The heterogeneity of Parkinson’s disease

Abstract

The heterogeneity of Parkinson’s disease (PD), i.e. the various clinical phenotypes, pathological findings, genetic predispositions and probably also the various implicated pathophysiological pathways pose a major challenge for future research projects and therapeutic trail design. We outline several pathophysiological concepts, pathways and mechanisms, including the presumed roles of α-synuclein misfolding and aggregation, Lewy bodies, oxidative stress, iron and melanin, deficient autophagy processes, insulin and incretin signaling, T-cell autoimmunity, the gut–brain axis and the evidence that microbial (viral) agents may induce molecular hallmarks of neurodegeneration. The hypothesis is discussed, whether PD might indeed be triggered by exogenous (infectious) agents in susceptible individuals upon entry via the olfactory bulb (brain first) or the gut (body-first), which would support the idea that disease mechanisms may change over time. The unresolved heterogeneity of PD may have contributed to the failure of past clinical trials, which attempted to slow the course of PD. We thus conclude that PD patients need personalized therapeutic approaches tailored to specific phenomenological and etiologic subtypes of disease.

3D-CAM: a novel context-aware feature extraction framework for neurological disease classification

“…Recently, several studies have shown promising results in the diagnosis of PD and MSA using machine learning methods, such as Chen et al (2017), Pang et al (2020), Bu et al (2023), and Chen et al (2023). Among them, the dataset volume used by Pang et al (2020) is comparable to our research, making it highly relevant.…”

“…This poses a great challenge for doctors in their diagnosis ( Song et al, 2007 ; Antonini, 2010 ). Parkinson’s disease has a high degree of heterogeneity, with different clinical subtypes, which makes diagnosis difficult ( Wullner et al, 2023 ). According to statistics, the misdiagnosis rate of early-stage Parkinson’s disease can be as high as 20–30% ( Poewe and Wenning, 2002 ).…”

“…Among them, machine learning-based methods for extracting medical image features have shown promising results. For example, Chen et al (2017,2023) explored the differences in brain functional connectivity patterns between patients with PD and MSA, provided a diagnostic tool for PD and MSA using machine learning methods. Pang et al (2020) extracted radiomics features on Susceptibility-weighted-imaging using machine learning methods for differential diagnosis of PD and MSA.…”

Common genetic risk for Parkinson's disease and dysfunction of the endo-lysosomal system

“…Although PD is characterized by these pathological hallmarks, there is a remarkable heterogeneity in the aetiology and pathogenesis of the disorder [ 5 , 9 ]. The hetereogeneity can manifest as variation in age of onset, disease progression, clinical phenotypes, cellular pathways, neurotransmitter systems, epigenetics and underlying genetic risks [ 10 , 11 ].…”

In vitro modulation of mTOR and mGlur5 influence α-synuclein accumulation.

“…Indeed, a-synuclein is normally a presynaptic cytosolic monomer but can undergo oligomerization and brillation contributing to synucleopathies (Stefanis 2012;Bendor et al 2013;Goedert, 2001;Gallardo et al, 2020). Competing theories suggest that a-syn may rst begin to misfold and aggregate in either the periphery and/or in the anterior olfactory region of the brain before eventually reaching the midbrain dopaminergic system (Braak et al, 2003;Wüllner et al, 2023;Borghammer et al, 2022). Aggregation and spread of a-synuclein can be affected by several missense mutations, including A30P, E46K, H50Q and A53T (Burré et al, 2018), with the A53T mutation being particularly involved in the acceleration of brilization (Tofaris & Spillantini, 2007;Teravskis et al, 2018).…”