A Genetic Perspective on Ischemic Stroke: Recent Advances and Future Directions

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Abstract

Objective. This narrative review aimed to explore the multifaceted nature of ischemic stroke (IS) and its underlying genetic factors, emphasize the role of genetics in early detection and prevention, and acknowledge the complex influences on stroke prevalence across various countries.

Methods. An extensive overview of the causes, mechanisms, and genetics of IS was conducted by reviewing several studies and recent findings. The role of specific genes in monogenic stroke disorders, implications of polygenic influences, recent advances in genetic evaluation, and methods for early IS detection were synthesized and discussed.

Results. IS was influenced by genetics, underlying medical conditions, and lifestyle. Specific genes, including NOTCH3, HTRA1, COL3A1, and mtDNA, are involved in monogenic stroke syndromes and predominantly affect younger populations. Polygenic disorders, studied using genome-wide association study and sequencing techniques, play a prominent role in susceptibility to IS. Genetic evaluation has become instrumental in risk prediction, influencing clinical practices and potential therapeutic interventions. Early detection methods, such as enhanced imaging techniques and blood biomarkers, are crucial for managing IS outcomes.

Conclusion. Ischemic stroke is a complex disorder with a significant global impact. Understanding its genetic basis promises to improve early detection and effectively establish preventative measures. Although genetic evaluation and innovative detection techniques offer promise, focusing on lifestyle modifications and managing underlying health conditions remains paramount for reducing the incidence and severity of IS. Continuous research and technological advancements are essential for developing personalized medical approaches and improving global healthcare strategies.

About the authors

Praveen Kumar Chandra Sekar

Chettinad Academy of Research and Education

Author for correspondence.
Email: rkgenes@gmail.com
ORCID iD: 0009-0008-5346-9597

Chettinad Hospital and Research Institute, Dr. Sci (Med.), Human cytogenetics and genomics laboratory, Faculty of allied health sciences

India, Kelambakkam, Tamil Nadu

Ramakrishnan Veerabathiran

Chettinad Academy of Research and Education

Email: rkgenes@gmail.com
ORCID iD: 0000-0002-9307-5428

Chettinad Hospital and Research Institute, Cand. Sci (Med.), Human cytogenetics and genomics laboratory, Faculty of allied health sciences

India, Kelambakkam, Tamil Nadu

References

  1. Bevan S., Traylor M., Adib-Samii P. et al. Genetic heritability of ischemic stroke and the contribution of previously reported candidate gene and genomewide associations. Stroke. 2012;43(12):3161–3167. doi: 10.1161/STROKEAHA.112.665760
  2. Tadi P., Lui F. Acute stroke. Treasure Island; 2023.
  3. GBD 2016 Stroke Collaborators. Global, regional, and national burden of stroke, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(5):439–458. doi: 10.1016/S1474-4422(19)30034-1
  4. Zhou M., Wang H., Zeng X. et al. Mortality, morbidity, and risk factors in China and its provinces, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2019;394(10204):1145–1158. doi: 10.1016/S0140-6736(19)30427-1
  5. GBD 2019 Stroke Collaborators. Global, regional, and national burden of stroke and its risk factors, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Neurol. 2021;20(10):795–820. doi: 10.1016/S1474-4422(21)00252-0
  6. Falcone G.J., Malik R., Dichgans M., Rosand J. Current concepts and clinical applications of stroke genetics. Lancet Neurol. 2014;13(4):405–418. doi: 10.1016/S1474-4422(14)70029-8
  7. Ilinca A., Samuelsson S., Piccinelli P. et al. A stroke gene panel for wholeexome sequencing. Eur. J. Hum. Genet. 2019;27(2):317–324. doi: 10.1038/s41431-018-0274-4
  8. Chen W., Sinha B., Li Y. et al. Monogenic, polygenic, and microRNA markers for ischemic stroke. Mol. Neurobiol. 2019;56(2):1330–1343. doi: 10.1007/s12035-018-1055-3
  9. Razvi S.S., Bone I. Single gene disorders causing ischaemic stroke. J. Neurol. 2006;253(6):685–700. doi: 10.1007/s00415-006-0048-8
  10. Fox C.S., Polak J.F., Chazaro I. et al. Genetic and environmental contributions to atherosclerosis phenotypes in men and women: heritability of carotid intima-media thickness in the Framingham Heart Study. Stroke. 2003;34(2):397–401. doi: 10.1161/01.str.0000048214.56981.6f
  11. Pu L., Wang L., Zhang R. et al. Projected global trends in ischemic stroke incidence, deaths and disability-adjusted life years from 2020 to 2030. Stroke. 2023;54(5):1330–1339. doi: 10.1161/STROKEAHA.122.040073
  12. Kaur D., Bansal R.P., Uppal A. A comparative analysis of diagnostic imaging in acute ischaemic stroke. Chettinad Health City Med J. 2023;12(2):3–8. doi: 10.24321/2278.2044.202320
  13. Aggarwal A., Aggarwal P., Khatak M., Khatak S. Cerebral ischemic stroke: sequels of cascade. Int. J. Pharma. Bio. Sci. 2010;1(3):1–24.
  14. Lyaker M.R., Tulman D.B., Dimitrova G.T. et al. Arterial embolism. Int. J. Crit. Illn. Inj. Sci. 2013;3(1):77–87. doi: 10.4103/2229-5151.109429
  15. Guo Y., Li P., Guo Q. et al. Pathophysiology and biomarkers in acute ischemic stroke — a review. Trop. J. Pharm. Res. 2014;12(6):1097. doi: 10.4314/tjpr.v12i6.35
  16. Wu Q.J., Tymianski M. Targeting NMDA receptors in stroke: new hope in neuroprotection. Mol. Brain. 2018;11(1):15. doi: 10.1186/s13041-018-0357-8
  17. Rama R., García Rodríguez J.C. Excitotoxicity and oxidative stress in acute ischemic stroke. In: García Rodríguez J.C. (ed.) Acute ischemic stroke. [Internet]. InTech; 2012. P. 30–58.
  18. Rutten J.W., Haan J., Terwindt G.M. et al. Interpretation of NOTCH3 mutations in the diagnosis of CADASIL. Expert. Rev. Mol. Diagn. 2014;14(5):593–603. doi: 10.1586/14737159.2014.922880
  19. Wang M.M. CADASIL. Handb. Clin. Neurol. 2018;148:733–743.
  20. Pan A.P., Potter T., Bako A. et al. Lifelong cerebrovascular disease burden among CADASIL patients: analysis from a global health research network. Front. Neurol. 2023;14:1203985. doi: 10.3389/fneur.2023.1203985
  21. Oide T., Nakayama H., Yanagawa S. et al. Extensive loss of arterial medial smooth muscle cells and mural extracellular matrix in cerebral autosomal recessive arteriopathy with subcortical infarcts and leukoencephalopathy (CARASIL). Neuropathology. 2008;28(2):132–142. doi: 10.1111/j.1440-1789.2007.00864.x
  22. Hara K., Shiga A., Fukutake T. et al. Association of HTRA1 mutations and familial ischemic cerebral small-vessel disease. N. Engl. J. Med. 2009;360(17):1729–1739. doi: 10.1056/NEJMoa0801560
  23. Clausen T., Kaiser M., Huber R., Ehrmann M. HTRA proteases: regulated proteolysis in protein quality control. Nat. Rev. Mol. Cell. Biol. 2011;12(3):1521–1562. doi: 10.1038/nrm3065
  24. Todorovic V., Rifkin D.B. LTBPs, more than just an escort service. J. Cell. Biochem. 2012;113(2):410–418. doi: 10.1002/jcb.23385
  25. Hara K., Shiga A., Fukutake T. Association of HTRA1 mutations and familial ischemic cerebral small-vessel disease. N. Engl. J. Med. 2009;360(17):1729–1739.
  26. Malfait F., Francomano C., Byers P. et al. The 2017 international classification of the Ehlers–Danlos syndromes. Am. J. Med. Genet. C. Semin. Med. Genet. 2017;175(1):8–26. doi: 10.1002/ajmg.c.31552
  27. Huang K.W., Liu T.C., Liang R.Y. et al. Structural basis for overhang excision and terminal unwinding of DNA duplexes by TREX1. PLoS Biol. 2018;16(5):e2005653. doi: 10.1371/journal.pbio.2005653
  28. Stam A.H., Kothari P.H., Shaikh A. et al. Retinal vasculopathy with cerebral leukoencephalopathy and systemic manifestations. Brain. 2016;139(11):2909–2922. doi: 10.1093/brain/aww217
  29. Winkler D.T., Lyrer P., Probst A. et al. Hereditary systemic angiopathy (HSA) with cerebral calcifications, retinopathy, progressive nephropathy, and hepatopathy. J. Neurol. 2008;255(1):77–88. doi: 10.1007/s00415-008-0675-3
  30. Richards A., van den Maagdenberg A.M., Jen J.C. et al. C-terminal truncations in human 3'-5' DNA exonuclease TREX1 cause autosomal dominant retinal vasculopathy with cerebral leukodystrophy. Nat. Genet. 2007;39(9):1068–1070. doi: 10.1038/ng2082
  31. Kothari P.H., Kolar G.R., Jen J.C. et al. TREX1 is expressed by microglia in normal human brain and increases in regions affected by ischemia. Brain Pathol. 2018;28(6):806–821. doi: 10.1111/bpa.12626
  32. Kim B.J., Kim J.S. Ischemic stroke subtype classification: an asian viewpoint. J. Stroke. 2014;16(1):8–17. doi: 10.5853/jos.2014.16.1.8
  33. Craven L., Alston C.L., Taylor R.W., Turnbull D.M. Recent advances in mitochondrial disease. Annu. Rev. Genomics Hum. Genet. 2017;18:257–275. doi: 10.1146/annurev-genom-091416-035426
  34. El-Hattab A.W., Adesina A.M., Jones J., Scaglia F. MELAS syndrome: clinical manifestations, pathogenesis, and treatment options. Mol. Genet. Metab. 2015;116(1-2):4–12. doi: 10.1016/j.ymgme.2015.06.004
  35. Kowalska M., Piekut T., Prendecki M. et al. Mitochondrial and nuclear DNA oxidative damage in physiological and pathological aging. DNA Cell. Biol. 2020;39(8):1410–1420. doi: 10.1089/dna.2019.5347
  36. Rahman S., Copeland W.C. POLG-related disorders and their neurological manifestations. Nat. Rev. Neurol. 2019;15(1):40–52. doi: 10.1038/s41582-018-0101-0
  37. Zhang Z., Liu M., He J. et al. Maternally inherited coronary heart disease is associated with a novel mitochondrial tRNA mutation. BMC Cardiovasc. Disord. 2019;19(1):293. doi: 10.1186/s12872-019-01284-4
  38. Irani F., Kasmani R. Hereditary hemorrhagic telangiectasia: fatigue and dyspnea. CMAJ. 2009;180(8):839. doi: 10.1503/cmaj.081212
  39. Franchini M., Frattini F., Crestani S., Bonfanti C. Novel treatments for epistaxis in hereditary hemorrhagic telangiectasia: a systematic review of the clinical experience with thalidomide. J. Thromb. Thrombolysis. 2013;36(3):355–357. doi: 10.1007/s11239-012-0840-5
  40. McDonald J., Bayrak-Toydemir P., Pyeritz R.E. Hereditary hemorrhagic telangiectasia: an overview of diagnosis, management, and pathogenesis. Genet. Med. 2011;13(7):607–616. doi: 10.1097/GIM.0b013e3182136d32
  41. Jerkic M., Sotov V., Letarte M. Oxidative stress contributes to endothelial dysfunction in mouse models of hereditary hemorrhagic telangiectasia. Oxid. Med. Cell. Longev. 2012;2012:686972. doi: 10.1155/2012/686972
  42. Vignali D.A., Kuchroo V.K. IL-12 family cytokines: immunological playmakers. Nat. Immunol. 2012;13(8):722–728. doi: 10.1038/ni.2366
  43. Yang J., Ma K., Zhang C. et al. Burns impair blood-brain barrier and mesenchymal stem cells can reverse the process in mice. Front. Immunol. 2020;11:578879. doi: 10.3389/fimmu.2020.578879
  44. Dinarello C.A. Immunological and inflammatory functions of the interleukin-1 family. Annu. Rev. Immunol. 2009;27:519–550. doi: 10.1146/annurev.immunol.021908.132612
  45. Fu Y., Yan Y. Emerging role of immunity in cerebral small vessel disease. Front. Immunol. 2018;9:67. doi: 10.3389/fimmu.2018.00067
  46. Scheller J., Chalaris A., Schmidt-Arras D., Rose-John S. The pro- and anti-inflammatory properties of the cytokine interleukin-6. Biochim. Biophys. Acta. 2011;1813(5):878–888. doi: 10.1016/j.bbamcr.2011.01.034
  47. Scheller J., Grötzinger J., Rose-John S. Updating interleukin-6 classic- and trans-signaling. Signal Transduction. 2006;6(4):240–259. doi: 10.1002/SITA.200600086
  48. Rincon M. Interleukin-6: from an inflammatory marker to a target for inflammatory diseases. Trends Immunol. 2012;33(11):571–577. doi: 10.1016/j.it.2012.07.003
  49. Cui G., Wang H., Li R. et al. Polymorphism of tumor necrosis factor alpha (TNF-alpha) gene promoter, circulating TNF-alpha level, and cardiovascular risk factor for ischemic stroke. J. Neuroinflammation. 2012;9:235. doi: 10.1186/1742-2094-9-235
  50. Mekinian A., Tamouza R., Pavy S. et al. Functional study of TNF-α promoter polymorphisms: literature review and meta-analysis. Eur. Cytokine Netw. 2011;22(2):88–102. doi: 10.1684/ecn.2011.0285
  51. Pan A.P., Potter T., Bako A. et al. Lifelong cerebrovascular disease burden among CADASIL patients: analysis from a global health research network. Front. Neurol. 2023;14:1203985. doi: 10.3389/fneur.2023.1203985
  52. Pfeiffer D., Chen B., Schlicht K. et al. Genetic imbalance is associated with functional outcome after ischemic stroke. Stroke. 2019;50(2):298–304. doi: 10.1161/STROKEAHA.118.021856
  53. Ekkert A., Šliachtenko A., Grigaitė J. et al. Ischemic stroke genetics: what is new and how to apply it in clinical practice? Genes. (Basel). 2021;13(1):48. doi: 10.3390/genes13010048
  54. Rao S., Yao Y., Bauer D.E. Editing GWAS: experimental approaches to dissect and exploit disease-associated genetic variation. Genome Med. 2021;13(1):41. doi: 10.1186/s13073-021-00857-3
  55. Markus H.S., Mäkelä K.M., Bevan S. et al. Evidence HDAC9 genetic variant associated with ischemic stroke increases risk via promoting carotid atherosclerosis. Stroke. 2013;44(5):1220–1225. doi: 10.1161/STROKEAHA.111.000217
  56. Lee T.H., Ko T.M., Chen C.H. et al. Identification of PTCSC3 as a novel locus for large‐vessel ischemic stroke: a genome-wide association study. J. Am. Heart Assoc. 2016;5(3):e003003. doi: 10.1161/JAHA.115.003003
  57. NINDS Stroke Genetics Network (SiGN), International Stroke Genetics Consortium (ISGC). Loci associated with ischaemic stroke and its subtypes (SiGN): a genome-wide association study. Lancet Neurol. 2016;15(2):174–184. doi: 10.1016/S1474-4422(15)00338-5
  58. Ilinca A., Martinez-Majander N., Samuelsson S. et al. Whole-exome sequencing in 22 young ischemic stroke patients with familial clustering of stroke. Stroke. 2020;51(4):1056–1063. doi: 10.1161/STROKEAHA.119.027474
  59. Ilinca A., Puschmann A., Putaala J. et al. Updated stroke gene panels: rapid evolution of knowledge on monogenic causes of stroke. Eur. J. Hum. Genet. 2023;31(2):239–242. doi: 10.1038/s41431-022-01207-6
  60. Scott R.M., Smith E.R. Moyamoya disease and moyamoya syndrome. N. Engl. J. Med. 2009;360(12):1226–1237. doi: 10.1056/NEJMra0804622
  61. Guey S., Tournier-Lasserve E., Hervé D., Kossorotoff M. Moyamoya disease and syndromes: from genetics to clinical management. Appl. Clin. Genet. 2015;8:49–68. doi: 10.2147/TACG.S42772
  62. Castori M., Voermans N.C. Neurological manifestations of Ehlers–Danlos syndrome(s): a review. Iran J. Neurol. 2014;13(4):190–208.
  63. Rodan L.H., Mishra N., Yau I. et al. Expanding the spectrum of methylmalonic acid-induced pallidal stroke: first reported case of metabolic globus pallidus stroke in transcobalamin II deficiency. JIMD Rep. 2013;11:7–11. doi: 10.1007/8904_2013_215
  64. Mishra V., Banerjee A., Gandhi A.B. et al. Stroke and Fabry disease: a review of literature. Cureus. 2020;12(12):e12083. doi: 10.7759/cureus.12083
  65. Feldt-Rasmussen U. Fabry disease and early stroke. Stroke Res. Treat. 2011;2011: 615218. doi: 10.4061/2011/615218
  66. Kang J., Ko Y., Park J.H. et al. Effect of blood pressure on 3-month functional outcome in the subacute stage of ischemic stroke. Neurology. 2012;79(20):2018–2024. doi: 10.1212/WNL.0b013e3182749eb8
  67. Edwards J.D., Jacova C., Sepehry A.A. et al. A quantitative systematic review of domain-specific cognitive impairment in lacunar stroke. Neurology. 2013;80(3):315–322. doi: 10.1212/WNL.0b013e31827deb85
  68. Arboix A., Milian M., Oliveres M. et al. Impact of female gender on prognosis in type 2 diabetic patients with ischemic stroke. Eur. Neurol. 2006;56(1):6–12. doi: 10.1159/000094249
  69. Arboix A., Font A., Garro C. et al. Recurrent lacunar infarction following a previous lacunar stroke: a clinical study of 122 patients. J. Neurol. Neurosurg. Psychiatry. 2007;78(12):1392–1394. doi: 10.1136/jnnp.2007.119776
  70. Krishnamoorthy S., Khoo C.W., Lim H.S. et al. Prognostic role of plasma von Willebrand factor and soluble E-selectin levels for future cardiovascular events in a 'real-world' community cohort of patients with atrial fibrillation. Eur. J. Clin. Invest. 2013;43(10):1032–1038. doi: 10.1111/eci.12140
  71. Kishore A., Vail A., Majid A. et al. Detection of atrial fibrillation after ischemic stroke or transient ischemic attack: a systematic review and meta-analysis. Stroke. 2014;45(2):520–526. doi: 10.1161/STROKEAHA.113.003433
  72. Mishra A., Malik R., Hachiya T. et al. Stroke genetics informs drug discovery and risk prediction across ancestries. Nature. 2022;611(7934):115–123. doi: 10.1038/s41586-022-05165-3
  73. Neumann J.T., Riaz M., Bakshi A. et al. Predictive performance of a polygenic risk score for incident ischemic stroke in a healthy older population. Stroke. 2021;52(9):2882–2891. doi: 10.1161/STROKEAHA.120.033670
  74. Debette S., Markus H.S. Stroke genetics: discovery, insight into mechanisms, and clinical perspectives. Circ. Res. 2022;130(8):1095–1111. doi: 10.1161/CIRCRESAHA.122.319950
  75. Arboix A., Alioc J. Cardioembolic stroke: clinical features, specific cardiac disorders and prognosis. Curr. Cardiol. Rev. 2010;6(3):150–161. doi: 10.2174/157340310791658730
  76. Bhagat R., Marini S., Romero J.R. Genetic considerations in cerebral small vessel diseases. Front. Neurol. 2023;14:1080168. doi: 10.3389/fneur.2023.1080168
  77. Kohne E. Hemoglobinopathies: clinical manifestations, diagnosis, and treatment. Dtsch. Ärztebl. Int. 2011;108(31-32):532–540. doi: 10.3238/arztebl.2011.0532
  78. Ng K.W.P., Loh P.K.L., Sharma V.K. Role of investigating thrombophilic disorders in young stroke. Stroke Res. Treat. 2011;2011:670138. doi: 10.4061/2011/670138
  79. Sajjadi M., Karami M., Amirfattahi R. et al. A promising method of enhancement for early detection of ischemic stroke. J. Res. Med. Sci. 2012;17(9):843–849.
  80. Bustamante A., López-Cancio E., Pich S. et al. Blood biomarkers for the early diagnosis of stroke: the stroke-chip study. Stroke. 2017;48(9):2419–2425. doi: 10.1161/STROKEAHA.117.017076

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2. Fig. 1. Mechanism of IS.

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3. Fig. 2. Role of interleukin gene in IS.

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