Longitudinal CSF biomarkers in patients with early Parkinson disease and healthy controls

Neuroimaging and fluid biomarkers in Parkinson's disease in an era of targeted interventions

A major challenge in Parkinson's disease is the variability in symptoms and rates of progression, underpinned by heterogeneity of pathological processes. Biomarkers are urgently needed for accurate diagnosis, patient stratification, monitoring disease progression and precise treatment. These were previously lacking, but recently, novel imaging and fluid biomarkers have been developed. Here, we consider new imaging approaches showing sensitivity to brain tissue composition, and examine novel fluid biomarkers showing specificity for pathological processes, including seed amplification assays and extracellular vesicles. We reflect on these biomarkers in the context of new biological staging systems, and on emerging techniques currently in development.

Neuroimaging and plasma evidence of early white matter loss in Parkinson's disease with poor outcomes

Parkinson's disease is a common and debilitating neurodegenerative disorder, with over half of patients progressing to postural instability, dementia or death within 10 years of diagnosis. However, the onset and rate of progression to poor outcomes is highly variable, underpinned by heterogeneity in underlying pathological processes. Quantitative and sensitive measures predicting poor outcomes will be critical for targeted treatment, but most studies to date have been limited to a single modality or assessed patients with established cognitive impairment. Here, we used multimodal neuroimaging and plasma measures in 98 patients with Parkinson's disease and 28 age-matched controls followed up over 3 years. We examined: grey matter (cortical thickness and subcortical volume), white matter (fibre cross-section, a measure of macrostructure; and fibre density, a measure of microstructure) at whole-brain and tract level; structural and functional connectivity; and plasma levels of neurofilament light chain and phosphorylated tau 181. We evaluated relationships with subsequent poor outcomes, defined as development of mild cognitive impairment, dementia, frailty or death at any time during follow-up, in people with Parkinson's disease. We show that extensive white matter macrostructural changes are already evident at baseline assessment in people with Parkinson's disease who progress to poor outcomes (n = 31): with up to 19% reduction in fibre cross-section in multiple tracts, and a subnetwork of reduced structural connectivity strength, particularly involving connections between right frontoparietal and left frontal, right frontoparietal and left parietal and right temporo-occipital and left parietal modules. In contrast, grey matter volumes and functional connectivity were preserved in people with Parkinson's disease with poor outcomes. Neurofilament light chain, but not phosphorylated tau 181 levels were increased in people with Parkinson's disease with poor outcomes, and correlated with white matter loss. These findings suggest that imaging sensitive to white matter macrostructure and plasma neurofilament light chain may be useful early markers of poor outcomes in Parkinson's disease. As new targeted treatments for neurodegenerative disease are emerging, these measures show important potential to aid patient selection for treatment and improve stratification for clinical trials.

An interactive web application to identify early Parkinsonian non-tremor-dominant subtypes

BACKGROUND

Parkinson's disease (PD) patients with tremor-dominant (TD) and non-tremor-dominant (NTD) subtypes exhibit heterogeneity. Rapid identification of different motor subtypes may help to develop personalized treatment plans.

METHODS

The data were acquired from the Parkinson's Disease Progression Marker Initiative (PPMI). Following the identification of predictors utilizing recursive feature elimination (RFE), seven classical machine learning (ML) models, including logistic regression, support vector machine, decision tree, random forest, extreme gradient boosting, etc., were trained to predict patients' motor subtypes, evaluating the performance of models through the area under the receiver operating characteristic curve (AUC) and validating by the follow-up data.

RESULTS

The feature subset engendered by RFE encompassed 20 features, comprising some clinical assessments and cerebrospinal fluid α-synuclein (CSF α-syn). ML models fitted in the RFE subset performed better in the test and validation sets. The best performing model was support vector machines with the polynomial kernel (P-SVM), achieving an AUC of 0.898. Five-fold repeated cross-validation showed the P-SVM model with CSF α-syn performed better than the model without CSF α-syn (P = 0.034). The Shapley additive explanation plot (SHAP) illustrated that how the levels of each feature affect the predicted probability as NTD subtypes.

CONCLUSION

An interactive web application was developed based on the P-SVM model constructed from feature subset by RFE. It can identify the current motor subtypes of PD patients, making it easier to understand the status of patients and develop personalized treatment plans.

The neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, and neutrophil-to-high-density-lipoprotein ratio are correlated with the severity of Parkinson's disease

Background

Inflammation plays a pivotal role in the pathogenesis of Parkinson's disease (PD). However, the correlation between peripheral inflammatory markers and the severity of PD remains unclear.

Methods

The following items in plasma were collected for assessment among patients with PD (n = 303) and healthy controls (HCs; n = 303) were assessed for the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR) and neutrophil-to-high-density-lipoprotein ratio (NHR) in plasma, and neuropsychological assessments were performed for all patients with PD. Spearman rank or Pearson correlation was used to evaluate the correlation between the NLR, the LMR and the NHR and the severity of PD. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of the NLR, LMR and NHR for PD.

Results

The plasma NLR and NHR were substantially higher in patients with PD than in HCs, while the plasma LMR was substantially lower. The plasma NLR was positively correlated with Hoehn and Yahr staging scale (H&Y), Unified Parkinson's Disease Rating Scale (UPDRS), UPDRS-I, UPDRS-II, and UPDRS-III scores. Conversely, it exhibited a negative relationship with Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Furthermore, the plasma NHR was positively correlated with H&Y, UPDRS, UPDRS-I, UPDRS-II and UPDRS-III scores. Moreover, negative associations were established between the plasma LMR and H&Y, UPDRS, UPDRS-I, UPDRS-II, and UPDRS-III scores. Finally, based on the ROC curve analysis, the NLR, LMR and NHR exhibited respectable PD discriminating power.

Conclusion

Our research indicates that a higher NLR and NHR and a lower LMR may be relevant for assessing the severity of PD and appear to be promising disease-state biomarker candidates.

Prevalence of Concomitant Pathologies in Parkinson's Disease: Implications for Prognosis, Diagnosis, and Insights into Common Pathogenic Mechanisms

Pathologies characteristic of Alzheimer's disease (i.e., hyperphosphorylated tau and amyloid-β (Aβ) plaques), cardiovascular disease, and limbic predominant TDP-43 encephalopathy (LATE) often co-exist in patients with Parkinson's disease (PD), in addition to Lewy body pathology (α-synuclein). Numerous studies point to a putative synergistic relationship between hyperphosphorylation tau, Aβ, cardiovascular lesions, and TDP-43 with α-synuclein, which may alter the stereotypical pattern of pathological progression and accelerate cognitive decline. Here we discuss the prevalence and relationships between common concomitant pathologies observed in PD. In addition, we highlight shared genetic risk factors and developing biomarkers that may provide better diagnostic accuracy for patients with PD that have co-existing pathologies. The tremendous heterogeneity observed across the PD spectrum is most likely caused by the complex interplay between pathogenic, genetic, and environmental factors, and increasing our understanding of how these relate to idiopathic PD will drive research into finding accurate diagnostic tools and disease modifying therapies.

Cerebrospinal fluid biomarkers profile in scans without evidence of dopaminergic deficits (SWEDD)

Background

A small proportion of patients with clinical parkinsonism have normal transporter-single photon emission computed tomography (DaTSPECT) which is commonly defined as scans without evidence of dopaminergic deficits (SWEDD). A better understanding of SWEDD can improve the current therapeutic options and appropriate disease monitoring.

Aim

We aimed to assess CSF biomarkers levels including α-synuclein (α-syn), amyloid βeta (Aβ1-42), total tau (t-tau), and phosphorylated tau (p-tau) in SWEDD and investigate the longitudinal alteration in the CSF profile.

Methods

In total, 406 early-stage PD, 58 SWEDD, and 187 healthy controls (HCs) were entered into our study from PPMI. We compared the level of CSF biomarkers at baseline, six months, one year, and two years. Furthermore, the longitudinal alteration of CSF biomarkers was explored in each group using linear mixed models.

Results

There was no significant difference in the level of CSF α-syn Aβ1-42, t-tau, and p-tau between HCs and SWEDD at different time points. Investigating the level of CSF α-syn in PD and SWEDD showed a significant difference at one (p = 0.016) and two years (p = 0.006). Also, we observed a significant difference in the level of CSF Aβ1-42 between SWEDD and PD at one year (p = 0.012). Moreover, there was a significant difference in the level of CSF t-tau between SWEDD and PD subjects at one (p = 0.013) and two years (p = 0.017). Furthermore, there was a significant difference in the level of CSF p-tau between SWEDD and PD groups at two years visits (p = 0.030). Longitudinal analysis showed a significant decrease after one (p = 0.029) and two years (p = 0.002) from baseline in the level of CSF α-syn only in the PD group. Also, we observed that the level of CSF Aβ1-42 significantly increased after one year in SWEDD (p = 0.031) and decreased after two years from baseline in PD subjects (p = 0.005). Moreover, there was a significant increase in the level of CSF t-tau after two years (p = 0.036) and CSF p-tau after six months from baseline in SWEDD subjects (p = 0.011).

Conclusion

This finding suggests a faster neurodegeneration process in PD patients compared to SWEDD at least based on these biomarkers. Future studies with longer follow-up duration and more sample sizes are necessary to validate our results.

Tau: a biomarker of Huntington's disease

Developing effective treatments for patients with Huntington's disease (HD)-a neurodegenerative disorder characterized by severe cognitive, motor and psychiatric impairments-is proving extremely challenging. While the monogenic nature of this condition enables to identify individuals at risk, robust biomarkers would still be extremely valuable to help diagnose disease onset and progression, and especially to confirm treatment efficacy. If measurements of cerebrospinal fluid neurofilament levels, for example, have demonstrated use in recent clinical trials, other proteins may prove equal, if not greater, relevance as biomarkers. In fact, proteins such as tau could specifically be used to detect/predict cognitive affectations. We have herein reviewed the literature pertaining to the association between tau levels and cognitive states, zooming in on Alzheimer's disease, Parkinson's disease and traumatic brain injury in which imaging, cerebrospinal fluid, and blood samples have been interrogated or used to unveil a strong association between tau and cognition. Collectively, these areas of research have accrued compelling evidence to suggest tau-related measurements as both diagnostic and prognostic tools for clinical practice. The abundance of information retrieved in this niche of study has laid the groundwork for further understanding whether tau-related biomarkers may be applied to HD and guide future investigations to better understand and treat this disease.

Extracellular Vesicles for the Diagnosis of Parkinson's Disease: Systematic Review and Meta-Analysis

Parkinson's disease (PD) biomarkers are needed by both clinicians and researchers (for diagnosis, identifying study populations, and monitoring therapeutic response). Imaging, genetic, and biochemical biomarkers have been widely studied. In recent years, extracellular vesicles (EVs) have become a promising material for biomarker development. Proteins and molecular material from any organ, including the central nervous system, can be packed into EVs and transported to the periphery into easily obtainable biological specimens like blood, urine, and saliva. We performed a systematic review and meta-analysis of articles (published before November 15, 2022) reporting biomarker assessment in EVs in PD patients and healthy controls (HCs). Biomarkers were analyzed using random effects meta-analysis and the calculated standardized mean difference (Std.MD). Several proteins and ribonucleic acids have been identified in EVs in PD patients, but only α-synuclein (aSyn) and leucine-rich repeat kinase 2 (LRRK2) were reported in sufficient studies (n = 24 and 6, respectively) to perform a meta-analysis. EV aSyn was significantly increased in neuronal L1 cell adhesion molecule (L1CAM)-positive blood EVs in PD patients compared to HCs (Std.MD = 1.84, 95% confidence interval = 0.76-2.93, P = 0.0009). Further analysis of the biological sample and EV isolation method indicated that L1CAM-IP (immunoprecipitation) directly from plasma was the best isolation method for assessing aSyn in PD patients. Upcoming neuroprotective clinical trials immediately need peripheral biomarkers for identifying individuals at risk of developing PD. Overall, the improved sensitivity of assays means they can identify biomarkers in blood that reflect changes in the brain. CNS-derived EVs in blood will likely play a major role in biomarker development in the coming years. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Charting the Next Road Map for CSF Biomarkers in Alzheimer's Disease and Related Dementias

Clinical prediction of underlying pathologic substrates in people with Alzheimer's disease (AD) dementia or related dementia syndromes (ADRD) has limited accuracy. Etiologic biomarkers - including cerebrospinal fluid (CSF) levels of AD proteins and cerebral amyloid PET imaging - have greatly modernized disease-modifying clinical trials in AD, but their integration into medical practice has been slow. Beyond core CSF AD biomarkers (including beta-amyloid 1-42, total tau, and tau phosphorylated at threonine 181), novel biomarkers have been interrogated in single- and multi-centered studies with uneven rigor. Here, we review early expectations for ideal AD/ADRD biomarkers, assess these goals' future applicability, and propose study designs and performance thresholds for meeting these ideals with a focus on CSF biomarkers. We further propose three new characteristics: equity (oversampling of diverse populations in the design and testing of biomarkers), access (reasonable availability to 80% of people at risk for disease, along with pre- and post-biomarker processes), and reliability (thorough evaluation of pre-analytical and analytical factors influencing measurements and performance). Finally, we urge biomarker scientists to balance the desire and evidence for a biomarker to reflect its namesake function, indulge data- as well as theory-driven associations, re-visit the subset of rigorously measured CSF biomarkers in large datasets (such as Alzheimer's disease neuroimaging initiative), and resist the temptation to favor ease over fail-safe in the development phase. This shift from discovery to application, and from suspended disbelief to cogent ingenuity, should allow the AD/ADRD biomarker field to live up to its billing during the next phase of neurodegenerative disease research.

Parkinson's disease therapy: what lies ahead?

The worldwide prevalence of Parkinson's disease (PD) has been constantly increasing in the last decades. With rising life expectancy, a longer disease duration in PD patients is observed, further increasing the need and socioeconomic importance of adequate PD treatment. Today, PD is exclusively treated symptomatically, mainly by dopaminergic stimulation, while efforts to modify disease progression could not yet be translated to the clinics. New formulations of approved drugs and treatment options of motor fluctuations in advanced stages accompanied by telehealth monitoring have improved PD patients care. In addition, continuous improvement in the understanding of PD disease mechanisms resulted in the identification of new pharmacological targets. Applying novel trial designs, targeting of pre-symptomatic disease stages, and the acknowledgment of PD heterogeneity raise hopes to overcome past failures in the development of drugs for disease modification. In this review, we address these recent developments and venture a glimpse into the future of PD therapy in the years to come.

Longitudinal hippocampal subfields, CSF biomarkers, and cognition in patients with Parkinson disease

Objective

Hippocampal atrophy is an indicator of emerging dementia in PD, though it is unclear whether cerebral spinal fluid (CSF) Abeta-42, t-tau, or alpha-syn predict hippocampal subfield atrophy in a de novo cohort of PD patients. To examine whether levels of CSF alpha-synuclein (alpha-syn), beta-amyloid 1-42 (Abeta-42), or total-tau (t-tau) are associated with hippocampal subfield volumes over time.

Methods

We identified a subset of Parkinson's Progression Markers Initiative (PPMI) de novo PD patients with longitudinal T1-weighted imaging (baseline plus at least two additional visits across 12, 24, and 48 months) and CSF biomarkers available at baseline. We performed cross-sectional, regression, and linear mixed model analyses to evaluate the baseline and longitudinal CSF biomarkers, hippocampal subfields, and cognition. A false discovery rate (FDR) was used to correct for multiple comparisons.

Results

88 PD-CN and 21 PD-MCI had high quality longitudinal data. PD-MCI patients exhibited reduced bilateral CA1 volumes relative to PD-CN, though there were no significant differences in CSF biomarkers between these groups. Relationships between CSF biomarkers and hippocampal subfields changed over time, with a general pattern that lower CSF Abeta-42, higher t-tau and higher alpha-syn were associated with smaller hippocampal subfields, primarily in the right hemisphere.

Conclusion

We replicated prior reports that demonstrated reduced CA1 volumes in PD-MCI in a de novo PD cohort. CSF biomarkers were associated with individual subfields, with evidence that the increased CSF t-tau was associated with smaller subiculum volumes at baseline and over time, though there was no clear indication that the subfields associated with cognition (CA1 and HATA) were associated with CSF biomarkers.

Ependyma in Neurodegenerative Diseases, Radiation-Induced Brain Injury and as a Therapeutic Target for Neurotrophic Factors

The neuron loss caused by the progressive damage to the nervous system is proposed to be the main pathogenesis of neurodegenerative diseases. Ependyma is a layer of ciliated ependymal cells that participates in the formation of the brain-cerebrospinal fluid barrier (BCB). It functions to promotes the circulation of cerebrospinal fluid (CSF) and the material exchange between CSF and brain interstitial fluid. Radiation-induced brain injury (RIBI) shows obvious impairments of the blood-brain barrier (BBB). In the neuroinflammatory processes after acute brain injury, a large amount of complement proteins and infiltrated immune cells are circulated in the CSF to resist brain damage and promote substance exchange through the BCB. However, as the protective barrier lining the brain ventricles, the ependyma is extremely vulnerable to cytotoxic and cytolytic immune responses. When the ependyma is damaged, the integrity of BCB is destroyed, and the CSF flow and material exchange is affected, leading to brain microenvironment imbalance, which plays a vital role in the pathogenesis of neurodegenerative diseases. Epidermal growth factor (EGF) and other neurotrophic factors promote the differentiation and maturation of ependymal cells to maintain the integrity of the ependyma and the activity of ependymal cilia, and may have therapeutic potential in restoring the homeostasis of the brain microenvironment after RIBI or during the pathogenesis of neurodegenerative diseases.

Microglia and Astrocytes Dysfunction and Key Neuroinflammation-Based Biomarkers in Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disease, with symptoms such as tremor, bradykinesia with rigidity, and depression appearing in the late stage of life. The key hallmark of PD is the loss or death of dopaminergic neurons in the region substantia nigra pars compacta. Neuroinflammation plays a key role in the etiology of PD, and the contribution of immunity-related events spurred the researchers to identify anti-inflammatory agents for the treatment of PD. Neuroinflammation-based biomarkers have been identified for diagnosing PD, and many cellular and animal models have been used to explain the underlying mechanism; however, the specific cause of neuroinflammation remains uncertain, and more research is underway. So far, microglia and astrocyte dysregulation has been reported in PD. Patients with PD develop neural toxicity, inflammation, and inclusion bodies due to activated microglia and a-synuclein-induced astrocyte conversion into A1 astrocytes. Major phenotypes of PD appear in the late stage of life, so there is a need to identify key early-stage biomarkers for proper management and diagnosis. Studies are under way to identify key neuroinflammation-based biomarkers for early detection of PD. This review uses a constructive analysis approach by studying and analyzing different research studies focused on the role of neuroinflammation in PD. The review summarizes microglia, astrocyte dysfunction, neuroinflammation, and key biomarkers in PD. An approach that incorporates multiple biomarkers could provide more reliable diagnosis of PD.

Mendelian Randomization Analysis Reveals No Causal Relationship Between Plasma α-Synuclein and Parkinson's Disease

So far, the studies exploring plasma α-synuclein as a biomarker of Parkinson's disease (PD) have provided contradictory results. Here, we first employed the Mendelian randomization (MR) approach to elucidate their potential causal relationship. Five genetic instrumental variables of plasma α-synuclein were acquired from two publicly available datasets. Three independent genome-wide association studies of PD were used as outcome cohorts (PD cohorts 1, 2, and 3). Two-sample MR analyses were conducted using inverse-variance weighted (IVW), MR-Egger, weighted median, simple mode, and leave-one-out methods. Though the IVW approach demonstrated positive plasma α-synuclein effect on the PD risk in three outcome cohorts (OR = 1.134, 1.164, and 1.189, respectively), the P values were all larger than 0.05. The conclusions were robust under complementary sensitivity analyses. Our results did not support the causal relationship between plasma α-synuclein and PD.

Cerebrospinal fluid alpha-synuclein, amyloid beta, total tau, and phosphorylated tau in tremor-dominant Parkinson's disease

BACKGROUND

Protein misfolding within specific brain regions is a common characteristic of neurodegenerative diseases, such as Alzheimer's disease and Parkinson's disease (PD). Therefore, a common term often used for these disorders is "proteinopathy". Currently, there has been increasing attention toward the overlap of pathogenesis between proteinopathies.

AIMS

We aimed to explore the cross-sectional and longitudinal level of the CSF α-synuclein (α-syn), amyloid βeta (Aβ1-42), total tau (t-tau), and phosphorylated tau (p-tau) in PD subjects with tremor dominant (TD) and a non-tremor dominant (nonTD) subtype from the Parkinson Progression Markers Initiative (PPMI).

METHODS

We enrolled 411 early-stage PD patients and 187 healthy controls (HCs) from the PPMI. We compared the level of CSF biomarkers at four time points including baseline, 6 months, 1 year, and 2 years. To investigate longitudinal changes in CSF proteins within each group, we used linear mixed models.

RESULTS

The level of CSF biomarkers was significantly lower in PD patients compared to HCs at any visit. Moreover, there was no statistically significant difference in the level of CSF α-syn, Aβ1-42, t-tau, and p-tau between PD-TD and PD-nonTD. Longitudinal analysis showed significant CSF α-syn reduction after one year from baseline in PD-TD patients (P = 0.047). Also, there was a significant reduction in the level of CSF Aβ1-42 after two years in PD-nonTD patients but not HCs and PD-TD (P = 0.033).

CONCLUSION

Our results indicate that different patterns in longitudinal changes of CSF biomarkers could be due to different pathophysiological mechanisms involved in each PD motor subtype.

Role of novel endpoints and evaluations of response in Parkinson disease

With progress in our understanding of Parkinson disease (PD) and other neurodegenerative disorders, from clinical features to imaging, genetic, and molecular characterization comes the opportunity to refine and revise how we measure these diseases and what outcome measures are used as endpoints in clinical trials. While several rater-, patient-, and milestone-based outcomes for PD exist that may serve as clinical trial endpoints, there remains an unmet need for endpoints that are clinically meaningful, patient centric while also being more objective and quantitative, less susceptible to effects of symptomatic therapy (for disease-modification trials), and that can be measured over a short period and yet accurately represent longer-term outcomes. Several novel outcomes that may be used as endpoints in PD clinical trials are in development, including digital measures of signs and symptoms, as well a growing array of imaging and biospecimen biomarkers. This chapter provides an overview of the state of PD outcome measures as of 2022, including considerations for selection of clinical trial endpoints in PD, advantages and limitations of existing measures, and emerging potential novel endpoints.

Diagnostic metabolomic profiling of Parkinson's disease biospecimens

BACKGROUND

Reliable and sensitive biomarkers are needed for enhancing and predicting Parkinson's disease (PD) diagnosis.

OBJECTIVE

To investigate comprehensive metabolomic profiling of biochemicals in CSF and serum for determining diagnostic biomarkers of PD.

METHODS

Fifty subjects, symptomatic with PD for ≥5 years, were matched to 50 healthy controls (HCs). We used ultrahigh-performance liquid chromatography linked to tandem mass spectrometry (UHPLC-MS/MS) for measuring relative concentrations of ≤1.5 kDalton biochemicals. A reference library created from authentic standards facilitated chemical identifications. Analytes underwent univariate analysis for PD association, with false discovery rate-adjusted p-value (≤0.05) determinations. Multivariate analysis (for identifying a panel of biochemicals discriminating PD from HCs) used several biostatistical methods, including logistic LASSO regression.

RESULTS

Comparing PD and HCs, strong differentiation was achieved from CSF but not serum specimens. With univariate analysis, 21 CSF compounds exhibited significant differential concentrations. Logistic LASSO regression led to selection of 23 biochemicals (11 shared with those determined by the univariate analysis). The selected compounds, as a group, distinguished PD from HCs, with Area-Under-the-Receiver-Operating-Characteristic (ROC) curve of 0.897. With optimal cutoff, logistic LASSO achieved 100% sensitivity and 96% specificity (and positive and negative predictive values of 96% and 100%). Ten-fold cross-validation gave 84% sensitivity and 82% specificity (and 82% positive and 84% negative predictive values). From the logistic LASSO-chosen regression model, 2 polyamine metabolites (N-acetylcadaverine and N-acetylputrescine) were chosen and had the highest fold-changes in comparing PD to HCs. Another chosen biochemical, acisoga (N-(3-acetamidopropyl)pyrrolidine-2-one), also is a polyamine metabolism derivative.

CONCLUSIONS

UHPLC-MS/MS assays provided a metabolomic signature highly predictive of PD. These findings provide further evidence for involvement of polyamine pathways in the neurodegeneration of PD.

Longitudinal striatal dopamine transporter binding and cerebrospinal fluid alpha-synuclein, amyloid beta, total tau, and phosphorylated tau in Parkinson's disease

BACKGROUND

Previous studies investigated CSF levels of α-synuclein (α-syn), amyloid-β (Aβ1-42), total tau (t-tau), and phosphorylated tau (p-tau) with clinical progression of Parkinson's disease (PD). However, there is limited data on the association between CSF biomarkers and dopamine uptake status in PD.

AIM

In the current study, we aim to investigate the longitudinal association between striatal dopaminergic neuronal loss assessed by dopamine active transporter single photon emission computerized tomography (DaTSCAN) imaging with CSF α-syn, t-tau, p-tau, and Aβ1-42.

METHODS

A total of 413 early-stage PD patients and 187 healthy controls (HCs) from the PPMI. Striatal binding ratios (SBRs) of DaTSCAN images in caudate and putamen nuclei were calculated. We investigated the cross-sectional and longitudinal association between CSF biomarkers and dopamine uptake using partial correlation models adjusted for the effect of age, sex, and years of education over 24 months of follow-up.

RESULTS

The level of CSF α-syn, Aβ1-42, t-tau, and p-tau was significantly higher in HCs compared to PD groups at any time point. We found that higher CSF α-syn was associated with a higher SBR score in the left caudate at baseline (P = 0.038) and after 12 months (P = 0.012) in PD patients. Moreover, SBR scores in the left caudate and CSF Aβ1-42 were positively correlated at baseline (P = 0.021), 12 months (P = 0.006), and 24 months (P = 0.014) in patients with PD. Our findings demonstrated that change in CSF Aβ1-42 was positively correlated with change in SBR score in the left caudate after 24 months in the PD group (P = 0.043).

CONCLUSION

We found that cross-sectional levels of α-syn and Aβ1-42 could reflect the degree of dopaminergic neuron loss in the left caudate nucleus. Interestingly, longitudinal changes in CSF Aβ1-42 could predict the severity of left caudal dopaminergic neuron loss throughout the disease. This suggested that Aβ pathology might precede dopaminergic loss in striatal nuclei in this case left caudate and subsequently cognitive impairment in PD patients, although future studies are needed to confirm our results and expand the understanding of the pathophysiology of cognitive dysfunction in PD.

A meta-analysis of the diagnostic utility of biomarkers in cerebrospinal fluid in Parkinson's disease

Biomarkers play important roles in the diagnosis and differential diagnosis of Parkinson's disease (PD). Thus, we carried out a systematic review and meta-analysis evaluating the diagnostic utility of cerebrospinal fluid (CSF) biomarkers to distinguish PD from atypical parkinsonian syndromes (APSs) and controls. Data for PD and APS and controls were extracted from 123 studies that reported the concentration of CSF biomarkers. Comparisons were presented using pooled Hedges' g. Sources of heterogeneity were evaluated using meta-regression, and subgroup and sensitivity analyses. We found that compared with controls, PD patients had lower levels of amyloid beta 1-42, phosphorylated tau, total tau, total α-synuclein, Zn, DJ-1, and YKL-40, and higher levels of oligomeric and phosphorylated α-synuclein. Moreover, lower CSF levels of neurofilament light chain, t-tau, YKL-40, and C-reactive protein were found in PD patients compared to those with multiple system atrophy. PD patients also had lower levels of NFL and higher levels of Aβ42 compared with patients with progressive supranuclear palsy. Reduced levels of p-tau and t-tau and higher Aβ42 levels were found in PD patients compared with patients with dementia with Lewy bodies. Finally, reduced NFL levels were found in patients with PD compared with patients with cortical basal degeneration. Therefore, we believe that the combinations of t-α-syn, Aβ42, and NFL could be promising biomarkers for the differential diagnosis of PD and APSs.

Machine learning-based prediction of cognitive outcomes in de novo Parkinson's disease

Cognitive impairment is a debilitating symptom in Parkinson's disease (PD). We aimed to establish an accurate multivariate machine learning (ML) model to predict cognitive outcome in newly diagnosed PD cases from the Parkinson's Progression Markers Initiative (PPMI). Annual cognitive assessments over an 8-year time span were used to define two cognitive outcomes of (i) cognitive impairment, and (ii) dementia conversion. Selected baseline variables were organized into three subsets of clinical, biofluid and genetic/epigenetic measures and tested using four different ML algorithms. Irrespective of the ML algorithm used, the models consisting of the clinical variables performed best and showed better prediction of cognitive impairment outcome over dementia conversion. We observed a marginal improvement in the prediction performance when clinical, biofluid, and epigenetic/genetic variables were all included in one model. Several cerebrospinal fluid measures and an epigenetic marker showed high predictive weighting in multiple models when included alongside clinical variables.

Detection and assessment of alpha-synuclein in Parkinson disease

PURPOSE

Different studies have reported varying alpha-synuclein values in the cerebrospinal fluid (CSF), serum, and plasma, making determination of the alpha-synuclein cutoff value for Parkinson's disease difficult and rendering identifying the cause of variation essential.

METHOD

We searched PubMed from inception to June 2021 and identified 76 eligible studies. Included studies reported data on total, phosphorylated, and oligomeric alpha-synuclein in the CSF, serum, or plasma from individuals with Parkinson's disease and healthy controls. The mean or median alpha-synuclein values from the included studies were summarized and categorized through laboratory assays to visualize potential trends.

RESULTS

The enzyme-linked immunosorbent assay (ELISA) is the most common assay used to determine alpha-synuclein concentrations. Less common assays include Luminex, single molecule arrays, electrochemiluminescence, and immunomagnetic reduction (IMR). IMR is a single-antibody and wash-free immunoassay designed for determining the extremely low concentration of bio-molecules. For patients with Parkinson's disease, the median or mean testing values ranged from 60.9 to 55,000 pg/mL in the CSF, 0.446 to 1,777,100 pg/mL in plasma, and 0.0292 to 38,200,000 pg/mL in serum. The antibody selection was diverse between studies. The tendency of distribution was more centralized among studies that used the same kit. Studies adopting specific antibodies or in-house assays contribute to the extreme values. Only a few studies on phosphorylated and oligomeric alpha-synuclein were included.

CONCLUSION

The type of assay and antibody selection in the laboratory played major roles in the alpha-synuclein variation. Studies that used the same assay and kit yielded relatively unanimous results. Furthermore, IMR may be a promising assay for plasma and serum alpha-synuclein quantification. A consensus on sample preparation and testing protocol unification is warranted in the future.

Biomarker of Neuroinflammation in Parkinson's Disease

Parkinson's disease (PD) is caused by abnormal accumulation of α-synuclein in dopaminergic neurons of the substantia nigra, which subsequently causes motor symptoms. Neuroinflammation plays a vital role in the pathogenesis of neurodegeneration in PD. This neuroinflammatory neurodegeneration involves the activation of microglia, upregulation of proinflammatory factors, and gut microbiota. In this review, we summarized the recent findings on detection of PD by using inflammatory biomarkers, such as interleukin (IL)-1β, IL-2, IL-6, IL-10, tumor necrosis factor (TNF)-α; regulated upon activation, normal T cell expressed and presumably secreted (RANTES) and high-sensitivity c-reactive protein (hsCRP); and radiotracers such as [11C]PK11195 and [18F]-FEPPA, as well as by monitoring disease progression and the treatment response. Many PD-causing mutations in SNCA, LRRK2, PRKN, PINK1, and DJ-1 are also associated with neuroinflammation. Several anti-inflammatory medications, including nonsteroidal anti-inflammatory drugs (NSAID), inhibitors of TNF-α and NLR family pyrin domain containing 3 (NLRP3), agonists of nuclear factor erythroid 2-related factor 2 (NRF2), peroxisome proliferator-activated receptor gamma (PPAR-γ), and steroids, have demonstrated neuroprotective effects in in vivo or in vitro PD models. Clinical trials applying objective biomarkers are required to investigate the therapeutic potential of anti-inflammatory medications for PD.

The Role of Tau beyond Alzheimer’s Disease: A Narrative Review

Nowadays, there is a need for reliable fluid biomarkers to improve differential diagnosis, prognosis, and the prediction of treatment response, particularly in the management of neurogenerative diseases that display an extreme variability in clinical phenotypes. In recent years, Tau protein has been progressively recognized as a valuable neuronal biomarker in several neurological conditions, not only Alzheimer’s disease (AD). Cerebrospinal fluid and serum Tau have been extensively investigated in several neurodegenerative disorders, from classically defined proteinopathy, e.g., amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and Parkinson’s disease (PD), but also in inflammatory conditions such as multiple sclerosis (MS), as a marker of axonal damage. In MS, total Tau (t-Tau) may represent, along with other proteins, a marker with diagnostic and prognostic value. In ALS, t-Tau and, mainly, the phosphorylated-Tau/t-Tau ratio alone or integrated with transactive DNA binding protein of ~43 kDa (TDP-43), may represent a tool for both diagnosis and differential diagnosis of other motoneuron diseases or tauopathies. Evidence indicated the crucial role of the Tau protein in the pathogenesis of PD and other parkinsonian disorders. This narrative review summarizes current knowledge regarding non-AD neurodegenerative diseases and the Tau protein.

SNCA rs3910105 Is Associated With Development of Rapid Eye Movement Sleep Behavior Disorder in Parkinson’s Disease

Background and Purpose

Rapid eye movement (REM) Rapid eye movement sleep behavior disorder (RBD) is a common non-motor symptom of PD. However, the association between the SNCA rs3910105 genotype and RBD in Parkinson’s disease (PD) remains unclear.

Methods

This study used Parkinson’s Progression Markers Initiative (PPMI) data and included 270 patients with newly diagnosed PD without RBD who were divided into SNCA rs3910105 C carriers (CC+CT; n = 187) and TT carriers (n = 83). They were followed up for 5 years to identify the development of RBD. To investigate the influence of cerebrospinal fluid (CSF) alpha-synuclein (α-syn) and β-amyloid 1–42 (Aβ₄₂) in the association between rs3910105 and RBD, the patients were additionally classified into “high-level” and “low-level” groups using cutoff values for CSF α-syn and Aβ₄₂ levels.

Results

At baseline, the rs3910105 C allele group had lower CSF α-syn and Aβ₄₂ levels than the TT group. During the 5.0-year follow-up, the rs3910105 C allele group had a higher incidence of RBD than the TT group. In the subgroup analyses, the effect of the rs3910105 C allele was not found in the “low-level” group. However, in the “high-level” group, the rs3910105 C allele independently increased the risk of RBD.

Conclusion

The SNCA rs3910105 C allele might be a novel genetic risk factor for RBD development in PD, α-syn pathways might have a role in this association and more basic research would be needed to elucidate the mechanism in the future.

Plasma α-synuclein and phosphorylated tau 181 as a diagnostic biomarker panel for de novo Parkinson's Disease

The use of a diagnostic panel comprising multiple biomarkers has the potential to accurately diagnose Parkinson’s disease (PD). However, a panel consisting solely of plasma biomarkers to diagnose PD is not available. This study aimed to examine the diagnostic ability of plasma biomarker panels for de novo PD using novel digital ultrasensitive immunoassay technology. We recruited 45 patients with de novo PD and 20 healthy controls (HCs). The concentrations of plasma α‐synuclein (α‐syn), amyloid β‐42 (Aβ42), Aβ40, phosphorylated tau 181 (p‐tau181), neurofilament light (NFL), and glial fibrillary acidic protein (GFAP) were quantified using the ultrasensitive single molecule array (Simoa) platform. Patients with de novo PD had higher plasma levels of α‐syn and p‐tau181 than HCs, adjusting for age and sex. Plasma levels of α‐syn and p‐tau181 were positively correlated in de novo PD patients. Higher plasma α‐syn levels were significantly associated with worse Unified Parkinson’s Disease Rating Scale (UPDRS) Part III motor scores, modified Hoehn and Yahr (H‐Y) stages, and increased risk of PD with mild cognitive impairment (PD‐MCI). Higher plasma p‐tau181 concentrations were linked to worse H‐Y stages. The diagnostic panel using plasma α‐syn and p‐tau181, combined with age and sex, showed good performance in discriminating de novo PD patients from HCs (area under the curve = 0.806). These findings suggest that plasma α‐syn and p‐tau181 together may be a promising diagnostic biomarker panel for de novo PD patients.

Prodromal Parkinson's disease: hype or hope for disease-modification trials?

The ultimate goal in Parkinson's disease (PD) research remains the identification of treatments that are capable of slowing or even halting the progression of the disease. The failure of numerous past disease-modification trials in PD has been attributed to a variety of factors related not only to choosing wrong interventions, but also to using inadequate trial designs and target populations. In patients with clinically established PD, neuronal pathology may already have advanced too far to be modified by any intervention. Based on such reasoning, individuals in yet prediagnostic or prodromal disease stages, may provide a window of opportunity to test disease-modifying strategies. There is now sufficient evidence from prospective studies to define diagnostic criteria for prodromal PD and several approaches have been studied in observational cohorts. These include the use of PD-risk algorithms derived from multiple established risk factors for disease as well as follow-up of cohorts with single defined prodromal markers like hyposmia, rapid eye movement sleep behavior disorders, or PD gene carriers. In this review, we discuss recruitment strategies for disease-modification trials in various prodromal PD cohorts, as well as potential trial designs, required trial durations, and estimated sample sizes. We offer a concluding outlook on how the goal of implementing disease-modification trials in prodromal cohorts might be achieved in the future.

Fluid markers of synapse degeneration in synucleinopathies

The abnormal accumulation of α-synuclein in the brain is a common feature of Parkinson's disease (PD), PD dementia (PDD), dementia with Lewy bodies (DLB) and multiple system atrophy (MSA), and synucleinopathies that present with overlapping but distinct clinical symptoms that include motor and cognitive deficits. Synapse degeneration is the crucial neuropathological event in these synucleinopathies and the neuropathological correlate of connectome dysfunction. The cognitive and motor deficits resulting from the connectome dysfunction are currently measured by scalar systems that are limited in their sensitivity and largely subjective. Ideally, a marker of synapse degeneration would correlate with measures of cognitive or motor impairment, and could therefore be used as a more objective, surrogate biomarker of the core clinical features of these diseases. Furthermore, an objective surrogate biomarker that can detect and monitor the progression of synapse degeneration would improve patient management and clinical trial design, and could provide a measure of therapeutic response. Here, we review the published findings relating to candidate biomarkers of synapse degeneration in PD, PDD, DLB, and MSA patient-derived biofluids and discuss the findings in the context of the mechanisms associated with α-synuclein-mediated synapse degeneration. Understanding these mechanisms is essential not only for discovery of biomarkers, but also to improve our understanding of the earliest changes in disease pathogenesis of synucleinopathies.

Perivascular space in Parkinson's disease: Association with CSF amyloid/tau and cognitive decline

OBJECTIVE

Whether perivascular space (PVS) visible on magnetic resonance imaging (MRI) represents glymphatic dysfunction and whether this imaging marker is pathologic in Parkinson's disease (PD) have been controversial. The objective was to determine whether PVS visible on MRI is independently associated with cognitive decline in patients with PD, and to test whether pathologic proteins in the CSF (such as Aβ₄₂) mediate the pathologic role of PVS.

METHODS

A total of 341 patients with Parkinson's disease from Parkinson's Progression Marker Initiative (PPMI) cohort was included in the present study. PVS in the basal ganglia (BG-PVS) and centrum semiovale were evaluated with a semiquantitative scale. Changes in the Montreal Cognitive Assessment (MoCA) score and the absolute MoCA score at the 3-year assessment were considered the main cognitive outcome. A multivariable linear regression model was used to test the association between PVS and cognitive decline. A mixed linear model and path analysis were used to test the interaction among PVS, CSF biomarkers and cognitive decline.

RESULTS

BG-PVS was associated with cognitive decline in patients with PD at the 3-year follow-up independent of age, baseline cognition, motor and nonmotor function, presynaptic dopaminergic deficiency, and CSF biomarkers. The interaction between BG-PVS and Aβ₄₂/tTau, Aβ₄₂/pTau, and Aβ₄₂ levels was significantly predictive of 3-year cognitive decline. Path analysis confirmed that CSF Aβ₄₂/tTau levels partially mediated the pathologic effect of BG-PVS on cognitive outcome in PD.

CONCLUSIONS

BG-PVS is independently associated with cognitive decline in PD, and this association may be partially mediated by toxic CSF proteins.

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.

Disease modifying therapies III: Novel targets

Despite significant research advances, treatment of Parkinson's disease (PD) remains confined to symptomatic therapies. Approaches aiming to halt or reverse disease progression remain an important but unmet goal. A growing understanding of disease pathogenesis and the identification of novel pathways contributing to initiation of neurodegeneration and subsequent progression has highlighted a range of potential novel targets for intervention that may influence the rate of progression of the disease process. Exploiting techniques to stratify patients according to these targets alongside using them as biomarkers to measure target engagement will likely improve patient selection and preliminary outcome measurements in clinical trials. In this review, we summarize a number of PD-related mechanisms that have recently gained interest such as neuroinflammation, lysosomal dysfunction and insulin resistance, while also exploring the potential for targeting peripheral interfaces such as the gastrointestinal tract and its ecosystem to achieve disease modification. We explore the rationale for these approaches based on preclinical studies, while also highlighting the status of relevant clinical trials as well as the promising role biomarkers may play in current and future studies.

Biomarkers of Cerebral Glucose Metabolism and Neurodegeneration in Parkinson's Disease: A Cerebrospinal Fluid-Based Study

BACKGROUND

Several biomarkers have been evaluated in Parkinson's disease (PD); cerebrospinal fluid (CSF) levels of lactate may reflect cerebral metabolism function and CSF amyloid-β42 (Aβ42), total tau (t-tau) and phosphorylated tau (p-tau) concentrations may detect an underlying neurodegenerative process.

OBJECTIVE

CSF levels of lactate, Aβ42, t-tau, and p-tau were measured in patients with mild to moderate PD. CSF levels of dopamine (DA) and its metabolite 3,4-Dihydroxyphenylacetic acid (DOPAC) were also assessed, exploring their relations with the other CSF biomarkers.

METHODS

101 drug-naive PD patients and 60 controls were included. Participants underwent clinical assessments and CSF biomarker analysis. Patients were divided into subgroups according to their Hoehn & Yahr stage (PD-1, PD-2, PD-3).

RESULTS

PD patients showed higher lactate levels (M = 1.91; p = 0.03) and lower Aβ42 (M = 595; p < 0.001) and DA levels (M = 0.32; p = 0.04) than controls (Mlactate = 1.72; MAβ42 = 837; MDA = 0.50), while no significant differences were found in t-tau, p-tau and DOPAC concentrations. Considering the subgroup analysis, PD-3 group had higher lactate (M = 2.12) and t-tau levels (M = 333) than both PD-1 (Mlactate = 1.75, p = 0.006; Mt - tau = 176, p = 0.008) and PD-2 groups (Mlactate = 1.91, p = 0.01; Mt - tau = 176, p = 0.03), as well as the controls (Mlactate = 1.72, p = 0.04; Mt - tau = 205, p = 0.04). PD-2 group showed higher lactate levels than PD-1 group (p = 0.04) and controls (p = 0.03). Finally, CSF lactate levels negatively correlated with DA (r = -0.42) and positively with t-tau CSF levels (r = 0.33).

CONCLUSION

This CSF-based study shows that lactate levels in PD correlated with both clinical disease progression and neurodegeneration biomarkers, such as tau proteins and DA. Further studies should explore the clinical potential of measuring CSF biomarkers for better understanding the role of brain energy metabolism in PD, for research and therapeutic options.

Sex-Related Longitudinal Change of Motor, Non-Motor, and Biological Features in Early Parkinson's Disease

Background:

Investigation of sex-related motor and non-motor differences and biological markers in Parkinson’s disease (PD) may improve precision medicine approach.

Objective:

To examine sex-related longitudinal changes in motor and non-motor features and biologic biomarkers in early PD.

Methods:

We compared 5-year longitudinal changes in de novo, untreated PD men and women (at baseline N = 423; 65.5%male) of the Parkinson’s Progression Markers Initiative (PPMI), assessing motor and non-motor manifestations of disease; and biologic measures in cerebrospinal fluid (CSF) and dopamine transporter deficit on DaTscan^TM uptake.

Results:

Men experienced greater longitudinal decline in self-reported motor (p < 0.001) and non-motor (p = 0.009) aspects of experiences of daily living, such that men had a yearly increase in MDS-UPDRS part II by a multiplicative factor of 1.27 compared to women at 0.7, while men had a yearly increase in MDS-UPDRS part I by a multiplicative factor of 0.98, compared to women at 0.67. Compared to women, men had more longitudinal progression in clinician-assessed motor features in the ON medication state (p = 0.010) and required higher dopaminergic medication dosages over time (p = 0.014). Time to reach specific disease milestones and longitudinal changes in CSF biomarkers and DaTscan^TM uptake were not different by sex.

Conclusion:

Men showed higher self-assessed motor and non-motor burden of disease, with possible contributions from suboptimal dopaminergic therapeutic response in men. However, motor features of disease evaluated with clinician-based scales in the OFF medication state, as well as biological biomarkers do not show specific sex-related progression patterns.

Tau in the Pathophysiology of Parkinson's Disease

The pathological hallmarks of Parkinson's disease (PD) are the progressive loss of dopaminergic neurons in the substantia nigra and the formation of Lewy bodies (LBs) in remaining neurons. LBs primarily consist of aggregated α-Synuclein (α-Syn). However, accumulating evidence suggests that Tau, which is associated with tauopathies such as Alzheimer's disease (AD), progressive supranuclear palsy (PSP), and argyrophilic grain disease, is also involved in the pathophysiology of PD. A genome-wide association study (GWAS) identified MAPT, the gene encoding the Tau protein, as a risk gene for PD. Autopsy of PD patients also revealed the colocalization of Tau and α-Syn in LBs. Experimental evidence has shown that Tau interacts with α-Syn and influences the pathology of α-Syn in PD. In this review, we discuss the structure and function of Tau and provide a summary of the current evidence supporting Tau's involvement as either an active or passive element in the pathophysiology of PD, which may provide novel targets for the early diagnosis and treatment of PD.

Parkinson Disease: Translating Insights from Molecular Mechanisms to Neuroprotection

Parkinson disease (PD) used to be considered a nongenetic condition. However, the identification of several autosomal dominant and recessive mutations linked to monogenic PD has changed this view. Clinically manifest PD is then thought to occur through a complex interplay between genetic mutations, many of which have incomplete penetrance, and environmental factors, both neuroprotective and increasing susceptibility, which variably interact to reach a threshold over which PD becomes clinically manifested. Functional studies of PD gene products have identified many cellular and molecular pathways, providing crucial insights into the nature and causes of PD. PD originates from multiple causes and a range of pathogenic processes at play, ultimately culminating in nigral dopaminergic loss and motor dysfunction. An in-depth understanding of these complex and possibly convergent pathways will pave the way for therapeutic approaches to alleviate the disease symptoms and neuroprotective strategies to prevent disease manifestations. This review is aimed at providing a comprehensive understanding of advances made in PD research based on leveraging genetic insights into the pathogenesis of PD. It further discusses novel perspectives to facilitate identification of critical molecular pathways that are central to neurodegeneration that hold the potential to develop neuroprotective and/or neurorestorative therapeutic strategies for PD. SIGNIFICANCE STATEMENT: A comprehensive review of PD pathophysiology is provided on the complex interplay of genetic and environmental factors and biologic processes that contribute to PD pathogenesis. This knowledge identifies new targets that could be leveraged into disease-modifying therapies to prevent or slow neurodegeneration in PD.

Comprehensive subtyping of Parkinson's disease patients with similarity fusion: a case study with BioFIND data

Parkinson’s disease (PD) is a complex neurodegenerative disorder with diverse clinical manifestations. To better understand this disease, research has been done to categorize, or subtype, patients, using an array of criteria derived from clinical assessments and biospecimen analyses. In this study, using data from the BioFIND cohort, we aimed at identifying subtypes of moderate-to-advanced PD via comprehensively considering motor and non-motor manifestations. A total of 103 patients were included for analysis. Through the use of a patient-wise similarity matrix fusion technique and hierarchical agglomerative clustering analysis, three unique subtypes emerged from the clustering results. Subtype I, comprised of 60 patients (~58.3%), was characterized by mild symptoms, both motor and non-motor. Subtype II, comprised of 20 (~19.4%) patients, was characterized by an intermediate severity, with a high tremor score and mild non-motor symptoms. Subtype III, comprised of 23 (~22.3%) patients, was characterized by more severe motor and non-motor symptoms. These subtypes show statistically significant differences when looking at motor (on and off medication) clinical features and non-motor clinical features, while there was no clear difference in demographics, biomarker levels, and genetic risk scores.

Current advances in metabolomic studies on non-motor psychiatric manifestations of Parkinson's disease (Review)

Life expectancy has increased worldwide and, along with it, a greater prevalence of age-dependent disorders, chronic illnesses and comorbidities can be observed. In 2019, in both Europe and the Americas, dementias ranked 3rd among the top 10 causes of death. Parkinson's disease (PD) is the second most frequent type of neurodegenerative disease. In the last decades, globally, the number of people suffering from PD has more than doubled to over 6 million. Of all the neurological disorders, PD increased with the fastest rate. This troubling trend highlights the stringent need for accurate diagnostic biomarkers, especially in the early stages of the disease and to evaluate treatment response. To gain a broad and complex understanding of the recent advances in the '-omics' research fields, electronic databases such as PubMed, Google Academic, and Science Direct were searched for publications regarding metabolomic studies on PD to identify specific biomarkers for PD, and especially PD with associated psychiatric symptomatology. Discoveries in the fields of metagenomics, transcriptomics and proteomics, may lead to an improved comprehension of the metabolic pathways involved in disease etiology and progression and contribute to the discovery of novel therapeutic targets for effective treatment options.

CSF Diagnostics: A Potentially Valuable Tool in Neurodegenerative and Inflammatory Disorders Involving Motor Neurons: A Review

Cerebrospinal fluid (CSF) diagnostics has emerged as a valid tool for a variety of neurological diseases. However, CSF diagnostics has been playing a subordinate role in the diagnosis of many neurological conditions. Thus, in the multitude of neuromuscular diseases in which motor neurons are affected, a CSF sample is rarely taken routinely. However, CSF diagnostics has the potential to specify the diagnosis and monitor the treatment of neuromuscular disorders. In this review, we therefore focused on a variety of neuromuscular diseases, among them amyotrophic lateral sclerosis (ALS), peripheral neuropathies, and spinal muscular atrophy (SMA), for which CSF diagnostics has emerged as a promising option for determining the disease itself and its progression. We focus on potentially valuable biomarkers among different disorders, such as neurofilaments, cytokines, other proteins, and lipids to determine their suitability, differentiating between different neurological disorders and their potential to determine early disease onset, disease progression, and treatment outcome. We further recommend novel approaches, e.g., the use of mass spectrometry as a promising alternative techniques to standard ELISA assays, potentially enhancing biomarker significance in clinical applications.

Alpha-synuclein research: defining strategic moves in the battle against Parkinson's disease

With the advent of the genetic era in Parkinson's disease (PD) research in 1997, α-synuclein was identified as an important player in a complex neurodegenerative disease that affects >10 million people worldwide. PD has been estimated to have an economic impact of $51.9 billion in the US alone. Since the initial association with PD, hundreds of researchers have contributed to elucidating the functions of α-synuclein in normal and pathological states, and these remain critical areas for continued research. With this position paper the authors strive to achieve two goals: first, to succinctly summarize the critical features that define α-synuclein's varied roles, as they are known today; and second, to identify the most pressing knowledge gaps and delineate a multipronged strategy for future research with the goal of enabling therapies to stop or slow disease progression in PD.

Temporal trajectory of biofluid markers in Parkinson's disease

Full dynamics of biofluid biomarkers have been unknown in patients with Parkinson’s disease (PD). Using data from 396 PD patients and 182 controls in the Parkinson's Progression Markers Initiative (PPMI) database, we estimated long-term temporal trajectories of CSF α-synuclein (α-syn), amyloid-β (Aβ), total tau (t-tau), phosphorylated tau (p-tau) and serum neurofilament light chain (NfL) by integrating function between the baseline levels and annual changes. At baseline, PD patients showed lower CSF α-syn, Aβ, t-tau and p-tau levels than those of the controls. In all PD patients, CSF α-syn and Aβ decreased in a negative exponential pattern before the onset of motor symptoms, whereas CSF t-tau and p-tau, and serum NfL increased. Patients with cognitive impairment exhibited faster decline of Aβ and α-syn and faster rise of t-tau, p-tau and NfL, when compared to those without. Similarly, low Aβ group showed earlier decline of α-syn, faster rise of t-tau, p-tau and NfL, and faster decline of cognitive performances, when compared to high Aβ group. Our results suggest that longitudinal changes in biomarkers can be influenced by cognitive impairment and Aβ burden at baseline. PD patients with Aβ pathology may be associated with early appearance of α-synuclein pathology, rapid progression of axonal degeneration and neurodegeneration, and consequently greater cognitive decline.

The blood biomarkers puzzle - A review of protein biomarkers in neurodegenerative diseases

Neurodegenerative diseases are heterogeneous in their cause and clinical presentation making clinical assessment and disease monitoring challenging. Because of this, there is an urgent need for objective tools such as fluid biomarkers able to quantitate different aspects of the disease. In the last decade, technological improvements and awareness of the importance of biorepositories led to the discovery of an evolving number of fluid biomarkers covering the main characteristics of neurodegenerative diseases such as neurodegeneration, protein aggregates and inflammation. The ability to quantitate each aspect of the disease at a high definition enables a more precise stratification of the patients at inclusion in clinical trials, hence reducing the noise that may hamper the detection of therapeutical efficacy and allowing for smaller but likewise powered studies, which particularly improves the ability to start clinical trials for rare neurological diseases. Moreover, the use of fluid biomarkers has the potential to support a targeted therapeutical intervention, as it is now emerging for the treatment of amyloid-beta deposition in patients suffering from Alzheimer's disease. Here we review the knowledge that evolved from the measurement of fluid biomarker proteins in neurodegenerative conditions.

Asymmetric Dopamine Transporter Loss Affects Cognitive and Motor Progression in Parkinson's Disease

Background

Asymmetric hemispheric loss of dopaminergic neurons is one of the characteristic features of Parkinson's disease (PD). However, it is still debated if right or left asymmetry differently affects cognitive and motor progression.

Objectives

The objective of this study was to investigate, for the first time, the relevance of dopamine transporter (DAT) asymmetry on cognitive and motor manifestations at onset and at 4‐year progression in drug‐naïve PD.

Methods

From the Parkinson's Progression Markers Initiative multicenter cohort, we identified 249 right‐handed patients with PD with baseline asymmetry greater than 20% in putamen DAT binding at single‐photon emission computed tomography. A predominant putamen asymmetry was found on the left in 143 patients (PD‐left), and on the right side in 106 patients (PD‐right); we compared them with 196 healthy controls. Patients were followed longitudinally (2‐year and 4‐year visits), examining their clinical, cognitive, and imaging data.

Results

At baseline, the PD‐left group showed worse performance on the Symbol Digit Modality Test, an attention and processing‐speed test, and lower cerebrospinal fluid β‐amyloid levels than the PD‐right group. These differences were maintained at follow‐up, declining over time in both groups. By contrast, the PD‐right group showed greater motor impairment at baseline, which increased over 4 years. Striatal DAT binding decreased over time in both groups, but the PD‐right group showed a steeper decline, particularly during the first 2‐year follow‐up. Putaminal asymmetry assessed at baseline was maintained over time.

Conclusions

These findings suggest that hemispheric asymmetric dopaminergic denervation influences PD cognitive and motor performance as well as progression. Predominant right hemisphere nigrostriatal dopaminergic loss is associated with greater motor severity, whereas more pronounced left hemisphere denervation affects cognitive manifestations at onset and their progression. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Recent Insights into the Interplay of Alpha-Synuclein and Sphingolipid Signaling in Parkinson's Disease

Molecular studies have provided increasing evidence that Parkinson’s disease (PD) is a protein conformational disease, where the spread of alpha-synuclein (ASN) pathology along the neuraxis correlates with clinical disease outcome. Pathogenic forms of ASN evoke oxidative stress (OS), neuroinflammation, and protein alterations in neighboring cells, thereby intensifying ASN toxicity, neurodegeneration, and neuronal death. A number of evidence suggest that homeostasis between bioactive sphingolipids with opposing function—e.g., sphingosine-1-phosphate (S1P) and ceramide—is essential in pro-survival signaling and cell defense against OS. In contrast, imbalance of the “sphingolipid biostat” favoring pro-oxidative/pro-apoptotic ceramide-mediated changes have been indicated in PD and other neurodegenerative disorders. Therefore, we focused on the role of sphingolipid alterations in ASN burden, as well as in a vast range of its neurotoxic effects. Sphingolipid homeostasis is principally directed by sphingosine kinases (SphKs), which synthesize S1P—a potent lipid mediator regulating cell fate and inflammatory response—making SphK/S1P signaling an essential pharmacological target. A growing number of studies have shown that S1P receptor modulators, and agonists are promising protectants in several neurological diseases. This review demonstrates the relationship between ASN toxicity and alteration of SphK-dependent S1P signaling in OS, neuroinflammation, and neuronal death. Moreover, we discuss the S1P receptor-mediated pathways as a novel promising therapeutic approach in PD.

Can Plasma α-Synuclein Help Us to Differentiate Parkinson's Disease from Essential Tremor?

Background

Studies have revealed controversial results regarding the diagnostic accuracy of plasma α-synuclein levels in patients with Parkinson's disease (PD). This study was aimed to analyze the diagnostic accuracy of plasma α-synuclein in PD versus healthy controls and patients with essential tremor (ET).

Methods

In this cross-sectional study, we included de novo (n = 19) and advanced PD patients [OFF (n = 33), and On (n = 35) states], patients with ET (n = 19), and controls (n = 35). The total plasma α-synuclein levels were determined using an ELISA sandwich method. We performed adjusted multivariate regression analysis to estimate the association of α-synuclein levels with group conditions [controls, ET, and de novo, OFF and ON-PD]. We studied the diagnostic accuracy of plasma α-synuclein using the area under the curve (AUC).

Results

The plasma α-synuclein levels were higher in controls compared to PD and ET (p < 0.0001), discriminating de novo PD from controls (AUC = 0.74, 95% CI 0.60-0.89), with a trend towards in advanced PD (OFF state) from ET (AUC = 0.69, 95% CI 0.53-0.84).

Conclusions

This is the first study examining and comparing plasma α-synuclein levels in ET vs. PD and controls. Preliminary findings suggest that plasma α-synuclein levels might help to discriminate de novo and advanced PD from controls and ET.

Cerebrospinal α-Synuclein Oligomers Reflect Disease Motor Severity in DeNoPa Longitudinal Cohort

BACKGROUND

Tangible efforts have been made to identify biomarkers for Parkinson's disease (PD) diagnosis and progression, with α-synuclein (α-syn) related biomarkers being at the forefront.

OBJECTIVES

The objectives of this study were to explore whether cerebrospinal fluid (CSF) levels of total, oligomeric, phosphorylated Ser 129 α-synuclein, along with total tau, phosphorylated tau 181, and β-amyloid 1-42 are (1) informative as diagnostic markers for PD, (2) changed over disease progression, and/or (3) correlated with motor and cognitive indices of disease progression in the longitudinal De Novo Parkinson cohort.

METHODS

A total of 94 de novo PD patients and 52 controls at baseline and 24- and 48-month follow-up were included, all of whom had longitudinal lumbar punctures and clinical assessments for both cognitive and motor functions. Using our in-house enzymelinked immunosorbent assays and commercially available assays, different forms of α-synuclein, tau, and β-amyloid 1-42 were quantified in CSF samples from the De Novo Parkinson cohort.

RESULTS

Baseline CSF total α-synuclein was significantly lower in early de novo PD compared with healthy controls, whereas the ratio of oligomeric/total and phosphorylated/total were significantly higher in the PD group. CSF oligomeric-α-synuclein longitudinally increased over the 4-year follow-up in the PD group and correlated with PD motor progression. Patients at advanced stages of PD presented with elevated CSF oligomeric-α-synuclein levels compared with healthy controls.

CONCLUSIONS

Longitudinal transitions of CSF biomarkers over disease progression might not occur linearly and are susceptible to disease state. CSF oligomeric-α-synuclein levels appear to increase with diseases severity and reflect PD motor rather than cognitive trajectories. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Compared with the monocyte to high-density lipoprotein ratio (MHR) and the neutrophil to lymphocyte ratio (NLR), the neutrophil to high-density lipoprotein ratio (NHR) is more valuable for assessing the inflammatory process in Parkinson's disease

Background

The inflammatory response plays essential roles in the pathological process and prognosis of Parkinson’s disease (PD). This research investigated the predictive value of the neutrophil to high-density lipoprotein ratio (NHR), neutrophil to lymphocyte ratio (NLR), and monocyte to high-density lipoprotein ratio (MHR) for PD.

Methods

Patients with PD (n = 98) were divided into three groups according to disease duration: < 6 years (n = 55), 6–10 years (n = 29) and > 10 years (n = 14). Based on the classification system of Hoehn and Yahr, grades 1 ~ 2.5 were considered early-stage PD (n = 44), and grades 3 ~ 5 were considered advanced-stage PD (n = 54). In addition, healthy subjects (n = 98) matched to the above PD patients in the same period were selected as the control group. Differences in the NHR, NLR, MHR and other indicators among the groups were evaluated.

Results

Smoking, drinking, the neutrophil count and the NHR and NLR were remarkably greater and hypertension, index of body mass, the lymphocyte count, and the levels of cholesterol in total, triglycerides, lipoprotein cholesterol with low density and uric acid were sharply lower in the PD group compared with in the control group. Analysis of multifactor logistic regression indicated that the NHR (odds ratio (adjusted OR) = 1.576, 95% CI: 1.053 ~ 2.358, P = 0.027) and NLR (adjusted OR = 1.734, 95% CI: 1.046 ~ 2.876, P = 0.033) were factors of risk for PD, while the MHR was not significantly correlated with PD. The areas under the receiver operating characteristic (ROC) curve (AUCs) for the prediction of PD by the NHR and NLR were 0.654 (95% CI: 0.583 ~ 0.721, P = 0.0001) and 0.69 (95% CI: 0.62 ~ 0.754, P < 0.0001), respectively, and the optimal cutoff values were 1.848 × 10⁹/mmol and 2.62 × 10⁹/mmol. Spearman’s correlation analysis indicated that the NHR was correlated with the disease duration significantly negatively and that the MHR was positively correlated with disease severity.

Conclusions

In summary, the NHR not only has strong predictive value for PD but is also closely related to disease duration. The NHR may be a better prediction for the long-period clinical results in PD patients than the MHR and NLR.

Trial registration

Clinical medical reserach center project of Qinghai Province (2017-SF-L1).

α-syn and SNP rs356219 as a potential biomarker in blood for Parkinson's disease in Mexican Mestizos

Clinical criteria diagnose Parkinson's disease (PD), therefore, it is crucial to find biological elements that could support diagnosis or even act as prognostic tools of PD. The SNCA gene codifies a protein called α - synuclein; several studies associate genetic and biochemical factors of SNCA with PD, including transcript and plasmatic protein levels, however, contradictory evidence indicates inconclusive results. We aim to compare SNCA mRNA expression, plasmatic α-syn protein and rs356219 SNP between PD cases and a control group, and to identify a potential biomarker in Mexican mestizos', focusing on these three components determined in blood. We included 88 PD patients and 88 age-matched controls. We observed higher α-syn protein and decreased SNCA mRNA levels in PD subjects, compared to control group (p = 0.044 and p < 0.001, respectively). A statistically significant difference was found in allelic and genotypic frequencies of SNP rs356219 between PD patients and normal subjects (p = 0.006 and p = 0.023, respectively). Logistic regression analysis determined as optimal predictors of PD the GG genotype of SNP rs356219 (OR 2.49; p = 0.006) in a recessive model and α-syn protein (OR 1.057; p = 0.033). Furthermore, the G allele of SNP rs356219 was associated with higher plasmatic α-syn and mRNA levels in PD subjects. The receiver operating curves (ROC) distinguished PD from healthy controls with good sensitivity and specificity considering the plasmatic α-syn protein (AUC = 0.693, Sensitivity = 66.7 %, Specificity = 63.9 %) or a predictive probability of plasmatic α-syn protein and SNP rs356219 in a single model (AUC = 0.692, Sensitivity = 62.3 %, Specificity = 62.5 %). The performance of this classifier model in PD at early stage (n = 31) increase the discriminant power in both, plasmatic α-syn protein (AUC = 0.779, Sensitivity = 72.7 %, Specificity = 73.9 %) and predictive probability (AUC = 0.707, Sensitivity = 63.6 %, Specificity = 62.5 %). We propose that α-syn protein and SNP rs356219 together may work as a good signature of PD, and they can be suggested as a non-invasive biomarker of PD risk.