Update on CSF Biomarkers in Parkinson's Disease

Insights into spinal muscular atrophy from molecular biomarkers

Spinal muscular atrophy is a devastating motor neuron disease characterized by severe cases of fatal muscle weakness. It is one of the most common genetic causes of mortality among infants aged less than 2 years. Biomarker research is currently receiving more attention, and new candidate biomarkers are constantly being discovered. This review initially discusses the evaluation methods commonly used in clinical practice while briefly outlining their respective pros and cons. We also describe recent advancements in research and the clinical significance of molecular biomarkers for spinal muscular atrophy, which are classified as either specific or non-specific biomarkers. This review provides new insights into the pathogenesis of spinal muscular atrophy, the mechanism of biomarkers in response to drug-modified therapies, the selection of biomarker candidates, and would promote the development of future research. Furthermore, the successful utilization of biomarkers may facilitate the implementation of gene-targeting treatments for patients with spinal muscular atrophy.

Integrative Metabolome and Proteome Analysis of Cerebrospinal Fluid in Parkinson's Disease

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by the loss of dopaminergic neurons in the substantia nigra. Recent studies have highlighted the significant role of cerebrospinal fluid (CSF) in reflecting pathophysiological PD brain conditions by analyzing the components of CSF. Based on the published literature, we created a single network with altered metabolites in the CSF of patients with PD. We analyzed biological functions related to the transmembrane of mitochondria, respiration of mitochondria, neurodegeneration, and PD using a bioinformatics tool. As the proteome reflects phenotypes, we collected proteome data based on published papers, and the biological function of the single network showed similarities with that of the metabolomic network. Then, we analyzed the single network of integrated metabolome and proteome. In silico predictions based on the single network with integrated metabolomics and proteomics showed that neurodegeneration and PD were predicted to be activated. In contrast, mitochondrial transmembrane activity and respiration were predicted to be suppressed in the CSF of patients with PD. This review underscores the importance of integrated omics analyses in deciphering PD's complex biochemical networks underlying neurodegeneration.

Plasma acellular transcriptome contains Parkinson's disease signatures that can inform clinical diagnosis

We aimed to identify plasma cell-free transcripts (cfRNA) associated with Parkinson's disease (PD) that also have a high predictive value to differentiate PD from healthy controls. Leveraging two independent populations from two different movement disorder centers we identified 2,188 differentially expressed cfRNAs after meta-analysis. The identified transcripts were enriched in PD relevant pathways, such as PD (p=9.26×10-4), ubiquitin-mediated proteolysis (p=7.41×10-5) and endocytosis (p=4.21×10-6). Utilizing in-house and publicly available brain, whole blood, and acellular plasma transcriptomic and proteomic PD datasets, we found significant overlap across dysregulated biological species in the different tissues and the different biological layers. We developed three predictive models containing increasing number of transcripts that can distinguish PD from healthy control with an area under the ROC Curve (AUC) ≥0.85. Finally, we showed that several of the predictive transcripts significantly correlate with symptom severity measured by UPDRS-III. Overall, we have demonstrated that cfRNA contains pathological signatures and has the potential to be utilized as biomarker to aid in PD diagnostics and monitoring.

Active Immunotherapy for the Prevention of Alzheimer's and Parkinson's Disease

Neurodegenerative diseases (ND) give rise to significant declines in motor, autonomic, behavioral, and cognitive functions. Of these conditions, Alzheimer's disease (AD) and Parkinson's disease (PD) are the most prevalent, impacting over 55 million people worldwide. Given the staggering financial toll on the global economy and their widespread manifestation, NDs represent a critical issue for healthcare systems worldwide. Current treatment options merely seek to provide symptomatic relief or slow the rate of functional decline and remain financially inaccessible to many patients. Indeed, no therapy has yet demonstrated the potential to halt the trajectory of NDs, let alone reverse them. It is now recognized that brain accumulation of pathological variants of AD- or PD-associated proteins (i.e., amyloid-β, Tau, α-synuclein) begins years to decades before the onset of clinical symptoms. Accordingly, there is an urgent need to pursue therapies that prevent the neurodegenerative processes associated with pathological protein aggregation long before a clinical diagnosis can be made. These therapies must be safe, convenient, and affordable to ensure broad coverage in at-risk populations. Based on the need to intervene long before clinical symptoms appear, in this review, we present a rationale for greater investment to support the development of active immunotherapy for the prevention of the two most common NDs based on their safety profile, ability to specifically target pathological proteins, as well as the significantly lower costs associated with manufacturing and distribution, which stands to expand accessibility to millions of people globally.

Prevalence of Thai patients with advanced Parkinson's disease and external validation of the 5-2-1 Criteria and the CDEPA Questionnaire: A single-centered, cross-sectional study

BACKGROUND

Advanced stage of Parkinson's disease (APD) diagnosis is challenging for general neurologists. The 5-2-1 Criteria and the Cuestionario De Enfermedad de Parkinson Avanzada (CDEPA) have been validated for screening for APD.

OBJECTIVE

This article reports the period-prevalence of APD defined by a movement disorder expert, the 5-2-1 Criteria, and CDEPA and to improve the screening performance of the 5-2-1 Criteria METHODS: A cross-sectional retrospective study at the Parkinson's disease (PD) clinic of a tertiary hospital in Bangkok, Thailand amongst all PD patients aged ≥ 18 years was performed from January 2016 to January 2020. We compared the characteristics of APD and non-APD patients. We externally validated the 5-2-1 Criteria and CDEPA. We explored improving the 5-2-1 Criteria.

RESULTS

Of 480 PD patients with complete data, the period-prevalence of APD by the movement disorder expert, the 5-2-1 Criteria and CDEPA were 37.1 %, 48.5 %, and 27.5 %, respectively. Adding requiring help with an activity of daily living and freezing of gait to the original 5-2-1 Criteria enhanced the sensitivity from 86.5 % (95 %CI 80.6, 91.2) to 94.9 % (95 %CI 90.6, 97.7) and negative predictive value (NPV) from 90.3 % (95 %CI 85.9, 93.7) to 96 % (95 %CI 92.6, 98.2). However, the CDEPA had a sensitivity of 62.9 % (95 %CI 55.4, 70) and NPV of 81.0 (95 %CI 76.5, 85).

CONCLUSION

The 5-2-1 Criteria had a good screening tool performance for general neurologists to refer APD patients for optimal treatments. The modified 5-2-1 Criteria had better performance than the original one. External validation is needed.

The Potential of Metabolomics to Find Proper Biomarkers for Addressing the Neuroprotective Efficacy of Drugs Aimed at Delaying Parkinson's and Alzheimer's Disease Progression

The first objective is to highlight the lack of tools to measure whether a given intervention affords neuroprotection in patients with Alzheimer's or Parkinson's diseases. A second aim is to present the primary outcome measures used in clinical trials in cohorts of patients with neurodegenerative diseases. The final aim is to discuss whether metabolomics using body fluids may lead to the discovery of biomarkers of neuroprotection. Information on the primary outcome measures in clinical trials related to Alzheimer's and Parkinson's disease registered since 2018 was collected. We analysed the type of measures selected to assess efficacy, not in terms of neuroprotection since, as stated in the aims, there is not yet any marker of neuroprotection. Proteomic approaches using plasma or CSF have been proposed. PET could estimate the extent of lesions, but disease progression does not necessarily correlate with a change in tracer uptake. We propose some alternatives based on considering the metabolome. A new opportunity opens with metabolomics because there have been impressive technological advances that allow the detection, among others, of metabolites related to mitochondrial function and mitochondrial structure in serum and/or cerebrospinal fluid; some of the differentially concentrated metabolites can become reliable biomarkers of neuroprotection.

Clinical Application of Blood Biomarkers in Neurodegenerative Diseases-Present and Future Perspectives

Neurodegenerative diseases are a group of complex diseases characterized by a progressive loss of neurons and degeneration in different areas of the nervous system. They share similar mechanisms, such as neuroinflammation, oxidative stress, and mitochondrial injury, resulting in neuronal loss. One of the biggest challenges in diagnosing neurodegenerative diseases is their heterogeneity. Clinical symptoms are usually present in the advanced stages of the disease, thus it is essential to find optimal biomarkers that would allow early diagnosis. Due to the development of ultrasensitive methods analyzing proteins in other fluids, such as blood, huge progress has been made in the field of biomarkers for neurodegenerative diseases. The application of protein biomarker measurement has significantly influenced not only diagnosis but also prognosis, differentiation, and the development of new therapies, as it enables the recognition of early stages of disease in individuals with preclinical stages or with mild symptoms. Additionally, the introduction of biochemical markers into routine clinical practice may improve diagnosis and allow for a stratification group of people with higher risk, as well as an extension of well-being since a treatment could be started early. In this review, we focus on blood biomarkers, which could be potentially useful in the daily medical practice of selected neurodegenerative diseases.

Exploring Inner Ear and Brain Connectivity through Perilymph Sampling for Early Detection of Neurological Diseases: A Provocative Proposal

Recent evidence shows that it is possible to identify the elements responsible for sensorineural hearing loss, such as pro-inflammatory cytokines and macrophages, by performing perilymph sampling. However, current studies have only focused on the diagnosis of such as otologic conditions. Hearing loss is a feature of certain neuroinflammatory disorders such as multiple sclerosis, and sensorineural hearing loss (SNHL) is widely detected in Alzheimer's disease. Although the environment of the inner ear is highly regulated, there are several communication pathways between the perilymph of the inner ear and cerebrospinal fluid (CSF). Thus, examination of the perilymph may help understand the mechanism behind the hearing loss observed in certain neuroinflammatory and neurodegenerative diseases. Herein, we review the constituents of CSF and perilymph, the anatomy of the inner ear and its connection with the brain. Then, we discuss the relevance of perilymph sampling in neurology. Currently, perilymph sampling is only performed during surgical procedures, but we hypothesize a simplified and low-invasive technique that could allow sampling in a clinical setting with the same ease as performing an intratympanic injection under direct visual check. The use of this modified technique could allow for perilymph sampling in people with hearing loss and neuroinflammatory/neurodegenerative disorders and clarify the relationship between these conditions; in fact, by measuring the concentration of neuroinflammatory and/or neurodegenerative biomarkers and those typically expressed in the inner ear in aging SNHL, it could be possible to understand if SNHL is caused by aging or neuroinflammation.

From the Gut to the Brain: Is Microbiota a New Paradigm in Parkinson's Disease Treatment?

Parkinson's disease (PD) is recognized as the second most prevalent primary chronic neurodegenerative disorder of the central nervous system. Clinically, PD is characterized as a movement disorder, exhibiting an incidence and mortality rate that is increasing faster than any other neurological condition. In recent years, there has been a growing interest concerning the role of the gut microbiota in the etiology and pathophysiology of PD. The establishment of a brain-gut microbiota axis is now real, with evidence denoting a bidirectional communication between the brain and the gut microbiota through metabolic, immune, neuronal, and endocrine mechanisms and pathways. Among these, the vagus nerve represents the most direct form of communication between the brain and the gut. Given the potential interactions between bacteria and drugs, it has been observed that the therapies for PD can have an impact on the composition of the microbiota. Therefore, in the scope of the present review, we will discuss the current understanding of gut microbiota on PD and whether this may be a new paradigm for treating this devastating disease.

The Effect of Gut Microbiota-Targeted Interventions on Neuroinflammation and Motor Function in Parkinson's Disease Animal Models-A Systematic Review

Gut microbiome-targeted interventions such as fecal transplant, prebiotics, probiotics, synbiotics, and antibiotic gut depletion are speculated to be of potential use in delaying the onset and progression of Parkinson's disease by rebalancing the gut microbiome in the context of the gut-brain axis. Our study aims to organize recent findings regarding these interventions in Parkinson's disease animal models to identify how they affect neuroinflammation and motor outcomes. A systematic literature search was applied in PubMed, Web of Science, Embase, and SCOPUS for gut microbiome-targeted non-dietary interventions. Studies that investigated gut-targeted interventions by using in vivo murine PD models to follow dopaminergic cell loss, motor tests, and neuroinflammatory markers as outcomes were considered to be eligible. A total of 1335 studies were identified in the databases, out of which 29 were found to be eligible. A narrative systematization of the resulting data was performed, and the effect direction for the outcomes was represented. Quality assessment using the SYRCLE risk of bias tool was also performed. Out of the 29 eligible studies, we found that a significant majority report that the intervention reduced the dopaminergic cell loss (82.76%, 95% CI [64.23%, 94.15%]) produced by the induction of the disease model. Also, most studies reported a reduction in microglial (87.5%, 95% CI [61.65%, 98.45%]) and astrocytic activation (84,62%, 95% CI [54.55%, 98.08%]) caused by the induction of the disease model. These results were also mirrored in the majority (96.4% 95% CI [81.65%, 99.91%]) of the studies reporting an increase in performance in behavioral motor tests. A significant limitation of the study was that insufficient information was found in the studies to assess specific causes of the risk of bias. These results show that non-dietary gut microbiome-targeted interventions can improve neuroinflammatory and motor outcomes in acute Parkinson's disease animal models. Further studies are needed to clarify if these benefits transfer to the long-term pathogenesis of the disease, which is not yet fully understood. The study had no funding source, and the protocol was registered in the PROSPERO database with the ID number CRD42023461495.

Fakhri M, T. Salim E, Subramaniam S. Exploring faradaic and non-faradaic electrochemical impedance spectroscopy approaches in Parkinson's disease diagnosis

Parkinson's disease is a neurodegenerative condition defined by the progressive death of dopaminergic neurons in the brain. The diagnosis of Parkinson's disease often uses time-consuming clinical evaluations and subjective assessments. Electrochemical Impedance Spectroscopy (EIS) is a useful technique for electroanalytical devices due to its label-free performance, in-situ measurements, and low cost. The development of reliable diagnostic tools for Parkinson's disease can be significantly enhanced by exploring novel techniques like faradaic and non-faradaic EIS detection methods. These techniques have the ability to identify specific biomarkers or changes in electrochemical properties linked to Parkinson's disease, allowing for an early and accurate diagnosis. Faradaic EIS detection methods utilize redox processes on the electrode surface, while non-faradaic EIS methods rely on charge transfer or capacitive properties. EIS can identify biomarkers or changes in electrical properties as indicators of Parkinson's disease by measuring impedance at different frequencies. By combining both faradaic and non-faradaic EIS approaches, it may be possible to obtain a comprehensive understanding of the electrochemical changes occurring in Parkinson's disease patients. This may lead to the development of more effective diagnostic techniques and potentially opening up new avenues for personalized treatment strategies. This review explores the current research on faradaic and non-faradaic EIS approaches for diagnosing Parkinson's disease using electrochemical impedance spectroscopy.

Cerebrospinal Fluid Metabolomic Pattern of Different Pituitary Stalk Lesions

OBJECTIVE

To describe the cerebrospinal fluid (CSF) metabolomic pattern of pituitary stalk lesions.

METHODS

CSF was collected from patients with different pituitary stalk lesions treated at Peking Union Medical College Hospital: germ cell tumor (GCT, n = 27); hypophysitis (n = 10); and Langerhans cell histiocytosis (LCH) or Erdheim-Chester disease (ECD) (LCH + ECD, n = 10). The CSF metabolome profiles were characterized by liquid chromatography-mass spectrometry (LC-MS).

RESULTS

There were 44 metabolites that significantly differed between patients with GCT and those with hypophysitis (P < .05). Between patients with GCT with CSF level of beta subunit of human chorionic gonadotrophin (β-hCG) < 5 mIU/mL and those with hypophysitis, there were 15 differential metabolites (P < .05, fold change > 1.5 or < 1/1.5). All of the metabolites had an area under the curve (AUC) above 0.7. There were 9 metabolites that significantly differed between patients with GCT and those with LCH + ECD (P < .05) and 7 metabolites had significant differences between GCT (CSF β-hCG < 5 mIU/mL) and LCH + ECD (P < .05, fold change > 1.5 or < 1/1.5). We found 6 metabolites that were significantly different between patients with hypophysitis and those with LCH + ECD (P < .05) and 5 of these had fold change more than 1.5 or less than 1/1.5. Three metabolites, 5-deoxydiplosporin, cloversaponin I, and phytosphingosine, showed excellent capabilities to differentiate the 3 disease categories. Furthermore, we identified 67 metabolites associated with clinical test results (ρ > 0.2, P < .05) and 29 metabolites showed strong correlation (ρ > 0.4, P < .05).

CONCLUSION

Our study is the first to systematically investigate the metabolomics of CSF in different pituitary stalk lesions. CSF metabolomics is a useful strategy for biomarker discovery.

Salivary Biomarkers for Parkinson's Disease: A Systematic Review with Meta-Analysis

Parkinson's Disease (PD) is a common neurodegenerative disease which manifests with motor features, such as bradykinesia, resting tremor, rigidity, and postural instability. Using the non-invasive technique of saliva collection, we designed a systematic review to answer the question "Are salivary biomarkers reliable for the diagnosis of Parkinson's Disease?". Following inclusion and exclusion criteria, 30 studies were included in this systematic review (according to the PRISMA statement guidelines). Mostly proteins were reported as potential biomarkers in saliva. Based on meta-analysis, in PD patients, salivary levels of total alpha-synuclein were significantly decreased, and those of oligomeric alpha-synuclein were significantly increased. Also, according to pooled AUC, heme oxygenase-1 demonstrated significant predictive value for saliva-based PD diagnosis. In conclusion, some potential biomarkers, especially alpha-synuclein, can be altered in the saliva of PD patients, which could be reliably useful for early diagnosis of this neurodegenerative disease differentiating other synucleopathies.

An update on new-age potential biomarkers for Parkinson's disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder that deals with dopaminergic deficiency in Substantia nigra pars compact (SNpc) region of the brain. Dopaminergic deficiency manifests into motor dysfunction. Alpha-synuclein protein aggregation is the source for inception of the pathology. Motor symptoms include rigidity, akinesia, tremor and gait dysfunction. Pre-motor symptoms are also seen in early stage of the disease; however, they are not distinguishable. Lack of early diagnosis in PD pathology poses a major challenge for development of disease modifying therapeutics. Substantial neuronal loss has already been occurred before the clinical manifestations appear and hence, it becomes impossible to halt the disease progression. Current diagnostics are majorly based on the clinical symptoms and thus fail to detect early progression of the disease. Thus, there is need for early diagnosis of PD, for detection of the disease at its inception. This will facilitate the effective use of therapies that halt the progression and will make remission possible. Many novel biomarkers are being developed that include blood-based biomarker, CSF biomarker. Other than that, there are non-invasive techniques that can detect biomarkers. We aim to discuss potential role of these new age biomarkers and their association with PD pathogenesis in this review.

Axonal Lysosomal Assays for Characterizing the Effects of LRRK2 G2019S

The degeneration of axon terminals before the soma, referred to as "dying back", is a feature of Parkinson's disease (PD). Axonal assays are needed to model early PD pathogenesis as well as identify protective therapeutics. We hypothesized that defects in axon lysosomal trafficking as well as injury repair might be important contributing factors to "dying back" pathology in PD. Since primary human PD neurons are inaccessible, we developed assays to quantify axonal trafficking and injury repair using induced pluripotent stem cell (iPSC)-derived neurons with LRRK2 G2019S, which is one of the most common known PD mutations, and isogenic controls. We observed a subtle axonal trafficking phenotype that was partially rescued by a LRRK2 inhibitor. Mutant LRRK2 neurons showed increased phosphorylated Rab10-positive lysosomes, and lysosomal membrane damage increased LRRK2-dependent Rab10 phosphorylation. Neurons with mutant LRRK2 showed a transient increase in lysosomes at axotomy injury sites. This was a pilot study that used two patient-derived lines to develop its methodology; we observed subtle phenotypes that might correlate with heterogeneity in LRRK2-PD patients. Further analysis using additional iPSC lines is needed. Therefore, our axonal lysosomal assays can potentially be used to characterize early PD pathogenesis and test possible therapeutics.

A metabolomics study in aqueous humor discloses altered arginine metabolism in Parkinson's disease

BACKGROUND

The lack of accessible and informative biomarkers results in a delayed diagnosis of Parkinson's disease (PD), whose symptoms appear when a significant number of dopaminergic neurons have already disappeared. The retina, a historically overlooked part of the central nervous system (CNS), has gained recent attention. It has been discovered that the composition of cerebrospinal fluid influences the aqueous humor composition through microfluidic circulation. In addition, alterations found in the brain of patients with PD have a correlate in the retina. This new paradigm highlights the potential of the aqueous humor as a sample for identifying differentially concentrated metabolites that could, eventually, become biomarkers if also found altered in blood or CSF of patients. In this research we aim at analyzing the composition of the aqueous humor from healthy controls and PD patients.

METHODS

A targeted metabolomics approach with concentration determination by mass spectrometry was used. Statistical methods including principal component analysis and linear discriminants were used to select differentially concentrated metabolites that allow distinguishing patients from controls.

RESULTS

In this first metabolomics study in the aqueous humor of PD patients, elevated levels of 16 compounds were found; molecules differentially concentrated grouped into biogenic amines, amino acids, and acylcarnitines. A biogenic amine, putrescine, alone could be a metabolite capable of differentiating between PD and control samples. The altered levels of the metabolites were correlated, suggesting that the elevations stem from a common mechanism involving arginine metabolism.

CONCLUSIONS

A combination of three metabolites, putrescine, tyrosine, and carnitine was able to correctly classify healthy participants from PD patients. Altered metabolite levels suggest altered arginine metabolism. The pattern of metabolomic disturbances was not due to the levodopa-based dopamine replacement medication because one of the patients was not yet taking levodopa but a dopamine receptor agonist.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Protein Biomarkers Shared by Multiple Neurodegenerative Diseases Are Calmodulin-Binding Proteins Offering Novel and Potentially Universal Therapeutic Targets

Seven major neurodegenerative diseases and their variants share many overlapping biomarkers that are calmodulin-binding proteins: Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), frontotemporal lobar dementia (FTD), Huntington's disease (HD), Lewy body disease (LBD), multiple sclerosis (MS), and Parkinson's disease (PD). Calcium dysregulation is an early and persistent event in each of these diseases, with calmodulin serving as an initial and primary target of increased cytosolic calcium. Considering the central role of calcium dysregulation and its downstream impact on calcium signaling, calmodulin has gained interest as a major regulator of neurodegenerative events. Here, we show that calmodulin serves a critical role in neurodegenerative diseases via binding to and regulating an abundance of biomarkers, many of which are involved in multiple neurodegenerative diseases. Of special interest are the shared functions of calmodulin in the generation of protein biomarker aggregates in AD, HD, LBD, and PD, where calmodulin not only binds to amyloid beta, pTau, alpha-synuclein, and mutant huntingtin but also, via its regulation of transglutaminase 2, converts them into toxic protein aggregates. It is suggested that several calmodulin binding proteins could immediately serve as primary drug targets, while combinations of calmodulin binding proteins could provide simultaneous insight into the onset and progression of multiple neurodegenerative diseases.

Toward Personalized Medicine Approaches for Parkinson Disease Using Digital Technologies

Parkinson disease (PD) is a complex neurodegenerative disorder that afflicts over 10 million people worldwide, resulting in debilitating motor and cognitive impairment. In the United States alone (with approximately 1 million cases), the economic burden for treating and caring for persons with PD exceeds US $50 billion and myriad therapeutic approaches are under development, including both symptomatic- and disease-modifying agents. The challenges presented in addressing PD are compounded by observations that numerous, statistically distinct patient phenotypes present with a wide variety of motor and nonmotor symptomatic profiles, varying responses to current standard-of-care symptom-alleviating medications (L-DOPA and dopaminergic agonists), and different disease trajectories. The existence of these differing phenotypes highlights the opportunities in personalized approaches to symptom management and disease control. The prodromal period of PD can span across several decades, allowing the potential to leverage the unique array of composite symptoms presented to trigger early interventions. This may be especially beneficial as disease progression in PD (alongside Alzheimer disease and Huntington disease) may be influenced by biological processes such as oxidative stress, offering the potential for individual lifestyle factors to be tailored to delay disease onset. In this viewpoint, we offer potential scenarios where emerging diagnostic and monitoring strategies might be tailored to the individual patient under the tenets of P4 medicine (predict, prevent, personalize, and participate). These approaches may be especially relevant as the causative factors and biochemical pathways responsible for the observed neurodegeneration in patients with PD remain areas of fluid debate. The numerous observational patient cohorts established globally offer an excellent opportunity to test and refine approaches to detect, characterize, control, modify the course, and ultimately stop progression of this debilitating disease. Such approaches may also help development of parallel interventive strategies in other diseases such as Alzheimer disease and Huntington disease, which share common traits and etiologies with PD. In this overview, we highlight near-term opportunities to apply P4 medicine principles for patients with PD and introduce the concept of composite orthogonal patient monitoring.

Cerebrospinal fluid-contacting neurons: multimodal cells with diverse roles in the CNS

The cerebrospinal fluid (CSF) is a complex solution that circulates around the CNS, and whose composition changes as a function of an animal's physiological state. Ciliated neurons that are bathed in the CSF - and thus referred to as CSF-contacting neurons (CSF-cNs) - are unusual polymodal interoceptive neurons. As chemoreceptors, CSF-cNs respond to variations in pH and osmolarity and to bacterial metabolites in the CSF. Their activation during infections of the CNS results in secretion of compounds to enhance host survival. As mechanosensory neurons, CSF-cNs operate together with an extracellular proteinaceous polymer known as the Reissner fibre to detect compression during spinal curvature. Once activated, CSF-cNs inhibit motor neurons, premotor excitatory neurons and command neurons to enhance movement speed and stabilize posture. At longer timescales, CSF-cNs instruct morphogenesis throughout life via the release of neuropeptides that act over long distances on skeletal muscle. Finally, recent evidence suggests that mouse CSF-cNs may act as neural stem cells in the spinal cord, inspiring new paths of investigation for repair after injury.

Cerebrospinal fluid GFAP is a predictive biomarker for conversion to dementia and Alzheimer's disease-associated biomarkers alterations among de novo Parkinson's disease patients: a prospective cohort study

BACKGROUND

Dementia is a prevalent non-motor manifestation among individuals with advanced Parkinson's disease (PD). Glial fibrillary acidic protein (GFAP) is an inflammatory marker derived from astrocytes. Research has demonstrated the potential of plasma GFAP to forecast the progression to dementia in PD patients with mild cognitive impairment (PD-MCI). However, the predictive role of cerebrospinal fluid (CSF) GFAP on future cognitive transformation and alterations in Alzheimer's disease (AD)-associated CSF biomarkers in newly diagnosed PD patients has not been investigated.

METHODS

210 de novo PD patients from the Parkinson's Progression Markers Initiative were recruited. Cognitive progression in PD participants was evaluated using Cox regression. Cross-sectional and longitudinal associations between baseline CSF GFAP and cognitive function and AD-related CSF biomarkers were evaluated using multiple linear regression and generalized linear mixed model.

RESULTS

At baseline, the mean age of PD participants was 60.85 ± 9.78 years, including 142 patients with normal cognition (PD-NC) and 68 PD-MCI patients. The average follow-up time was 6.42 ± 1.69 years. A positive correlation was observed between baseline CSF GFAP and age (β = 0.918, p < 0.001). There was no statistically significant difference in baseline CSF GFAP levels between PD-NC and PD-MCI groups. Higher baseline CSF GFAP predicted greater global cognitive decline over time in early PD patients (Montreal Cognitive Assessment, β = - 0.013, p = 0.014). Furthermore, Cox regression showed that high baseline CSF GFAP levels were associated with a high risk of developing dementia over an 8-year period in the PD-NC group (adjusted HR = 3.070, 95% CI 1.119-8.418, p = 0.029). In addition, the baseline CSF GFAP was positively correlated with the longitudinal changes of not only CSF α-synuclein (β = 0.313, p < 0.001), but also CSF biomarkers associated with AD, namely, amyloid-β 42 (β = 0.147, p = 0.034), total tau (β = 0.337, p < 0.001) and phosphorylated tau (β = 0.408, p < 0.001).

CONCLUSIONS

CSF GFAP may be a valuable prognostic tool that can predict the severity and progression of cognitive deterioration, accompanied with longitudinal changes in AD-associated pathological markers in early PD.

Neuroinflammation and Mitochondrial Dysfunction in Parkinson's Disease: Connecting Neuroimaging with Pathophysiology

There is a pressing need for disease-modifying therapies in patients suffering from neurodegenerative diseases, including Parkinson's disease (PD). However, these disorders face unique challenges in clinical trial designs to assess the neuroprotective properties of potential drug candidates. One of these challenges relates to the often unknown individual disease mechanisms that would, however, be relevant for targeted treatment strategies. Neuroinflammation and mitochondrial dysfunction are two proposed pathophysiological hallmarks and are considered to be highly interconnected in PD. Innovative neuroimaging methods can potentially help to gain deeper insights into one's predominant disease mechanisms, can facilitate patient stratification in clinical trials, and could potentially map treatment responses. This review aims to highlight the role of neuroinflammation and mitochondrial dysfunction in patients with PD (PwPD). We will specifically introduce different neuroimaging modalities, their respective technical hurdles and challenges, and their implementation into clinical practice. We will gather preliminary evidence for their potential use in PD research and discuss opportunities for future clinical trials.

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.

Ganglioside analysis in body fluids by liquid-phase separation techniques hyphenated to mass spectrometry

The expression of gangliosides in central nervous system is a few times higher than in the extraneural tissue, a characteristic highlighting their major role at this level. Although in very low amounts, gangliosides are ubiquitously distributed in body fluids too, where, depending on many factors, including pathological states, their composition fluctuates, thus having diagnostic value. Ganglioside investigation in biological fluids, which, except for cerebrospinal fluid (CSF), may be sampled noninvasively, was for years impeded by the limited sensitivity of the analytical instrumentation available in glycomics. However, because the last decade has witnessed significant developments in biological mass spectrometry (MS) and the hyphenated separation techniques, marked by a major increase in sensitivity, reproducibility, and data reliability, ganglioside research started to be focused on biofluid analysis by separation techniques coupled to MS. In this context, our review presents the achievements in this emerging field of gangliosidomics, with a particular emphasis on modern liquid chromatography (LC), thin-layer chromatography, hydrophilic interaction LC, and ion mobility separation coupled to high-performance MS, as well as the results generated by these systems and allied experimental procedures in profiling and structural analysis of gangliosides in healthy or diseased body fluids, such as CSF, plasma/serum, and milk.

Metabolomic Footprint of Disrupted Energetics and Amino Acid Metabolism in Neurodegenerative Diseases: Perspectives for Early Diagnosis and Monitoring of Therapy

The prevalence of neurodegenerative diseases (NDs) is increasing due to the aging population and improved longevity. They are characterized by a range of pathological hallmarks, including protein aggregation, mitochondrial dysfunction, and oxidative stress. The aim of this review is to summarize the alterations in brain energy and amino acid metabolism in Alzheimer’s disease (AD), Parkinson’s disease (PD), and Huntington’s disease (HD). Based on our findings, we proposed a group of selected metabolites related to disturbed energy or mitochondrial metabolism as potential indicators or predictors of disease. We also discussed the hidden challenges of metabolomics studies in NDs and proposed future directions in this field. We concluded that biochemical parameters of brain energy metabolism disruption (obtained with metabolomics) may have potential application as a diagnostic tool for the diagnosis, prediction, and monitoring of the effectiveness of therapies for NDs. However, more studies are needed to determine the sensitivity of the proposed candidates. We suggested that the most valuable biomarkers for NDs studies could be groups of metabolites combined with other neuroimaging or molecular techniques. To attain clinically applicable results, the integration of metabolomics with other “omic” techniques might be required.

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.

Outcome Measures for Disease-Modifying Trials in Parkinson's Disease: Consensus Paper by the EJS ACT-PD Multi-Arm Multi-Stage Trial Initiative

BACKGROUND

Multi-arm, multi-stage (MAMS) platform trials can accelerate the identification of disease-modifying treatments for Parkinson's disease (PD) but there is no current consensus on the optimal outcome measures (OM) for this approach.

OBJECTIVE

To provide an up-to-date inventory of OM for disease-modifying PD trials, and a framework for future selection of OM for such trials.

METHODS

As part of the Edmond J Safra Accelerating Clinical Trials in Parkinson Disease (EJS ACT-PD) initiative, an expert group with Patient and Public Involvement and Engagement (PPIE) representatives' input reviewed and evaluated available evidence on OM for potential use in trials to delay progression of PD. Each OM was ranked based on aspects such as validity, sensitivity to change, participant burden and practicality for a multi-site trial. Review of evidence and expert opinion led to the present inventory.

RESULTS

An extensive inventory of OM was created, divided into: general, motor and non-motor scales, diaries and fluctuation questionnaires, cognitive, disability and health-related quality of life, capability, quantitative motor, wearable and digital, combined, resource use, imaging and wet biomarkers, and milestone-based. A framework for evaluation of OM is presented to update the inventory in the future. PPIE input highlighted the need for OM which reflect their experience of disease progression and are applicable to diverse populations and disease stages.

CONCLUSION

We present a range of OM, classified according to a transparent framework, to aid selection of OM for disease-modifying PD trials, whilst allowing for inclusion or re-classification of relevant OM as new evidence emerges.

Future Prospects in Parkinson's Disease Diagnosis and Treatment

Parkinson's disease (PD) is a neurodegenerative disease with a rapidly increasing incidence and prevalence. Although it affects more than 6 million people worldwide, it is predicted to be doubled by 2040. Current criteria used in the diagnosis of PD include the presence of bradykinesia as well as the presence of rest tremor and/or rigidity, but the clinic is multifaceted and includes many non-motor symptoms. Non-motor symptoms may occur in the prodromal period, years before clinically evident Parkinson's disease. During this period, diagnosing the disease will likely be even more important when disease-modifying treatments are available. Currently, there is no single biomarker that can be used in the diagnosis of PD and no disease-modifying treatment is available. Identification of biomarkers in early diagnosis will enable the most effective use of disease-modifying therapies and will shed light on possible underlying pathologies, studies in this area have gained momentum in recent years. Molecular imaging methods, genetic studies, salivary gland and skin biopsies, metabolomics, lysosomal pathway are some of them. In this article, besides the current diagnosis and treatment methods of the disease, biomarkers and treatments that are expected to be better understood in the near future will be mentioned.

Relevance of plasma biomarkers to pathologies in Alzheimer's disease, Parkinson's disease and frontotemporal dementia

Amyloid plaques and tau tangles are pathological hallmarks of Alzheimer's disease (AD). Parkinson's disease (PD) results from the accumulation of α-synuclein. TAR DNA-binding protein (TDP-43) and total tau protein (T-Tau) play roles in FTD pathology. All of the pathological evidence was found in the biopsy. However, it is impossible to perform stein examinations in clinical practice. Assays of biomarkers in plasma would be convenient. It would be better to investigate the combinations of various biomarkers in AD, PD and FTD. Ninety-one subjects without neurodegenerative diseases, 76 patients with amnesic mild cognitive impairment (aMCI) or AD dementia, combined as AD family, were enrolled. One hundred and nine PD patients with normal cognition (PD-NC) or dementia (PDD), combined as PD family, were enrolled. Twenty-five FTD patients were enrolled for assays of plasma amyloid β 1-40 (Aβ_1-40), Aβ_1-42, T-Tau, α-synuclein and TDP-43 using immunomagnetic reduction (IMR). The results show that Aβs and T-Tau are major domains in AD family. α-synuclein is highly dominant in PD family. FTD is closely associated with TDP-43 and T-Tau. The dominant plasma biomarkers in AD family, PD family and FTD are consistent with pathology. This implies that plasma biomarkers are promising for precise and differential assessments of AD, PD and FTD in clinical practice.

Biomarkers Related to Synaptic Dysfunction to Discriminate Alzheimer's Disease from Other Neurological Disorders

Recently, the synaptic proteins neurogranin (Ng) and α-synuclein (α-Syn) have attracted scientific interest as potential biomarkers for synaptic dysfunction in neurodegenerative diseases. In this study, we measured the CSF Ng and α-Syn concentrations in patients affected by AD (n = 69), non-AD neurodegenerative disorders (n-AD = 50) and non-degenerative disorders (n-ND, n = 98). The concentrations of CSF Ng and α-Syn were significantly higher in AD than in n-AD and n-ND. Moreover, the Aβ42/Ng and Aβ42/α-Syn ratios showed statistically significant differences between groups and discriminated AD patients from n-AD patients, better than Ng or α-Syn alone. Regression analyses showed an association of higher Ng concentrations with MMSE < 24, pathological Aβ 42/40 ratios, pTau, tTau and the ApoEε4 genotype. Aβ 42/Ng was associated with MMSE < 24, an AD-related FDG-PET pattern, the ApoEε4 genotype, pathological Aβ 42 levels and Aβ 42/40 ratios, pTau, and tTau. Moreover, APO-Eε4 carriers showed higher Ng concentrations than non-carriers. Our results support the idea that the Aβ 42/Ng ratio is a reliable index of synaptic dysfunction/degeneration able to discriminate AD from other neurological conditions.

Multi-predictor modeling for predicting early Parkinson’s disease and non-motor symptoms progression

Background

Identifying individuals with high-risk Parkinson’s disease (PD) at earlier stages is an urgent priority to delay disease onset and progression. In the present study, we aimed to develop and validate clinical risk models using non-motor predictors to distinguish between early PD and healthy individuals. In addition, we constructed prognostic models for predicting the progression of non-motor symptoms [cognitive impairment, Rapid-eye-movement sleep Behavior Disorder (RBD), and depression] in de novo PD patients at 5 years of follow-up.

Methods

We retrieved the data from the Parkinson’s Progression Markers Initiative (PPMI) database. After a backward variable selection approach to identify predictors, logistic regression analyses were applied for diagnosis model construction, and cox proportional-hazards models were used to predict non-motor symptom progression. The predictive models were internally validated by correcting measures of predictive performance for “optimism” or overfitting with the bootstrap resampling approach.

Results

For constructing diagnostic models, the final model reached a high accuracy with an area under the curve (AUC) of 0.93 (95% CI: 0.91–0.96), which included eight variables (age, gender, family history, University of Pennsylvania Smell Inventory Test score, Montreal Cognitive Assessment score, RBD Screening Questionnaire score, levels of cerebrospinal fluid α-synuclein, and SNCA rs356181 polymorphism). For the construction of prognostic models, our results showed that the AUC of the three prognostic models improved slightly with increasing follow-up time. The overall AUCs fluctuated around 0.70. The model validation established good discrimination and calibration for predicting PD onset and progression of non-motor symptoms.

Conclusion

The findings of our study facilitate predicting the individual risk at an early stage based on the predictors derived from these models. These predictive models provide relatively reliable information to prevent PD onset and progression. However, future validation analysis is still needed to clarify these findings and provide more insight into the predictive models over more extended periods of disease progression in more diverse samples.

Disease modification in Parkinsonism: obstacles and ways forward

To date, the diagnoses of Parkinson syndromes are based on clinical examination. Therefore, these specific diagnoses are made, when the neuropathological process is already advanced. However, disease modification or neuroprotection, is considered to be most effective before marked neurodegeneration has occurred. In recent years, early clinical or prodromal stages of Parkinson syndromes came into focus. Moreover, subtypes of distinct diseases will allow predictions of the individual course of the diseases more precisely. Thereby, patients will be enrolled into clinical trials with more specific disease entities and endpoints. Furthermore, novel fluid and imaging biomarkers that allow biochemical diagnoses are under development. These will lead to earlier diagnoses and earlier therapy in the future as consequence. Furthermore, therapeutic approaches will take the underlying neuropathological process of neurodegenerative Parkinson syndromes more specific into account. Specifically, future therapies will target the aggregation of aggregation-prone proteins such as alpha-synuclein and tau, the degradation of pathological aggregates, and the spreading of pathological protein aggregates throughout the brain. Many of these approaches are already in (pre)clinical development. In addition, anti-inflammatory approaches are in development. Furthermore, drug-repurposing is a feasible approach to shorten the developmental process of new drugs.

A Randomized First‐in‐Human Study With UB‐312, a UBITh® α‐Synuclein Peptide Vaccine

Background

α‐Synuclein (αSyn) is believed to play a central role in Parkinson's disease (PD) neuropathology and is considered a target for disease modification. UB‐312 is a synthetic αSyn peptide conjugated to a T helper peptide and is expected to induce antibodies specifically against oligomeric and fibrillar αSyn, making UB‐312 a potential immunotherapeutic for synucleopathies.

Objective

To investigate the safety, tolerability, and immunogenicity of UB‐312 vaccination in healthy participants and to determine a safe and immunologically optimal dose for the first‐in‐patient study.

Methods

Fifty eligible healthy participants were enrolled in a 44‐week, randomized, placebo‐controlled, double‐blind study. Participants in seven cohorts were randomized to three intramuscular UB‐312 or placebo injections at weeks 1, 5, and 13 (doses ranging between 40 and 2000 μg). Safety and tolerability were assessed by adverse events, clinical laboratory, vital signs, electrocardiograms, and neurological and physical examinations. Immunogenicity was assessed by measuring serum and cerebrospinal fluid (CSF) anti‐αSyn antibody concentrations.

Results

Twenty‐three participants received all three vaccinations of UB‐312. Most adverse events were mild, transient, and self‐resolving. Common treatment‐emergent adverse events included headache, nasopharyngitis, vaccination‐site pain, lumbar puncture‐site pain, and fatigue. UB‐312 induced dose‐ and time‐dependent antibody production. Antibodies were detectable in serum and CSF of all participants receiving the 300/300/300 μg UB‐312 dose regimen. The average CSF/serum ratio was 0.2%.

Conclusions

UB‐312 was generally safe, well tolerated, and induced anti‐αSyn antibodies in serum and CSF of healthy participants. The 100 and 300 μg doses are selected for further evaluation in participants with PD. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society