Genome-wide gene-environment study identifies glutamate receptor gene GRIN2A as a Parkinson's disease modifier gene via interaction with coffee

Geometry based prediction of tau protein sites and motifs associated with misfolding and aggregation

Recent studies of tau proteins point to specific sites or motifs along the protein related to its misfolding and aggregation propensity, which is associated with neurodegenerative diseases of structure-dependent pathology. In this manuscript we employ topology and geometry to analyze the local structure of tau proteins obtained from the Protein Data Bank. Our results show that mathematical topology/geometry of cryo-EM structures alone identify the PGGG motifs, and the PHF6(*) motifs as sites of interest and reveal a geometrical hierarchy of the PGGG motifs that differs for 3R+4R and 4R tauopathies. By employing the Local Topological Free Energy (LTE), we find that progressive supranuclear palsy (PSP) and globular glial tauopathy (GGT) have the highest LTE values around residues 302-305, which are inside the jR2R3 peptide and in the vicinity of the 301 site, experimentally associated with aggregation. By extending the LTE definition to estimate a global topological free energy, we find that the jR2R3 peptide of PSP and GGT, has in fact the lowest global topological free energy among other tauopathies. These results point to a possible correlation between the global topological free energy of parts of the protein and the LTE of specific sites.

Caffeine: A Multifunctional Efficacious Molecule with Diverse Health Implications and Emerging Delivery Systems

Natural caffeine is found in many plants, including coffee beans, cacao beans, and tea leaves. Around the world, many beverages, including coffee, tea, energy drinks, and some soft drinks, have this natural caffeine compound. This paper reviewed the results of meta-studies on caffeine's effects on chronic diseases. Of importance, many meta-studies have shown that regularly drinking caffeine or caffeinated coffee significantly reduces the risk of developing Alzheimer's disease, epilepsy, and Parkinson's disease. Based on the health supplements of caffeine, this review summarizes various aspects related to the application of caffeine, including its pharmacokinetics, and various functional health benefits of caffeine, such as its effects on the central nervous system. The importance of caffeine and its use in alleviating or treating cancer, diabetes, eye diseases, autoimmune diseases, and cardiovascular diseases is also discussed. Overall, consuming caffeine daily in drinks containing antioxidant and neuroprotective properties, such as coffee, prevents progressive neurodegenerative diseases, such as Alzheimer's and Parkinson's. Furthermore, to effectively deliver caffeine to the body, recently developed nanoformulations using caffeine, for instance, nanoparticles, liposomes, etc., are summarized along with regulatory and safety considerations for caffeine. The U.S. Department of Agriculture (USDA) and the Food and Drug Administration (FDA) recommended that healthy adults consume up to 400 mg of caffeine per day or 5~6 mg/kg body weight. Since a cup of coffee contains, on average, 100 to 150 mg of coffee, 1 to 3 cups of coffee may help prevent chronic diseases. Furthermore, this review summarizes various interesting and important areas of research on caffeine and its applications related to human health.

Microbiome-based therapeutics for Parkinson's disease

Recent experimental and clinical data demonstrate a significant dysregulation of the gut microbiome in individuals with Parkinson's disease (PD). With an immense influence on all aspects of physiology, this dysregulation has potential to directly or indirectly contribute to disease pathology. Experimental models have bridged these associations toward defined contributions, identifying various microbiome-dependent impacts to PD pathology. These studies have laid the foundation for human translation, examining whether certain members of the microbiome and/or whole restoration of the gut microbiome community can provide therapeutic benefit for people living with PD. Here, we review recent and ongoing clinically-focused studies that use microbiome-targeted therapies to limit the severity and progression of PD. Fecal microbiome transplants, prebiotic interventions, and probiotic supplementation are each emerging as viable methodologies to augment the gut microbiome and potentially limit PD symptoms. While still early, the data in the field to date support continued cross-talk between experimental systems and human studies to identify key microbial factors that contribute to PD pathologies.

Genome-wide association studies of coffee intake in UK/US participants of European ancestry uncover cohort-specific genetic associations

Coffee is one of the most widely consumed beverages. We performed a genome-wide association study (GWAS) of coffee intake in US-based 23andMe participants (N = 130,153) and identified 7 significant loci, with many replicating in three multi-ancestral cohorts. We examined genetic correlations and performed a phenome-wide association study across hundreds of biomarkers, health, and lifestyle traits, then compared our results to the largest available GWAS of coffee intake from the UK Biobank (UKB; N = 334,659). We observed consistent positive genetic correlations with substance use and obesity in both cohorts. Other genetic correlations were discrepant, including positive genetic correlations between coffee intake and psychiatric illnesses, pain, and gastrointestinal traits in 23andMe that were absent or negative in the UKB, and genetic correlations with cognition that were negative in 23andMe but positive in the UKB. Phenome-wide association study using polygenic scores of coffee intake derived from 23andMe or UKB summary statistics also revealed consistent associations with increased odds of obesity- and red blood cell-related traits, but all other associations were cohort-specific. Our study shows that the genetics of coffee intake associate with substance use and obesity across cohorts, but also that GWAS performed in different populations could capture cultural differences in the relationship between behavior and genetics.

Caffeine consumption outcomes on amyotrophic lateral sclerosis disease progression and cognition

Caffeine consumption outcomes on Amyotrophic Lateral Sclerosis (ALS) including progression, survival and cognition remain poorly defined and may depend on its metabolization influenced by genetic variants. 378 ALS patients with a precise evaluation of their regular caffeine consumption were monitored as part of a prospective multicenter study. Demographic, clinical characteristics, functional disability as measured with revised ALS Functional Rating Scale (ALSFRS-R), cognitive deficits measured using Edinburgh Cognitive and Behavioural ALS Screen (ECAS), survival and riluzole treatment were recorded. 282 patients were genotyped for six single nucleotide polymorphisms tagging different genes involved in caffeine intake and/or metabolism: CYP1A1 (rs2472297), CYP1A2 (rs762551), AHR (rs4410790), POR (rs17685), XDH (rs206860) and ADORA2A (rs5751876) genes. Association between caffeine consumption and ALSFRS-R, ALSFRS-R rate, ECAS and survival were statistically analyzed to determine the outcome of regular caffeine consumption on ALS disease progression and cognition. No association was observed between caffeine consumption and survival (p = 0.25), functional disability (ALSFRS-R; p = 0.27) or progression of ALS (p = 0.076). However, a significant association was found with higher caffeine consumption and better cognitive performance on ECAS scores in patients carrying the C/T and T/T genotypes at rs2472297 (p-het = 0.004). Our results support the safety of regular caffeine consumption on ALS disease progression and survival and also show its beneficial impact on cognitive performance in patients carrying the minor allele T of rs2472297, considered as fast metabolizers, that would set the ground for a new pharmacogenetic therapeutic strategy.

Interaction between caffeine consumption & genetic susceptibility in Parkinson's disease: A systematic review

BACKGROUND

Caffeine is one of the most consumed psychoactive substances globally. Caffeine-gene interactions in Parkinson's disease (PD) has not been systematically examined.

OBJECTIVES

To conduct a systematic review on the interaction between caffeine consumption and genetic susceptibility to PD.

METHODOLOGY

We conducted PubMed and Embase search using terms "Genetic association studies", "Caffeine", "polymorphism" and "Parkinson's disease", from inception till 2023. Of the initial 2391 studies, 21 case-control studies were included. The demographic, genetic and clinical data were extracted and analyzed.

RESULTS

We identified 21 studies which involved a total of 607,074 study subjects and 17 gene loci (SNCA, MAPT, HLA-DRA, NOS1, NOS3, GBA, ApoE, BST1, ESR2, NAT2, SLC2A13, LRRK2, NOS2A, GRIN2A, CYP1A2, ESR1, ADORA2A) have been investigated for the effect of gene-caffeine interaction and PD risk. The genes were identified through PD GWAS or involved in caffeine or related metabolism pathways. Based on the genetic association and interaction studies, only MAPT, SLC2A13, LRRK2, ApoE, NOS2A, GRIN2A, CYP1A2, and ADORA2A have been shown by at least one study to have a positive caffeine-gene interaction influencing the risk of PD.

CONCLUSION

Studies have shown an interaction between caffeine with genetic variants of MAPT, SLC2A13, LRRK2, ApoE, NOS2A, GRIN2A, CYP1A2, and ADORA2A in modulating the risk of PD. Due to the potential limitations of these discovery/pilot studies, further independent replication studies are needed. Better designed genetic association studies in multi-ancestry and admixed cohorts to identify potential shared or unique multivariate gene-environmental interactions, as well as functional studies of gene-caffeine interactions will be useful.

The combined effect of lifestyle factors and polygenic scores on age at onset in Parkinson's disease

The objective of this study was to investigate the association between a Parkinson's disease (PD)-specific polygenic score (PGS) and protective lifestyle factors on age at onset (AAO) in PD. We included data from 4367 patients with idiopathic PD, 159 patients with GBA1-PD, and 3090 healthy controls of European ancestry from AMP-PD, PPMI, and Fox Insight cohorts. The association between PGS and lifestyle factors on AAO was assessed with linear and Cox proportional hazards models. The PGS showed a negative association with AAO (β = - 1.07, p = 6 × 10-7) in patients with idiopathic PD. The use of one, two, or three of the protective lifestyle factors showed a reduction in the hazard ratio by 21% (p = 0.0001), 44% (p < 2 × 10-16), and 55% (p < 2 × 10-16), compared to no use. An additive effect of aspirin (β = 7.62, p = 9 × 10-7) and PGS (β = - 1.58, p = 0.0149) was found for AAO without an interaction (p = 0.9993) in the linear regressions, and similar effects were seen for tobacco. In contrast, no association between aspirin intake and AAO was found in GBA1-PD (p > 0.05). In our cohort, coffee, tobacco, aspirin, and PGS are independent predictors of PD AAO. Additionally, lifestyle factors seem to have a greater influence on AAO than common genetic risk variants with aspirin presenting the largest effect.

GluN2B subunit selective N-methyl-D-aspartate receptor ligands: Democratizing recent progress to assist the development of novel neurotherapeutics

N-methyl-D-aspartate receptors (NMDARs) play essential roles in vital aspects of brain functions. NMDARs mediate clinical features of neurological diseases and thus, represent a potential therapeutic target for their treatments. Many findings implicated the GluN2B subunit of NMDARs in various neurological disorders including epilepsy, ischemic brain damage, and neurodegenerative disorders such as Parkinson's disease, Alzheimer's disease, Huntington's chorea, and amyotrophic lateral sclerosis. Although a large amount of information is growing consistently on the importance of GluN2B subunit, however, limited recent data is available on how subunit-selective ligands impact NMDAR functions, which blunts the ability to render the diagnosis or craft novel treatments tailored to patients. To bridge this gap, we have focused on and summarized recently reported GluN2B selective ligands as emerging subunit-selective antagonists and modulators of NMDAR. Herein, we have also presented an overview of the structure-function relationship for potential GluN2B/NMDAR ligands with their binding sites and connection to CNS functionalities. Understanding of design rules and roles of GluN2B selective compounds will provide the link to medicinal chemists and neuroscientists to explore novel neurotherapeutic strategies against dysfunctions of glutamatergic neurotransmission.

Mathematical topology and geometry-based classification of tauopathies

Neurodegenerative diseases, like Alzheimer's, are associated with the presence of neurofibrillary lesions formed by tau protein filaments in the cerebral cortex. While it is known that different morphologies of tau filaments characterize different neurodegenerative diseases, there are few metrics of global and local structure complexity that enable to quantify their structural diversity rigorously. In this manuscript, we employ for the first time mathematical topology and geometry to classify neurodegenerative diseases by using cryo-electron microscopy structures of tau filaments that are available in the Protein Data Bank. By employing mathematical topology metrics (Gauss linking integral, writhe and second Vassiliev measure) we achieve a consistent, but more refined classification of tauopathies, than what was previously observed through visual inspection. Our results reveal a hierarchy of classification from global to local topology and geometry characteristics. In particular, we find that tauopathies can be classified with respect to the handedness of their global conformations and the handedness of the relative orientations of their repeats. Progressive supranuclear palsy is identified as an outlier, with a more complex structure than the rest, reflected by a small, but observable knotoid structure (a diagrammatic structure representing non-trivial topology). This topological characteristic can be attributed to a pattern in the beginning of the R3 repeat that is present in all tauopathies but at different extent. Moreover, by comparing single filament to paired filament structures within tauopathies we find a consistent change in the side-chain orientations with respect to the alpha carbon atoms at the area of interaction.

Machine Learning-Based Classification of Parkinson's Disease Patients Using Speech Biomarkers

BACKGROUND

Parkinson's disease (PD) is the most prevalent neurodegenerative movement disorder and a growing health concern in demographically aging societies. The prevalence of PD among individuals over the age of 60 and 80 years has been reported to range between 1% and 4%. A timely diagnosis of PD is desirable, even though it poses challenges to medical systems.

OBJECTIVE

This study aimed to classify PD and healthy controls based on the analysis of voice records at different frequencies using machine learning (ML) algorithms.

METHODS

The voices of 252 individuals aged 33 to 87 years were recorded. Based on the voice record data, ML algorithms can distinguish PD patients and healthy controls. One binary decision variable was associated with 756 instances and 754 attributes. Voice records data were analyzed through supervised ML algorithms and pipelines. A 10-fold cross-validation method was used to validate models.

RESULTS

In the classification of PD patients, ML models were performed with 84.21 accuracy, 93 precision, 89 Sensitivity, 89 F1-scores, and 87 AUC. The pipeline performance improved to accuracy: 85.09, precision: 92, Sensitivity:91, F1-score: 89, and AUC: 90. The Pipeline methods improved the performance of classifying PD from voice record.

CONCLUSIONS

Our study demonstrated that ML classifiers and pipelines can classify PD patients based on speech biomarkers. It was found that pipelines were more effective at selecting the most relevant features from high-dimensional data and at accurately classifying PD patients and healthy controls. This approach can therefore be used for early diagnosis of initial forms of PD.

Trends on Novel Targets and Nanotechnology-Based Drug Delivery System in the Treatment of Parkinson's disease: Recent Advancement in Drug Development

Parkinson's disease (PD) is a progressive neurodegenerative disorder that impacts a significant portion of the population. Despite extensive research, an effective cure for PD remains elusive, and conventional pharmacological treatments often face limitations in efficacy and management of symptoms. There has been a lot of discussion about using nanotechnology to increase the bioavailability of small- molecule drugs to target cells in recent years. It is possible that PD treatment might become far more effective and have fewer side effects if medication delivery mechanisms were to be improved. Potential alternatives to pharmacological therapy for molecular imaging and treatment of PD may lie in abnormal proteins such as parkin, α-synuclein, leucine-rich repeat serine and threonine protein kinase 2. Published research has demonstrated encouraging outcomes when nanomedicine-based approaches are used to address the challenges of PD therapy. So, to address the present difficulties of antiparkinsonian treatment, this review outlines the key issues and limitations of antiparkinsonian medications, new therapeutic strategies, and the breadth of delivery based on nanomedicine. This review covers a wide range of subjects, including drug distribution in the brain, the efficacy of drug-loaded nano-carriers in crossing the blood-brain barrier, and their release profiles. In PD, the nano-carriers are also used. Novel techniques of pharmaceutical delivery are currently made possible by vesicular carriers, which eliminate the requirement to cross the blood-brain barrier (BBB).

Genome-Wide Association Studies of Coffee Intake in UK/US Participants of European Ancestry Uncover Gene-Cohort Influences

Coffee is one of the most widely consumed beverages. We performed a genome-wide association study (GWAS) of coffee intake in US-based 23andMe participants (N=130,153) and identified 7 significant loci, with many replicating in three multi-ancestral cohorts. We examined genetic correlations and performed a phenome-wide association study across thousands of biomarkers and health and lifestyle traits, then compared our results to the largest available GWAS of coffee intake from UK Biobank (UKB; N=334,659). The results of these two GWAS were highly discrepant. We observed positive genetic correlations between coffee intake and psychiatric illnesses, pain, and gastrointestinal traits in 23andMe that were absent or negative in UKB. Genetic correlations with cognition were negative in 23andMe but positive in UKB. The only consistent observations were positive genetic correlations with substance use and obesity. Our study shows that GWAS in different cohorts could capture cultural differences in the relationship between behavior and genetics.

Glycogen-binding protein STBD1: Molecule and role in pathophysiology

Starch-binding domain-containing protein 1 (STBD1) is a glycogen-binding protein discovered in skeletal muscle gene differential expression that is pivotal to cellular energy metabolism. Recent studies have indicated that STBD1 is involved in many physiological processes, such as glycophagy, glycogen accumulation, and lipid droplet formation. Moreover, dysregulation of STBD1 causes multiple diseases, including cardiovascular disease, metabolic disease, and even cancer. Deletions and/or mutations in STBD1 promote tumorigenesis. Therefore, STBD1 has garnered considerable interest in the pathology community. In this review, we first summarized the current understanding of STBD1, including its structure, subcellular localization, tissue distribution, and biological functions. Next, we examined the roles and molecular mechanisms of STBD1 in related diseases. Based on available research, we discussed the novel function and future of STBD1, including its potential application as a therapeutic target in glycogen-related diseases. Given the significance of STBD1 in energy metabolism, an in-depth understanding of the protein is crucial for understanding physiological processes and developing therapeutic strategies for related diseases.

The combined effect of lifestyle factors and polygenic scores on age at onset in Parkinson's disease

Objective

To investigate the association between a Parkinson's disease (PD)-specific polygenic score (PGS) and protective lifestyle factors on age at onset (AAO) in PD.

Methods

We included data from 4375 patients with idiopathic PD, 167 patients with GBA1-PD, and 3091 healthy controls of European ancestry from AMP-PD, PPMI, and Fox Insight cohorts. The PGS was calculated based on a previously proposed composition of 1805 variants. The association between PGS and lifestyle factors (i.e., coffee, tobacco, and aspirin) on AAO was assessed with linear and Cox proportional hazards models.

Results

The PGS showed a negative association with AAO (β=-1.07, p=6×10-7). The use of one, two, or three of the protective lifestyle factors showed a reduction in the hazard ratio by 21% (p=0.0001), 45% (p<2×10-16), and 55% (p<2×10-16), respectively, compared to no use. An additive effect of aspirin (β=7.61, p=8×10-7) and PGS (β=-1.63, p=0.0112) was found for AAO without an interaction (p=0.9789) in the linear regressions, and similar effects were seen for tobacco. Aspirin is shown to be a better predictor of AAO (R2=0.1740) compared to coffee and tobacco use (R2=0.0243, R2=0.0295) or the PGS (R2=0.0141). In contrast, no association between aspirin and AAO was found in GBA1-PD (p>0.05).

Interpretation

In our cohort, coffee, tobacco, aspirin, and PGS are independent predictors of PD AAO. Additionally, lifestyle factors seem to have a greater influence on AAO than common genetic risk variants with aspirin presenting the largest effect. External validation of our findings is needed.

The evolution of Big Data in neuroscience and neurology

Neurological diseases are on the rise worldwide, leading to increased healthcare costs and diminished quality of life in patients. In recent years, Big Data has started to transform the fields of Neuroscience and Neurology. Scientists and clinicians are collaborating in global alliances, combining diverse datasets on a massive scale, and solving complex computational problems that demand the utilization of increasingly powerful computational resources. This Big Data revolution is opening new avenues for developing innovative treatments for neurological diseases. Our paper surveys Big Data's impact on neurological patient care, as exemplified through work done in a comprehensive selection of areas, including Connectomics, Alzheimer's Disease, Stroke, Depression, Parkinson's Disease, Pain, and Addiction (e.g., Opioid Use Disorder). We present an overview of research and the methodologies utilizing Big Data in each area, as well as their current limitations and technical challenges. Despite the potential benefits, the full potential of Big Data in these fields currently remains unrealized. We close with recommendations for future research aimed at optimizing the use of Big Data in Neuroscience and Neurology for improved patient outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40537-023-00751-2.

Parkinson's disease - genetic cause

PURPOSE OF REVIEW

Our knowledge of the genetic architecture underlying Parkinson's disease has vastly improved in the past quarter century. About 5-10% of all patients suffer from a monogenic form of Parkinson's disease.

RECENT FINDINGS

Mutations in autosomal dominant genes (e.g. SNCA, LRRK2, VPS35) or autosomal recessive genes (e.g. PRKN, PINK1, DJ-1) can cause genetic Parkinson's disease. Recessive DNAJC6 mutations can present predominantly as atypical parkinsonism, but also rarely as typical Parkinson's disease. Majority of Parkinson's disease is genetically complex. Mutation in RIC3, a chaperone of neuronal nicotinic acetylcholine receptor subunit α-7 (CHRNA7), provides strong evidence for the role of cholinergic pathway, for the first time, in cause of Parkinson's disease. X-linked parkinsonism manifests at a young age accompanied by many (atypical) features such as intellectual disability, spasticity, seizures, myoclonus, dystonia, and have poor response to levodopa.

SUMMARY

This review article aims to provide a comprehensive overview on Parkinson's disease genetics. MAPT, which encodes the microtubule associated protein tau, TMEM230, LRP10, NUS1 and ARSA are the five new putative disease-causing genes in Parkinson's disease. The validation of novel genes and its association with Parkinson's disease remains extremely challenging, as genetically affected families are sparse and globally widespread. In the near future, genetic discoveries in Parkinson's disease will influence our ability to predict and prognosticate the disease, help in defining etiological subtypes that are critical in implementation of precision medicine.

Early-Onset Parkinson's Disease: Creating the Right Environment for a Genetic Disorder

Parkinson's disease (PD) by its common understanding is a late-onset sporadic movement disorder. However, there is a need to recognize not only the fact that PD pathogenesis expands beyond (or perhaps to) the brain but also that many early-onset patients develop motor signs before the age of 50 years. Indeed, studies have shown that it is likely the protein aggregation observed in the brains of patients with PD precedes the motor symptoms by perhaps a decade. Studies on early-onset forms of PD have shown it to be a heterogeneous disease with multiple genetic and environmental factors determining risk of different forms of disease. Genetic and neuropathological evidence suggests that there are α-synuclein centric forms (e.g., SNCA genomic triplication), and forms that are driven by a breakdown in mitochondrial function and specifically in the process of mitophagy and clearance of damaged mitochondria (e.g., PARKIN and PINK1 recessive loss-of-function mutations). Aligning genetic forms with recognized environmental influences will help better define patients, aid prognosis, and hopefully lead to more accurately targeted clinical trial design. Work is now needed to understand the cross-talk between these two pathomechanisms and determine a sense of independence, it is noted that autopsies studies for both have shown the presence or absence of α-synuclein aggregation. The integration of genetic and environmental data is critical to understand the etiology of early-onset forms of PD and determine how the different pathomechanisms crosstalk.

Metagenomics of Parkinson's disease implicates the gut microbiome in multiple disease mechanisms

Parkinson's disease (PD) may start in the gut and spread to the brain. To investigate the role of gut microbiome, we conducted a large-scale study, at high taxonomic resolution, using uniform standardized methods from start to end. We enrolled 490 PD and 234 control individuals, conducted deep shotgun sequencing of fecal DNA, followed by metagenome-wide association studies requiring significance by two methods (ANCOM-BC and MaAsLin2) to declare disease association, network analysis to identify polymicrobial clusters, and functional profiling. Here we show that over 30% of species, genes and pathways tested have altered abundances in PD, depicting a widespread dysbiosis. PD-associated species form polymicrobial clusters that grow or shrink together, and some compete. PD microbiome is disease permissive, evidenced by overabundance of pathogens and immunogenic components, dysregulated neuroactive signaling, preponderance of molecules that induce alpha-synuclein pathology, and over-production of toxicants; with the reduction in anti-inflammatory and neuroprotective factors limiting the capacity to recover. We validate, in human PD, findings that were observed in experimental models; reconcile and resolve human PD microbiome literature; and provide a broad foundation with a wealth of concrete testable hypotheses to discern the role of the gut microbiome in PD.

Development of a Systematic Strategy toward Promotion of α-Synuclein Aggregation Using 2-Hydroxyisophthalamide-Based Systems

Establishing a potent scheme against α-synuclein aggregation involved in Parkinson's disease has been evaluated as a promising route to identify compounds that either inhibit or promote the aggregation process of α-synuclein. In the last two decades, this perspective has guided a dramatic increase in the efforts, focused on developing potent drugs either for retardation or promotion of the self-assembly process of α-synuclein. To address this issue, using a chemical kinetics platform, we developed a strategy that enabled a progressively detailed analysis of the molecular events leading to protein aggregation at the microscopic level in the presence of a recently synthesized 2-hydroxyisophthalamide class of small organic molecules based on their binding affinity. Furthermore, qualitatively, we have developed a strategy of disintegration of α-synuclein fibrils in the presence of these organic molecules. Finally, we have shown that these organic molecules effectively suppress the toxicity of α-synuclein oligomers in neuron cells.

Parkinson's Disease: Risk Factor Modification and Prevention

The global burden of Parkinson's disease (PD) has increased from 2.5 to 6.1 million since the 1990s. This is expected to rise as the world population ages and lives longer. With the current consensus on the existence of a prediagnostic phase of PD, which can be divided into a preclinical stage and a prodromal stage, we can better define the risk markers and prodromal markers of PD in the broader context of PD pathogenesis. Here, we review this pathogenetic process, and discuss the evidence behind various heritability factors, exposure to pesticides and farming, high dairy consumption, and traumatic brain injuries that have been known to raise PD risk. Physical activity, early active lifestyle, high serum uric acid, caffeine consumption, exposure to tobacco, nonsteroidal anti-inflammatory drugs, and calcium channel blockers, as well as the Mediterranean and the MIND diets are observed to lower PD risk. This knowledge, when combined with ways to identify at-risk populations and early prodromal PD patients, can help the clinician make practical recommendations. Most importantly, it helps us set the parameters for epidemiological studies and create the paradigms for clinical trials.

Addressing the Neuroprotective Actions of Coffee in Parkinson’s Disease: An Emerging Nutrigenomic Analysis

Caffeine is one of the predominant dietary components and psychostimulants present in coffee, a widely appreciated beverage. Corroborating epidemiological and laboratory evidence have suggested an inverse association between the dietary intakes of coffee and the risk of Parkinson’s Disease (PD). Growing attention has been paid to the impact of coffee consumption and genetic susceptibility to PD pathogenesis. Coffee is believed to play prominent roles in mediating the gene makeup and influencing the onset and progression of PD. The current review documents a current discovery of the coffee × gene interaction for the protective management of PD. The evidence underlying its potent impacts on the adenosine receptors (A2AR), estrogen receptors (ESR), heme oxygenase (HO), toxicant responsive genes, nitric oxide synthase (NOS), cytochrome oxidase (Cox), familial parkinsonism genetic susceptibility loci, bone marrow stromal cell antigen 1 (BST1), glutamate receptor gene and apolipoprotein E (APOE) genotype expressions is outlined. Furthermore, the neuroprotective mechanisms of coffee for the amelioration of PD are elucidated.

Cognition and serotonin in Parkinson's disease

Cognitive impairment affects up to 80% of patients with Parkinson's disease (PD) and is associated with poor quality of life. PD cognitive dysfunction includes poor working memory, impairments in executive function and difficulty in set-shifting. The pathophysiology underlying cognitive impairment in PD is still poorly understood, but there is evidence to support involvements of the cholinergic, dopaminergic, and noradrenergic systems. Only rivastigmine, an acetyl- and butyrylcholinesterase inhibitor, is efficacious for the treatment of PD dementia, which limits management of cognitive impairment in PD. Whereas the role of the serotonergic system in PD cognition is less understood, through its interactions with other neurotransmitters systems, namely, the cholinergic system, it may be implicated in cognitive processes. In this chapter, we provide an overview of the pharmacological, clinical and pathological evidence that implicates the serotonergic system in mediating cognition in PD.

Smooth-threshold multivariate genetic prediction incorporating gene–environment interactions

We propose a genetic prediction modeling approach for genome-wide association study (GWAS) data that can include not only marginal gene effects but also gene–environment (GxE) interaction effects—i.e., multiplicative effects of environmental factors with genes rather than merely additive effects of each. The proposed approach is a straightforward extension of our previous multiple regression-based method, STMGP (smooth-threshold multivariate genetic prediction), with the new feature being that genome-wide test statistics from a GxE interaction analysis are used to weight the corresponding variants. We develop a simple univariate regression approximation to the GxE interaction effect that allows a direct fit of the STMGP framework without modification. The sparse nature of our model automatically removes irrelevant predictors (including variants and GxE combinations), and the model is able to simultaneously incorporate multiple environmental variables. Simulation studies to evaluate the proposed method in comparison with other modeling approaches demonstrate its superior performance under the presence of GxE interaction effects. We illustrate the usefulness of our prediction model through application to real GWAS data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI).

Does Caffeine Consumption Affect the Symptoms of Parkinson’s Disease? A Systematic Review of Clinical Trials

Objectives: This systematic review of the literature was carried out to see whether coffee consumption could affect Parkinson’s disease (PD) symptoms. Methods: Randomized controlled trials (RCTs), crossover studies, and quasi-experimental studies were assessed to evaluate the effect of caffeine on PD. The databases including Medline/PubMed, ProQuest, Embase, Cochrane Library, and ClinicalTrials.gov were systematically searched. The Cochrane Collaboration’s tool for assessing the risk of bias in randomized clinical trials and the Cochrane risk of bias assessment tool for non-randomized studies of interventions (ROBINS-I) were used to assess the quality of RCTs and non-randomized clinical trials, respectively. A meta-analysis of the results was not possible because of reporting different outcomes. Results: Four papers were included in this study. Only one study reported the significant effect of caffeine on ESS and UPDRS. Another study observed no significant effect of caffeine on ESS during three- and six-week interventions. However, a significant reduction in ESS scores in the sixth week was reported after excluding four protocol violations. This study reported that the UPDRS score reduced in the third week, but significant changes were observed after six weeks. The other two studies did not show a significant effect of caffeine on ESS and UPDRS. Conclusions: Since a meta-analysis was not conducted, there was insufficient evidence to evaluate the effect of caffeine on PD. Thus, it is recommended to conduct more well-designed RCTs with a larger sample size to assess the effect of caffeine on PD.

Parkinson Disease: Translating Insights from Molecular Mechanisms to Neuroprotection

Parkinson disease (PD) used to be considered a nongenetic condition. However, the identification of several autosomal dominant and recessive mutations linked to monogenic PD has changed this view. Clinically manifest PD is then thought to occur through a complex interplay between genetic mutations, many of which have incomplete penetrance, and environmental factors, both neuroprotective and increasing susceptibility, which variably interact to reach a threshold over which PD becomes clinically manifested. Functional studies of PD gene products have identified many cellular and molecular pathways, providing crucial insights into the nature and causes of PD. PD originates from multiple causes and a range of pathogenic processes at play, ultimately culminating in nigral dopaminergic loss and motor dysfunction. An in-depth understanding of these complex and possibly convergent pathways will pave the way for therapeutic approaches to alleviate the disease symptoms and neuroprotective strategies to prevent disease manifestations. This review is aimed at providing a comprehensive understanding of advances made in PD research based on leveraging genetic insights into the pathogenesis of PD. It further discusses novel perspectives to facilitate identification of critical molecular pathways that are central to neurodegeneration that hold the potential to develop neuroprotective and/or neurorestorative therapeutic strategies for PD. SIGNIFICANCE STATEMENT: A comprehensive review of PD pathophysiology is provided on the complex interplay of genetic and environmental factors and biologic processes that contribute to PD pathogenesis. This knowledge identifies new targets that could be leveraged into disease-modifying therapies to prevent or slow neurodegeneration in PD.

A two-stage testing strategy for detecting genes×environment interactions in association studies

Identifying gene×environment (G×E) interactions, especially when rare variants are included in genome-wide association studies, is a major challenge in statistical genetics. However, the detection of G×E interactions is very important for understanding the etiology of complex diseases. Although currently some statistical methods have been developed to detect the interactions between genes and environment, the detection of the interactions for the case of rare variants is still limited. Therefore, it is particularly important to develop a new method to detect the interactions between genes and environment for rare variants. In this study, we extend an existing method of adaptive combination of P-values (ADA) and design a novel strategy (called iSADA) for testing the effects of G×E interactions for rare variants. We propose a new two-stage test to detect the interactions between genes and environment in a certain region of a chromosome or even for the whole genome. First, the score statistic is used to test the associations between trait value and the interaction terms of genes and environment and obtain the original P-values. Then, based on the idea of the ADA method, we further construct a full test statistic via the P-values of the preliminary tests in the first stage, so that we can comprehensively test the interactions between genes and environment in the considered genome region. Simulation studies are conducted to compare our proposed method with other existing methods. The results show that the iSADA has higher power than other methods in each case. A GAW17 data set is also applied to illustrate the applicability of the new method.

Exploring human-genome gut-microbiome interaction in Parkinson's disease

The causes of complex diseases remain an enigma despite decades of epidemiologic research on environmental risks and genome-wide studies that have uncovered tens or hundreds of susceptibility loci for each disease. We hypothesize that the microbiome is the missing link. Genetic studies have shown that overexpression of alpha-synuclein, a key pathological protein in Parkinson’s disease (PD), can cause familial PD and variants at alpha-synuclein locus confer risk of idiopathic PD. Recently, dysbiosis of gut microbiome in PD was identified: altered abundances of three microbial clusters were found, one of which was composed of opportunistic pathogens. Using two large datasets, we found evidence that the overabundance of opportunistic pathogens in PD gut is influenced by the host genotype at the alpha-synuclein locus, and that the variants responsible modulate alpha-synuclein expression. Results put forth testable hypotheses on the role of gut microbiome in the pathogenesis of PD, the incomplete penetrance of PD susceptibility genes, and potential triggers of pathology in the gut.

Understanding the Pathogenesis Involved in Parkinson's Disease and Potential Therapeutic Treatment Strategies

A vast advancement has been made in the treatment related to central nervous system disorders especially Parkinson's disease. The development in therapeutics and a better understanding of the targets results in upsurge of many promising therapies for Parkinson's disease. Parkinson's disease is defined by neuronal degeneration and neuroinflammation and it is reported that the presence of the neurofibrillary aggregates such as Lewy bodies is considered as the marker. Along with this, it is also characterized by the presence of motor and non-motor symptoms, as seen in Parkinsonian patients. A lot of treatment options mainly focus on prophylactic measures or the symptomatic treatment of Parkinson's disease. Neuroinflammation and neurodegeneration are the point of interest which can be exploited as a new target to emphasis on Parkinson's disease. A thorough study of these targets helps in modifications of those molecules which are particularly involved in causing the neuronal degeneration and neuroinflammation in Parkinson's disease. A lot of drug regimens are available for the treatment of Parkinson's disease, although levodopa remains the choice of drug for controlling the symptoms, yet is accompanied with significant snags. It is always suggested to use other drug therapies concomitantly with levodopa. A number of significant causes and therapeutic targets for Parkinson's disease have been identified in the last decade, here an attempt was made to highlight the most significant of them. It was also found that the treatment regimen and involvement of therapies are totally dependent on individuals and can be tailored to the needs of each individual patient.

Genome-wide conditional association study reveals the influences of lifestyle cofactors on genetic regulation of body surface area in MESA population

Body surface area (BSA) is an important trait used for many clinical purposes. People's BSA may vary due to genetic background, race, and different lifestyle factors (such as walking, exercise, reading, smoking, transportation, etc.). GWAS of BSA was conducted on 5,324 subjects of four ethnic populations of European-American, African-American, Hispanic-American, and Chinese-American from the Multi-Ethnic Study of Atherocloris (MESA) data using unconditional and conditional full genetic models. In this study, fifteen SNPs were identified (Experiment-wise PEW < 1×10-5) using unconditional full genetic model, of which thirteen SNPs had individual genetic effects and seven SNPs were involved in four pairs of epistasis interactions. Seven single SNPs and eight pairs of epistasis SNPs were additionally identified using exercise, smoking, and transportation cofactor-conditional models. By comparing association analysis results from unconditional and cofactor conditional models, we observed three different scenarios: (i) genetic effects of several SNPs did not affected by cofactors, e.g., additive effect of gene CREB5 (a≙ -0.013 for T/T and 0.013 for G/G, -Log10 PEW = 8.240) did not change in the cofactor models; (ii) genetic effects of several SNPs affected by cofactors, e.g., the genetic additive effect (a≙ 0.012 for A/A and -0.012 for G/G, -Log10 PEW = 7.185) of SNP of the gene GRIN2A was not significant in transportation cofactor model; and (iii) genetic effects of several SNPs suppressed by cofactors, e.g., additive (a≙ -0.018 for G/G and 0.018 for C/C, -Log10 PEW = 19.737) and dominance (d≙ -0.038 for G/C, -Log10 PEW = 27.734) effects of SNP of gene ERBB4 was identified using only transportation cofactor model. Gene ontology analysis showed that several genes are related to the metabolic pathway of calcium compounds, coronary artery disease, type-2 Diabetes, Alzheimer disease, childhood obesity, sleeping duration, Parkinson disease, and cancer. This study revealed that lifestyle cofactors could contribute, suppress, increase or decrease the genetic effects of BSA associated genes.

Prioritizing Pain-Associated Targets with Machine Learning

While hundreds of genes have been associated with pain, much of the molecular mechanisms of pain remain unknown. As a result, current analgesics are limited to few clinically validated targets. Here, we trained a machine learning (ML) ensemble model to predict new targets for 17 categories of pain. The model utilizes features from transcriptomics, proteomics, and gene ontology to prioritize targets for modulating pain. We focused on identifying novel G-protein-coupled receptors (GPCRs), ion channels, and protein kinases because these proteins represent the most successful drug target families. The performance of the model to predict novel pain targets is 0.839 on average based on AUROC, while the predictions for arthritis had the highest accuracy (AUROC = 0.929). The model predicts hundreds of novel targets for pain; for example, GPR132 and GPR109B are highly ranked GPCRs for rheumatoid arthritis. Overall, gene-pain association predictions cluster into three groups that are enriched for cytokine, calcium, and GABA-related cell signaling pathways. These predictions can serve as a foundation for future experimental exploration to advance the development of safer and more effective analgesics.

Advancing Personalized Medicine in Common Forms of Parkinson's Disease through Genetics: Current Therapeutics and the Future of Individualized Management

Parkinson’s disease (PD) is a condition with heterogeneous clinical manifestations that vary in age at onset, rate of progression, disease course, severity, motor and non-motor symptoms, and a variable response to antiparkinsonian drugs. It is considered that there are multiple PD etiological subtypes, some of which could be predicted by genetics. The characterization and prediction of these distinct molecular entities provides a growing opportunity to use individualized management and personalized therapies. Dissecting the genetic architecture of PD is a critical step in identifying therapeutic targets, and genetics represents a step forward to sub-categorize and predict PD risk and progression. A better understanding and separation of genetic subtypes has immediate implications in clinical trial design by unraveling the different flavors of clinical presentation and development. Personalized medicine is a nascent area of research and represents a paramount challenge in the treatment and cure of PD. This manuscript summarizes the current state of precision medicine in the PD field and discusses how genetics has become the engine to gain insights into disease during our constant effort to develop potential etiological based interventions.

Novel targeted therapies for Parkinson's disease

Parkinson’s disease (PD) is the second more common neurodegenerative disease with increasing incidence worldwide associated to the population ageing. Despite increasing awareness and significant research advancements, treatment options comprise dopamine repleting, symptomatic therapies that have significantly increased quality of life and life expectancy, but no therapies that halt or reverse disease progression, which remain a great, unmet goal in PD research. Large biomarker development programs are undertaken to identify disease signatures that will improve patient selection and outcome measures in clinical trials. In this review, we summarize PD-related mechanisms that can serve as targets of therapeutic interventions aiming to slow or modify disease progression, as well as previous and ongoing clinical trials in each field, and discuss future perspectives.

Single Nucleotide Polymorphisms Associated With Gut Homeostasis Influence Risk and Age-at-Onset of Parkinson's Disease

Research is increasingly focusing on gut inflammation as a contributor to Parkinson's disease (PD). Such gut inflammation is proposed to arise from a complex interaction between various genetic, environmental, and lifestyle factors, however these factors are under-characterized. This study investigated the association between PD and single-nucleotide polymorphisms (SNPs) in genes responsible for binding of bacterial metabolites and intestinal homeostasis, which have been implicated in intestinal infections or inflammatory bowel disease. A case-control analysis was performed utilizing the following cohorts: (i) patients from the Australian Parkinson's Disease Registry (APDR) (n = 212); (ii) a Caucasian subset of the Parkinson's Progression Markers Initiative (PPMI) cohort (n = 376); (iii) a combined control group (n = 404). The following SNPs were analyzed: PGLYRP2 rs892145, PGLYRP4 rs10888557, TLR1 rs4833095, TLR2 rs3804099, TLR4 rs7873784, CD14 rs2569190, MUC1 rs4072037, MUC2 rs11825977, CLDN2 rs12008279 and rs12014762, and CLDN4 rs8629. PD risk was significantly associated with PGLYRP4 rs10888557 genotype in both cohorts. PGLYRP2 rs892145 and TLR1 rs4833095 were also associated with disease risk in the APDR cohort, and TLR2 rs3804099 and MUC2 rs11825977 genotypes in the PPMI cohort. Interactive risk effects between PGLYRP2/PGLYRP4 and PGLYRP4/TLR2 were evident in the APDR and PPMI cohorts, respectively. In the APDR cohort, the PGLYRP4 GC genotype was significantly associated with age of symptom onset, independently of gender, toxin exposure or smoking status. This study demonstrates that genetic variation in the bacterial receptor PGLYRP4 may modulate risk and age-of-onset in idiopathic PD, while variants in PGLYRP2, TLR1/2, and MUC2 may also influence PD risk. Overall, this study provides evidence to support the role of dysregulated host-microbiome signaling and gut inflammation in PD, and further investigation of these SNPs and proteins may help identify people at risk of developing PD or increase understanding of early disease mechanisms.

Caffeine and Parkinson's Disease: Multiple Benefits and Emerging Mechanisms

Parkinson’s disease (PD) is the second most common neurodegenerative disorder, characterized by dopaminergic neurodegeneration, motor impairment and non-motor symptoms. Epidemiological and experimental investigations into potential risk factors have firmly established that dietary factor caffeine, the most-widely consumed psychoactive substance, may exerts not only neuroprotective but a motor and non-motor (cognitive) benefits in PD. These multi-benefits of caffeine in PD are supported by convergence of epidemiological and animal evidence. At least six large prospective epidemiological studies have firmly established a relationship between increased caffeine consumption and decreased risk of developing PD. In addition, animal studies have also demonstrated that caffeine confers neuroprotection against dopaminergic neurodegeneration using PD models of mitochondrial toxins (MPTP, 6-OHDA, and rotenone) and expression of α-synuclein (α-Syn). While caffeine has complex pharmacological profiles, studies with genetic knockout mice have clearly revealed that caffeine’s action is largely mediated by the brain adenosine A_2A receptor (A_2AR) and confer neuroprotection by modulating neuroinflammation and excitotoxicity and mitochondrial function. Interestingly, recent studies have highlighted emerging new mechanisms including caffeine modulation of α-Syn degradation with enhanced autophagy and caffeine modulation of gut microbiota and gut-brain axis in PD models. Importantly, since the first clinical trial in 2003, United States FDA has finally approved clinical use of the A_2AR antagonist istradefylline for the treatment of PD with OFF-time in Sept. 2019. To realize therapeutic potential of caffeine in PD, genetic study of caffeine and risk genes in human population may identify useful pharmacogenetic markers for predicting individual responses to caffeine in PD clinical trials and thus offer a unique opportunity for “personalized medicine” in PD.

Inflammation and Parkinson's disease pathogenesis: Mechanisms and therapeutic insight

After Alzheimer's disease, Parkinson's disease is the most frequent neurodegenerative disorder. Although numerous treatments have been developed to control the disease symptomatology, with some successes, an efficacious therapy affecting the causes of PD is still a goal to pursue. The genetic evidence and the identification of α-synuclein as the main component of intracellular Lewy bodies, the neuropathological hallmark of PD and related disorders, have changed the approach to these disorders. More recently, the detrimental role of α-synuclein has been further extended to explain the wide spread of cerebral pathology through its oligomers. To emphasize the central pathogenic role of these soluble aggregates, we have defined synucleinopathies and other neurodegenerative disorders associated with protein misfolding as oligomeropathies. Another common element in the pathogenesis of oligomeropathies is the role played by inflammation, both at the peripheral and cerebral levels. In the brain parenchyma, inflammatory reaction has been considered an obvious consequence of neuronal degeneration, but recent observations indicate a direct contribution of glial alteration in the early phase of the disease. Furthermore, systemic inflammation also influences the development of neuronal dysfunction caused by specific elements, β amyloid, α-synuclein, tau or prion. However, each disorder has its own specific pathological process and within the same pathological condition, it is possible to find inter-individual differences. This heterogeneity might explain the difficulties developing efficacious therapeutic approaches, even though the possibility of intervention is supported by robust biological evidence. We have recently demonstrated that peripheral inflammation can amplify the neuronal dysfunction induced by α-synuclein oligomers and the neuropathological consequences observed in a Parkinson's disease model. In both cases, activation of microglia was incremented by the "double hit" process, compared to the single treatment. In contrast, astrocyte activation was attenuated and these cells appeared damaged when chronic inflammation was combined with α-synuclein exposure. This evidence might indicate a more specific anti-inflammatory strategy rather than the generic anti-inflammatory treatment.

Genetics of Parkinson's disease

Less than a quarter century after the discovery of SNCA as the first attributable gene in Parkinson's disease (PD), our knowledge of the genetic architecture underlying this disease has improved by leaps and bounds. About 5-10% of all patients suffer from a monogenic form of PD where mutations in autosomal-dominant (AD) genes-SNCA, LRRK2, and VPS35 and autosomal recessive (AR) genes-PINK1, DJ-1, and Parkin cause the disease. Whole-exome sequencing has described AR DNAJC6 mutations not only in predominantly atypical, but also in patients with typical PD. Majority of PD is genetically complex, caused by the combination of common genetic variants in concert with environmental factors. Genome-wide association studies have identified twenty six PD risk loci till date; however, these show only moderate effects on the risk for PD. The validation of novel genes and its association with PD remains extremely challenging as families harboring rare genetic variants are sparse and globally widespread. This review article aims to provide a comprehensive overview on PD genetics.

Network Protein Interaction in Parkinson's Disease and Periodontitis Interplay: A Preliminary Bioinformatic Analysis

Recent studies supported a clinical association between Parkinson's disease (PD) and periodontitis. Hence, investigating possible interactions between proteins associated to these two conditions is of interest. In this study, we conducted a protein-protein network interaction analysis with recognized genes encoding proteins with variants strongly associated with PD and periodontitis. Genes of interest were collected via the Genome-Wide Association Studies (GWAS) database. Then, we conducted a protein interaction analysis, using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, with a highest confidence cutoff of 0.9 and sensitivity analysis with confidence cutoff of 0.7. Our protein network casts a comprehensive analysis of potential protein-protein interactions between PD and periodontitis. This analysis may underpin valuable information for new candidate molecular mechanisms between PD and periodontitis and may serve new potential targets for research purposes. These results should be carefully interpreted, giving the limitations of this approach.

Parkinson's disease determinants, prediction and gene-environment interactions in the UK Biobank

OBJECTIVE

To systematically investigate the association of environmental risk factors and prodromal features with incident Parkinson's disease (PD) diagnosis and the interaction of genetic risk with these factors. To evaluate whether existing risk prediction algorithms are improved by the inclusion of genetic risk scores.

METHODS

We identified individuals with an incident diagnosis of PD (n=1276) and controls (n=500 406) in UK Biobank. We determined the association of risk factors with incident PD using adjusted logistic regression models. We constructed polygenic risk scores (PRSs) using external weights and selected the best PRS from a subset of the cohort (30%). The PRS was used in a separate testing set (70%) to examine gene-environment interactions and compare predictive models for PD.

RESULTS

Strong evidence of association (false discovery rate <0.05) was found between PD and a positive family history of PD, a positive family history of dementia, non-smoking, low alcohol consumption, depression, daytime somnolence, epilepsy and earlier menarche. Individuals with the highest 10% of PRSs had increased risk of PD (OR 3.37, 95% CI 2.41 to 4.70) compared with the lowest risk decile. A higher PRS was associated with earlier age at PD diagnosis and inclusion of the PRS in the PREDICT-PD algorithm led to a modest improvement in model performance. We found evidence of an interaction between the PRS and diabetes.

INTERPRETATION

Here, we used UK Biobank data to reproduce several well-known associations with PD, to demonstrate the validity of a PRS and to demonstrate a novel gene-environment interaction, whereby the effect of diabetes on PD risk appears to depend on background genetic risk for PD.

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.

Integrated Microarray and RNAseq Transcriptomic Analysis of Retinal Pigment Epithelium/Choroid in Age-Related Macular Degeneration

We report for the first time an integrated transcriptomic analysis of RPE/choroid dysfunction in AMD (mixed stages) based on combining data from publicly available microarray (GSE29801) and RNAseq (GSE135092) datasets aimed at increasing the ability and power of detection of differentially expressed genes and AMD-associated pathways. The analysis approach employed an integrating quantitative method designed to eliminate bias among different transcriptomic studies. The analysis highlighted 764 meta-genes (366 downregulated and 398 upregulated) in macular AMD RPE/choroid and 445 meta-genes (244 downregulated and 201 upregulated) in non-macular AMD RPE/choroid. Of these, 731 genes were newly detected as differentially expressed (DE) genes in macular AMD RPE/choroid and 434 genes in non-macular AMD RPE/choroid compared with controls. Over-representation analysis of KEGG pathways associated with these DE genes mapped revealed two most significantly associated biological processes in macular RPE/choroid in AMD, namely the neuroactive ligand-receptor interaction pathway (represented by 30 DE genes) and the extracellular matrix-receptor interaction signaling pathway (represented by 12 DE genes). Furthermore, protein-protein interaction (PPI) network identified two central hub genes involved in the control of cell proliferation/differentiation processes, HDAC1 and CDK1. Overall, the analysis provided novel insights for broadening the exploration of AMD pathogenesis by extending the number of molecular determinants and functional pathways that underpin AMD-associated RPE/choroid dysfunction.

Characterizing dysbiosis of gut microbiome in PD: evidence for overabundance of opportunistic pathogens

In Parkinson's disease (PD), gastrointestinal features are common and often precede the motor signs. Braak and colleagues proposed that PD may start in the gut, triggered by a pathogen, and spread to the brain. Numerous studies have examined the gut microbiome in PD; all found it to be altered, but found inconsistent results on associated microorganisms. Studies to date have been small (N = 20 to 306) and are difficult to compare or combine due to varied methodology. We conducted a microbiome-wide association study (MWAS) with two large datasets for internal replication (N = 333 and 507). We used uniform methodology when possible, interrogated confounders, and applied two statistical tests for concordance, followed by correlation network analysis to infer interactions. Fifteen genera were associated with PD at a microbiome-wide significance level, in both datasets, with both methods, with or without covariate adjustment. The associations were not independent, rather they represented three clusters of co-occurring microorganisms. Cluster 1 was composed of opportunistic pathogens and all were elevated in PD. Cluster 2 was short-chain fatty acid (SCFA)-producing bacteria and all were reduced in PD. Cluster 3 was carbohydrate-metabolizing probiotics and were elevated in PD. Depletion of anti-inflammatory SCFA-producing bacteria and elevated levels of probiotics are confirmatory. Overabundance of opportunistic pathogens is an original finding and their identity provides a lead to experimentally test their role in PD.

Synergistic Neuroprotective Effect of Endogenously-Produced Hydroxytyrosol and Synaptic Vesicle Proteins on Pheochromocytoma Cell Line Against Salsolinol

Oxidative stress triggers a lethal cascade, leading to Parkinson's disease by causing degeneration of dopaminergic neurons. In this study, eight antioxidants were screened for their neuroprotective effect on PC12 cells (pheochromocytoma cell line) under oxidative stress induced by salsolinol (OSibS). Hydroxytyrosol was found to be the strongest neuroprotective agent; it improved viability of PC12 cells by up to 81.69% under OSibS. Afterward, two synaptic vesicle proteins, synapsin-1 and septin-5, were screened for their neuroprotective role; the overexpression of synapsin-1 and the downregulation of septin-5 separately improved the viability of PC12 cells by up to 71.17% and 67.00%, respectively, compared to PC12 cells only treated with salsolinol (PoTwS) under OSibS. Subsequently, the PC12+syn++sep- cell line was constructed and pretreated with 100 µM hydroxytyrosol, which improved its cell viability by up to 99.03% and led to 14.71- and 6.37-fold reductions in the levels of MDA and H2O2, respectively, and 6.8-, 12.97-, 10.57-, and 7.57-fold increases in the activity of catalase, glutathione reductase, superoxide dismutase, and glutathione peroxidase, respectively, compared to PoTwS under OSibS. Finally, alcohol dehydrogenase-6 from Saccharomyces cerevisiae was expressed in PC12+syn++sep- cells to convert 3,4-dihydroxyphenylacetaldehyde (an endogenous neurotoxin) into hydroxytyrosol. The PC12+syn++sep-+ADH6+ cell line also led to 22.38- and 12.33-fold decreases in the production of MDA and H2O2, respectively, and 7.15-, 13.93-, 12.08-, and 8.11-fold improvements in the activity of catalase, glutathione reductase, superoxide dismutase, and glutathione peroxidase, respectively, compared to PoTwS under OSibS. Herein, we report the endogenous production of a powerful antioxidant, hydroxytyrosol, from 3,4-dihydroxyphenylacetaldehyde, and evaluate its synergistic neuroprotective effect, along with synapsin-1 and septin-5, on PC12 cells under OSibS.

The belated US FDA approval of the adenosine A2A receptor antagonist istradefylline for treatment of Parkinson's disease

After more than two decades of preclinical and clinical studies, on August 27, 2019, the US Food and Drug Administration (FDA) approved the adenosine A_2A receptor antagonist Nourianz® (istradefylline) developed by Kyowa Hakko Kirin Inc., Japan, as an add-on treatment to levodopa in Parkinson's disease (PD) with "OFF" episodes. This milestone achievement is the culmination of the decade-long clinical studies of the effects of istradefylline in more than 4000 PD patients. Istradefylline is the first non-dopaminergic drug approved by FDA for PD in the last two decades. This approval also provides some important lessons to be remembered, namely, concerning disease-specific adenosine signaling and targeting subpopulation of PD patients. Importantly, this approval paves the way to foster entirely novel therapeutic opportunities for adenosine A_2A receptor antagonists, such as neuroprotection or reversal of mood and cognitive deficits in PD and other neuropsychiatric diseases.

Association Between Parkinson's Disease and Melanoma: Putting the Pieces Together

Patients with Parkinson’s disease (PD) generally have reduced risk of developing many types of cancers, except melanoma—a malignant tumor of melanin-producing cells in the skin. For decades, a large number of epidemiological studies have reported that the occurrence of melanoma is higher than expected among subjects with PD, and the occurrence of PD is reciprocally higher than expected among patients with melanoma. More recent epidemiological studies further indicated a bidirectional association, not only in the patients themselves but also in their relatives. This association between PD and melanoma offers a unique opportunity to understand PD. Here, we summarize epidemiological, clinical, and biological evidence in regard to shared risk factors and possible underlying mechanisms for these two seemingly distinct conditions.

WITHDRAWN: Genetics of Parkinson's disease

The Publisher regrets that this article is an accidental duplication of an article that has already been published, DOI of original article: https://doi.org/10.1016/j.mcp.2016.11.001. The duplicate article has therefore been withdrawn. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal.

Chemical composition and health properties of coffee and coffee by-products

Coffee can be an ally in the fight against diseases such as type 2 diabetes, cancer, hepatic injury, cirrhosis, depression, suicidal behavior, and neurological and cardiovascular disorders. The properties of coffee also favor gastrointestinal tract and gut microbiota establishment. Coffee bioactive components include phenolic compounds (chlorogenic acids, cafestol and kahweol), alkaloids (caffeine and trigonelin), diterpenes (cafestol and kahweol) and other secondary metabolites. The image of coffee as a super functional food has helped to increase coffee consumption across the globe. This chapter addresses the main health promotion mechanisms associated with coffee consumption. Related topics on coffee production chain, world consumption and reuse of coffee by-products in the production of high-value-adding molecules with potential applications in the food industry are addressed and discussed.

Living With Parkinson's: The Process of Finding Optimism

Individuals with Parkinson's disease (PD) often experience poor mental and emotional well-being, which negatively affect their quality of life. Optimism is a protective factor which has been shown to promote resiliency, reduce distress in health crises, and protect against the effects of negative mental health outcomes. The current article utilized grounded theory methodology to examine personal accounts (N = 85) detailing how individuals were able to cultivate optimism despite challenges presented by PD. The grounded theory indicated that a process occurs in which individuals with PD move through the following five phases on their journey toward optimism: (a) diagnosis, (b) initial reactions, (c) adjustment, (d) acceptance, and (e) living with optimism. These findings indicate that individuals with PD often struggle to experience optimism. Nevertheless, by reframing optimism as a choice rather than a feeling, participants were able to make decisions that allowed them to progress on their journey toward optimism.

Gene-environment interaction and Mendelian randomisation

Genetic factors only account for up to a third of the cases of Parkinson's disease (PD), while the remaining cases are of unknown aetiology. Environmental exposures (such as pesticides or heavy metals) and the interaction with genetic susceptibility factors (summarized in the concept of impaired xenobiotic metabolism) are believed to play a major role in the mechanisms of neurodegeneration. Beside of the classical association studies (e.g. genome-wide association studies), a novel approach to investigate environmental risk factors are Mendelian randomisation studies. This review explores the gene-environment interaction and the gain of Mendelian randomisation studies in assessing causalities of modifiable risk factors for PD.

Glutamate ionotropic receptor NMDA type subunit 2A (GRIN2A) gene polymorphism (rs4998386) and Parkinson's disease susceptibility: A meta-analysis

OBJECTIVE

Dopaminergic neuronal degeneration seen in Parkinson's disease (PD) might result from a single nucleotide polymorphism (SNP) in the glutamate ionotropic receptor NMDA type subunit 2A (GRIN2A) gene. We thus performed a meta-analysis exploring the relationship between the rs4998386 SNP of the GRIN2A gene and PD susceptibility.

METHODS

We searched PubMed, EMBASE, Web of Science, Google Scholar, and China National Knowledge Infrastructure for studies published between January 2005 and January 2019. The association between the rs4998386 polymorphism and PD susceptibility was evaluated by calculating the pooled odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

Meta-analysis results did not show a significant association between the rs4998386 polymorphism of the GRIN2A gene and PD susceptibility when assuming an allelic model (OR, 0.90; 95% CI, 0.76-1.07; P = .22; I 2 = 53%), a dominant model (OR, 0.96; 95% CI, 0.82-1.12; P = .62; I 2 = 64%), or a recessive model (OR, 1.14; 95% CI, 0.93-1.38; P = .22; I 2 = 0%).

CONCLUSION

Our meta-analysis found that the rs4998386 polymorphism of the GRIN2A gene is not associated with risk of PD in either Europeans or white Americans. However, large sample studies with different ethnicities should be conducted to establish the role of the rs4998386 polymorphism in PD pathophysiology.

Gene-by-environment interactions in Alzheimer's disease and Parkinson's disease

Diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD) arise from complex interactions of genetic and environmental factors, with genetic variants regulating individual responses to environmental exposures (i.e. gene-by-environment interactions). Identifying gene-by-environment interactions will be critical to fully understanding disease mechanisms and developing personalized therapeutics, though these interactions are still poorly understood and largely under-studied. Candidate gene approaches have shown that known disease risk variants often regulate response to environmental factors. However, recent improvements in exposome- and genome-wide association and interaction studies in humans and mice are enabling discovery of novel genetic variants and pathways that predict response to a variety of environmental factors. Here, we highlight recent approaches and ongoing developments in human and rodent studies to identify genetic modulators of environmental factors using AD and PD as exemplars. Identifying gene-by-environment interactions in disease will be critical to developing personalized intervention strategies and will pave the way for precision medicine.