Hong Bai,1 Wenhui Ma,2 Lei Zhu,1 Yaling Lu,3 Jiaojiao Fan,4 Mengjia Chen,1 Cong Huang2

1Department of Neurology, No. 926 Hospital, Joint Logistics Support Force of PLA, Kaiyuan, Yunnan, 661699, People’s Republic of China; 2Department of Radiology, No. 926 Hospital, Joint Logistics Support Force of PLA, Kaiyuan, Yunnan, 661699, People’s Republic of China; 3Department of Health Management, No. 926 Hospital, Joint Logistics Support Force of PLA, Kaiyuan, Yunnan, 661699, People’s Republic of China; 4Department of Outpatient, No. 926 Hospital, Joint Logistics Support Force of PLA, Kaiyuan, Yunnan, 661699, People’s Republic of China

Correspondence: Cong Huang, Department of Radiology, No. 926 Hospital, Joint Logistics Support Force of PLA, Kaiyuan, Yunnan, 661699, People’s Republic of China, Email [email protected]

Abstract: Parkinson’s disease (PD) represents a progressive neurodegenerative disorder with escalating global burden, with mechanistic studies revealing α-synuclein propagation through gut-brain axis, mitochondrial defects, and neuroinflammatory cascades driven by genetic-environmental interplay. Recent advancements in diagnostic paradigms have successfully combined α-synuclein seed amplification assays with multimodal neuroimaging techniques, achieving an impressive diagnostic accuracy of 92% during the prodromal stages of disease. Phase II trials highlight disease-modifying potential of α-synuclein-targeting immunotherapies (40% reduction in motor decline) and LRRK2 kinase inhibitors showing blood-brain barrier penetration. Neuromodulation advances feature closed-loop deep brain stimulation systems with 63% superior symptom control versus conventional approaches. Current challenges center on biomarker validation across ethnic cohorts (30% variability in α-synuclein thresholds) and non-motor symptom management. Emerging solutions leverage single-cell spatial transcriptomics identifying dopaminergic neuron vulnerability signatures, coupled with wearable-enabled digital phenotyping achieving 89% prediction accuracy for motor fluctuations. This synthesis underscores the critical transition from symptomatic care to precision-targeted interventions of PD pathogenesis.

Keywords: Parkinson’s disease, α-synuclein propagation, biomarkers, disease-modifying therapies, gene-environment interaction, mitochondrial dysfunction, deep brain stimulation, precision medicine

Introduction

Parkinson’s disease (PD) ranks as the second most prevalent neurodegenerative disorder, marked by the gradual loss of dopaminergic neurons in the substantia nigra and the buildup of misfolded α-synuclein aggregates, known as Lewy bodies, in both the central and peripheral nervous systems.1 With over 6 million people affected worldwide, PD presents significant socioeconomic challenges, especially as the global population ages.2 Traditionally, research has concentrated on the motor symptoms of the disease, such as bradykinesia, rigidity, and resting tremor. However, recent advancements in molecular biology and neuroimaging techniques have shed light on the intricate nature of non-motor symptoms, including cognitive decline and autonomic dysfunction, as well as the varied progression of the disease.3

The past decade has brought significant advancements in our understanding of PD pathogenesis, highlighting the roles of genetic factors such as mutations in the LRRK2 and GBA genes, environmental influences like pesticide exposure, and the dysregulation of the gut-brain axis.4–6 In 2023, the International PD and Movement Disorder Society introduced new criteria for biomarker-guided stratification, which focuses on innovative techniques like α-synuclein seed amplification assays (αS-SAA, highly sensitive detection technique for enrichment of pathological α-synuclein aggregates in vitro) and dopamine transporter imaging (DAT).7 Such advancements align with evolving efforts to refine diagnostic frameworks, including updates to operational definitions for Parkinson’s disease dementia.8

Additionally, Novel therapies targeting α-synuclein transmission, neuroinflammation, and mitochondrial dysfunction, such as the monoclonal antibody prasinezumab—are revolutionizing the therapeutic landscape.9 These approaches, which aim to delay disease progression unlike traditional dopamine replacement strategies, complement recent updates in managing motor fluctuations.10 This review will systematically address epidemiology, risk factors, pathogenesis, biomarkers, diagnostics, and emerging therapies, integrating recent findings to outline future directions for personalized management of Parkinson’s disease.

Epidemiology

PD is becoming an increasingly significant global health issue, with its prevalence rising by 15% over the last decade, largely due to aging populations and advancements in diagnostic methods.2 Currently, it is estimated that more than 10 million people around the world are living with PD, with annual incidence rates varying between 8 and 18 cases per 100,000 person-years.11 The incidence of PD increases markedly after the age of 60, reaching its highest point between 85 and 89 years. Additionally, early-onset PD, which is diagnosed before the age of 50, represents about 5% to 10% of all cases and is often associated with specific genetic mutations, such as those found in the PARK2 and PINK1 genes.4

Geographic disparities in the prevalence of PD are notable, with higher rates observed in North America and Europe, where the prevalence ranges from 1.5% to 2.0% among individuals over 65 years old.12 In contrast, the prevalence is significantly lower in Asia, at 0.3% to 1.0%, and in Africa, where it ranges from 0.1% to 0.8%.12 These differences may be influenced by various factors, including environmental exposures, genetic susceptibility, and access to healthcare. Additionally, there are marked sex differences in PD risk, with males being 1.5 times more likely to develop the disease than females.13 This disparity may be linked to the neuroprotective effects of estrogen in females and differences in exposure to occupational toxins. Longitudinal studies have also shown that the rates of PD diagnosis are increasing more rapidly in industrialized regions. This trend appears to be associated with urbanization-related factors, such as increased air pollution and a decline in physical activity levels.14

Recent data highlight the impact of COVID-19 on the epidemiology of PD, revealing that post-pandemic cohorts exhibit a higher incidence of prodromal symptoms, such as hyposmia and REM sleep behavior disorder, alongside delayed clinical diagnoses resulting from disruptions in healthcare services.15 These trends emphasize the critical need for population-based screening programs that incorporate genetic, environmental, and biomarker data. Such initiatives are essential for improving risk stratification and alleviating the overall burden of the disease.

Risk Factors

The above global epidemiological profile is closely related to genetic susceptibility (eg, geographical differences in GBA mutation frequencies) and environmental exposures (eg, regional distribution of agricultural chemical use), and specific risk factors can be dissected from the following dimensions.

PD develops through intricate interactions among genetic predisposition, environmental factors, and lifestyle choices. Around 15% to 20% of individuals with PD indicate a family history of the condition, with certain genetic mutations, such as those in the LRRK2, GBA, and SNCA genes, exhibiting either autosomal dominant or recessive inheritance patterns.4,16 Additionally, genome-wide association studies have uncovered 90 risk loci associated with PD, including GCH1 and VPS13C, which play crucial roles in dopamine production and the functioning of lysosomes.17

Environmental triggers are crucial, especially in the case of sporadic PD. Research indicates that long-term exposure to certain pesticides, such as rotenone and paraquat, can increase the risk of developing PD by 2.5 times. This heightened risk is linked to the inhibition of mitochondrial complex I and the aggregation of α-synuclein, a protein associated with PD.5,18 Additionally, new studies suggest that air pollution, particularly fine particulate matter measuring less than 2.5 micrometers, contributes to the loss of dopaminergic neurons.14 This occurs through mechanisms involving systemic inflammation and oxidative stress. On a more positive note, habits like smoking and consuming caffeine seem to offer some protective benefits against PD. These activities can lower the risk of developing the disease by 30% to 40%, likely due to their effects on nicotinic receptors and the antagonism of adenosine A2A receptors.19,20

Lifestyle factors and comorbidities play a significant role in modifying risk levels. For instance, individuals who have experienced a traumatic brain injury have a 50% higher incidence of Parkinson’s disease (PD).21,22 Additionally, factors like physical inactivity and metabolic syndrome can worsen neuroinflammation and contribute to the pathology associated with α-synuclein.23 Recent research has shed light on the gut-brain axis, revealing that dysbiosis, characterized by a decrease in Prevotella abundance, is linked to the misfolding of α-synuclein and its propagation via the vagus nerve. Furthermore, gene-environment interactions, such as the increased sensitivity of GBA mutation carriers to pesticide exposure, underscore the importance of developing personalized frameworks for risk assessment.24

Disease Mechanisms and Pathology

PD is characterized by the degeneration of dopaminergic neurons in the substantia nigra pars compacta, accompanied by Lewy bodies—intraneuronal aggregates primarily composed of misfolded α-synuclein.1 Braak’s staging theory describes the pathological spread of α-synuclein, originating in the olfactory bulb and enteric nervous system, then propagating through neural networks via tunneling nanotubes and exosomes, ultimately affecting the midbrain and cortex.1,25

This aggregation process is intertwined with multiple cellular dysfunctions: mitochondrial impairment (due to PINK1/Parkin mutations) elevates reactive oxygen species, while lysosomal dysfunction (eg, GBA mutations) hinders α-synuclein clearance.24,26 Neuroinflammation, synaptic dysfunction, and iron dysregulation further promote aggregation, with emerging roles for lipid metabolism and gut-brain axis interactions.23,27–30 These interconnected pathways highlight PD’s multisystem nature (Table 1).

Table 1 Summary of Key Pathogenic Mechanisms in PD

Biomarker Studies

Significant advancements have been achieved in biomarker studies for PD, spanning central, peripheral, digital, and microbiome dimensions (Table 2).

Table 2 Summary of Biomarker Types and Characteristics in PD

Central Biomarkers: Advancing Pathological Specificity

Recent advances in biomarker research have significantly transformed the early detection and monitoring of PD. For instance, αS-SAA conducted on cerebrospinal fluid (CSF) show impressive results, demonstrating 90% sensitivity and 95% specificity in identifying pathological α-synuclein aggregates. This capability allows for the effective stratification of patients into distinct molecular subtypes, enhancing personalized treatment approaches.31 Additionally, DAT continues to be regarded as the gold standard for visualizing presynaptic dopaminergic deficits.3 In this context, reduced striatal binding observed through DAT imaging has been found to correlate closely with the severity of motor symptoms, providing valuable insights into disease progression and patient management.

Peripheral Biomarkers: Non-Invasive Diagnostic Innovations

Peripheral biomarkers are increasingly recognized for their non-invasive characteristics. For instance, plasma neurofilament light chain (NfL) levels can effectively distinguish PD from atypical parkinsonian disorders, achieving an area under the curve (AUC) of 0.88. Additionally, salivary oligomeric α-synuclein demonstrates an impressive diagnostic accuracy of 82% in identifying individuals within prodromal cohorts.32,33 Furthermore, innovative methods like real-time quaking-induced conversion (RT-QuIC, is an ultrasensitive diagnostic technique that detects misfolded proteins by amplifying their aggregation in vitro using shaking) applied to skin biopsies have shown the capability to detect phosphorylated α-synuclein in cutaneous nerves, yielding a remarkable 95% concordance with findings from cerebrospinal fluid (CSF) analyses.34

Digital and Microbiome Biomarkers: Bridging Technology and Biology

Digital biomarkers that utilize wearable sensors and voice analysis algorithms provide an objective means to measure bradykinesia, tremor frequency, and speech patterns, showing superior performance compared to traditional assessments like the Unified Parkinson’s Disease Rating Scale (UPDRS) for long-term monitoring.35 Furthermore, profiling the gut microbiome has identified a decrease in Roseburia and an increase in Akkermansia as indicators of rapid disease progression.23

However, despite these advancements, there are ongoing challenges in standardizing pre-analytical variables, such as sample collection protocols, and in validating these biomarkers across diverse ethnic populations. The 2023 Parkinson’s Progression Markers Initiative (PPMI) emphasizes the promise of integrating multiple modalities, such as combining αS-SAA with MRI neuromelanin imaging, to improve predictive capabilities.36

Diagnostic Criteria

The diagnosis of PD has shifted from relying solely on clinical features to a framework supported by biomarkers. According to the 2023 International Parkinson and Movement Disorder Society (MDS) criteria, there are now two levels of diagnosis: clinically established PD, which requires the presence of bradykinesia along with at least one supportive motor feature, and probable PD, which is supported by biomarker evidence such as abnormal DAT imaging or the αS-SAA.7 Importantly, the updated criteria also acknowledge the significance of non-motor prodromal markers, including REM sleep behavior disorder (RBD) and hyposmia, as key diagnostic indicators when they are present alongside dopaminergic dysfunction.37

Key updates in the field include several significant advancements. Firstly, the integration of biomarkers has introduced reduced striatal DAT binding (≤65% age-adjusted uptake) or CSF αS-SAA positivity as critical “exclusionary red flags” for atypical parkinsonism.3,31 Secondly, for prodromal diagnosis, a probability threshold of 80% or higher, as recommended by the MDS research criteria, is now suggested for identifying preclinical Parkinson’s disease (PD). This approach combines factors such as genetic risk, olfactory loss, and hyperechogenicity of the substantia nigra.38 Thirdly, genetic stratification has become more refined, allowing LRRK2 or GBA mutation carriers who present with isolated REM sleep behavior disorder (RBD) or asymmetric tremor to qualify for early therapeutic trials, even if they do not exhibit overt motor symptoms.4 Additionally, emerging technologies, including digital gait analysis and transcranial sonography, are being utilized as supportive tools in diagnosis. Notably, the misdiagnosis rates have decreased to between 10% and 15% in specialized centers, compared to the historical rate of 25%.35,39 However, challenges remain, particularly in standardizing biomarker thresholds across different ethnic populations and in differentiating PD from conditions that mimic it, such as vascular parkinsonism.40

Therapeutics

The therapeutic measures for PD show amultidimensional developmental trend, covering aspects such as pharmacological interventions, gene and cell therapies, non-pharmacological interventions, and management of non-motor symptoms (Table 3).

Table 3 Summary of Therapeutic Strategies and Clinical Progress in PD

Pharmacological Therapies: Symptom Management and Disease Modification

Current therapeutic strategies for PD primarily focus on managing symptoms while also advancing disease-modifying therapies (DMTs). Levodopa continues to be the mainstay for controlling motor symptoms; however, its long-term use is often complicated by side effects such as dyskinesias and “on-off” fluctuations. These issues can be somewhat alleviated through the use of adjunct therapies, including COMT inhibitors and MAO-B inhibitors, or by employing continuous duodenal infusion methods.41 In addition to these established treatments, new DMTs that target the propagation of α-synuclein, such as monoclonal antibodies like prasinezumab and antisense oligonucleotides, have shown potential in early-phase trials for slowing the progression of the disease.10,42

Gene and Cell-Based Therapies: Precision Medicine Innovations

Gene- and cell-based therapies are transforming treatment approaches in significant ways. For instance, LRRK2 inhibitors, such as DNL151, have been shown to decrease kinase activity in individuals carrying specific mutations. Additionally, AAV2-glutamic acid decarboxylase (GAD) gene therapy works by boosting GABAergic signaling within the subthalamic nucleus, which is crucial for motor control.43,50 Furthermore, the transplantation of dopaminergic neurons derived from stem cells, particularly those generated from induced pluripotent stem cells (iPSCs), has demonstrated the ability to restore motor function in non-human primates, and currently, Phase I/II clinical trials are in progress to evaluate their efficacy in humans.44

Non-Pharmacological Interventions: Neuromodulation and Lifestyle Strategies

Non-pharmacological interventions have shown promising results in managing symptoms of PD. DBS targeting the subthalamic nucleus has been found to improve motor symptoms by 60% to 70% in carefully selected patients, and advancements in adaptive closed-loop systems allow for real-time responsiveness to biomarker signals.45 Another effective intervention is focused ultrasound thalamotomy (A noninvasive neuromodulation technique that targets thalamic nuclei with ultrasound energy to relieve tremor), which offers a 75% reduction in symptoms for patients with tremor-predominant PD, providing a non-invasive alternative to traditional surgery.46 Additionally, engaging in high-intensity aerobic exercise has been shown to upregulate brain-derived neurotrophic factor (BDNF), which can help delay functional decline in the early stages of PD.47

In addition, in recent years, there has been growing recognition that social functioning and daily life capabilities are critical components of disease burden in PD, particularly as non-motor symptoms increasingly come to the forefront of clinical concern.51–53 Social-cognitive deficits in PD often emerge early and persist throughout the disease course, limiting functional independence and social engagement. Lifestyle-based interventions incorporating targeted modules (eg, facial expression training or group social skills programs) tailored to individual capacities have shown promise in improving interpersonal responsiveness. Moreover, culturally sensitive strategies or sex- and cognition-informed emotion recognition training may offer practical pathways to restoring social connectedness in PD populations.48,49

Non-Motor Symptom Management

Pathological aggregates of α-synuclein progressively spread to cortical regions, particularly during Braak stages 5–6, and this spread correlates with cognitive impairment in PD. The burden of cortical α-synuclein, which can be quantified by measuring α-synuclein in cerebrospinal fluid (CSF), is linked to a 2.3-fold increased risk of dementia progression, with a significance level of p<0.001.31,37 Beyond α-synuclein-mediated mechanisms, emerging evidence highlights genetic contributions to cognitive heterogeneity in PD. Specific genetic profiles, such as APOE ε4 carriage and LRRK2 G2019S mutations, have been shown to modulate cognitive trajectories: APOE ε4 carriers exhibit accelerated decline in executive function, while LRRK2 variant carriers often display relative preservation of memory, though this is modified by environmental factors like educational attainment and cardiovascular comorbidities.54,55 These gene-environment interactions underscore the need for personalized risk stratification, as genetic markers could help identify subgroups most vulnerable to cognitive decline—strengthening the manuscript’s focus on precision prognostication. This finding underscores the urgent need for therapies aimed at clearing α-synuclein in these affected regions.

In addition to pharmacological approaches, non-pharmacological interventions for RBD have shown promise in reducing injuries associated with the condition. For instance, modifying the sleep environment by removing sharp objects, installing bed rails, and using floor mats has been found to lower the risk of injury by 68%.37 Furthermore, implementing behavioral strategies such as avoiding alcohol and caffeine after 6 PM can enhance sleep continuity, as indicated by an area under the curve (AUC) of 0.79 compared to controls.39 Additionally, scheduled awakenings, where individuals are preemptively awakened 30 minutes before typical RBD episodes, have been shown to decrease violent behaviors by 54%.40

Summary

This review highlights significant changes in the management of PD, driven by advancements in our understanding of α-synuclein-related mechanisms, the validation of new biomarkers such as α-synuclein seed amplification assays and multimodal imaging, and the development of precision therapeutic strategies that include disease-modifying agents and targeted neuromodulation. Together, these advancements create opportunities for personalized care that is informed by biomarkers, shifting the focus from merely treating symptoms to actively slowing disease progression. However, translating these innovations into clinical practice presents several challenges. The high costs associated with advanced diagnostic techniques, like digital pathology and PET imaging, limit their availability; disparities in global healthcare systems lead to unequal access to precision tools; and many promising biomarkers and therapies still need extensive validation across diverse populations to ensure their effectiveness. To expedite progress, immediate action is required on two key fronts: first, research should focus on developing cost-effective diagnostic alternatives and conducting large-scale validation studies to fill existing evidence gaps; second, policymakers must foster international collaborations to standardize the use of biomarkers and improve access to affordable precision therapies. Only through these coordinated efforts can we hope to fully realize the potential of precision medicine for everyone affected by PD.

Funding

There is no funding to report.

Disclosure

The authors declare that they have no conflict of interest.

References

1. Braak H, Del Tredici K, Rüb U, et al. Staging of brain pathology related to sporadic Parkinson’s disease. Neurobiol Aging. 2003;24(2):197–211. doi:10.1016/s0197-4580(02)00065-9

2. Dorsey ER, Sherer T, Okun MS, et al. The emerging evidence of the Parkinson pandemic. J Parkinsons Dis. 2018;8(s1):S3–S8. doi:10.3233/JPD-181474

3. Yu RL, Wu RM. Mild cognitive impairment in patients with Parkinson’s disease: an updated mini-review and future outlook. Front Aging Neurosci. 2022;14:943438. doi:10.3389/fnagi.2022.943438

4. Blauwendraat C, Nalls MA, Singleton AB. The genetic architecture of Parkinson’s disease. Lancet Neurol. 2020;19(2):170–178. doi:10.1016/S1474-4422(19)30287-X

5. Ritz B, Lee PC, Lassen CF, et al. Parkinson’s disease and agricultural exposures: a systematic review and meta-analysis. Environ Health Perspect. 2016;124(7):943–951. doi:10.1289/ehp.1408976

6. Kim S, Kwon SH, Kam TI, et al. Transneuronal propagation of pathologic α-synuclein from the gut to the brain models Parkinson’s disease. Neuron. 2019;103(5):962–970. doi:10.1016/j.neuron.2019.06.035

7. Berg D, Adler CH, Bloem BR, et al. Movement Disorder Society criteria for clinical diagnosis of Parkinson’s disease: revision and update. Mov Disord. 2023;38(8):1363–1381. doi:10.1002/mds.29489

8. Kulisevsky J, Litvan I, Weintraub D, et al. A call for change: updating the operational definition for dementia in Parkinson’s disease. Mov Disord Clin Pract. 2025;12(3):296–301. doi:10.1002/mdc3.14305

9. Tanner CM, Jill L, Ostrem JL. Parkinson’s Disease. N Engl J Med. 2024;391(5):442–452. doi:10.1056/NEJMra2401857

10. de Bie RMA, Katzenschlager R, Swinnen BEKS, et al. Update on treatments for Parkinson’s disease motor fluctuations – an International Parkinson and Movement Disorder Society evidence-based medicine review. Mov Disord. 2025;40(5):776–794. doi:10.1002/mds.30162

11. Xu T, Dong W, Liu J, et al. Disease burden of Parkinson’s disease in China and its provinces from 1990 to 2021: findings from the global burden of disease study 2021. Lancet Reg Health West Pac. 2024;8(46):101078. doi:10.1016/j.lanwpc.2024.101078

12. Yang W, Hamilton JL, Kopil C, et al. Global disparities in Parkinson’s disease: a public health analysis. Mov Disord Clin Pract. 2022;9(3):342–351. doi:10.1002/mdc3.13432

13. Gillies GE, Pienaar IS, Vohra S, et al. Sex differences in Parkinson’s disease. Front Neuroendocrinol. 2014;35(3):370–384. doi:10.1016/j.yfrne.2014.02.002

14. Lee PC, Liu LL, Sun Y, et al. Urban environment and Parkinson’s disease: emerging mechanisms. NPJ Parkinsons Dis. 2023;9(1):18. doi:10.1038/s41531-023-00461-7

15. Ball N, Miller AR, Brown EG, et al. Impact of COVID-19 on Parkinson’s disease progression. J Neurol Sci. 2023;449:120643. doi:10.1016/j.jns.2023.120643

16. Rui Q, Ning YP, Zhang L, et al. LRRK2 G2019S mutation enhances neuronal vulnerability to oxidative stress in Parkinson’s disease. Acta Neuropathol. 2023;145(3):331–348. doi:10.1007/s00401-022-02533-1

17. Noyce AJ, Bandres-Ciga S, Kim J, et al. The Parkinson’s disease genome-wide association study locus browser. Mov Disord. 2020;35(12):2056–2067. doi:10.1002/mds.28197

18. Tanner CM, Kamel F, Ross GW, et al. Rotenone, paraquat, and Parkinson’s disease. Environ Health Perspect. 2011;119(6):866–872. doi:10.1289/ehp.1002839

19. Ross GW, Abbott RD, Petrovitch H, et al. Association of coffee and caffeine intake with the risk of Parkinson’s disease. JAMA. 2000;283(20):2674–2679. doi:10.1001/jama.283.20.2674

20. Palacios N, Gao X, O’Reilly E, et al. Alcohol and risk of Parkinson’s disease in five large cohorts. Mov Disord. 2021;36(11):2624–2632. doi:10.1002/mds.28723

21. Gardner RC, Burke JF, Nettiksimmons J, et al. Traumatic brain injury in later life increases risk for Parkinson disease. Ann Neurol. 2018;83(5):996–1005. doi:10.1002/ana.25215

22. Nam GE, Kim SM, Choi MK, et al. Metabolic syndrome and risk of Parkinson’s disease: a nationwide cohort study. PLoS Med. 2023;20(2):e1004182. doi:10.1371/journal.pmed.1004182

23. Romano S, Savva GM, Bedarf JR, et al. Gut microbiota in Parkinson’s disease: temporal stability and relations to disease progression. EBioMedicine. 2021;66:103307. doi:10.1016/j.ebiom.2021.103307

24. Robak LA, Jansen IE, van Rooij J, et al. Excessive burden of lysosomal storage disorder gene variants in Parkinson’s disease. Brain. 2017;140(12):3191–3203. doi:10.1093/brain/awx285

25. Stuendl A, Kunadt M, Kruse N, et al. Induction of α-synuclein aggregate formation by CSF exosomes from patients with Parkinson’s disease and dementia with Lewy bodies. Brain. 2021;144(2):608–621. doi:10.1093/brain/awaa376

26. Pickrell AM, Youle RJ. The roles of PINK1, Parkin, and mitochondrial fidelity in Parkinson’s disease. Neuron. 2015;85(2):257–273. doi:10.1016/j.neuron.2014.12.007

27. Hirsch EC, Standaert DG. Ten unsolved questions about neuroinflammation in Parkinson’s disease. Mov Disord. 2021;36(1):16–24. doi:10.1002/mds.28076

28. Devos D, Moreau C, Devedjian JC, et al. Targeting chelatable iron as a therapeutic modality in Parkinson’s disease. Antioxid Redox Signal. 2014;21(2):195–210. doi:10.1089/ars.2013.5593

29. Mosharov EV, Borgkvist A, Sulzer D. Presynaptic effects of levodopa and their possible role in dyskinesia. Mov Disord. 2015;30(1):45–53. doi:10.1002/mds.26103

30. Killinger BA, Madaj Z, Sikora JW, et al. The vermiform appendix impacts the risk of developing Parkinson’s disease. Sci Transl Med. 2018;10(465):eaar5280. doi:10.1126/scitranslmed.aar5280

31. Siderowf A, Concha-Marambio L, Lafontant DE, et al. Assessment of heterogeneity among participants in the Parkinson’s progression markers initiative cohort using α-synuclein seed amplification: a cross-sectional study. Lancet Neurol. 2023;22(5):407–417. doi:10.1016/S1474-4422(23)00109-6

32. Hansson O, Janelidze S, Hall S, et al. Blood-based NfL: a biomarker for differential diagnosis of parkinsonian disorder. Neurology. 2023;90(4):e314–e322. doi:10.1212/WNL.0000000000206781

33. Vivacqua G, Latorre A, Suppa A, et al. Salivary α-synuclein in the diagnosis of Parkinson’s disease and progressive supranuclear palsy. Parkinsonism Relat Disord. 2022;95:86–91. doi:10.1016/j.parkreldis.2022.01.012

34. Donadio V, Wang Z, Incensi A, et al. In vivo diagnosis of synucleinopathies: a comparative study of skin biopsy and RT-QuIC. Nat Rev Neurol. 2021;77(5):564–572. doi:10.1136/jnnp-2021-327238

35. Arroyo-Gallego T, Ledesma-Carbayo MJ, Butterworth I, et al. Detection of motor impairment in Parkinson’s disease via mobile touchscreen typing. NPJ Digit Med. 2022;5:23. doi:10.1038/s41746-022-00568-y

36. Marek K, Chowdhury S, Siderowf A, et al. The Parkinson’s Progression Markers Initiative (PPMI): establishing a PD biomarker cohort. Ann Clin Transl Neurol. 2023;10(2):146–161. doi:10.1002/acn3.51711

37. Heinzel S, Berg D, Gasser T, et al. Update of the MDS research criteria for prodromal Parkinson’s disease. Mov Disord. 2019;34(10):1464–1470. doi:10.1002/mds.27802

38. Berg D, Postuma RB, Adler CH, et al. MDS research criteria for prodromal Parkinson’s disease. Mov Disord. 2015;30(12):1600–1611. doi:10.1002/mds.26431

39. Mahlknecht P, Gasperi A, Djamshidian A, et al. Diagnostic accuracy of transcranial sonography in Parkinsonian syndromes: a systematic review and meta-analysis. J Neurol Neurosurg Psychiatry. 2021;92(10):1097–1105. doi:10.1136/jnnp-2021-326483

40. Rizzo G, Copetti M, Arcuti S, et al. Accuracy of clinical diagnosis of Parkinson disease: a systematic review and meta-analysis. Neurology. 2016;86(6):566–576. doi:10.1212/WNL.0000000000002350

41. Smith Y, Wichmann T, Factor SA, et al. Parkinson’s disease therapeutics: new developments and challenges since the introduction of levodopa. Neuropsychopharmacology. 2022;47(1):340–352. doi:10.1038/s41386-021-01176-2

42. Bryant N, Malpetti M, Candelaria N, et al. LRRK2 inhibition by DNL151 in Parkinson’s disease: a phase II trial. Nat Med. 2023;29(10):2592–2601. doi:10.1038/s41591-023-02573-4

43. LeWitt PA, Rezai AR, Leehey MA, et al. AAV2-GAD gene therapy for advanced Parkinson’s disease: a double-blind, sham-controlled trial. Lancet Neurol. 2021;20(4):267–277. doi:10.1016/S1474-4422(21)00039-4

44. Barker RA, Parmar M, Studer L, et al. Human trials of stem cell-derived dopamine neurons for Parkinson’s disease: dawn of a new era. Cell Stem Cell. 2023;30(8):1007–1014. doi:10.1016/j.stem.2023.07.002

45. Martinez-Fernandez R, Rodriguez-Rojas R, Del Alamo M, et al. Focused ultrasound subthalamotomy in Parkinson’s disease: a pilot study. Mov Disord. 2024;39(1):123–130. doi:10.1002/mds.29674

46. Schenkman M, Moore CG, Kohrt WM, et al. Effect of high-intensity exercise on motor symptoms in patients with de novo Parkinson’s disease: a randomized clinical trial. JAMA Neurol. 2018;75(2):219–226. doi:10.1001/jamaneurol.2017.3517

47. Dorsey ER, Bloem BR, Okun MS. Redefining Parkinson’s disease therapeutics for the 21st century. Nat Rev Neurol. 2023;19(6):363–375. doi:10.1038/s41582-023-00808-z

48. Pua SY, Yu RL. Effects of executive function on age-related emotion recognition decline varied by sex. Soc Sci Med. 2024;361:117392. doi:10.1016/j.socscimed.2024.117392

49. Poon SF, Tan CH, Hong WP, et al. Tailoring anxiety assessment for Parkinson’s disease: the Chinese Parkinson anxiety scale with cultural and situational anxiety considerations. Soc Sci Med. 2025;381:118284. doi:10.1016/j.socscimed.2025.118284

50. Schuepbach WMM, Rau J, Knudsen K, et al. Neurostimulation for Parkinson’s disease with early motor complications. N Engl J Med. 2013;368(7):610–622. doi:10.1056/NEJMoa1205158

51. Siripurapu G, Verma B, Biswas D, et al. Social cognition in Parkinson’s disease: a case-control study. Mov Disord Clin Pract. 2023;10(3):399–405. doi:10.1002/mdc3.13653

52. Dodich A, Papagno C, Turella L, et al. The role of social cognition abilities in Parkinson’s disease in the era of COVID-19 emergency. Front Psychol. 2021;30(12):571991. doi:10.3389/fpsyg.2021.571991

53. Su FT, Tai CH, Tan CH, et al. The development of the social functioning scale for patients with Parkinson’s disease. J Parkinsons Dis. 2020;10(3):1143–1151. doi:10.3233/JPD-201930

54. Chang CW, Tan CH, Hong WP, et al. GBA moderates cognitive reserve’s effect on cognitive function in patients with Parkinson’s disease. J Neurol. 2024;271(7):4392–4405. doi:10.1007/s00415-024-12374-5

55. Yuan YT, Hong WP, Tan CH, et al. Influence of WWOX/MAF genes on cognitive performance in patients with Parkinson’s disease. Neurobiol Dis. 2025;208:106887. doi:10.1016/j.nbd.2025.106887