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Identification of distinct blood-based biomarkers in early stage of Parkinson’s disease

  • Yingyan Wu
  • Qian Yao
  • Guo-Xin Jiang
  • Gang Wang
  • Qi ChengEmail author
Original Article

Abstract

Parkinson’s disease (PD) is a slowly progressive geriatric disease, which can be one of the leading causes of serious socioeconomic burden in the aging society. Clinical trials suggest that prompt treatment of early-stage Parkinson’s disease (EPD) may slow down the disease progress and have a better response. Therefore, conducting proteomics study to identify biomarkers for the diagnosis and disease-modifying therapies of EPD is vital. We aimed at identifying distinct protein autoantibody biomarkers of EPD by using the database of GSE62283 based on the platform GPL13669 downloaded from Gene Expression Omnibus database. Differentially expressed proteins (DEPs) between the EPD group (n = 103) and the normal control (NC) group (n = 111) were identified by protein-specific t test. Cluster analysis of DEPs was conducted by protein–protein interaction network to detect hub proteins. The hub proteins were then evaluated to determine the distinct biomarkers by principal component analysis, as well as functional and pathway enrichment analysis. Their biological functions were confirmed by gene ontology functional (GO) and Kyoto encyclopedia of genes and genomes pathway enrichment (KEGG). Two biomarkers, mitochondrial ribosome recycling factor (MRRF) and ribosomal protein S18 (RPS18), distinguished the EPD samples from the NC samples, and they were regarded as high-confidence distinct protein autoantibody biomarkers of EPD. The most significant GO function was protein serine/threonine kinase activity (GO: 0004674) and most of DEPs were enriched in ATP binding in molecular function category (GO: 0005524). These results may help in establishing the prompt and accurate diagnosis of EPD and may also contribute to develop mechanism-based treatments.

Keywords

Early-stage Parkinson’s disease Blood-based biomarker Functional analysis Protein-protein interaction 

Abbreviations

PD

Parkinson’s disease

EPD

Early-stage Parkinson’s disease

NC

Normal control

DEPs

Differentially expressed proteins

KEGG

Kyoto encyclopedia of genes and genomes

GO

Gene ontology

PPI

Protein–protein interaction

α-syn

α-Synuclein

PCA

Principal component analysis

Notes

Funding information

This work was supported by the National Key R&D Program of China (grant number 2016YFC1306000).

Compliance with ethical standards

The original study [20] is approved by Rowan-Stratford Institutional Review Board.

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

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References

  1. 1.
    Lin X, Cook TJ, Zabetian CP, Leverenz JB, Peskind ER, Hu SC, Cain KC, Pan C, Edgar JS, Goodlett DR, Racette BA, Checkoway H, Montine TJ, Shi M, Zhang J (2012) DJ-1 isoforms in whole blood as potential biomarkers of Parkinson disease. Sci Rep 2:954.  https://doi.org/10.1038/srep00954 CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Zhao YJ, Wee HL, Chan YH, Seah SH, Au WL, Lau PN, Pica EC, Li SC, Luo N, Tan LC (2010) Progression of Parkinson’s disease as evaluated by Hoehn and Yahr stage transition times. Mov Disord 25(6):710–716.  https://doi.org/10.1002/mds.22875 CrossRefPubMedGoogle Scholar
  3. 3.
    Ma CL, Su L, Xie JJ, Long J-x, Wu P, Gu L (2014) The prevalence and incidence of Parkinson’s disease in China systematic review and meta-analysis. J Neural Transm 121:123–134.  https://doi.org/10.1007/s00702-013-1092-z) CrossRefPubMedGoogle Scholar
  4. 4.
    Dorsey ER, Constantinescu R, Thompson JP, Biglan KM, Holloway RG, Kieburtz K, Marshall FJ, Ravina BM, Schifitto G, Siderowf A, Tanner CM (2007) Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030. Neurology 68(5):384–386.  https://doi.org/10.1212/01.wnl.0000247740.47667.03 CrossRefGoogle Scholar
  5. 5.
    Rodriguez-Blazquez C, Forjaz MJ, Lizan L, Paz S, Martinez-Martin P (2015) Estimating the direct and indirect costs associated with Parkinson’s disease. Expert Rev Pharmacoecon Outcomes Res 15(6):889–911.  https://doi.org/10.1586/14737167.2015.1103184 CrossRefPubMedGoogle Scholar
  6. 6.
    Zhao YJ, Wee HL, Au WL, Seah SH, Luo N, Li SC, Tan LC (2011) Selegiline use is associated with a slower progression in early Parkinson’s disease as evaluated by Hoehn and Yahr stage transition times. Parkinsonism Relat Disord 17(3):194–197.  https://doi.org/10.1016/j.parkreldis.2010.11.010 CrossRefPubMedGoogle Scholar
  7. 7.
    Schrag A, Spottke A, Quinn NP, Dodel R (2009) Comparative responsiveness of Parkinson’s disease scales to change over time. Mov Disord 24(6):813–818.  https://doi.org/10.1002/mds.22438 CrossRefPubMedGoogle Scholar
  8. 8.
    Scanlon BK, Katzen HL, Levin BE, Singer C, Papapetropoulos S (2008) A formula for the conversion of UPDRS-III scores to Hoehn and Yahr stage. Parkinsonism Relat Disord 14(4):379–380.  https://doi.org/10.1016/j.parkreldis.2007.09.010 CrossRefPubMedGoogle Scholar
  9. 9.
    Hoehn M, Yahr M (2011) Parkinsonism: Onset, progression, and mortality. Neurology 77(9):874–874.  https://doi.org/10.1212/01.wnl.0000405146.06300.91 CrossRefGoogle Scholar
  10. 10.
    Tsanas A, Little MA, McSharry PE, Scanlon BK, Papapetropoulos S (2012) Statistical analysis and mapping of the unified Parkinson’s disease rating scale to Hoehn and Yahr staging. Parkinsonism Relat Disord 18(5):697–699.  https://doi.org/10.1016/j.parkreldis.2012.01.011 CrossRefPubMedGoogle Scholar
  11. 11.
    Reichmann H (2010) Clinical criteria for the diagnosis of Parkinson’s disease. Neurodegener Dis 7(5):284–290.  https://doi.org/10.1159/000314478 CrossRefPubMedGoogle Scholar
  12. 12.
    Kalia LV, Lang AE (2015) Parkinson’s disease. Lancet 386(9996):896–912.  https://doi.org/10.1016/s0140-6736(14)61393-3 CrossRefGoogle Scholar
  13. 13.
    Marconi S, Zwingers T (2014) Comparative efficacy of selegiline versus rasagiline in the treatment of early Parkinson’s disease. Eur Rev Med Pharmacol Sci 18(13):1879–1882PubMedGoogle Scholar
  14. 14.
    Fahn S (2008) The history of dopamine and levodopa in the treatment of Parkinson’s disease. Mov Disord 23(Suppl 3):S497–S508.  https://doi.org/10.1002/mds.22028 CrossRefPubMedGoogle Scholar
  15. 15.
    Group PsS (1996) Impact of deprenyl and tocopherol treatment on Parkinson’s disease in DATATOP patients requiring levodopa. Ann Neurol 39(1):37–45CrossRefGoogle Scholar
  16. 16.
    Adler CH, Beach TG, Hentz JG, Shill HA, Caviness JN, Driver-Dunckley E, Sabbagh MN, Sue LI, Jacobson SA, Belden CM, Dugger BN (2014) Low clinical diagnostic accuracy of early vs advanced Parkinson disease: clinicopathologic study. Neurology 83(5):406–412.  https://doi.org/10.1212/WNL.0000000000000641 CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Miller DB, O’Callaghan JP (2015) Biomarkers of Parkinson’s disease: present and future. Metabolism 64(3 Suppl 1):S40–S46.  https://doi.org/10.1016/j.metabol.2014.10.030 CrossRefGoogle Scholar
  18. 18.
    Sulzer D, Cassidy C, Horga G, Kang UJ, Fahn S, Casella L, Pezzoli G, Langley J, Hu XP, Zucca FA, Isaias IU, Zecca L (2018) Neuromelanin detection by magnetic resonance imaging (MRI) and its promise as a biomarker for Parkinson’s disease. NPJ Parkinson's disease 4:11.  https://doi.org/10.1038/s41531-018-0047-3 CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    George S, Brundin P (2015) Immunotherapy in Parkinson’s disease: micromanaging alpha-synuclein aggregation. J Parkinsons Dis 5(3):413–424.  https://doi.org/10.3233/JPD-150630 CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    DeMarshall CA, Han M, Nagele EP, Sarkar A, Acharya NK, Godsey G, Goldwaser EL, Kosciuk M, Thayasivam U, Belinka B, Nagele RG, Parkinson’s Study Group I (2015) Potential utility of autoantibodies as blood-based biomarkers for early detection and diagnosis of Parkinson’s disease. Immunol Lett 168(1):80–88.  https://doi.org/10.1016/j.imlet.2015.09.010 CrossRefPubMedGoogle Scholar
  21. 21.
    Bougea A, Stefanis L, Paraskevas GP, Emmanouilidou E, Vekrelis K, Kapaki E (2019) Plasma alpha-synuclein levels in patients with Parkinson’s disease: a systematic review and meta-analysis. Neurological Sciences 40(5):929–938.  https://doi.org/10.1007/s10072-019-03738-1 CrossRefPubMedGoogle Scholar
  22. 22.
    Alegre-Abarrategui J, Ansorge O, Esiri M, Wade-Martins R (2008) LRRK2 is a component of granular alpha-synuclein pathology in the brainstem of Parkinson’s disease. Neuropathol Appl Neurobiol 34(3):272–283.  https://doi.org/10.1111/j.1365-2990.2007.00888.x CrossRefPubMedGoogle Scholar
  23. 23.
    Mills RD, Sim CH, Mok SS, Mulhern TD, Culvenor JG, Cheng HC (2008) Biochemical aspects of the neuroprotective mechanism of PTEN-induced kinase-1 (PINK1). J Neurochem 105(1):18–33.  https://doi.org/10.1111/j.1471-4159.2008.05249.x CrossRefPubMedGoogle Scholar
  24. 24.
    Reetz K, Lencer R, Steinlechner S, Gaser C, Hagenah J, Buchel C, Petersen D, Kock N, Djarmati A, Siebner HR, Klein C, Binkofski F (2008) Limbic and frontal cortical degeneration is associated with psychiatric symptoms in PINK1 mutation carriers. Biol Psychiatry 64(3):241–247.  https://doi.org/10.1016/j.biopsych.2007.12.010 CrossRefPubMedGoogle Scholar
  25. 25.
    van Duijn CM, Dekker MC, Bonifati V, Galjaard RJ, Houwing-Duistermaat JJ, Snijders PJ, Testers L, Breedveld GJ, Horstink M, Sandkuijl LA, van Swieten JC, Oostra BA, Heutink P (2001) Park7, a novel locus for autosomal recessive early-onset parkinsonism, on chromosome 1p36. Am J Human Genet 69(3):629–634.  https://doi.org/10.1086/322996 CrossRefGoogle Scholar
  26. 26.
    Huang DW, Sherman BT, Tan Q, Collins JR, Alvord WG, Roayaei J, Stephens R, Baseler MW, Lane HC, Lempicki RA (2007) The DAVID gene functional classification tool: a novel biological module-centric algorithm to functionally analyze large gene lists. Genome Biol 8(9):R183.  https://doi.org/10.1186/gb-2007-8-9-r183 CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Consortium GO (2015) Gene ontology consortium: going forward. Nucleic Acids Res 43:1049–1056CrossRefGoogle Scholar
  28. 28.
    Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M (2010) KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res 38(Database issue):D355–D360.  https://doi.org/10.1093/nar/gkp896 CrossRefPubMedGoogle Scholar
  29. 29.
    Von Mering CHM, Jaeggi D, Schmidt S, Bork P, Snel B (2003) STRING: a database of predicted functional associations between proteins. Nucleic Acids Res 31:258–261CrossRefGoogle Scholar
  30. 30.
    Kohl M, Wiese S, Warscheid B (2011) Cytoscape: software for visualization and analysis of biological networks. Methods Mol Biol 696(696):291–303.  https://doi.org/10.1007/978-1-60761-987-1_18 CrossRefPubMedGoogle Scholar
  31. 31.
    Soreq L, Bergman H, Israel Z, Soreq H (2013) Deep brain stimulation modulates nonsense-mediated RNA decay in Parkinson’s patients leukocytes. BMC Genomics 14:478.  https://doi.org/10.1186/1471-2164-14-478 CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Perier C, Bove J, Vila M (2012) Mitochondria and programmed cell death in Parkinson’s disease: apoptosis and beyond. Antioxid Redox Signal 16(9):883–895.  https://doi.org/10.1089/ars.2011.4074 CrossRefPubMedGoogle Scholar
  33. 33.
    Niranjan R (2014) The role of inflammatory and oxidative stress mechanisms in the pathogenesis of Parkinson’s disease: focus on astrocytes. Mol Neurobiol 49(1):28–38.  https://doi.org/10.1007/s12035-013-8483-x CrossRefPubMedGoogle Scholar
  34. 34.
    Sim CH, Lio DS, Mok SS, Masters CL, Hill AF, Culvenor JG, Cheng HC (2006) C-terminal truncation and Parkinson’s disease-associated mutations down-regulate the protein serine/threonine kinase activity of PTEN-induced kinase-1. Human Mol Genet 15(21):3251–3262.  https://doi.org/10.1093/hmg/ddl398 CrossRefGoogle Scholar
  35. 35.
    Inamdar AA, Masurekar P, Hossain M, Richardson JR, Bennett JW (2014) Signaling pathways involved in 1-octen-3-ol-mediated neurotoxicity in Drosophila melanogaster: implication in Parkinson’s disease. Neurotox Res 25(2):183–191.  https://doi.org/10.1007/s12640-013-9418-z CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Jha SK, Jha NK, Kar R, Ambasta RK, Kumar P (2015) p38 MAPK and PI3K/AKT signalling cascades in Parkinson’s disease. Int J Mol Cell Med 4(2):67–86PubMedPubMedCentralGoogle Scholar
  37. 37.
    EMBL-EBI Quick GO (2009) https://wwwe.biacuk/QuickGO/. Accessed 3 Apr 2018
  38. 38.
    ElAli A, Hermann DM (2011) ATP-binding cassette transporters and their roles in protecting the brain. Neuroscientist 17(4):423–436.  https://doi.org/10.1177/1073858410391270 CrossRefPubMedGoogle Scholar
  39. 39.
    Taymans JM, Nkiliza A, Chartier-Harlin MC (2015) Deregulation of protein translation control, a potential game-changing hypothesis for Parkinson’s disease pathogenesis. Trends Mol Med 21(8):466–472.  https://doi.org/10.1016/j.molmed.2015.05.004 CrossRefPubMedGoogle Scholar
  40. 40.
    Olanow CW, Schapira AH (2013) Therapeutic prospects for Parkinson disease. Ann Neurol 74(3):337–347.  https://doi.org/10.1002/ana.24011 CrossRefPubMedGoogle Scholar
  41. 41.
    AlDakheel A, Kalia LV, Lang AE (2014) Pathogenesis-targeted, disease-modifying therapies in Parkinson disease. Neurotherapeutics 11(1):6–23.  https://doi.org/10.1007/s13311-013-0218-1 CrossRefPubMedGoogle Scholar
  42. 42.
    Lin MT, Beal MF (2006) Mitochondrial dysfunction and oxidative stress in neurodegenerative diseases. Nature 443(7113):787–795.  https://doi.org/10.1038/nature05292 CrossRefPubMedGoogle Scholar
  43. 43.
    Voshavar C, Shah M, Xu L, Dutta AK (2015) Assessment of protective role of multifunctional dopamine agonist D-512 against oxidative stress produced by depletion of glutathione in PC12 cells: implication in neuroprotective therapy for Parkinson’s disease. Neurotox Res 28(4):302–318.  https://doi.org/10.1007/s12640-015-9548-6 CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Bhat AH, Dar KB, Anees S, Zargar MA, Masood A, Sofi MA, Ganie SA (2015) Oxidative stress, mitochondrial dysfunction and neurodegenerative diseases; a mechanistic insight. Biomed Pharmacother 74:101–110.  https://doi.org/10.1016/j.biopha.2015.07.025 CrossRefPubMedPubMedCentralGoogle Scholar
  45. 45.
    Muftuoglu M, Elibol B, Dalmizrak O, Ercan A, Kulaksiz G, Ogus H, Dalkara T, Ozer N (2004) Mitochondrial complex I and IV activities in leukocytes from patients with parkin mutations. Mov Disord 19(5):544–548.  https://doi.org/10.1002/mds.10695 CrossRefPubMedGoogle Scholar
  46. 46.
    Ryan BJ, Hoek S, Fon EA, Wade-Martins R (2015) Mitochondrial dysfunction and mitophagy in Parkinson’s: from familial to sporadic disease. Trends Biochem Sci 40(4):200–210.  https://doi.org/10.1016/j.tibs.2015.02.003 CrossRefPubMedGoogle Scholar
  47. 47.
    Gotz ME, Double K, Gerlach M, Youdim MB, Riederer P (2004) The relevance of iron in the pathogenesis of Parkinson’s disease. Ann N Y Acad Sci 1012:193–208CrossRefGoogle Scholar
  48. 48.
    Jiang D, Shi S, Zhang L, Liu L, Ding B, Zhao B, Yagnik G, Zhou F (2013) Inhibition of the Fe(III)-catalyzed dopamine oxidation by ATP and its relevance to oxidative stress in Parkinson’s disease. ACS Chem Neurosci 4(9):1305–1313.  https://doi.org/10.1021/cn400105d CrossRefPubMedPubMedCentralGoogle Scholar
  49. 49.
    Santiago JA, Potashkin JA (2015) Blood biomarkers associated with cognitive decline in early stage and drug-naive Parkinson’s disease patients. PLoS One 10(11):e0142582.  https://doi.org/10.1371/journal.pone.0142582 CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.
    Sveinbjornsdottir S (2016) The clinical symptoms of Parkinson’s disease. J Neurochem 139(Suppl 1):318–324.  https://doi.org/10.1111/jnc.13691 CrossRefPubMedGoogle Scholar
  51. 51.
    Bonifati V, Rizzu P, van Baren MJ, Schaap O, Breedveld GJ, Krieger E, Dekker MC, Squitieri F, Ibanez P, Joosse M, van Dongen JW, Vanacore N, van Swieten JC, Brice A, Meco G, van Duijn CM, Oostra BA, Heutink P (2003) Mutations in the DJ-1 gene associated with autosomal recessive early-onset parkinsonism. Science (New York, NY) 299(5604):256–259.  https://doi.org/10.1126/science.1077209 CrossRefGoogle Scholar

Copyright information

© Fondazione Società Italiana di Neurologia 2019

Authors and Affiliations

  1. 1.School of Public HealthShanghai Jiao Tong UniversityShanghaiChina
  2. 2.Department of Learning, Informatics, Management and EthicsKarolinska InstituteStockholmSweden
  3. 3.Department of Neurology & Neuroscience InstituteRuijin Hospital affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina

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