Skip to main content
SpringerLink
Log in

Dysregulated Genes and Signaling Pathways in the Formation and Rupture of Intracranial Aneurysm

  • Research
  • Published:
Translational Stroke Research Aims and scope Submit manuscript

Abstract

Intracranial aneurysm (IA) has the potential to rupture. Despite scientific advances, we are still not in a position to screen patients for IA and identify those at risk of rupture. It is critical to comprehend the molecular basis of disease to facilitate the development of novel diagnostic strategies. We used transcriptomics to identify the dysregulated genes and understand their role in the disease biology. In particular, RNA-Seq was performed in tissue samples of controls, unruptured IA, and ruptured IA. Dysregulated genes (DGs) were identified and analyzed to understand the functional aspects of molecules. Subsequently, candidate genes were validated at both transcript and protein level. There were 314 DGs in patients with unruptured IA when compared to control samples. Out of these, SPARC and OSM were validated as candidate molecules in unruptured IA. PI3K-AKT signaling pathway was found to be an important pathway for the formation of IA. Similarly, 301 DGs were identified in the samples of ruptured IA when compared with unruptured IAs. CTSL was found to be a key candidate molecule which along with Hippo signaling pathway may be involved in the rupture of IA. We conclude that activation of PI3K-AKT signaling pathway by OSM along with up-regulation of SPARC is important for the formation of IA. Further, regulation of Hippo pathway through PI3K-AKT signaling results in the down-regulation of YAP1 gene. This along with up-regulation of CTSL leads to further weakening of aneurysm wall and its subsequent rupture.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data Availability

The datasets generated for this study can be found in the Sequence Read Archive hosted by National Center for Biotechnology Information Search database (NCBI) with accession number: PRJNA524023.

References

  1. Thompson JW, Elwardany O, McCarthy DJ, Sheinberg DL, Alvarez CM, Nada A, et al. In vivo cerebral aneurysm models. Neurosurg Focus. 2019;47:E20. https://doi.org/10.3171/2019.4.FOCUS19219.

    Article  PubMed  Google Scholar 

  2. Wu Y, Li Z, Shi Y, Chen L, Tan H, Wang Z, et al. Exome sequencing identifies LOXL2 mutation as a cause of familial intracranial aneurysm. World Neurosurg. 2018;109:e812–8. https://doi.org/10.1016/j.wneu.2017.10.094.

    Article  PubMed  Google Scholar 

  3. Song Y, Lee JK, Lee JO, Kwon B, Seo EJ, Suh DC. Whole exome sequencing in patients with phenotypically associated familial intracranial aneurysm. Korean J Radiol. 2022;23:101–11. https://doi.org/10.3348/kjr.2021.0467.

    Article  PubMed  Google Scholar 

  4. Tromp G, Weinsheimer S, Ronkainen A, Kuivaniemi H. Molecular basis and genetic predisposition to intracranial aneurysm. Ann Med. 2014;46:597–606. https://doi.org/10.3109/07853890.2014.949299.

    Article  CAS  PubMed  Google Scholar 

  5. Sharma T, Datta KK, Kumar M, Dey G, Khan AA, Mangalaparthi KK, et al. Intracranial aneurysm biomarker candidates identified by a proteome-wide study. OMICS. 2020;24:483–92. https://doi.org/10.1089/omi.2020.0057.

    Article  CAS  PubMed  Google Scholar 

  6. Wang J, Yu L, Huang X, Wang Y, Zhao J. Comparative proteome analysis of saccular intracranial aneurysms with iTRAQ quantitative proteomics. J Proteomics. 2016;130:120–8. https://doi.org/10.1016/j.jprot.2015.09.014.

    Article  CAS  PubMed  Google Scholar 

  7. Sakaya GR, Parada CA, Eichler RA, Yamaki VN, Navon A, Heimann AS, et al. Peptidomic profiling of cerebrospinal fluid from patients with intracranial saccular aneurysms. J Proteomics. 2021;240:104188. https://doi.org/10.1016/j.jprot.2021.104188.

    Article  CAS  PubMed  Google Scholar 

  8. Poppenberg KE, Li L, Waqas M, Paliwal N, Jiang K, Jarvis JN, et al. Whole blood transcriptome biomarkers of unruptured intracranial aneurysm. PLoS One. 2020;15:e0241838. https://doi.org/10.1371/journal.pone.0241838.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Tutino VM, Zebraski HR, Rajabzadeh-Oghaz H, Waqas M, Jarvis JN, Bach K, et al. Identification of circulating gene expression signatures of intracranial aneurysm in peripheral blood mononuclear cells. Diagnostics (Basel). 2021;11:1092. https://doi.org/10.3390/diagnostics11061092.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Fan J, Yu L, Zhao J. Comparative transcriptome analysis reveals involvement of TLR-2 signaling in the pathogenesis of intracranial aneurysm. J Clin Neurosci. 2018;47:258–63. https://doi.org/10.1016/j.jocn.2017.07.016.

    Article  CAS  PubMed  Google Scholar 

  11. Kleinloog R, Verweij BH, van der Vlies P, Deelen P, Swertz MA, de Muynck L, et al. RNA sequencing analysis of intracranial aneurysm walls reveals involvement of lysosomes and immunoglobulins in rupture. Stroke. 2016;47:1286–93. https://doi.org/10.1161/STROKEAHA.116.012541.

    Article  CAS  PubMed  Google Scholar 

  12. Kurki MI, Hakkinen SK, Frosen J, Tulamo R, von Und Zu Fraunberg M, Wong G, et al. Upregulated signaling pathways in ruptured human saccular intracranial aneurysm wall: an emerging regulative role of toll-like receptor signaling and nuclear factor-kB, hypoxia-inducible factor-1A, and ETS transcription factors. Neurosurgery. 2011;68:1667–75. https://doi.org/10.1227/NEU.0b013e318210f001.

    Article  PubMed  Google Scholar 

  13. Nakaoka H, Tajima A, Yoneyama T, Hosomichi K, Kasuya H, Mizutani T, et al. Gene expression profiling reveals distinct molecular signatures associated with the rupture of intracranial aneurysm. Stroke. 2014;45(8):2239–45. https://doi.org/10.1161/STROKEAHA.114.005851.

    Article  CAS  PubMed  Google Scholar 

  14. Pera J, Korostynski M, Krzyszkowski T, Czopek J, Slowik A, Dziedzic T, et al. Gene expression profiles in human ruptured and unruptured intracranial aneurysms. What Is the Role of Inflammation? Stroke. 2010;41:224–31. https://doi.org/10.1161/STROKEAHA.109.562009.

    Article  CAS  PubMed  Google Scholar 

  15. Jiang Y, Zhang M, He H, Chen J, Zeng H, Li J, et al. MicroRNA/mRNA profiling and regulatory network of intracranial aneurysm. BMC Med Genomics. 2013;6:36. https://doi.org/10.1186/1755-8794-6-36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Tutino VM, Zebraski HR, Rajabzadeh-Oghaz H, Chaves L, Dmytriw AA, Siddiqui AH, et al. RNA sequencing data from human intracranial aneurysm tissue reveals a complex inflammatory environment associated with rupture. Mol Diagn Ther. 2021;25:775–90. https://doi.org/10.1007/s40291-021-00552-4.

    Article  CAS  PubMed  Google Scholar 

  17. Chen X, Yang S, Yang J, Liu Q, Li M, Wu J, et al. Circular RNA circDUS2 is a potential biomarker for intracranial aneurysm. Front Aging Neurosci. 2021;13:632448. https://doi.org/10.3389/fnagi.2021.63244.

    Article  CAS  PubMed Central  Google Scholar 

  18. Chen S, Li M, Xin W, Liu S, Zheng L, Li Y, et al. Intracranial aneurysm's association with genetic variants, transcription abnormality, and methylation changes in ADAMTS genes. PeerJ. 2020;8:e8596. https://doi.org/10.7717/peerj.8596.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Lorenzo-Betancor O, Blackburn PR, Edwards E, Vázquez-do-Campo R, Klee EW, Labbé C, et al. PCNT point mutations and familial intracranial aneurysms. Neurology. 2018;91:e217081. https://doi.org/10.1212/WNL.0000000000006614.

    Article  CAS  Google Scholar 

  20. Aoki T, Koseki H, Miyata H, Itoh M, Kawaji H, Takizawa K, et al. RNA sequencing analysis revealed the induction of CCL3 expression in human intracranial aneurysms. Sci Rep. 2019;9:10387. https://doi.org/10.1038/s41598-019-46886-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Andrews S (2010). FastQC: a quality control tool for high throughput sequence data. Available online at: http://www.bioinformatics.babraham.ac.uk/projects/fastqc

  22. Pertea G. 2015. Fqtrim: v0.9.4 release. https://ccb.jhu.edu/software/fqtrim/

  23. Kim D, Langmead B, Salzberg SL. HISAT: A fast spliced aligner with low memory requirements. Nat Methods. 2015;12:357–60. https://doi.org/10.1038/nmeth.3317.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Pertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL. Stringtie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol. 2015;33:290–5. https://doi.org/10.1038/nbt.3122.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Anders S, Pyl PT, Huber W. HTSeq-a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31:166–9. https://doi.org/10.1093/bioinformatics/btu638.

    Article  CAS  PubMed  Google Scholar 

  26. Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010;11:R106. https://doi.org/10.1186/gb-2010-11-10-r106.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Pathan M, Keerthikumar S, Ang CS, Gangoda L, Quek CY, Williamson NA, et al. FunRich: An open access standalone functional enrichment and interaction network analysis tool. Proteomics. 2015;15:2597–601. https://doi.org/10.1002/pmic.201400515.

    Article  CAS  PubMed  Google Scholar 

  28. Huang da W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4:44–57. https://doi.org/10.1038/nprot.2008.211.

    Article  CAS  PubMed  Google Scholar 

  29. Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: Protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47:D607–13. https://doi.org/10.1093/nar/gky1131.

    Article  CAS  PubMed  Google Scholar 

  30. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13:2498–504. https://doi.org/10.1101/gr.1239303.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Mi H, Muruganujan A, Huang X, Ebert D, Mills C, Guo X, et al. Protocol update for large-scale genome and gene function analysis with the PANTHER classification system (v.14.0). Nat Protoc. 2019;14:703–21. https://doi.org/10.1038/s41596-019-0128-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Ye J, Coulouris G, Zaretskaya I, Cutcutache I, Rozen S, Madden TL. Primer-blast: a tool to design target-specific primers for polymerase chain reaction. BMC Bioinformatics. 2012;13:134. https://doi.org/10.1186/1471-2105-13-134.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Bekelis K, Kerley-Hamilton JS, Teegarden A, Tomlinson CR, Kuintzle R, Simmons N, et al. MicroRNA and gene expression changes in unruptured human cerebral aneurysms. J Neurosurg. 2016;125:1390–9. https://doi.org/10.3171/2015.11.JNS151841.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Li H, Wang W, Zhang L, Lan Q, Wang J, Cao Y, et al. Identification of a long noncoding RNA-associated competing endogenous RNA network in intracranial aneurysm. World Neurosurg. 2017;97:684–692.e4. https://doi.org/10.1016/j.wneu.2016.10.016.

    Article  PubMed  Google Scholar 

  35. Li Z, Tan H, Shi Y, Huang G, Wang Z, Liu L, et al. Global gene expression patterns and somatic mutations in sporadic intracranial aneurysms. World Neurosurg. 2017;100:15–21. https://doi.org/10.1016/j.wneu.2016.12.109.

    Article  PubMed  Google Scholar 

  36. Laarman MD, Kleinloog R, Bakker MK, Rinkel GJ, Bakkers J, Ruigrok YM. Assessment of the most optimal control tissue for intracranial aneurysm gene expression studies. Stroke. 2019;50:2933–6. https://doi.org/10.1161/STROKEAHA.119.024881.

    Article  CAS  PubMed  Google Scholar 

  37. Aoki T, Frosen J, Fukuda M, Bando K, Shioi G, Tsuji K, et al. Prostaglandin E2-EP2-NF-κB signaling in macrophages as a potential therapeutic target for intracranial aneurysms. Sci Signal. 2017;10(465):eaah6037. https://doi.org/10.1126/scisignal.aah6037.

    Article  CAS  PubMed  Google Scholar 

  38. Laaksamo E, Tulamo R, Baumann M, Dashti R, Hernesniemi J, Juvela S, et al. Involvement of mitogen-activated protein kinase signaling in growth and rupture of human intracranial aneurysms. Stroke. 2008;39:886–92. https://doi.org/10.1161/STROKEAHA.107.497875.

    Article  CAS  PubMed  Google Scholar 

  39. Wang L, Chen Y, Sternberg P, Cai J. Essential roles of the PI3 Kinase/Akt pathway in regulating Nrf2-dependent antioxidant functions in the RPE. Invest Ophthalmol Vis Sci. 2008;49:1671–8. https://doi.org/10.1167/iovs.07-1099.

    Article  PubMed  Google Scholar 

  40. Liu R, Chen Y, Liu G, Li C, Song Y, Cao Z, et al. PI3K/Akt pathway as a key link modulates the multidrug resistance of cancers. Cell Death Dis. 2020;11:797. https://doi.org/10.1038/s41419-020-02998-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Zhao Y, Qian Y, Sun Z, Shen X, Cai Y, Li L, et al. Role of PI3K in the progression and regression of atherosclerosis. Front Pharmacol. 2021;12:632378. https://doi.org/10.3389/fphar.2021.632378.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Penn DL, Witte SR, Komotar RJ, Connolly ES Jr. The role of vascular remodeling and inflammation in the pathogenesis of intracranial aneurysms. J Clin Neurosci. 2014;21:28–32. https://doi.org/10.1016/j.jocn.2013.07.004.

    Article  PubMed  Google Scholar 

  43. Greene MA, Loeser RF. Function of the chondrocyte PI-3 kinase-Akt signaling pathway is stimulus dependent. Osteoarthritis Cartilage. 2015;23:949–56. https://doi.org/10.1016/j.joca.2015.01.014.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Li MH, Li PG, Huang QL, Ling J. Endothelial injury preceding intracranial aneurysm formation in rabbits. West Indian Med J. 2014;63:167–71. https://doi.org/10.7727/wimj.2013.129.

    Article  CAS  PubMed  Google Scholar 

  45. Chalouhi N, Hoh BL, Hasan D. Review of cerebral aneurysm formation, growth, and rupture. Stroke. 2013;44:3613–22. https://doi.org/10.1161/STROKEAHA.113.002390.

    Article  PubMed  Google Scholar 

  46. Turkmani AH, Edwards NJ, Chen PR. The role of inflammation in cerebral aneurysms. Neuroimmunol Neuroinflammation. 2015;2:102–6.

    Article  CAS  Google Scholar 

  47. Mai J, Virtue A, Shen J, Wang H, Yang XF. An evolving new paradigm: endothelial cells-- conditional innate immune cells. J Hematol Oncol. 2013;6:61. https://doi.org/10.1186/1756-8722-6-61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Rega G, Kaun C, Weiss TW, Demyanets S, Zorn G, Kastl SP, et al. Inflammatory cytokines interleukin-6 and oncostatin-M induce plasminogen activator inhibitor-1 in human adipose tissue. Circulation. 2005;111:1938–45. https://doi.org/10.1161/01.CIR.0000161823.55935.BE.

    Article  CAS  PubMed  Google Scholar 

  49. Setiadi H, Yago T, Liu Z, McEver RP. Endothelial signaling by neutrophil-released oncostatin M enhances P-selectin-dependent inflammation and thrombosis. Blood Adv. 2019;3:168–83. https://doi.org/10.1182/bloodadvances.2018026294.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Bou-Gharios G, Ponticos M, Rajkumar V, Abraham D. Extra-cellular matrix in vascular networks. Cell Prolif. 2004;37:207–20. https://doi.org/10.1111/j.1365-2184.2004.00306.x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Phan E, Ahluwalia A, Tarnawski AS. Role of SPARC-matricellular protein in pathophysiology and tissue injury healing. Implications for gastritis and gastric ulcers. Med Sci Monit. 2007;13:RA25-30.

    PubMed  Google Scholar 

  52. Alkabie S, Basivireddy J, Zhou L, Roskams J, Rieckmann P, Quandt JA. SPARC expression by cerebral microvascular endothelial cells in vitro and its influence on blood-brain barrier properties. J Neuroinflammation. 2016;13:225. https://doi.org/10.1186/s12974-016-0657-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Li B, Li F, Chi L, Zhang L, Zhu S. The expression of SPARC in human intracranial aneurysms and its relationship with MMP-2/-9. PLoS One. 2013;8:e58490. https://doi.org/10.1371/journal.pone.0058490.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. McClung HM, Thomas SL, Osenkowski P, Toth M, Menon P, Raz A, et al. SPARC upregulates MT1-MMP expression, MMP-2 activation, and the secretion and cleavage of Galectin-3 in U87MG glioma cells. Neurosci Lett. 2007;419:172–7. https://doi.org/10.1016/j.neulet.2007.04.037.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Seet LF, Su R, Toh LZ, Wong TT. In vitro analyses of the anti-fibrotic effect of SPARC silencing in human Tenon’s fibroblasts: comparisons with mitomycin C. J Cell Mol Med. 2012;16:1245–59. https://doi.org/10.1111/j.1582-4934.2011.01400.x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Zhou S, Dion PA, Rouleau GA. Genetics of intracranial aneurysms. Stroke. 2018;49:780–7. https://doi.org/10.1161/STROKEAHA.117.018152.

    Article  PubMed  Google Scholar 

  57. He J, Bao Q, Yan M, Liang J, Zhu Y, Wang C, et al. The role of Hippo/yes-associated protein signalling in vascular remodelling associated with cardiovascular disease. Br J Pharmacol. 2018;175:1354–61. https://doi.org/10.1016/j.joca.2015.01.014.

    Article  CAS  PubMed  Google Scholar 

  58. Jiang WJ, Ren WH, Liu XJ, Liu Y, Wu FJ, Sun LZ, et al. Disruption of mechanical stress in extracellular matrix is related to Stanford type A aortic dissection through down-regulation of Yes-associated protein. Aging (Albany NY). 2016;8:1923–39. https://doi.org/10.18632/aging.101033.

    Article  CAS  PubMed  Google Scholar 

  59. Ponticos M, Smith BD. Extracellular matrix synthesis in vascular disease: hypertension, and atherosclerosis. J Biomed Res. 2014;28(1):25. https://doi.org/10.7555/JBR.27.20130064.

    Article  CAS  PubMed  Google Scholar 

  60. Miyata T, Minami M, Kataoka H, Hayashi K, Ikedo T, Yang T, et al. Osteoprotegerin prevents intracranial aneurysm progression by promoting collagen biosynthesis and vascular smooth muscle cell proliferation. J Am Heart Assoc. 2020;9:e015731. https://doi.org/10.1161/JAHA.119.015731.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Sun J, Sukhova GK, Zhang J, Chen H, Sjoberg S, Libby P, et al. Cathepsin L activity is essential to elastase perfusion-induced abdominal aortic aneurysms in mice. Arterioscler Thromb Vasc Biol. 2011;31:2500–8. https://doi.org/10.1161/ATVBAHA.111.230201.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Kitamoto S, Sukhova GK, Sun J, Yang M, Libby P, Love V, et al. Cathepsin L deficiency reduces diet-induced atherosclerosis in low-density lipoprotein receptor-knockout mice. Circulation. 2007;115:2065–75. https://doi.org/10.1161/CIRCULATIONAHA.107.688523.

    Article  CAS  PubMed  Google Scholar 

  63. Liu J, Sukhova GK, Yang JT, Sun J, Ma L, Ren A, et al. Cathepsin L expression and regulation in human abdominal aortic aneurysm, atherosclerosis, and vascular cells. Atherosclerosis. 2006;184:302–11. https://doi.org/10.1016/j.atherosclerosis.2005.05.012.

    Article  CAS  PubMed  Google Scholar 

  64. Takeda T, Yamamoto Y, Tsubaki M, Matsuda T, Kimura A, Shimo N, et al. PI3K/Akt/YAP signaling promotes migration and invasion of DLD-1 colorectal cancer cells. Oncol Lett. 2022;23:106. https://doi.org/10.3892/ol.2022.13226.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors thank the patients and their family members for the participation in this study. We thank PGIMER, Chandigarh, for financial support.

Funding

The study was financially supported by the PGIMER, Chandigarh [No.71/2-Edu-16/4484] through intramural research grant scheme. M.K. was funded by University Grants Commission (UGC) fellowship. T.S. was funded by a PGIMER fellowship. K.P. was funded by CSIR, New Delhi.

Author information

Author notes

  1. Krishna Patel and Shobia Chinnapparaj contributed equally to this work.

Authors and Affiliations

  1. Division of Neuro-anesthesia, Department of Anesthesia and Intensive Care, Postgraduate Institute of Medical Education and Research, Chandigarh, India

    Munish Kumar, Shobia Chinnapparaj, Tanavi Sharma, Vinod Kumar Grover & Hemant Bhagat

  2. Institute of Bioinformatics, International Tech Park, Bangalore, India

    Krishna Patel, Aditi Chatterjee & Harsha Gowda

  3. Department of Neurosurgery, Postgraduate Institute of Medical Education and Research, Chandigarh, India

    Ashish Aggarwal, Navneet Singla, Madhivanan Karthigeyan, Apinderpreet Singh, Sushanta Kumar Sahoo, Manjul Tripathi, Sunil K. Gupta & Kanchan Kumar Mukherjee

  4. Department of Neurology, Postgraduate Institute of Medical Education and Research, Chandigarh, India

    Aastha Takkar

  5. Department of Anatomy, Postgraduate Institute of Medical Education and Research, Chandigarh, India

    Tulika Gupta

  6. Department of Biochemistry, Postgraduate Institute of Medical Education and Research, Chandigarh, India

    Arnab Pal & Rajendra Prasad

  7. Pediatric Biochemistry, Department of Pediatrics, Advanced Pediatrics Centre, Postgraduate Institute of Medical Education and Research, Chandigarh, India

    Savita Verma Attri

  8. Department of Forensic Medicine, Postgraduate Institute of Medical Education and Research, Chandigarh, India

    Yogender Singh Bansal

  9. Department of Virology, Postgraduate Institute of Medical Education and Research, Chandigarh, India

    Radha Kanta Ratho

  10. Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India

    Madhu Khullar

  11. Department of Histopathology, Postgraduate Institute of Medical Education and Research, Chandigarh, India

    Rakesh Kumar Vashishta

Authors
  1. Munish Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Krishna Patel
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shobia Chinnapparaj
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tanavi Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ashish Aggarwal
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Navneet Singla
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Madhivanan Karthigeyan
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Apinderpreet Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Sushanta Kumar Sahoo
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Manjul Tripathi
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Aastha Takkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Tulika Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Arnab Pal
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Savita Verma Attri
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Yogender Singh Bansal
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Radha Kanta Ratho
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Sunil K. Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Madhu Khullar
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Rakesh Kumar Vashishta
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Kanchan Kumar Mukherjee
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Vinod Kumar Grover
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Rajendra Prasad
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Aditi Chatterjee
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Harsha Gowda
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Hemant Bhagat
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: HB, M Kumar, AC, HG, KKM, VKG; Sample and data collection: M Kumar, SC, TS; Samples provided by: AA, NS, M Karthigeyan, AS, SKS, MT, AT, YSB, SKG, KKM; Research facilities: TG, AP, SVA, RKR; Bioinformatics analysis: KP; Data Interpretation: M Kumar, HB; Project administration: HB; Supervision: HB, VKG, RKV, RP, M Khullar, AC, HG; Validation: M Kumar, TS; Visualization: M Kumar, TS, KP; Writing-original draft preparation: M Kumar, HB; Writing-review and editing: M Kumar, HB, KP, TS, RP, AC, HG. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Hemant Bhagat.

Ethics declarations

Ethics Approval and Consent to Participate

This study was approved by the Institute Ethics Committee of PGIMER, Chandigarh, India (IEC no. MK/2866/Ph.D/7735). All the patients/subjects were enrolled only after obtaining the written informed consent from patients/relatives.

Consent for Publication

NA

Competing Interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Munish Kumar is the first author.

Rakesh Kumar Vashishta, Kanchan Kumar Mukherjee and Vinod Kumar are deceased.

Supplementary Information

ESM 1

Supplementary Table 1. List of Primers used for qRT-PCR. Supplementary Table 2: Clinicopathological details of study participants. Supplementary Table 3. RNA Integrity Number (RIN) of samples. Supplementary Table 4. Complete list of significantly dysregulated genes between Unruptured IA and Control. Supplementary Table 5. Complete list of significantly dysregulated genes between Ruptured IA and Unruptured IA (PDF 165 kb)

ESM 2

Supplementary Figure 1. Principal Component Analysis. A. Unruptured IA (T1) vs Control (C). B. Ruptured IA (T2) vs Unruptured IA (T1). Supplementary Figure 2. Protein-Protein Interaction network - Unruptured IA vs Control. Supplementary Figure 3. Protein-Protein Interaction network - Ruptured IA vs Unruptured IA (PDF 625 kb)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kumar, M., Patel, K., Chinnapparaj, S. et al. Dysregulated Genes and Signaling Pathways in the Formation and Rupture of Intracranial Aneurysm. Transl. Stroke Res. (2023). https://doi.org/10.1007/s12975-023-01178-w

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12975-023-01178-w

Keywords

Search

Navigation