Abstract
The need for an early and differential diagnosis of Parkinson’s disease (PD) is undoubtedly one of the main quests of the century. An early biomarker would enable therapy to begin sooner and would, hopefully, slow or better prevent progression of the disease. We performed transcript profiling via quantitative RT-PCR in RNA originating from peripheral blood samples. The groups were de novo (n = 11) and medicated PD (n = 94) subjects and healthy controls (n = 34), while for negative control Alzheimer’s disease (AD; n = 14) subjects were recruited as an additional neurodegenerative disease. The results were retested on a second recruitment consisting 22 medicated PD subjects versus 33 controls and 12 AD. Twelve transcripts were chosen as candidate genes, according to previous postmortem brain profiling. Multiple analyses resulted in four significant genes: proteasome (prosome, macropain) subunit-alpha type-2 (PSMA2; p = 0.0002, OR = 1.15 95% CI 1.07–1.24), laminin, beta-2 (laminin S) (LAMB2; p = 0.0078, OR = 2.26 95% CI 1.24–4.14), aldehyde dehydrogenase 1 family-member A1 (ALDH1A1; p = 0.016, OR = 1.05 95% CI 1.01–1.1), and histone cluster-1 H3e (HIST1H3E; p = 0.03, OR = 0.975 95% CI 0.953–0.998) differentiating between medicated PD subjects versus controls. Using these four biomarkers for PD diagnosis, we achieved sensitivity and specificity of more than 80%. These biomarkers might be specific for PD diagnosis, since in AD subjects no significant results were observed. In the second validation, three genes (PSMA2, LAMB2 and ALDH1A1) demonstrated high reproducibility. This result supports previous studies of gene expression profiling and may facilitate the development of biomarkers for early diagnosis of PD.
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References
Berg L (1988) Clinical Dementia Rating (CDR). Psychopharmacol Bull 24:637–639
Bernheimer H, Birkmayer W, Hornykiewicz O, Jellinger K, Seitelberger F (1973) Brain dopamine and the syndromes of Parkinson and Huntington. Clinical, morphological and neurochemical correlations. J Neurol Sci 20:415–455
Bhidayasiri R (2006) How useful is (123I) beta-CIT SPECT in the diagnosis of Parkinson’s disease? Rev Neurol Dis 3:19–22
Bogdanov M, Matson WR, Wang L, Matson T, Saunders-Pullman R, Bressman SS, Beal MF (2008) Metabolomic profiling to develop blood biomarkers for Parkinson’s disease. Brain 131:389–396
Brooks DJ (1998) The early diagnosis of Parkinson’s disease. Ann Neurol 44:S10–S18
Coste J, Ouchchane L, Sarry L, Derost P, Durif F, Gabrillargues J, Hemm S, Lemaire JJ (2009) New electrophysiological mapping combined with MRI in parkinsonian’s subthalamic region. Eur J Neurosci 29:1627–1633
Eerola J, Tienari PJ, Kaakkola S, Nikkinen P, Launes J (2005) How useful is [123I]beta-CIT SPECT in clinical practice? J Neurol Neurosurg Psychiatry 76:1211–1216
Fahn S, Elton R, Committee, Mot UD (1987) Unified Parkinson’s disease rating scale. In: Fahn S, Marsden C, Goldstein M (eds) Recent developments in Parkinson’s disease. Macmillan, New York, pp 153–167
Fasano M, Alberio T, Lopiano L (2008) Peripheral biomarkers of Parkinson’s disease as early reporters of central neurodegeneration. Biomarkers Med 2:465–478
Grünblatt E (2008) Commonalities in the genetics of Alzheimer’s disease and Parkinson’s disease. Expert Rev Neurother 8:1865–1877
Grünblatt E, Mandel S, Jacob-Hirsch J et al (2004) Gene expression profiling of parkinsonian substantia nigra pars compacta; alterations in ubiquitin-proteasome, heat shock protein, iron and oxidative stress regulated proteins, cell adhesion/cellular matrix and vesicle trafficking genes. J Neural Transm 111:1543–1573
Grünblatt E, Zander N, Bartl J et al (2007) Comparison analysis of gene expression patterns between sporadic Alzheimer’s and Parkinson’s disease. J Alzheimers Dis 12:291–311
Grünblatt E, Bartl J, Zehetmayer S, Ringel TM, Bauer P, Riederer P, Jacob CP (2009) Gene expression as peripheral biomarkers for sporadic Alzheimer’s disease. J Alzheimers Dis 16:627–634
Hamilton M (1960) A rating scale for depression. J Neurol Neurosurg Psychiatry 23:56–62
Hatano T, Kubo S, Sato S, Hattori N (2009) Pathogenesis of familial Parkinson’s disease: new insights based on monogenic forms of Parkinson’s disease. J Neurochem 111:1075–1093
Hauser MA, Li YJ, Xu H et al (2005) Expression profiling of substantia nigra in Parkinson disease, progressive supranuclear palsy, and frontotemporal dementia with parkinsonism. Arch Neurol 62:917–921
Hennecke G, Scherzer CR (2008) RNA biomarkers of Parkinson’s disease: developing tools for novel therapies. Biomarkers Med 2:41–53
Hoehn MM, Yahr MD (1967) Parkinsonism: onset, progression and mortality. Neurology 17:427–442
Hughes AJ, Daniel SE, Ben-Shlomo Y, Lees AJ (2002) The accuracy of diagnosis of parkinsonian syndromes in a specialist movement disorder service. Brain 125:861–870
Hurley MJ, Mash DC, Jenner P (2003) Markers for dopaminergic neurotransmission in the cerebellum in normal individuals and patients with Parkinson’s disease examined by RT-PCR. Eur J Neurosci 18:2668–2672
Jankovic J, Rajput AH, McDermott MP, Perl DP (2000) The evolution of diagnosis in early Parkinson disease. Parkinson Study Group. Arch Neurol 57:369–372
Kassiou M, Banati R, Holsinger RM, Meikle S (2009) Challenges in molecular imaging of Parkinson’s disease: a brief overview. Brain Res Bull 78:105–108
Klein C, Schneider SA, Lang AE (2009) Hereditary parkinsonism: Parkinson disease look-alikes—an algorithm for clinicians to “PARK” genes and beyond. Mov Disord 24:2042–2058
Koerts J, Leenders KL, Koning M, Portman AT, van Beilen M (2007) Striatal dopaminergic activity (FDOPA-PET) associated with cognitive items of a depression scale (MADRS) in Parkinson’s disease. Eur J Neurosci 25:3132–3136
Lovrecic L, Kastrin A, Kobal J, Pirtosek Z, Krainc D, Peterlin B (2009) Gene expression changes in blood as a putative biomarker for Huntington’s disease. Mov Disord 24:2277–2281
Lu L, Neff F, Alvarez-Fischer D, Henze C, Xie Y, Oertel WH, Schlegel J, Hartmann A (2005) Gene expression profiling of Lewy body-bearing neurons in Parkinson’s disease. Exp Neurol 195:27–39
Manolio T (2003) Novel risk markers and clinical practice. N Engl J Med 349:1587–1589
McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM (1984) Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s disease. Neurology 34:939–944
Michell AW, Lewis SJG, Foltynie T, Barker RA (2004) Biomarkers and Parkinson’s disease. Brain 127:1693–1705
Mollenhauer B, Trenkwalder C (2009) Neurochemical biomarkers in the differential diagnosis of movement disorders. Mov Disord 24:1411–1426
O’Connor DW, Pollitt PA, Hyde JB, Fellows JL, Miller ND, Brook CP, Reiss BB (1989) The reliability and validity of the mini-mental state in a British community survey. J Psychiatr Res 23:87–96
Paulsen JS (2009) Biomarkers to predict and track diseases. Lancet Neurol 8:776–777
Postuma RB, Montplaisir J (2006) Potential early markers of Parkinson’s disease in idiopathic rapid-eye-movement sleep behaviour disorder. Lancet Neurol 5:552–553
Ravina B, Tanner C, Dieuliis D et al (2009) A longitudinal program for biomarker development in Parkinson’s disease: a feasibility study. Mov Disord 24:2081–2090
Scherzer CR (2009) Chipping away at diagnostics for neurodegenerative diseases. Neurobiol Dis 35:148–156
Scherzer CR, Eklund AC, Morse LJ et al (2007) Molecular markers of early Parkinson’s disease based on gene expression in blood. Proc Natl Acad Sci USA 104:955–960
Simunovic F, Yi M, Wang YL et al (2009) Gene expression profiling of substantia nigra dopamine neurons: further insights into Parkinson’s disease pathology. Brain 132:1795–1809
Sullivan PF, Fan C, Perou CM (2006) Evaluating the comparability of gene expression in blood and brain. Am J Med Genet B Neuropsychiatr Genet 141:261–268
Tolosa E, Wenning G, Poewe W (2006) The diagnosis of Parkinson’s disease. Lancet Neurol 5:75–86
Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3(7):research0034.1–research0034.11
Wouters H, van Gool WA, Schmand B, Lindeboom R (2008) Revising the ADAS-cog for a more accurate assessment of cognitive impairment. Alzheimer Dis Assoc Disord 22(3):236–244
Zhang Y, James M, Middleton FA, Davis RL (2005) Transcriptional analysis of multiple brain regions in Parkinson’s disease supports the involvement of specific protein processing, energy metabolism, and signaling pathways, and suggests novel disease mechanisms. Am J Med Genet B Neuropsychiatr Genet 137:5–16
Acknowledgments
This work was supported by the “Verein zur Durchführung neurowissenschaftliche Tagungen e.V” (2006) and the Hirnliga e.V. (2004). We wish to thank all the patients and the healthy volunteers who took part in this study and contributed to our findings. Special thanks to the study coordinator Monika Humann and the technicians, Miryame Hofmann and Carola Gagel, for their excellent work. All authors report no biomedical, financial, or potential conflicts of interest.
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Grünblatt, E., Zehetmayer, S., Jacob, C.P. et al. Pilot study: peripheral biomarkers for diagnosing sporadic Parkinson’s disease. J Neural Transm 117, 1387–1393 (2010). https://doi.org/10.1007/s00702-010-0509-1
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DOI: https://doi.org/10.1007/s00702-010-0509-1