Blood biomarkers with Parkinson's disease clusters and prognosis: The oxford discovery cohort

Approaches to Early Parkinson's Disease Subtyping

Parkinson's disease (PD) unfolds with pathological processes and neurodegeneration well before the emergence of noticeable motor symptoms, providing a window for early identification. The extended prodromal phase allows the use of risk stratification measures and prodromal markers to pinpoint individuals likely to develop PD. Importantly, a growing body of evidence emphasizes the heterogeneity within prodromal and clinically diagnosed PD. The disease likely comprises distinct subtypes exhibiting diverse clinical manifestations, pathophysiological mechanisms, and patterns of α-synuclein progression in the central and peripheral nervous systems. There is a pressing need to refine the definition and early identification of these prodromal subtypes. This requires a comprehensive strategy that integrates genetic, pathological, imaging, and multi-omics markers, alongside careful observation of subtle motor and non-motor symptoms. Such multi-dimensional classification of early PD subtypes will improve our understanding of underlying disease pathophysiology, improve predictions of clinical endpoints, progression trajectory and medication response, contribute to drug discovery and personalized medicine by identifying subtype-specific disease mechanisms, and facilitate drug trials by reducing confounding effects of heterogeneity. Here we explore different subtyping methodologies in prodromal and clinical PD, focusing on clinical, imaging, genetic and molecular subtyping approaches. We also emphasize the need for refined, theoretical a priori disease models. These will be prerequisite to understanding the biological underpinnings of biological subtypes, which have been defined by large scale data-driven approaches and multi-omics fingerprints.

Sex differences in the association between Body Mass Index and cognitive function in Parkinson disease: a cross-sectional study

Objective

This study utilized a binary logistic regression model to explore the relationship between Body Mass Index (BMI) and cognitive function in Parkinson's disease (PD) patients.

Methods

In this cross-sectional study, data were obtained from 1,005 Parkinson's patients enrolled in the Parkinson's Progression Markers Initiative (PPMI) from 2010 to 2023, including 378 females and 627 males. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) scale, and the correlation between BMI and cognitive function was determined using binary logistic regression.

Results

The median age of enrollment was 63.6 (56.2, 69.6) years old, including 378 (37.6%) females and 627 (62.4%) males. In the final adjusted model, a significant positive correlation was found between BMI and the prevalence of cognitive impairment in females (OR = 1.06, 95% CI = 1.01 ~ 1.12, p = 0.022), while no correlation was found in males (OR = 1.03, 95% CI = 0.99 ~ 1.08, p = 0.165). The results after categorizing BMI indicate that, among females, the risk of cognitive impairment increases for both groups with BMI ≥ 30 kg/m2 and those with 25 ≤ BMI < 30 kg/m2 compared to the reference group with BMI < 25 kg/m2, with a p for trend <0.001 indicating a stable and strong association between BMI and cognitive impairment in females. In males, the results were not significant. The trend of linear fitting was consistent with the above results.

Conclusion

In female Parkinson's patients, there is a positive correlation between BMI and cognitive impairment, while no correlation was found in male patients. This study provides new evidence of sex differences in the correlation between BMI and cognitive impairment among Parkinson's patients. The role of sex differences in the relationship between BMI and cognitive impairment should be considered in future research.

Two sample Mendelian Randomisation using an outcome from a multilevel model of disease progression

Identifying factors that are causes of disease progression, especially in neurodegenerative diseases, is of considerable interest. Disease progression can be described as a trajectory of outcome over time-for example, a linear trajectory having both an intercept (severity at time zero) and a slope (rate of change). A technique for identifying causal relationships between one exposure and one outcome in observational data whilst avoiding bias due to confounding is two sample Mendelian Randomisation (2SMR). We consider a multivariate approach to 2SMR using a multilevel model for disease progression to estimate the causal effect an exposure has on the intercept and slope. We carry out a simulation study comparing a naïve univariate 2SMR approach to a multivariate 2SMR approach with one exposure that effects both the intercept and slope of an outcome that changes linearly with time since diagnosis. The simulation study results, across six different scenarios, for both approaches were similar with no evidence against a non-zero bias and appropriate coverage of the 95% confidence intervals (for intercept 93.4-96.2% and the slope 94.5-96.0%). The multivariate approach gives a better joint coverage of both the intercept and slope effects. We also apply our method to two Parkinson's cohorts to examine the effect body mass index has on disease progression. There was no strong evidence that BMI affects disease progression, however the confidence intervals for both intercept and slope were wide.

M6A-related bioinformatics analysis indicates that LRPPRC is an immune marker for ischemic stroke

Ischemic stroke (IS) is a common cerebrovascular disease whose pathogenesis involves a variety of immune molecules, immune channels and immune processes. 6-methyladenosine (m6A) modification regulates a variety of immune metabolic and immunopathological processes, but the role of m6A in IS is not yet understood. We downloaded the data set GSE58294 from the GEO database and screened for m6A-regulated differential expression genes. The RF algorithm was selected to screen the m6A key regulatory genes. Clinical prediction models were constructed and validated based on m6A key regulatory genes. IS patients were grouped according to the expression of m6A key regulatory genes, and immune markers of IS were identified based on immune infiltration characteristics and correlation. Finally, we performed functional enrichment, protein interaction network analysis and molecular prediction of the immune biomarkers. We identified a total of 7 differentially expressed genes in the dataset, namely METTL3, WTAP, YWHAG, TRA2A, YTHDF3, LRPPRC and HNRNPA2B1. The random forest algorithm indicated that all 7 genes were m6A key regulatory genes of IS, and the credibility of the above key regulatory genes was verified by constructing a clinical prediction model. Based on the expression of key regulatory genes, we divided IS patients into 2 groups. Based on the expression of the gene LRPPRC and the correlation of immune infiltration under different subgroups, LRPPRC was identified as an immune biomarker for IS. GO enrichment analyses indicate that LRPPRC is associated with a variety of cellular functions. Protein interaction network analysis and molecular prediction indicated that LRPPRC correlates with a variety of immune proteins, and LRPPRC may serve as a target for IS drug therapy. Our findings suggest that LRPPRC is an immune marker for IS. Further analysis based on LRPPRC could elucidate its role in the immune microenvironment of IS.

Genes Selectively Expressed in Rat Organs

Background

Understanding organic functions at a molecular level is important for scientists to unveil the disease mechanism and to develop diagnostic or therapeutic methods.

Aims

The present study tried to find genes selectively expressed in 11 rat organs, including the adrenal gland, brain, colon, duodenum, heart, ileum, kidney, liver, lung, spleen, and stomach.

Materials and Methods

Three normal male Sprague-Dawley (SD) rats were anesthetized, their organs mentioned above were harvested, and RNA in the fresh organs was extracted. Purified RNA was reversely transcribed and sequenced using the Solexa high-throughput sequencing technique. The abundance of a gene was measured by the expected value of fragments per kilobase of transcript sequence per million base pairs sequenced (FPKM). Genes in organs with the highest expression level were sought out and compared with their median value in organs. If a gene in the highest expressed organ was significantly different (p < 0.05) from that in the medianly expressed organ, accompanied by q value < 0.05, and accounted for more than 70% of the total abundance, the gene was assumed as the selective gene in the organ.

Results & Discussion

The Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Ontology (GO) pathways were enriched by the highest expressed genes. Based on the criterion, 1,406 selective genes were screened out, 1,283 of which were described in the gene bank and 123 of which were waiting to be described. KEGG and GO pathways in the organs were partly confirmed by the known understandings and a good portion of the pathways needed further investigation.

Conclusion

The novel selective genes and organic functional pathways are useful for scientists to unveil the mechanisms of the organs at the molecular level, and the selective genes' products are candidate disease markers for organs.

Tai Chi improves non-motor symptoms of Parkinson's disease: One-year randomized controlled study with the investigation of mechanisms

BACKGROUND

Tai Chi was found to improve motor symptoms in Parkinson's disease (PD). Whether long-term Tai Chi training could improve non-motor symptoms (NMS) and the related mechanisms were unknown.

OBJECTIVE

To investigate Tai Chi's impact on non-motor symptoms in PD and related mechanisms.

METHODS

95 early-stage PD patients were recruited and randomly divided into Tai Chi (N = 32), brisk walking (N = 31), and no-exercise groups (N = 32). All subjects were evaluated at baseline, 6 months, and 12 months within one-year intervention. Non-motor symptoms (including cognition, sleep, autonomic symptoms, anxiety/depression, and quality of life) were investigated by rating scales. fMRI, plasma cytokines and metabolomics, and blood Huntingtin interaction protein 2 (HIP2) mRNA levels were detected to observe changes in brain networks and plasma biomarkers.

RESULTS

Sixty-six patients completed the study. Non-motor functions assessed by rating scales, e.g. PD cognitive rating scale (PDCRS) and Epworth Sleepiness scale (ESS), were significantly improved in the Tai Chi group than the control group. Besides, Tai Chi had advantages in improving NMS-Quest and ESS than brisk walking. Improved brain function was seen in the somatomotor network, correlating with improved PDCRS (p = 0.003, respectively). Downregulation of eotaxin and upregulation of BDNF demonstrated a positive correlation with improvement of PDCRS and PDCRS-frontal lobe scores (p ≤ 0.037). Improvement of energy and immune-related metabolomics (p ≤ 0.043), and elevation of HIP2 mRNA levels (p = 0.003) were also found associated with the improvement of PDCRS.

CONCLUSIONS

Tai Chi improved non-motor symptoms in PD, especially in cognition and sleep. Enhanced brain network function, downregulation of inflammation, and enhanced energy metabolism were observed after Tai Chi training.

Transitioning from Subtyping to Precision Medicine in Parkinson's Disease: A Purpose-Driven Approach

The International Parkinson and Movement Disorder Society (MDS) created a task force (TF) to provide a critical overview of the Parkinson's disease (PD) subtyping field and develop a guidance on future research in PD subtypes. Based on a literature review, we previously concluded that PD subtyping requires an ultimate alignment with principles of precision medicine, and consequently novel approaches were needed to describe heterogeneity at the individual patient level. In this manuscript, we present a novel purpose-driven framework for subtype research as a guidance to clinicians and researchers when proposing to develop, evaluate, or use PD subtypes. Using a formal consensus methodology, we determined that the key purposes of PD subtyping are: (1) to predict disease progression, for both the development of therapies (use in clinical trials) and prognosis counseling, (2) to predict response to treatments, and (3) to identify therapeutic targets for disease modification. For each purpose, we describe the desired product and the research required for its development. Given the current state of knowledge and data resources, we see purpose-driven subtyping as a pragmatic and necessary step on the way to precision medicine. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Association between a body shape index and Parkinson's disease: A large cross-sectional study from NHANES

Objective

To further evaluate the connection between obesity and Parkinson's disease, we utilized A body shape index which normalizes waist circumference for Body mass index. Derived from the National Health and Nutrition Examination Survey.

Methods

Based on National Health and Nutrition Examination Survey data from 2005 to 2018, this study included 31,933 adult participants in total. First, all the participants were divided into the Parkinson's disease group and non-Parkinson's disease group, respectively. Next, according to their quartiles of A body shape index levels, they were further classified into Q1 group (0.058-0.077), Q2 group (0.078-0.081), Q3 group (0.082-0.084), and Q4 group (0.085-0.117). A body shape index was the primary exposure, while Parkinson's disease was the primary outcome. A body shape index is defined by waist circumference divided by Body mass index2/3 × height1/2, and the expected value of waist circumference based on height and weight derived empirically from National Health and Nutrition Examination Survey. Consequently, A body shape index and Parkinson's disease were analyzed through multifactor logistic regression.

Results

According to the unadjusted multivariate logistic analysis, the Q4 group had a greater likelihood of acquiring Parkinson's disease than the Q1 group [OR = 4.519, 95% CI: 3.094-6.600; P < 0.001]. After adjusting the demographic variables such as age, sex, and race, Q4 group was at a higher risk of Parkinson's disease acquisition than Q1 [OR (95% CI): 2.677 (1.774-4.038); P < 0.001]. Compared with Q1 group, the male participants were in a greater chance of getting Parkinson's disease than female participants in Q4 group, as shown by subgroup analysis by gender [male vs. female: OR = 6.563 (3.289-13.098) vs. OR = 3.827 (2.398-6.108); Interaction P-value<0.001].

Conclusions

There is a non-linear positive correlation between the adult A body shape index and the risk of Parkinson's disease. Adults are at a greater risk of getting Parkinson's disease as A body shape index rises, and the link is particularly strong among men aged 20 to 59.

Dopamine Synthesis in the Nigrostriatal Dopaminergic System in Patients at Risk of Developing Parkinson's Disease at the Prodromal Stage

Parkinson's disease (PD) is diagnosed by the onset of motor symptoms and treated long after its onset. Therefore, the development of the early diagnosis of PD is a priority for neurology. Advanced methodologies for this include (1) searching for patients at risk of developing prodromal PD based on premotor symptoms; (2) searching for changes in the body fluids in these patients as diagnostic biomarkers; (3) verifying the diagnosis of prodromal PD and diagnostic-value biomarkers using positron emission tomography (PET); (4) anticipating the development of motor symptoms. According to our data, the majority of patients (n = 14) at risk of developing PD selected in our previous study show pronounced interhemispheric asymmetry in the incorporation of 18F-DOPA into dopamine synthesis in the striatum. This was assessed for the caudate nucleus and putamen separately using the specific binding coefficient, asymmetry index, and putamen/caudate nucleus ratio. Interhemispheric asymmetry in the incorporation of 18F-DOPA into the striatum provides strong evidence for its dopaminergic denervation and the diagnostic value of previously identified blood biomarkers. Of the 17 patients at risk of developing prodromal PD studied using PET, 3 patients developed motor symptoms within a year. Thus, our study shows the promise of using the described methodology for the development of early diagnosis of PD.

Peripheral Inflammatory and Immune Landscape in Multiple System Atrophy: A Cross-Sectional Study

BACKGROUND

Neuroinflammation might contribute to the pathogenesis of multiple systemic atrophy (MSA). However, specific alterations in the peripheral inflammatory and immune profiles of patients with MSA remain unclear.

OBJECTIVES

To determine the peripheral inflammatory and immune profiles of patients with MSA and their potential value as biomarkers for facilitating clinical diagnosis and monitoring disease severity.

METHODS

This cross-sectional study included 235, 240, and 235 patients with MSA, patients with Parkinson's disease (PD), and healthy controls (HCs), respectively. Inflammatory and immune parameters were measured in peripheral blood, differences between groups were assessed, and clusters were analyzed. Associations between the parameters and clinical characteristics of MSA were assessed using Spearman and partial correlation analyses.

RESULTS

Significant differences were observed especially in monocytes, neutrophils-to-lymphocyte ratio (NLR) and neutrophils-to-lymphocyte ratio (MPV) between MSA patients and HCs (P < 0.01). Monocytes and uric acid (UA) levels were also significantly different between the MSA and PD patients (P < 0.05). The combination of NLR and MPV distinguished MSA-P patients from HCs (areas under the curve = 0.824). In addition, complement components C4 and C3 were significantly correlated with the Scale Outcomes in PD for Autonomic Symptoms and Wexner scale, whereas immunoglobulin G (IgG) was significantly correlated with scores of Unified Multiple System Atrophy Rating Scale (P < 0.05).

CONCLUSIONS

In MSA patients, monocytes, NLR and MPV might serve as potential diagnostic biomarkers, whereas MLR, C3, C4, and IgG significantly correlate with disease severity. © 2023 International Parkinson and Movement Disorder Society.

The pyroptosis mediated biomarker pattern: an emerging diagnostic approach for Parkinson's disease

BACKGROUND

Parkinson's disease (PD) affects 1% of people over 60, and long-term levodopa treatment can cause side effects. Early diagnosis is of great significance in slowing down the pathological process of PD. Multiple pieces of evidence showed that non-coding RNAs (ncRNAs) could participate in the progression of PD pathology. Pyroptosis is known to be regulated by ncRNAs as a key pathological feature of PD. Therefore, evaluating ncRNAs and pyroptosis-related proteins in serum could be worthy biomarkers for early diagnosis of PD.

METHODS

NcRNAs and pyroptosis/inflammation mRNA levels were measured with reverse transcriptase quantitative polymerase chain reaction (RT-qPCR). Luciferase assays were performed to confirm GSDME as a target of miR-675-5p and HMGB1 as a target of miR-1247-5p. In the serum of healthy controls (n = 106) and PD patients (n = 104), RT-qPCR was utilized to assess miR-675-5p, miR-1247-5p, and two related ncRNAs (circSLC8A1and lncH19) levels. The enzyme-linked immunosorbent assay measured serum levels of pyroptosis-related proteins in controls (n = 54) and PD patients (n = 70).

RESULTS

Our data demonstrated that miR-675-5p and miR-1247-5p significantly changed in PD neuron and animal models. Overexpressed miR-675-5p or downregulated miR-1247-5p could regulate pyroptosis and inflammation in PD neuron models. Using the random forest algorithm, we constructed a classifier based on PD neuron-pyroptosis pathology (four ncRNAs and six proteins) having better predictive power than single biomarkers (AUC = 92%). Additionally, we verified the performance of the classifier in early-stage PD patients (AUC ≥ 88%).

CONCLUSION

Serum pyroptosis-related ncRNAs and proteins could serve as reliable, inexpensive, and non-invasive diagnostic biomarkers for PD.

LIMITATIONS

All participants were from the same region. Additionally, longitudinal studies in the aged population are required to explore the practical application value of the classifier.

The Role of Diet in Parkinson's Disease

The aim of this review is to examine the intersection of Parkinson's disease (PD) with nutrition, to identify best nutritional practices based on current evidence, and to identify gaps in the evidence and suggest future directions. Epidemiological work has linked various dietary patterns and food groups to changes in PD risk; however, fewer studies have evaluated the role of various diets, dietary components, and supplements in the management of established PD. There is substantial interest in exploring the role of diet-related interventions in both symptomatic management and potential disease modification. In this paper, we evaluate the utility of several dietary patterns, including the Mediterranean (MeDi), Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND), Alternative Healthy Eating Index (AHEI), vegan/vegetarian, and ketogenic diet in persons with PD. Additionally, we provide an overview of the evidence relating several individual food groups and nutritional supplements to PD risk, symptoms and progression.

Effect of 12-Week BMI-Based Vitamin D3 Supplementation in Parkinson's Disease with Deep Brain Stimulation on Physical Performance, Inflammation, and Vitamin D Metabolites

Parkinson's disease (PD) is the second most common neurodegenerative disease. To manage motor symptoms not controlled adequately with medication, deep brain stimulation (DBS) is used. PD patients often manifest vitamin D deficiency, which may be connected with a higher risk of falls. We administered a 12-week vitamin D₃ supplementation based on BMI (with higher doses given to patients with higher BMI) to investigate its effects on physical performance and inflammation status in PD patients with DBS. Patients were randomly divided into two groups: treated with vitamin D₃ (VitD, n = 13), and supplemented with vegetable oil as the placebo group (PL, n = 16). Patients underwent functional tests to assess their physical performance three times during this study. The serum 25(OH)D₃ concentration increased to the recommended level of 30 ng/mL in the VitD group, and a significant elevation in vitamin D metabolites in this group was found. We observed significant improvement in the Up and Go and the 6 MWT in the VitD group. In inflammation status, we noticed a trend toward a decrease in the VitD group. To conclude, achieving the optimal serum 25(OH)D₃ concentration is associated with better functional test performance and consequently may have a positive impact on reducing falling risk in PD.

Peripheral Inflammation Is Associated with Dopaminergic Degeneration in Parkinson's Disease

BACKGROUND

Peripheral inflammatory immune responses are suggested to play a major role in dopaminergic degeneration in Parkinson's disease (PD). The neutrophil-to-lymphocyte ratio (NLR) is a well-established biomarker of systemic inflammation in PD. Degeneration of the nigrostriatal dopaminergic system can be assessed in vivo using [¹²³ I]FP-CIT single photon emission computed tomography imaging of striatal dopamine transporter (DAT) density.

OBJECTIVES

To assess the relationship between the peripheral immune profile (NLR, lymphocytes, and neutrophils) and striatal DAT density in patients with PD.

METHODS

We assessed clinical features, the peripheral immune profile, and striatal [¹²³ I]FP-CIT DAT binding levels of 211 patients with PD (primary-cohort). Covariate-controlled associations between the immune response and striatal DAT levels were assessed using linear regression analyses. For replication purposes, we also studied a separate cohort of 344 de novo patients with PD enrolled in the Parkinson's Progression Markers Initiative (PPMI-cohort).

RESULTS

A higher NLR was significantly associated with lower DAT levels in the caudate (primary-cohort: β = -0.01, p < 0.001; PPMI-cohort: β = -0.05, p = 0.05) and the putamen (primary-cohort: β = -0.05, p = 0.02; PPMI-cohort: β = -0.06, p = 0.02). Intriguingly, a lower lymphocyte count was significantly associated with lower DAT levels in both the caudate (primary-cohort: β = +0.09, p < 0.05; PPMI-cohort: β = +0.11, p = 0.02) and the putamen (primary-cohort: β = +0.09, p < 0.05, PPMI-cohort: β = +0.14, p = 0.01), but an association with the neutrophil count was not consistently observed (caudate; primary-cohort: β = -0.05, p = 0.02; PPMI-cohort: β = 0, p = 0.94; putamen; primary-cohort: β = -0.04, p = 0.08; PPMI-cohort: β = -0.01, p = 0.73).

CONCLUSIONS

Our findings across two independent cohorts suggest a relationship between systemic inflammation and dopaminergic degeneration in patients with PD. This relationship was mainly driven by the lymphocyte count. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Identification of Parkinson's disease-associated chromatin regulators

Parkinson's disease (PD) is a common neurological disorder that causes quiescent tremors, motor delays, depression, and sleep disturbances. Existing treatments can only improve symptoms, not stop progression or cure the disease, but effective treatments can significantly improve patients' quality of life. There is growing evidence that chromatin regulatory proteins (CRs) are involved in a variety of biological processes, including inflammation, apoptosis, autophagy, and proliferation. But the relationship of chromatin regulators in Parkinson's disease has not been studied. Therefore, we aim to investigate the role of CRs in the pathogenesis of Parkinson's disease. We collected 870 chromatin regulatory factors from previous studies and downloaded data on patients with PD from the GEO database. 64 differentially expressed genes were screened, the interaction network was constructed and the key genes with the top 20 scores were calculated. Then we discussed its correlation with the immune function of PD. Finally, we screened potential drugs and miRNAs. Five genes related to the immune function of PD, BANF1, PCGF5, WDR5, RYBP and BRD2, were obtained by using the absolute value of correlation greater than 0.4. And the disease prediction model showed good predictive efficiency. We also screened 10 related drugs and 12 related miRNAs, which provided a reference for the treatment of PD. BANF1, PCGF5, WDR5, RYBP and BRD2 are related to the immune process of Parkinson's disease and can predict the occurrence of Parkinson's disease, which is expected to become a new target for the diagnosis and treatment of Parkinson's disease.

Biomarkers: Role and Scope in Neurological Disorders

Neurological disorders pose a great threat to social health and are a major cause for mortality and morbidity. Effective drug development complemented with the improved drug therapy has made considerable progress towards easing symptoms associated with neurological illnesses, yet poor diagnosis and imprecise understanding of these disorders has led to imperfect treatment options. The scenario is complicated by the inability to extrapolate results of cell culture studies and transgenic models to clinical applications which has stagnated the process of improving drug therapy. In this context, the development of biomarkers has been viewed as beneficial to easing various pathological complications. A biomarker is measured and evaluated in order to gauge the physiological process or a pathological progression of a disease and such a marker can also indicate the clinical or pharmacological response to a therapeutic intervention. The development and identification of biomarkers for neurological disorders involves several issues including the complexity of the brain, unresolved discrepant data from experimental and clinical studies, poor clinical diagnostics, lack of functional endpoints, and high cost and complexity of techniques yet research in the area of biomarkers is highly desired. The present work describes existing biomarkers for various neurological disorders, provides support for the idea that biomarker development may ease our understanding underlying pathophysiology of these disorders and help to design and explore therapeutic targets for effective intervention.

Peripheral inflammatory immune response differs among sporadic and familial Parkinson's disease

Peripheral inflammatory immune responses are thought to play a major role in the pathogenesis of Parkinson's disease (PD). The neutrophil-to-lymphocyte ratio (NLR), a biomarker of systemic inflammation, has been reported to be higher in patients with PD than in healthy controls (HCs). The present study was aimed at determining if the peripheral inflammatory immune response could be influenced by the genetic background of patients with PD. We included a discovery cohort with 222 patients with PD (132 sporadic PD, 44 LRRK2-associated PD (with p.G2019S and p.R1441G variants), and 46 GBA-associated PD), as well as 299 HCs. Demographic and clinical data were recorded. Leukocytes and their subpopulations, and the NLR were measured in peripheral blood. Multivariate lineal regression and post-hoc tests were applied to determine the differences among the groups. Subsequently, a replication study using the Parkinson's Progression Markers Initiative cohort was performed which included 401 patients with PD (281 sPD patients, 66 LRRK2-PD patients, 54 GBA-PD patients) and a group of 174 HCs. Patients with sporadic PD and GBA-associated PD showed a significantly lower lymphocyte count, a non-significantly higher neutrophil count and a significantly higher NLR than HCs. The peripheral inflammatory immune response of patients with LRRK2-associated PD did not differ from HCs. Our study supports the involvement of a peripheral inflammatory immune response in the pathophysiology of sPD and GBA-associated PD. However, this inflammatory response was not found in LRRK2-associated PD, probably reflecting different pathogenic inflammatory mechanisms.

Serum Uric Acid as a Putative Biomarker in Prodromal Parkinson's Disease: Longitudinal Data from the PPMI Study

BACKGROUND

The role of blood uric acid as a biomarker in symptomatic motor PD has been increasingly established in the literature.

OBJECTIVE

Our present study assessed the role of serum uric acid as a putative biomarker in a prodromal PD cohort [REM Sleep Behavior disorder (RBD) and Hyposmia] followed longitudinally.

METHODS

Longitudinal 5-year serum uric acid measurement data of 39 RBD patients and 26 Hyposmia patients with an abnormal DATSCAN imaging were downloaded from the Parkinson's Progression Markers Initiative database. These cohorts were compared with 423 de novo PD patients and 196 healthy controls enrolled in the same study.

RESULTS

After adjusting for age, sex, body mass index, and concomitant disorders (hypertension/gout), baseline and longitudinal serum uric acid levels were higher in the RBD subgroup as compared to the established PD cohort (p = 0.004 and p = 0.001). (Baseline RBD 6.07±1.6 vs. Baseline PD 5.35±1.3 mg/dL and Year-5 RBD 5.7±1.3 vs. Year-5 PD 5.26±1.33). This was also true for longitudinal measurements in the Hyposmic subgroup (p = 0.008) (Baseline Hyposmic 5.7±1.6 vs. PD 5.35±1.3 mg/dL and Year-5 Hyposmic 5.58±1.6 vs. PD 5.26±1.33).

CONCLUSION

Our results indicate that serum uric acid levels are higher in prodromal PD subjects with ongoing dopaminergic degeneration compared to those with manifest PD. These data indicate that the well-established decrease in the levels of serum uric acid occurs with the transition from prodromal to clinical PD. Whether the higher levels of serum uric acid observed in prodromal PD may provide protection against conversion to full-blown clinical PD will require further study.

Identification of a possible proteomic biomarker in Parkinson's disease: discovery and replication in blood, brain and cerebrospinal fluid

Biomarkers to aid diagnosis and delineate the progression of Parkinson's disease are vital for targeting treatment in the early phases of the disease. Here, we aim to discover a multi-protein panel representative of Parkinson's and make mechanistic inferences from protein expression profiles within the broader objective of finding novel biomarkers. We used aptamer-based technology (SomaLogic®) to measure proteins in 1599 serum samples, 85 cerebrospinal fluid samples and 37 brain tissue samples collected from two observational longitudinal cohorts (the Oxford Parkinson's Disease Centre and Tracking Parkinson's) and the Parkinson's Disease Brain Bank, respectively. Random forest machine learning was performed to discover new proteins related to disease status and generate multi-protein expression signatures with potential novel biomarkers. Differential regulation analysis and pathway analysis were performed to identify functional and mechanistic disease associations. The most consistent diagnostic classifier signature was tested across modalities [cerebrospinal fluid (area under curve) = 0.74, P = 0.0009; brain area under curve = 0.75, P = 0.006; serum area under curve = 0.66, P = 0.0002]. Focusing on serum samples and using only those with severe disease compared with controls increased the area under curve to 0.72 (P = 1.0 × 10^-4). In the validation data set, we showed that the same classifiers were significantly related to disease status (P < 0.001). Differential expression analysis and weighted gene correlation network analysis highlighted key proteins and pathways with known relationships to Parkinson's. Proteins from the complement and coagulation cascades suggest a disease relationship to immune response. The combined analytical approaches in a relatively large number of samples, across tissue types, with replication and validation, provide mechanistic insights into the disease as well as nominate a protein signature classifier that deserves further biomarker evaluation.

Precision medicine for Parkinson's disease: The subtyping challenge

Despite many pharmacological and surgical treatments addressing the symptoms of Parkinson's disease, there are no approved treatments that slow disease progression. Genetic discoveries in the last 20 years have increased our understanding of the molecular contributors to Parkinson's pathophysiology, uncovered many druggable targets and pathways, and increased investment in treatments that might slow or stop the disease process. Longitudinal, observational studies are dissecting Parkinson's disease heterogeneity and illuminating the importance of molecularly defined subtypes more likely to respond to targeted interventions. Indeed, clinical and pathological differences seen within and across carriers of PD-associated gene mutations suggest the existence of greater biological complexity than previously appreciated and increase the likelihood that targeted interventions based on molecular characteristics will be beneficial. This article offers our current perspective on the promise and current challenges in subtype identification and precision medicine approaches in Parkinson's disease.

Deciphering clock genes as emerging targets against aging

The old people often suffer from circadian rhythm disturbances, which in turn accelerate aging. Many aging-related degenerative diseases such as Alzheimer's disease, Parkinson's disease, and osteoarthritis have an inextricable connection with circadian rhythm. In light of the predominant effects of clock genes on regulating circadian rhythm, we systematically present the elaborate network of roles that clock genes play in aging in this review. First, we briefly introduce the basic background regarding clock genes. Second, we systemically summarize the roles of clock genes in aging and aging-related degenerative diseases. Third, we discuss the relationship between clock genes polymorphisms and aging. In summary, this review is intended to clarify the indispensable roles of clock genes in aging and sheds light on developing clock genes as anti-aging targets.

Genetic architecture of Parkinson’s disease subtypes – Review of the literature

The heterogeneity of Parkinson’s disease (PD) has been recognized since its description by James Parkinson over 200 years ago. The complexity of motor and non-motor PD manifestations has led to many attempts of PD subtyping with different prognostic outcomes; however, the pathophysiological foundations of PD heterogeneity remain elusive. Genetic contributions to PD may be informative in understanding the underpinnings of PD subtypes. As such, recognizing genotype-phenotype associations may be crucial for successful gene therapy. We review the state of knowledge on the genetic architecture underlying PD subtypes, discussing the monogenic forms, as well as oligo- and polygenic risk factors associated with various PD subtypes. Based on our review, we argue for the unification of PD subtyping classifications, the dichotomy of studies on genetic factors and genetic modifiers of PD, and replication of results from previous studies.

Global, in situ analysis of the structural proteome in individuals with Parkinson's disease to identify a new class of biomarker

Parkinson's disease (PD) is a prevalent neurodegenerative disease for which robust biomarkers are needed. Because protein structure reflects function, we tested whether global, in situ analysis of protein structural changes provides insight into PD pathophysiology and could inform a new concept of structural disease biomarkers. Using limited proteolysis-mass spectrometry (LiP-MS), we identified 76 structurally altered proteins in cerebrospinal fluid (CSF) of individuals with PD relative to healthy donors. These proteins were enriched in processes misregulated in PD, and some proteins also showed structural changes in PD brain samples. CSF protein structural information outperformed abundance information in discriminating between healthy participants and those with PD and improved the discriminatory performance of CSF measures of the hallmark PD protein α-synuclein. We also present the first analysis of inter-individual variability of a structural proteome in healthy individuals, identifying biophysical features of variable protein regions. Although independent validation is needed, our data suggest that global analyses of the human structural proteome will guide the development of novel structural biomarkers of disease and enable hypothesis generation about underlying disease processes.

QEEG indices are associated with inflammatory and metabolic risk factors in Parkinson's disease dementia: An observational study

BACKGROUND

Quantitative electroencephalography (QEEG) is a reliable and non-invasive diagnostic tool to quantify cortical synaptic injury or loss in the clinical assessment of neurodegenerative diseases, and may be able to differentiate various types of dementia. We investigated if QEEG indices can differentiate Parkinson's Disease (PD) with nondementia (PD-ND) from PD with dementia (PDD), and to determine if QEEG indices correlate with inflammation and lipid metabolism markers in PD.

METHODS

This clinical study collected data between July 1, 2018 and July 1, 2021 in Zhujiang Hospital of Southern Medical University in China and data was analysed. A total of 125 individuals comprising of 31 PDD, 47 patients with PD-ND and 47 healthy controls were included. We calculated the absolute spectral power (ASP) of frequency bands and the slow-to-fast frequency ratios of specific brain regions. Plasma levels of hypersensitive C-reactive protein (Hs-CRP), superoxide dismutase (SOD), and high-density lipoprotein cholesterol (HDL-C) were measured and correlations with QEEG indices were examined.

FINDINGS

A significantly higher ASP of delta frequency especially in the frontal region was observed in patients with PDD compared to PD-ND (P=0.004) and controls (P=0.000). Decreased HDL-C (OR=0.186, P=0.030), and increased Hs-CRP (OR =2.856, P=0.015) were associated with PDD. Frontal-delta ASP was negatively correlated with plasma HDL-C (r=-0.353, P=0.000) and SOD (r=-0.322, P=0.001), and positively correlated with Hs-CRP (r=0.342, P=0.000).

INTERPRETATION

We highlight novel correlations between QEEG indices and inflammation and lipid metabolism markers in PD-ND and PDD. QEEG indices, HDL-C and Hs-CRP are potentially useful for the evaluation of PDD. Our current findings suggest that peripheral inflammation might contribute to the pathogenesis of cognitive impairment and EEG slowing in PDD. The mechanism underlying frontal-delta ASP and its correlation with neuro-inflammatory and metabolic markers in PDD should be further investigated.

FUNDING

The National Natural Science Foundation of China (NO: 81873777, 82071414); the Scientific Research Foundation of Guangzhou (NO: 202206010005); the Science and Technology Program of Guangdong of China (NO: 2020A0505100037); the High-level Hospital Construction Research Project of Maoming People's Hospital (NO: xz2020009); the Science and Technology Program of Maoming City (NO: 2021S0026). Dr EK Tan is supported by the National Medical Research Council, Singapore.

Biomarker characterization of clinical subtypes of Parkinson Disease

The biological underpinnings of the PD clusters remain unknown as the existing PD clusters lacks biomarker characterization. We try to identify clinical subtypes of Parkinson Disease (PD) in an Asian cohort and characterize them by comparing clinical assessments, genetic status and blood biochemical markers. A total of 206 PD patients were included from a multi-centre Asian cohort. Hierarchical clustering was performed to generate PD subtypes. Clinical and biological characterization of the subtypes were performed by comparing clinical assessments, allelic distributions of Asian related PD gene (SNCA, LRRK2, Park16, ITPKB, SV2C) and blood biochemical markers. Hierarchical clustering method identified three clusters: cluster A (severe subtype in motor, non-motor and cognitive domains), cluster B (intermediate subtype with cognitive impairment and mild non-motor symptoms) and cluster C (mild subtype and young age of onset). The three clusters had significantly different allele frequencies in two SNPs (Park16 rs6679073 A allele carriers in cluster A B C: 67%, 74%, 89%, p = 0.015; SV2C rs246814 T allele distribution: 7%, 12%, 25%, p = 0.026). Serum homocysteine (Hcy) and C-reactive protein (CRP) levels were also significantly different among three clusters (Mean levels of Hcy and CRP among cluster A B C were: 19.4 ± 4.2, 18.4 ± 5.7, 15.6 ± 5.6, adjusted p = 0.005; 2.5 ± 5.0, 1.5 ± 2.4, 0.9 ± 2.1, adjusted p < 0.0001, respectively). Of the 3 subtypes identified amongst early PD patients, the severe subtype was associated with significantly lower frequency of Park16 and SV2C alleles and higher levels of Hcy and CRP. These biomarkers may be useful to stratify PD subtypes and identify more severe subtypes.

Biomarkers of Neurodegenerative Diseases: Biology, Taxonomy, Clinical Relevance, and Current Research Status

The understanding of neurodegenerative diseases, traditionally considered to be well-defined entities with distinguishable clinical phenotypes, has undergone a major shift over the last 20 years. The diagnosis of neurodegenerative diseases primarily requires functional brain imaging techniques or invasive tests such as lumbar puncture to assess cerebrospinal fluid. A new biological approach and research efforts, especially in vivo, have focused on biomarkers indicating underlying proteinopathy in cerebrospinal fluid and blood serum. However, due to the complexity and heterogeneity of neurodegenerative processes within the central nervous system and the large number of overlapping clinical diagnoses, identifying individual proteinopathies is relatively difficult and often not entirely accurate. For this reason, there is an urgent need to develop laboratory methods for identifying specific biomarkers, understand the molecular basis of neurodegenerative disorders and classify the quantifiable and readily available tools that can accelerate efforts to translate the knowledge into disease-modifying therapies that can improve and simplify the areas of differential diagnosis, as well as monitor the disease course with the aim of estimating the prognosis or evaluating the effects of treatment. The aim of this review is to summarize the current knowledge about clinically relevant biomarkers in different neurodegenerative diseases.

Genetics of validated Parkinson's disease subtypes in the Oxford Discovery and Tracking Parkinson's cohorts

OBJECTIVES

To explore the genetics of four Parkinson's disease (PD) subtypes that have been previously described in two large cohorts of patients with recently diagnosed PD. These subtypes came from a data-driven cluster analysis of phenotypic variables.

METHODS

We looked at the frequency of genetic mutations in glucocerebrosidase (GBA) and leucine-rich repeat kinase 2 against our subtypes. Then we calculated Genetic Risk Scores (GRS) for PD, multiple system atrophy, progressive supranuclear palsy, Lewy body dementia, and Alzheimer's disease. These GRSs were regressed against the probability of belonging to a subtype in the two independent cohorts and we calculated q-values as an adjustment for multiple testing across four subtypes. We also carried out a Genome-Wide Association Study (GWAS) of belonging to a subtype.

RESULTS

A severe disease subtype had the highest rates of patients carrying GBA mutations while the mild disease subtype had the lowest rates (p=0.009). Using the GRS, we found a severe disease subtype had a reduced genetic risk of PD (p=0.004 and q=0.015). In our GWAS no individual variants met genome wide significance (<5×10e-8) although four variants require further follow-up, meeting a threshold of <1×10e-6.

CONCLUSIONS

We have found that four previously defined PD subtypes have different genetic determinants which will help to inform future studies looking at underlying disease mechanisms and pathogenesis in these different subtypes of disease.

Vitamin D Status and Parkinson's Disease

Parkinson’s disease (PD) is a complex and progressive neurodegenerative disease, characterized by resting tremor, rigidity, slowness of movement, and postural instability. Furthermore, PD is associated with a wide spectrum of non-motor symptoms that add to overall disability. In recent years, some investigations, from basic science to clinical applications, have focused on the role of vitamin D in PD, often with controversial findings. Vitamin D has widespread effects on several biological processes in the central nervous system, including neurotransmission in dopaminergic neural circuits. Various studies have recorded lower levels of vitamin D in PD patients than in healthy controls. Low vitamin D status has also been correlated with the risk for PD and motor severity, whereas less is known about the effects vitamin D has on cognitive function and other non-motor symptoms. This review aims to better characterize the correlation between vitamin D and PD, clarify the role of vitamin D in PD prevention and treatment, and discuss avenues for future research in this field.

Extraction of Reduced Infrared Biomarker Signatures for the Stratification of Patients Affected by Parkinson’s Disease: An Untargeted Metabolomic Approach

An untargeted Fourier transform infrared (FTIR) metabolomic approach was employed to study metabolic changes and disarrangements, recorded as infrared signatures, in Parkinson’s disease (PD). Herein, the principal aim was to propose an efficient sequential classification strategy based on SELECT-LDA, which enabled optimal stratification of three main categories: PD patients from subjects with Alzheimer’s disease (AD) and healthy controls (HC). Moreover, sub-categories, such as PD at the early stage (PDI) from PD in the advanced stage (PDD), and PDD vs. AD, were stratified. Every classification step with selected wavenumbers achieved 90.11% to 100% correct assignment rates in classification and internal validation. Therefore, selected metabolic signatures from new patients could be used as input features for screening and diagnostic purposes.

Diagnostic value of cerebrospinal fluid alpha-synuclein seed quantification in synucleinopathies

Several studies have confirmed the α-synuclein real-time quaking-induced conversion (RT-QuIC) assay to have high sensitivity and specificity for Parkinson's disease. However, whether the assay can be used as a robust, quantitative measure to monitor disease progression, stratify different synucleinopathies and predict disease conversion in patients with idiopathic REM sleep behaviour disorder remains undetermined. The aim of this study was to assess the diagnostic value of CSF α-synuclein RT-QuIC quantitative parameters in regard to disease progression, stratification and conversion in synucleinopathies. We performed α-synuclein RT-QuIC in the CSF samples from 74 Parkinson's disease, 24 multiple system atrophy and 45 idiopathic REM sleep behaviour disorder patients alongside 55 healthy controls, analysing quantitative assay parameters in relation to clinical data. α-Synuclein RT-QuIC showed 89% sensitivity and 96% specificity for Parkinson's disease. There was no correlation between RT-QuIC quantitative parameters and Parkinson's disease clinical scores (e.g. Unified Parkinson's Disease Rating Scale motor), but RT-QuIC positivity and some quantitative parameters (e.g. Vmax) differed across the different phenotype clusters. RT-QuIC parameters also added value alongside standard clinical data in diagnosing Parkinson's disease. The sensitivity in multiple system atrophy was 75%, and CSF samples showed longer T50 and lower Vmax compared to Parkinson's disease. All RT-QuIC parameters correlated with worse clinical progression of multiple system atrophy (e.g. change in Unified Multiple System Atrophy Rating Scale). The overall sensitivity in idiopathic REM sleep behaviour disorder was 64%. In three of the four longitudinally followed idiopathic REM sleep behaviour disorder cohorts, we found around 90% sensitivity, but in one sample (DeNoPa) diagnosing idiopathic REM sleep behaviour disorder earlier from the community cases, this was much lower at 39%. During follow-up, 14 of 45 (31%) idiopathic REM sleep behaviour disorder patients converted to synucleinopathy with 9/14 (64%) of convertors showing baseline RT-QuIC positivity. In summary, our results showed that α-synuclein RT-QuIC adds value in diagnosing Parkinson's disease and may provide a way to distinguish variations within Parkinson's disease phenotype. However, the quantitative parameters did not correlate with disease severity in Parkinson's disease. The assay distinguished multiple system atrophy patients from Parkinson's disease patients and in contrast to Parkinson's disease, the quantitative parameters correlated with disease progression of multiple system atrophy. Our results also provided further evidence for α-synuclein RT-QuIC having potential as an early biomarker detecting synucleinopathy in idiopathic REM sleep behaviour disorder patients prior to conversion. Further analysis of longitudinally followed idiopathic REM sleep behaviour disorder patients is needed to better understand the relationship between α-synuclein RT-QuIC signature and the progression from prodromal to different synucleinopathies.

Monogenetic Forms of Parkinson’s Disease – Bridging the Gap Between Genetics and Biomarkers

The therapy of neurodegenerative diseases such as Parkinson’s disease (PD) is still limited to the treatment of symptoms and primarily aimed at compensating for dopaminergic hypofunction. Numerous disease-modifying therapies currently in the pipeline attempt to modify the underlying pathomechanisms. In recent decades, the results of molecular genetics and biomarker research have raised hopes of earlier diagnosis and new neuroprotective therapeutic approaches. As the disease-causing processes in monogenetic forms of PD are better understood than in sporadic PD, these disease subsets are likely to benefit first from disease-modifying therapies. Recent studies have suggested that disease-relevant changes found in genetically linked forms of PD (i.e., PARK-LRRK2, PARK-GBA) can also be reproduced in patients in whom no genetic cause can be found, i.e., those with sporadic PD. It can, therefore, be assumed that as soon as the first causal therapy for genetic forms of PD is approved, more patients with PD will undergo genetic testing and counseling. Regarding future neuroprotective trials in neurodegenerative diseases and objective parameters such as biomarkers with high sensitivity and specificity for the diagnosis and course of the disease are needed. These biomarkers will also serve to monitor treatment success in clinical trials. Promising examples in PD, such as alpha-synuclein species, lysosomal enzymes, markers of amyloid and tau pathology, and neurofilament light chain, are under investigation in blood and CSF. This paper provides an overview of the opportunities and current limitations of monogenetic diagnostic and biomarker research in PD and aims to build a bridge between current knowledge and association with PD genetics and biomarkers.

Blood SSR1: A Possible Biomarker for Early Prediction of Parkinson’s Disease

Parkinson’s disease (PD) is the second most common neurodegenerative disease associated with age. Early diagnosis of PD is key to preventing the loss of dopamine neurons. Peripheral-blood biomarkers have shown their value in recent years because of their easy access and long-term monitoring advantages. However, few peripheral-blood biomarkers have proven useful. This study aims to explore potential peripheral-blood biomarkers for the early diagnosis of PD. Three substantia nigra (SN) transcriptome datasets from the Gene Expression Omnibus (GEO) database were divided into a training cohort and a test cohort. We constructed a protein–protein interaction (PPI) network and a weighted gene co-expression network analysis (WGCNA) network, found their overlapping differentially expressed genes and studied them as the key genes. Analysis of the peripheral-blood transcriptome datasets of PD patients from GEO showed that three key genes were upregulated in PD over healthy participants. Analysis of the relationship between their expression and survival and analysis of their brain expression suggested that these key genes could become biomarkers. Then, animal models were studied to validate the expression of the key genes, and only SSR1 (the signal sequence receptor subunit1) was significantly upregulated in both animal models in peripheral blood. Correlation analysis and logistic regression analysis were used to analyze the correlation between brain dopaminergic neurons and SSR1 expression, and it was found that SSR1 expression was negatively correlated with dopaminergic neuron survival. The upregulation of SSR1 expression in peripheral blood was also found to precede the abnormal behavior of animals. In addition, the application of artificial intelligence technology further showed the value of SSR1 in clinical PD prediction. The three classifiers all showed that SSR1 had high predictability for PD. The classifier with the best prediction accuracy was selected through AUC and MCC to construct a prediction model. In short, this research not only provides potential biomarkers for the early diagnosis of PD but also establishes a possible artificial intelligence model for predicting PD.

6-Hydroxydopamine Induces Abnormal Iron Sequestration in BV2 Microglia by Activating Iron Regulatory Protein 1 and Inhibiting Hepcidin Release

Disrupted iron homeostasis in the substantia nigra pars compacta (SNpc) is an important pathological mechanism in Parkinson’s disease (PD). It is unclear what role microglia play in iron metabolism and selective iron deposition in the SNpc of PD brain. In this study, we observed that 6-hydroxydopamine (6-OHDA) induced the expression of divalent metal transporter-1 (DMT1) and iron influx in BV2 microglia cells, which might be associated with the upregulation of iron regulatory protein 1 (IRP1) expression. Moreover, we found that 6-OHDA had no significant effect on the expression of ferroportin 1 (FPN1) and iron efflux in BV2 microglial cells, which might be the combined action of IRP1 upregulation and reduced hepcidin levels. Furthermore, 6-OHDA treatment activated BV2 microglia and enhanced the release of pro-inflammatory cytokines. Interestingly, iron overloading suppressed IRP1 expression, thus downregulating DMT1 and upregulating FPN1 levels in these microglial cells. On the contrary, iron deficiency activated IRP1, leading to increased expression of DMT1 and decreased expression of FPN1—which indicates that activated IRP1 induces iron overloading in 6-OHDA-treated microglia, but not iron overloading modulates the expression of IRP1. Taken together, our data suggest that 6-OHDA can regulate the expression of DMT1 and FPN1 by activating IRP1 and inhibiting hepcidin release, thus leading to abnormal iron sequestration in microglia. In addition, 6-OHDA can activate microglia, which leads to increased release of pro-inflammatory factors that can further induce genome damage in dopaminergic neurons.

Quantitative Electroencephalography as a Biomarker for Cognitive Dysfunction in Parkinson's Disease

Background: Quantitative electroencephalography (qEEG) has been suggested as a biomarker for cognitive decline in Parkinson's disease (PD). Objective: Determine if applying a wavelet-based qEEG algorithm to 21-electrode, resting-state EEG recordings obtained in a routine clinical setting has utility for predicting cognitive impairment in PD. Methods: PD subjects, evaluated by disease stage and motor score, were compared to healthy controls (N = 20 each). PD subjects with normal (PDN, MoCA 26-30, N = 6) and impaired (PDD, MoCA ≤ 25, N = 14) cognition were compared. The wavelet-transform based time-frequency algorithm assessed the instantaneous predominant frequency (IPF) at 60 ms intervals throughout entire recordings. We then determined the relative time spent by the IPF in the four standard EEG frequency bands (RTF) at each scalp location. The resting occipital rhythm (ROR) was assessed using standard power spectral analysis. Results: Comparing PD subjects to healthy controls, mean values are decreased for ROR and RTF-Beta, greater for RTF-Theta and similar for RTF-Delta and RTF-Alpha. In logistic regression models, arithmetic combinations of RTF values [e.g., (RTF-Alpha) + (RTF-Beta)/(RTF-Delta + RTF-Theta)] and RTF-Alpha values at occipital or parietal locations are most able to discriminate between PD and controls. A principal component (PC) from principal component analysis (PCA) using RTF-band values in all subjects is associated with PD status (p = 0.004, β = 0.31, AUC = 0.780). Its loadings show positive contribution from RTF-Theta at all scalp locations, and negative contributions from RTF-Beta at occipital, parietal, central, and temporal locations. Compared to cognitively normal PD subjects, cognitively impaired PD subjects have lower median RTF-Alpha and RTF-Beta values, greater RTF-Theta values and similar RTF-Delta values. A PC from PCA using RTF-band values in PD subjects is associated with cognitive status (p = 0.002, β = 0.922, AUC = 0.89). Its loadings show positive contributions from RTF-Theta at all scalp locations, negative contributions from RTF-Beta at central locations, and negative contributions from RTF-Delta at central, frontal and temporal locations. Age, disease duration and/or sex are not significant covariates. No PC was associated with motor score or disease stage. Significance: Analyzing standard EEG recordings obtained in a community practice setting using a wavelet-based qEEG algorithm shows promise as a PD biomarker and for predicting cognitive impairment in PD.

Parkinson's Disease Subtyping Using Clinical Features and Biomarkers: Literature Review and Preliminary Study of Subtype Clustering

The second most common progressive neurodegenerative disorder, Parkinson’s disease (PD), is characterized by a broad spectrum of symptoms that are associated with its progression. Several studies have attempted to classify PD according to its clinical manifestations and establish objective biomarkers for early diagnosis and for predicting the prognosis of the disease. Recent comprehensive research on the classification of PD using clinical phenotypes has included factors such as dominance, severity, and prognosis of motor and non-motor symptoms and biomarkers. Additionally, neuroimaging studies have attempted to reveal the pathological substrate for motor symptoms. Genetic and transcriptomic studies have contributed to our understanding of the underlying molecular pathogenic mechanisms and provided a basis for classifying PD. Moreover, an understanding of the heterogeneity of clinical manifestations in PD is required for a personalized medicine approach. Herein, we discuss the possible subtypes of PD based on clinical features, neuroimaging, and biomarkers for developing personalized medicine for PD. In addition, we conduct a preliminary clustering using gait features for subtyping PD. We believe that subtyping may facilitate the development of therapeutic strategies for PD.

Serum fractalkine and 3-nitrotyrosine levels correlate with disease severity in Parkinson's disease: a pilot study

Parkinson's disease (PD) and Parkinsonian syndromes; Progressive supranuclear palsy (PSP), and Multiple system atrophy (MSA) are debilitating neurodegenerative disorders. Fractalkine is a chemokine involved in neuroinflammation, whereas, 3-nitrotyrosine (3-NT) is a marker of early neurodegenerative cellular-damage. We measured Fractalkine and 3-NT levels in the serum of these patients to examine the neuroinflammation hypothesis and also to decipher the propensity of these biologics to be used as early (5 years from onset) biochemical markers in neurodegenerative Parkinsonism. The diagnoses of PD, PSP and MSA were performed as per the respective clinical criteria. 21 PD, 9 PSP and 8 MSA patients along with controls participated in this study. Serum concentrations of Fractalkine and 3-NT were measured by ELISA. Fractalkine levels were increased in PD, PSP and MSA cohorts in comparison with controls with p < 0.001, p < 0.05 and p < 0.05 respectively. Levels of 3-NT also showed elevation in PD (p < 0.01) vs. controls. However, Pearson plot showed that Fractalkine levels were high in the patients with unified Parkinson's disease rating scale (UPDRS) part III motor score of 1, meaning slight disability, but gradually dropped in patients with motor score of 4, which is a measure of severe motor disability. This negative correlation (- .565, p < .0.01) also accentuates the neuroprotectant/anti-inflammatory nature of Fractalkine in PD. Continuous rise of 3-NT in PD, positively correlating (.512, p < 0.05) with worsening motor symptoms points to deleterious consequences of nitrosative stress. To our knowledge, this is the first report providing evidence that serum Fractalkine and 3-NT have early diagnostic/prognostic significance as PD biomarkers.

Advances in clinical basic research: Performance, treatments, and mechanisms of Parkinson disease

The loss of neuronal in the substantia nigra of the elderly contributes to striatal damage and plays a critical part in the common forms of neurodegenerative diseases such as Parkinson disease (PD). The deficit of dopamine is one of the most familiar neuropathological features of PD as well as α-Synuclein aggregation. The peripheral autonomic nervous system is also affected negatively during the course of the disease, although the subsistent of dyskinesias and else major motor characteristic deficits take significant role in the diagnostic methods during clinical practice, which is related to a number of non-motor symptoms that might increase aggregate risks. Multiple pathways and mechanisms are involved in the molecular pathogenesis: α-Synuclein, neuronal homeostasis, mitochondrial function, oxidative stress, as well as neuroinflammation. Investigations in the last few years for diagnostic biomarkers used neuroimaging, including single photon emission computed tomography  as well as cutting-edge magnetic resonance imaging techniques, which has been presented to facilitate discrepant diagnosis. Pharmacological treatment is also important and efficient in equal measure. In addition to reliance on striatal dopamine replacement therapy, many solutions that are used for motor or nonmotor symptoms in these patients are available.

It Is Time to Study Overlapping Molecular and Circuit Pathophysiologies in Alzheimer's and Lewy Body Disease Spectra

Alzheimer's disease (AD) is the leading cause of dementia due to neurodegeneration and is characterized by extracellular senile plaques composed of amyloid β1 - 42 (Aβ) as well as intracellular neurofibrillary tangles consisting of phosphorylated tau (p-tau). Dementia with Lewy bodies constitutes a continuous spectrum with Parkinson's disease, collectively termed Lewy body disease (LBD). LBD is characterized by intracellular Lewy bodies containing α-synuclein (α-syn). The core clinical features of AD and LBD spectra are distinct, but the two spectra share common cognitive and behavioral symptoms. The accumulation of pathological proteins, which acquire pathogenicity through conformational changes, has long been investigated on a protein-by-protein basis. However, recent evidence suggests that interactions among these molecules may be critical to pathogenesis. For example, Aβ/tau promotes α-syn pathology, and α-syn modulates p-tau pathology. Furthermore, clinical evidence suggests that these interactions may explain the overlapping pathology between AD and LBD in molecular imaging and post-mortem studies. Additionally, a recent hypothesis points to a common mechanism of prion-like progression of these pathological proteins, via neural circuits, in both AD and LBD. This suggests a need for understanding connectomics and their alterations in AD and LBD from both pathological and functional perspectives. In AD, reduced connectivity in the default mode network is considered a hallmark of the disease. In LBD, previous studies have emphasized abnormalities in the basal ganglia and sensorimotor networks; however, these account for movement disorders only. Knowledge about network abnormalities common to AD and LBD is scarce because few previous neuroimaging studies investigated AD and LBD as a comprehensive cohort. In this paper, we review research on the distribution and interactions of pathological proteins in the brain in AD and LBD, after briefly summarizing their clinical and neuropsychological manifestations. We also describe the brain functional and connectivity changes following abnormal protein accumulation in AD and LBD. Finally, we argue for the necessity of neuroimaging studies that examine AD and LBD cases as a continuous spectrum especially from the proteinopathy and neurocircuitopathy viewpoints. The findings from such a unified AD and Parkinson's disease (PD) cohort study should provide a new comprehensive perspective and key data for guiding disease modification therapies targeting the pathological proteins in AD and LBD.

Plasma extracellular vesicles tau and β-amyloid as biomarkers of cognitive dysfunction of Parkinson's disease

The contribution of circulatory tau and β-amyloid in Parkinson's disease (PD), especially the cognitive function, remains inconclusive. Extracellular vesicles (EVs) cargo these proteins throughout the bloodstream after they are directly secreted from many cells, including neurons. The present study aims to investigate the role of the plasma EV-borne tau and β-amyloid as biomarkers for cognitive dysfunction in PD by investigating subjects with mild to moderate stage of PD (n = 116) and non-PD controls (n = 46). Plasma EVs were isolated, and immunomagnetic reduction-based immunoassay was used to assess the levels of α-synuclein, tau, and β-amyloid 1-42 (Aβ1-42) within the EVs. Artificial neural network (ANN) models were then applied to predict cognitive dysfunction. We observed no significant difference in plasma EV tau and Aβ1-42 between PD patients and controls. Plasma EV tau was significantly associated with cognitive function. Moreover, plasma EV tau and Aβ1-42 were significantly elevated in PD patients with cognitive impairment when compared to PD patients with optimal cognition. The ANN model used the plasma EV α-synuclein, tau, and Aβ1-42, as well as the patient's age and gender, as predicting factors. The model achieved an accuracy of 91.3% in identifying cognitive dysfunction in PD patients, and plasma EV tau and Aβ1-42 are the most valuable factors. In conclusion, plasma EV tau and Aβ1-42 are significant markers of cognitive function in PD patients. Combining with the plasma EV α-synuclein, age, and sex, plasma EV tau and Aβ1-42 can identify cognitive dysfunction in PD patients. This study corroborates the prognostic roles of plasma EV tau and Aβ1-42 in PD.

Longitudinal Changes in Parkinson's Disease Symptoms with and Without Rapid Eye Movement Sleep Behavior Disorder: The Oxford Discovery Cohort Study

BACKGROUND

Parkinson's disease (PD) comorbid with rapid eye movement sleep behavior disorder (RBD) may show more severe motor and nonmotor symptoms, suggesting a distinct PD subtype.

OBJECTIVE

The aim of this study was to investigate the impact of RBD on the longitudinal change of motor and nonmotor symptoms in patients with PD.

METHODS

Patients with early PD (diagnosed within 3.5 years) recruited from 2010 to 2019 were followed every 18 months in the Oxford Parkinson's Disease Centre Discovery cohort. At each visit, we used standard questionnaires and measurements to assess demographic features and motor and nonmotor symptoms (including RBD, daytime sleepiness, mood, autonomic symptoms, cognition, and olfaction). Data were analyzed with linear mixed effects and Cox regression models. Possible RBD (pRBD) was longitudinally determined according to RBD Screening Questionnaire scores.

RESULTS

A total of 923 patients were recruited (mean age: 67.1 ± 9.59 years; 35.9% female), and 788 had follow-up assessment(s) (mean: 4.8 ± 1.98 years, range: 1.3-8.3). Among them, 33.3% were identified as pRBD (PD + pRBD). Patients with PD + pRBD had more severe baseline symptoms and showed faster progression on Movement Disorder Society-Unified Parkinson's Disease Rating Scale parts I and III, Purdue Pegboard test, and Beck Depression Inventory scores. Moreover, PD + pRBD was associated with an increased level of risk for mild cognitive impairment (hazard ratio [HR] = 1.36, 95% confidence interval [CI]: 1.01-1.83), freezing of gait (HR = 1.42, 95% CI: 1.10-1.86), and frequent falling (HR = 1.62, 95% CI: 1.02-2.60).

CONCLUSIONS

Patients with PD + pRBD progress faster on motor, mood, and cognitive symptoms, confirming a more aggressive PD subtype that can be identified at baseline and has major clinical implications. © 2021 International Parkinson and Movement Disorder Society.

Calcitriol Alleviates MPP+- and MPTP-Induced Parthanatos Through the VDR/PARP1 Pathway in the Model of Parkinson's Disease

The pathogenesis of Parkinson’s disease (PD) is currently unclear. Recent studies have suggested a correlation between vitamin D and PD. Vitamin D and its analogs have protective effects in animal models of PD, but these studies have not clarified the mechanism. Parthanatos is a distinct type of cell death caused by excessive activation of poly (ADP-ribose) polymerase-1 (PARP1), and the activation of PARP1 in PD models suggests that parthanatos may exist in PD pathophysiology. 1,25-Dihydroxyvitamin D3 (calcitriol) is a potential inhibitor of PARP1 in macrophages. This study aimed to investigate whether calcitriol treatment improves PD models and its effects on the parthanatos pathway. A 1-methyl-4-phenylpyridinium (MPP⁺)-induced cell model and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) subacute animal model were selected as the in vitro and in vivo PD models, and calcitriol was applied in these models. Results showed that parthanatos existed in the MPP⁺-induced cell model and pretreatment with calcitriol improved cell viability, reduced the excessive activation of PARP1, and relieved parthanatos. The application of calcitriol in the MPTP subacute animal model also improved behavioral tests, restored the damage to dopamine neurons, and reduced the activation of PARP1-related signaling pathways. To verify whether calcitriol interacts with PARP1 through its vitamin D receptor (VDR), siRNA, and overexpression plasmids were used to downregulate or overexpress VDR. Following the downregulation of VDR, the expression and activation of PARP1 increased and PARP1 was inhibited when VDR was overexpressed. Coimmunoprecipitation verified the combination of VDR and PARP1. In short, calcitriol can substantially improve parthanatos in the MPP⁺-induced cell model and MPTP model, and the protective effect might be partly through the VDR/PARP1 pathway, which provides a new possibility for the treatment of PD.

Prodromal Parkinson disease subtypes - key to understanding heterogeneity

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.

Deep sequencing of sncRNAs reveals hallmarks and regulatory modules of the transcriptome during Parkinson’s disease progression

Noncoding RNAs have diagnostic and prognostic importance in Parkinson's disease (PD). We studied circulating small noncoding RNAs (sncRNAs) in two large-scale longitudinal PD cohorts (Parkinson's Progression Markers Initiative (PPMI) and Luxembourg Parkinson's Study (NCER-PD)) and modeled their impact on the transcriptome. Sequencing of sncRNAs in 5,450 blood samples of 1,614 individuals in PPMI yielded 323 billion reads, most of which mapped to microRNAs but covered also other RNA classes such as piwi-interacting RNAs, ribosomal RNAs and small nucleolar RNAs. Dysregulated microRNAs associated with disease and disease progression occur in two distinct waves in the third and seventh decade of life. Originating predominantly from immune cells, they resemble a systemic inflammation response and mitochondrial dysfunction, two hallmarks of PD. Profiling 1,553 samples from 1,024 individuals in the NCER-PD cohort validated biomarkers and main findings by an independent technology. Finally, network analysis of sncRNA and transcriptome sequencing from PPMI identified regulatory modules emerging in patients with progressing PD.

Spectral characteristics of subthalamic nucleus local field potentials in Parkinson's disease: Phenotype and movement matter

Parkinson's disease (PD) is clinically heterogeneous across patients and may be classified in three motor phenotypes: tremor dominant (TD), postural instability and gait disorder (PIGD), and undetermined. Despite the significant clinical characterization of motor phenotypes, little is known about how electrophysiological data, particularly subthalamic nucleus local field potentials (STN-LFP), differ between TD and PIGD patients. This is relevant since increased STN-LFP bandpower at α-β range (8-35 Hz) is considered a potential PD biomarker and, therefore, a critical setpoint to drive adaptive deep brain stimulation. Acknowledging STN-LFP differences between phenotypes, mainly in rest and movement states, would better fit DBS to clinical and motor demands. We studied this issue through spectral analyses on 35 STN-LFP in TD and PIGD patients during rest and movement. We demonstrated that higher β₂ activity (22-35 Hz) was observed in PIGD only during rest. Additionally, bandpower differences between rest and movement occurred at the α-β range, but with different patterns as per phenotypes: movement-induced desynchronization concerned lower frequencies in TD (10-20 Hz) and higher frequencies in PIGD patients (21-28 Hz). Finally, when supervised learning algorithms were employed aiming to discriminate PD phenotypes based on STN-LFP bandpower features, movement information had improved the classification accuracy, achieving peak performances when TD and PIGD movement-induced desynchronization ranges were considered. These results suggest that STN-LFP β-band encodes phenotype-movement dependent information in PD patients.

Association of lipid levels with motor and cognitive function and decline in advanced Parkinson's disease in the Mark-PD study

OBJECTIVES

In prospective cohort studies different blood lipid fractions have been identified as risk factors of Parkinson's disease (PD). However, data relating lipoproteins to disease phenotypes and progression in advanced PD patients are sparse. Therefore, we assessed the most common lipoproteins in a case-control design and evaluated their associations with motor and cognitive function and decline in PD patients.

METHODS

Triglycerides, LDL-cholesterol (LDL-C), HDL-cholesterol (HDL-C), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), and lipoprotein a (Lp(a)) were analyzed in 294 PD patients of the MARK-PD study cohort and 588 controls matched for age, sex and cardiovascular risk factors. In PD patients, motor (MDS-UPDRS III, Hoehn-Yahr stage) and cognitive function (MoCA) were examined. In a sub-cohort (n = 98 patients), baseline lipid levels were correlated with motor and cognitive disease progression during a follow-up period of 523 ± 199 days.

RESULTS

At baseline, HDL-C levels were lower in PD patients compared to matched controls after adjustment. We observed a very weak association of Lp(a) levels with UDPRS III scores. In cross-sectional analyses, no other lipid fraction revealed a significant and consistent association with motor or cognitive function. During follow-up, no lipid fraction level was associated with motor or cognitive progression.

CONCLUSION

In advanced PD, there is no strong and consistent association of lipid levels with motor or cognitive function and decline.

Biochemical markers for severity and risk in GBA and LRRK2 Parkinson's disease

BACKGROUND

The phenotype of Parkinson's disease (PD) is variable with mutations in genes such as LRRK2 and GBA explaining part of this heterogeneity. Additional genetic and environmental factors contribute to disease variability.

OBJECTIVE

To assess the association between biochemical markers, PD severity and probability score for prodromal PD, among GBA and LRRK2 mutation carriers.

METHODS

Levels of uric acid, vitamin D, C-reactive protein, microalbumin/creatinine ratio (ACR), white blood count (WBC), hemoglobin, platelets, neutrophil/lymphocyte ratio and estimated glomerular filtration rate (eGFR) were assessed from patients with PD and non-manifesting carriers (NMC) of mutations in GBA and LRRK2, together with disease related questionnaires enabling the construction of the MDS prodromal probability score.

RESULT

A total of 241 patients with PD: 105 idiopathic PD (iPD), 49 LRRK2-PD and 87 GBA-PD and 412 non-manifesting subjects; 74 LRRK2-NMC, 118 GBA-NMC and 220 non-manifesting non-carriers (NMNC), participated in this study. No significant differences in biochemical measures were detected among patients with PD or non-manifesting carriers. Among GBA-PD patients, worse motor performance was associated with ACR (B = 4.68, 95% CI (1.779-7.559); p = 0.002). The probability score for prodromal PD among all non-manifesting participants was associated with eGFR; NMNC (B = - 0.531 95% CI (- 0.879 to - 0.182); p < 0.001, LRRK2-NMC (B = - 1.014 95% CI (- 1.663 to - 0.366); p < 0.001) and GBA-NMC (B = - 0.686 95% CI (1.300 to - 0.071); p = 0.029).

CONCLUSION

Sub-clinical renal impairment is associated with increased likelihood for prodromal PD regardless of genetic status. While the mechanism behind this finding needs further elucidation, it suggests that kidney function might play a role in PD pathogenesis.

Parkinson's Disease Subtypes: Critical Appraisal and Recommendations

BACKGROUND

In Parkinson's disease (PD), there is heterogeneity in the clinical presentation and underlying biology. Research on PD subtypes aims to understand this heterogeneity with potential contribution for the knowledge of disease pathophysiology, natural history and therapeutic development. There have been many studies of PD subtypes but their impact remains unclear with limited application in research or clinical practice.

OBJECTIVE

To critically evaluate PD subtyping systems.

METHODS

We conducted a systematic review of PD subtypes, assessing the characteristics of the studies reporting a subtyping system for the first time. We completed a critical appraisal of their methodologic quality and clinical applicability using standardized checklists.

RESULTS

We included 38 studies. The majority were cross-sectional (n = 26, 68.4%), used a data-driven approach (n = 25, 65.8%), and non-clinical biomarkers were rarely used (n = 5, 13.1%). Motor characteristics were the domain most commonly reported to differentiate PD subtypes. Most of the studies did not achieve the top rating across items of a Methodologic Quality checklist. In a Clinical Applicability Checklist, the clinical importance of differences between subtypes, potential treatment implications and applicability to the general population were rated poorly, and subtype stability over time and prognostic value were largely unknown.

CONCLUSION

Subtyping studies undertaken to date have significant methodologic shortcomings and most have questionable clinical applicability and unknown biological relevance. The clinical and biological signature of PD may be unique to the individual, rendering PD resistant to meaningful cluster solutions. New approaches that acknowledge the individual-level heterogeneity and that are more aligned with personalized medicine are needed.

Recent advances in understanding and treatment of Parkinson's disease

Though primarily a sporadic condition, Parkinson’s disease is increasingly recognized to be a multifactorial disease with a strong genetic component. At a cellular level, disruptions of protein trafficking and recycling, particularly by misfolding, accumulation, and aggregation of α-synuclein, mitochondrial dysfunction, oxidative stress, and other etiopathogenic mechanisms, have been found to result in the death of vulnerable neuronal populations and appear to drive the neurodegeneration underlying Parkinson’s disease. The improved understanding of these mechanisms has led to the development of novel pathogenesis-targeted and potentially disease-modifying therapeutic approaches in Parkinson’s disease. Until these treatments are fully developed and approved, clinicians must rely on therapies designed to improve quality of life of patients by treating various motor and non-motor symptoms of the disease.