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Biomarkers of Parkinson's disease in perspective of early diagnosis and translation of neurotrophic therapies

Raimo K. Tuominen, Juho‐Matti Renko

2024Basic & Clinical Pharmacology & Toxicology15 citationsDOIOpen Access PDF

Abstract

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by progressive loss of dopamine neurons and aberrant deposits of alpha-synuclein (α-syn) in the brain. The symptomatic treatment is started after the onset of motor manifestations in a late stage of the disease. Preclinical studies with neurotrophic factors (NTFs) show promising results of disease-modifying neuroprotective or even neurorestorative effects. Four NTFs have entered phase I-II clinical trials with inconclusive outcomes. This is not surprising because the preclinical evidence is from acute early-stage disease models, but the clinical trials included advanced PD patients. To conclude the value of NTF therapies, clinical studies should be performed in early-stage patients with prodromal symptoms, that is, before motor manifestations. In this review, we summarize currently available diagnostic and prognostic biomarkers that could help identify at-risk patients benefiting from NTF therapies. Focus is on biochemical and imaging biomarkers, but also other modalities are discussed. Neuroimaging is the most important diagnostic tool today, but α-syn imaging is not yet viable. Modern techniques allow measuring various forms of α-syn in cerebrospinal fluid, blood, saliva, and skin. Digital biomarkers and artificial intelligence offer new means for early diagnosis and longitudinal follow-up of degenerative brain diseases.

Topics & Concepts

MedicineDiseaseNeuroimagingParkinson's diseaseClinical trialNeuroprotectionProdromal StageNeurotrophic factorsStage (stratigraphy)BioinformaticsIntensive care medicineNeuroscienceOncologyPathologyInternal medicinePsychiatryPsychologyCognitive impairmentReceptorPaleontologyBiologyParkinson's Disease Mechanisms and TreatmentsNeurological disorders and treatmentsNeuroscience and Neural Engineering
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