Genetic Determinants of Parkinson's Disease: Can They Help to Stratify the Patients Based on the Underlying Molecular Defect?

Overlap in synaptic neurological condition susceptibility pathways and the neural pannexin 1 interactome revealed by bioinformatics analyses

Many neurological conditions exhibit synaptic impairments, suggesting mechanistic convergence. Additionally, the pannexin 1 (PANX1) channel and signaling scaffold is linked to several of these neurological conditions and is an emerging regulator of synaptic development and plasticity; however, its synaptic pathogenic contributions are relatively unexplored. To this end, we explored connections between synaptic neurodevelopmental disorder and neurodegenerative disease susceptibility genes discovered by genome-wide association studies (GWASs), and the neural PANX1 interactome (483 proteins) identified from mouse Neuro2a (N2a) cells. To identify shared susceptibility genes, we compared synaptic suggestive GWAS candidate genes amongst autism spectrum disorders, schizophrenia, Parkinson's disease, and Alzheimer's disease. To further probe PANX1 signaling pathways at the synapse, we used bioinformatics tools to identify PANX1 interactome signaling pathways and protein-protein interaction clusters. To shed light on synaptic disease mechanisms potentially linking PANX1 and these four neurological conditions, we performed additional cross-analyses between gene ontologies enriched for the PANX1 synaptic and disease-susceptibility gene sets. Finally, to explore the regional specificity of synaptic PANX1-neurological condition connections, we identified brain region-specific elevations of synaptic PANX1 interactome and GWAS candidate gene set transcripts. Our results confirm considerable overlap in risk genes for autism spectrum disorders and schizophrenia and identify potential commonalities in genetic susceptibility for neurodevelopmental disorders and neurodegenerative diseases. Our findings also pinpointed novel putative PANX1 links to synaptic disease-associated pathways, such as regulation of vesicular trafficking and proteostasis, warranting further validation.

Gene Signals and SNPs Associated with Parkinson's Disease: A Nutrigenomics and Computational Prospective Insights

Parkinson's disease is the most prevalent chronic neurodegenerative disease. Neurological conditions for PD were influenced by a variety of epigenetic factors and SNPs in some of the coexisting genes that were expressed. This article focused on nutrigenomics of PD and the prospective highlighting of how these genes are regulated in terms of nutritive factors and the genetic basis of PD risk, onset, and progression. Multigenetic associations of the following genetic alterations in the genes of SNCA, LRRK2, UCHL1, PARK2,PINK1, DJ-1, and ATP13A2 have been reported with the familial and de novo genetic origins of PD. Over the past two decades, significant attempts have been made to understand the biological mechanisms that are potential causes for this disease, as well as to identify therapeutic substances for the prevention and management of PD. Nutrigenomics has sparked considerable interest due to its nutritional, safe, and therapeutic effects on a variety of chronic diseases. In this study, we summarise some of the nutritive supplements that have an impact on PD.

A genome-wide association study coupled with machine learning approaches to identify influential demographic and genomic factors underlying Parkinson's disease

Background: Despite the recent success of genome-wide association studies (GWAS) in identifying 90 independent risk loci for Parkinson's disease (PD), the genomic underpinning of PD is still largely unknown. At the same time, accurate and reliable predictive models utilizing genomic or demographic features are desired in the clinic for predicting the risk of Parkinson's disease. Methods: To identify influential demographic and genomic factors associated with PD and to further develop predictive models, we utilized demographic data, incorporating 200 variables across 33,473 participants, along with genomic data involving 447,089 SNPs across 8,840 samples, both derived from the Fox Insight online study. We first applied correlation and GWAS analyses to find the top demographic and genomic factors associated with PD, respectively. We further developed and compared a variety of machine learning (ML) models for predicting PD. From the developed ML models, we performed feature importance analysis to reveal the predictability of each demographic or the genomic input feature for PD. Finally, we performed gene set enrichment analysis on our GWAS results to identify PD-associated pathways. Results: In our study, we identified both novel and well-known demographic and genetic factors (along with the enriched pathways) related to PD. In addition, we developed predictive models that performed robustly, with AUC = 0.89 for demographic data and AUC = 0.74 for genomic data. Our GWAS analysis identified several novel and significant variants and gene loci, including three intron variants in LMNA (p-values smaller than 4.0e-21) and one missense variant in SEMA4A (p-value = 1.11e-26). Our feature importance analysis from the PD-predictive ML models highlighted some significant and novel variants from our GWAS analysis (e.g., the intron variant rs1749409 in the RIT1 gene) and helped identify potentially causative variants that were missed by GWAS, such as rs11264300, a missense variant in the gene DCST1, and rs11584630, an intron variant in the gene KCNN3. Conclusion: In summary, by combining a GWAS with advanced machine learning models, we identified both known and novel demographic and genomic factors as well as built well-performing ML models for predicting Parkinson's disease.

Applications of multi-omics analysis in human diseases

Multi-omics usually refers to the crossover application of multiple high-throughput screening technologies represented by genomics, transcriptomics, single-cell transcriptomics, proteomics and metabolomics, spatial transcriptomics, and so on, which play a great role in promoting the study of human diseases. Most of the current reviews focus on describing the development of multi-omics technologies, data integration, and application to a particular disease; however, few of them provide a comprehensive and systematic introduction of multi-omics. This review outlines the existing technical categories of multi-omics, cautions for experimental design, focuses on the integrated analysis methods of multi-omics, especially the approach of machine learning and deep learning in multi-omics data integration and the corresponding tools, and the application of multi-omics in medical researches (e.g., cancer, neurodegenerative diseases, aging, and drug target discovery) as well as the corresponding open-source analysis tools and databases, and finally, discusses the challenges and future directions of multi-omics integration and application in precision medicine. With the development of high-throughput technologies and data integration algorithms, as important directions of multi-omics for future disease research, single-cell multi-omics and spatial multi-omics also provided a detailed introduction. This review will provide important guidance for researchers, especially who are just entering into multi-omics medical research.

Shared molecular genetic factors influence subcortical brain morphometry and Parkinson's disease risk

Parkinson's disease (PD) is a late-onset and genetically complex neurodegenerative disorder. Here we sought to identify genes and molecular pathways underlying the associations between PD and the volume of ten brain structures measured through magnetic resonance imaging (MRI) scans. We leveraged genome-wide genetic data from several cohorts, including the International Parkinson's Disease Genomics Consortium (IPDG), the UK Biobank, the Adolescent Brain Cognitive Development (ABCD) study, the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE), the Enhancing Neuroimaging Genetics through Meta-Analyses (ENIGMA), and 23andMe. We observed significant positive genetic correlations between PD and intracranial and subcortical brain volumes. Genome-wide association studies (GWAS) - pairwise analyses identified 210 genomic segments with shared aetiology between PD and at least one of these brain structures. Pathway enrichment results highlight potential links with chronic inflammation, the hypothalamic-pituitary-adrenal pathway, mitophagy, disrupted vesicle-trafficking, calcium-dependent, and autophagic pathways. Investigations for putative causal genetic effects suggest that a larger putamen volume could influence PD risk, independently of the potential causal genetic effects of intracranial volume (ICV) on PD. Our findings suggest that genetic variants influencing larger intracranial and subcortical brain volumes, possibly during earlier stages of life, influence the risk of developing PD later in life.

Deciphering the molecular mechanism and crosstalk between Parkinson's disease and breast cancer through multi-omics and drug repurposing approach

Epidemiological studies indicate a higher occurrence of breast cancer (BRCA) in patients with Parkinson's disease. However, the exact molecular mechanism is still not precise. Herein, we tested the hypothesis that this inverse comorbidity result from shared genetic and molecular processes. We conducted an integrated omics analysis to identify the common gene signatures associated with PD and BRCA. Secondly, several dysregulated biological processes in both indications were analyzed by functional enrichment methods, and significant overlapping processes were identified. To establish common regulatory mechanisms, information about transcription factors and miRNAs associated with both the disorders was extracted. Finally, disease-specific gene expression signatures were compared through LINCS L1000 analysis to identify potential repurposing drugs for PD. The potential repurposed drug candidates were then correlated with PD-specific gene signatures by Cmap analysis. In conclusion, this study highlights the shared genes, biological pathways and regulatory signatures associated with PD and BRCA with an improved understanding of crosstalk involved. Additionally, the role of therapeutics was investigated in context with their comorbid associations. These findings could help to explain the complex molecular patterns of associations between PD and BRCA.

Genome-Wide Polygenic Score Predicts Large Number of High Risk Individuals in Monogenic Undiagnosed Young Onset Parkinson's Disease Patients from India

Parkinson's disease (PD) is a genetically heterogeneous neurodegenerative disease with poorly defined environmental influences. Genomic studies of PD patients have identified disease-relevant monogenic genes, rare variants of significance, and polygenic risk-associated variants. In this study, whole genome sequencing data from 90 young onset Parkinson's disease (YOPD) individuals are analyzed for both monogenic and polygenic risk. The genetic variant analysis identifies pathogenic/likely pathogenic variants in eight of the 90 individuals (8.8%). It includes large homozygous coding exon deletions in PRKN and SNV/InDels in VPS13C, PLA2G6, PINK1, SYNJ1, and GCH1. Eleven rare heterozygous GBA coding variants are also identified in 13 (14.4%) individuals. In 34 (56.6%) individuals, one or more variants of uncertain significance (VUS) in PD/PD-relevant genes are observed. Though YOPD patients with a prioritized pathogenic variant show a low polygenic risk score (PRS), patients with prioritized VUS or no significant rare variants show an increased PRS odds ratio for PD. This study suggests that both significant rare variants and polygenic risk from common variants together may contribute to the genesis of PD. Further validation using a larger cohort of patients will confirm the interplay between monogenic and polygenic variants and their use in routine genetic PD diagnosis and risk assessment.

Distinct sex-specific DNA methylation differences in Alzheimer's disease

BACKGROUND

Sex is increasingly recognized as a significant factor contributing to the biological and clinical heterogeneity in AD. There is also growing evidence for the prominent role of DNA methylation (DNAm) in Alzheimer's disease (AD).

METHODS

We studied sex-specific DNA methylation differences in the blood samples of AD subjects compared to cognitively normal subjects, by performing sex-specific meta-analyses of two large blood-based epigenome-wide association studies (ADNI and AIBL), which included DNA methylation data for a total of 1284 whole blood samples (632 females and 652 males). Within each dataset, we used two complementary analytical strategies, a sex-stratified analysis that examined methylation to AD associations in male and female samples separately, and a methylation-by-sex interaction analysis that compared the magnitude of these associations between different sexes. After adjusting for age, estimated immune cell type proportions, batch effects, and correcting for inflation, the inverse-variance fixed-effects meta-analysis model was used to identify the most consistent DNAm differences across datasets. In addition, we also evaluated the performance of the sex-specific methylation-based risk prediction models for AD diagnosis using an independent external dataset.

RESULTS

In the sex-stratified analysis, we identified 2 CpGs, mapped to the PRRC2A and RPS8 genes, significantly associated with AD in females at a 5% false discovery rate, and an additional 25 significant CpGs (21 in females, 4 in males) at P-value < 1×10^-5. In methylation-by-sex interaction analysis, we identified 5 significant CpGs at P-value < 10^-5. Out-of-sample validations using the AddNeuroMed dataset showed in females, the best logistic prediction model included age, estimated immune cell-type proportions, and methylation risk scores (MRS) computed from 9 of the 23 CpGs identified in AD vs. CN analysis that are also available in AddNeuroMed dataset (AUC = 0.74, 95% CI: 0.65-0.83). In males, the best logistic prediction model included only age and MRS computed from 2 of the 5 CpGs identified in methylation-by-sex interaction analysis that are also available in the AddNeuroMed dataset (AUC = 0.70, 95% CI: 0.56-0.82).

CONCLUSIONS

Overall, our results show that the DNA methylation differences in AD are largely distinct between males and females. Our best-performing sex-specific methylation-based prediction model in females performed better than that for males and additionally included estimated cell-type proportions. The significant discriminatory classification of AD samples with our methylation-based prediction models demonstrates that sex-specific DNA methylation could be a predictive biomarker for AD. As sex is a strong factor underlying phenotypic variability in AD, the results of our study are particularly relevant for a better understanding of the epigenetic architecture that underlie AD and for promoting precision medicine in AD.

Predicting Parkinson disease related genes based on PyFeat and gradient boosted decision tree

Identifying genes related to Parkinson’s disease (PD) is an active research topic in biomedical analysis, which plays a critical role in diagnosis and treatment. Recently, many studies have proposed different techniques for predicting disease-related genes. However, a few of these techniques are designed or developed for PD gene prediction. Most of these PD techniques are developed to identify only protein genes and discard long noncoding (lncRNA) genes, which play an essential role in biological processes and the transformation and development of diseases. This paper proposes a novel prediction system to identify protein and lncRNA genes related to PD that can aid in an early diagnosis. First, we preprocessed the genes into DNA FASTA sequences from the University of California Santa Cruz (UCSC) genome browser and removed the redundancies. Second, we extracted some significant features of DNA FASTA sequences using the PyFeat method with the AdaBoost as feature selection. These selected features achieved promising results compared with extracted features from some state-of-the-art feature extraction techniques. Finally, the features were fed to the gradient-boosted decision tree (GBDT) to diagnose different tested cases. Seven performance metrics were used to evaluate the performance of the proposed system. The proposed system achieved an average accuracy of 78.6%, the area under the curve equals 84.5%, the area under precision-recall (AUPR) equals 85.3%, F1-score equals 78.3%, Matthews correlation coefficient (MCC) equals 0.575, sensitivity (SEN) equals 77.1%, and specificity (SPC) equals 80.2%. The experiments demonstrate promising results compared with other systems. The predicted top-rank protein and lncRNA genes are verified based on a literature review.

Genomics and Functional Genomics of Alzheimer's Disease

Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disease. Due to its long clinical course and lack of an effective treatment, AD has become a major public health problem in the USA and worldwide. Due to variation in age-at-onset, AD is classified into early-onset (< 60 years) and late-onset (≥ 60 years) forms with early-onset accounting for only 5-10% of all cases. With the exception of a small number of early-onset cases that are afflicted because of high penetrant single gene mutations in APP, PSEN1, and PSEN2 genes, AD is genetically heterogeneous, especially the late-onset form having a polygenic or oligogenic risk inheritance. Since the identification of APOE as the most significant risk factor for late-onset AD in 1993, the path to the discovery of additional AD risk genes had been arduous until 2009 when the use of large genome-wide association studies opened up the discovery gateways that led the identification of ~ 95 additional risk loci from 2009 to early 2022. This article reviews the history of AD genetics followed by the potential molecular pathways and recent application of functional genomics methods to identify the causal AD gene(s) among the many genes that reside within a single locus. The ultimate goal of integrating genomics and functional genomics is to discover novel pathways underlying the AD pathobiology in order to identify drug targets for the therapeutic treatment of this heterogeneous disorder.

Combining Automated Organoid Workflows With Artificial Intelligence-Based Analyses: Opportunities to Build a New Generation of Interdisciplinary High-Throughput Screens for Parkinson's Disease and Beyond

Parkinson's disease (PD) is the second most common neurodegenerative disease and primarily characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta of the midbrain. Despite decades of research and the development of various disease model systems, there is no curative treatment. This could be due to current model systems, including cell culture and animal models, not adequately recapitulating human PD etiology. More complex human disease models, including human midbrain organoids, are maturing technologies that increasingly enable the strategic incorporation of the missing components needed to model PD in vitro. The resulting organoid-based biological complexity provides new opportunities and challenges in data analysis of rich multimodal data sets. Emerging artificial intelligence (AI) capabilities can take advantage of large, broad data sets and even correlate results across disciplines. Current organoid technologies no longer lack the prerequisites for large-scale high-throughput screening (HTS) and can generate complex yet reproducible data suitable for AI-based data mining. We have recently developed a fully scalable and HTS-compatible workflow for the generation, maintenance, and analysis of three-dimensional (3D) microtissues mimicking key characteristics of the human midbrain (called "automated midbrain organoids," AMOs). AMOs build a reproducible, scalable foundation for creating next-generation 3D models of human neural disease that can fuel mechanism-agnostic phenotypic drug discovery in human in vitro PD models and beyond. Here, we explore the opportunities and challenges resulting from the convergence of organoid HTS and AI-driven data analytics and outline potential future avenues toward the discovery of novel mechanisms and drugs in PD research. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

No effect of Parkinson's disease-polygenic load on striatal density of dopaminergic neuron in healthy subjects

OBJECTIVE

There has been increasing evidence to support the role of genetic factors in Parkinson's disease (PD). ¹²³I-FP-CIT single-photon emission computed tomography (SPECT) enables in vivo visualization of the striatal density of dopaminergic neuron.

METHODS

We investigated the association between PD-associated polygenic load and striatal density of dopaminergic neuron in healthy subjects. Data used in the preparation of this article were obtained from Parkinson's Progression Markers Initiative database. ¹²³I-FP-CIT SPECT was performed for all subjects. Specific binding ratios (SBRs) were calculated from the ventral striatum, caudate nucleus, and putamen with reference to cerebellum. Singe nucleotide polymorphism (SNP) genotyping from the PPMI database was adopted in calculating genetic risk score (GRS). GRS was defined as the sum of the number of risk alleles weighted by log odds ratios for PD. We calculated three GRSs using three different sets of SNPs.

RESULT

A total of 151 subjects were included in this study (101 males, 50 females). GRS1, GRS2 and GRS3 were significantly different with the highest scores of GRS1. Multiple regression was done to investigate whether striatal SBRs are influenced by GRSs after adjusting for age and sex. However, none of GRSs were associated with SBRs of the ventral striatum, caudate nucleus and putamen.

CONCLUSION

PD risk SNPs weighted by odds ratio for PD were not associated with SBRs measured from SPECT in healthy subjects. Therefore, there is no effect of PD-associated polygenic load on striatal density of dopaminergic neuron in healthy subjects.

Genotype-driven therapeutic developments in Parkinson's disease

BACKGROUND

Remarkable advances have been reached in the understanding of the genetic basis of Parkinson's disease (PD), with the identification of monogenic causes (mPD) and a plethora of gene loci leading to an increased risk for idiopathic PD. The expanding knowledge and subsequent identification of genetic contributions fosters the understanding of molecular mechanisms leading to disease development and progression. Distinct pathways involved in mitochondrial dysfunction, oxidative stress, and lysosomal function have been identified and open a unique window of opportunity for individualized treatment approaches. These genetic findings have led to an imminent progress towards pathophysiology-targeted clinical trials and potentially disease-modifying treatments in the future.

MAIN BODY OF THE MANUSCRIPT

In this review article we will summarize known genetic contributors to the pathophysiology of Parkinson's disease, the molecular mechanisms leading to disease development, and discuss challenges and opportunities in clinical trial designs.

CONCLUSIONS

The future success of clinical trials in PD is mainly dependent on reliable biomarker development and extensive genetic testing to identify genetic cases. Whether genotype-dependent stratification of study participants will extend the potential application of new drugs will be one major challenge in conceptualizing clinical trials. However, the latest developments in genotype-driven treatments will pave the road to individualized pathophysiology-based therapies in the future.

Ethnic and trans-ethnic genome-wide association studies identify new loci influencing Japanese Alzheimer's disease risk

Alzheimer's disease (AD) has no cure, but early detection and risk prediction could allow earlier intervention. Genetic risk factors may differ between ethnic populations. To discover novel susceptibility loci of AD in the Japanese population, we conducted a genome-wide association study (GWAS) with 3962 AD cases and 4074 controls. Out of 4,852,957 genetic markers that passed stringent quality control filters, 134 in nine loci, including APOE and SORL1, were convincingly associated with AD. Lead SNPs located in seven novel loci were genotyped in an independent Japanese AD case-control cohort. The novel locus FAM47E reached genome-wide significance in a meta-analysis of association results. This is the first report associating the FAM47E locus with AD in the Japanese population. A trans-ethnic meta-analysis combining the results of the Japanese data sets with summary statistics from stage 1 data of the International Genomics of Alzheimer's Project identified an additional novel susceptibility locus in OR2B2. Our data highlight the importance of performing GWAS in non-European populations.

Differences in MTHFR and LRRK2 variant's association with sporadic Parkinson's disease in Mexican Mestizos correlated to Native American ancestry

Parkinson's disease (PD), a common neurodegenerative disorder, has a complex etiology where environmental and genetic factors intervene. While a number of genes and variants have been identified in recent decades as causative or protective agents of this condition, a limited number of studies have been conducted in mixed populations, such as Mexican Mestizos. The historical convergence of two founding groups and three ethnicities, and the increasing north-to-south gradient of Native American ancestry in Mexico resulted in a subpopulation structure with considerable genetic diversity. In this work, we investigate the influence of 21 known susceptibility variants for PD. Our case-control study, with a cohort of 311 Mexican Mestizo subjects, found a significant risk association for the variant rs1491942 in LRRK2. However, when stratification by ancestry was performed, a risk effect for MTHFR rs1801133 was observed only in the group with the highest percentage of European ancestry, and the PD risk effect for LRRK2 rs1491942 was significant in subjects with a higher ratio of Native American ancestry. Meta-analyses of these SNP revealed the effect of LRRK2 rs1491942 to be even more significant than previously described in populations of European descent. Although corroboration is necessary, our findings suggest that polymorphism rs1491942 may be useful as a risk marker of PD in Mexican Mestizos with greater Native American ancestry. The absence of associations with the remaining known risk factors is, in itself, a relevant finding and invites further research into the shared risk factors' role in the pathophysiological mechanisms of this neurodegenerative disorder.

Parkinson's Disease: A Review from Pathophysiology to Treatment

Parkinson's Disease (PD) is the second most common neurodegenerative disease in the elderly population, with a higher prevalence in men, independent of race and social class; it affects approximately 1.5 to 2.0% of the elderly population over 60 years and 4% for those over 80 years of age. PD is caused by the necrosis of dopaminergic neurons in the substantia nigra, which is the brain region responsible for the synthesis of the neurotransmitter dopamine (DA), resulting in its decrease in the synaptic cleft. The monoamine oxidase B (MAO-B) degrades dopamine, promoting the glutamate accumulation and oxidative stress with the release of free radicals, causing excitotoxicity. The PD symptoms are progressive physical limitations such as rigidity, bradykinesia, tremor, postural instability and disability in functional performance. Considering that there are no laboratory tests, biomarkers or imaging studies to confirm the disease, the diagnosis of PD is made by analyzing the motor features. There is no cure for PD, and the pharmacological treatment consists of a dopaminergic supplement with levodopa, COMT inhibitors, anticholinergics agents, dopaminergic agonists, and inhibitors of MAO-B, which basically aims to control the symptoms, enabling better functional mobility and increasing life expectancy of the treated PD patients. Due to the importance and increasing prevalence of PD in the world, this study reviews information on the pathophysiology, symptomatology as well as the most current and relevant treatments of PD patients.

Targeting Mitochondrial Impairment in Parkinson's Disease: Challenges and Opportunities

The underlying pathophysiology of Parkinson's disease is complex, but mitochondrial dysfunction has an established and prominent role. This is supported by an already large and rapidly growing body of evidence showing that the role of mitochondrial (dys)function is central and multifaceted. However, there are clear gaps in knowledge, including the dilemma of explaining why inherited mitochondriopathies do not usually present with parkinsonian symptoms. Many aspects of mitochondrial function are potential therapeutic targets, including reactive oxygen species production, mitophagy, mitochondrial biogenesis, mitochondrial dynamics and trafficking, mitochondrial metal ion homeostasis, sirtuins, and endoplasmic reticulum links with mitochondria. Potential therapeutic strategies may also incorporate exercise, microRNAs, mitochondrial transplantation, stem cell therapies, and photobiomodulation. Despite multiple studies adopting numerous treatment strategies, clinical trials to date have generally failed to show benefit. To overcome this hurdle, more accurate biomarkers of mitochondrial dysfunction are required to detect subtle beneficial effects. Furthermore, selecting study participants early in the disease course, studying them for suitable durations, and stratifying them according to genetic and neuroimaging findings may increase the likelihood of successful clinical trials. Moreover, treatments involving combined approaches will likely better address the complexity of mitochondrial dysfunction in Parkinson's disease. Therefore, selecting the right patients, at the right time, and using targeted combination treatments, may offer the best chance for development of an effective novel therapy targeting mitochondrial dysfunction in Parkinson's disease.

When Friendship Turns Sour: Effective Communication Between Mitochondria and Intracellular Organelles in Parkinson's Disease

Parkinson's disease (PD) is a complex neurodegenerative disease with pathological hallmarks including progressive neuronal loss from the substantia nigra pars compacta and α-synuclein intraneuronal inclusions, known as Lewy bodies. Although the etiology of PD remains elusive, mitochondrial damage has been established to take center stage in the pathogenesis of PD. Mitochondria are critical to cellular energy production, metabolism, homeostasis, and stress responses; the association with PD emphasizes the importance of maintenance of mitochondrial network integrity. To accomplish the pleiotropic functions, mitochondria are dynamic not only within their own network but also in orchestrated coordination with other organelles in the cellular community. Through physical contact sites, signal transduction, and vesicle transport, mitochondria and intracellular organelles achieve the goals of calcium homeostasis, redox homeostasis, protein homeostasis, autophagy, and apoptosis. Herein, we review the finely tuned interactions between mitochondria and surrounding intracellular organelles, with focus on the nucleus, endoplasmic reticulum, Golgi apparatus, peroxisomes, and lysosomes. Participants that may contribute to the pathogenic mechanisms of PD will be highlighted in this review.

The beneficial effect of vanillin on 6-hydroxydopamine rat model of Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is a progressive neurodegenerative disorder that is related to neuroinflammation. Vanillin, which possesses both antioxidant, and anti-inflammatory properties, can be a candidate for neuroprotection in PD.

OBJECTIVE

This study was aimed to investigate the effects of vanillin on the 6-hydroxydopamine (6-OHDA) rodent model of PD.

METHODS

Male Wistar rats were administrated intraperitoneal (i.p) or oral vanillin at a dose of 20 mg/kg/day for 7 days that was started at three days before or seven days after intracerebral injection of 6-OHDA. The 6-OHDA-induced lesions were assessed behaviorally using the apomorphine rotation test, neurochemically via measuring striatal dopamine concentrations, and through immunohistochemistry.

RESULTS

Both oral and IP vanillin at three days before or seven days after 6-OHDA lesioning exhbited significantly lower tight contralateral rotations upon apomorphine challenge, and higher striatal dopamine concentrations.

CONCLUSIONS

Vanillin seems to offer protective properties against 6-OHDA lesion via preserving striatal dopamine levels.

The role of pharmacogenomics in the personalization of Parkinson's disease treatment

Parkinson's disease (PD)-related phenotypes can vary among patients substantially, including response to dopaminergic treatment in terms of efficacy and occurrence of adverse events. Many pharmacogenetic studies have already been conducted to find genetic markers of response to dopaminergic treatment. Integration of genetic and clinical data has already resulted in construction of clinical pharmacogenetic models for prediction of adverse events. However, the results of pharmacogenetic studies are inconsistent. More comprehensive genome-wide approaches are needed to find genetic biomarkers of PD-related phenotypes to better explain the variability in response to treatment. These genetic markers should be integrated with clinical, environmental, imaging, and other omics data to build clinically useful algorithms for personalization of PD management.

Biomaterials in Neurodegenerative Disorders: A Promising Therapeutic Approach

Neurodegenerative disorders (i.e., Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and spinal cord injury) represent a great problem worldwide and are becoming prevalent because of the increasing average age of the population. Despite many studies having focused on their etiopathology, the exact cause of these diseases is still unknown and until now, there are only symptomatic treatments. Biomaterials have become important not only for the study of disease pathogenesis, but also for their application in regenerative medicine. The great advantages provided by biomaterials are their ability to mimic the environment of the extracellular matrix and to allow the growth of different types of cells. Biomaterials can be used as supporting material for cell proliferation to be transplanted and as vectors to deliver many active molecules for the treatments of neurodegenerative disorders. In this review, we aim to report the potentiality of biomaterials (i.e., hydrogels, nanoparticles, self-assembling peptides, nanofibers and carbon-based nanomaterials) by analyzing their use in the regeneration of neural and glial cells their role in axon outgrowth. Although further studies are needed for their use in humans, the promising results obtained by several groups leads us to suppose that biomaterials represent a potential therapeutic approach for the treatments of neurodegenerative disorders.

A Network-Based Bioinformatics Approach to Identify Molecular Biomarkers for Type 2 Diabetes that Are Linked to the Progression of Neurological Diseases

Neurological diseases (NDs) are progressive disorders, the progression of which can be significantly affected by a range of common diseases that present as comorbidities. Clinical studies, including epidemiological and neuropathological analyses, indicate that patients with type 2 diabetes (T2D) have worse progression of NDs, suggesting pathogenic links between NDs and T2D. However, finding causal or predisposing factors that link T2D and NDs remains challenging. To address these problems, we developed a high-throughput network-based quantitative pipeline using agnostic approaches to identify genes expressed abnormally in both T2D and NDs, to identify some of the shared molecular pathways that may underpin T2D and ND interaction. We employed gene expression transcriptomic datasets from control and disease-affected individuals and identified differentially expressed genes (DEGs) in tissues of patients with T2D and ND when compared to unaffected control individuals. One hundred and ninety seven DEGs (99 up-regulated and 98 down-regulated in affected individuals) that were common to both the T2D and the ND datasets were identified. Functional annotation of these identified DEGs revealed the involvement of significant cell signaling associated molecular pathways. The overlapping DEGs (i.e., seen in both T2D and ND datasets) were then used to extract the most significant GO terms. We performed validation of these results with gold benchmark databases and literature searching, which identified which genes and pathways had been previously linked to NDs or T2D and which are novel. Hub proteins in the pathways were identified (including DNM2, DNM1, MYH14, PACSIN2, TFRC, PDE4D, ENTPD1, PLK4, CDC20B, and CDC14A) using protein-protein interaction analysis which have not previously been described as playing a role in these diseases. To reveal the transcriptional and post-transcriptional regulators of the DEGs we used transcription factor (TF) interactions analysis and DEG-microRNAs (miRNAs) interaction analysis, respectively. We thus identified the following TFs as important in driving expression of our T2D/ND common genes: FOXC1, GATA2, FOXL1, YY1, E2F1, NFIC, NFYA, USF2, HINFP, MEF2A, SRF, NFKB1, USF2, HINFP, MEF2A, SRF, NFKB1, PDE4D, CREB1, SP1, HOXA5, SREBF1, TFAP2A, STAT3, POU2F2, TP53, PPARG, and JUN. MicroRNAs that affect expression of these genes include mir-335-5p, mir-16-5p, mir-93-5p, mir-17-5p, mir-124-3p. Thus, our transcriptomic data analysis identifies novel potential links between NDs and T2D pathologies that may underlie comorbidity interactions, links that may include potential targets for therapeutic intervention. In sum, our neighborhood-based benchmarking and multilayer network topology methods identified novel putative biomarkers that indicate how type 2 diabetes (T2D) and these neurological diseases interact and pathways that, in the future, may be targeted for treatment.

The Overcrowded Crossroads: Mitochondria, Alpha-Synuclein, and the Endo-Lysosomal System Interaction in Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder worldwide, mainly affecting the elderly. The disease progresses gradually, with core motor presentations and a multitude of non-motor manifestations. There are two neuropathological hallmarks of PD, the dopaminergic neuronal loss and the alpha-synuclein-containing Lewy body inclusions in the substantia nigra. While the exact pathomechanisms of PD remain unclear, genetic investigations have revealed evidence of the involvement of mitochondrial function, alpha-synuclein (α-syn) aggregation, and the endo-lysosomal system, in disease pathogenesis. Due to the high energy demand of dopaminergic neurons, mitochondria are of special importance acting as the cellular powerhouse. Mitochondrial dynamic fusion and fission, and autophagy quality control keep the mitochondrial network in a healthy state. Should defects of the organelle occur, a variety of reactions would ensue at the cellular level, including disrupted mitochondrial respiratory network and perturbed calcium homeostasis, possibly resulting in cellular death. Meanwhile, α-syn is a presynaptic protein that helps regulate synaptic vesicle transportation and endocytosis. Its misfolding into oligomeric sheets and fibrillation is toxic to the mitochondria and neurons. Increased cellular oxidative stress leads to α-syn accumulation, causing mitochondrial dysfunction. The proteasome and endo-lysosomal systems function to regulate damage and unwanted waste management within the cell while facilitating the quality control of mitochondria and α-syn. This review will analyze the biological functions and interactions between mitochondria, α-syn, and the endo-lysosomal system in the pathogenesis of PD.

Case of Early-Onset Parkinson's Disease in a Heterozygous Mutation Carrier of the ATP7B Gene

In this paper, we report a clinically proven case of Parkinson’s disease (PD) with early onset in a patient who is a heterozygous mutation carrier of ATP7B (the Wilson’s disease gene). The patient was observed from 2011 to 2018 in the Center for Neurodegenerative Diseases, Institute of Experimental Medicine (St. Petersburg, Russia). During this period, the patient displayed aggravation of PD clinical symptoms that were accompanied by a decrease in the ceruloplasmin concentration (from 0.33 to 0.27 g/L) and an increase in serum nonceruloplasmin copper, which are typical of the late stages of Wilson’s disease. It was found that one of the alleles of exon 14 in the ATP7B gene, which partially codes of the nucleotide-binding domain (N-domain), carries a mutation not previously reported corresponding to Cys1079Gly substitution. Alignment of the ATP7B N-domain amino acid sequences of representative vertebrate species has shown that the Cys at 1079 position is conserved throughout the evolution. Molecular dynamic analysis of a polypeptide with Cys1079Gly substitution showed that the mutation causes profound conformational changes in the N-domain, which could potentially lead to impairment of its functions. The role of ATP7B gene mutations in PD development is discussed.

A replication study of GWAS-genetic risk variants associated with Parkinson's disease in a Spanish population

Recently, 5 previously Parkinson's disease (PD)-related loci: ACMSD/TMEM163, STK39, MIR4697, SREBF1/RAI1PD and MAPT, have been associated to PD in a Southern Spanish population. However, due to the small sample size of the cohort, this association did not reach genome wide significance. Our aim was to investigate the robustness of this association in a larger and independent cohort from the South of Spain. Variants were genotyped employing TaqMan SNP Genotyping Assay and high resolution melting analysis in 738 PD patients and 1138 healthy controls. Furthermore, a meta-analysis study was carried out with both cohorts. In the replication analysis, only two loci (ACMSD/TMEM163 and MAPT) were replicated with a Bonferroni significance level. In the meta-analysis study no loci reached a genome-wide significance level (P<5xE-8), but a suggestive association (P-value = 1.04E-6) between rs6430538 (ACMSD/TMEM163) and an increased risk of PD was found. In addition, rs9468 (MAPT) was associated with a decreased risk of PD (P-value = 5.70E-7). Our results add further support for the genetic involvement of these two loci in the susceptibility to PD in population from the South of Spain. We believe that our findings will be very useful for future genetic studies on PD.

The interplay of aging, genetics and environmental factors in the pathogenesis of Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is characterized by dopaminergic neuronal loss in the substantia nigra pars compacta and intracellular inclusions called Lewy bodies (LB). During the course of disease, misfolded α-synuclein, the major constituent of LB, spreads to different regions of the brain in a prion-like fashion, giving rise to successive non-motor and motor symptoms. Etiology is likely multifactorial, and involves interplay among aging, genetic susceptibility and environmental factors.

MAIN BODY

The prevalence of PD rises exponentially with age, and aging is associated with impairment of cellular pathways which increases susceptibility of dopaminergic neurons to cell death. However, the majority of those over the age of 80 do not have PD, thus other factors in addition to aging are needed to cause disease. Discovery of neurotoxins which can result in parkinsonism led to efforts in identifying environmental factors which may influence PD risk. Nevertheless, the causality of most environmental factors is not conclusively established, and alternative explanations such as reverse causality and recall bias cannot be excluded. The lack of geographic clusters and conjugal cases also go against environmental toxins as a major cause of PD. Rare mutations as well as common variants in genes such as SNCA, LRRK2 and GBA are associated with risk of PD, but Mendelian causes collectively only account for 5% of PD and common polymorphisms are associated with small increase in PD risk. Heritability of PD has been estimated to be around 30%. Thus, aging, genetics and environmental factors each alone is rarely sufficient to cause PD for most patients.

CONCLUSION

PD is a multifactorial disorder involving interplay of aging, genetics and environmental factors. This has implications on the development of appropriate animal models of PD which take all these factors into account. Common converging pathways likely include mitochondrial dysfunction, impaired autophagy, oxidative stress and neuroinflammation, which are associated with the accumulation and spread of misfolded α-synuclein and neurodegeneration. Understanding the mechanisms involved in the initiation and progression of PD may lead to potential therapeutic targets to prevent PD or modify its course.

Association of the Polygenic Risk Score with the Incidence Risk of Parkinson's Disease and Cerebrospinal Fluid α-Synuclein in a Chinese Cohort

Parkinson's disease (PD) is attributed to interactions among genes and environmental and lifestyle factors, but the genetic architecture of PD is complex and not completely understood. To evaluate whether the genetic profile modifies PD development and cerebrospinal fluid (CSF) pathological biomarkers, we enrolled 418 PD patients and 426 age- and sex-matched normal controls. Forty-six single nucleotide polymorphisms (SNPs) that were reported to be significantly associated with PD in large-scale genome-wide association studies (GWASs) were genotyped and analysed. The alleles associated with PD were used to build polygenic risk score (PRS) models to represent polygenic risk. The Cox proportional hazards model and receiver operating characteristic (ROC) analyses were used to evaluate the prediction value of the PRS for PD risk and age at onset. The CSF α-synuclein levels were measured in a subgroup of control subjects (n = 262), and its relationship with the PRS was analysed. We found that some SNPs identified from other populations had significant correlations with PD in our Chinese cohort. The PRS we built had prediction value for PD risk and age at onset. The CSF α-synuclein level had no correlation with the PRS in normal subjects.

Clinical-Pharmacogenetic Predictive Models for Time to Occurrence of Levodopa Related Motor Complications in Parkinson's Disease

The response to dopaminergic treatment in Parkinson's disease depends on many clinical and genetic factors. The very common motor fluctuations (MF) and dyskinesia affect approximately half of patients after 5 years of treatment with levodopa. We did an evaluation of a combined effect of 16 clinical parameters and 34 single nucleotide polymorphisms to build clinical and clinical-pharmacogenetic models for prediction of time to occurrence of motor complications and to compare their predictive abilities. In total, 220 Parkinson's disease patients were included in the analysis. Their demographic, clinical, and genotype data were obtained. The combined effect of clinical and genetic factors was assessed using The Least Absolute Shrinkage and Selection Operator penalized regression in the Cox proportional hazards model. Clinical and clinical-pharmacogenetic models were constructed. The predictive capacity of the models was evaluated with the cross-validated area under time-dependent receiver operating characteristic curve. Clinical-pharmacogenetic model included age at diagnosis (HR = 0.99), time from diagnosis to initiation of levodopa treatment (HR = 1.24), COMT rs165815 (HR = 0.90), DRD3 rs6280 (HR = 1.03), and BIRC5 rs9904341 (HR = 0.95) as predictive factors for time to occurrence of MF. Furthermore, clinical-pharmacogenetic model for prediction of time to occurrence of dyskinesia included female sex (HR = 1.07), age at diagnosis (HR = 0.97), tremor-predominant Parkinson's disease (HR = 0.88), beta-blockers (HR = 0.95), alcohol consumption (HR = 0.99), time from diagnosis to initiation of levodopa treatment (HR = 1.15), CAT rs1001179 (HR = 1.27), SOD2 rs4880 (HR = 0.95), NOS1 rs2293054 (HR = 0.99), COMT rs165815 (HR = 0.92), and SLC22A1 rs628031 (HR = 0.80). Areas under the curves for clinical and clinical-pharmacogenetic models for MF after 5 years of levodopa treatment were 0.68 and 0.70, respectively. Areas under the curves for clinical and clinical-pharmacogenetic models for dyskinesia after 5 years of levodopa treatment were 0.71 and 0.68, respectively. These results show that clinical-pharmacogenetic models do not have better ability to predict time to occurrence of motor complications in comparison to the clinical ones despite the significance of several polymorphisms. Models could be improved by a larger sample size and by additional polymorphisms, epigenetic predictors or serum biomarkers.

Dysregulated Lipid Metabolism and Its Role in α-Synucleinopathy in Parkinson's Disease

Parkinson’s disease (PD) is the second most common neurodegenerative disease, the main pathological hallmark of which is the accumulation of α-synuclein (α-syn) and the formation of filamentous aggregates called Lewy bodies in the brainstem, limbic system, and cortical areas. Lipidomics is a newly emerging field which can provide fresh insights and new answers that will enhance our capacity for early diagnosis, tracking disease progression, predicting critical endpoints, and identifying risk in pre-symptomatic persons. In recent years, lipids have been implicated in many aspects of PD pathology. Biophysical and lipidomic studies have demonstrated that α-syn binds preferentially not only to specific lipid families but also to specific molecular species and that these lipid-protein complexes enhance its interaction with synaptic membranes, influence its oligomerization and aggregation, and interfere with the catalytic activity of cytoplasmic lipid enzymes and lysosomal lipases, thereby affecting lipid metabolism. The genetic link between aberrant lipid metabolism and PD is even more direct, with mutations in GBA and SMPD1 enhancing PD risk in humans and loss of GALC function increasing α-syn aggregation and accumulation in experimental murine models. Moreover, a number of lipidomic studies have reported PD-specific lipid alterations in both patient brains and plasma, including alterations in the lipid composition of lipid rafts in the frontal cortex. A further aspect of lipid dysregulation promoting PD pathogenesis is oxidative stress and inflammation, with proinflammatory lipid mediators such as platelet activating factors (PAFs) playing key roles in arbitrating the progressive neurodegeneration seen in PD linked to α-syn intracellular trafficking. Lastly, there are a number of genetic risk factors of PD which are involved in normal lipid metabolism and function. Genes such as PLA2G6 and SCARB2, which are involved in glycerophospholipid and sphingolipid metabolism either directly or indirectly are associated with risk of PD. This review seeks to describe these facets of metabolic lipid dysregulation as they relate to PD pathology and potential pathomechanisms involved in disease progression, while highlighting incongruous findings and gaps in knowledge that necessitate further research.

Genetic variability of inflammation and oxidative stress genes does not play a major role in the occurrence of adverse events of dopaminergic treatment in Parkinson's disease

BACKGROUND

Inflammation and oxidative stress are recognized as important contributors to Parkinson's disease pathogenesis. As such, genetic variability in these pathways could have a role in susceptibility for the disease as well as in the treatment outcome. Dopaminergic treatment is effective in management of motor symptoms, but poses a risk for motor and non-motor adverse events. Our aim was to evaluate the impact of selected single-nucleotide polymorphisms in genes involved in inflammation and oxidative stress on Parkinson's disease susceptibility and the occurrence of adverse events of dopaminergic treatment.

METHODS

In total, 224 patients were enrolled, and their demographic and clinical data on the disease course were collected. Furthermore, a control group of 146 healthy Slovenian blood donors were included for Parkinson's disease' risk evaluation. Peripheral blood was obtained for DNA isolation. Genotyping was performed for NLRP3 rs35829419, CARD8 rs2043211, IL1β rs16944, IL1β rs1143623, IL6 rs1800795, CAT rs1001179, CAT rs10836235, SOD2 rs4880, NOS1 rs2293054, NOS1 rs2682826, TNF-α rs1800629, and GPX1 rs1050450. Logistic regression was used for analysis of possible associations.

RESULTS

We observed a nominally significant association of the IL1β rs1143623 C allele with the risk for Parkinson's disease (OR = 0.59; 95%CI = 0.38-0.92, p = 0.021). CAT rs1001179 A allele was significantly associated with peripheral edema (OR = 0.32; 95%CI = 0.15-0.68; p = 0.003). Other associations observed were only nominally significant after adjustments: NOS1 rs2682826 A allele and excessive daytime sleepiness and sleep attacks (OR = 1.75; 95%CI = 1.00-3.06, p = 0.048), SOD2 rs4880 T allele and nausea/vomiting (OR = 0.49, 95%CI = 0.25-0.94; p = 0.031), IL1β rs1143623 C allele and orthostatic hypotension (OR = 0.57, 95%CI = 0.32-1.00, p = 0.050), and NOS1 rs2682826 A allele and impulse control disorders (OR = 2.59; 95%CI = 1.09-6.19; p = 0.032). We did not find any associations between selected polymorphisms and motor adverse events.

CONCLUSIONS

Apart from some nominally significant associations, one significant association between CAT genetic variability and peripheral edema was observed as well. Therefore, the results of our study suggest some links between genetic variability in inflammation- and oxidative stress-related pathways and non-motor adverse events of dopaminergic treatment. However, the investigated polymorphisms do not play a major role in the occurrence of the disease and the adverse events of dopaminergic treatment.

Effects of rs591323 on serotonin transporter availability in healthy male subjects

OBJECTIVES

We aimed to investigate the association between genetic factors of SNPs dopamine transporter (DAT) and serotonin transporter (SERT) availabilities in healthy controls.

METHODS

The study population consisted of healthy controls with screening ¹²³I-FP-CIT single-photon emission computed tomography. Specific binding of ¹²³I-FP-CIT regarding DAT and SERT was calculated using a region of interest analysis. VOI template was applied to measure specific binding ratios (SBRs) of caudate nucleus, putamen, striatum, midbrain, and pons.

RESULTS

One hundred sixty healthy controls (male 106, female 54, 61.0 ± 11.5 years) were included in this study. Sex difference did not exist in DAT availabilities of caudate nucleus (p = 0.5344), putamen (p = 0.5006), and striatum (p = 0.5056). However, male subjects had higher SERT availabilities of both midbrain (p = 0.0436), and pons (p = 0.0061). Therefore, we analyzed the effect of SNP on DAT availabilities of subjects in all, and that on SERT availabilities of males and females separately. None of 19 SNPs included in this study showed the effect on DAT availabilities. However, rs591323 in Fibroblast Growth Factor 20 on chromosome 8 had a significant impact on SERT availability of both midbrain (p = 0.0056) and pons (p = 0.0007).

CONCLUSION

SNP rs591323 of risk loci for Parkinson's disease is associated with SERT availability of healthy male subjects.

Role of Copper Dyshomeostasis in the Pathogenesis of Parkinson's Disease

Serum concentration of copper, immunoreactive polypeptides of ceruloplasmin and its oxidase activity, and the number of copper atoms per ceruloplasmin molecule were decreased in patients with Parkinson's disease in comparison with the corresponding parameters in age-matched healthy individuals, but the ratio of apoceruloplasmin to holoceruloplasmin in patients with Parkinson's disease was similar in both groups. Treatment of blood serum with Helex 100, a high-affinity copper chelator, revealed reduced content of labile copper atoms per ceruloplasmin molecule in patients with Parkinson's disease in comparison with that in healthy controls. The mechanism underlying impaired metabolic incorporation of labile copper atoms into CP molecule is discussed as a possible cause of copper dyshomeostasis associated with Parkinson's disease.

Is Parkinson's Disease a Neurodevelopmental Disorder and Will Brain Organoids Help Us to Understand It?

Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease. The incidence of PD cases increases with age, accordingly classically PD is considered to be an age-associated neurodegenerative disease. In this review, the hypothesis that PD is actually a neurodevelopmental disorder that is compensated for a long time will be discussed. However, patients who suffer from PD typically do not show symptoms early in their lives. This implies that, if the hypothesis that PD has a significant neurodevelopmental component is correct, the developmental defects are compensated for a long time. Furthermore, these developmental defects might not causally lead to the disease but increase the susceptibility for disease onset after a "second hit." In this logic, deregulated developmental processes might represent the "first hit." Even a minor developmental defect could lead to a reduced compensatory capacity or reduced fault tolerance of the entire system. In such a case of an already imbalanced system one or more additional hits could perturb the entire system sufficiently to bring it out of balance and lead to the pathology and symptoms which we classify as PD. However, if the developmental hypothesis and the "multiple hit" hypothesis are correct, an early diagnosis of these developmental defects might allow the start of a therapy for at-risk individuals before disease pathology becomes severe and before symptoms occur. Modern stem cell technologies, including the generation of personalized brain organoids, might play an important role in these strategies.

Neurotoxins as Preclinical Models for Parkinson's Disease

Translational medicine is one of the major concerns in this century. While significant advances have been made with scientific knowledge, the translation of their promising results has not led to any new therapies. In Parkinson's disease, a long list of clinical studies, based on preclinical models with exogenous neurotoxins, has failed. Therefore, the aim of this opinion paper is to open discussion about preclinical models for Parkinson's disease based on neurotoxins.

From Genomics to Omics Landscapes of Parkinson's Disease: Revealing the Molecular Mechanisms

Molecular mechanisms of Parkinson's disease (PD) have already been investigated in various different omics landscapes. We reviewed the literature about different omics approaches between November 2005 and November 2017 to depict the main pathological pathways for PD development. In total, 107 articles exploring different layers of omics data associated with PD were retrieved. The studies were grouped into 13 omics layers: genomics-DNA level, transcriptomics, epigenomics, proteomics, ncRNomics, interactomics, metabolomics, glycomics, lipidomics, phenomics, environmental omics, pharmacogenomics, and integromics. We discussed characteristics of studies from different landscapes, such as main findings, number of participants, sample type, methodology, and outcome. We also performed curation and preliminary synthesis of multiple omics data, and identified overlapping results, which could lead toward selection of biomarkers for further validation of PD risk loci. Biomarkers could support the development of targeted prognostic/diagnostic panels as a tool for early diagnosis and prediction of progression rate and prognosis. This review presents an example of a comprehensive approach to revealing the underlying processes and risk factors of a complex disease. It urges scientists to structure the already known data and integrate it into a meaningful context.

Targeting Adenosine Signaling in Parkinson's Disease: From Pharmacological to Non-pharmacological Approaches

Parkinson's disease (PD) is one of the most prevalent neurodegenerative disease displaying negative impacts on both the health and social ability of patients and considerable economical costs. The classical anti-parkinsonian drugs based in dopaminergic replacement are the standard treatment, but several motor side effects emerge during long-term use. This mini-review presents the rationale to several efforts from pre-clinical and clinical studies using adenosine receptor antagonists as a non-dopaminergic therapy. As several studies have indicated that the monotherapy with adenosine receptor antagonists reaches limited efficacy, the usage as a co-adjuvant appeared to be a promising strategy. The formulation of multi-targeted drugs, using adenosine receptor antagonists and other neurotransmitter systems than the dopaminergic one as targets, have been receiving attention since Parkinson's disease presents a complex biological impact. While pharmacological approaches to cure or ameliorate the conditions of PD are the leading strategy in this area, emerging positive aspects have arisen from non-pharmacological approaches and adenosine function inhibition appears to improve both strategies.