Biomarkers of Parkinson's Disease: An Introduction

Unveiling Parkinson's disease through biomarker research: current insights and future prospects

Parkinson's disease (PD) is a neurodegenerative condition marked by the gradual depletion of dopaminergic neurons in the substantia nigra. Despite substantial strides in comprehending potential causative mechanisms, the validation of biomarkers with unequivocal evidence for routine clinical application remains elusive. Consequently, the diagnosis heavily relies on patients' clinical assessments and medical backgrounds. The imperative need for diagnostic and prognostic biomarkers arises due to the prevailing limitations of treatments, which predominantly address symptoms without modifying the disease course. This comprehensive review aims to elucidate the existing landscape of diagnostic and prognostic biomarkers for PD, drawing insights from contemporary literature.

Budget-Based Classification of Parkinson's Disease From Resting State EEG

Early detection is vital for future neuroprotective treatments of Parkinson's disease (PD). Resting state electroencephalographic (EEG) recording has shown potential as a cost-effective means to aid in detection of neurological disorders such as PD. In this study, we investigated how the number and placement of electrodes affects classifying PD patients and healthy controls using machine learning based on EEG sample entropy. We used a custom budget-based search algorithm for selecting optimized sets of channels for classification, and iterated over variable channel budgets to investigate changes in classification performance. Our data consisted of 60-channel EEG collected at three different recording sites, each of which included observations collected both eyes open (total N = 178) and eyes closed (total N = 131). Our results with the data recorded eyes open demonstrated reasonable classification performance (ACC = .76; AUC = .76) with only 5 channels placed far away from each other, the selected regions including right-frontal, left-temporal and midline-occipital sites. Comparison to randomly selected subsets of channels indicated improved classifier performance only with relatively small channel-budgets. The results with the data recorded eyes closed demonstrated consistently worse classification performance (when compared to eyes open data), and classifier performance improved more steadily as a function of number of channels. In summary, our results suggest that a small subset of electrodes of an EEG recording can suffice for detecting PD with a classification performance on par with a full set of electrodes. Furthermore our results demonstrate that separately collected EEG data sets can be used for pooled machine learning based PD detection with reasonable classification performance.

Does the 5-2-1 criteria identify patients with advanced Parkinson's disease? Real-world screening accuracy and burden of 5-2-1-positive patients in 7 countries

BACKGROUND

The burden of Parkinson's disease (PD) worsens with disease progression. However, the lack of objective and uniform disease classification challenges our understanding of the incremental burden in patients with advanced Parkinson's disease (APD) and suboptimal medication control. The 5-2-1 criteria was proposed by clinical consensus to identify patients with advancing PD. Our objective was to evaluate the screening accuracy and incremental clinical burden, healthcare resource utilization (HCRU), and humanistic burden in PD patients meeting the 5-2-1 screening criteria.

METHODS

Data were drawn from the Adelphi Parkinson's Disease Specific Program (DSP™), a multi-country point-in-time survey (2017-2020). People with PD who were naive to device-aided therapy and on oral PD therapy were included. Patients meeting the 5-2-1 screening criteria had one or more of the three clinical indicators of APD: (i) ≥5 doses of oral levodopa/day, OR (ii) "off" symptoms for ≥2 h of waking day, OR (iii) ≥1 h of troublesome dyskinesia. Clinician assessment of PD stage was used as the reference in this study. Clinical screening accuracy of the 5-2-1 criteria was assessed using area under the curve and multivariable logistic regression models. Incremental clinical, HCRU, and humanistic burden were assessed by known-group comparisons between 5 and 2-1-positive and negative patients.

RESULTS

From the analytic sample (n = 4714), 33% of patients met the 5-2-1 screening criteria. Among physician-classified APD patients, 78.6% were 5-2-1 positive. Concordance between clinician judgment and 5-2-1 screening criteria was > 75%. 5-2-1-positive patients were nearly 7-times more likely to be classified as APD by physician judgment. Compared with the 5-2-1-negative group, 5-2-1-positive patients had significantly higher clinical, HCRU, and humanistic burden across all measures. In particular, 5-2-1-positive patients had 3.8-times more falls, 3.6-times higher annual hospitalization rate, and 3.4-times greater dissatisfaction with PD treatment. 5-2-1-positive patients also had significantly lower quality of life and worse caregiver burden.

CONCLUSIONS

5-2-1 criteria demonstrated potential as a screening tool for identifying people with APD with considerable clinical, humanistic, and HCRU burden. The 5-2-1 screening criteria is an objective and reliable tool that may aid the timely identification and treatment optimization of patients inadequately controlled on oral PD medications.

Genetic Markers as Risk Factors for the Development of Impulsive-Compulsive Behaviors in Patients with Parkinson's Disease Receiving Dopaminergic Therapy

Impulsive–compulsive and related behavioral disorders (ICD) are drug-induced non-motor symptoms of Parkinson’s disease (PD). Recently research has focused on evaluating whether ICD could be predicted and managed using a pharmacogenetic approach based on dopaminergic therapies, which are the main risk factors. The aim of our study was to evaluate the role of candidate genes such as DBH, DRD2, MAOA, BDNF, COMT, SLC6A4, SLC6A3, ACE, DRD1 gene polymorphisms in the pathogenesis of ICD in PD. We compared patients with PD and ICD (n = 49), patients with PD without ICD (n = 36) and a healthy control group (n = 365). ICD was diagnosed using the QUIP questionnaires and specific diagnostic criteria for subtypes of ICD. Genotyping was conducted using a number of PCR techniques and SNaPshot. Statistical analysis was performed using WinPepi and APSampler v3.6 software. PCA testing was conducted using RStudio software v1.4.1106-5. The following substitutions showed statistically significant correlations with PD and ICD: DBH (rs2097629, rs1611115), DRD2 (rs6275, rs12364283, rs1076560), ACE (rs4646994), DRD1 (rs686), BDNF (rs6265), these associations are novel in Russian PD patients. Our findings suggest that polymorphisms in DBH, BDNF, DRD2, ACE genes in Russian subjects are associated with an increased risk of ICD development.

Investigation of α-Synuclein Species in Plasma Exosomes and the Oligomeric and Phosphorylated α-Synuclein as Potential Peripheral Biomarker of Parkinson's Disease

α-Synuclein (α-syn), especially its abnormal oligomeric and phosphorylated form, plays a critical role in the pathogenesis of Parkinson's disease (PD). Plasma exosomal α-syn species have been shown to be a promising PD biomarker. However, whether different α-syn species in plasma exosomes (the oligomeric α-syn and the Ser129 phosphorylated α-syn (p-α-syn)) which represent the PD pathogenesis in the brain could be specific peripheral PD biomarker haven't been well elucidated. In this study, we successfully extracted and identified the human plasma exosomes, and the CNS-derived exosomes were detected. The different aggregation status, localization and degradation characteristics of α-syn and p-α-syn in the plasma exosomes between PD patients and healthy controls were further analyzed. The results suggested that α-syn and p-α-syn in the plasma exosomes of PD patients showed poor solubility after protease K (PK) treatment. Aggregated α-syn and p-α-syn existed both inside and on the membrane surface of plasma exosomes. The Receiver operating characteristic (ROC) performance of α-syn oligomer/total α-syn in exosomes was moderately helpful in PD diagnosis (AUC = 0.71, sensitivity = 60.5%, specificity = 59.4%), and the ratio of p-α-syn oligomer/total p-α-syn showed similar result (AUC = 0.69, sensitivity = 60.0%, specificity = 59.5%). This study indicates that the oligomeric α-syn/total α-syn and oligomeric p-α-syn/total p-α-syn ratio in plasma exosomes may be applied to assist the PD diagnosis, which needs further research.

Creation of a gene expression classifier for predicting Parkinson's disease rate of progression

Parkinson's disease (PD) etiology is heterogeneous, genetic, and multi-factorial, resulting in a varied disease from a mild slow progression to a more severe rapid progression. Prognostic information on the nature of the patient's disease at diagnosis aids the physician in counseling patients on treatment options and life planning. In a cohort of PD patients from the PPMI study, the relative gene expression levels of SKP1A, UBE2K, ALDH1A1, PSMC4, HSPA8 and LAMB2 were measured in baseline blood samples by real-time quantitative PCR. At baseline PD patients were up to 2 years from diagnosis, H&Y scale ≤ 2 and PD treatment naïve. PD-Prediction algorithm comprised of ALDH1A1, LAMB2, UBE2K, SKP1A and age was created by logistic regression for predicting progression to ≤ 70% Modified Schwab and England Activities of Daily Living (S&E-ADL). In relation to patients negative for PD-Prediction (n = 180), patients positive (n = 30) for Cutoff-1 (at 82% specificity, 80.0% sensitivity) had positive hazard ratio (HR+) of 10.6 (95% CI, 2.2-50.1), and positive (n = 23) for Cutoff-2 (at 93% specificity, 47% sensitivity) had HR+ of 17.1 (95% CI, 3.2-89.9) to progress to ≤ 70% S&E-ADL within 3 years (P value < 0.0001). Likewise, patients positive for PD-Prediction Cutoff-1 (n = 49) had HR+ 4.3 (95% CI, 1.6-11.6) for faster time to H&Y 3 in relation to patients negative (n = 170) for PD-Prediction (P value = 0.0002). Our findings show an algorithm that seems to predict fast PD progression and may potentially be used as a tool to assist the physician in choosing an optimal treatment plan, improving the patient's quality of life and overall health outcome.

Non-motor Parkinson disease: new concepts and personalised management

Most patients with Parkinson disease (PD) have non-motor symptoms (NMS), and on average these can range from four to 19 different symptoms. NMS dominate the prodromal phase of PD and some may serve as clinical biomarkers of PD. NMS can be dopaminergic, non-dopaminergic, of genetic origin or drug induced. Clinical assessment of NMS should include the NMS Questionnaire (completed by patients) for screening, as recommended by the International Parkinson and Movement Disorders Society and other international societies. The total number of NMS in a patient with PD constitutes the NMS burden, which can be graded using validated cut-off scores on the NMS Questionnaire and Scale and can be used as an outcome measure in clinical trials. Despite NMS burden having a major effect on the quality of life of patients and carers, a large European study showed that NMS are often ignored in the clinic. The syndromic nature of PD is underpinned by non-motor subtypes which are likely to be related to specific dysfunction of cholinergic, noradrenergic, serotonergic pathways in the brain, not just the dopaminergic pathways. NMS can be treated by dopaminergic and non-dopaminergic strategies, but further robust studies supported by evidence from animal models are required. The future of modern treatment of PD needs to be supported by the delivery of personalised medicine.

Societal Burden and Persisting Unmet Needs of Parkinson’s Disease

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Dietary Variations in a Multiethnic Parkinson's Disease Cohort and Possible Influences on Nonmotor Aspects: A Cross-Sectional Multicentre Study

Dietary habits may differ between Parkinson's disease (PD) patients of different ethnicities. The primary aim of this cross-sectional analysis was to compare dietary habits in a multiethnic PD population and investigate potential nonmotor differences. All patients completed a dietary habits questionnaire. Besides basic demographics, patients' motor involvement (Hoehn and Yahr (HY)) and nonmotor symptoms (Nonmotor Symptoms Scale; Hospital Anxiety and Depression Scale) were assessed. 139 PD patients were included (mean age 66.8 ± 11.6 years; 61.2% male; mean disease duration 6.2 ± 5.2 years; median HY 3): 47.5% were White, 24.5% Asian, and 28.0% Black African and Caribbean (BAC). We found dietary differences between the groups, including a greater frequency of vegetarians and greater consumption of cumin, turmeric, and cinnamon as well as lower consumption of beef in Asian patients than in White and BAC and greater consumption of chili than in White patients and higher consumption of pork in White than Asian and BAC patients. There were no significant differences in dietary supplement consumption after correction for multiple comparisons. None of the dietary factors examined were associated with differences in nonmotor symptoms. Diet and supplement use vary in PD patients across ethnicities, this is both a problem and opportunity for nutritional medicine research. These data support the importance of considering ethnic diversity as part of recruitment strategy in nutrition and clinical studies.

Paradoxical Decision-Making: A Framework for Understanding Cognition in Parkinson's Disease

People with Parkinson's disease (PD) show impaired decision-making when sensory and memory information must be combined. This recently identified impairment results from an inability to accumulate the proper amount of information needed to make a decision and appears to be independent of dopamine tone and reinforcement learning mechanisms. Although considerable work focuses on PD and decisions involving risk and reward, in this Opinion article we propose that the emerging findings in perceptual decision-making highlight the multisystem nature of PD, and that unraveling the neuronal circuits underlying perceptual decision-making impairment may help in understanding other cognitive impairments in people with PD. We also discuss how a decision-making framework may be extended to gain insights into mechanisms of motor impairments in PD.

Update on visual function and choroidal-retinal thickness alterations in Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative process that affects 7.5 million people around the world. Since 2004, several studies have demonstrated changes in various retinal layers in PD using optical coherence tomography (OCT). However, there are some discrepancies in the results of those studies. Some of them have correlated retinal thickness with the severity or duration of the disease, demonstrating that OCT measurements may be an innocuous and easy biomarker for PD progression. Other studies have demonstrated visual dysfunctions since early phases of the disease. Lastly, the most recent studies that use Swept Source OCT technology, have found choroidal thickness increase in PD patients and provide new information related to the retinal degenerative process in this disease. The aim of this paper is to review the literature on OCT and PD, in order to determine the altered retinal and choroidal parameters in PD and their possible clinical usefulness, and also the visual dysfunctions with higher impact in these patients.

Advanced Parkinson's or "complex phase" Parkinson's disease? Re-evaluation is needed

Holistic management of Parkinson's disease, now recognised as a combined motor and nonmotor disorder, remains a key unmet need. Such management needs relatively accurate definition of the various stages of Parkinson's from early untreated to late palliative as each stage calls for personalised therapies. Management also needs to have a robust knowledge of the progression pattern and clinical heterogeneity of the presentation of Parkinson's which may manifest in a motor dominant or nonmotor dominant manner. The "advanced" stages of Parkinson's disease qualify for advanced treatments such as with continuous infusion or stereotactic surgery yet the concept of "advanced Parkinson's disease" (APD) remains controversial in spite of growing knowledge of the natural history of the motor syndrome of PD. Advanced PD is currently largely defined on the basis of consensus opinion and thus with several caveats. Nonmotor aspects of PD may also reflect advancing course of the disorder, so far not reflected in usual scale based assessments which are largely focussed on motor symptoms. In this paper, we discuss the problems with current definitions of "advanced" PD and also propose the term "complex phase" Parkinson's disease as an alternative which takes into account a multimodal symptoms and biomarker based approach in addition to patient preference.