Advertisement

Distinct proteomic profiles in monozygotic twins discordant for ischaemic stroke

  • Nirmal Vadgama
  • Douglas Lamont
  • John Hardy
  • Jamal NasirEmail author
  • Ruth C. Lovering
Article

Abstract

Stroke is a common disorder with significant morbidity and mortality, and complex aetiology involving both environmental and genetic risk factors. Although some of the major risk factors for stoke, such as smoking and hypertension, are well-documented, the underlying genetic and detailed molecular mechanisms remain elusive. Exploring the relevant biochemical pathways may contribute to the clinical diagnosis of stroke and shed light on its aetiology. A comparative proteomic analysis of blood serum of a pair of monozygotic (MZ) twins discordant for ischaemic stroke (IS) was performed using a label-free quantitative proteomics approach. To overcome the limit of reproducibility in the serum preparation, two separate runs were performed, each consisting of three technical replicates per sample. Biological processes associated with proteins differentially expressed between the twins were explored with gene ontology (GO) classification using the functional analysis tool g:Profiler. ANOVA test performed in Progenesis LC-MS identified 179 (run 1) and 209 (run 2) proteins as differentially expressed between the affected and unaffected twin (p < 0.05). Furthermore, the level of serum fibulin 1, an extracellular matrix protein associated with arterial stiffness, was on average 13.37-fold higher in the affected twin. Each dataset was then analysed independently, and the proteins were classified according to GO terms. The categories overrepresented in the affected twin predominantly corresponded to stroke-relevant processes, including wound healing, blood coagulation and haemostasis, with a high proportion of the proteins overexpressed in the affected twin associated with these terms. By contrast, in the unaffected twin diagnosed with atopic dermatitis, there were increased levels of keratin proteins and GO terms associated with skin development. The identification of cellular pathways enriched in IS as well as the upregulation of fibulin 1 sheds new light on the underlying disease-causing mechanisms at the molecular level. Our findings of distinct proteomic signatures associated with IS and atopic dermatitis suggest proteomic profiling could be used as a general approach for improved diagnostic, prognostic and therapeutic strategies.

Keywords

Proteomics Stroke Biomarker Monozygotic twins Fibulin 1 Gene 

Notes

Acknowledgements

We would like to thank the FingerPrints Proteomics Facility, School of Life Sciences, University of Dundee for the proteomic and mass spectrometry analysis, and The Leverhulme Trade Charities Trust for a bursary to NV.

Funding

RCL: Parkinson’s UK Grant G-1307, British Heart Foundation (RG/13/5/30112), the National Institute for Health Research University College London Hospitals Biomedical Research Centre.

Compliance with ethical standards

Conflict of interest

The authors report no conflicts.

Supplementary material

11010_2019_3501_MOESM1_ESM.pdf (711 kb)
Supplementary material 1 (PDF 711 KB)

References

  1. 1.
    Raffeld MR, Debette S, Woo D (2016) International stroke genetics consortium update. Stroke 47:1144–1145.  https://doi.org/10.1161/STROKEAHA.116.012682 CrossRefGoogle Scholar
  2. 2.
    Goodwin S, McPherson JD, McCombie WR (2016) Coming of age: ten years of next-generation sequencing technologies. Nat Rev Genet 17:333–351.  https://doi.org/10.1038/nrg.2016.49 CrossRefGoogle Scholar
  3. 3.
    Lever NM, Nyström KV, Schindler JL et al (2013) Missed opportunities for recognition of ischemic stroke in the emergency department. J Emerg Nurs 39:434–439.  https://doi.org/10.1016/j.jen.2012.02.011 CrossRefGoogle Scholar
  4. 4.
    Makris K, Haliassos A, Chondrogianni M, Tsivgoulis G (2018) Blood biomarkers in ischemic stroke: potential role and challenges in clinical practice and research. Crit Rev Clin Lab Sci 55:294–328.  https://doi.org/10.1080/10408363.2018.1461190 CrossRefGoogle Scholar
  5. 5.
    Jickling GC, Sharp FR (2015) Biomarker panels in ischemic stroke. Stroke 46:915–920.  https://doi.org/10.1161/STROKEAHA.114.005604 CrossRefGoogle Scholar
  6. 6.
    Zwijnenburg PJG, Meijers-Heijboer H, Boomsma DI (2010) Identical but not the same: the value of discordant monozygotic twins in genetic research. Am J Med Genet Part B.  https://doi.org/10.1002/ajmg.b.31091 Google Scholar
  7. 7.
    Vadgama N, Gaze D, Ranson J et al (2015) Elevated γ-glutamyltransferase and erythrocyte sedimentation rate in ischemic stroke in discordant monozygotic twin study. Int J Stroke 10:.  https://doi.org/10.1111/ijs.12440
  8. 8.
    Reimand J, Kull M, Peterson H et al (2007) g:Profiler–a web-based toolset for functional profiling of gene lists from large-scale experiments. Nucleic Acids Res 35:W193–W200.  https://doi.org/10.1093/nar/gkm226 CrossRefGoogle Scholar
  9. 9.
    Smoot ME, Ono K, Ruscheinski J et al (2011) Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27:431–432.  https://doi.org/10.1093/bioinformatics/btq675 CrossRefGoogle Scholar
  10. 10.
    Walker HK, Hall WD, Hurst JW (1990) Clinical Methods. ButterworthsGoogle Scholar
  11. 11.
    Connor DE, Chaitanya GV, Chittiboina P et al (2017) Variations in the cerebrospinal fluid proteome following traumatic brain injury and subarachnoid hemorrhage. Pathophysiology 24:169–183.  https://doi.org/10.1016/j.pathophys.2017.04.003 CrossRefGoogle Scholar
  12. 12.
    Huang P, Lo L-H, Chen Y-C et al (2009) Serum free hemoglobin as a novel potential biomarker for acute ischemic stroke. J Neurol 256:625–631.  https://doi.org/10.1007/s00415-009-0133-x CrossRefGoogle Scholar
  13. 13.
    Nezu T, Hosomi N, Aoki S et al (2013) Alpha2-macroglobulin as a promising biomarker for cerebral small vessel disease in acute ischemic stroke patients. J Neurol 260:2642–2649.  https://doi.org/10.1007/s00415-013-7040-x CrossRefGoogle Scholar
  14. 14.
    Hanson E, Kanse SM, Joshi A et al (2012) Plasma factor VII-activating protease antigen levels and activity are increased in ischemic stroke. J Thromb Haemost 10:848–856.  https://doi.org/10.1111/j.1538-7836.2012.04692.x CrossRefGoogle Scholar
  15. 15.
    Ziegler G, Harhausen D, Schepers C et al (2007) TLR2 has a detrimental role in mouse transient focal cerebral ischemia. Biochem Biophys Res Commun 359:574–579.  https://doi.org/10.1016/j.bbrc.2007.05.157 CrossRefGoogle Scholar
  16. 16.
    Füst G, Munthe-Fog L, Illes Z et al (2011) Low ficolin-3 levels in early follow-up serum samples are associated with the severity and unfavorable outcome of acute ischemic stroke. J Neuroinflammation 8:185.  https://doi.org/10.1186/1742-2094-8-185 CrossRefGoogle Scholar
  17. 17.
    Carcaillon L, Alhenc-Gelas M, Bejot Y et al (2011) Increased thrombin generation is associated with acute ischemic stroke but not with coronary heart disease in the elderly. Arterioscler Thromb Vasc Biol 31:1445–1451.  https://doi.org/10.1161/ATVBAHA.111.223453 CrossRefGoogle Scholar
  18. 18.
    Cangemi C, Skov V, Poulsen MK et al (2011) Fibulin-1 is a marker for arterial extracellular matrix alterations in type 2 diabetes. Clin Chem 57:1556–1565.  https://doi.org/10.1373/clinchem.2011.162966 CrossRefGoogle Scholar
  19. 19.
    López-Farré AJ, Zamorano-León JJ, Segura A et al (2012) Plasma desmoplakin I biomarker of vascular recurrence after ischemic stroke. J Neurochem 121:314–325.  https://doi.org/10.1111/j.1471-4159.2012.07683.x CrossRefGoogle Scholar
  20. 20.
    Chao J, Bledsoe G, Yin H, Chao L (2006) The tissue kallikrein-kinin system protects against cardiovascular and renal diseases and ischemic stroke independently of blood pressure reduction. Biol Chem 387:665–675.  https://doi.org/10.1515/BC.2006.085 CrossRefGoogle Scholar
  21. 21.
    Garrod D, Chidgey M (2008) Desmosome structure, composition and function. Biochim Biophys Acta 1778:572–587.  https://doi.org/10.1016/j.bbamem.2007.07.014 CrossRefGoogle Scholar
  22. 22.
    Gori AM, Giusti B, Piccardi B et al (2017) Inflammatory and metalloproteinases profiles predict three-month poor outcomes in ischemic stroke treated with thrombolysis. J Cereb Blood Flow Metab 37:3253–3261.  https://doi.org/10.1177/0271678X17695572 CrossRefGoogle Scholar
  23. 23.
    Kannemeier C, Al-Fakhri N, Preissner KT, Kanse SM (2004) Factor VII-activating protease (FSAP) inhibits growth factor-mediated cell proliferation and migration of vascular smooth muscle cells. FASEB J 18:728–730.  https://doi.org/10.1096/fj.03-0898fje CrossRefGoogle Scholar
  24. 24.
    Willeit J, Kiechl S, Weimer T et al (2003) Marburg I polymorphism of factor VII—activating protease: a prominent risk predictor of carotid stenosis. Circulation 107:667–670CrossRefGoogle Scholar
  25. 25.
    Wang L, Luo H, Chen X et al (2014) Functional characterization of S100A8 and S100A9 in altering monolayer permeability of human umbilical endothelial cells. PLoS ONE 9:e90472.  https://doi.org/10.1371/journal.pone.0090472 CrossRefGoogle Scholar
  26. 26.
    Schiopu A, Cotoi OS (2013) S100A8 and S100A9: DAMPs at the crossroads between innate immunity, traditional risk factors, and cardiovascular disease. Mediators Inflamm 2013:828354.  https://doi.org/10.1155/2013/828354
  27. 27.
    Chao J, Bledsoe G, Chao L (2016) Protective role of Kallistatin in vascular and organ injury. Hypertens (Dallas, Tex 1979) 68:533–541.  https://doi.org/10.1161/HYPERTENSIONAHA.116.07861 CrossRefGoogle Scholar
  28. 28.
    Stokes DL (2007) Desmosomes from a structural perspective. Curr Opin Cell Biol 19:565–571.  https://doi.org/10.1016/j.ceb.2007.09.003 CrossRefGoogle Scholar
  29. 29.
    Yang Z, Bowles NE, Scherer SE et al (2006) Desmosomal Dysfunction due to Mutations in Desmoplakin Causes Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy. Circ Res 99:646–655.  https://doi.org/10.1161/01.RES.0000241482.19382.c6 CrossRefGoogle Scholar
  30. 30.
    Argraves WS, Tran H, Burgess WH, Dickerson K (1990) Fibulin is an extracellular matrix and plasma glycoprotein with repeated domain structure. J Cell Biol 111:3155–3164CrossRefGoogle Scholar
  31. 31.
    Liu G, Cooley MA, Jarnicki AG et al (2016) Fibulin-1 regulates the pathogenesis of tissue remodeling in respiratory diseases. JCI Insight.  https://doi.org/10.1172/jci.insight.86380 Google Scholar
  32. 32.
    Godyna S, Diaz-Ricart M, Argraves WS (1996) Fibulin-1 mediates platelet adhesion via a bridge of fibrinogen. Blood 88:2569–2577Google Scholar
  33. 33.
    Al Maskari R, McEniery CM et al (2018) The matrix proteins aggrecan and fibulin-1 play a key role in determining aortic stiffness. Sci Rep 8:8550.  https://doi.org/10.1038/s41598-018-25851-5 CrossRefGoogle Scholar
  34. 34.
    Lee Y-B, Park J-H, Kim E et al (2014) Arterial stiffness and functional outcome in acute ischemic stroke. J Cerebrovasc Endovasc Neurosurg 16:11–19.  https://doi.org/10.7461/jcen.2014.16.1.11 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Nirmal Vadgama
    • 1
    • 2
  • Douglas Lamont
    • 3
  • John Hardy
    • 1
  • Jamal Nasir
    • 2
    • 5
    Email author
  • Ruth C. Lovering
    • 4
  1. 1.Institute of NeurologyUniversity College LondonLondonUK
  2. 2.Cell Biology and Genetics Research CentreSt. George’s University of LondonLondonUK
  3. 3.College of Life SciencesUniversity of DundeeDundeeUK
  4. 4.Centre for Cardiovascular Genetics, Institute of Cardiovascular ScienceUniversity College LondonLondonUK
  5. 5.Molecular Biosciences Research Group, Faculty of Health & SocietyUniversity of NorthamptonNorthamptonUK

Personalised recommendations