Toggle Main Menu Toggle Search

Open Access padlockePrints

Disease modification in advanced Parkinson’s disease: a review and roadmap for paving the way for next-generation interventions

Lookup NU author(s): Professor Tiago OuteiroORCiD

Downloads


Licence

This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© The Author(s) 2026.Parkinson’s disease (PD) exhibits highly heterogeneous clinical trajectories, yet “advanced PD” (aPD) lacks a standardized definition. Current reliance on clinical milestones (e.g., motor fluctuations, cognitive decline) is limited by non-linear progression and the absence of objective measures. Although biomarkers like aggregated α-synuclein, MRI, and PET are under investigation, their correlation with clinical progression remains modest. Robust, reproducible endpoints are urgently needed to evaluate disease-modifying therapies across diverse phenotypes, accounting for genetic background, age of onset, co-pathologies, and motor/autonomic/cognitive domains. Given this complexity, single-target interventions are likely insufficient. We propose a multi-domain therapeutic framework for aPD that integrates: (A) simultaneous targeting of key pathological cascades, including α-synuclein aggregation, mitochondrial dysfunction, oxidative stress, proteostasis imbalance, neuroinflammation, and the gut–brain axis; (B) biology-driven patient stratification using emerging biomarkers to match subgroups with targeted interventions; and (C) systematic management of comorbidities and lifestyle factors, such as cardiovascular health and exercise, to enhance neuroresilience. Finally, advancing aPD care requires addressing systemic determinants, including global healthcare inequities, and prioritizing caregiver well-being. Mechanistically informed, patient-centered strategies that combine multi-target therapies with precision stratification and holistic support will be essential to modify disease progression and improve long-term outcomes.


Publication metadata

Author(s): Groppa S, Fasano A, Urso D, Yang X, Popescu B, Klivenyi P, van Laar T, Jost W, Garcia-Ruiz PJ, Bhidayasiri R, Outeiro TF

Publication type: Review

Publication status: Published

Journal: Journal of Neural Transmission

Year: 2026

Pages: epub ahead of print

Online publication date: 19/06/2026

Acceptance date: 08/06/2026

ISSN (print): 0300-9564

ISSN (electronic): 1435-1463

Publisher: Springer

URL: https://doi.org/10.1007/s00702-026-03208-x

DOI: 10.1007/s00702-026-03208-x

Data Access Statement: No datasets were generated or analysed during the current study.


Share