Volume 30, Issue 3 (September 2026)
Physiol Pharmacol 2026, 30(3): 283-295 |
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Shamshiri S, Shamshiri S, Kalantari-Khandani B, Niazi M, Ziaastani Z, Kazemipour A. Identification of drug targets and their candidate drugs in multiple sclerosis and bipolar disorder via systems biology approach. Physiol Pharmacol 2026; 30 (3) :283-295
URL: http://ppj.phypha.ir/article-1-2587-en.html
URL: http://ppj.phypha.ir/article-1-2587-en.html
Shahang Shamshiri 
, Shahedeh Shamshiri , Behjat Kalantari-Khandani , Mohammad-Javad Niazi , Zahra Ziaastani , Ali Kazemipour 
, Shahedeh Shamshiri , Behjat Kalantari-Khandani , Mohammad-Javad Niazi , Zahra Ziaastani , Ali Kazemipour
Abstract: (982 Views)
Introduction: Multiple sclerosis (MS) is an autoimmune disease characterized by demyelination of the central nervous system. Bipolar Disorder (BD) is a complex psychiatric condition. Patients with MS have a significantly elevated risk of developing BD. The present study aimed to investigate the shared genetic mechanisms between MS-BD using systems biology approaches.
Methods: We constructed a protein-protein interaction (PPI) network of the overlapping MS-BD genes using the STRING database and identified functional modules and hub genes with Cytoscape. Gene ontology and pathway enrichment analyses of the modules and hub genes were performed using g:Profiler. Potential drug targets among these genes were further explored using DGIdb.
Results: A total of 206 genes associated with MS and 201 genes associated with BD were retrieved from the NCBI, of which 55 genes were common to both diseases. PPI network analysis revealed ten functional modules. Ten hub genes—TNF, IL6, IL1B, TLR4, AKT1, BCL2, IFNG, APP, NFKB1, and mTOR—were identified as central players in both conditions. TNF and IL-6 showed upregulated expression in MS-BD and emerged as promising drug targets. The enriched KEGG pathways included tuberculosis, HIF-1 signaling, AGE-RAGE signaling in diabetic complications, and the Toll-like receptor signaling pathway.
Conclusion: Our findings highlight the shared biological processes and gene expression patterns between MS-BD. These results suggest that MS-BD may involve common underlying mechanisms, which could provide opportunities for repurposing existing drugs and developing combined therapeutic strategies. Such insights may ultimately improve prevention and treatment approaches for MS-BD, as well as related comorbidities.
Keywords: Multiple sclerosis, Bipolar disorder, PPI network, Drug target identification, Systems biology
Type of Manuscript: Review |
Subject:
Neurophysiology/Pharmacology
References
1. Aflouk Y, Saoud H, Inoubli O, Yacoub S, Zaafrane F, Gaha L, et al. TLR4 polymorphisms (T399I/D299G) Association with schizophrenia and bipolar disorder in a tunisian population. Biochemical Genetics 2024; 62: 2418-2436. [DOI:10.1007/s10528-023-10553-z]
2. Akbarian F, Tabatabaiefar M A, Shaygannejad V, Shahpouri M M, Badihian N, Sajjadi R, et al. Upregulation of MTOR, RPS6KB1, and EIF4EBP1 in the whole blood samples of Iranian patients with multiple sclerosis compared to healthy controls. Metabolic Brain Disease 2020; 35: 1309-1316. [DOI:10.1007/s11011-020-00590-7]
3. Aldinger F, Schulze T G. Environmental factors, life events, and trauma in the course of bipolar disorder. Psychiatry and Clinical Neurosciences 2017; 71: 6-17. [DOI:10.1111/pcn.12433]
4. Asadzadeh Manjili F, Yousefi-Ahmadipour A, Kazemi Arababadi M. The roles played by TLR4 in the pathogenesis of multiple sclerosis; A systematic review article. Immunology Letters 2020; 220: 63-70. [DOI:10.1016/j.imlet.2020.02.004]
5. Balcerac A, Louapre C. Genetics and familial distribution of multiple sclerosis: A review. Revue Neurologique 2022; 178: 512-520. [DOI:10.1016/j.neurol.2021.11.009]
6. Bame M, McInnis M G, O’Shea K S. MicroRNA alterations in induced pluripotent stem cell-derived neurons from bipolar disorder patients: pathways involved in neuronal differentiation, axon guidance, and plasticity. Stem Cells and Development 2020; 29: 1145-1159. [DOI:10.1089/scd.2020.0046]
7. Boles G S, Hillert J, Ramanujam R, Westerlind H, Olsson T, Kockum I, et al. The familial risk and heritability of multiple sclerosis and its onset phenotypes: A case-control study. Multiple Sclerosis Journal 2023; 29: 1209-1215. [DOI:10.1177/13524585231185258]
8. Brietzke E, Kapczinski F. TNF-α as a molecular target in bipolar disorder. Progress in Neuro-Psychopharmacology and Biological Psychiatry 2008; 32: 1355-1361. [DOI:10.1016/j.pnpbp.2008.01.006]
9. Carta M G, Moro M F, Lorefice L, Trincas G, Cocco E, Giudice E D, et al. The risk of Bipolar Disorders in Multiple Sclerosis. Journal of Affective Disorders 2014; 155: 255-260. [DOI:10.1016/j.jad.2013.11.008]
10. Corrêa-Velloso J C, Gonçalves M C B, Naaldijk Y, Oliveira-Giacomelli Á, Pillat M M, Ulrich H. Pathophysiology in the comorbidity of Bipolar Disorder and Alzheimer’s Disease: pharmacological and stem cell approaches. Progress in Neuro-Psychopharmacology and Biological Psychiatry 2018; 80: 34-53. [DOI:10.1016/j.pnpbp.2017.04.033]
11. Darrau E, Jacquemet E, Pons S, Schlick L, Zouridakis M, Wu C-L, et al. Serum autoantibodies against α7-nicotinic receptors in subgroups of patients with bipolar disorder or schizophrenia: clinical features and link with peripheral inflammation. Translational Psychiatry 2024; 14: 146. [DOI:10.1038/s41398-024-02853-8]
12. Ebers G C, Bulman D E, Sadovnick A D, Paty D W, Warren S, Hader W, et al. A population-based study of multiple sclerosis in twins. New England Journal of Medicine 1986; 315: 1638-1642. [DOI:10.1056/NEJM198612253152603]
13. Fabbri C. The role of genetics in bipolar disorder.” Bipolar disorder: from neuroscience to treatment. Cham: Springer International Publishing 2021: 41-60. [DOI:10.1007/7854_2020_153]
14. Fazia T, Nova A, Gentilini D, Beecham A, Piras M, Saddi V, et al. Investigating the causal effect of brain expression of CCL2, NFKB1, MAPK14, TNFRSF1A, CXCL10 genes on multiple sclerosis: a two-sample mendelian randomization approach. Frontiers in Bioengineering and Biotechnology 2020; 8: 397. [DOI:10.3389/fbioe.2020.00397]
15. Franz M, Lopes C T, Fong D, Kucera M, Cheung M, Siper M C, et al. Cytoscape. js 2023 update: a graph theory library for visualization and analysis. Bioinformatics 2023; 39: btad031. [DOI:10.1093/bioinformatics/btad031]
16. Fresegna D, Bullitta S, Musella A, Rizzo F R, De Vito F, Guadalupi L, et al. Re-examining the role of TNF in MS pathogenesis and therapy. Cells 2020; 9: 2290. [DOI:10.3390/cells9102290]
17. Fymat A L. Multiple sclerosis: II. Diagnosis and symptoms management. Journal of Neurology and Psychology Research 2023; 4: 1-21.
18. Gehrmann J, Banati R B, Cuzner M L, Kreutzberg G W, Newcombe J. Amyloid precursor protein (APP) expression in multiple sclerosis lesions. Glia 1995; 15: 141-151. [DOI:10.1002/glia.440150206]
19. Gonzalez Caldito N. Role of tumor necrosis factor-alpha in the central nervous system: a focus on autoimmune disorders. Frontiers in Immunology 2023; 14: 1213448. [DOI:10.3389/fimmu.2023.1213448]
20. Goodin D S, Khankhanian P, Gourraud P-A, Vince N. Multiple sclerosis: Exploring the limits and implications of genetic and environmental susceptibility. PLOS One 2023; 18: e0285599. [DOI:10.1371/journal.pone.0285599]
21. Healy L M, Stratton J A, Kuhlmann T, Antel J. The role of glial cells in multiple sclerosis disease progression. Nature Reviews Neurology 2022; 18: 237-248. [DOI:10.1038/s41582-022-00624-x]
22. Javed A, Reder A T. Therapeutic role of beta-interferons in multiple sclerosis. Pharmacology & Therapeutics 2006; 110: 35-56. [DOI:10.1016/j.pharmthera.2005.08.011]
23. Jin Q, Yang Y, Chen Q, Lu Z. GeneGPT: augmenting large language models with domain tools for improved access to biomedical information. Bioinformatics 2024; 40: btae075. [DOI:10.1093/bioinformatics/btae075]
24. Johansson V, Kuja-Halkola R, Cannon T D, Hultman C M, Hedman A M. A population-based heritability estimate of bipolar disorder - In a Swedish twin sample. Psychiatry Research 2019; 278: 180-187. [DOI:10.1016/j.psychres.2019.06.010]
25. Joseph B, Nandakumar A L, Ahmed A T, Gopal N, Murad M H, Frye M A, et al. Prevalence of bipolar disorder in multiple sclerosis: a systematic review and meta-analysis. BMJ Mental Health 2021a; 24: 88-94. [DOI:10.1136/ebmental-2020-300207]
26. Joseph B, Nandakumar A L, Ahmed A T, Gopal N, Murad M H, Frye M A, et al. Prevalence of bipolar disorder in multiple sclerosis: a systematic review and meta-analysis. Evidence-Based Mental Health 2021b; 24: 88-94. [DOI:10.1136/ebmental-2020-300207]
27. Kasyanov E D, Merkulova T V, Kibitov A O, Mazo G E. Genetics of bipolar spectrum disorders: focus on family studies using whole exome sequencing. Russian Journal of Genetics 2020; 56: 786-801. [DOI:10.1134/S1022795420070054]
28. Kinnunen E, Koskenvuo M, Kaprio J, Aho K. Multiple sclerosis in a nationwide series of twins. Neurology 1987; 37: 1627-1627. [DOI:10.1212/WNL.37.10.1627]
29. Kokas Z, Járdánházy A, Sandi D, Biernacki T, Fricska-Nagy Z, Füvesi J, et al. Real-world operation of multiple sclerosis centres in Central-Eastern European countries covering 107 million inhabitants. Multiple Sclerosis and Related Disorders 2023; 69: 104406. [DOI:10.1016/j.msard.2022.104406]
30. Lalli M, Brouillette K, Kapczinski F, de Azevedo Cardoso T. Substance use as a risk factor for bipolar disorder: A systematic review. Journal of Psychiatric Research 2021; 144: 285-295. [DOI:10.1016/j.jpsychires.2021.10.012]
31. Li Z, Liu Y, Jia A, Cui Y, Feng J. Cerebrospinal fluid cells immune landscape in multiple sclerosis. Journal of Translational Medicine 2021; 19: 1-16. [DOI:10.1186/s12967-021-02804-7]
32. Liu S, Chen H, He X-D, Yang X-O. Glucometabolic-.related genes as diagnostic biomarkers and therapeutic targets for Alzheimer’s Disease and type 2 Diabetes Mellitus: a bioinformatics analysis. Neurology Research International 2024; 2024: 5200222. [DOI:10.1155/2024/5200222]
33. Luczynski P, Laule C, Hsiung G-Y R, Moore G R W, Tremlett H. Coexistence of Multiple Sclerosis and Alzheimer’s disease: A review. Multiple Sclerosis and Related Disorders 2019; 27: 232-238. [DOI:10.1016/j.msard.2018.10.109]
34. Lutfullin I, Eveslage M, Bittner S, Antony G, Flaskamp M, Luessi F, et al. Association of obesity with disease outcome in multiple sclerosis. Journal of Neurology, Neurosurgery & Psychiatry 2023; 94: 57-61. [DOI:10.1136/jnnp-2022-329685]
35. Machado-Vieira R, Zanetti M V, Teixeira A L, Uno M, Valiengo L L, Soeiro-de-Souza M G, et al. Decreased AKT1/mTOR pathway mRNA expression in short-term bipolar disorder. European Neuropsychopharmacology 2015; 25: 468-473. [DOI:10.1016/j.euroneuro.2015.02.002]
36. Marcus R. What is Multiple Sclerosis? Journal of the American Medical Association 2022; 328: 2078-2078. [DOI:10.1001/jama.2022.14236]
37. McIntyre R S, Berk M, Brietzke E, Goldstein B I, López-Jaramillo C, Kessing L V, et al. Bipolar disorders. The Lancet 2020; 396: 1841-1856. [DOI:10.1016/S0140-6736(20)31544-0]
38. Meier U-C, Ramagopalan S V, Goldacre M J, Goldacre R. Risk of Schizophrenia and Bipolar Disorder in Patients With Multiple Sclerosis: Record-Linkage Studies. Frontiers in Psychiatry 2020; 11. [DOI:10.3389/fpsyt.2020.00662]
39. Menculini G, Balducci P M, Attademo L, Bernardini F, Moretti P, Tortorella A. Environmental risk factors for bipolar disorders and high-risk states in adolescence: a systematic review. Medicina 2020; 56: 689. [DOI:10.3390/medicina56120689]
40. Mora P, Chapouly C. Astrogliosis in multiple sclerosis and neuro-inflammation: what role for the notch pathway? Frontiers in Immunology 2023; 14: 1254586. [DOI:10.3389/fimmu.2023.1254586]
41. Muneer A. Bipolar disorder: role of inflammation and the development of disease biomarkers. Psychiatry Investig 2016; 13: 18-33. [DOI:10.4306/pi.2016.13.1.18]
42. Oktelik F B, Yilmaz V, Turkoglu R, Akbayir E, Tuzun E, Deniz G, et al. Expression of Akt1 and p-Akt1 in peripheral T cell subsets of multiple sclerosis patients. Acta Neurologica Belgica 2021; 121: 1777-1782. [DOI:10.1007/s13760-020-01518-9]
43. Park S W, Seo M K, Webster M J, Lee J G, Kim S. Differential expression of gene co-expression networks related to the mTOR signaling pathway in bipolar disorder. Translational Psychiatry 2022; 12: 184. [DOI:10.1038/s41398-022-01944-8]
44. Rantala M J, Luoto S, Borráz-León J I, Krams I. Bipolar disorder: An evolutionary psychoneuroimmunological approach. Neuroscience & Biobehavioral Reviews 2021; 122: 28-37. [DOI:10.1016/j.neubiorev.2020.12.031]
45. Robinson N, Bergen S E. Environmental risk factors for schizophrenia and bipolar disorder and their relationship to genetic risk: current knowledge and future directions. Frontiers in Genetics 2021; 12. [DOI:10.3389/fgene.2021.686666]
46. Rodríguez Murúa S, Farez M F, Quintana F J. The immune response in multiple sclerosis. Annual Review of Pathology: Mechanisms of Disease 2022; 17: 121-139. [DOI:10.1146/annurev-pathol-052920-040318]
47. Roman K M, Jenkins A K, Lewis D A, Volk D W. Involvement of the nuclear factor-κB transcriptional complex in prefrontal cortex immune activation in bipolar disorder. Translational Psychiatry 2021; 11: 40. [DOI:10.1038/s41398-020-01092-x]
48. Stampanoni Bassi M, Iezzi E, Drulovic J, Pekmezovic T, Gilio L, Furlan R, et al. IL-6 in the Cerebrospinal Fluid Signals Disease Activity in Multiple Sclerosis. Frontiers in Cellular Neuroscience 2020; 14. [DOI:10.3389/fncel.2020.00120]
49. Strenn N, Pålsson E, Liberg B, Landén M, Ekman A. Influence of genetic variations in IL1B on brain region volumes in bipolar patients and controls. Psychiatry Research 2021; 296: 113606. [DOI:10.1016/j.psychres.2020.113606]
50. Szklarczyk D, Kirsch R, Koutrouli M, Nastou K, Mehryary F, Hachilif R, et al. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Research 2023; 51: D638-D646. [DOI:10.1093/nar/gkac1000]
51. Vadodaria K C, Mendes A P, Mei A, Racha V, Erikson G, Shokhirev M N, et al. Altered neuronal support and inflammatory response in bipolar disorder patient-derived astrocytes. Stem Cell Reports 2021; 16: 825-835. [DOI:10.1016/j.stemcr.2021.02.004]
52. Vasić M, Topić A, Marković B, Milinković N, Dinčić E. Oxidative stress-related risk of the multiple sclerosis development. Journal of Medical Biochemistry 2023; 42: 1. [DOI:10.5937/jomb0-37546]
53. Vesic K, Gavrilovic A, Mijailović N R, Borovcanin M M. Neuroimmune, clinical and treatment challenges in multiple sclerosis-related psychoses. World Journal of Psychiatry 2023; 13: 161-170. [DOI:10.5498/wjp.v13.i4.161]
54. Vitturi B K, Rahmani A, Dini G, Montecucco A, Debarbieri N, Sbragia E, et al. Occupational outcomes of people with multiple sclerosis: a scoping review. BMJ Open 2022; 12: e058948. [DOI:10.1136/bmjopen-2021-058948]
55. Vong V, Simpson-Yap S, Phaiju S, Davenport R A, Neate S L, Pisano M I, et al. The association between tobacco smoking and depression and anxiety in people with multiple sclerosis: A systematic review. Multiple Sclerosis and Related Disorders 2023; 70: 104501. [DOI:10.1016/j.msard.2023.104501]
56. Walton C, King R, Rechtman L, Kaye W, Leray E, Marrie R A, et al. Rising prevalence of multiple sclerosis worldwide: Insights from the Atlas of MS. Multiple Sclerosis Journal 2020; 26: 1816-1821. [DOI:10.1177/1352458520970841]
57. Waubant E, Lucas R, Mowry E, Graves J, Olsson T, Alfredsson L, et al. Environmental and genetic risk factors for MS: an integrated review. Annals of Clinical and Translational Neurology 2019; 6: 1905-1922. [DOI:10.1002/acn3.50862]
58. Xu F, Su Y, Wang X, Zhang T, Xie T, Wang Y. Olink proteomics analysis uncovers inflammatory proteins in patients with different states of bipolar disorder. International Immunopharmacology 2024; 131: 111816. [DOI:10.1016/j.intimp.2024.111816]
59. Younger D S. Chapter 6 - Multiple sclerosis: Motor dysfunction. In: Younger DS, editor. Handbook of Clinical Neurology. Vol 196: Elsevier, 2023: 119-147. [DOI:10.1016/B978-0-323-98817-9.00016-8]
60. Ziaastani Z, Kalantari-Khandani B, Niazi M-J, Kazemipour A. Identification of critical genes and metabolic pathways in rheumatoid arthritis and osteoporosis toward drug repurposing. Computers in Biology and Medicine 2024; 180: 108912. [DOI:10.1016/j.compbiomed.2024.108912]
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