Parkinson’s disease (PD) is the fastest-growing neurological condition in the world, affecting 11·8 million people worldwide in 2021. Due to the globally expanding and ageing population, as well as growing industrialisation, this number is likely to increase. Given the absence of disease-modifying pharmacological therapies, this review aimed to examine the effect of dietary interventions on PD progression, motor symptoms, non-motor symptoms, specifically those affecting the gastrointestinal (GI) tract, and severity. To do so, this review synthesised the current evidence from randomised controlled trials (RCTs) on dietary patterns, individual foods and beverages, and nutritional supplements including nutrients, bioactive compounds, and biotics.

Results from the included RCTs failed to demonstrate conclusive evidence for the use of a dietary intervention as a therapy for improving PD progression, symptoms and severity. However, this is likely a reflection of the current scarcity of RCTs in the literature, rather than an outright demonstration of the ineffectiveness of such dietary approaches. In contrast, several trials have demonstrated a beneficial effect of biotic supplementation in managing GI symptoms, particularly constipation syndrome, which may be a promising avenue for improving GI-related issues that affect up to 80 % of PD patients. In conclusion, further RCTs are required to decipher the role that diet may play in mitigating PD progression and severity and improving overall patient care by reducing both motor and non-motor symptoms.

The objective was to identify the predictive markers and develop a diagnostic model with predictive markers for Parkinson’s disease (PD) and investigate the roles of immune cells in the disease pathology. Microarray datasets of PD and control samples were obtained from the Gene Expression Omnibus (GEO) database. We then performed a comprehensive analysis of differentially expressed genes (DEGs), functional enrichment, and protein-protein interactions to pinpoint a set of promising candidate genes. To establish a diagnosis model for PD, we utilized machine learning algorithms and evaluated the corresponding diagnostic performance using the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC). Additionally, the differential abundance of immune cell subsets between PD and control samples was evaluated using the single-sample Gene Set Enrichment Analysis (ssGSEA) method. A total of 264 DEGs were identified in GSE72267. The PPI network ultimately identified 30 hub genes for model construction. Seven genes, namely CD79B, CD40, CCR9, ADRA2A, SIGLEC1, FLT3LG, and THBD, were identified as diagnostic markers for PD, with an AUC of 0.870. This seven-gene signature model was subsequently validated in an independent cohort (GSE22491), demonstrating an AUC of 0.825. Ultimately, the infiltration of 28 immune cells showed that activated B cells, natural killer T cells, and regulatory T cells may contribute to the occurrence and progression of PD. We also found complex associations between these genes and immune cells. CD79B, CD40, CCR9, ADRA2A, SIGLEC1, FLT3LG, and THBD were identified as diagnostic markers for PD, and the infiltration of immune cells may contribute to the pathogenesis of the disease.

Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease globally(1) whereby there is a loss of dopaminergic neurons in the brain and a deficiency of dopamine. PD is characterised by dyskinesia, rigidity, tremor and postural instability, and non-motor symptoms which include neuropsychiatric, sleep and autonomic dysfunction which often occur before motor symptoms(2). Several of these motor and non-motor symptoms can adversely affect nutritional status(3) and a significant number of people with PD are at risk of malnutrition(4). Observational studies have examined the relationship between dietary intake, symptoms and disease progression yet there is a lack of randomised controlled trials of dietary interventions. This presentation will examine the evidence base and suggest future directions for nutrition research in this important area.

Neurodegenerative diseases (NDDs) are a group of complex disorders marked by pathophysiological mechanisms involving protein aggregation, mitochondrial dysfunction, oxidative stress and neuroinflammation. Irrespective of extensive research advances, NDDs have become a serious global concern and persist as a major therapeutic challenge. In recent years, microRNAs (miRNAs), a class of small non-coding RNAs, have established a pivotal role in combating NDDs. The altered expression of miRNAs is reported to be associated with the progression of various NDDs. This review aims to discuss miRNA biogenesis; dysregulation in NDDs, specifically Alzheimer’s disease, Parkinson’s disease (PD) and amyotrophic lateral sclerosis; their potential as biomarkers; and promising therapeutic targets. Additionally, there are various emerging technologies discussed that are advanced approaches to enhance miRNA-based diagnostics and therapeutics.

Parkinson’s disease (PD) is a severe neurodegenerative disorder characterized by prominent motor and non-motor (e.g., cognitive) abnormalities. Notwithstanding Food and Drug Administration (FDA)-approved treatments (e.g., L-dopa), most persons with PD do not adequately benefit from the FDA-approved treatments and treatment emergent adverse events are often reasons for discontinuation. To date, no current therapy for PD is disease modifying or curative. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are central nervous system (CNS) penetrant and have shown to be neuroprotective against oxidative stress, neuroinflammation, and insulin resistance, as well as promoting neuroplasticity. Preclinical evidence suggests that GLP-1RAs also attenuate the accumulation of α-synuclein. The cellular and molecular effects of GLP-1RAs provide a basis to hypothesize putative therapeutic benefit in individuals with PD. Extant preclinical and clinical trial evidence in PD provide preliminary evidence of clinically meaningful benefit in the cardinal features of PD. Herein, we synthesize extant preclinical and early-phase clinical evidence, suggesting that GLP-1RAs may be beneficial as a treatment and/or illness progression modification therapeutic in PD.

Parkinson’s disease (PD) is a complex neurodegenerative disorder that is heterogeneous in both its pathophysiology and clinical presentation. Genetic, imaging and biochemical biomarkers not only provide innovative, objective ways to subtype PD but also offer new insights into the underlying pathophysiology, revealing potential therapeutic targets and improving predictions of clinical phenotype, disease progression and treatment response. In this review, we first summarize the phenotypes linked to key PD genes – such as SNCA, LRRK2, GBA and PRKN – highlighting, for instance, that GBA-PD is often associated with prominent nonmotor features. We then explore studies that have defined new robust subtypes with imaging biomarkers, particularly T1-weighted MRI brain atrophy patterns, and their clinical implications. We also review the role of blood, CSF and urine biomarkers for monitoring disease progression and predicting its presentation in various domains (motor, cognitive, autonomic, psychiatric). These findings could have practical implications by guiding clinicians to individualize symptomatic treatment and helping researchers improve clinical trial design and recruitment, thus bringing us closer to the discovery of effective disease-modifying therapies.

Parkinson’s disease (PD) has become the second most prominent neurogenerative disorder relating to aging individuals. PD involves the loss of neurons containing dopamine in the midbrain and leads to a number of motor issues as well as non-motor complications such as cognitive and psychological abnormalities. The default mode network (DMN) is a complex brain network primarily active during rest and serves multiple roles relating to memory, self-referential processing, social cognition and consciousness and awareness. Multiple brain regions are involved in the DMN such as the medial prefrontal cortex (mPFC), the posterior cingulate cortex (PCC), the inferior parietal lobule, the precuneus and the lateral temporal cortex. Normal DMN connectivity is vital to preserving consciousness and self-awareness. Neurological pathologies such as PD disrupt DMN connectivity, leading to complex issues. Functional MRI (fMRI) is a neuroimaging modality used to observe brain activity through measuring blood flow differences as it relates to brain activity. DMN connectivity experiments using fMRI find that individuals with PD exhibit impaired DMN connectivity in specific regions including the PCC, mPFC and the precuneus. Individuals with greater PD motor symptoms have also been found to suffer larger alterations in DMN connections anatomically within the frontal lobe and PCC. While fMRI has been utilized as a tool to explore the relationship between PD patients and DMN connectivity, future research should look to develop a better understanding of the specific mechanisms of action that drive this link between DMN abnormality and PD severity.

Parkinson’s disease (PD) is a prevalent neurological disorder and the second most common neurodegenerative disease. Research has explored the impact of infectious agents, such as the parasites, on neurological conditions, including PD. Given the limited studies worldwide and in Iran, this study aims to investigate the relationship between Toxocara infection and PD. This case-control study involved 91 PD patients and 90 healthy controls. After obtaining consent, serum samples and questionnaires were collected. All sera were examined using an ELISA test for IgG antibodies against Toxocara canis. Results were analyzed with SPSS, using chi-square tests, and odds ratios (OR), and confidence intervals (CI) were calculated via univariate and multivariate analyses. The prevalence of anti-Toxocara IgG was 33% (30/91) in PD patients and 33.3% (30/90) in the control group. Both univariate analysis (OR: 0.98; 95% CI: 0.52–1.82) and multivariate analysis (OR: 0.95; 95% CI: 0.49–1.83) indicated no statistically significant association. Additionally, univariate analysis (OR: 0.49; 95% CI: 0.16–1.5) and multivariate analysis (OR: 0.37; 95% CI: 0.09–1.43) suggested non-significant association between Toxocara infection and the severity of PD. Our findings do not support a statistically significant association between Toxocara infection and the PD. While the analysis suggested that Toxocara infection might reduce the severity of PD, these results were also not statistically significant. Further research with larger sample sizes and diverse populations is needed to fully understand the potential relationship between Toxocara infection and PD.