Our results support the usefulness of integrative, systems biology approach to gain insights into complex neurobiological disease processes as in ALS and posit that the proposed methodology is not restricted to this biological context and could be used in a variety of other non-cell-autonomous communication -
A Glycine-Insulin Autocrine Feedback Loop Enhances Insulin Secretion
Page 1 of 41 Diabetes Yan-Do et al. A glycine-insulin autocrine feedback loop enhances insulin secretion from human β-cells and is impaired in type 2 diabetes Richard Yan-Do, Eric Duong, Jocelyn E. Manning Fox, Xiaoqing Dai, Kunimasa Suzuki, Shara Khan, Austin Bautista, Mourad Ferdaoussi, James Lyon, Xichen Wu, Stephen Cheley#, Patrick E. MacDonald*, Matthias Braun# Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Canada, T6G 2E1 #Deceased Running title: Glycine enhances insulin secretion from β-cells Words: 3991 Figures: 6 *Address correspondence to Dr. Patrick MacDonald, Alberta Diabetes Institute, 6-126 Li Ka Shing Centre for Health Research Innovation, Edmonton, Alberta, T6G 2E1, Canada; e-mail: [email protected]; web: www.bcell.org; phone: 780 492 8063 1 Diabetes Publish Ahead of Print, published online May 3, 2016 Diabetes Page 2 of 41 Yan-Do et al. Abstract The secretion of insulin from pancreatic islet β-cells is critical for glucose homeostasis. Disrupted insulin secretion underlies almost all forms of diabetes including the most common form, type 2 diabetes (T2D). The control of insulin secretion is complex and impacted by circulating nutrients, neuronal inputs, and local signaling. In the present study we examined the contribution of glycine, an amino acid and neurotransmitter that activates ligand-gated Cl- currents, to insulin secretion from islets of both non-diabetic (ND) and T2D human donors. We find that human islet β-cells express glycine receptors (GlyR), notably the GlyRα1 subunit, and the glycine transporter (GlyT) isoforms GlyT1 and GlyT2. β-cells exhibit significant glycine- induced Cl- currents that promote membrane depolarization, Ca2+ entry, and insulin secretion from ND β-cells. -
Gene Expression Changes in Glutamate and GABA-A Receptors
HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Alcohol Manuscript Author Clin Exp Res. Author Manuscript Author manuscript; available in PMC 2017 May 01. Published in final edited form as: Alcohol Clin Exp Res. 2016 May ; 40(5): 955–968. doi:10.1111/acer.13056. Gene expression changes in glutamate and GABA-A receptors, neuropeptides, ion channels and cholesterol synthesis in the periaqueductal gray following binge-like alcohol drinking by adolescent alcohol-preferring (P) rats Jeanette N. McClinticka,b, William J. McBridec, Richard L. Bellc, Zheng-Ming Dingc, Yunlong Liud, Xiaoling Xueia,b, and Howard J. Edenberga,b,d,* aDepartment of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, IN 46202, United States bCenter for Medical Genomics, Indiana University School of Medicine, Indianapolis, IN 46202, United States cInstitute of Psychiatric Research, Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN 46202, United States dDepartment of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, United States Abstract Background—Binge-drinking of alcohol during adolescence is a serious public health concern with long-term consequences, including increased pain, fear and anxiety. The periaqueductal gray (PAG) is involved in processing pain, fear and anxiety. The effects of adolescent binge drinking on gene expression in this region have yet to be studied. Methods—Male adolescent P (alcohol preferring) rats were exposed to repeated binge-drinking (three 1-h sessions/day during the dark-cycle, 5 days/week for 3 weeks starting at 28 days of age; ethanol intakes of 2.5 – 3 g/kg/session). We used RNA sequencing to assess the effects of ethanol intake on gene expression. -
GSE50161, (C) GSE66354, (D) GSE74195 and (E) GSE86574
Figure S1. Boxplots of normalized samples in five datasets. (A) GSE25604, (B) GSE50161, (C) GSE66354, (D) GSE74195 and (E) GSE86574. The x‑axes indicate samples, and the y‑axes represent the expression of genes. Figure S2. Volanco plots of DEGs in five datasets. (A) GSE25604, (B) GSE50161, (C) GSE66354, (D) GSE74195 and (E) GSE86574. Red nodes represent upregulated DEGs and green nodes indicate downregulated DEGs. Cut‑off criteria were P<0.05 and |log2 FC|>1. DEGs, differentially expressed genes; FC, fold change; adj.P.Val, adjusted P‑value. Figure S3. Transcription factor‑gene regulatory network constructed using the Cytoscape iRegulion plug‑in. Table SI. Primer sequences for reverse transcription‑quantitative polymerase chain reaction. Genes Sequences hsa‑miR‑124 F: 5'‑ACACTCCAGCTGGGCAGCAGCAATTCATGTTT‑3' R: 5'‑CTCAACTGGTGTCGTGGA‑3' hsa‑miR‑330‑3p F: 5'‑CATGAATTCACTCTCCCCGTTTCTCCCTCTGC‑3' R: 5'‑CCTGCGGCCGCGAGCCGCCCTGTTTGTCTGAG‑3' hsa‑miR‑34a‑5p F: 5'‑TGGCAGTGTCTTAGCTGGTTGT‑3' R: 5'‑GCGAGCACAGAATTAATACGAC‑3' hsa‑miR‑449a F: 5'‑TGCGGTGGCAGTGTATTGTTAGC‑3' R: 5'‑CCAGTGCAGGGTCCGAGGT‑3' CD44 F: 5'‑CGGACACCATGGACAAGTTT‑3' R: 5'‑TGTCAATCCAGTTTCAGCATCA‑3' PCNA F: 5'‑GAACTGGTTCATTCATCTCTATGG‑3' F: 5'‑TGTCACAGACAAGTAATGTCGATAAA‑3' SYT1 F: 5'‑CAATAGCCATAGTCGCAGTCCT‑3' R: 5'‑TGTCAATCCAGTTTCAGCATCA‑3' U6 F: 5'‑GCTTCGGCAGCACATATACTAAAAT‑3' R: 5'‑CGCTTCACGAATTTGCGTGTCAT‑3' GAPDH F: 5'‑GGAAAGCTGTGGCGTGAT‑3' R: 5'‑AAGGTGGAAGAATGGGAGTT‑3' hsa, homo sapiens; miR, microRNA; CD44, CD44 molecule (Indian blood group); PCNA, proliferating cell nuclear antigen; -
Gene Expression Predictors of Breast Cancer Outcomes
GENE EXPRESSION PREDICTORS OF BREAST CANCER OUTCOMES Erich Huang2, Skye H Cheng1, Holly Dressman2, Jennifer Pittman5, Mei-Hua Tsou1, Cheng-Fang Horng1, Andrea Bild2, Edwin S Iversen4,5, Ming Liao5, Chii-Ming Chen1, Mike West5, Joseph R Nevins2,6 and Andrew T Huang1,3 1Koo Foundation Sun Yat-Sen Cancer Center, Taipei, Taiwan 2Department of Molecular Genetics and Microbiology, Duke University Medical Center 3Department of Medicine, Duke University Medical Center 4Department of Biostatistics and Bioinformatics, Duke University Medical Center 5Institute of Statistics and Decision Sciences, Duke University 6Howard Hughes Medical Institute SUMMARY Background The integration of currently accepted risk factors with genomic data carries the promise of focusing the practice of medicine on the individual patient. Such integration requires interpreting the complex, multivariate patterns in gene expression data, and evaluating their capacity to improve clinical predictions. We do this here, in a study of predicting nodal metastatic states and relapse for breast cancer patients. Methods DNA microarray data from samples of primary breast tumors were analyzed using non-linear statistical analyses to evaluate multiple patterns of interactions of groups of genes that have predictive value, at the individual patient level, with respect to lymph node metastasis and cancer recurrence. Findings We identify aggregate patterns of gene expression (metagenes) that associate with lymph node status and recurrence, and that are capable of honestly predicting outcomes in individual patients with about 90% accuracy. The identified metagenes define distinct groups of genes, suggesting different biological processes underlying these two characteristics of breast cancer. Initial external validation comes from similarly accurate predictions of nodal status of a small sample in a quite distinct population group. -
Differences in Neural-Immune Gene Expression Response in Rat Spinal Dorsal Horn Correlates with Variations in Electroacupuncture Analgesia
Differences in Neural-Immune Gene Expression Response in Rat Spinal Dorsal Horn Correlates with Variations in Electroacupuncture Analgesia Ke Wang1., Rong Zhang2., Xiaohui Xiang2, Fei He1, Libo Lin1, Xingjie Ping2, Lei Yu3, Jisheng Han2, Guoping Zhao1,4*, Qinghua Zhang1*, Cailian Cui2* 1 Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai and National Engineering Research Center for Biochip at Shanghai, Shanghai, China, 2 Neuroscience Research Institute; Department of Neurobiology, Peking University Health Science Center; Key Laboratory of Neuroscience of the Ministry of Education and the Ministry of Public Health; Peking University, Beijing, China, 3 Department of Genetics and Center of Alcohol Studies, Piscataway, New Jersey, United States of America, 4 Department of Microbiology and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong Special Administrative Region, China Abstract Background: Electroacupuncture (EA) has been widely used to alleviate diverse pains. Accumulated clinical experiences and experimental observations indicated that significant differences exist in sensitivity to EA analgesia for individuals of patients and model animals. However, the molecular mechanism accounting for this difference remains obscure. Methodology/Principal Findings: We classified model male rats into high-responder (HR; TFL changes .150) and non- responder (NR; TFL changes #0) groups based on changes of their pain threshold detected by tail-flick latency (TFL) before and after 2 Hz or 100 Hz EA treatment. Gene expression analysis of spinal dorsal horn (DH) revealed divergent expression in HR and NR after 2 Hz/100 Hz EA. The expression of the neurotransmitter system related genes was significantly highly regulated in the HR animals while the proinflammation cytokines related genes were up-regulated more significantly in NR than that in HR after 2 Hz and 100 Hz EA stimulation, especially in the case of 2 Hz stimulation.