Skip to main content

Advertisement

Log in

Development of Early Diagnosis of Parkinson’s Disease Using Premotor Symptoms and Blood Changes as Biomarkers

  • Published:
Neuroscience and Behavioral Physiology Aims and scope Submit manuscript

Objectives. To identify changes in the biochemical composition of the plasma in a group of patients at risk of developing Parkinson’s disease (PD) at the prodromal stage in comparison with age-matched controls. Materials and methods. Subjects in the risk group were selected on the basis of the having impairments to sleep, olfaction, and peristalsis. The risk group consisted of 12 people and the control group of eight people. Results. The results showed that of seven catecholamines and their metabolites, the only blood change was in the L-dihydroxyphenylalanine (L-DOPA) level, which decreased in the risk group from the level in controls. A decreased L-DOPA concentration is regarded as a marker for selective degeneration of central and peripheral catecholaminergic neurons in PD. In contrast to L-DOPA, the blood concentrations of seven of 12 sphingomyelins increased. Given that changes in sphingomyelin metabolism are linked with apoptosis, autophagy, and synucleinopathies, increases in their concentrations in the risk group are regarded as indicators of systemic degeneration of central and peripheral neurons. Furthermore, the risk group showed a tendency to decreased urate concentrations, which are endogenous neuroprotectors. Conclusions. The results obtained here suggest that changes in blood L-DOPA, sphingomyelin, and urate levels can serve as diagnostic markers for the development of PD at the prodromal stage.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. R. B. Postuma, D. Berg, M. Stern, et al., “MDS clinical diagnostic criteria for Parkinson’s disease,” Mov. Disord., 30, No. 12, 1591–1601 (2015), https://doi.org/10.1002/mds.26424.

    Article  PubMed  Google Scholar 

  2. M. R. Nodel, “The impact of neuropsychiatric impairments on quality of life of patients with Parkinson’s disease,” Nevrol. Zh., 20, No. 1, 20–25 (2015), https://doi.org/10.18821/1560-9545-2015-20-1-20-27.

  3. M. R. Nodel, Yu. V. Ukraintseva, and N. N. Yakhno, “Rapid eye movements sleep behavioral disorder in Parkinson’s disease,” Nevrol. Zh., 20, No. 6, 28–34 (2015), https://doi.org/10.17116/jnevro20171179115-20.

  4. E. A. Katunina, E. P. Il’ina, G. I. Sadekova, and E. I. Gaisenyuk, “Approaches to early diagnosis of Parkinson’s disease,” Zh. Nevrol. Psikhiatr., 119, No. 6, 119–127 (2019), https://doi.org/10.17116/jnevro2019119061119.

  5. E. Bezard and C. E. Gross, “Compensatory mechanisms in experimental and human parkinsonism: towards a dynamic approach,” Prog. Neurobiol., 55, No. 2, 93–116 (1998), https://doi.org/10.1016/s0301-0082(98)00006-9.

    Article  CAS  PubMed  Google Scholar 

  6. J. Blesa, I. Trigo-Damas, M. Dileone, et al., “Compensatory mechanisms in Parkinson’s disease: Circuits adaptations and role in disease modification,” Exp. Neurol., 298, Part B, 148–161 (2017), https://doi.org/10.1016/j.expneurol.2017.10.002.

  7. Y. Agid, “Parkinson’s disease: pathophysiology,” Lancet, 337, No. 8753, 1321–1324 (1991), https://doi.org/10.1016/0140-6736(91)92989-f.

    Article  CAS  PubMed  Google Scholar 

  8. M. Ugrumov, “Development of early diagnosis of Parkinson’s disease: illusion or reality?” CNS Neurosci. Ther., 26, No. 10, 997–1009 (2020), https://doi.org/10.1111/cns.13429.

    Article  PubMed Central  Google Scholar 

  9. B. S. Connolly and A. E. Lang, “Pharmacological treatment of Parkinson disease: a review,” JAMA, 311, No. 16, 1670–1683 (2014), https://doi.org/10.1001/jama.2014.3654.

    Article  CAS  PubMed  Google Scholar 

  10. D. S. Goldstein, “Dysautonomia in Parkinson disease,” Compr. Physiol., 4, No. 2, 805–826 (2014), https://doi.org/10.1002/cphy.c130026.

    Article  PubMed  PubMed Central  Google Scholar 

  11. H. Braak, K. Del Tredici, U. Rüb, et al., “Staging of brain pathology related to sporadic Parkinson’s disease,” Neurobiol. Aging, 24, No. 2, 197–211 (2003), https://doi.org/10.1016/s0197-4580(02)00065-9.

    Article  PubMed  Google Scholar 

  12. P. Mahlknecht, K. Seppi, and W. Poewe, “The concept of prodromal Parkinson’s disease,” J. Parkinsons Dis., 5, No. 4, 681–697 (2015), https://doi.org/10.3233/JPD-150685.

    Article  PubMed  PubMed Central  Google Scholar 

  13. R. B. Postuma and D. Berg, “Advances in markers of prodromal Parkinson disease,” Nat. Rev. Neurol., 12, No. 11, 622–634 (2016), https://doi.org/10.1038/nrneurol.2016.152.

    Article  CAS  PubMed  Google Scholar 

  14. C. Pont-Sunyer, A. Hotter, C. Gaig, et al., “The onset of nonmotor symptoms in Parkinson’s disease (the ONSET PD study),” Mov. Disord., 30, No. 2, 229–237 (2015), https://doi.org/10.1002/mds.26077.

    Article  PubMed  Google Scholar 

  15. M. O. Izawa, H. Miwa, Y. Kajimoto, and T. Kondo, “Combination of transcranial sonography, olfactory testing, and MIBG myocardial scintigraphy as a diagnostic indicator for Parkinson’s disease,” Eur. J. Neurol., 19, No. 3, 411–416 (2012), https://doi.org/10.1111/j.1468-1331.2011.03533.x.

    Article  CAS  PubMed  Google Scholar 

  16. H. Y. Shin, E. Y. Joo, S. T. Kim, et al., “Comparison study of olfactory function and substantia nigra hyperechogenicity in idiopathic REM sleep behavior disorder, Parkinson’s disease and normal control,” Neurol. Sci., 34, No. 6, 935–940 (2013), https://doi.org/10.1007/s10072-012-1164-0.

    Article  PubMed  Google Scholar 

  17. M. Eller and D. R. Williams, “Biological fluid biomarkers in neurodegenerative parkinsonism,” Nat. Rev. Neurol., 5, No. 10, 561–570 (2009), https://doi.org/10.1038/nrneurol.2009.135.

    Article  CAS  PubMed  Google Scholar 

  18. W. Le, J. Dong, S. Li, and A.D. Korczyn, “Can biomarkers help the early diagnosis of Parkinson’s disease?” Neurosci. Bull., 33, No. 5, 535–542 (2017), https://doi.org/10.1007/s12264-017-0174-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. A. Kim, R. Nigmatullina, Z. Zalyalova, et al., “Upgraded methodology for the development of early diagnosis of Parkinson’s Disease based on searching blood markers in patients and experimental models,” Mol. Neurobiol., 56, No. 5, 3437–3450 (2019), https://doi.org/10.1007/s12035-018-1315-2.

    Article  CAS  PubMed  Google Scholar 

  20. K. Stiasny-Kolster, G. Mayer, S. Schäfer, et al., “The REM sleep behavior disorder screening questionnaire – a new diagnostic instrument,” Mov. Disord., 22, No. 16, 2386–2393 (2007), https://doi.org/10.1002/mds.21740.

    Article  PubMed  Google Scholar 

  21. S. Fahn and R. L. Elton, S. “UPDRS Development Committee. The Unified Parkinson’s Disease Rating Scale,” in: Recent Developments in Parkinson’s Disease, S. Fahn et al. (eds.), Macmillan Healthcare Information; Florham, NJ (1987), 2nd ed., pp. 153–163, 293–304.

  22. M. Visser, J. Marinus, A. M. Stiggelbout, and J. J. Van Hilten, “Assessment of autonomic dysfunction in Parkinson’s disease: the SCOPA-AUT,” Mov. Disord., 19, No. 11, 1306–1312 (2004), https://doi.org/10.1002/mds.20153.

    Article  PubMed  Google Scholar 

  23. A. S. Zigmond and R. P. Snaith, “The Hospital Anxiety and Depression Scale,” Acta Psychiatr. Scand., 67, No. 6, 361–370 (1983), https://doi.org/10.1111/j.1600-0447.1983.tb09716.x.

    Article  CAS  PubMed  Google Scholar 

  24. S. E. Starkstein, H. S. Mayberg, T. J. Preziosi, et al., “Reliability, validity, and clinical correlates of apathy in Parkinson’s disease,” J. Neuropsychiatry Clin. Neurosci., 4, No. 2, 134–139 (1992), https://doi.org/10.1176/jnp.4.2.134.

    Article  CAS  PubMed  Google Scholar 

  25. R. G. Brown, A. Dittner, L. Findley, and S. C. Wessely, “The Parkinson Fatigue Scale,” Parkinsonism Relat. Disord., 11, No. 1, 49–55 (2005), https://doi.org/10.1016/j.parkreldis.2004.07.007.

    Article  CAS  PubMed  Google Scholar 

  26. Z. S. Nasreddine, N. A. Phillips, V. Bédirian, et al., “The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment [published correction appears in J. Am. Geriatr. Soc., 67, No. 9, 1991 (2019)].,” J. Am. Geriatr. Soc., 53, No. 4, 695–699 (2005), https://doi.org/10.1111/j.1532-5415.2005.53221.x.

  27. S. Choi-Kwon, S. W. Han, S. U. Kwon, and J. S. Kim, “Poststroke fatigue: characteristics and related factors,” Cerebrovasc. Dis., 19, No. 2, 84–90 (2005), https://doi.org/10.1159/000082784.

    Article  PubMed  Google Scholar 

  28. D. Berg, R. B. Postuma, C. H. Adler, et al., “MDS research criteria for prodromal Parkinson’s disease,” Mov. Disord., 30, No. 12, 1600–1611 (2015), https://doi.org/10.1002/mds.26431.

    Article  PubMed  Google Scholar 

  29. E. A. Kozina, A. R. Kim, A. Y. Kurina, and M. V. Ugrumov, “Cooperative synthesis of dopamine by non-dopaminergic neurons as a compensatory mechanism in the striatum of mice with MPTP-induced Parkinsonism,” Neurobiol. Dis., 98, 108–121 (2017), https://doi.org/10.1016/j.nbd.2016.12.005.

    Article  CAS  PubMed  Google Scholar 

  30. E. G. Bligh and W. J. Dyer, “A rapid method of total lipid extraction and purification,” Can. J. Biochem. Physiol., 37, No. 8, 911–917 (1959), https://doi.org/10.1139/o59-099.

    Article  CAS  PubMed  Google Scholar 

  31. C. A. Antoniades and R. A. Barker, “The search for biomarkers in Parkinson’s disease: a critical review,” Expert Rev. Neurother., 8, No. 12, 1841–1852 (2008), https://doi.org/10.1586/14737175.8.12.1841.

    Article  PubMed  Google Scholar 

  32. Z. Yu, T. Stewart, J. Aasly, et al., “Combining clinical and biofluid markers for early Parkinson’s disease detection,” Ann. Clin. Transl.Neurol., 5, No. 1, 109–114 (2017), https://doi.org/10.1002/acn3.509.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. T. Li and W. Le, “Biomarkers for Parkinson’s disease: How good are they?” Neurosci. Bull., 36, No. 2, 183–194 (2020), https://doi.org/10.1007/s12264-019-00433-1.

    Article  PubMed  Google Scholar 

  34. O. B. Tysnes and A. Storstein, “Epidemiology of Parkinson’s disease,” J. Neural Transm. (Vienna), 124, No. 8, 901–905 (2017), https://doi.org/10.1007/s00702-017-1686-y.

    Article  Google Scholar 

  35. B. L. B. Marino, L. R. de Souza, K. P. A. Sousa, et al., “Parkinson’s disease: A review from pathophysiology to treatment,” Mini Rev. Med. Chem., 20, No. 9, 754–767 (2020), https://doi.org/10.2174/1389557519666191104110908.

    Article  CAS  PubMed  Google Scholar 

  36. A. V. Alessenko and E. Albi, “Exploring sphingolipid implications in neurodegeneration,” Front. Neurol., 11, 437 (2020), https://doi.org/10.3389/fneur.2020.00437.

    Article  PubMed  PubMed Central  Google Scholar 

  37. G. F. Nixon, “Sphingolipids in infl ammation: pathological implications and potential therapeutic targets,” Br. J. Pharmacol., 158, No. 4, 982–993 (2009), https://doi.org/10.1111/j.1476-5381.2009.00281.x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. G. H. Norris and C. N. Blesso, “Dietary and endogenous sphingolipid metabolism in chronic inflammation,” Nutrients, 9, No. 11, 1180 (2017), https://doi.org/10.3390/nu9111180.

  39. M. J. Jembrek, P. R. Hof, and G. Šimić, “Ceramides in Alzheimer’s Disease: key mediators of neuronal apoptosis induced by oxidative stress and Aβ accumulation,” Oxid. Med. Cell. Longev., 2015, 346783 (2015), https://doi.org/10.1155/2015/346783.

  40. Y. Kiraz, A. Adan, M. Kartal Yandim, and Y. Baran, “Major apoptotic mechanisms and genes involved in apoptosis,” Tumour Biol., 37, No. 7, 8471–8486 (2016), https://doi.org/10.1007/s13277-016-5035-9.

    Article  CAS  PubMed  Google Scholar 

  41. C. Y. Mao, J. Yang, H. Wang, et al., “SMPD1 variants in Chinese Han patients with sporadic Parkinson’s disease,” Parkinsonism Relat. Disord., 34, 59–61 (2017), https://doi.org/10.1016/j.parkreldis.2016.10.014.

    Article  PubMed  Google Scholar 

  42. J. N. Foo, H. Liany, J. X. Bei, et al., “Rare lysosomal enzyme gene SMPD1 variant (p.R591C) associates with Parkinson’s disease,” Neurobiol. Aging, 34, No. 12, 37–42 (2013), https://doi.org/10.1016/j.neurobiolaging.2013.06.010.

    Article  CAS  Google Scholar 

  43. W. S. Kim and G. M. Halliday, “Changes in sphingomyelin level affect alpha-synuclein and ABCA5 expression,” J. Parkinsons Dis., 2, No. 1, 41–46 (2012), https://doi.org/10.3233/JPD-2012-11059.

    Article  CAS  PubMed  Google Scholar 

  44. W. A. den Jager, “Sphingomyelin in Lewy inclusion bodies in Parkinson’s disease,” Arch. Neurol., 21, No. 6, 615–619 (1969), https://doi.org/10.1001/archneur.1969.00480180071006.

    Article  Google Scholar 

  45. M. Vila and S. Przedborski, “Targeting programmed cell death in neurodegenerative diseases,” Nat. Rev. Neurosci., 4, No. 5, 365–375 (2003), https://doi.org/10.1038/nrn1100.

    Article  CAS  PubMed  Google Scholar 

  46. N. Simola, M. Morelli, and A. R. Carta, “The 6-hydroxydopamine model of Parkinson’s disease,” Neurotox. Res., 11, No. 3–4, 151–167 (2007), https://doi.org/10.1007/BF03033565.

    Article  CAS  PubMed  Google Scholar 

  47. F. Cicchetti, J. Drouin-Ouellet, an R. E. Gross, “Environmental toxins and Parkinson’s disease: what have we learned from pesticide-induced animal models?” Trends. Pharmacol. Sci., 30, No. 9, 475–483 (2009), https://doi.org/10.1016/j.tips.2009.06.005.

  48. L. C. Guedes, R. B. Chan, M. A. Gomes, et al., “Serum lipid alterations in GBA-associated Parkinson’s disease,” Parkinsonism Relat. Disord., 44, 58–65 (2017), https://doi.org/10.1016/j.parkreldis.2017.08.026.

    Article  PubMed  Google Scholar 

  49. S. Cipriani, X. Chen, and M. A. Schwarzschild, “Urate: a novel biomarker of Parkinson’s disease risk, diagnosis and prognosis,” Biomark Med., 4, No. 5, 701–712 (2010), https://doi.org/10.2217/bmm.10.94.

    Article  CAS  PubMed  Google Scholar 

  50. M. Wen, B. Zhou, Y. H. Chen, et al., “Serum uric acid levels in patients with Parkinson’s disease: A meta-analysis,” PLoS One, 12, No. 3, e0173731 (2017), https://doi.org/10.1371/journal.pone.0173731.

  51. R. Uribe-San Martín, P. Venegas Francke, F. López Illanes, et al., “Plasma urate in REM sleep behavior disorder,” Mov. Disord., 28, No. 8, 1150–1151 (2013), https://doi.org/10.1002/mds.25441.

    Article  PubMed  Google Scholar 

  52. D. J. van Wamelen, R. N. Taddei, A. Calvano, et al., “Serum uric acid levels and non-motor symptoms in Parkinson’s disease,” J. Parkinsons Dis., 10, No. 3, 1003–1010 (2020), https://doi.org/10.3233/jpd-201988.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to E. A. Katunina.

Additional information

Translated from Zhurnal Nevrologii i Psikhiatrii imeni S. S. Korsakova, Vol. 120, No. 12, Iss. 1, pp. 7–17, December, 2020.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gusev, E.I., Katunina, E.A., Martinov, M.Y. et al. Development of Early Diagnosis of Parkinson’s Disease Using Premotor Symptoms and Blood Changes as Biomarkers. Neurosci Behav Physi 51, 1050–1058 (2021). https://doi.org/10.1007/s11055-021-01164-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11055-021-01164-5

Keywords

Navigation