Identification of blood-based biomarkers for diagnosis and prognosis of Parkinson's disease: A systematic review of proteomics studies

Prominent role of PM10 in the link between air pollution and incident Parkinson's Disease

Air pollution has been associated with Parkinson's Disease (PD) risk, although this relationship remains unclear. We estimated yearly levels of exposure to ten air pollutants (period 2006-2018) in an Italian population cohort, the Moli-sani study (N = 24,325; ≥35 years; 51.9% women), and derived three principal components, testing their associations with incident PD risk over 23,841 participants (213 cases, median(IQR) follow-up 11.2(2.0) years). This revealed a statistically significant association of PC1 (explaining 38.2% of common variance, tagging PM10 levels), independent on sociodemographic, professional and lifestyles covariates (Hazard Ratio [95%CI] = 1.04[1.02-1.07]). The association was confirmed testing average PM10 levels during follow-up (18[13-24]% increase of PD risk per 1 μg/m3 increase of PM10). Among different circulating markers, lipoprotein a explained a significant proportion of this association (2.8[0.9; 8.4]%). These findings suggest PM10 as a target to lower PD risk at the population level and a potential implication of lipoprotein a in PD etiology.

Cardiovascular health and its association with dementia, Parkinson's Disease, and mortality among UK older adults

Background

Previous research has primarily examined individual factors of cardiovascular health (CVH) and disease in PD and dementia, but no study has examined CVH measures with PD, dementia, and mortality simultaneously while accounting for potentially confounding factors.

Objectives

To examine the relationship between CVH, all-cause dementia, Parkinson's disease (PD), and mortality, focusing on associations and health transitions from a large population-based study.

Methods

We investigated these relationships using Cox Proportional Hazards and multistate parametric models with Weibull regression from the UK Biobank data (n = 269,816, Age = 50 + y individuals, ≤15y follow-up, 2006-2021).

Results

Full Cox models found poor CVH (measured with standardized reverse-coded Life's Essential 8 total score, LE8zrev), to be associated with increased risks for all-cause dementia (Hazard Ratio (HR) = 1.14, 95 % CI: 1.11-1.18, P < 0.001) and all-cause mortality (HR = 1.31, 95 % CI: 1.29-1.33, P < 0.001). Unlike "Healthy to PD" and "Dementia→Death" transitions, PD→Death (Weibull full model: HR = 1.18, 95 % CI: 1.06-1.31, P = 0.002), Healthy→dementia (HR = 1.15, 95 % CI: 1.12-1.19, P < 0.001), and Healthy→Death (HR = 1.33, 95 % CI: 1.32-1.35, P < 0.001) exhibited a positive relationship with poor CVH.

Conclusions

Poor CVH is directly associated with an increased risk of mortality from PD, transition into Dementia, and all-cause mortality without dementia or PD occurrence. Clinicians should aggressively screen for and manage CVH risk measures to reduce the risk of poor cognitive health outcomes.

Large-scale proteomic analyses of incident Parkinson's disease reveal new pathophysiological insights and potential biomarkers

The early pathophysiology of Parkinson's disease (PD) is poorly understood. We analyzed 2,920 Olink-measured plasma proteins in 51,804 UK Biobank participants, identifying 859 incident PD cases after 14.45 years. We found 38 PD-related proteins, with six of the top ten validated in the Parkinson's Progression Markers Initiative (PPMI) cohort. ITGAV, HNMT and ITGAM showed consistent significant association (hazard ratio: 0.11-0.57, P = 6.90 × 10-24 to 2.10 × 10-11). Lipid metabolism dysfunction was evident 15 years before PD onset, and levels of BAG3, HPGDS, ITGAV and PEPD continuously decreased before diagnosis. These proteins were linked to prodromal symptoms and brain measures. Mendelian randomization suggested ITGAM and EGFR as potential causes of PD. A predictive model using machine learning combined the top 16 proteins and demographics, achieving high accuracy for 5-year (area under the curve (AUC) = 0.887) and over-5-year PD prediction (AUC = 0.816), outperforming demographic-only models. It was externally validated in PPMI (AUC = 0.802). Our findings reveal early peripheral pathophysiological changes in PD crucial for developing early biomarkers and precision therapies.

Urinary based biomarkers identification and genetic profiling in Parkinson's disease: a systematic review of metabolomic studies

Background

Parkinson's disease is a complex, age-related, neurodegenerative disease associated with dopamine deficiency and both motor and nonmotor deficits. Therapeutic pathways remain challenging in Parkinson's disease due to the low accuracy of early diagnosis, the difficulty in monitoring disease progression, and the limited availability of treatment options.

Objectives

Few data are present to identify urinary biomarkers for various ailments, potentially aiding in the diagnosis and tracking of illness progression in individuals with Parkinson's disease. Thus, the analysis of urinary metabolomic biomarkers (UMB) for early and mid-stage idiopathic Parkinson's disease (IPD) is the main goal of this systematic review.

Methods

For this study, six electronic databases were searched for articles published up to 23 February 2024: PubMed, Ovid Medline, Embase, Scopus, Science Direct, and Cochrane. 5,377 articles were found and 40 articles were screened as per the eligibility criteria. Out of these, 7 controlled studies were selected for this review. Genetic profiling for gene function and biomarker interactions between urinary biomarkers was conducted using the STRING and Cytoscape database.

Results

A total of 40 metabolites were identified to be related to the early and mid-stage of the disease pathology out of which three metabolites, acetyl phenylalanine (a subtype of phenylalanine), tyrosine and kynurenine were common and most significant in three studies. These metabolites cause impaired dopamine synthesis along with mitochondrial disturbances and brain energy metabolic disturbances which are considered responsible for neurodegenerative disorders. Furoglycine, Cortisol, Hydroxyphenylacetic acid, Glycine, Tiglyglycine, Aminobutyric acid, Hydroxyprogesterone, Phenylacetylglutamine, and Dihydrocortisol were also found commonly dysregulated in two of the total 7 studies. 158 genes were found which are responsible for the occurrence of PD and metabolic regulation of the corresponding biomarkers from our study.

Conclusion

The current review identified acetyl phenylalanine (a subtype of phenylalanine), tyrosine and kynurenine as potential urinary metabolomic biomarkers for diagnosing PD and identifying disease progression.

The complement system in neurodegenerative and inflammatory diseases of the central nervous system

Neurodegenerative and neuroinflammatory diseases, including Alzheimer's disease, Parkinson's disease, and multiple sclerosis, affect millions of people globally. As aging is a major risk factor for neurodegenerative diseases, the continuous increase in the elderly population across Western societies is also associated with a rising prevalence of these debilitating conditions. The complement system, a crucial component of the innate immune response, has gained increasing attention for its multifaceted involvement in the normal development of the central nervous system (CNS) and the brain but also as a pathogenic driver in several neuroinflammatory disease states. Although complement is generally understood as a liver-derived and blood or interstitial fluid operative system protecting against bloodborne pathogens or threats, recent research, particularly on the role of complement in the healthy and diseased CNS, has demonstrated the importance of locally produced and activated complement components. Here, we provide a succinct overview over the known beneficial and pathological roles of complement in the CNS with focus on local sources of complement, including a discussion on the potential importance of the recently discovered intracellularly active complement system for CNS biology and on infection-triggered neurodegeneration.

Comprehensive blood metabolomics profiling of Parkinson's disease reveals coordinated alterations in xanthine metabolism

Parkinson's disease (PD) is a highly heterogeneous disorder influenced by several environmental and genetic factors. Effective disease-modifying therapies and robust early-stage biomarkers are still lacking, and an improved understanding of the molecular changes in PD could help to reveal new diagnostic markers and pharmaceutical targets. Here, we report results from a cohort-wide blood plasma metabolic profiling of PD patients and controls in the Luxembourg Parkinson's Study to detect disease-associated alterations at the level of systemic cellular process and network alterations. We identified statistically significant changes in both individual metabolite levels and global pathway activities in PD vs. controls and significant correlations with motor impairment scores. As a primary observation when investigating shared molecular sub-network alterations, we detect pronounced and coordinated increased metabolite abundances in xanthine metabolism in de novo patients, which are consistent with previous PD case/control transcriptomics data from an independent cohort in terms of known enzyme-metabolite network relationships. From the integrated metabolomics and transcriptomics network analysis, the enzyme hypoxanthine phosphoribosyltransferase 1 (HPRT1) is determined as a potential key regulator controlling the shared changes in xanthine metabolism and linking them to a mechanism that may contribute to pathological loss of cellular adenosine triphosphate (ATP) in PD. Overall, the investigations revealed significant PD-associated metabolome alterations, including pronounced changes in xanthine metabolism that are mechanistically congruent with alterations observed in independent transcriptomics data. The enzyme HPRT1 may merit further investigation as a main regulator of these network alterations and as a potential therapeutic target to address downstream molecular pathology in PD.

Research progress in the molecular mechanism of ferroptosis in Parkinson's disease and regulation by natural plant products

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder of the central nervous system after Alzheimer's disease. The current understanding of PD focuses mainly on the loss of dopamine neurons in the substantia nigra region of the midbrain, which is attributed to factors such as oxidative stress, alpha-synuclein aggregation, neuroinflammation, and mitochondrial dysfunction. These factors together contribute to the PD phenotype. Recent studies on PD pathology have introduced a new form of cell death known as ferroptosis. Pathological changes closely linked with ferroptosis have been seen in the brain tissues of PD patients, including alterations in iron metabolism, lipid peroxidation, and increased levels of reactive oxygen species. Preclinical research has demonstrated the neuroprotective qualities of certain iron chelators, antioxidants, Fer-1, and conditioners in Parkinson's disease. Natural plant products have shown significant potential in balancing ferroptosis-related factors and adjusting their expression levels. Therefore, it is vital to understand the mechanisms by which natural plant products inhibit ferroptosis and relieve PD symptoms. This review provides a comprehensive look at ferroptosis, its role in PD pathology, and the mechanisms underlying the therapeutic effects of natural plant products focused on ferroptosis. The insights from this review can serve as useful references for future research on novel ferroptosis inhibitors and lead compounds for PD treatment.

Identification of PLOD3 and LRRN3 as potential biomarkers for Parkinson's disease based on integrative analysis

Parkinson's disease (PD) is one of the most prevalent movement disorders and its diagnosis relies heavily on the typical clinical manifestations in the late stages. This study aims to screen and identify biomarkers of PD for earlier intervention. We performed a differential analysis of postmortem brain transcriptome studies. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify biomarkers related to Braak stage. We found 58 genes with significantly different expression in both PD brain tissue and blood samples. PD gene signature and risk score model consisting of nine genes were constructed using least absolute shrinkage and selection operator regression (LASSO) and logistic regression. PLOD3 and LRRN3 in gene signature were identified to serve as key genes as well as potential risk factors in PD. Gene function enrichment analysis and evaluation of immune cell infiltration revealed that PLOD3 was implicated in suppression of cellular metabolic function and inflammatory cell infiltration, whereas LRRN3 exhibited an inverse trend. The cellular subpopulation expression of the PLOD3 and LRRN3 has significant distributional variability. The expression of PLOD3 was more enriched in inflammatory cell subpopulations, such as microglia, whereas LRRN3 was more enriched in neurons and oligodendrocyte progenitor cells clusters (OPC). Additionally, the expression of PLOD3 and LRRN3 in Qilu cohort was verified to be consistent with previous results. Collectively, we screened and identified the functions of PLOD3 and LRRN3 based the integrated study. The combined detection of PLOD3 and LRRN3 expression in blood samples can improve the early detection of PD.

Complement system changes in blood in Parkinson's disease and progressive Supranuclear Palsy/Corticobasal Syndrome

Parkinson's Disease (PD) is diagnosed clinically, and early PD is often challenging to differentiate from atypical parkinsonian disorders such as the Four-repeat (4R-) Tauopathies Progressive Supranuclear Palsy and Corticobasal Syndrome. Diagnostic biomarkers are needed, and proteomic studies have suggested that the plasma complement system is altered in PD, but validation studies are lacking. In this study, plasma from 148 individuals (PD, 4R-Tauopathies, and healthy controls (HC)) were used to quantify 12 complement proteins with immunoassays, and CH50 classical pathway complement activity was quantified in sera from further 78 individuals (PD and HC). Complement factors C1q and C3 in plasma were lower in individuals with 4R-Tauopathies (ANOVA, p = 0.0041, p = 0.0057 respectively) compared to both PD and HC. None of the complement proteins were altered between PD and HC, however a few proteins correlated with clinical parameters within the PD group. Notably, levels of C3 correlated with non-motor symptoms in female patients. Classical pathway complement activity was not altered in PD serum, but did correlate with mental fatigue. In conclusion, individuals with 4R-Tauopathies showed lower plasma C1q and C3 compared PD and HC. Neither complement levels nor CH50 activity were significantly altered in PD versus HC but may associate with PD symptom severity.

Biomarkers in Neurodegenerative Diseases: Proteomics Spotlight on ALS and Parkinson’s Disease

Neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD) are both characterized by pathogenic protein aggregates that correlate with the progressive degeneration of neurons and the loss of behavioral functions. Both diseases lack biomarkers for diagnosis and treatment efficacy. Proteomics is an unbiased quantitative tool capable of the high throughput quantitation of thousands of proteins from minimal sample volumes. We review recent proteomic studies in human tissues, plasma, cerebrospinal fluid (CSF), and exosomes in ALS and PD that identify proteins with potential utility as biomarkers. Further, we review disease-related post-translational modifications in key proteins TDP43 in ALS and α-synuclein in PD studies, which may serve as biomarkers. We compare relative and absolute quantitative proteomic approaches in key biomarker studies in ALS and PD and discuss recent technological advancements which may identify suitable biomarkers for the early-diagnosis treatment efficacy of these diseases.

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

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