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Parkinson disease (PD) is a progressive neurodegenerative disease that affects peripheral organs as well as the central nervous system and involves a fundamental role of neuroinflammation in its pathophysiology. Neurohistological and neuroimaging studies support the presence of ongoing and end-stage neuroinflammatory processes in PD. Moreover, numerous studies of peripheral blood and cerebrospinal fluid from patients with PD suggest alterations in markers of inflammation and immune cell populations that could initiate or exacerbate neuroinflammation and perpetuate the neurodegenerative process. A number of disease genes and risk factors have been identified as modulators of immune function in PD and evidence is mounting for a role of viral or bacterial exposure, pesticides and alterations in gut microbiota in disease pathogenesis. This has led to the hypothesis that complex gene-by-environment interactions combine with an ageing immune system to create the ‘perfect storm’ that enables the development and progression of PD. We discuss the evidence for this hypothesis and opportunities to harness the emerging immunological knowledge from patients with PD to create better preclinical models with the long-term goal of enabling earlier identification of at-risk individuals to prevent, delay and more effectively treat the disease.This Review from Tansey and colleagues explores how an ageing immune system, host genetics and exposure to various environmental stressors combine to promote the development of Parkinson disease.

Evidence for a close bidirectional link between the brain and the gut has led to a paradigm shift in neurology, especially in the case of Parkinson disease (PD), in which gastrointestinal dysfunction is a prominent feature. Over the past decade, numerous high-quality preclinical and clinical publications have shed light on the highly complex relationship between the gut and the brain in PD, providing potential for the development of new biomarkers and therapeutics. With the advent of high-throughput sequencing, the role of the gut microbiome has been specifically highlighted. Here, we provide a critical review of the literature on the microbiome–gut–brain axis in PD and present perspectives that will be useful for clinical practice. We begin with an overview of the gut–brain axis in PD, including the potential roles and interrelationships of the vagus nerve, α-synuclein in the enteric nervous system, altered intestinal permeability and inflammation, and gut microbes and their metabolic activities. The sections that follow synthesize the proposed roles of gut-related factors in the development and progression of, in responses to PD treatment, and as therapeutic targets. Finally, we summarize current knowledge gaps and challenges and delineate future directions for the field.The prominence of gastrointestinal dysfunction among the non-motor features of Parkinson disease (PD) indicates a close bidirectional link between the brain and the gut. This Review discusses the proposed roles of gut-related factors in PD development, progression and treatment responses, and as therapeutic targets.

Parkinson disease (PD) is the second most common neurodegenerative disorder, affecting >1% of the population ≥65 years of age and with a prevalence set to double by 2030. In addition to the defining motor symptoms of PD, multiple non-motor symptoms occur; among them, cognitive impairment is common and can potentially occur at any disease stage. Cognitive decline is usually slow and insidious, but rapid in some cases. Recently, the focus has been on the early cognitive changes, where executive and visuospatial impairments are typical and can be accompanied by memory impairment, increasing the risk for early progression to dementia. Other risk factors for early progression to dementia include visual hallucinations, older age and biomarker changes such as cortical atrophy, as well as Alzheimer-type changes on functional imaging and in cerebrospinal fluid, and slowing and frequency variation on EEG. However, the mechanisms underlying cognitive decline in PD remain largely unclear. Cortical involvement of Lewy body and Alzheimer-type pathologies are key features, but multiple mechanisms are likely involved. Cholinesterase inhibition is the only high-level evidence-based treatment available, but other pharmacological and non-pharmacological strategies are being tested. Challenges include the identification of disease-modifying therapies as well as finding biomarkers to better predict cognitive decline and identify patients at high risk for early and rapid cognitive impairment. Cognitive impairment is common in patients with Parkinson disease and ranges in severity. This Primer reviews the epidemiology, pathophysiology, diagnosis and treatment of cognitive impairment in Parkinson disease and describes the effects on patient quality of life and the future outlook for the field.

In Parkinson disease (PD), pathological processes and neurodegeneration begin long before the cardinal motor symptoms develop and enable clinical diagnosis. In this prodromal phase, risk and prodromal markers can be used to identify individuals who are likely to develop PD, as in the recently updated International Parkinson and Movement Disorders Society research criteria for prodromal PD. However, increasing evidence suggests that clinical and prodromal PD are heterogeneous, and can be classified into subtypes with different clinical manifestations, pathomechanisms and patterns of spatial and temporal progression in the CNS and PNS. Genetic, pathological and imaging markers, as well as motor and non-motor symptoms, might define prodromal subtypes of PD. Moreover, concomitant pathology or other factors, including amyloid-β and tau pathology, age and environmental factors, can cause variability in prodromal PD. Patients with REM sleep behaviour disorder (RBD) exhibit distinct patterns of α-synuclein pathology propagation and might indicate a body-first subtype rather than a brain-first subtype. Identification of prodromal PD subtypes and a full understanding of variability at this stage of the disease is crucial for early and accurate diagnosis and for targeting of neuroprotective interventions to ensure efficacy.In this Review, Berg et al. summarize current understanding of prodromal Parkinson disease and consider the prodrome in the context of the clinical and pathological heterogeneity of the disease. They explore the possibility that prodromal Parkinson disease can be classified into subtypes.

Multiple lines of evidence indicate that immune system dysfunction has a role in Parkinson disease (PD); this evidence includes clinical and genetic associations between autoimmune disease and PD, impaired cellular and humoral immune responses in PD, imaging evidence of inflammatory cell activation and evidence of immune dysregulation in experimental models of PD. However, the mechanisms that link the immune system with PD remain unclear, and the temporal relationships of innate and adaptive immune responses with neurodegeneration are unknown. Despite these challenges, our current knowledge provides opportunities to develop immune-targeted therapeutic strategies for testing in PD, and clinical studies of some approaches are under way. In this Review, we provide an overview of the clinical observations, preclinical experiments and clinical studies that provide evidence for involvement of the immune system in PD and that help to define the nature of this association. We consider autoimmune mechanisms, central and peripheral inflammatory mechanisms and immunogenetic factors. We also discuss the use of this knowledge to develop immune-based therapeutic approaches, including immunotherapy that targets α-synuclein and the targeting of immune mediators such as inflammasomes. We also consider future research and clinical trials necessary to maximize the potential of targeting the immune system.In this Review, Tan et al. provide an overview of the clinical and preclinical evidence that immune system dysfunction is involved in Parkinson disease, and discuss how increasing knowledge of the underlying mechanisms is driving development of immune-based therapeutic approaches.

Parkinson’s disease (PD) may start in the gut and spread to the brain. To investigate the role of gut microbiome, we conducted a large-scale study, at high taxonomic resolution, using uniform standardized methods from start to end. We enrolled 490 PD and 234 control individuals, conducted deep shotgun sequencing of fecal DNA, followed by metagenome-wide association studies requiring significance by two methods (ANCOM-BC and MaAsLin2) to declare disease association, network analysis to identify polymicrobial clusters, and functional profiling. Here we show that over 30% of species, genes and pathways tested have altered abundances in PD, depicting a widespread dysbiosis. PD-associated species form polymicrobial clusters that grow or shrink together, and some compete. PD microbiome is disease permissive, evidenced by overabundance of pathogens and immunogenic components, dysregulated neuroactive signaling, preponderance of molecules that induce alpha-synuclein pathology, and over-production of toxicants; with the reduction in anti-inflammatory and neuroprotective factors limiting the capacity to recover. We validate, in human PD, findings that were observed in experimental models; reconcile and resolve human PD microbiome literature; and provide a broad foundation with a wealth of concrete testable hypotheses to discern the role of the gut microbiome in PD. Here, the authors perform large-scale high-resolution Parkinson’s disease metagenomics analyses, revealing widespread dysbiosis characterized by overabundance of pathogens, immunogens, toxicants, and curli, reduction in neuroprotective and antiinflammatory molecules, and dysregulated neuroactive signaling.

Estimates of the prevalence of Parkinson’s disease in North America have varied widely and many estimates are based on small numbers of cases and from small regional subpopulations. We sought to estimate the prevalence of Parkinson’s disease in North America by combining data from a multi-study sampling strategy in diverse geographic regions and/or data sources. Five separate cohort studies in California (2), Minnesota (1), Hawaii USA (1), and Ontario, Canada (1) estimated the prevalence of PD from health-care records (3), active ascertainment through facilities, large group, and neurology practices (1), and longitudinal follow-up of a population cohort (1). US Medicare program data provided complementary estimates for the corresponding regions. Using our age- and sex-specific meta-estimates from California, Minnesota, and Ontario and the US population structure from 2010, we estimate the overall prevalence of PD among those aged ≥45 years to be 572 per 100,000 (95% confidence interval 537–614) that there were 680,000 individuals in the US aged ≥45 years with PD in 2010 and that that number will rise to approximately 930,000 in 2020 and 1,238,000 in 2030 based on the US Census Bureau population projections. Regional variations in prevalence were also observed in both the project results and the Medicare-based calculations with which they were compared. The estimates generated by the Hawaiian study were lower across age categories. These estimates can guide health-care planning but should be considered minimum estimates. Some heterogeneity exists that remains to be understood.

There are currently no effective biomarkers for diagnosing Parkinson’s disease (PD) or tracking its progression. Here, we developed an artificial intelligence (AI) model to detect PD and track its progression from nocturnal breathing signals. The model was evaluated on a large dataset comprising 7,671 individuals, using data from several hospitals in the United States, as well as multiple public datasets. The AI model can detect PD with an area-under-the-curve of 0.90 and 0.85 on held-out and external test sets, respectively. The AI model can also estimate PD severity and progression in accordance with the Movement Disorder Society Unified Parkinson’s Disease Rating Scale ( R  = 0.94, P  = 3.6 × 10 –25 ). The AI model uses an attention layer that allows for interpreting its predictions with respect to sleep and electroencephalogram. Moreover, the model can assess PD in the home setting in a touchless manner, by extracting breathing from radio waves that bounce off a person’s body during sleep. Our study demonstrates the feasibility of objective, noninvasive, at-home assessment of PD, and also provides initial evidence that this AI model may be useful for risk assessment before clinical diagnosis. Using a neural network-based model, Parkinson’s disease can be diagnosed and its severity monitored based on breathing patterns while someone is asleep, with the potential for at-home touchless monitoring.

Parkinson disease (PD) is the fastest growing neurological disorder globally and poses substantial management challenges owing to progressive disability, emergence of levodopa-resistant symptoms, and treatment-related complications. In this Review, we examine the current state of research into PD therapies and outline future priorities for advancing our understanding and treatment of the disease. We identify two main research priorities for the coming years: first, slowing the progression of the disease through the integration of sensitive biomarkers and targeted biological therapies, and second, enhancing existing symptomatic treatments, encompassing surgical and infusion therapies, with the goal of postponing complications and improving long-term patient management. The path towards disease modification is impeded by the multifaceted pathophysiology and diverse mechanisms underlying PD. Ongoing studies are directed at α-synuclein aggregation, complemented by efforts to address specific pathways associated with the less common genetic forms of the disease. The success of these efforts relies on establishing robust end points, incorporating technology, and identifying reliable biomarkers for early diagnosis and continuous monitoring of disease progression. In the context of symptomatic treatment, the focus should shift towards refining existing approaches and fostering the development of novel therapeutic strategies that target levodopa-resistant symptoms and clinical manifestations that substantially impair quality of life.Parkinson disease (PD) poses substantial management challenges owing to progressive disability and emergence of levodopa-resistant symptoms and treatment-related complications. This Review examines the current state of research into symptomatic and disease-modifying PD therapies and outlines future priorities for advancing our understanding and treatment of the disease.

Misfolded alpha-synuclein (αSyn) aggregates are a hallmark event in Parkinson’s disease (PD) and other synucleinopathies. Recently, αSyn seed amplification assays (αSyn-SAAs) have shown promise as a test for biochemical diagnosis of synucleinopathies. αSyn-SAAs use the intrinsic self-replicative nature of misfolded αSyn aggregates (seeds) to multiply them in vitro. In these assays, αSyn seeds circulating in biological fluids are amplified by a cyclical process that includes aggregate fragmentation into smaller self-propagating seeds, followed by elongation at the expense of recombinant αSyn (rec-αSyn). Amplification of the seeds allows detection by fluorescent dyes specific for amyloids, such as thioflavin T. Several αSyn-SAA reports have been published in the past under the names ‘protein misfolding cyclic amplification’ (αSyn-PMCA) and ‘real-time quaking-induced conversion’. Here, we describe a protocol for αSyn-SAA, originally reported as αSyn-PMCA, which allows detection of αSyn aggregates in cerebrospinal fluid samples from patients affected by PD, dementia with Lewy bodies or multiple-system atrophy (MSA). Moreover, this αSyn-SAA can differentiate αSyn aggregates from patients with PD versus those from patients with MSA, even in retrospective samples from patients with pure autonomic failure who later developed PD or MSA. We also describe modifications to the original protocol introduced to develop an optimized version of the assay. The optimized version shortens the assay length, decreases the amount of rec-αSyn required and reduces the number of inconclusive results. The protocol has a hands-on time of ~2 h per 96-well plate and can be performed by personnel trained to perform basic experiments with specimens of human origin. The amplification of misfolded alpha-synuclein aggregates in vitro can be used for the detection, via fluorescent dyes, of pathologic amyloids in cerebrospinal fluid samples from patients affected by Parkinson’s disease, dementia with Lewy bodies or multiple-system atrophy.