Cerebrospinal Fluid Levels of 5-Hydroxyindoleacetic Acid in Parkinson's Disease and Atypical Parkinsonian Syndromes

Correlations between serotonin impairments and clinical indices in multiple system atrophy

BACKGROUND AND PURPOSE

Multiple system atrophy (MSA) is a neurodegenerative disease with characteristic motor and autonomic symptoms. Impaired brain serotonergic innervation can be associated with various clinical indices of MSA; however, the relationship between clinical symptoms and cerebrospinal fluid (CSF) levels of 5-hydroxyindole acetic acid (5-HIAA), a main serotonin metabolite, has not been fully elucidated.

METHODS

To compare CSF 5-HIAA levels between patients with MSA and healthy controls, we included 33 controls and 69 MSA patients with either predominant parkinsonian or cerebellar ataxia subtypes. CSF 5-HIAA levels were measured using high-performance liquid chromatography. Additionally, we investigated correlations between CSF 5-HIAA and various clinical indices in 34 MSA patients.

RESULTS

CSF 5-HIAA levels were significantly lower in MSA patients than in controls (p < 0.0001). Probable MSA patients had lower CSF 5-HIAA levels than possible MSA patients (p < 0.001). In MSA patients, CSF 5-HIAA levels were inversely correlated with scores in Parts 1, 2, and 4 of the Unified Multiple System Atrophy Rating Scale, and with systolic and diastolic blood pressure in Part 3. Structural equation modeling revealed significant paths between serotonin and clinical symptoms, and significance was highest for activities of daily living, walking, and body sway.

CONCLUSIONS

Serotonin dysfunction, as assessed by CSF 5-HIAA levels, may implicate greater MSA severity.

Patients with Neurodegenerative Proteinopathies Exhibit Altered Tryptophan Metabolism in the Serum and Cerebrospinal Fluid

Some pathological conditions affecting the human body can also disrupt metabolic pathways and thus alter the overall metabolic profile. Knowledge of metabolic disturbances in specific diseases could thus enable the differential diagnosis of otherwise similar conditions. This work therefore aimed to comprehensively characterize changes in tryptophan metabolism in selected neurodegenerative diseases. Levels of 18 tryptophan-related neuroactive substances were determined by high throughput and sensitive ultrahigh-performance liquid chromatography-tandem mass spectrometry in time-linked blood serum and cerebrospinal fluid samples from 100 age-matched participants belonging to five cohorts: healthy volunteers (n = 21) and patients with Lewy body disease (Parkinson's disease and dementia with Lewy bodies; n = 31), four-repeat tauopathy (progressive supranuclear palsy and corticobasal syndrome; n = 10), multiple system atrophy (n = 13), and Alzheimer's disease (n = 25). Although these conditions have different pathologies and clinical symptoms, the discovery of new biomarkers is still important. The most statistically significant differences (with p-values of ≤0.05 to ≤0.0001) between the study cohorts were observed for three tryptophan metabolites: l-kynurenine in cerebrospinal fluid and 3-hydroxy-l-kynurenine and 5-hydroxy-l-tryptophan in blood serum. This led to the discovery of distinctive correlation patterns between the profiled cerebrospinal fluid and serum metabolites that could provide a basis for the differential diagnosis of neurodegenerative tauopathies and synucleinopathies. However, further large-scale studies are needed to determine the direct involvement of these metabolites in the studied neuropathologies, their response to medication, and their potential therapeutic relevance.

Transcriptome-based biomarker prediction for Parkinson's disease using genome-scale metabolic modeling

Parkinson's disease (PD) is the second most common neurodegenerative disease in the world. Identification of PD biomarkers is crucial for early diagnosis and to develop target-based therapeutic agents. Integrative analysis of genome-scale metabolic models (GEMs) and omics data provides a computational approach for the prediction of metabolite biomarkers. Here, we applied the TIMBR (Transcriptionally Inferred Metabolic Biomarker Response) algorithm and two modified versions of TIMBR to investigate potential metabolite biomarkers for PD. To this end, we mapped thirteen post-mortem PD transcriptome datasets from the substantia nigra region onto Human-GEM. We considered a metabolite as a candidate biomarker if its production was predicted to be more efficient by a TIMBR-family algorithm in control or PD case for the majority of the datasets. Different metrics based on well-known PD-related metabolite alterations, PD-associated pathways, and a list of 25 high-confidence PD metabolite biomarkers compiled from the literature were used to compare the prediction performance of the three algorithms tested. The modified algorithm with the highest prediction power based on the metrics was called TAMBOOR, TrAnscriptome-based Metabolite Biomarkers by On-Off Reactions, which was introduced for the first time in this study. TAMBOOR performed better in terms of capturing well-known pathway alterations and metabolite secretion changes in PD. Therefore, our tool has a strong potential to be used for the prediction of novel diagnostic biomarkers for human diseases.

CSF Aβ40 Levels Do Not Correlate with the Clinical Manifestations of Alzheimer's Disease

INTRODUCTION

Cerebrospinal fluid (CSF) biomarker quantification provides physicians with a reliable diagnosis of Alzheimer's disease (AD). However, the relationship between their concentration and disease course has not been clearly elucidated. This work aimed to investigate the clinical and prognostic significance of Aβ40 CSF levels.

METHODS

A retrospective cohort of 76 patients diagnosed with AD using a decreased Aβ42/Aβ40 ratio was subclassified into hyposecretors (Aβ40 <7,755 pg/mL), normosecretors (Aβ40 7,755-16,715 pg/mL), and hypersecretors (Aβ40 >16,715 pg/mL). Potential differences in AD phenotype, Montreal Cognitive Assessment (MoCA) scores, and Global Deterioration Scale (GDS) stages were assessed. Correlation tests for biomarker concentrations were also performed.

RESULTS

Participants were classified as hyposecretors (n = 22, median Aβ40 5,870.500 pg/mL, interquartile range [IQR] 1,431), normosecretors (n = 47, median Aβ40 10,817 pg/mL, IQR 3,622), and hypersecretors (n = 7, 19,767 pg/mL, IQR 3,088). The distribution of positive phosphorylated Tau (p-Tau) varied significantly between subgroups and was more common in the normo- and hypersecretor categories (p = 0.003). Aβ40 and p-Tau concentrations correlated positively (ρ = 0.605, p < 0.001). No significant differences were found among subgroups regarding age, initial MoCA score, initial GDS stage, progression to the dementia stage, or changes in the MoCA score.

CONCLUSION

In this study, we found no significant differences in clinical symptoms or disease progression in AD patients according to their CSF Aβ40 concentration. Aβ40 was positively correlated with p-Tau and total Tau concentrations, supporting their potential interaction in AD pathophysiology.

A story of the potential effect of non-steroidal anti-inflammatory drugs (NSAIDs) in Parkinson's disease: beneficial or detrimental effects

Parkinson's disease (PD) is an advanced neurodegenerative disease (NDD) caused by the degeneration of dopaminergic neurons (DNs) in the substantia nigra (SN). As PD is an age-related disorder, the majority of PD patients are associated with musculoskeletal disorders with prolonged use of analgesic and anti-inflammatory agents, such as non-steroidal anti-inflammatory drugs (NSAIDs). Therefore, NSAIDs can affect PD neuropathology in different ways. Thus, the objective of the present narrative review was to clarify the potential role of NSAIDs in PD according to the assorted view of preponderance. Inhibition of neuroinflammation and modulation of immune response by NSAIDs could be an effective way in preventing the development of NDD. NSAIDs affect PD neuropathology in different manners could be beneficial or detrimental effects. Inhibition of cyclooxygenase 2 (COX2) by NSAIDs may prevent the development of PD. NSAIDs afforded a neuroprotective role against the development and progression of PD neuropathology through the  modulation of neuroinflammation. Though, NSAIDs may lead to neutral or harmful effects by inhibiting neuroprotective prostacyclin (PGI2) and accentuation of pro-inflammatory leukotrienes (LTs). In conclusion, there is still a potential conflict regarding the effect of NSAIDs on PD neuropathology.

Neurobiology of depression in Parkinson's disease: Insights into epidemiology, molecular mechanisms and treatment strategies

Parkinson's disease (PD) is characterized mainly by motor dysfunctions due to the progressive loss of dopaminergic neurons. However, PD patients experience a multitude of debilitating non-motor symptoms, including depression, which may have deleteriously detrimental effects on life. Depression is multifactorial and exhibits a bimodal progression in PD, but its underlying molecular mechanisms are poorly understood. Studies demonstrating the pathophysiology of depression in PD and the specific treatment strategies for depression-like symptoms in PD patients are largely lacking, often underrated, under-recognized and, consequently, inadequately/under-treated. Nevertheless, reports suggest that the incidence of depression is approximately 20-30% of PD patients and may precede the onset of motor symptoms. Diagnosing depression in PD becomes difficult due to the clinical overlap in symptomatology between the two diseases, and the nigrostriatal dysfunction alone is insufficient to explain depressive symptoms in PD. Therefore, the current study provides an overview of the molecular mechanisms underlying the development of depression in PD and new insights into developing current antidepressant strategies to treat depression in PD. This review will identify and understand the molecular pathological mechanisms of depression in PD that will fundamentally help tailoring therapeutic interventions for depressive symptoms in PD.

Serotonin in synucleinopathies

Dysfunction of the serotonergic system represents an important feature in synucleinopathies like Parkinson disease (PD), dementia with Lewy bodies (DLB) and Multiple system atrophy (MSA). Serotonergic fibers from the raphe nuclei (RN) extend broadly throughout the central nervous system, innervating several brain areas affected in synucleinopathies. Alterations of the serotonergic system are associated with non-motor symptoms or motor complications in PD as well as with autonomic features of MSA. Postmortem studies, data from transgenic animal models and imaging techniques greatly contributed to the understanding of this serotonergic pathophysiology in the past, even leading to preclinical and clinical candidate drug tests targeting different parts of the serotonergic system. In this article, we review most recent work extending the knowledge of the serotonergic system and highlighting its relevance for the pathophysiology of synucleinopathies.

Metabolites and Biomarker Compounds of Neurodegenerative Diseases in Cerebrospinal Fluid

Despite recent advances in diagnostic procedures for neurological disorders, it is still difficult to definitively diagnose some neurodegenerative diseases without neuropathological examination of autopsied brain tissue. As pathological processes in the brain are frequently reflected in the components of cerebrospinal fluid (CSF), CSF samples are sometimes useful for diagnosis. After CSF is secreted from the choroid plexus epithelial cells in the ventricles, some flows in the brain, some is mixed with intracerebral interstitial fluid, and some is excreted through two major drainage pathways, i.e., the intravascular periarterial drainage pathway and the glymphatic system. Accordingly, substances produced by metabolic and pathological processes in the brain may be detectable in CSF. Many papers have reported changes in the concentration of substances in the CSF of patients with metabolic and neurological disorders, some of which can be useful biomarkers of the disorders. In this paper, we show the significance of glucose- and neurotransmitter-related CSF metabolites, considering their transporters in the choroid plexus; summarize the reported candidates of CSF biomarkers for neurodegenerative diseases, including amyloid-β, tau, α-synuclein, microRNAs, and mitochondrial DNA; and evaluate their potential as efficient diagnostic tools.

Cerebrospinal Fluid Metabolome in Parkinson's Disease and Multiple System Atrophy

Parkinson’s disease (PD) and multiple system atrophy (MSA) belong to the neurodegenerative group of synucleinopathies; differential diagnosis between PD and MSA is difficult, especially at early stages, owing to their clinical and biological similarities. Thus, there is a pressing need to identify metabolic biomarkers for these diseases. The metabolic profile of the cerebrospinal fluid (CSF) is reported to be altered in PD and MSA; however, the altered metabolites remain unclear. We created a single network with altered metabolites in PD and MSA based on the literature and assessed biological functions, including metabolic disorders of the nervous system, inflammation, concentration of ATP, and neurological disorder, through bioinformatics methods. Our in-silico prediction-based metabolic networks are consistent with Parkinsonism events. Although metabolomics approaches provide a more quantitative understanding of biochemical events underlying the symptoms of PD and MSA, limitations persist in covering molecules related to neurodegenerative disease pathways. Thus, omics data, such as proteomics and microRNA, help understand the altered metabolomes mechanism. In particular, integrated omics and machine learning approaches will be helpful to elucidate the pathological mechanisms of PD and MSA. This review discusses the altered metabolites between PD and MSA in the CSF and omics approaches to discover diagnostic biomarkers.