Integrative analysis of multi-omics data to identify three immune-related genes in the formation and progression of intracranial aneurysms

Vlak MH, Algra A, Brandenburg R, Rinkel GJ. Prevalence of unruptured intracranial aneurysms, with emphasis on sex, age, comorbidity, country, and time period: a systematic review and meta-analysis. Lancet Neurol. 2011;10:626–36. https://doi.org/10.1016/s1474-4422(11)70109-0.

Article  PubMed  Google Scholar 

Gabriel RA, Kim H, Sidney S, et al. Ten-year detection rate of brain arteriovenous malformations in a large, multiethnic, defined population. Stroke. 2010;41:21–6. https://doi.org/10.1161/strokeaha.109.566018.

Article  PubMed  Google Scholar 

Bakker MK, van der Spek RAA, van Rheenen W, et al. Genome-wide association study of intracranial aneurysms identifies 17 risk loci and genetic overlap with clinical risk factors. Nat Genet. 2020;52:1303–13. https://doi.org/10.1038/s41588-020-00725-7.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ogilvy CS, Gomez-Paz S, Kicielinski KP, et al. Cigarette smoking and risk of intracranial aneurysms in middle-aged women. J Neurol Neurosurg Psychiatry. 2020;91:985–90. https://doi.org/10.1136/jnnp-2020-323753.

Article  PubMed  Google Scholar 

Macdonald RL, Schweizer TA. Spontaneous subarachnoid haemorrhage. Lancet (London, England). 2017;389:655–66. https://doi.org/10.1016/s0140-6736(16)30668-7.

Article  PubMed  Google Scholar 

Nieuwkamp DJ, Setz LE, Algra A, et al. Changes in case fatality of aneurysmal subarachnoid haemorrhage over time, according to age, sex, and region: a meta-analysis. Lancet Neurol. 2009;8:635–42. https://doi.org/10.1016/s1474-4422(09)70126-7.

Article  PubMed  Google Scholar 

Thompson BG, Brown RD Jr, Amin-Hanjani S, et al. Guidelines for the management of patients with unruptured intracranial aneurysms: a guideline for healthcare professionals from the American heart association/American stroke association. Stroke. 2015;46:2368–400. https://doi.org/10.1161/str.0000000000000070.

Article  PubMed  Google Scholar 

Frösen J, Cebral J, Robertson AM, Aoki T. Flow-induced, inflammation-mediated arterial wall remodeling in the formation and progression of intracranial aneurysms. Neurosurg Focus. 2019;47:E21. https://doi.org/10.3171/2019.5.Focus19234.

Article  PubMed  PubMed Central  Google Scholar 

Can A, Du R. Association of hemodynamic factors with intracranial aneurysm formation and rupture: systematic review and meta-analysis. Neurosurgery. 2016;78:510–20. https://doi.org/10.1227/neu.0000000000001083.

Article  PubMed  Google Scholar 

Huang Z, Zeng M, Tao WG, et al. A hemodynamic mechanism correlating with the initiation of MCA bifurcation aneurysms. AJNR Am J Neuroradiol. 2020;41:1217–24. https://doi.org/10.3174/ajnr.A6615.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Turjman AS, Turjman F, Edelman ER. Role of fluid dynamics and inflammation in intracranial aneurysm formation. Circulation. 2014;129:373–82. https://doi.org/10.1161/circulationaha.113.001444.

Article  PubMed  PubMed Central  Google Scholar 

Furukawa H, Wada K, Tada Y, et al. Mast cell promotes the development of intracranial aneurysm rupture. Stroke. 2020;51:3332–9. https://doi.org/10.1161/strokeaha.120.030834.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kanematsu Y, Kanematsu M, Kurihara C, et al. Critical roles of macrophages in the formation of intracranial aneurysm. Stroke. 2011;42:173–8. https://doi.org/10.1161/strokeaha.110.590976.

Article  PubMed  Google Scholar 

Tulamo R, Frösen J, Junnikkala S, et al. Complement system becomes activated by the classical pathway in intracranial aneurysm walls. Lab Invest J Tech Methods Pathol. 2010;90:168–79. https://doi.org/10.1038/labinvest.2009.133.

Article  CAS  Google Scholar 

Sawyer DM, Pace LA, Pascale CL, et al. Lymphocytes influence intracranial aneurysm formation and rupture: role of extracellular matrix remodeling and phenotypic modulation of vascular smooth muscle cells. J Neuroinflammation. 2016;13:185. https://doi.org/10.1186/s12974-016-0654-z.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Pera J, Korostynski M, Krzyszkowski 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 

Kleinloog R, Verweij BH, van der Vlies P, 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 

Liu Y, Song Y, Liu P, et al. Comparative bioinformatics analysis between proteomes of rabbit aneurysm model and human intracranial aneurysm with label-free quantitative proteomics. CNS Neurosci Ther. 2021;27:101–12. https://doi.org/10.1111/cns.13570.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Shan D, Guo X, Yang G, et al. Integrated transcriptional profiling analysis and immune-related risk model construction for intracranial aneurysm rupture. Front Neurosci. 2021;15:613329. https://doi.org/10.3389/fnins.2021.613329.

Article  PubMed  PubMed Central  Google Scholar 

Zhong A, Ding N, Zhou Y, et al. Identification of hub genes associated with the pathogenesis of intracranial aneurysm via integrated bioinformatics analysis. Int J Gen Med. 2021;14:4039–50. https://doi.org/10.2147/ijgm.S320396.

Article  PubMed  PubMed Central  Google Scholar 

Aoki T, Koseki H, Miyata H, 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 

Nakaoka H, Tajima A, Yoneyama T, et al. Gene expression profiling reveals distinct molecular signatures associated with the rupture of intracranial aneurysm. Stroke. 2014;45:2239–45. https://doi.org/10.1161/strokeaha.114.005851.

Article  CAS  PubMed  Google Scholar 

Ritchie ME, Phipson B, Wu D, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43: e47. https://doi.org/10.1093/nar/gkv007.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16:284–7. https://doi.org/10.1089/omi.2011.0118.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005;102:15545–50. https://doi.org/10.1073/pnas.0506580102.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Aran D, Hu Z, Butte AJ. xCell: digitally portraying the tissue cellular heterogeneity landscape. Genome Biol. 2017;18:220. https://doi.org/10.1186/s13059-017-1349-1.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Bindea G, Mlecnik B, Tosolini M, et al. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity. 2013;39:782–95. https://doi.org/10.1016/j.immuni.2013.10.003.

Article  CAS  PubMed  Google Scholar 

Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics. 2008;9:559. https://doi.org/10.1186/1471-2105-9-559.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ernst J, Bar-Joseph Z. STEM: a tool for the analysis of short time series gene expression data. BMC Bioinformatics. 2006;7:191. https://doi.org/10.1186/1471-2105-7-191.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Tian Y, Morris TJ, Webster AP, et al. ChAMP: updated methylation analysis pipeline for Illumina BeadChips. Bioinform (Oxford, England). 2017;33:3982–4. https://doi.org/10.1093/bioinformatics/btx513.

Article  CAS  Google Scholar 

Li S, Tao W, Huang Z, et al. The transcriptional landscapes and key genes in brain arteriovenous malformation progression in a venous hypertension rat model revealed by RNA sequencing. J Inflamm Res. 2022;15:1381–97. https://doi.org/10.2147/jir.S347754.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Butler A, Hoffman P, Smibert P, Papalexi E, Satija R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat Biotechnol. 2018;36:411–20. https://doi.org/10.1038/nbt.4096.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Martinez AN, Tortelote GG, Pascale CL, et al. Single-cell transcriptome analysis of the circle of Willis in a mouse cerebral aneurysm model. Stroke. 2022;53:2647–57. https://doi.org/10.1161/strokeaha.122.038776.

Article  CAS  PubMed  Google Scholar 

Ruigrok YM, Rinkel GJ, van’t Slot R, et al. Evidence in favor of the contribution of genes involved in the maintenance of the extracellular matrix of the arterial wall to the development of intracranial aneurysms. Hum Mol Genet. 2006;15:3361–8. https://doi.org/10.1093/hmg/ddl412.

Article  CAS  PubMed  Google Scholar 

Zhang X, Ares WJ, Taussky P, Ducruet AF, Grandhi R. Ro

留言 (0)

沒有登入
gif