The Parkinson's Disease Mendelian Randomization Research Portal

Causal relationships between inflammatory cytokines and myopia: an analysis of genetic and observational studies

Objective

This study aims to explore the causal relationship between inflammatory markers and myopia through the use of bidirectional Mendelian randomization (MR) and myopia animal models.

Methods

The authors utilized data from a comprehensive and publicly accessible genome-wide association study (GWAS) for our analysis, which includes 460 536 European ancestry control subjects and 37 362 myopia patients. Utilizing a two-sample Mendelian randomization analysis framework, 27 inflammatory markers were investigated as exposure variables with myopia serving as the outcome variable. Nine MR analysis techniques were employed, with inverse-variance weighting (IVW) as the principal MR analysis method. Heterogeneity was assessed using Cochrane's Q test. The identification of single-nucleotide polymorphisms (SNPs) and outliers linked to myopia was achieved via MR-PRESSO. The expression of interleukin-2 (IL-2) in the vitreous of guinea pigs subjected to experimentally induced form-deprivation myopia (FDM) was examined.

Results

Elevated concentrations of IL-2 and IL-2ra were found to be associated [IVW estimate odds ratio (OR): 1.003, 95% CI: 1.001-1.005, P=0.001] and strongly associated (IVW estimate OR: 1.002, 95% CI: 1.000-1.003, P=0.049) with an increased risk of myopia, respectively. Conversely, lower levels of C-reactive protein (CRP) (IVW estimate OR: 0.996, 95% CI: 0.994-0.999, P=0.002) and tumour necrosis factor alpha (IVW estimate OR: 0.995, 95% CI: 0.994-0.996, P<0.001) were robustly linked to a heightened risk of myopia. IL-2 expression was notably upregulated in the vitreous of guinea pigs with experimentally induced FDM.

Conclusions

Elevated levels of inflammatory factors, especially IL-2 and IL-2ra, have a potential causal relationship with myopia susceptibility, providing new insights into the pathogenesis of myopia.

Discovery and Exploration of Lipid-Modifying Drug Targets for ALS by Mendelian Randomization

Observational studies have faced challenges in identifying replicable causes for amyotrophic lateral sclerosis (ALS). To address this, we employed an unbiased and data-driven approach to discover and explore potential causal exposures using two-sample Mendelian randomization (MR) analyses. In the phenotype discovery stage, we assessed 3948 environmental exposures from the UK Biobank and utilized ALS summary statistics (Europeans, 20,806 cases, 59,804 controls) as the outcome within a phenome-wide MR pipeline. Through a range of sensitivity analyses, two medication traits were identified to be protective for ALS. In the target exploration stage, we further conducted drug target MR analyses using the latest and trans-ethnic summary data on lipid-related traits and ALS (Europeans, 27,205 cases, 110,881 controls; East Asians, 1234 cases, 2850 controls). Our aim was to explore potential causal drug targets through six lipid-modifying effects. These comprehensive analyses revealed significant findings. Specifically, "cholesterol-lowering medication" and "atorvastatin" survived predefined criteria in the phenotype discovery stage and exhibited a protective effect on ALS. Further in the target exploration stage, we demonstrated that the therapeutic effect of APOB through LDL-lowering was associated with reduced ALS liability in Europeans (OR = 0.835, P = 5.61E - 5). Additionally, the therapeutic effect of APOA1 and LDLR through TC-lowering was associated with reduced ALS liability in East Asians (APOA1, OR = 0.859, P = 5.38E - 4; LDLR, OR = 0.910, P = 2.73E - 5). Overall, we propose potential protective effects of cholesterol-lowering drugs or statins on ALS risk from thousands of exposures. Our research also suggests APOB, APOA1, and LDLR as novel therapeutic targets for ALS and supports their potential protective mechanisms may be mediated by LDL-lowering or TC-lowering effects.

Exploring causal effects of sarcopenia on risk and progression of Parkinson disease by Mendelian randomization

Previous observational studies suggested that sarcopenia is associated with Parkinson disease (PD), but it is unclear whether this association is causal. The objective of this study was to examine causal associations between sarcopenia-related traits and the risk or progression of PD using a Mendelian randomization (MR) approach. Two-sample bidirectional MR analyses were conducted to evaluate causal relationships. Genome-wide association study (GWAS) summary statistics for sarcopenia-related traits, including right handgrip strength (n = 461,089), left handgrip strength (n = 461,026), and appendicular lean mass (n = 450,243), were retrieved from the IEU OpenGWAS database. GWAS data for the risk of PD were derived from the FinnGen database (4235 cases; 373,042 controls). Summary-level data for progression of PD, including progression to Hoehn and Yahr stage 3, progression to dementia, and development of levodopa-induced dyskinesia, were obtained from a recent GWAS publication on progression of PD in 4093 patients from 12 longitudinal cohorts. Significant causal associations identified in MR analysis were verified through a polygenic score (PGS)-based approach and pathway enrichment analysis using genotype data from the Parkinson's Progression Markers Initiative. MR results supported a significant causal influence of right handgrip strength (odds ratio [OR] = 0.152, 95% confidence interval [CI] = 0.055-0.423, adjusted P = 0.0036) and appendicular lean mass (OR = 0.597, 95% CI = 0.440-0.810, adjusted P = 0.0111) on development of levodopa-induced dyskinesia. In Cox proportional hazard analysis, higher PGSs for right handgrip strength (hazard ratio [HR] = 0.225, 95% CI = 0.095-0.530, adjusted P = 0.0019) and left handgrip strength (HR = 0.303, 95% CI = 0.121-0.59, adjusted P = 0.0323) were significantly associated with a lower risk of developing levodopa-induced dyskinesia, after adjusting for covariates. Pathway enrichment analysis revealed that genome-wide significant single-nucleotide polymorphisms for right handgrip strength were substantially enriched in biological pathways involved in the control of synaptic plasticity. This study provides genetic evidence of the protective role of handgrip strength or appendicular lean mass on the development of levodopa-induced dyskinesia in PD. Sarcopenia-related traits can be promising prognostic markers for levodopa-induced dyskinesia and potential therapeutic targets for preventing levodopa-induced dyskinesia in patients with PD.

Association of Body Mass Index and Parkinson Disease: A Bidirectional Mendelian Randomization Study

BACKGROUND AND OBJECTIVES

The role of body mass index (BMI) in Parkinson disease (PD) is unclear. Based on the Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in PD (Courage-PD) consortium, we used 2-sample Mendelian randomization (MR) to replicate a previously reported inverse association of genetically predicted BMI with PD and investigated whether findings were robust in analyses addressing the potential for survival and incidence-prevalence biases. We also examined whether the BMI-PD relation is bidirectional by performing a reverse MR.

METHODS

We used summary statistics from a genome-wide association study (GWAS) to extract the association of 501 single-nucleotide polymorphisms (SNPs) with BMI and from the Courage-PD and international Parkinson Disease Genomics Consortium (iPDGC) to estimate their association with PD. Analyses are based on participants of European ancestry. We used the inverse-weighted method to compute odds ratios (ORIVW per 4.8 kg/m2 [95% CI]) of PD and additional pleiotropy robust methods. We performed analyses stratified by age, disease duration, and sex. For reverse MR, we used SNPs associated with PD from 2 iPDGC GWAS to assess the effect of genetic liability toward PD on BMI.

RESULTS

Summary statistics for BMI are based on 806,834 participants (54% women). Summary statistics for PD are based on 8,919 (40% women) cases and 7,600 (55% women) controls from Courage-PD, and 19,438 (38% women) cases and 24,388 (51% women) controls from iPDGC. In Courage-PD, we found an inverse association between genetically predicted BMI and PD (ORIVW 0.82 [0.70-0.97], p = 0.012) without evidence for pleiotropy. This association tended to be stronger in younger participants (≤67 years, ORIVW 0.71 [0.55-0.92]) and cases with shorter disease duration (≤7 years, ORIVW 0.75 [0.62-0.91]). In pooled Courage-PD + iPDGC analyses, the association was stronger in women (ORIVW 0.85 [0.74-0.99], p = 0.032) than men (ORIVW 0.92 [0.80-1.04], p = 0.18), but the interaction was not statistically significant (p-interaction = 0.48). In reverse MR, there was evidence for pleiotropy, but pleiotropy robust methods showed a significant inverse association.

DISCUSSION

Using an independent data set (Courage-PD), we replicate an inverse association of genetically predicted BMI with PD, not explained by survival or incidence-prevalence biases. Moreover, reverse MR analyses support an inverse association between genetic liability toward PD and BMI, in favor of a bidirectional relation.

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.

Mendelian randomization: causal inference leveraging genetic data

Mendelian randomization (MR) leverages genetic information to examine the causal relationship between phenotypes allowing for the presence of unmeasured confounders. MR has been widely applied to unresolved questions in epidemiology, making use of summary statistics from genome-wide association studies on an increasing number of human traits. However, an understanding of essential concepts is necessary for the appropriate application and interpretation of MR. This review aims to provide a non-technical overview of MR and demonstrate its relevance to psychiatric research. We begin with the origins of MR and the reasons for its recent expansion, followed by an overview of its statistical methodology. We then describe the limitations of MR, and how these are being addressed by recent methodological advances. We showcase the practical use of MR in psychiatry through three illustrative examples - the connection between cannabis use and psychosis, the link between intelligence and schizophrenia, and the search for modifiable risk factors for depression. The review concludes with a discussion of the prospects of MR, focusing on the integration of multi-omics data and its extension to delineating complex causal networks.

A genome-wide association study of neutrophil count in individuals associated to an African continental ancestry group facilitates studies of malaria pathogenesis

BACKGROUND

'Benign ethnic neutropenia' (BEN) is a heritable condition characterized by lower neutrophil counts, predominantly observed in individuals of African ancestry, and the genetic basis of BEN remains a subject of extensive research. In this study, we aimed to dissect the genetic architecture underlying neutrophil count variation through a linear-mixed model genome-wide association study (GWAS) in a population of African ancestry (N = 5976). Malaria caused by P. falciparum imposes a tremendous public health burden on people living in sub-Saharan Africa. Individuals living in malaria endemic regions often have a reduced circulating neutrophil count due to BEN, raising the possibility that reduced neutrophil counts modulate severity of malaria in susceptible populations. As a follow-up, we tested this hypothesis by conducting a Mendelian randomization (MR) analysis of neutrophil counts on severe malaria (MalariaGEN, N = 17,056).

RESULTS

We carried out a GWAS of neutrophil count in individuals associated to an African continental ancestry group within UK Biobank, identifying 73 loci (r2 = 0.1) and 10 index SNPs (GCTA-COJO loci) associated with neutrophil count, including previously unknown rare loci regulating neutrophil count in a non-European population. BOLT-LMM was reliable when conducted in a non-European population, and additional covariates added to the model did not largely alter the results of the top loci or index SNPs. The two-sample bi-directional MR analysis between neutrophil count and severe malaria showed the greatest evidence for an effect between neutrophil count and severe anaemia, although the confidence intervals crossed the null.

CONCLUSION

Our GWAS of neutrophil count revealed unique loci present in individuals of African ancestry. We note that a small sample-size reduced our power to identify variants with low allele frequencies and/or low effect sizes in our GWAS. Our work highlights the need for conducting large-scale biobank studies in Africa and for further exploring the link between neutrophils and severe malaria.

Parkinson's Disease is Predominantly a Genetic Disease

The discovery of a pathogenic variant in the alpha-synuclein (SNCA) gene in the Contursi kindred in 1997 indisputably confirmed a genetic cause in a subset of Parkinson's disease (PD) patients. Currently, pathogenic variants in one of the seven established PD genes or the strongest known risk factor gene, GBA1, are identified in ∼15% of PD patients unselected for age at onset and family history. In this Debate article, we highlight multiple avenues of research that suggest an important - and in some cases even predominant - role for genetics in PD aetiology, including familial clustering, high rates of monogenic PD in selected populations, and complete penetrance with certain forms. At first sight, the steep increase in PD prevalence exceeding that of other neurodegenerative diseases may argue against a predominant genetic etiology. Notably, the principal genetic contribution in PD is conferred by pathogenic variants in LRRK2 and GBA1 and, in both cases, characterized by an overall late age of onset and age-related penetrance. In addition, polygenic risk plays a considerable role in PD. However, it is likely that, in the majority of PD patients, a complex interplay of aging, genetic, environmental, and epigenetic factors leads to disease development.

Exploring the interplay between metabolomics and genetics in Parkinson's disease: Insights from ongoing research and future avenues

Parkinson's disease (PD) is a widespread neurodegenerative disorder, whose complex aetiology remains under construction. While rare variants have been associated with the monogenic PD form, most PD cases are influenced by multiple genetic and environmental aspects. Nonetheless, the pathophysiological pathways and molecular networks involved in monogenic/idiopathic PD overlap, and genetic variants are decisive in elucidating the convergent underlying mechanisms of PD. In this scenario, metabolomics has furnished a dynamic and systematic picture of the synergy between the genetic background and environmental influences that impact PD, making it a valuable tool for investigating PD-related metabolic dysfunctions. In this review, we performed a brief overview of metabolomics current research in PD, focusing on significant metabolic alterations observed in idiopathic PD from different biofluids and strata and exploring how they relate to genetic factors associated with monogenic PD. Dysregulated amino acid metabolism, lipid metabolism, and oxidative stress are the critical metabolic pathways implicated in both genetic and idiopathic PD. By merging metabolomics and genetics data, it is possible to distinguish metabolic signatures of specific genetic backgrounds and to pinpoint subgroups of PD patients who could derive personalized therapeutic benefits. This approach holds great promise for advancing PD research and developing innovative, cost-effective treatments.

Causal effect of gut-microbiota-derived metabolite trimethylamine N-oxide on Parkinson's disease: A Mendelian randomization study

BACKGROUND AND PURPOSE

It has been suggested that trimethylamine N-oxide (TMAO) is related to Parkinson's disease (PD) in observational studies. However, the direction of this association is inconsistent. An exploratory Mendelian randomization study was conducted to investigate whether TMAO and its precursors have a causal relationship with PD.

METHODS

Summary statistics were obtained for single nucleotide polymorphisms related to circulating levels of TMAO, betaine, carnitine and choline, and the corresponding data for the risk, age at onset and progression of PD from genome-wide association studies. Inverse-variance weighting was used as the primary method for effect estimation. The false discovery rate was applied to the correction of multiple testing. A p value of association <0.05 but above the false discovery rate corrected threshold was deemed suggestive evidence of a possible association. A range of robust Mendelian randomization methods were used for sensitivity analysis.

RESULTS

Suggestive evidence was observed of an inverse causal effect of TMAO on motor fluctuations (odds ratio [OR] 0.851, 95% confidence interval [CI] 0.731, 0.990, p = 0.037) and carnitine on insomnia (OR 0.817, 95% CI 0.700, 0.954, p = 0.010) and a positive causal effect of betaine on Hoehn-Yahr stage (OR 1.397, 95% CI 1.112, 1.756, p = 0.004), Unified Parkinson's Disease Rating Scale (UPDRS) III score (β = 0.138, 95% CI 0.051, 0.225, p = 0.002), motor fluctuations (OR 1.236, 95% CI 1.011, 1.511, p = 0.039), and choline on UPDRS IV (β = 0.106, 95% CI 0.026, 0.185, p = 0.009) and modified Schwab and England Activities of Daily Living Scale score (β = 0.806, 95% CI 0.127, 1.484, p = 0.020).

CONCLUSIONS

Our findings provide suggestive evidence that TMAO and its precursors have a causal effect on the progression of PD. Further investigation of the underlying mechanisms is required.

Integration of transcriptome-wide association study with neuronal dysfunction assays provides functional genomics evidence for Parkinson's disease genes

Genome-wide association studies (GWAS) have markedly advanced our understanding of the genetics of Parkinson's disease (PD), but they currently do not account for the full heritability of PD. In many cases it is difficult to unambiguously identify a specific gene within each locus because GWAS does not provide functional information on the identified candidate loci. Here we present an integrative approach that combines transcriptome-wide association study (TWAS) with high-throughput neuronal dysfunction analyses in Drosophila to discover and validate candidate PD genes. We identified 160 candidate genes whose misexpression is associated with PD risk via TWAS. Candidates were validated using orthogonal in silico methods and found to be functionally related to PD-associated pathways (i.e. endolysosome). We then mimicked these TWAS-predicted transcriptomic alterations in a Drosophila PD model and discovered that 50 candidates can modulate α-Synuclein(α-Syn)-induced neurodegeneration, allowing us to nominate new genes in previously known PD loci. We also uncovered additional novel PD candidate genes within GWAS suggestive loci (e.g. TTC19, ADORA2B, LZTS3, NRBP1, HN1L), which are also supported by clinical and functional evidence. These findings deepen our understanding of PD, and support applying our integrative approach to other complex trait disorders.

Body Mass Index, Abdominal Adiposity, and Incidence of Parkinson Disease in French Women From the E3N Cohort Study

BACKGROUND AND OBJECTIVES

Previous studies on the relationship between body mass index (BMI) and Parkinson disease (PD) provided inconsistent results, likely due to reverse causation explained by weight loss during the prodromal phase. We examined the association of BMI and abdominal adiposity with PD incidence using lagged analyses to address the potential for reverse causation and compared BMI trajectories in patients before diagnosis and matched controls.

METHODS

We used data from the E3N cohort study of French women with a 29-year follow-up (1990-2018). BMI (kg/m²) was computed based on self-reported weight and height up to 11 times; up to 6 waist circumference (WC) and hip circumference measures were available. PD diagnoses were validated based on medical records and drug claim databases. Multivariable time-varying Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs according to BMI categories (underweight <18.5 kg/m²; normal = [18.5-25.0[ kg/m²; overweight = [25.0-30.0[ kg/m²; obese ≥30.0 kg/m²). Exposures were lagged by 5 years in main analyses; we used longer lags (10 and 20 years) in sensitivity analyses. We examined trajectories of BMI categories within a nested case-control study using multivariable generalized estimating equations multinomial logistic models.

RESULTS

Of 96,702 women (baseline age = 40-65 years), 1,164 developed PD. PD incidence was lower (HR = 0.76, 95% CI = 0.59-0.98, p = 0.032) among women with obesity compared with those with normal BMI. There was a similar association in analyses using longer lag times (20 years, 598 cases, HR = 0.52, 95% CI = 0.30-0.88, p = 0.016). A similar pattern was seen for WC and waist-height ratio but not waist-hip ratio. Trajectories of BMI categories (1,196 patients and 23,876 controls) showed that obesity was less frequent in patients with PD before diagnosis than in controls, with a statistically significant difference 29 years before. In addition, the frequency of obesity decreased 5-10 years before diagnosis in patients.

DISCUSSION

In this large cohort of women with a long follow-up, obesity was associated with a lower hazard of PD, even when measured 20 years before diagnosis, in agreement with Mendelian randomization studies. Our analyses underscore the importance of lagged analyses to account for reverse causation. These findings warrant further investigations to understand the mechanisms underlying this inverse association.

The Effect of Blood Lipids, Type 2 Diabetes, and Body Mass Index on Parkinson's Disease: A Korean Mendelian Randomization Study

OBJECTIVE

Associations between various metabolic conditions and Parkinson's disease (PD) have been previously identified in epidemiological studies. We aimed to investigate the causal effect of lipid levels, type 2 diabetes mellitus (T2DM), and body mass index (BMI) on PD in a Korean population via Mendelian randomization (MR).

METHODS

Two-sample MR analyses were performed with inverse-variance weighted (IVW), weighted median, and MR-Egger regression approaches. We identified genetic variants associated with lipid concentrations, T2DM, and BMI in publicly available summary statistics, which were either collected from genome-wide association studies (GWASs) or from meta-analyses of GWAS that targeted only Korean individuals or East Asian individuals, including Korean individuals. The outcome dataset was a GWAS on PD performed in a Korean population.

RESULTS

From previous GWASs and meta-analyses, we selected single nucleotide polymorphisms as the instrumental variables. Variants associated with serum levels of low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides, as well as with T2DM and BMI, were selected (n = 11, 19, 17, 89, and 9, respectively). There were no statistically significant causal associations observed between the five exposures and PD using either the IVW, weighted median, or MR-Egger methods (p-values of the IVW method: 0.332, 0.610, 0.634, 0.275, and 0.860, respectively).

CONCLUSION

This study does not support a clinically relevant causal effect of lipid levels, T2DM, and BMI on PD risk in a Korean population.

Alcohol and Parkinson's Disease: A Systematic Review and Meta-Analysis

BACKGROUND

A substantial body of research has examined the relationship between alcohol consumption and risk of Parkinson's disease (PD).

OBJECTIVE

To provide an updated systematic review and meta-analysis of observational studies examining the relationship between alcohol consumption and risk of PD.

METHODS

Eligible studies comparing PD risk in ever vs. never alcohol drinkers were sourced from six databases. Outcomes were pooled using standard meta-analysis techniques. Separate female and male estimates were generated from studies reporting sex-specific data. Additionally, cohort studies stratifying participants by quantity of alcohol intake were integrated in a dose-response analysis.

RESULTS

52 studies were included, totaling 63,707 PD patients and 9,817,924 controls. Our meta-analysis supported a statistically significant overrepresentation of never drinkers among PD subjects; odds ratio (OR) for ever drinking alcohol 0.84 (95% confidence interval (CI) 0.76 - 0.92). A subgroup analysis revealed similar effect estimates in females and males. A further synthesis of seven cohort studies suggested a negative, dose-dependent association between alcohol and risk of PD.

CONCLUSION

In the absence of a known neuroprotective pathway, there may be reason to doubt a true biological effect. The role of survivor bias, selection and recall bias, misclassification, and residual confounding requires consideration. Alternatively, observations might be attributable to reverse causation if those predestined for PD alter their alcohol habits during the preclinical phase. Major limitations of our study include high between-study heterogeneity (I2 = 93.2%) and lack of adjustment for key confounders, namely smoking status.

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.

Leveraging genetic discoveries for sleep to determine causal relationships with common complex traits

Sleep occurs universally and is a biological necessity for human functioning. The consequences of diminished sleep quality impact physical and physiological systems such as neurological, cardiovascular, and metabolic processes. In fact, people impacted by common complex diseases experience a wide range of sleep disturbances. It is challenging to uncover the underlying molecular mechanisms responsible for decreased sleep quality in many disease systems owing to the lack of suitable sleep biomarkers. However, the discovery of a genetic component to sleep patterns has opened a new opportunity to examine and understand the involvement of sleep in many disease states. It is now possible to use major genomic resources and technologies to uncover genetic contributions to many common diseases. Large scale prospective studies such as the genome wide association studies (GWAS) have successfully revealed many robust genetic signals associated with sleep-related traits. With the discovery of these genetic variants, a major objective of the community has been to investigate whether sleep-related traits are associated with disease pathogenesis and other health complications. Mendelian Randomization (MR) represents an analytical method that leverages genetic loci as proxy indicators to establish causal effect between sleep traits and disease outcomes. Given such variants are randomly inherited at birth, confounding bias is eliminated with MR analysis, thus demonstrating evidence of causal relationships that can be used for drug development and to prioritize clinical trials. In this review, we outline the results of MR analyses performed to date on sleep traits in relation to a multitude of common complex diseases.

Immunogenetic Determinants of Parkinson’s Disease Etiology

Parkinson’s disease (PD) is increasingly recognised as a systemic disorder in which inflammation might play a causative role rather than being a consequence or an epiphenomenon of the neurodegenerative process. Although growing genetic evidence links the central and peripheral immune system with both monogenic and sporadic PD, our understanding on how the immune system contributes to PD pathogenesis remains a daunting challenge. In this review, we discuss recent literature aimed at exploring the role of known genes and susceptibility loci to PD pathogenesis through immune system related mechanisms. Furthermore, we outline shared genetic etiologies and interrelations between PD and autoimmune diseases and underlining challenges and limitations faced in the translation of relevant allelic and regulatory risk loci to immune-pathological mechanisms. Lastly, with the field of immunogenetics expanding rapidly, we place these insights into a future context highlighting the prospect of immune modulation as a promising disease-modifying strategy.

Validation of external and internal exposome of the findings associated to cerebral small vessel disease: A Mendelian randomization study

The exposome characterizes all environmental exposures and their impact on a disease. To determine the causally-associated components of the exposome for cerebral small vessel disease (CSVD), we performed mendelian randomization analysis of 5365 exposures on six clinical and subclinical CSVD measures. We found statistically significant evidence (FDR-corrected P < 0.05) that hypertension, high cholesterol, longer television-watching time, lower educational qualifications, younger age of first sexual intercourse, smoking, reduced pulmonary function, higher subjective overall health rating, and frequent tiredness were associated with increased risk of intracerebral hemorrhage or small vessel stroke. Adiposity, diabetes, frequent alcoholic drinks, higher white blood cell count and neutrophil count were significantly associated with higher risk of non-lobar hemorrhage or small vessel stroke, but not lobar hemorrhage. Hypertension, higher arm or leg fat-free mass and higher sitting height were significantly associated with higher white matter hyperintensities. The results were robust to sensitivity analyses and showed no evidence of horizontal pleiotropy. We also identified 41 exposures suggestively associated (uncorrected P < 0.05) with multiple CSVD measures as the "the CSVD exposome". This exposome-wide association study provides insight into CSVD development and prevention.

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.

Causal Relations between Exposome and Stroke: A Mendelian Randomization Study

BACKGROUND AND PURPOSE

To explore the causal relationships of elements of the exposome with ischemic stroke and its subtypes at the omics level and to provide evidence for stroke prevention.

METHODS

We conducted a Mendelian randomization study between exposure and any ischemic stroke (AIS) and its subtypes (large-artery atherosclerotic disease [LAD], cardioembolic stroke [CE], and small vessel disease [SVD]). The exposure dataset was the UK Biobank involving 361,194 subjects, and the outcome dataset was the MEGASTROKE consortium including 52,000 participants.

RESULTS

We found that higher blood pressure (BP) (systolic BP: odds ratio [OR], 1.02; 95% confidence interval [CI], 1.01 to 1.04; diastolic BP: OR, 1.03; 95% CI, 1.01 to 1.05; pulse pressure: OR, 1.03; 95% CI, 1.00 to 1.06), atrial fibrillation (OR, 1.18; 95% CI, 1.13 to 1.25), and diabetes (OR, 1.13; 95% CI, 1.07 to 1.18) were significantly associated with ischemic stroke. Importantly, higher education (OR, 0.69; 95% CI, 0.60 to 0.79) decreased the risk of ischemic stroke. Higher systolic BP (OR, 1.06; 95% CI, 1.02 to 1.10), pulse pressure (OR, 1.08; 95% CI, 1.02 to 1.14), diabetes (OR, 1.28; 95% CI, 1.13 to 1.45), and coronary artery disease (OR, 1.58; 95% CI, 1.25 to 2.00) could cause LAD. Atrial fibrillation could cause CE (OR, 1.90; 95% CI, 1.71 to 2.11). For SVD, higher systolic BP (OR, 1.04; 95% CI, 1.00 to 1.07), diastolic BP (OR, 1.06; 95% CI, 1.01 to 1.12), and diabetes (OR, 1.22; 95% CI, 1.10 to 1.36) were causal factors.

CONCLUSIONS

The study revealed elements of the exposome causally linked to ischemic stroke and its subtypes, including conventional causal risk factors and novel protective factors such as higher education.

Genetically Predicted Levels of Circulating Inflammatory Cytokines and the Risk and Age at Onset of Parkinson’s Disease: A Two-Sample Mendelian Randomization Study

Parkinson’s disease (PD) is widely considered to be a disabling neurodegenerative disorder, which has been ranked second worldwide just after Alzheimer’s disease. Until present, a wide range of studies has focused on the role of circulating inflammatory cytokines in the development of PD. However, the causal relationship between circulating inflammatory cytokines and the risk and age at the onset of PD has not been elucidated. Hence, to evaluate the effects of circulating inflammatory cytokines on the risk or age at the onset of PD more accurately, we conducted this two-sample Mendelian randomization (MR) study involving summary statistics from genome-wide association studies (GWASs). Totally, we included a GWAS for inflammatory cytokines (8,293 participants), a meta-analysis of GWASs for PD risk (482,730 participants), and a GWAS dataset for age at the onset of PD (17,996 patients with PD). A total of 149 and 131 polymorphisms for exploring relationships between 19 inflammatory cytokines and the risk and age at the onset of PD were obtained as instrumental variants. Then, we used a total of five MR methods, including inverse-variance weighted (IVW), Wald ratio, MR Egger regression, weighted median, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods. Finally, we found a causal association between circulating levels of macrophage inflammatory protein-1 beta (MIP1b) and PD risk in the IVW method (OR: 1.06; 95% CI: 1.02–1.10; P = 0.001). Meanwhile, other MR estimates by weighted median and MR-PRESSO methods yielded similar effect estimates. Besides, we identified a suggestive association of interleukin-16 (IL-16) levels with PD risk (OR: 1.08; 95% CI: 1.00–1.17; P = 0.037). For age at PD onset, there was no evidence supporting its correlation with inflammatory cytokines. Our findings implied that MIP1b and IL-16 may be novel biomarkers and promising therapeutic targets for PD development.

The Promise of Mendelian Randomization in Parkinson's Disease: Has the Smoke Cleared Yet for Smoking and Parkinson's Disease Risk?

This commentary discusses the strengths and limitations of utilizing the Mendelian randomization (MR) approach in Parkinson's disease (PD) studies. Epidemiologists proposed to employ MR when genetic instruments are available that represent reliable proxies for modifiable lifelong exposures which elude easy measurement in studies of late onset diseases like PD. Here, we are using smoking as an example. The great promise of the MR approach is its resilience to confounding and reverse causation. Nevertheless, the approach has some drawbacks such as being liable to selection- and survival-bias, it makes some strong assumptions about the genetic instruments employed, and requires very large sample sizes. When interpreted carefully and put into the context of other studies that take both genetics and the environment into consideration, MR studies help us to not only ask interesting questions but also can support causal inference and provide novel insights.

Causal role of high body mass index in multiple chronic diseases: a systematic review and meta-analysis of Mendelian randomization studies

BACKGROUND

Obesity is a worldwide epidemic that has been associated with a plurality of diseases in observational studies. The aim of this study was to summarize the evidence from Mendelian randomization (MR) studies of the association between body mass index (BMI) and chronic diseases.

METHODS

PubMed and Embase were searched for MR studies on adult BMI in relation to major chronic diseases, including diabetes mellitus; diseases of the circulatory, respiratory, digestive, musculoskeletal, and nervous systems; and neoplasms. A meta-analysis was performed for each disease by using results from published MR studies and corresponding de novo analyses based on summary-level genetic data from the FinnGen consortium (n = 218,792 individuals).

RESULTS

In a meta-analysis of results from published MR studies and de novo analyses of the FinnGen consortium, genetically predicted higher BMI was associated with increased risk of type 2 diabetes mellitus, 14 circulatory disease outcomes, asthma, chronic obstructive pulmonary disease, five digestive system diseases, three musculoskeletal system diseases, and multiple sclerosis as well as cancers of the digestive system (six cancer sites), uterus, kidney, and bladder. In contrast, genetically predicted higher adult BMI was associated with a decreased risk of Dupuytren's disease, osteoporosis, and breast, prostate, and non-melanoma cancer, and not associated with Alzheimer's disease, amyotrophic lateral sclerosis, or Parkinson's disease.

CONCLUSIONS

The totality of the evidence from MR studies supports a causal role of excess adiposity in a plurality of chronic diseases. Hence, continued efforts to reduce the prevalence of overweight and obesity are a major public health goal.

Evidence for GRN connecting multiple neurodegenerative diseases

Previous research using genome-wide association studies has identified variants that may contribute to lifetime risk of multiple neurodegenerative diseases. However, whether there are common mechanisms that link neurodegenerative diseases is uncertain. Here, we focus on one gene, GRN, encoding progranulin, and the potential mechanistic interplay between genetic risk, gene expression in the brain and inflammation across multiple common neurodegenerative diseases. We utilized genome-wide association studies, expression quantitative trait locus mapping and Bayesian colocalization analyses to evaluate potential causal and mechanistic inferences. We integrate various molecular data types from public resources to infer disease connectivity and shared mechanisms using a data-driven process. Expression quantitative trait locus analyses combined with genome-wide association studies identified significant functional associations between increasing genetic risk in the GRN region and decreased expression of the gene in Parkinson's, Alzheimer's and amyotrophic lateral sclerosis. Additionally, colocalization analyses show a connection between blood-based inflammatory biomarkers relating to platelets and GRN expression in the frontal cortex. GRN expression mediates neuroinflammation function related to multiple neurodegenerative diseases. This analysis suggests shared mechanisms for Parkinson's, Alzheimer's and amyotrophic lateral sclerosis.

Visceral adipose tissue had a causal, independent role in lowering the risk of Parkinson's disease: A mendelian randomization study

Genetic evidence based on two-sample Mendelian randomization approaches suggested that visceral adipose tissue had a causal, independent role in lowering the risk of Parkinson's disease. Further studies are needed to explore the underlying mechanism.

Mendelian Randomisation Study of Smoking, Alcohol, and Coffee Drinking in Relation to Parkinson's Disease

BACKGROUND

Previous studies showed that lifestyle behaviors (cigarette smoking, alcohol, coffee) are inversely associated with Parkinson's disease (PD). The prodromal phase of PD raises the possibility that these associations may be explained by reverse causation.

OBJECTIVE

To examine associations of lifestyle behaviors with PD using two-sample Mendelian randomisation (MR) and the potential for survival and incidence-prevalence biases.

METHODS

We used summary statistics from publicly available studies to estimate the association of genetic polymorphisms with lifestyle behaviors, and from Courage-PD (7,369 cases, 7,018 controls; European ancestry) to estimate the association of these variants with PD. We used the inverse-variance weighted method to compute odds ratios (ORIVW) of PD and 95%confidence intervals (CI). Significance was determined using a Bonferroni-corrected significance threshold (p = 0.017).

RESULTS

We found a significant inverse association between smoking initiation and PD (ORIVW per 1-SD increase in the prevalence of ever smoking = 0.74, 95%CI = 0.60-0.93, p = 0.009) without significant directional pleiotropy. Associations in participants ≤67 years old and cases with disease duration ≤7 years were of a similar size. No significant associations were observed for alcohol and coffee drinking. In reverse MR, genetic liability toward PD was not associated with smoking or coffee drinking but was positively associated with alcohol drinking.

CONCLUSION

Our findings are in favor of an inverse association between smoking and PD that is not explained by reverse causation, confounding, and survival or incidence-prevalence biases. Genetic liability toward PD was positively associated with alcohol drinking. Conclusions on the association of alcohol and coffee drinking with PD are hampered by insufficient statistical power.

Investigating causal relationships between exposome and human longevity: a Mendelian randomization analysis

BACKGROUND

Environmental factors are associated with human longevity, but their specificity and causality remain mostly unclear. By integrating the innovative "exposome" concept developed in the field of environmental epidemiology, this study aims to determine the components of exposome causally linked to longevity using Mendelian randomization (MR) approach.

METHODS

A total of 4587 environmental exposures extracting from 361,194 individuals from the UK biobank, in exogenous and endogenous domains of exposome were assessed. We examined the relationship between each environmental factor and two longevity outcomes (i.e., surviving to the 90th or 99th percentile age) from various cohorts of European ancestry. Significant results after false discovery rates correction underwent validation using an independent exposure dataset.

RESULTS

Out of all the environmental exposures, eight age-related diseases and pathological conditions were causally associated with lower odds of longevity, including coronary atherosclerosis (odds ratio = 0.77, 95% confidence interval [0.70, 0.84], P = 4.2 × 10-8), ischemic heart disease (0.66, [0.51, 0.87], P = 0.0029), angina (0.73, [0.65, 0.83], P = 5.4 × 10-7), Alzheimer's disease (0.80, [0.72, 0.89], P = 3.0 × 10-5), hypertension (0.70, [0.64, 0.77], P = 4.5 × 10-14), type 2 diabetes (0.88 [0.80, 0.96], P = 0.004), high cholesterol (0.81, [0.72, 0.91], P = 0.0003), and venous thromboembolism (0.92, [0.87, 0.97], P = 0.0028). After adjusting for genetic correlation between different types of blood lipids, higher levels of low-density lipoprotein cholesterol (0.72 [0.64, 0.80], P = 2.3 × 10-9) was associated with lower odds of longevity, while high-density lipoprotein cholesterol (1.36 [1.13, 1.62], P = 0.001) showed the opposite. Genetically predicted sitting/standing height was unrelated to longevity, while higher comparative height size at 10 was negatively associated with longevity. Greater body fat, especially the trunk fat mass, and never eat sugar or foods/drinks containing sugar were adversely associated with longevity, while education attainment showed the opposite.

CONCLUSIONS

The present study supports that some age-related diseases as well as education are causally related to longevity and highlights several new targets for achieving longevity, including management of venous thromboembolism, appropriate intake of sugar, and control of body fat. Our results warrant further studies to elucidate the underlying mechanisms of these reported causal associations.

Understanding the effect of smoking and drinking behavior on Parkinson's disease risk: a Mendelian randomization study

Previous observational studies have identified correlations between Parkinson's disease (PD) risk and lifestyle factors. However, whether or not those associations are causal remains unclear. To infer causality between PD risk and smoking or alcohol intake, we conducted a two-sample Mendelian randomization study using genome-wide association study summary statistics from the GWAS & Sequencing Consortium of Alcohol and Nicotine use study (1.2 million participants) and the latest meta-analysis from the International Parkinson's Disease Genomics Consortium (37,688 PD cases and 18,618 proxy-cases). We performed sensitivity analyses, including testing for pleiotropy with MR-Egger and MR-PRESSO, and multivariable MR modeling to account for the genetic effects of competing substance use traits on PD risk. Our results revealed causal associations of alcohol intake (OR 0.79; 95% CI 0.65-0.96; p = 0.021) and smoking continuation (which compares current vs. former smokers) (OR 0.64; 95% CI 0.46-0.89; p = 0.008) with lower PD risk. Multivariable MR analyses showed that the causal association between drinks per week and PD is unlikely due to confounding by smoking behavior. Finally, frailty analyses suggested that the causal effects of both alcohol intake and smoking continuation on PD risk estimated from MR analysis are not explained by the presence of survival bias alone. Our findings support the role of smoking as a protective factor against PD, but only when comparing current vs. former smokers. Similarly, increased alcohol intake had a protective effect over PD risk, with the alcohol dehydrogenase 1B (ADH1B) locus as a potential candidate for further investigation of the mechanisms underlying this association.

Probing the Pre-diagnostic Phase of Parkinson's Disease in Population-Based Studies

Parkinson's disease covers a wide spectrum of symptoms, ranging from early non-motor symptoms to the characteristic bradykinesia, tremor and rigidity. Although differences in the symptomatology of Parkinson's disease are increasingly recognized, there is still a lack of insight into the heterogeneity of the pre-diagnostic phase of Parkinson's disease. In this perspective, we highlight three aspects regarding the role of population-based studies in providing new insights into the heterogeneity of pre-diagnostic Parkinson's disease. First we describe several specific advantages of population-based cohort studies, including the design which overcomes some common biases, the broad data collection and the high external validity. Second, we draw a parallel with the field of Alzheimer's disease to provide future directions to uncover the heterogeneity of pre-diagnostic Parkinson's disease. Finally, we anticipate on the emergence of prevention and disease-modification trials and the potential role of population-based studies herein. In the coming years, bridging gaps between study designs will be essential to make vital advances in elucidating the heterogeneity of pre-diagnostic Parkinson's disease.

Parkinson's disease

Parkinson's disease is a recognisable clinical syndrome with a range of causes and clinical presentations. Parkinson's disease represents a fast-growing neurodegenerative condition; the rising prevalence worldwide resembles the many characteristics typically observed during a pandemic, except for an infectious cause. In most populations, 3-5% of Parkinson's disease is explained by genetic causes linked to known Parkinson's disease genes, thus representing monogenic Parkinson's disease, whereas 90 genetic risk variants collectively explain 16-36% of the heritable risk of non-monogenic Parkinson's disease. Additional causal associations include having a relative with Parkinson's disease or tremor, constipation, and being a non-smoker, each at least doubling the risk of Parkinson's disease. The diagnosis is clinically based; ancillary testing is reserved for people with an atypical presentation. Current criteria define Parkinson's disease as the presence of bradykinesia combined with either rest tremor, rigidity, or both. However, the clinical presentation is multifaceted and includes many non-motor symptoms. Prognostic counselling is guided by awareness of disease subtypes. Clinically manifest Parkinson's disease is preceded by a potentially long prodromal period. Presently, establishment of prodromal symptoms has no clinical implications other than symptom suppression, although recognition of prodromal parkinsonism will probably have consequences when disease-modifying treatments become available. Treatment goals vary from person to person, emphasising the need for personalised management. There is no reason to postpone symptomatic treatment in people developing disability due to Parkinson's disease. Levodopa is the most common medication used as first-line therapy. Optimal management should start at diagnosis and requires a multidisciplinary team approach, including a growing repertoire of non-pharmacological interventions. At present, no therapy can slow down or arrest the progression of Parkinson's disease, but informed by new insights in genetic causes and mechanisms of neuronal death, several promising strategies are being tested for disease-modifying potential. With the perspective of people with Parkinson's disease as a so-called red thread throughout this Seminar, we will show how personalised management of Parkinson's disease can be optimised.

Sleep/wake cycle alterations as a cause of neurodegenerative diseases: A Mendelian randomization study

Sleep and/or wake cycle alterations are common in neurodegenerative diseases (ND). Our aim was to determine whether there is a causal relationship between sleep and/or wake cycle patterns and ND (Parkinson's disease (PD) age at onset (AAO), Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS)) using two-sample Mendelian Randomization (MR). We selected 12 sleep traits with available Genome-Wide Association Study (GWAS) to evaluate their causal relationship with the ND risk through Inverse-Variance Weighted regression as main analysis. We used as outcome the latest ND GWAS with available summary-statistics: PD-AAO (N = 17,996), AD (N = 21,235) and ALS (N = 40,136). MR results pointed to a causal effect of subjective and objective-measured morning chronotype on later PD-AAO (95%CI:0.33-1.81, p = 8.47×10^-09 and 95%CI:-7.28 to -4.44, p = 5.87×10^-16, respectively). Sleep efficiency was causally associated with a decreased AD risk (95%CI:-20.408 to -0.66, p = 0.04) and daytime sleepiness with an increased ALS risk (95%CI:0.15 to 1.61, p = 0.01). Our study suggests that sleep and/or wake patterns have causal relationship with ND. Given that sleep and/or wake patterns are modifiable risk factors, sleep interventions should be investigated as a potential treatment in PD-AAO, AD and ALS.

Causal Association between Periodontitis and Parkinson's Disease: A Bidirectional Mendelian Randomization Study

The latest evidence revealed a possible association between periodontitis and Parkinson’s disease (PD). We explored the causal relationship of this bidirectional association through two-sample Mendelian randomization (MR) in European ancestry populations. To this end, we used openly accessible data of genome-wide association studies (GWAS) on periodontitis and PD. As instrumental variables for periodontitis, seventeen single-nucleotide polymorphisms (SNPs) from a GWAS of periodontitis (1817 periodontitis cases vs. 2215 controls) and eight non-overlapping SNPs of periodontitis from an additional GWAS for validation purposes. Instrumental variables to explore for the reverse causation included forty-five SNPs from a GWAS of PD (20,184 cases and 397,324 controls). Multiple approaches of MR were carried-out. There was no evidence of genetic liability of periodontitis being associated with a higher risk of PD (B = −0.0003, Standard Error [SE] 0.0003, p = 0.26). The eight independent SNPs (B = −0.0000, SE 0.0001, p = 0.99) validated this outcome. We also found no association of genetically primed PD towards periodontitis (B = −0.0001, SE 0.0001, p = 0.19). These MR study findings do not support a bidirectional causal genetic liability between periodontitis and PD. Further GWAS studies are needed to confirm the consistency of these results.

Shared genetic etiology between Parkinson's disease and blood levels of specific lipids

Parkinson’s disease (PD) is characterized by the degeneration of dopaminergic neurons in the substantia nigra and the formation of Lewy bodies. The mechanisms underlying these molecular and cellular effects are largely unknown. Previously, based on genetic and other data, we built a molecular landscape of PD that highlighted a central role for lipids. To explore which lipid species may be involved in PD pathology, we used published genome-wide association study (GWAS) data to conduct polygenic risk score-based analyses to examine putative genetic sharing between PD and blood levels of 370 lipid species and lipid-related molecules. We found a shared genetic etiology between PD and blood levels of 25 lipids. We then used data from a much-extended GWAS of PD to try and corroborate our findings. Across both analyses, we found genetic overlap between PD and blood levels of eight lipid species, namely two polyunsaturated fatty acids (PUFA 20:3n3-n6 and 20:4n6), four triacylglycerols (TAG 44:1, 46:1, 46:2, and 48:0), phosphatidylcholine aa 32:3 (PC aa 32:3) and sphingomyelin 26:0 (SM 26:0). Analysis of the concordance—the agreement in genetic variant effect directions across two traits—revealed a significant negative concordance between PD and blood levels of the four triacylglycerols and PC aa 32:3 and a positive concordance between PD and blood levels of both PUFA and SM 26:0. Taken together, our analyses imply that genetic variants associated with PD modulate blood levels of a specific set of lipid species supporting a key role of these lipids in PD etiology.

No Evidence for a Causal Relationship Between Cancers and Parkinson's Disease

BACKGROUND

Epidemiological data suggest that cancer patients have a reduced risk of subsequent Parkinson's disease (PD) development, but the prevalence of PD in melanoma patients is often reported to be increased. Causal relationships between cancers and PD have not been fully explored.

OBJECTIVE

To study causal relationship between different cancers and PD.

METHODS

We used GWAS summary statistics of 15 different types of cancers and two-sample Mendelian randomization to study the causal relationship with PD.

RESULTS

There was no evidence to support a causal relationship between the studied cancers and PD. We also performed reverse analyses between PD and cancers with available full summary statistics (melanoma, breast, prostate, endometrial and keratinocyte cancers) and did not find evidence of causal relationship.

CONCLUSION

We found no evidence to support a causal relationship between cancers and PD and the previously reported associations could be a result of genetic pleiotropy, shared biology or biases.

Beneficial Effects of Epigallocatechin-3-O-Gallate, Chlorogenic Acid, Resveratrol, and Curcumin on Neurodegenerative Diseases

Many observational and clinical studies have shown that consumption of diets rich in plant polyphenols have beneficial effects on various diseases such as cancer, obesity, diabetes, cardiovascular diseases, and neurodegenerative diseases (NDDs). Animal and cellular studies have indicated that these polyphenolic compounds contribute to such effects. The representative polyphenols are epigallocatechin-3-O-gallate in tea, chlorogenic acids in coffee, resveratrol in wine, and curcumin in curry. The results of human studies have suggested the beneficial effects of consumption of these foods on NDDs including Alzheimer's and Parkinson's diseases, and cellular animal experiments have provided molecular basis to indicate contribution of these representative polyphenols to these effects. This article provides updated information on the effects of these foods and their polyphenols on NDDs with discussions on mechanistic aspects of their actions mainly based on the findings derived from basic experiments.

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.

Bidirectional Relation Between Parkinson's Disease and Glioblastoma Multiforme

Cancer and Parkinson's disease (PD) define two disease entities that include opposite concepts. Indeed, the involved mechanisms are at different ends of a spectrum related to cell survival - one due to enhanced cellular proliferation and the other due to premature cell death. There is increasing evidence indicating that patients with neurodegenerative diseases like PD have a reduced incidence for most cancers. In support, epidemiological studies demonstrate an inverse association between PD and cancer. Both conditions apparently can involve the same set of genes, however, in affected tissues the expression was inversely regulated: genes that are down-regulated in PD were found to be up-regulated in cancer and vice versa, for example p53 or PARK7. When comparing glioblastoma multiforme (GBM), a malignant brain tumor with poor overall survival, with PD, astrocytes are dysregulated in both diseases in opposite ways. In addition, common genes, that are involved in both diseases and share common key pathways of cell proliferation and metabolism, were shown to be oppositely deregulated in PD and GBM. Here, we provide an overview of the involvement of PD- and GBM-associated genes in common pathways that are dysregulated in both conditions. Moreover, we illustrate why the simultaneous study of PD and GBM regarding the role of common pathways may lead to a deeper understanding of these still incurable conditions. Eventually, considering the inverse regulation of certain genes in PD and GBM will help to understand their mechanistic basis, and thus to define novel target-based strategies for causative treatments.

Missing heritability in Parkinson's disease: the emerging role of non-coding genetic variation

Parkinson's disease (PD) is a neurodegenerative disorder caused by a complex interplay of genetic and environmental factors. For the stratification of PD patients and the development of advanced clinical trials, including causative treatments, a better understanding of the underlying genetic architecture of PD is required. Despite substantial efforts, genome-wide association studies have not been able to explain most of the observed heritability. The majority of PD-associated genetic variants are located in non-coding regions of the genome. A systematic assessment of their functional role is hampered by our incomplete understanding of genotype-phenotype correlations, for example through differential regulation of gene expression. Here, the recent progress and remaining challenges for the elucidation of the role of non-coding genetic variants is reviewed with a focus on PD as a complex disease with multifactorial origins. The function of gene regulatory elements and the impact of non-coding variants on them, and the means to map these elements on a genome-wide level, will be delineated. Moreover, examples of how the integration of functional genomic annotations can serve to identify disease-associated pathways and to prioritize disease- and cell type-specific regulatory variants will be given. Finally, strategies for functional validation and considerations for suitable model systems are outlined. Together this emphasizes the contribution of rare and common genetic variants to the complex pathogenesis of PD and points to remaining challenges for the dissection of genetic complexity that may allow for better stratification, improved diagnostics and more targeted treatments for PD in the future.

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.

Using Mendelian randomization to understand and develop treatments for neurodegenerative disease

Common neurodegenerative diseases are thought to arise from a combination of environmental and genetic exposures. Mendelian randomization is a powerful way to leverage existing genetic data to investigate causal relationships between risk factors and disease. In recent years, Mendelian randomization has gathered considerable traction in neurodegenerative disease research, providing valuable insights into the aetiology of these conditions. This review aims to evaluate the impact of Mendelian randomization studies on translational medicine for neurodegenerative diseases, highlighting the advances made and challenges faced. We will first describe the fundamental principles and limitations of Mendelian randomization and then discuss the lessons from Mendelian randomization studies of environmental risk factors for neurodegeneration. We will illustrate how Mendelian randomization projects have used novel resources to study molecular pathways of neurodegenerative disease and discuss the emerging role of Mendelian randomization in drug development. Finally, we will conclude with our view of the future of Mendelian randomization in these conditions, underscoring unanswered questions in this field.

Overlapping genetic architecture between Parkinson disease and melanoma

Epidemiologic studies have reported inconsistent results regarding an association between Parkinson disease (PD) and cutaneous melanoma (melanoma). Identifying shared genetic architecture between these diseases can support epidemiologic findings and identify common risk genes and biological pathways. Here, we apply polygenic, linkage disequilibrium-informed methods to the largest available case-control, genome-wide association study summary statistic data for melanoma and PD. We identify positive and significant genetic correlation (correlation: 0.17, 95% CI 0.10-0.24; P = 4.09 × 10-06) between melanoma and PD. We further demonstrate melanoma and PD-inferred gene expression to overlap across tissues (correlation: 0.14, 95% CI 0.06 to 0.22; P = 7.87 × 10-04) and highlight seven genes including PIEZO1, TRAPPC2L, and SOX6 as potential mediators of the genetic correlation between melanoma and PD. These findings demonstrate specific, shared genetic architecture between PD and melanoma that manifests at the level of gene expression.

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.