The Genetic Architecture of Parkinson Disease in Spain: Characterizing Population-Specific Risk, Differential Haplotype Structures, and Providing Etiologic Insight

Exploring the dynamic pathogenesis of Parkinson's disease by case-control and longitudinal blood transcriptome analyses

The pathogenesis of Parkinson's disease (PD) was recently hypothesized to change along with the disease course. Given the fact that transcriptional changes in blood can provide insightful clues for PD pathogenesis, we performed case-control and longitudinal whole blood transcriptome analyses to identify the signature genes underlying the hypothesized dynamic pathogenesis of PD. In the case-control study, we compared the gene expression patterns in healthy control (N = 189), prodromal (N = 58) and de novo idiopathic PD subjects (N = 390). The results showed that the prodromal subjects were at the tipping-point stage, which is characterized by the abnormal expression patterns of 414 genes associated with oxygen transport and reactive oxygen species metabolic process. We next performed a longitudinal transcriptome analysis on 255 PD patients from the baseline to the third year, and identified 203 genes related to immune and inflammatory responses during disease progression. These findings not just offer deeper insights into the dynamic pathogenesis of PD, but also help to find potential drugs to prevent the early neurodegeneration process.

Sex differences in the diagnosis latency of Parkinson's disease in Latin America

BACKGROUND

Age and sex are known risk factors for Parkinson's Disease (PD), but it remains controversial if there are sex differences in the diagnosis latency. The objective of this study was to examine these sex differences in Latin America.

METHODS

The Latin American Research Consortium on the Genetics of PD (LARGE-PD) includes PD patients from countries across Latin America who were diagnosed using the UK Brain Bank criteria. Ages at onset (AAO; N = 2,792), diagnosis (AAD; N = 1,416), and calculated diagnosis latency (N = 1,416) were extracted from the LARGE-PD database and compared for both males and females overall, by country, and decade-long age ranges. A cohort was created based on available data for motor sign at onset (N = 492). Regressions examining diagnosis latency as a factor of sex, country, and motor subtype were performed. Two-tailed t-tests at 95 % confidence intervals were used to identify differences in mean AAOs, AADs, and diagnosis latencies between the sexes.

RESULTS

Across the LARGE-PD cohort, lower AAD was observed in males. Per country, AAO was lower for males in Mexico and diagnosis latency was shorter for males in Chile. Overall, younger females (≤39) and older males (≥70) are likely to experience longer latencies.

CONCLUSIONS

Our results suggest that there may be country and age dependent sex differences in AAO, AAD, and diagnosis latency of PD in Latin America. Interestingly, the mean AAO of LARGE-PD is approximately 6 years younger than studies done with European populations. Analyses with additional data are needed to determine the influence of other factors.

Integrated genetic analysis and single cell-RNA sequencing for brain image-derived phenotypes and Parkinson's disease

BACKGROUND

Previous studies have reported Parkinson's disease (PD) patients usually have changes in brain image-derived phenotypes (IDPs). However, the role of genetic factors in their association and biological mechanism remains unclear. We aimed to unveil genetic and biological links between brain IDPs and PD.

METHODS

Using genome-wide association study (GWAS) summary statistics and single-cell RNA sequencing (scRNA-seq) data, we performed a comprehensive analysis between 624 brain IDPs and PD. The genetic correlations and causality were examined by linkage disequilibrium score regression (LDSC), two-sample bidirectional Mendelian randomization (MR) and meta-analysis. Potential shared genes were identified using MAGMA and PLACO. Finally, pathway enrichment using FUMA and Metascape, and scRNA-seq analysis were performed to determine biological mechanisms and gene expression atlas across various cell types in brain tissue.

RESULTS

LDSC revealed that 50 brain IDPs were genetically correlated with PD (P < 0.05), in which 5 IDPs, exhibited putative causality on PD through MR (P < 0.05). For instance, we identified that the increased volume of the right thalamus (IVW: OR = 2.08, 95 % CI: 1.33 to 3.25, PFDR = 0.03) was positively correlated with the risk of PD, which was also supported by replicated MR (IVW: OR = 1.63, 95 % CI: 1.17-2.26, PFDR = 0.02) in FinnGen and meta-analysis (OR = 1.78, 95 % CI: 1.36-2.31, PFDR = 5.00 × 10-4). Additionally, we identified 56 unique pleiotropic genes, such as FAM13A, with notable enrichment in neuronal cells. Biological mechanism analysis revealed these genes were enriched in brain tissues and a variety of pathways such as negative regulation of neuron apoptotic processes.

CONCLUSION

We indicated the shared genetic architecture and biological mechanisms between brain IDPs and PD. These findings might provide insights on the therapeutic intervention and early prediction of PD at the brain imaging level.

The Exon-Based Transcriptomic Analysis of Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative disease with a complicated pathophysiology and diagnostics. Blood-based whole transcriptome analysis of the longitudinal PPMI cohort was performed with a focus on the change in the expression of exons to find potential RNA-based biomarkers. At the moment of diagnosis, the expression of exons was very similar in both control and PD patients. The exon-based analysis identified 27 differentially expressed exons in PD patients three years after the diagnosis compared to the health controls. Moreover, thirteen exons were differentially expressed during the three-year progression of the PD. At the same time, control subjects had only minimal changes that can mostly be attributed to being related to aging. Differentially regulated exons we identified in the PD cohort were mostly related to different aspects of the pathophysiology of PD, such as an innate immune response or lysosomal activity. We also observed a decline in the expression of the OPN1MW3 gene that is related to colour vision, which suggests that colour vision analysis could be a practical biomarker to monitor the progression of PD.

Glutathione S-transferase polymorphisms (GSTM1/GSTT1) outcomes in clinical profile and treatment responsiveness among Tunisian cohort of Parkinson's disease

Glutathione S-transferases are involved in the oxidative stress which contributes to the pathogenesis of Parkinson's disease (PD). our aim was to investigate the influence of GSTM1 and GSTT1 polymorphisms on the clinical features and treatments outcomes among PD Tunisian patients. We included 300-PD patients followed in neurology department at Razi-University-hospital. GSTM1 and GSTT1 were screened using PCR methods. Correlation between the clinical phenotype and the genotypes was then assessed after adequate parameters adjustment. Individuals carrying inactive GSTT1/GSTM1 were estimated to have 2.5-fold higher risk of developing PD, p = 0.035. The demographic and clinical baseline analysis of GSTM1 polymorphism revealed significant association between the inactive gene and development of tremor as first symptoms (p = 0.046), further, it was correlated to asymmetric start (p = 0.044). The evaluation of the impact of GSTM1/GSTT1 activity among PD at last follow-up revealed the significant variability of motor impairment among cases carrier of the active genes (p = 0.048). As patients with inactive GSTM1/GSTT1 had higher UPDRS-III score. Additionally, higher frequency of cases with good treatment responsiveness was reported among PD with active GSTM1/GSTT1 (p = 0.038).No motor complications were observed among PD by considering the GSTs genotypes (p > 0.05). Finally, we noted significant impairment of memory among cases with inactivate GSTs (p = 0.04), attention deficit (p = 0.013) and impaired judgement (p = 0.0031). This study represents one of the most comprehensive and extensive investigation to date regarding the influence of GSTT1/GSTM1 genotype among PD patients.We speculate that the impact of GSTT1/GSTM1 on PD progression may occur through a cumulative effect, potentially not manifesting during the initial PD stages. Further studies are necessary to validate our conclusions.

Understanding Parkinson disease in Spain: Genetic and clinical insights

BACKGROUND AND PURPOSE

Parkinson disease (PD) is a complex and heterogeneous neurodegenerative disorder with a broad spectrum of clinical manifestations, determined by a complex interplay of environmental and genetic factors. This study aimed to investigate genetic variants associated with PD and assess their impact on the disease phenotype through genotype-phenotype correlations.

METHODS

We employed a targeted resequencing panel to analyze 27 genes linked to PD in a cohort of 1185 PD patients from southern Spain. Variants were categorized based on the American College of Medical Genetics and Genomics pathogenicity criteria. Demographic and clinical data were also collected.

RESULTS

Among the patients analyzed, 13.5% carried potential disease-causing pathogenic or likely pathogenic variants in 12 different genes, indicating significant genetic heterogeneity. The most frequently affected genes were LRRK2, PRKN, and GBA1 (accounting for 72.1% of positive cases). Sex-specific differences were observed, with a higher proportion of female patients carrying LRRK2 variants. Differences in age at onset and clinical features were also observed among the different mutated genes. Notably, variants in genes associated with atypical parkinsonism presented distinct clinical presentations, highlighting the importance of genetic factors in the differential diagnosis.

CONCLUSIONS

Our study provides valuable information on the genetic landscape of PD and its clinical manifestations. The observed genotype-phenotype correlations, along with sex-specific differences, emphasize the complexity of PD pathogenesis, underlining the importance of personalized approaches to PD diagnosis and treatment. Further investigations into genetic interactions and population-specific effects are warranted to enhance our understanding of PD etiology and improve patient care.

Genetic-based diagnostics of Parkinson's disease and other Parkinsonian syndromes

INTRODUCTION

Parkinson's disease (PD) is a complex disorder with vast clinical heterogeneity. Recent genetic, imaging and clinical evidence suggest that there are multiple subtypes of PD, and perhaps even distinct clinical entities, which are being diagnosed under the umbrella of PD. These might have similar clinical presentation, but potentially different underlying mechanisms, which, in future, will require different treatments. Despite extensive genetic research progress, genetic testing is still not a common practice in clinical patient care.

AREAS COVERED

This review examines the numerous genes that have been discovered to affect the risk of, or cause, PD. We also outline genetic variants that affect PD age at onset, its progression, and the presence or severity of motor and non-motor symptoms. We differentiate between PD, other synucleinopathies, and atypical parkinsonism syndromes, and describe genes responsible for familial forms of typical PD and atypical parkinsonism. Lastly, we present current clinical trails that are underway for targeted therapies, particularly for GBA1-PD and LRRK2-PD which are the most significant subtypes.

EXPERT OPINION

While genetic studies alone cannot be diagnostic for PD, proper utilization of genetic screening for PD could improve diagnostic accuracy and predictions for prognosis, guide treatment, and identify individuals that qualify for clinical trials.

Factors Affecting Treatment Persistence in Japanese Patients with Psoriasis Prescribed Biologics: A Real-World Study Using an Insurance Claim Database

INTRODUCTION

Poor persistence to biologics can result in suboptimal health outcomes and increased economic burden for chronic conditions, including psoriasis (PsO). In Japan, studies evaluating factors responsible for biologic treatment persistence in patients with PsO are limited. We assessed biologic treatment persistence (median treatment duration and overall treatment survival) and associated factors in patients with PsO in a real-world setting.

METHODS

This retrospective analysis of insurance claims records from the Japan Medical Data Center (JMDC) database included patients with PsO [International Classification of Diseases (ICD) code: L40.x] ≥ 18 years of age who had received biologic treatment. Treatment persistence was analyzed using data from 2016 to 2020 by biologic class and by individual biologics (infliximab, adalimumab, ustekinumab, guselkumab, secukinumab, ixekizumab, and brodalumab) in bio-naïve (who initiate first biologic at index) and bio-experienced patients. Kaplan-Meier survival (treatment persistence), and multivariate Cox proportional hazard regression (predictive factors) analyses were used.

RESULTS

Overall, 1528 patients with PsO were included (mean age 47.4 years). Infliximab had the longest median treatment duration (33.6 months), while brodalumab had the shortest (9.7 months) among biologics evaluated. Of the biologics evaluated, 1-year treatment survival was highest with guselkumab (83%), and lowest with brodalumab (45%). Bio-experienced patients showed slightly longer median treatment duration than bio-naïve patients (22.8 versus 18.1 months). Factors predictive of treatment persistence were sex [male; hazard ratio (HR) 0.84, p = 0.016] and specific PsO diagnostic codes, such as L40.0 (PsO vulgaris; HR 0.69; p = 0.006), L40.1 (generalized pustular PsO; HR 0.75; p = 0.034), and L40.9 (PsO unspecified; HR 0.72; p = 0.001). Meanwhile, age and Charlson Comorbidity Index score were significantly associated with adalimumab and infliximab treatment persistence, respectively.

CONCLUSION

Among biologics evaluated, infliximab had the longest median treatment duration, and guselkumab had the highest 1-year treatment survival. Sex and specific PsO diagnostic codes influenced overall treatment persistence. These findings could inform long-term treatment plans for PsO in real-world clinical settings.

Chemical Characterization and Beneficial Effects of Walnut Oil on a Drosophila melanogaster Model of Parkinson's Disease

A nutritional approach could be a promising strategy to prevent or decrease the progression of neurodegenerative disorders such as Parkinson's disease (PD). The neuroprotective role of walnut oil (WO) was investigated in Drosophila melanogaster treated with rotenone (Rot), as a PD model, WO, or their combination, and compared to controls. WO reduced mortality and improved locomotor activity impairment after 3 and 7 days, induced by Rot. LC-MS analyses of fatty acid levels in Drosophila heads showed a significant increase in linolenic (ALA) and linoleic acid (LA) both in flies fed with the WO-enriched diet and in those treated with the association of WO with Rot. Flies supplemented with the WO diet showed an increase in brain dopamine (DA) level, while Rot treatment significantly depleted dopamine content; conversely, the association of Rot with WO did not modify DA content compared to controls. The greater intake of ALA and LA in the enriched diet enhanced their levels in Drosophila brain, suggesting a neuroprotective role of polyunsaturated fatty acids against Rot-induced neurotoxicity. The involvement of the dopaminergic system in the improvement of behavioral and biochemical parameters in Drosophila fed with WO is also suggested.

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.

A Genome-Wide Interaction Study of Erythrocyte ω-3 Polyunsaturated Fatty Acid Species and Memory in the Framingham Heart Study Offspring Cohort

BACKGROUND

Cognitive decline, and more specifically Alzheimer's disease, continues to increase in prevalence globally, with few, if any, adequate preventative approaches. Several tests of cognition are utilized in the diagnosis of cognitive decline that assess executive function, short- and long-term memory, cognitive flexibility, and speech and motor control. Recent studies have separately investigated the genetic component of both cognitive health, using these measures, and circulating fatty acids.

OBJECTIVES

We aimed to examine the potential moderating effect of main species of ω-3 polyunsaturated fatty acids (PUFAs) on an individual's genetically conferred risk of cognitive decline.

METHODS

The Offspring cohort from the Framingham Heart Study was cross-sectionally analyzed in this genome-wide interaction study (GWIS). Our sample included all individuals with red blood cell ω-3 PUFA, genetic, cognitive testing (via Trail Making Tests [TMTs]), and covariate data (N = 1620). We used linear mixed effects models to predict each of the 3 cognitive measures (TMT A, TMT B, and TMT D) by each ω-3 PUFA, single nucleotide polymorphism (SNP) (0, 1, or 2 minor alleles), ω-3 PUFA by SNP interaction term, and adjusting for sex, age, education, APOE ε4 genotype status, and kinship (relatedness).

RESULTS

Our analysis identified 31 unique SNPs from 24 genes reaching an exploratory significance threshold of 1×10-5. Fourteen of the 24 genes have been previously associated with the brain/cognition, and 5 genes have been previously associated with circulating lipids. Importantly, 8 of the genes we identified, DAB1, SORCS2, SERINC5, OSBPL3, CPA6, DLG2, MUC19, and RGMA, have been associated with both cognition and circulating lipids. We identified 22 unique SNPs for which individuals with the minor alleles benefit substantially from increased ω-3 fatty acid concentrations and 9 unique SNPs for which the common homozygote benefits.

CONCLUSIONS

In this GWIS of ω-3 PUFA species on cognitive outcomes, we identified 8 unique genes with plausible biology suggesting individuals with specific polymorphisms may have greater potential to benefit from increased ω-3 PUFA intake. Additional replication in prospective settings with more diverse samples is needed.

Transcriptomic analysis reveals associations of blood-based A-to-I editing with Parkinson's disease

BACKGROUND

Adenosine-to-inosine (A-to-I) editing is the most common type of RNA editing in humans and the role of A-to-I RNA editing remains unclear in Parkinson's disease (PD).

OBJECTIVE

We aimed to explore the potential causal association between A-to-I editing and PD, and to assess whether changes in A-to-I editing were associated with cognitive progression in PD.

METHODS

The RNA-seq data from 380 PD patients and 178 healthy controls in the Parkinson's Progression Marker Initiative cohort was used to quantify A-to-I editing sites. We performed cis-RNA editing quantitative trait loci analysis and a two-sample Mendelian Randomization (MR) study by integrating genome-wide association studies to infer the potential causality between A-to-I editing and PD pathogenesis. The potential causal A-to-I editing sites were further confirmed by Summary-data-based MR analysis. Spearman's correlation analysis was performed to characterize the association between longitudinal A-to-I editing and cognitive progression in patients with PD.

RESULTS

We identified 17 potential causal A-to-I editing sites for PD and indicated that genetic risk variants may contribute to the risk of PD through A-to-I editing. These A-to-I editing sites were located in genes NCOR1, KANSL1 and BST1. Moreover, we observed 57 sites whose longitudinal A-to-I editing levels correlated with cognitive progression in PD.

CONCLUSIONS

We found potential causal A-to-I editing sites for PD onset and longitudinal changes of A-to-I editing were associated with cognitive progression in PD. We anticipate this study will provide new biological insights and drive the discovery of the epitranscriptomic role underlying Parkinson's disease.

Risk factors associated with age at onset of Parkinson's disease in the UK Biobank

Substantial evidence shown that the age at onset (AAO) of Parkinson's disease (PD) is a major determinant of clinical heterogeneity. However, the mechanisms underlying heterogeneity in the AAO remain unclear. To investigate the risk factors with the AAO of PD, a total of 3156 patients with PD from the UK Biobank were included in this study. We evaluated the effects of polygenic risk scores (PRS), nongenetic risk factors, and their interaction on the AAO using Mann-Whitney U tests and regression analyses. We further identified the genes interacting with nongenetic risk factors for the AAO using genome-wide environment interaction studies. We newly found physical activity (P < 0.0001) was positively associated with AAO and excessive daytime sleepiness (P < 0.0001) was negatively associated with AAO, and reproduced the positive associations of smoking and non-steroidal anti-inflammatory drug intake and the negative association of family history with AAO. In the dose-dependent analyses, smoking duration (P = 1.95 × 10-6), coffee consumption (P = 0.0150), and tea consumption (P = 0.0008) were positively associated with AAO. Individuals with higher PRS had younger AAO (P = 3.91 × 10-5). In addition, we observed a significant interaction between the PRS and smoking for AAO (P = 0.0316). Specifically, several genes, including ANGPT1 (P = 7.17 × 10-7) and PLEKHA6 (P = 4.87 × 10-6), may influence the positive relationship between smoking and AAO. Our data suggests that genetic and nongenetic risk factors are associated with the AAO of PD and that there is an interaction between the two.

Prediction of Parkinson's Disease Using Machine Learning Methods

The detection of Parkinson's disease (PD) in its early stages is of great importance for its treatment and management, but consensus is lacking on what information is necessary and what models should be used to best predict PD risk. In our study, we first grouped PD-associated factors based on their cost and accessibility, and then gradually incorporated them into risk predictions, which were built using eight commonly used machine learning models to allow for comprehensive assessment. Finally, the Shapley Additive Explanations (SHAP) method was used to investigate the contributions of each factor. We found that models built with demographic variables, hospital admission examinations, clinical assessment, and polygenic risk score achieved the best prediction performance, and the inclusion of invasive biomarkers could not further enhance its accuracy. Among the eight machine learning models considered, penalized logistic regression and XGBoost were the most accurate algorithms for assessing PD risk, with penalized logistic regression achieving an area under the curve of 0.94 and a Brier score of 0.08. Olfactory function and polygenic risk scores were the most important predictors for PD risk. Our research has offered a practical framework for PD risk assessment, where necessary information and efficient machine learning tools were highlighted.

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 role of inflammaging in aortic aneurysm: new insights from bioinformatics analysis

Introduction

Aortic aneurysms (AA) are prevalent worldwide with a notable absence of drug therapies. Thus, identifying potential drug targets is of utmost importance. AA often presents in the elderly, coupled with consistently raised serum inflammatory markers. Given that ageing and inflammation are pivotal processes linked to the evolution of AA, we have identified key genes involved in the inflammaging process of AA development through various bioinformatics methods, thereby providing potential molecular targets for further investigation.

Methods

The transcriptome data of AA was procured from the datasets GSE140947, GSE7084, and GSE47472, sourced from the NCBI GEO database, whilst gene data of ageing and inflammation were obtained from the GeneCards Database. To identify key genes, differentially expressed analysis using the "Limma" package and WGCNA were implemented. Protein-protein intersection (PPI) analysis and machine learning (ML) algorithms were employed for the screening of potential biomarkers, followed by an assessment of the diagnostic value. Following the acquisition of the hub inflammaging and AA-related differentially expressed genes (IADEGs), the TFs-mRNAs-miRNAs regulatory network was established. The CIBERSORT algorithm was utilized to investigate immune cell infiltration in AA. The correlation of hub IADEGs with infiltrating immunocytes was also evaluated. Lastly, wet laboratory experiments were carried out to confirm the expression of hub IADEGs.

Results

342 and 715 AA-related DEGs (ADEGs) recognized from GSE140947 and GSE7084 datasets were procured by intersecting the results of "Limma" and WGCNA analyses. After 83 IADEGs were obtained, PPI analysis and ML algorithms pinpointed 7 and 5 hub IADEGs candidates respectively, and 6 of them demonstrated a high diagnostic value. Immune cell infiltration outcomes unveiled immune dysregulation in AA. In the wet laboratory experiments, 3 hub IADEGs, including BLNK, HLA-DRA, and HLA-DQB1, finally exhibited an expression trend in line with the bioinformatics analysis result.

Discussion

Our research identified three genes - BLNK, HLA-DRA, and HLA-DQB1- that play a significant role in promoting the development of AA through inflammaging, providing novel insights into the future understanding and therapeutic intervention of AA.

Cumulative Genetic Score and C9orf72 Repeat Status Independently Contribute to Amyotrophic Lateral Sclerosis Risk in 2 Case-Control Studies

BACKGROUND AND OBJECTIVES

Most patients with amyotrophic lateral sclerosis (ALS) lack a monogenic mutation. This study evaluates ALS cumulative genetic risk in an independent Michigan and Spanish replication cohort using polygenic scores.

METHODS

Participant samples from University of Michigan were genotyped and assayed for the chromosome 9 open reading frame 72 hexanucleotide expansion. Final cohort size was 219 ALS and 223 healthy controls after genotyping and participant filtering. Polygenic scores excluding the C9 region were generated using an independent ALS genome-wide association study (20,806 cases, 59,804 controls). Adjusted logistic regression and receiver operating characteristic curves evaluated the association and classification between polygenic scores and ALS status, respectively. Population attributable fractions and pathway analyses were conducted. An independent Spanish study sample (548 cases, 2,756 controls) was used for replication.

RESULTS

Polygenic scores constructed from 275 single-nucleotide variation (SNV) had the best model fit in the Michigan cohort. An SD increase in ALS polygenic score associated with 1.28 (95% CI 1.04-1.57) times higher odds of ALS with area under the curve of 0.663 vs a model without the ALS polygenic score (p value = 1 × 10-6). The population attributable fraction of the highest 20th percentile of ALS polygenic scores, relative to the lowest 80th percentile, was 4.1% of ALS cases. Genes annotated to this polygenic score enriched for important ALS pathomechanisms. Meta-analysis with the Spanish study, using a harmonized 132 single nucleotide variation polygenic score, yielded similar logistic regression findings (odds ratio: 1.13, 95% CI 1.04-1.23).

DISCUSSION

ALS polygenic scores can account for cumulative genetic risk in populations and reflect disease-relevant pathways. If further validated, this polygenic score will inform future ALS risk models.

Different pieces of the same puzzle: a multifaceted perspective on the complex biological basis of Parkinson's disease

The biological basis of the neurodegenerative movement disorder, Parkinson's disease (PD), is still unclear despite it being 'discovered' over 200 years ago in Western Medicine. Based on current PD knowledge, there are widely varying theories as to its pathobiology. The aim of this article was to explore some of these different theories by summarizing the viewpoints of laboratory and clinician scientists in the PD field, on the biological basis of the disease. To achieve this aim, we posed this question to thirteen "PD experts" from six continents (for global representation) and collated their personal opinions into this article. The views were varied, ranging from toxin exposure as a PD trigger, to LRRK2 as a potential root cause, to toxic alpha-synuclein being the most important etiological contributor. Notably, there was also growing recognition that the definition of PD as a single disease should be reconsidered, perhaps each with its own unique pathobiology and treatment regimen.

Genetic Architecture of Parkinson's Disease

Year 2022 marks 25 years since the first mutation in familial autosomal dominant Parkinson's disease was identified. Over the years, our understanding of the role of genetic factors in the pathogenesis of familial and idiopathic forms of Parkinson's disease has expanded significantly - a number of genes for the familial form of the disease have been identified, and DNA markers for an increased risk of developing its sporadic form have been found. But, despite all the success achieved, we are far from an accurate assessment of the contribution of genetic and, even more so, epigenetic factors to the disease development. The review summarizes the information accumulated to date on the genetic architecture of Parkinson's disease and formulates issues that need to be addressed, which are primarily related to the assessment of epigenetic factors in the disease pathogenesis.

Mucin (MUC) Family Influence on Acute Lymphoblastic Leukemia in Cancer and Non-Cancer Native American Populations from the Brazilian Amazon

The mucin (MUC) family includes several genes aberrantly expressed in multiple carcinomas and mediates diverse pathways essentials for oncogenesis, in both solid and hematological malignancies. Acute Lymphoblastic Leukemia (ALL) can have its course influenced by genetic variants, and it seems more frequent in the Amerindian population, which has been understudied. Therefore, the present work aimed to investigate the MUC family exome in Amerindian individuals from the Brazilian Amazon, in a sample containing healthy Native Americans (NAMs) and indigenous subjects with ALL, comparing the frequency of polymorphisms between these two groups. The population was composed of 64 Amerindians from the Brazilian Amazon, from 12 different isolated tribes, five of whom were diagnosed with ALL. We analyzed 16 genes from the MUC family and found a total of 1858 variants. We compared the frequency of each variant in the ALL vs. NAM group, which led to 77 variants with a significant difference and, among these, we excluded those with a low impact, resulting in 63 variants, which were distributed in nine genes, concentrated especially in MUC 19 (n = 30) and MUC 3A (n = 18). Finally, 11 new variants were found in the NAM population. This is the first work with a sample of native Americans with cancer, a population which is susceptible to ALL, but remains understudied. The MUC family seems to have an influence on the development of ALL in the Amerindian population and especially MUC19 and MUC3A are shown as possible hotspots. In addition, the 11 new variants found point to the need to have their clinical impact analyzed.

The influence of 17q21.31 and APOE genetic ancestry on neurodegenerative disease risk

Advances in genomic research over the last two decades have greatly enhanced our knowledge concerning the genetic landscape and pathophysiological processes involved in multiple neurodegenerative diseases. However, current insights arise almost exclusively from studies on individuals of European ancestry. Despite this, studies have revealed that genetic variation differentially impacts risk for, and clinical presentation of neurodegenerative disease in non-European populations, conveying the importance of ancestry in predicting disease risk and understanding the biological mechanisms contributing to neurodegeneration. We review the genetic influence of two important disease-associated loci, 17q21.31 (the "MAPT locus") and APOE, to neurodegenerative disease risk in non-European populations, touching on global population differences and evolutionary genetics by ancestry that may underlie some of these differences. We conclude there is a need to increase representation of non-European ancestry individuals in genome-wide association studies (GWAS) and biomarker analyses in order to help resolve existing disparities in understanding risk for, diagnosis of, and treatment for neurodegenerative diseases in diverse populations.

Genetics in parkinson's disease: From better disease understanding to machine learning based precision medicine

Parkinson's Disease (PD) is a neurodegenerative disorder with highly heterogeneous phenotypes. Accordingly, it has been challenging to robustly identify genetic factors associated with disease risk, prognosis and therapy response via genome-wide association studies (GWAS). In this review we first provide an overview of existing statistical methods to detect associations between genetic variants and the disease phenotypes in existing PD GWAS. Secondly, we discuss the potential of machine learning approaches to better quantify disease phenotypes and to move beyond disease understanding towards a better-personalized treatment of the disease.

Review of the epidemiology and variability of LRRK2 non-p.Gly2019Ser pathogenic mutations in Parkinson's disease

Parkinson's disease (PD) is a heterogenous neurodegenerative disorder. Genetic factors play a significant role, especially in early onset and familial cases. Mutations are usually found in the LRRK2 gene, but their importance varies. Some mutations, such as p.Arg1441Cys or other alterations in the 1441 codon, show clear correlation with PD, whereas others are risk factors found also in healthy populations or have neglectable consequences. They also exhibit various prevalence among different populations. The aim of this paper is to sum up the current knowledge regarding the epidemiology and pathogenicity of LRRK2 mutations, other than the well-established p.Gly2019Ser. We performed a review of the literature using PubMed database. 103 publications met our inclusion criteria. p.Arg1441Cys, p.Arg1441Gly, p.Arg1441His, p.Arg1441Ser are the most common pathogenic mutations in European populations, especially Hispanic. p.Asn1437His is pathogenic and occurs mostly in the Scandinavians. p.Asn1437Ser and p.Asn1437Asp have been reported in German and Chinese cohorts respectively. p.Ile2020Thr is a rare pathogenic mutation described only in a Japanese cohort. p.Met1869Thr has only been reported in Caucasians. p.Tyr1699Cys, p.Ile1122Val have only been found in one family each. p.Glu1874Ter has been described in just one patient. We found no references concerning mutation p.Gln416Ter. We also report the first case of a Polish PD family whose members carried p.Asn1437His.

A genetic analysis of Chinese patients with early-onset Parkinson' s disease

Genetic factors play an important role in early-onset Parkinson's disease (EOPD). The genetic spectrum of patients with EOPD varies widely among different ethnicities, with extensive investigations having been performed in Caucasian populations; however, research in Chinese populations remains limited. In this study, we performed multiplex ligation-dependent probe amplification assay and whole-exome sequencing in 15 unrelated Chinese EOPD patients with age of onset before 40 years. Among them, a patient carried compound heterozygous exon duplications in Parkin (exon 3 duplication and exon 4 duplication) (6.67%) and two patients carried the homozygous pathogenic variant (p.D331Y) in PLA2G6 (13.33%). Three novel variants in EIF4G1 (p.P1043S, p.R1505Q, and p.P266A) were identified and classified as uncertain significance. Additionally, a risk variant in GBA (p.L483P) was detected in one patient (6.67%). PLA2G6 (13.33%) was the most common causative gene among our EOPD patients. Furthermore, detailed clinical features were presented. Our results broaden the genetic spectrum and clinical phenotypic spectrum of EOPD patients.

Reassessment of candidate gene studies for idiopathic restless legs syndrome in a large genome-wide association study dataset of European ancestry

STUDY OBJECTIVES

Several candidate gene studies have been published for idiopathic restless legs syndrome (RLS) in populations of European ancestry, but the reported associations have not been confirmed in independent samples. Our aim was to reassess these findings in a large case-control dataset in order to evaluate their validity.

METHODS

We screened PubMed for RLS candidate gene studies. We used the genome-wide association study (GWAS) dataset of the International EU-RLS-GENE Consortium as our replication sample, which provided genome-wide single-variant association data based on at most 17 220 individuals of European ancestry. We performed additional gene-based tests using the software MAGMA and assessed the power of our study using the genpwr R package.

RESULTS

We identified 14 studies conducted in European samples which assessed 45 variants in 27 genes of which 5 variants had been reported as significantly associated. None of these individual variants were replicated in our GWAS-based reassessment (nominal p > 0.05) and gene-based tests for the respective five genes ADH1B, GABRR3, HMOX1, MAOA, and VDR, were also nonsignificant (nominal p > 0.05). Our replication dataset was well powered to detect the reported effects, even when adjusting for effect size overestimation due to winner's curse. Power estimates were close to 100% for all variants.

CONCLUSION

In summary, none of the significant single-variant associations from candidate gene studies were confirmed in our GWAS dataset. Therefore, these associations were likely false positive. Our observations emphasize the need for large sample sizes and stringent significance thresholds in future association studies for RLS.

17q21.31 sub-haplotypes underlying H1-associated risk for Parkinson's disease are associated with LRRC37A/2 expression in astrocytes

BACKGROUND

Parkinson's disease (PD) is genetically associated with the H1 haplotype of the MAPT 17q.21.31 locus, although the causal gene and variants underlying this association have not been identified.

METHODS

To better understand the genetic contribution of this region to PD and to identify novel mechanisms conferring risk for the disease, we fine-mapped the 17q21.31 locus by constructing discrete haplotype blocks from genetic data. We used digital PCR to assess copy number variation associated with PD-associated blocks, and used human brain postmortem RNA-seq data to identify candidate genes that were then further investigated using in vitro models and human brain tissue.

RESULTS

We identified three novel H1 sub-haplotype blocks across the 17q21.31 locus associated with PD risk. Protective sub-haplotypes were associated with increased LRRC37A/2 copy number and expression in human brain tissue. We found that LRRC37A/2 is a membrane-associated protein that plays a role in cellular migration, chemotaxis and astroglial inflammation. In human substantia nigra, LRRC37A/2 was primarily expressed in astrocytes, interacted directly with soluble α-synuclein, and co-localized with Lewy bodies in PD brain tissue.

CONCLUSION

These data indicate that a novel candidate gene, LRRC37A/2, contributes to the association between the 17q21.31 locus and PD via its interaction with α-synuclein and its effects on astrocytic function and inflammatory response. These data are the first to associate the genetic association at the 17q21.31 locus with PD pathology, and highlight the importance of variation at the 17q21.31 locus in the regulation of multiple genes other than MAPT and KANSL1, as well as its relevance to non-neuronal cell types.

Heterozygous PRKN mutations are common but do not increase the risk of Parkinson's disease

PRKN mutations are the most common recessive cause of Parkinson's disease and are a promising target for gene and cell replacement therapies. Identification of biallelic PRKN patients at the population scale, however, remains a challenge, as roughly half are copy number variants and many single nucleotide polymorphisms are of unclear significance. Additionally, the true prevalence and disease risk associated with heterozygous PRKN mutations is unclear, as a comprehensive assessment of PRKN mutations has not been performed at a population scale. To address these challenges, we evaluated PRKN mutations in two cohorts with near complete genotyping of both single nucleotide polymorphisms and copy number variants: the NIH-PD + AMP-PD cohort, the largest Parkinson's disease case-control cohort with whole genome sequencing data from 4094 participants, and the UK Biobank, the largest cohort study with whole exome sequencing and genotyping array data from 200 606 participants. Using the NIH-PD participants, who were genotyped using whole genome sequencing, genotyping array, and multi-plex ligation-dependent probe amplification, we validated genotyping array for the detection of copy number variants. Additionally, in the NIH-PD cohort, functional assays of patient fibroblasts resolved variants of unclear significance in biallelic carriers and suggested that cryptic loss of function variants in monoallelic carriers are not a substantial confounder for association studies. In the UK Biobank, we identified 2692 PRKN copy number variants from genotyping array data from nearly half a million participants (the largest collection to date). Deletions or duplications involving exon 2 accounted for roughly half of all copy number variants and the vast majority (88%) involved exons 2, 3, or 4. In the UK Biobank, we found a pathogenic PRKN mutation in 1.8% of participants and two mutations in ∼1/7800 participants. Those with one PRKN pathogenic variant were as likely as non-carriers to have Parkinson's disease [odds ratio = 0.91 (0.58-1.38), P-value 0.76] or a parent with Parkinson's disease [odds ratio = 1.12 (0.94-1.31), P-value = 0.19]. Similarly, those in the NIH-PD + AMP + PD cohort with one PRKN pathogenic variant were as likely as non-carriers to have Parkinson's disease [odds ratio = 1.29 (0.74-2.38), P-value = 0.43]. Together our results demonstrate that heterozygous pathogenic PRKN mutations are common in the population but do not increase the risk of Parkinson's disease.

The Big Picture of Neurodegeneration: A Meta Study to Extract the Essential Evidence on Neurodegenerative Diseases in a Network-Based Approach

The common features of all neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis (ALS), and Huntington's disease, are the accumulation of aggregated and misfolded proteins and the progressive loss of neurons, leading to cognitive decline and locomotive dysfunction. Still, they differ in their ultimate manifestation, the affected brain region, and the kind of proteinopathy. In the last decades, a vast number of processes have been described as associated with neurodegenerative diseases, making it increasingly harder to keep an overview of the big picture forming from all those data. In this meta-study, we analyzed genomic, transcriptomic, proteomic, and epigenomic data of the aforementioned diseases using the data of 234 studies in a network-based approach to study significant general coherences but also specific processes in individual diseases or omics levels. In the analysis part, we focus on only some of the emerging findings, but trust that the meta-study provided here will be a valuable resource for various other researchers focusing on specific processes or genes contributing to the development of neurodegeneration.

What have we learned from genome-wide association studies (GWAS) in Parkinson's disease?

After fifteen years of genome-wide association studies (GWAS) in Parkinson's disease (PD), what have we learned? Addressing this question will help catalogue the progress made towards elucidating disease mechanisms, improving the clinical utility of the identified loci, and envisioning how we can harness the strides to develop translational GWAS strategies. Here we review the advances of PD GWAS made to date while critically addressing the challenges and opportunities for next-generation GWAS. Thus, deciphering the missing heritability in underrepresented populations is currently at the reach of hand for a truly comprehensive understanding of the genetics of PD across the different ethnicities. Moreover, state-of-the-art GWAS designs hold a true potential for enhancing the clinical applicability of genetic findings, for instance, by improving disease prediction (PD risk and progression). Lastly, advanced PD GWAS findings, alone or in combination with clinical and environmental parameters, are expected to have the capacity for defining patient enriched cohorts stratified by genetic risk profiles and readily available for neuroprotective clinical trials. Overall, envisioning future strategies for advanced GWAS is currently timely and can be instrumental in providing novel genetic readouts essential for a true clinical translatability of PD genetic findings.

Longitudinal intronic RNA-Seq analysis of Parkinson's disease patients reveals disease-specific nascent transcription

Transcriptomic studies usually focus on either gene or exon-based annotations, and only limited experiments have reported changes in reads mapping to introns. The analysis of intronic reads allows the detection of nascent transcription that is not influenced by steady-state RNA levels and provides information on actively transcribed genes. Here, we describe substantial intronic transcriptional changes in Parkinson's disease (PD) patients compared to healthy controls (CO) at two different timepoints; at the time of diagnosis (BL) and three years later (V08). We used blood RNA-Seq data from the Parkinson's Progression Markers Initiative (PPMI) cohort and identified significantly changed transcription of intronic reads only in PD patients during this follow-up period. In CO subjects, only nine transcripts demonstrated differentially expressed introns between visits. However, in PD patients, 4873 transcripts had differentially expressed introns at visit V08 compared to BL, many of them in genes previously associated with neurodegenerative diseases, such as LRRK2, C9orf72, LGALS3, KANSL1AS1, and ALS2. In addition, at the time of diagnosis (BL visit), we identified 836 transcripts (e.g. SNCA, DNAJC19, PRRG4) and at visit V08, 2184 transcripts (e.g. PINK1, GBA, ALS2, PLEKHM1) with differential intronic expression specific to PD patients. In contrast, reads mapping to exonic regions demonstrated little variation indicating highly specific changes only in intronic transcription. Our study demonstrated that PD is characterized by substantial changes in the nascent transcription, and description of these changes could help to understand the molecular pathology underpinning this disease.

SMetABF: A rapid algorithm for Bayesian GWAS meta-analysis with a large number of studies included

Bayesian methods are widely used in the GWAS meta-analysis. But the considerable consumption in both computing time and memory space poses great challenges for large-scale meta-analyses. In this research, we propose an algorithm named SMetABF to rapidly obtain the optimal ABF in the GWAS meta-analysis, where shotgun stochastic search (SSS) is introduced to improve the Bayesian GWAS meta-analysis framework, MetABF. Simulation studies confirm that SMetABF performs well in both speed and accuracy, compared to exhaustive methods and MCMC. SMetABF is applied to real GWAS datasets to find several essential loci related to Parkinson's disease (PD) and the results support the underlying relationship between PD and other autoimmune disorders. Developed as an R package and a web tool, SMetABF will become a useful tool to integrate different studies and identify more variants associated with complex traits.

The Effect of Alzheimer's Disease-Associated Genetic Variants on Longevity

Human longevity is influenced by the genetic risk of age-related diseases. As Alzheimer’s disease (AD) represents a common condition at old age, an interplay between genetic factors affecting AD and longevity is expected. We explored this interplay by studying the prevalence of AD-associated single-nucleotide-polymorphisms (SNPs) in cognitively healthy centenarians, and replicated findings in a parental-longevity GWAS. We found that 28/38 SNPs that increased AD-risk also associated with lower odds of longevity. For each SNP, we express the imbalance between AD- and longevity-risk as an effect-size distribution. Based on these distributions, we grouped the SNPs in three groups: 17 SNPs increased AD-risk more than they decreased longevity-risk, and were enriched for β-amyloid metabolism and immune signaling; 11 variants reported a larger longevity-effect compared to their AD-effect, were enriched for endocytosis/immune-signaling, and were previously associated with other age-related diseases. Unexpectedly, 10 variants associated with an increased risk of AD and higher odds of longevity. Altogether, we show that different AD-associated SNPs have different effects on longevity, including SNPs that may confer general neuro-protective functions against AD and other age-related diseases.

Insights on Genetic and Environmental Factors in Parkinson's Disease from a Regional Swedish Case-Control Cohort

Background:

Risk factors for Parkinson’s disease (PD) can be more or less relevant to a population due to population-specific genetic architecture, local lifestyle habits, and environmental exposures. Therefore, it is essential to study PD at a local, regional, and continental scale in order to increase the knowledge on disease etiology.

Objective:

We aimed to investigate the contribution of genetic and environmental factors to PD in a new Swedish case-control cohort.

Methods:

PD patients (n = 929) and matched population-based controls (n = 935) from the southernmost county in Sweden were included in the cohort. Information on environmental exposures was obtained using questionnaires at inclusion. Genetic analyses included a genome-wide association study (GWAS), haplotype assessment, and a risk profile analysis using cumulative genetic risk scores.

Results:

The cohort is a representative PD case-control cohort (64% men, mean age at diagnosis = 67 years, median Hoehn and Yahr score 2.0), in which previously reported associations between PD and environmental factors, such as tobacco, could be confirmed. We describe the first GWAS of PD solely composed of PD patients from Sweden, and confirm associations to well-established risk alleles in SNCA. In addition, we nominate an unconfirmed and potentially population-specific genome-wide significant association in the PLPP4 locus (rs12771445).

Conclusion:

This work provides an in-depth description of a new PD case-control cohort from southern Sweden, giving insights into environmental and genetic risk factors for PD in the Swedish population.

Axial Impairment Following Deep Brain Stimulation in Parkinson's Disease: A Surgicogenomic Approach

Background:

Postoperative outcome following deep brain stimulation (DBS) of the subthalamic nucleus is variable, particularly with respect to axial motor improvement. We hypothesized a genetic underpinning to the response to surgical intervention, termed “surgicogenomics”.

Objective:

We aimed to identify genetic variants associated with clinical heterogeneity in DBS outcome of Parkinson’s disease (PD) patients that could then be applied clinically to target selection leading to improved surgical outcome.

Methods:

Retrospective clinical data was extracted from 150 patient’s charts. Each individual was genotyped using the genome-wide NeuroX array tailored to study neurologic diseases. Genetic data were clustered based on surgical outcome assessed by comparing pre- and post-operative scores of levodopa equivalent daily dose and axial impairment at one and five years post-surgery. Allele frequencies were compared between patients with excellent vs. moderate/poor outcomes grouped using a priori defined cut-offs. We analyzed common variants, burden of rare coding variants, and PD polygenic risk score.

Results:

NeuroX identified 2,917 polymorphic markers at 113 genes mapped to known PD loci. The gene-burden analyses of 202 rare nonsynonymous variants suggested a nominal association of axial impairment with 14 genes (most consistent with CRHR1, IP6K2, and PRSS3). The strongest association with surgical outcome was detected between a reduction in levodopa equivalent daily dose and common variations tagging two linkage disequilibrium blocks with SH3GL2.

Conclusion:

Once validated in independent populations, our findings may be implemented to improve patient selection for DBS in PD.

Fine mapping of the HLA locus in Parkinson's disease in Europeans

We fine mapped the leukocyte antigen (HLA) region in 13,770 Parkinson’s disease (PD) patients, 20,214 proxy-cases, and 490,861 controls of European origin. Four HLA types were associated with PD after correction for multiple comparisons, HLA-DQA1*03:01, HLA-DQB1*03:02, HLA-DRB1*04:01, and HLA-DRB1*04:04. Haplotype analyses followed by amino acid analysis and conditional analyses suggested that the association is protective and primarily driven by three specific amino acid polymorphisms present in most HLA-DRB1*04 subtypes—11V, 13H, and 33H (OR = 0.87, 95% CI: 0.83–0.90, p < 8.23 × 10⁻⁹ for all three variants). No other effects were present after adjustment for these amino acids. Our results suggest that specific HLA-DRB1 variants are associated with reduced risk of PD, providing additional evidence for the role of the immune system in PD. Although effect size is small and has no diagnostic significance, understanding the mechanism underlying this association may lead to the identification of new targets for therapeutics development.

Tau and MAPT genetics in tauopathies and synucleinopathies

MAPT encodes the microtubule-associated protein tau, which is the main component of neurofibrillary tangles (NFTs) and found in other protein aggregates. These aggregates are among the pathological hallmarks of primary tauopathies such as frontotemporal dementia (FTD). Abnormal tau can also be observed in secondary tauopathies such as Alzheimer's disease (AD) and synucleinopathies such as Parkinson's disease (PD). On top of pathological findings, genetic data also links MAPT to these disorders. MAPT variations are a cause or risk factors for many tauopathies and synucleinopathies and are associated with certain clinical and pathological features in affected individuals. In addition to clinical, pathological, and genetic overlap, evidence also suggests that tau and alpha-synuclein may interact on the molecular level, and thus might collaborate in the neurodegenerative process. Understanding the role of MAPT variations in tauopathies and synucleinopathies is therefore essential to elucidate the role of tau in the pathogenesis and phenotype of those disorders, and ultimately to develop targeted therapies. In this review, we describe the role of MAPT genetic variations in tauopathies and synucleinopathies, several genotype-phenotype and pathological features, and discuss their implications for the classification and treatment of those disorders.

Recalling the pathology of Parkinson's disease; lacking exact figure of prevalence and genetic evidence in Asia with an alarming outcome: A time to step-up

Parkinson's disease (PD) is the second most common and progressive neurodegenerative disease globally, with major symptoms like bradykinesia, impaired posture, and tremor. Several genetic and environmental factors have been identified but elucidating the main factors have been challenging due to the disease's complex nature. Diagnosis, prognosis, and management of such diseases are challenging and require effective targeted attention in developing countries. Recently, PD is growing rapidly in many crowded Asian countries as an alarming threat with inadequate knowledge of its prevalence, genetic architecture, and geographic distribution. This study gave an in-depth overview of the prevalence, incidence and genomic/genetics studies published so far in the Asian population. To the best of our knowledge, PD has increased significantly in several Asian countries, including China, South Korea, Japan, Thailand, and Israel over the past few years, requiring a greater level of care and attention. Genetic screening of families with PD at national levels and establishing an official database of PD cases are essential to get a comprehensive and conclusive view of the exact prevalence and genetic diversity of PD in the Asian population to properly manage and treat the disease.

The Genetics of Parkinson's Disease and Implications for Clinical Practice

The genetic landscape of Parkinson’s disease (PD) is characterised by rare high penetrance pathogenic variants causing familial disease, genetic risk factor variants driving PD risk in a significant minority in PD cases and high frequency, low penetrance variants, which contribute a small increase of the risk of developing sporadic PD. This knowledge has the potential to have a major impact in the clinical care of people with PD. We summarise these genetic influences and discuss the implications for therapeutics and clinical trial design.

Effect of plasma vitamin C levels on Parkinson's disease and age at onset: a Mendelian randomization study

BACKGROUND

Until now, epidemiological evidence regarding the association between vitamin C intake (both diet and supplements) and Parkinson's disease (PD) remains inconsistent. Hence, it is necessary to establish the causal link between vitamin C levels and PD, and further develop effective therapies or prevention.

METHODS

We selected 11 newly identified plasma vitamin C genetic variants from a large-scale plasma vitamin C GWAS dataset (n = 52,018) as the effective instrumental variables, and extracted their corresponding GWAS summary statistics from PD (33,674 PD cases and 449,056 controls) and PD age at onset (AAO) (n = 28,568). We then performed a Mendelian randomization (MR) study to evaluate the causal association of plasma vitamin C levels with PD and PD AAO using inverse-variance weighted (IVW), the weighted median, MR-Egger, and MR-PRESSO test.

RESULTS

We did not observe any significant association between genetically increased vitamin C levels and PD. Interestingly, we found a reduced trend of PD AAO (1.134 years) with 1 SD genetically increased vitamin C levels using IVW (beta = - 1.134, 95% CI: [- 2.515, 0.248], P = 0.108). Importantly, this trend was further successfully verified using both weighted median and MR-Egger. Each 1 SD genetically increased vitamin C levels could reduce PD AAO 1.75 and 2.592 years using weighted median (beta = - 1.750, 95% CI: [- 3.396, - 0.105], P = 0.037) and MR-Egger (beta = - 2.592, 95% CI: [- 4.623, - 0.560], P = 0.012).

CONCLUSIONS

We demonstrated the causal association between genetically increased plasma vitamin C levels and reduced PD AAO in people of European descent. Randomized controlled trials are required to clarify whether diet intake or supplement, or both could reduce the AAO of PD.

Imputation and Reanalysis of ExomeChip Data Identifies Novel, Conditional and Joint Genetic Effects on Parkinson's Disease Risk

Given that improved imputation software and high-coverage whole genome sequence (WGS)-based haplotype reference panels now enable inexpensive approximation of WGS genotype data, we hypothesised that WGS-based imputation and analysis of existing ExomeChip-based genome-wide association (GWA) data will identify novel intronic and intergenic single nucleotide polymorphism (SNP) effects associated with complex disease risk. In this study, we reanalysed a Parkinson’s disease (PD) dataset comprising 5540 cases and 5862 controls genotyped using the ExomeChip-based NeuroX array. After genotype imputation and extensive quality control, GWA analysis was performed using PLINK and a recently developed machine learning approach (GenEpi), to identify novel, conditional and joint genetic effects associated with PD. In addition to improved validation of previously reported loci, we identified five novel genome-wide significant loci associated with PD: three (rs137887044, rs78837976 and rs117672332) with 0.01 < MAF < 0.05, and two (rs187989831 and rs12100172) with MAF < 0.01. Conditional analysis within genome-wide significant loci revealed four loci (p < 1 × 10⁻⁵) with multiple independent risk variants, while GenEpi analysis identified SNP–SNP interactions in seven genes. In addition to identifying novel risk loci for PD, these results demonstrate that WGS-based imputation and analysis of existing exome genotype data can identify novel intronic and intergenic SNP effects associated with complex disease risk.

Transcript Variants of Genes Involved in Neurodegeneration Are Differentially Regulated by the APOE and MAPT Haplotypes

Genetic variations at the Apolipoprotein E (ApoE) and microtubule-associated protein tau (MAPT) loci have been implicated in multiple neurogenerative diseases, but their exact molecular mechanisms are unclear. In this study, we performed transcript level linear modelling using the blood whole transcriptome data and genotypes of the 570 subjects in the Parkinson’s Progression Markers Initiative (PPMI) cohort. ApoE, MAPT haplotypes and two SNPs at the SNCA locus (rs356181, rs3910105) were used to detect expression quantitative trait loci eQTLs associated with the transcriptome and differential usage of transcript isoforms. As a result, we identified 151 genes associated with the genotypic variations, 29 cis and 122 trans eQTL positions. Profound effect with genome-wide significance of ApoE e4 haplotype on the expression of TOMM40 transcripts was identified. This finding potentially explains in part the frequently established genetic association with the APOE e4 haplotypes in neurodegenerative diseases. Moreover, MAPT haplotypes had significant differential impact on 23 transcripts from the 17q21.31 and 17q24.1 loci. MAPT haplotypes had also the largest up-regulating (256) and the largest down-regulating (−178) effect sizes measured as β values on two different transcripts from the same gene (LRRC37A2). Intronic SNP in the SNCA gene, rs3910105, differentially induced expression of three SNCA isoforms. In conclusion, this study established clear association between well-known haplotypic variance and transcript specific regulation in the blood. APOE e4 and MAPT H1/H2 haplotypic variants are associated with the expression of several genes related to the neurodegeneration.

The role of genetics in Parkinson's disease: a large cohort study in Chinese mainland population

This study aimed to determine the mutational spectrum of familial Parkinson's disease and sporadic early-onset Parkinson's disease (sEOPD) in a mainland Chinese population and the clinical features of mutation carriers. We performed multiplex ligation-dependent probe amplification assays and whole-exome sequencing for 1676 unrelated patients with Parkinson's disease in a mainland Chinese population, including 192 probands from families with autosomal-recessive Parkinson's disease, 242 probands from families with autosomal-dominant Parkinson's disease, and 1242 sEOPD patients (age at onset ≤ 50). According to standards and guidelines from the American College of Medical Genetics and Genomics, pathogenic/likely pathogenic variants in 23 known Parkinson's disease-associated genes occurred more frequently in the autosomal-recessive Parkinson's disease cohort (65 of 192, 33.85%) than in the autosomal-dominant Parkinson's disease cohort (10 of 242, 4.13%) and the sEOPD cohort (57 of 1242, 4.59%), which leads to an overall molecular diagnostic yield of 7.88% (132 of 1676). We found that PRKN was the most frequently mutated gene (n = 83, 4.95%) and present the first evidence of an SNCA duplication and LRRK2 p.N1437D variant in mainland China. In addition, several novel pathogenic/likely pathogenic variants including LRRK2 (p.V1447M and p.Y1645S), ATP13A2 (p.R735X and p.A819D), FBXO7 (p.G67E), LRP10 (c.322dupC/p.G109Rfs*51) and TMEM230 (c.429delT/p.P144Qfs*2) were identified in our cohort. Furthermore, the age at onset of the 132 probands with genetic diagnoses (median, 31.5 years) was about 14.5 years earlier than that of patients without molecular diagnoses (i.e. non-carriers, median 46.0 years). Specifically, the age at onset of Parkinson's disease patients with pathogenic/likely pathogenic variants in ATP13A2, PLA2G6, PRKN, or PINK1 was significantly lower than that of non-carriers, while the age at onset of carriers with other gene pathogenic/likely pathogenic variants was similar to that of non-carriers. The clinical spectrum of Parkinson's disease-associated gene carriers in this mainland Chinese population was similar to that of other populations. We also detected 61 probands with GBA possibly pathogenic variants (3.64%) and 59 probands with GBA p.L444P (3.52%). These results shed insight into the genetic spectrum and clinical manifestations of Parkinson's disease in mainland China and expand the existing repertoire of pathogenic or likely pathogenic variants involved in known Parkinson's disease-associated genes. Our data highlight the importance of genetic testing in Parkinson's disease patients with age at onset < 40 years, especially in those from families with a recessive inheritance pattern, who may benefit from early diagnosis and treatment.

Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale

Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS) are heterogeneous, progressive diseases with frequently overlapping symptoms characterized by a loss of neurons. Studies have suggested relations between neurodegenerative diseases for many years (e.g., regarding the aggregation of toxic proteins or triggering endogenous cell death pathways). We gathered publicly available genomic, transcriptomic, and proteomic data from 177 studies and more than one million patients to detect shared genetic patterns between the neurodegenerative diseases on three analyzed omics-layers. The results show a remarkably high number of shared differentially expressed genes between the transcriptomic and proteomic levels for all conditions, while showing a significant relation between genomic and proteomic data between AD and PD and AD and ALS. We identified a set of 139 genes being differentially expressed in several transcriptomic experiments of all four diseases. These 139 genes showed overrepresented gene ontology (GO) Terms involved in the development of neurodegeneration, such as response to heat and hypoxia, positive regulation of cytokines and angiogenesis, and RNA catabolic process. Furthermore, the four analyzed neurodegenerative diseases (NDDs) were clustered by their mean direction of regulation throughout all transcriptomic studies for this set of 139 genes, with the closest relation regarding this common gene set seen between AD and HD. GO-Term and pathway analysis of the proteomic overlap led to biological processes (BPs), related to protein folding and humoral immune response. Taken together, we could confirm the existence of many relations between Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis on transcriptomic and proteomic levels by analyzing the pathways and GO-Terms arising in these intersections. The significance of the connection and the striking relation of the results to processes leading to neurodegeneration between the transcriptomic and proteomic data for all four analyzed neurodegenerative diseases showed that exploring many studies simultaneously, including multiple omics-layers of different neurodegenerative diseases simultaneously, holds new relevant insights that do not emerge from analyzing these data separately. Furthermore, the results shed light on processes like the humoral immune response that have previously been described only for certain diseases. Our data therefore suggest human patients with neurodegenerative diseases should be addressed as complex biological systems by integrating multiple underlying data sources.

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.

Genetics of Parkinson's disease: An introspection of its journey towards precision medicine

A substantial proportion of risk for Parkinson's disease (PD) is driven by genetics. Progress in understanding the genetic basis of PD has been significant. So far, highly-penetrant rare genetic alterations in SNCA, LRRK2, VPS35, PRKN, PINK1, DJ-1 and GBA have been linked with typical familial PD and common genetic variability at 90 loci have been linked to risk for PD. In this review, we outline the journey thus far of PD genetics, highlighting how significant advances have improved our knowledge of the genetic basis of PD risk, onset and progression. Despite remarkable progress, our field has yet to unravel how genetic risk variants disrupt biological pathways and molecular networks underlying the pathobiology of the disease. We highlight that currently identified genetic risk factors only represent a fraction of the likely genetic risk for PD. Identifying the remaining genetic risk will require us to diversify our efforts, performing genetic studies across different ancestral groups. This work will inform us on the varied genetic basis of disease across populations and also aid in fine mapping discovered loci. If we are able to take this course, we foresee that genetic discoveries in PD will directly influence our ability to predict disease and aid in defining etiological subtypes, critical steps for the implementation of precision medicine for PD.

Ten Years of the International Parkinson Disease Genomics Consortium: Progress and Next Steps

In June 2009 a small group of investigators met at the annual Movement Disorders Society meeting in Paris. The explicit goal of this meeting was to discuss a potential research alliance focused on the genetics of Parkinson disease (PD). The outcome of this informal meeting was the creation of the International Parkinson Disease Genomics Consortium (IPDGC), a group focused on collaborative genetics research, enabled by trust, sharing, and as little paperwork as possible. The IPDGC has grown considerably since its inception, including over 100 scientists from around the World. The focus has also grown, to include clinical and functional investigation of PD at scale. Most recently, the IPDGC has expanded to initiate major research efforts in East Asia and Africa, and has prioritized collaborations with ongoing major efforts in India and South America. Here we summarize the efforts of the IPDGC thus far and place these in the context of a decade of progress in PD genomics. We also discuss the future direction of IPDGC and our stated research priorities for the next decade.