Exploring the Effects of Genetic Variants on Clinical Profiles of Parkinson's Disease Assessed by the Unified Parkinson's Disease Rating Scale and the Hoehn-Yahr Stage

The Molecular Impact of Glucosylceramidase Beta 1 (Gba1) in Parkinson's Disease: a New Genetic State of the Art

Parkinson's disease (PD) is a neurodegenerative disorder affecting 2-3% of those aged over 65, characterized by motor symptoms like slow movement, tremors, and muscle rigidity, along with non-motor symptoms such as anxiety and dementia. Lewy bodies, clumps of misfolded proteins, contribute to neuron loss in PD. Mutations in the GBA1 gene are considered the primary genetic risk factor of PD. GBA1 mutations result in decreased activity of the lysosomal enzyme glucocerebrosidase (GCase) resulting in α-synuclein accumulation. We know that α-synuclein aggregation, lysosomal dysfunction, and endoplasmic reticulum disturbance are recognized factors to PD susceptibility; however, the molecular mechanisms connecting GBA1 gene mutations to increased PD risk remain partly unknown. Thus, in this narrative review conducted according to a systematic review method, we aimed to present the main contributions arising from the molecular impact of the GBA1 gene to the pathogenesis of PD providing new insights into potential impacts for advances in the clinical care of people with PD, a neurological disorder that has contributed to the substantial increase in the global burden of disease accentuated by the aging population. In summary, this narrative review highlights the multifaceted impact of GBA1 mutations in PD, exploring their role in clinical manifestations, genetic predispositions, and molecular mechanisms. The review emphasizes the importance of GBA1 mutations in both motor and non-motor symptoms of PD, suggesting broader therapeutic and management strategies. It also discusses the potential of CRISPR/Cas9 technology in advancing PD treatment and the need for future research to integrate these diverse aspects for improved diagnostics and therapies.

Genetic polymorphisms of bone marrow stromal cell antigen-1 (BST-1/CD157): implications for immune/inflammatory dysfunction in neuropsychiatric disorders

Bone marrow stromal cell antigen-1 (BST-1/CD157) is an immune/inflammatory regulator that functions as both nicotinamide adenine dinucleotide-metabolizing ectoenzyme and cell-surface signaling receptor. BST-1/CD157 is expressed not only in peripheral tissues, but in the central nervous system (CNS). Although its pathophysiological significance in the CNS is still unclear, clinical genetic studies over a decade have begun revealing relationships between BST-1/CD157 and neuropsychiatric diseases including Parkinson's disease, autism spectrum disorders, sleep disorders, depressive disorders and restless leg syndrome. This review summarizes the accumulating evidence for the involvement of BST-1/CD157 in these disorders.

A systematic review of associations between common SNCA variants and clinical heterogeneity in Parkinson's disease

There is great heterogeneity in both the clinical presentation and rate of disease progression among patients with Parkinson’s disease (PD). This can pose prognostic difficulties in a clinical setting, and a greater understanding of the risk factors that contribute to modify disease course is of clear importance for optimizing patient care and clinical trial design. Genetic variants in SNCA are an established risk factor for PD and are candidates to modify disease presentation and progression. This systematic review aimed to summarize all available primary research reporting the association of SNCA polymorphisms with features of PD. We systematically searched PubMed and Web of Science, from inception to 1 June 2020, for studies evaluating the association of common SNCA variants with age at onset (AAO) or any clinical feature attributed to PD in patients with idiopathic PD. Fifty-eight studies were included in the review that investigated the association between SNCA polymorphisms and a broad range of outcomes, including motor and cognitive impairment, sleep disorders, mental health, hyposmia, or AAO. The most reproducible findings were with the REP1 polymorphism or rs356219 and an earlier AAO, but no clear associations were identified with an SNCA polymorphism and any individual clinical outcome. The results of this comprehensive summary suggest that, while there is evidence that genetic variance in the SNCA region may have a small impact on clinical outcomes in PD, the mechanisms underlying the association of SNCA polymorphisms with PD risk may not be a major factor driving clinical heterogeneity in PD.

Predicting the progression of Parkinson's disease using conventional MRI and machine learning: An application of radiomic biomarkers in whole-brain white matter

PURPOSE

This study aimed to develop and validate a radiomics model based on whole-brain white matter and clinical features to predict the progression of Parkinson disease (PD).

METHODS

PD patient data from the Parkinson's Progress Markers Initiative (PPMI) database was evaluated. Seventy-two PD patients with disease progression, as measured by the Hoehn-Yahr Scale (HYS) (stage 1-5), and 72 PD patients with stable PD were matched by sex, age, and category of HYS and included in the current study. Each individual's T₁ -weighted MRI scans at the baseline timepoint were segmented to isolate whole-brain white matter for radiomics feature extraction. The total dataset was divided into a training and test set according to subject serial number. The size of the training dataset was reduced using the maximum relevance minimum redundancy (mRMR) algorithm to construct a radiomics signature using machine learning. Finally, a joint model was constructed by incorporating the radiomics signature and clinical progression scores. The test data were then used to validate the prediction models, which were evaluated based on discrimination, calibration, and clinical utility.

RESULTS

Based on the overall data, the areas under curve (AUCs) of the joint model, signature and Unified Parkinson Disease Rating Scale III PD rating score were 0.836, 0.795, and 0.550, respectively. Furthermore, the sensitivities were 0.805, 0.875, and 0.292, respectively, and the specificities were 0.722, 0.697, and 0.861, respectively. In addition, the predictive accuracy of the model was 0.827, the sensitivity was 0.829 and the specificity was 0.702 for stage-1 PD. For stage-2 PD, the predictive accuracy of the model was 0.854, the sensitivity was 0.960, and the specificity was 0.600.

CONCLUSION

Our results provide evidence that conventional structural MRI can predict the progression of PD. This work also supports the use of a simple radiomics signature built from whole-brain white matter features as a useful tool for the assessment and monitoring of PD progression.

Application of Precision Medicine in Neurodegenerative Diseases

One of the main challenges for healthcare systems is the increasing prevalence of neurodegenerative pathologies together with the rapidly aging populations. The enormous progresses made in the field of biomedical research and informatics have been crucial for improving the knowledge of how genes, epigenetic modifications, aging, nutrition, drugs and microbiome impact health and disease. In fact, the availability of high technology and computational facilities for large-scale analysis enabled a deeper investigation of neurodegenerative disorders, providing a more comprehensive overview of disease and encouraging the development of a precision medicine approach for these pathologies. On this subject, the creation of collaborative networks among medical centers, research institutes and highly qualified specialists can be decisive for moving the precision medicine from the bench to the bedside. To this purpose, the present review has been thought to discuss the main components which may be part of precise and personalized treatment programs applied to neurodegenerative disorders. Parkinson Disease will be taken as an example to understand how precision medicine approach can be clinically useful and provide substantial benefit to patients. In this perspective, the realization of web-based networks can be decisive for the implementation of precision medicine strategies across different specialized centers as well as for supporting clinical/therapeutical decisions and promoting a more preventive and participative medicine for neurodegenerative disorders. These collaborative networks are essentially addressed to find innovative, sustainable and effective strategies able to provide optimal and safer therapies, discriminate at risk individuals, identify patients at preclinical or early stage of disease, set-up individualized and preventative strategies for improving prognosis and patient's quality of life.

Association of polymorphisms and reduced expression levels of the NR4A2 gene with Parkinson's disease in a Mexican population

INTRODUCTION

The NR4A2 transcription factor is important in the development, survival and phenotype of dopaminergic neurons and it is postulated as a possible biomarker for Parkinson's disease (PD). Therefore, our aim was to analyze in a sample of a Mexican population with idiopathic PD, mutations (in two hotspot mutation regions) and two polymorphisms (rs34884856 in promotor and rs35479735 intronic regions) of the NR4A2 gene. We also evaluate the levels of NR4A2 gene expression in peripheral blood for a Mexican population, and identify whether they are associated with NR4A2 gene polymorphisms.

METHODS

We conducted a case-control study, which included 227 idiopathic PD cases and 454 unrelated controls. Genetic variants of the NR4A2 gene were genotyped by high-resolution melting (HRM) and validated by an automated sequencing method. The gene expression was performed in peripheral blood using a real-time polymerase chain reaction.

RESULTS

The rs35479735 polymorphism was associated with a higher risk of developing PD. In addition, NR4A2 gene expression was significantly decreased in patients with PD. Linkage disequilibrium analysis showed a haplotype H4 (3C-3G) that showed lower levels of expression, and contained the risk alleles for both polymorphisms.

CONCLUSIONS

In summary, this is the first study in a Mexican population that considers the analysis of NR4A2 in patients with PD. An association was identified between genotype and mRNA expression levels of NR4A2 in patients with PD. These results suggest that polymorphisms and expression of the NR4A2 gene could play an important role in the risk of developing PD in Mexican populations.