Genomewide association study of Parkinson's disease clinical biomarkers in 12 longitudinal patients' cohorts

Relationship between hearing impairment and dementia and cognitive function: a Mendelian randomization study

BACKGROUND

There is a substantial body of observational research indicating an association between hearing impairment and dementia, yet the causal relationship and underlying mechanisms remain uncertain. This study aims to investigate the causal relationship between hearing impairment and its subtypes with dementia and cognitive function using two-sample Mendelian randomization (MR) analysis.

METHODS

We performed two-sample MR analysis to examine the causal effects of hearing impairment and its subtypes, including conductive and sensorineural hearing loss (CSHL), conductive hearing loss (CHL), sensorineural hearing loss (SHL), and sudden sensorineural hearing loss (SIHL), on six dementia phenotypes (overall dementia, Alzheimer's disease [AD], Lewy body dementia [DLB], frontotemporal dementia [FTD], Parkinson's disease dementia, and vascular dementia) and four cognitive functions. Additionally, multivariable MR (MVMR) analysis was employed to investigate potential mediating mechanisms.

RESULTS

Genetically determined CSHL was associated with an elevated risk of DLB (odds ratio [OR] 1.69; 95% CI 1.08 to 2.63; P = 0.021) and FTD (OR 1.66; 1.04 to 2.67; P = 0.035), but not AD (P = 0.958). Genetic predisposition to CHL was found to link with increased risks of AD (OR 1.07; 1.01 to 1.14; P = 0.031). Genetically determined SHL was causally associated with an elevated risk of semantic dementia (OR 3.81; 1.09 to 13.37; P = 0.037). Genetically predicted CHL and SIHL were both causally associated with lower general cognitive performance (β -0.015 and - 0.043; P = 0.007 and 0.013) and fluid intelligence score (β -0.045 and - 0.095; P = 0.037 and 0.040). In MVMR analysis, the causal relationship between hearing impairment and dementia was mediated by loneliness, depressed mood, and brain cortical volume, particularly the medial temporal lobe, but not by aging or ischemic stroke.

CONCLUSION

Overall, the study provides evidence supporting a causal relationship between hearing impairment and increased risks of different types of dementia (including AD, FTD, and DLB), as well as poorer general cognitive function. These findings underscore the importance of addressing hearing impairment as a modifiable risk factor for dementia.

NeuroBooster Array: A Genome-Wide Genotyping Platform to Study Neurological Disorders Across Diverse Populations

BACKGROUND

Commercial genome-wide genotyping arrays have historically neglected coverage of genetic variation across populations.

OBJECTIVE

We aimed to create a multi-ancestry genome-wide array that would include a wide range of neuro-specific genetic content to facilitate genetic research in neurological disorders across multiple ancestral groups, fostering diversity and inclusivity in research studies.

METHODS

We developed the Illumina NeuroBooster Array (NBA), a custom high-throughput and cost-effective platform on a backbone of 1,914,934 variants from the Infinium Global Diversity Array and added custom content comprising 95,273 variants associated with more than 70 neurological conditions or traits, and we further tested its performance on more than 2000 patient samples. This novel platform includes approximately 10,000 tagging variants to facilitate imputation and analyses of neurodegenerative disease-related genome-wide association study loci across diverse populations.

RESULTS

In this article, we describe NBA's potential as an efficient means for researchers to assess known and novel disease genetic associations in a multi-ancestry framework. The NBA can identify rare genetic variants and accurately impute more than 15 million common variants across populations. Apart from enabling sample prioritization for further whole-genome sequencing studies, we envisage that NBA will play a pivotal role in recruitment for interventional studies in the precision medicine space.

CONCLUSIONS

From a broader perspective, the NBA serves as a promising means to foster collaborative research endeavors in the field of neurological disorders worldwide. Ultimately, this carefully designed tool is poised to make a substantial contribution to uncovering the genetic etiology underlying these debilitating conditions. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

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.

Identifying potential repurposable medications for Parkinson's disease through Mendelian randomization analysis

Observational studies have suggested the potential benefits of several medications for Parkinson's disease (PD) and their potential for repurposing. However, the conclusions drawn from these studies are not entirely consistent. To address this inconsistency, we used the two-sample Mendelian randomization (MR) method to explore the putative causal relationships between 23 medications and the risk and progression of PD. We applied inverse-variance weighted meta-analysis (IVW) to combine MR estimates. Additionally, sensitivity analyses were conducted to evaluate the robustness of the results. Our genetic evidence suggests that thyroid preparations and calcium channel blockers reduce the risk of PD, and salicylic acid and derivatives slow the progression of PD motor symptoms. Additionally, genetic evidence also suggests that four medications were associated with PD risk or progression, but the sensitivity analysis revealed that three of the medications may have interference caused by reverse causality. Our findings suggest that there are weak causal relationships between several medications and the risk or progression of PD. Though further replication studies are needed to verify these findings, these new insights may help in understanding the etiology of the disease, generate new clues related to drug discovery, and quantify the risk of future drug intake.

Lack of genetic evidence for NLRP3 inflammasome involvement in Parkinson's disease pathogenesis

Activation of the NLRP3 inflammasome has been implicated in Parkinson's disease (PD) based on in vitro and in vivo studies. Clinical trials targeting the NLRP3 inflammasome in PD are ongoing. However, the evidence supporting NLRP3's involvement in PD from human genetics data is limited. We analyzed common and rare variants in NLRP3 inflammasome-related genes in PD cohorts, performed pathway-specific polygenic risk score (PRS) analyses, and studied causal associations using Mendelian randomization (MR) with the NLRP3 components and the cytokines IL-1β and IL-18. Our findings showed no associations of common or rare variants, nor of the pathway PRS with PD. MR suggests that altering the expression of the NLRP3 inflammasome, IL-1β, or IL-18, does not affect PD risk or progression. Therefore, our results do not support a role for the NLRP3 inflammasome in PD pathogenesis or as a target for drug development.

GWAS Identifies DPP6 as Risk Gene of Cognitive Decline in Parkinson's Disease

BACKGROUND

Cognitive decline is among the most common non-motor symptoms in Parkinson's disease (PD), while its physiological mechanisms remain poorly understood. Genetic factors constituted a fundamental determinant in the heterogeneity of cognitive decline among PD patients. However, the underlying genetic background was still less studied.

METHODS

To explore the genetic determinants contributing to cognitive decline in PD, we performed genome-wide survival analysis using a Cox proportional hazards model in a longitudinal cohort of 450 Chinese patients with PD, and further explored the functional effect of the target variant. Additionally, we built a clinical-genetic model by incorporating clinical characteristics and polygenic risk score (PRS) to predict cognitive decline in PD.

RESULTS

The cohort was followed up for an average of 5.25 (SE = 2.46) years, with 95 incidents of cognitive impairment. We identified significant association between locus rs75819919 (DPP6) and accelerated cognitive decline (p = 8.63E-09, beta = 1.74, SE = 0.30). Dual-luciferase reporter assay suggested this locus might be involved in the regulation of DPP6 expression. Using data set from the UK Biobank, we identified rs75819919 was associated with cognitive performance in the general population. Incorporation of PRS increased the model's predictability, achieving an average AUC of 75.6% through fivefold cross-validation in 1 000 iterations.

CONCLUSIONS

These findings improve the current understanding of the genetic etiology of cognitive impairment in PD, and provide a novel target DPP6 to explore therapeutic options. Our results also demonstrate the potential to develop clinical-genetic model to identify patients susceptible to cognitive impairment and thus provide personalized clinical guidance.

Genome-wide determinants of mortality and motor progression in Parkinson's disease

There are 90 independent genome-wide significant genetic risk variants for Parkinson's disease (PD) but currently only five nominated loci for PD progression. The biology of PD progression is likely to be of central importance in defining mechanisms that can be used to develop new treatments. We studied 6766 PD patients, over 15,340 visits with a mean follow-up of between 4.2 and 15.7 years and carried out genome-wide survival studies for time to a motor progression endpoint, defined by reaching Hoehn and Yahr stage 3 or greater, and death (mortality). There was a robust effect of the APOE ε4 allele on mortality in PD. We also identified a locus within the TBXAS1 gene encoding thromboxane A synthase 1 associated with mortality in PD. We also report 4 independent loci associated with motor progression in or near MORN1, ASNS, PDE5A, and XPO1. Only the non-Gaucher disease causing GBA1 PD risk variant E326K, of the known PD risk variants, was associated with mortality in PD. Further work is needed to understand the links between these genomic variants and the underlying disease biology. However, these may represent new candidates for disease modification in PD.

Genome-wide association study of glucocerebrosidase activity modifiers

One of the most common genetic risk factors for Parkinson's disease (PD) are variants in GBA1, which encodes the lysosomal enzyme glucocerebrosidase (GCase). GCase deficiency has been associated with an increased PD risk, but not all individuals with low GCase activity are carriers of GBA1 mutations, suggesting other factors may be acting as modifiers. We aimed to discover common variants associated with GCase activity, as well as replicate previously reported associations, by performing a genome-wide association study using two independent cohorts: a Columbia University cohort consisting of 697 PD cases and 347 controls and the Parkinson's Progression Markers Initiative (PPMI) cohort consisting of 357 PD cases and 163 controls. As expected, GBA1 variants have the strongest association with decreased activity, led by p.N370S (beta = -4.36, se = 0.32, p = 5.05e-43). We also identify a novel association in the GAA locus (encoding for acid alpha-glucosidase, beta = -0.96, se = 0.17, p = 5.23e-09) that may be the result of an interaction between GCase and acid alpha-glucosidase based on various interaction analyses. Lastly, we show that several PD-risk loci are potentially associated with GCase activity. Further research will be needed to replicate and validate our findings and to uncover the functional connection between acid alpha-glucosidase and GCase.

Lack of genetic evidence for NLRP3-inflammasome involvement in Parkinson's disease pathogenesis

Activation of the NLRP3-inflammasome has been implicated in Parkinson's disease based on in vitro and in vivo studies. Clinical trials targeting the NLRP3-inflammasome in Parkinson's disease are ongoing. However, the evidence supporting NLRP3's involvement in Parkinson's disease from human genetics data is limited. In this study, we conducted analyses of common and rare variants in NLRP3-inflammasome related genes in Parkinson's disease cohorts. We performed pathway-specific analyses using polygenic risk scores and studied potential causal associations using Mendelian randomization with the NLRP3 components and the cytokines IL-1β and IL-18. Our findings showed no associations of common or rare variants, nor of the pathway polygenic risk score with Parkinson's disease. Mendelian randomization suggests that altering the expression of the NLRP3-inflammasome, IL-1β or IL-18, does not affect Parkinson's disease risk or progression. Therefore, our results do not support a role for the NLRP3-inflammasome in Parkinson's disease pathogenesis or as a target for drug development.

Common genetic risk for Parkinson's disease and dysfunction of the endo-lysosomal system

Parkinson's disease is a progressive neurological disorder, characterized by prominent movement dysfunction. The past two decades have seen a rapid expansion of our understanding of the genetic basis of Parkinson's, initially through the identification of monogenic forms and, more recently, through genome-wide association studies identifying common risk variants. Intriguingly, a number of cellular pathways have emerged from these analysis as playing central roles in the aetiopathogenesis of Parkinson's. In this review, the impact of data deriving from genome-wide analyses for Parkinson's upon our functional understanding of the disease will be examined, with a particular focus on examples of endo-lysosomal and mitochondrial dysfunction. The challenges of moving from a genetic to a functional understanding of common risk variants for Parkinson's will be discussed, with a final consideration of the current state of the genetic architecture of the disorder. This article is part of a discussion meeting issue 'Understanding the endo-lysosomal network in neurodegeneration'.

Disease progression strikingly differs in research and real-world Parkinson's populations

Characterization of Parkinson's disease (PD) progression using real-world evidence could guide clinical trial design and identify subpopulations. Efforts to curate research populations, the increasing availability of real-world data, and advances in natural language processing, particularly large language models, allow for a more granular comparison of populations than previously possible. This study includes two research populations and two real-world data-derived (RWD) populations. The research populations are the Harvard Biomarkers Study (HBS, N = 935), a longitudinal biomarkers cohort study with in-person structured study visits; and Fox Insights (N = 36,660), an online self-survey-based research study of the Michael J. Fox Foundation. Real-world cohorts are the Optum Integrated Claims-electronic health records (N = 157,475), representing wide-scale linked medical and claims data and de-identified data from Mass General Brigham (MGB, N = 22,949), an academic hospital system. Structured, de-identified electronic health records data at MGB are supplemented using a manually validated natural language processing with a large language model to extract measurements of PD progression. Motor and cognitive progression scores change more rapidly in MGB than HBS (median survival until H&Y 3: 5.6 years vs. >10, p < 0.001; mini-mental state exam median decline 0.28 vs. 0.11, p < 0.001; and clinically recognized cognitive decline, p = 0.001). In real-world populations, patients are diagnosed more than eleven years later (RWD mean of 72.2 vs. research mean of 60.4, p < 0.001). After diagnosis, in real-world cohorts, treatment with PD medications has initiated an average of 2.3 years later (95% CI: [2.1-2.4]; p < 0.001). This study provides a detailed characterization of Parkinson's progression in diverse populations. It delineates systemic divergences in the patient populations enrolled in research settings vs. patients in the real-world. These divergences are likely due to a combination of selection bias and real population differences, but exact attribution of the causes is challenging. This study emphasizes a need to utilize multiple data sources and to diligently consider potential biases when planning, choosing data sources, and performing downstream tasks and analyses.

Causal relationship between diabetes mellitus, glycemic traits and Parkinson's disease: a multivariable mendelian randomization analysis

BACKGROUND

Observational studies have indicated an association between diabetes mellitus (DM), glycemic traits, and the occurrence of Parkinson's disease (PD). However, the complex interactions between these factors and the presence of a causal relationship remain unclear. Therefore, we aim to systematically assess the causal relationship between diabetes, glycemic traits, and PD onset, risk, and progression.

METHOD

We used two-sample Mendelian randomization (MR) to investigate potential associations between diabetes, glycemic traits, and PD. We used summary statistics from genome-wide association studies (GWAS). In addition, we employed multivariable Mendelian randomization to evaluate the mediating effects of anti-diabetic medications on the relationship between diabetes, glycemic traits, and PD. To ensure the robustness of our findings, we performed a series of sensitivity analyses.

RESULTS

In our univariable Mendelian randomization (MR) analysis, we found evidence of a causal relationship between genetic susceptibility to type 1 diabetes (T1DM) and a reduced risk of PD (OR = 0.9708; 95% CI: 0.9466, 0.9956; P = 0.0214). In our multivariable MR analysis, after considering the conditions of anti-diabetic drug use, this correlation disappeared with adjustment for potential mediators, including anti-diabetic medications, insulin use, and metformin use.

CONCLUSION

Our MR study confirms a potential protective causal relationship between genetically predicted type 1 diabetes and reduced risk of PD, which may be mediated by factors related to anti-diabetic medications.

Relevance of Multiple Sclerosis Severity Genotype in Predicting Disease Course: A Real-World Cohort

OBJECTIVE

Currently, 233 genetic loci are known to be associated with susceptibility to multiple sclerosis (MS). Two independent pivotal severity genome-wide association studies recently found the first genome-wide significant single-nucleotide variant (SNV; rs10191329A ) and several other suggestive loci associated with overall disability outcomes. It is now important to understand if these findings can influence individual patient management.

METHODS

We assessed whether these progression SNVs are associated with detailed clinical phenotypes in a well-characterized prospective cohort of 1,455 MS patients. We used logistic regression, survival analysis, and propensity score matching to predict relevant long-term clinical outcomes.

RESULTS

We were unable to detect any association between rs10191329A and a range of clinically relevant outcomes (eg, time to Expanded Disability Status Scale milestones, age-related MS severity score, anatomical localization at onset or during subsequent relapses, annualized relapse rate). In addition, an extremes of outcome case-control analysis using a propensity score matching for genotype detected no association between disease severity and rs10191329A . However, we were able to replicate the association of two suggestive SNVs (rs7289446G and rs868824C ) with the development of fixed disability, albeit with modest effect sizes, and the association of HLA-DRB1*1501 with age at onset.

INTERPRETATION

Identification of rs10191329A and other suggestive SNVs are of considerable importance in understanding pathophysiological processes associated with MS severity. However, it is unlikely that individual genotyping can currently be used in a clinical setting to guide disease management. This study shows the importance of independent replication of genome-wide association studies associated with disease progression in neurodegenerative disorders. ANN NEUROL 2024;95:459-470.

Disease progression strikingly differs in research and real-world Parkinson's populations

Characterization of Parkinson's disease (PD) progression using real-world evidence could guide clinical trial design and identify subpopulations. Efforts to curate research populations, the increasing availability of real-world data and recent advances in natural language processing, particularly large language models, allow for a more granular comparison of populations and the methods of data collection describing these populations than previously possible. This study includes two research populations and two real-world data derived (RWD) populations. The research populations are the Harvard Biomarkers Study (HBS, N = 935), a longitudinal biomarkers cohort study with in-person structured study visits; and Fox Insights (N = 36,660), an online self-survey-based research study of the Michael J. Fox Foundation. Real-world cohorts are the Optum Integrated Claims-electronic health records (N = 157,475), representing wide-scale linked medical and claims data and de-identified data from Mass General Brigham (MGB, N = 22,949), an academic hospital system. Structured, de-identified electronic health records data at MGB are supplemented using natural language processing with a large language model to extract measurements of PD progression. This extraction process is manually validated for accuracy. Motor and cognitive progression scores change more rapidly in MGB than HBS (median survival until H&Y 3: 5.6 years vs. >10, p<0.001; mini-mental state exam median decline 0.28 vs. 0.11, p<0.001; and clinically recognized cognitive decline, p=0.001). In the real-world populations, patients are diagnosed more than eleven years later (RWD mean of 72.2 vs. research mean of 60.4, p<0.001). After diagnosis, in real-world cohorts, treatment with PD medications is initiated 2.3 years later on average (95% CI: [2.1-2.4]; p<0.001). This study provides a detailed characterization of Parkinson's progression in diverse populations. It delineates systemic divergences in the patient populations enrolled in research settings vs. patients in the real world. These divergences are likely due to a combination of selection bias and real population differences, but exact attribution of the causes is challenging using existing data. This study emphasizes a need to utilize multiple data sources and to diligently consider potential biases when planning, choosing data sources, and performing downstream tasks and analyses.

Genetics of Parkinson's disease heterogeneity: A genome-wide association study of clinical subtypes

INTRODUCTION

Substantial heterogeneity between individual patients in the clinical presentation of Parkinson's disease (PD) has led to the classification of distinct PD subtypes. However, genetic susceptibility factors for specific PD subtypes are not well understood. Therefore, the present study aimed to investigate the genetics of PD heterogeneity by performing a genome-wide association study (GWAS) of PD subtypes.

METHODS

A total of 799 PD patients were included and classified into tremor-dominant (TD) (N = 345), akinetic-rigid (AR) (N = 227), gait-difficulty (GD) (N = 82), and mixed (MX) (N = 145) phenotypic subtypes. After array genotyping and subsequent imputation, a total of 7,918,344 variants were assessed for association with each PD subtype using logistic regression models that were adjusted for age, sex, and the top five principal components of GWAS data.

RESULTS

We identified one genome-wide significant association (P < 5 × 10-8), which was between the MIR3976HG rs7504760 variant and the AR subtype (Odds ratio [OR] = 6.12, P = 2.57 × 10-8). Suggestive associations (P < 1 × 10-6) were observed regarding TD for RP11-497G19.3/RP11-497G19.1 rs7304254 (OR = 3.33, P = 3.89 × 10-7), regarding GD for HES2 rs111473931 (OR = 3.18, P = 6.85 × 10-7), RP11-400D2.3/CTD-2012I17.1 rs149082205 (OR = 8.96, P = 9.08 × 10-7), and RN7SL408P/SGK1 rs56161738 (OR = 2.97, P = 6.19 × 10-7), and regarding MX for MMRN2 rs112991171 (OR = 4.98, P = 1.02 × 10-7).

CONCLUSION

Our findings indicate that genetic variation may account for part of the clinical heterogeneity of PD. In particular, we found a novel genome-wide significant association between MIR3976HG variation and the AR PD subtype. Replication of these findings will be important in order to better define the genetic architecture of clinical variability in PD disease presentation.

Proxy-analysis of the genetics of cognitive decline in Parkinson's disease through polygenic scores

Cognitive decline is common in Parkinson's disease (PD) and its genetic risk factors are not well known to date, besides variants in the GBA and APOE genes. However, variation in complex traits is caused by numerous variants and is usually studied with genome-wide association studies (GWAS), requiring a large sample size, which is difficult to achieve for outcome measures in PD. Taking an alternative approach, we computed 100 polygenic scores (PGS) related to cognitive, dementia, stroke, and brain anatomical phenotypes and investigated their association with cognitive decline in six longitudinal cohorts. The analysis was adjusted for age, sex, genetic ancestry, follow-up duration, GBA and APOE status. Then, we meta-analyzed five of these cohorts, comprising a total of 1702 PD participants with 6156 visits, using the Montreal Cognitive Assessment as a cognitive outcome measure. After correction for multiple comparisons, we found four PGS significantly associated with cognitive decline: intelligence (p = 5.26e-13), cognitive performance (p = 1.46e-12), educational attainment (p = 8.52e-10), and reasoning (p = 3.58e-5). Survival analyses highlighted an offset of several years between the first and last quartiles of PGS, with significant differences for the PGS of cognitive performance (5 years) and educational attainment (7 years). In conclusion, we found four PGS associated with cognitive decline in PD, all associated with general cognitive phenotypes. This study highlights the common genetic factors between cognitive decline in PD and the general population, and the importance of the participant's cognitive reserve for cognitive outcome in PD.

Mendelian randomization reveals association between retinal thickness and non-motor symptoms of Parkinson's disease

Retinal thickness is related to Parkinson's disease (PD), but its association with the severity of PD is still unclear. We conducted a Mendelian randomized (MR) study to explore the association between retinal thickness and PD. For the two-sample MR analysis, the summary statistics obtained from genome-wide association studies on the thickness of Retinal nerve fiber layer (RNFL) and ganglion cell inner plexiform layer (GCIPL) were employed as exposure, while the summary statistics associated with PD were used as the outcome. The primary approach utilized was inverse variance weighted. To correct for multiple testing, the false discovery rate (FDR) was employed. For sensitivity analysis, an array of robust MR methods was utilized. We found genetically predicted significant association between reduced RNFL thickness and a reduced risk of constipation in PD (odds ratio [OR] = 0.854, 95% confidence interval [CI] (0.782, 0.933), P < 0.001, FDR-corrected P = 0.018). Genetically predicted reduced RNFL thickness was associated with a reduced Unified Parkinson's Disease Rating Scale total score (β = -0.042, 95% CI (-0.079, 0.005), P = 0.025), and reduced GCIPL thickness was associated with a lower risk of constipation (OR = 0.901, 95% CI (0.821, 0.988), P = 0.027) but a higher risk of depression (OR = 1.103, 95% CI (1.016, 1.198), P = 0.020), insomnia (OR = 1.090, 95% CI (1.013, 1.172), P = 0.021), and rapid eye movement sleep behaviour disorder (RBD) (OR = 1.198, 95% CI (1.061, 1.352), P = 0.003). In conclusion, we identify an association between retinal thickness and non-motor symptoms (constipation, depression, insomnia and RBD) in PD, highlighting the potential of retinal thickness as a biomarker for PD nonmotor symptoms.

CellGO: a novel deep learning-based framework and webserver for cell-type-specific gene function interpretation

Interpreting the function of genes and gene sets identified from omics experiments remains a challenge, as current pathway analysis tools often fail to consider the critical biological context, such as tissue or cell-type specificity. To address this limitation, we introduced CellGO. CellGO tackles this challenge by leveraging the visible neural network (VNN) and single-cell gene expressions to mimic cell-type-specific signaling propagation along the Gene Ontology tree within a cell. This design enables a novel scoring system to calculate the cell-type-specific gene-pathway paired active scores, based on which, CellGO is able to identify cell-type-specific active pathways associated with single genes. In addition, by aggregating the activities of single genes, CellGO extends its capability to identify cell-type-specific active pathways for a given gene set. To enhance biological interpretation, CellGO offers additional features, including the identification of significantly active cell types and driver genes and community analysis of pathways. To validate its performance, CellGO was assessed using a gene set comprising mixed cell-type markers, confirming its ability to discern active pathways across distinct cell types. Subsequent benchmarking analyses demonstrated CellGO's superiority in effectively identifying cell types and their corresponding cell-type-specific pathways affected by gene knockouts, using either single genes or sets of genes differentially expressed between knockout and control samples. Moreover, CellGO demonstrated its ability to infer cell-type-specific pathogenesis for disease risk genes. Accessible as a Python package, CellGO also provides a user-friendly web interface, making it a versatile and accessible tool for researchers in the field.

NeuroBooster Array: A Genome-Wide Genotyping Platform to Study Neurological Disorders Across Diverse Populations

Genome-wide genotyping platforms have the capacity to capture genetic variation across different populations, but there have been disparities in the representation of population-dependent genetic diversity. The motivation for pursuing this endeavor was to create a comprehensive genome-wide array capable of encompassing a wide range of neuro-specific content for the Global Parkinson's Genetics Program (GP2) and the Center for Alzheimer's and Related Dementias (CARD). CARD aims to increase diversity in genetic studies, using this array as a tool to foster inclusivity. GP2 is the first supported resource project of the Aligning Science Across Parkinson's (ASAP) initiative that aims to support a collaborative global effort aimed at significantly accelerating the discovery of genetic factors contributing to Parkinson's disease and atypical parkinsonism by generating genome-wide data for over 200,000 individuals in a multi-ancestry context. Here, we present the Illumina NeuroBooster array (NBA), a novel, high-throughput and cost-effective custom-designed content platform to screen for genetic variation in neurological disorders across diverse populations. The NBA contains a backbone of 1,914,934 variants (Infinium Global Diversity Array) complemented with custom content of 95,273 variants implicated in over 70 neurological conditions or traits with potential neurological complications. Furthermore, the platform includes over 10,000 tagging variants to facilitate imputation and analyses of neurodegenerative disease-related GWAS loci across diverse populations. The NBA can identify low frequency variants and accurately impute over 15 million common variants from the latest release of the TOPMed Imputation Server as of August 2023 (reference of over 300 million variants and 90,000 participants). We envisage this valuable tool will standardize genetic studies in neurological disorders across different ancestral groups, allowing researchers to perform genetic research inclusively and at a global scale.

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.

Expanding causal genes for Parkinson's disease via multi-omics analysis

Genome‑wide association studies (GWASs) have revealed numerous loci associated with Parkinson's disease (PD). However, some potential causal/risk genes were still not revealed and no etiological therapies are available. To find potential causal genes and explore genetically supported drug targets for PD is urgent. By integrating the expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) datasets from multiple tissues (blood, cerebrospinal fluid (CSF) and brain) and PD GWAS summary statistics, a pipeline combing Mendelian randomization (MR), Steiger filtering analysis, Bayesian colocalization, fine mapping, Protein-protein network and enrichment analysis were applied to identify potential causal genes for PD. As a result, GPNMB displayed a robust causal role for PD at the protein level in the blood, CSF and brain, and transcriptional level in the brain, while the protective role of CD38 (in brain pQTL and eQTL) was also identified. We also found inconsistent roles of DGKQ on PD between protein and mRNA levels. Another 9 proteins (CTSB, ARSA, SEC23IP, CD84, ENTPD1, FCGR2B, BAG3, SNCA, FCGR2A) were associated with the risk for PD based on only a single pQTL after multiple corrections. We also identified some proteins' interactions with known PD causative genes and therapeutic targets. In conclusion, this study suggested GPNMB, CD38, and DGKQ may act in the pathogenesis of PD, but whether the other proteins involved in PD needs more evidence. These findings would help to uncover the genes underlying PD and prioritize targets for future therapeutic interventions.

Lysosomal polygenic risk is associated with the severity of neuropathology in Lewy body disease

Intraneuronal accumulation of misfolded α-synuclein is the pathological hallmark of Parkinson's disease and dementia with Lewy bodies, often co-occurring with variable degrees of Alzheimer's disease related neuropathology. Genetic association studies have successfully identified common variants associated with disease risk and phenotypic traits in Lewy body disease, yet little is known about the genetic contribution to neuropathological heterogeneity. Using summary statistics from Parkinson's disease and Alzheimer's disease genome-wide association studies, we calculated polygenic risk scores and investigated the relationship with Lewy, amyloid-β and tau pathology. Associations were nominated in neuropathologically defined samples with Lewy body disease from the Netherlands Brain Bank (n = 217) and followed up in an independent sample series from the Mayo Clinic Brain Bank (n = 394). We also generated stratified polygenic risk scores based on single-nucleotide polymorphisms annotated to eight functional pathways or cell types previously implicated in Parkinson's disease and assessed for association with Lewy pathology in subgroups with and without significant Alzheimer's disease co-pathology. In an ordinal logistic regression model, the Alzheimer's disease polygenic risk score was associated with concomitant amyloid-β and tau pathology in both cohorts. Moreover, both cohorts showed a significant association between lysosomal pathway polygenic risk and Lewy pathology, which was more consistent than the association with a general Parkinson's disease risk score and specific to the subset of samples without significant concomitant Alzheimer's disease related neuropathology. Our findings provide proof of principle that the specific risk alleles a patient carries for Parkinson's and Alzheimer's disease also influence key aspects of the underlying neuropathology in Lewy body disease. The interrelations between genetic architecture and neuropathology are complex, as our results implicate lysosomal risk loci specifically in the subset of samples without Alzheimer's disease co-pathology. Our findings hold promise that genetic profiling may help predict the vulnerability to specific neuropathologies in Lewy body disease, with potential relevance for the further development of precision medicine in these disorders.

High-Throughput CSF Proteomics and Machine Learning to Identify Proteomic Signatures for Parkinson Disease Development and Progression

BACKGROUND AND OBJECTIVES

This study aimed to identify CSF proteomic signatures characteristic of Parkinson disease (PD) and evaluate their clinical utility.

METHODS

This observational study used data from the Parkinson's Progression Markers Initiative (PPMI), which enrolled patients with PD, healthy controls (HCs), and non-PD participants carrying GBA1, LRRK2, and/or SNCA pathogenic variants (genetic prodromals) at international sites. Study participants were chosen from PPMI enrollees based on the availability of aptamer-based CSF proteomic data, quantifying 4,071 proteins, and classified as patients with PD without GBA1, LRRK2, and/or SNCA pathogenic variants (nongenetic PD), HCs, patients with PD carrying the aforementioned pathogenic variants (genetic PD), or genetic prodromals. Differentially expressed protein (DEP) analysis and the least absolute shrinkage and selection operator (LASSO) were applied to the data from nongenetic PD and HCs. Signatures characteristics of nongenetic PD were quantified as a PD proteomic score (PD-ProS), validated internally and then externally using data of 1,556 CSF proteins from the LRRK2 Cohort Consortium (LCC). We further tested the PD-ProS in genetic PD and genetic prodromals and examined associations with clinical progression.

RESULTS

Data from 279 patients with nongenetic PD (mean ± SD, age 62.0 ± 9.6 years; male 67.7%) and 141 HCs (age 60.5 ± 11.9 years; male 64.5%) were used for PD-ProS derivation. From 23 DEPs, LASSO determined weights of 14 DEPs for the PD-ProS (area under the curve [AUC] 0.83, 95% CI 0.78-0.87), validated in an independent internal validation cohort of 71 patients with nongenetic PD and 35 HCs (AUC 0.81, 95% CI 0.73-0.90). In the LCC, only 5 of the 14 DEPs were also measured. Notably, these 5 DEPs still distinguished 34 patients with nongenetic PD from 31 HCs with the same weights (AUC 0.75, 95% CI 0.63-0.87). Furthermore, the PD-ProS distinguished 258 patients with genetic PD from 365 genetic prodromals. Finally, regardless of genetic status, the PD-ProS independently predicted both cognitive and motor decline in PD (dementia, adjusted hazard ratio in the highest quintile [aHR-Q5] 2.8 [95% CI 1.6-5.0]; Hoehn and Yahr stage IV, aHR-Q5 2.1 [95% CI 1.1-4.0]).

DISCUSSION

By integrating high-throughput proteomics with machine learning, we identified PD-associated CSF proteomic signatures crucial for PD development and progression.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov (NCT01176565). A link to the trial registry page is clinicaltrials.gov/ct2/show/NCT01141023.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that the CSF proteome contains clinically important information regarding the development and progression of Parkinson disease that can be deciphered by a combination of high-throughput proteomics and machine learning.

Genome-wide Analysis of Motor Progression in Parkinson Disease

Background and Objectives

The genetic basis of Parkinson disease (PD) motor progression is largely unknown. Previous studies of the genetics of PD progression have included small cohorts and shown a limited overlap with genetic PD risk factors from case-control studies. Here, we have studied genomic variation associated with PD motor severity and early-stage progression in large longitudinal cohorts to help to define the biology of PD progression and potential new drug targets.

Methods

We performed a GWAS meta-analysis of early PD motor severity and progression up to 3 years from study entry. We used linear mixed-effect models with additive effects, corrected for age at diagnosis, sex, and the first 5 genetic principal components to assess variability in axial, limb, and total Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) III scores.

Results

We included 3,572 unrelated European ancestry patients with PD from 5 observational cohorts and 1 drug trial. The average AAO was 62.6 years (SD = 9.83), and 63% of participants were male. We found an average increase in the total MDS-UPDRS III score of 2.3 points/year. We identified an association between PD axial motor progression and variation at the GJA5 locus at 1q12 (β = -0.25, SE = 0.04, p = 3.4e-10). Exploration of the regulation of gene expression in the region (cis-expression quantitative trait loci [eQTL] analysis) showed that the lead variant was associated with expression of ACP6, a lysophosphatidic acid phosphatase that regulates mitochondrial lipid biosynthesis (cis-eQTL p-values in blood and brain RNA expression data sets: <10-14 in eQTLGen and 10-7 in PsychEncode).

Discussion

Our study highlights the potential role of mitochondrial lipid homeostasis in the progression of PD, which may be important in establishing new drug targets that might modify disease progression.

Mitochondrial Dynamics in Neurodegenerative Diseases: Unraveling the Role of Fusion and Fission Processes

Neurodegenerative diseases (NDs) are a diverse group of disorders characterized by the progressive degeneration and death of neurons, leading to a range of neurological symptoms. Despite the heterogeneity of these conditions, a common denominator is the implication of mitochondrial dysfunction in their pathogenesis. Mitochondria play a crucial role in creating biomolecules, providing energy through adenosine triphosphate (ATP) generated by oxidative phosphorylation (OXPHOS), and producing reactive oxygen species (ROS). When they're not functioning correctly, becoming fragmented and losing their membrane potential, they contribute to these diseases. In this review, we explore how mitochondria fuse and undergo fission, especially in the context of NDs. We discuss the genetic and protein mutations linked to these diseases and how they impact mitochondrial dynamics. We also look at the key regulatory proteins in fusion (MFN1, MFN2, and OPA1) and fission (DRP1 and FIS1), including their post-translational modifications. Furthermore, we highlight potential drugs that can influence mitochondrial dynamics. By unpacking these complex processes, we aim to direct research towards treatments that can improve life quality for people with these challenging conditions.

LRRK2 and Parkinson's disease: from genetics to targeted therapy

LRRK2 variants are implicated in both familial and sporadic PD. LRRK2-PD has a generally benign clinical presentation and variable pathology, with inconsistent presence of Lewy bodies and marked Alzheimer's disease pathology. The mechanisms underlying LRRK2-PD are still unclear, but inflammation, vesicle trafficking, lysosomal homeostasis, and ciliogenesis have been suggested, among others. As novel therapies targeting LRRK2 are under development, understanding the role and function of LRRK2 in PD is becoming increasingly important. Here, we outline the epidemiological, pathophysiological, and clinical features of LRRK2-PD, and discuss the arising therapeutic approaches targeting LRRK2 and possible future directions for research.

The contributions of mitochondrial and nuclear mitochondrial genetic variation to neuroticism

Neuroticism is a heritable trait composed of separate facets, each conferring different levels of protection or risk, to health. By examining mitochondrial DNA in 269,506 individuals, we show mitochondrial haplogroups explain 0.07-0.01% of variance in neuroticism and identify five haplogroup and 15 mitochondria-marker associations across a general factor of neuroticism, and two special factors of anxiety/tension, and worry/vulnerability with effect sizes of the same magnitude as autosomal variants. Within-haplogroup genome-wide association studies identified H-haplogroup-specific autosomal effects explaining 1.4% variance of worry/vulnerability. These H-haplogroup-specific autosomal effects show a pleiotropic relationship with cognitive, physical and mental health that differs from that found when assessing autosomal effects across haplogroups. We identify interactions between chromosome 9 regions and mitochondrial haplogroups at P < 5 × 10-8, revealing associations between general neuroticism and anxiety/tension with brain-specific gene co-expression networks. These results indicate that the mitochondrial genome contributes toward neuroticism and the autosomal links between neuroticism and health.

Potential Protective Link Between Type I Diabetes and Parkinson's Disease Risk and Progression

BACKGROUND

Epidemiological studies suggested an association between Parkinson's disease (PD) and type 2 diabetes, but less is known about type 1 diabetes (T1D) and PD.

OBJECTIVE

This study sought to explore the association between T1D and PD.

METHODS

We used Mendelian randomization, linkage disequilibrium score regression, and multi-tissue transcriptome-wide analysis to examine the association between PD and T1D.

RESULTS

Mendelian randomization showed a potentially protective role of T1D for PD risk (odds ratio [OR], 0.97; 95% confidence interval [CI], 0.94-0.99; P = 0.039), as well as motor (OR, 0.94; 95% CI, 0.88-0.99; P = 0.044) and cognitive progression (OR, 1.50; 95% CI, 1.08-2.09; P = 0.015). We further found a negative genetic correlation between T1D and PD (rg = -0.17; P = 0.016), and we identified eight genes in cross-tissue transcriptome-wide analysis that were associated with both traits.

CONCLUSIONS

Our results suggest a potential genetic link between T1D and PD risk and progression. Larger comprehensive epidemiological and genetic studies are required to validate our findings. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Genetic analysis of the LRP10 gene in Chinese patients with Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is a neurodegenerative disorder characterized by resting tremor, bradykinesia, muscle rigidity, and abnormal gait. The low-density lipoprotein receptor-related protein 10 (LRP10) was recently shown to be a causal gene for PD, and different ethnic cohorts have distinct frequencies and spectrum of LRP10 variants.

METHODS

We sequenced the full coding regions and exon-intron boundaries of LRP10 in 129 patients with sporadic Chinese PD to further investigate the connection of LRP10 with PD in a sample of Chinese patients.

RESULTS

In this study, we identified four potentially pathogenic mutations, including one novel mutation of p.Gly328Asp and three known mutations of p.Cys165Tyr, p.Arg230Trp, and p.Arg661His in four of the 129 Chinese patients with PD.

CONCLUSION

According to our study, the LRP10 gene may attribute to PD pathogenesis.

Genetic mechanism vs genetic subtypes: The example of GBA

Genetic variants in GBA, encoding the lysosomal enzyme glucocerebrosidase (GCase), are common risk factors for Parkinson's disease (PD). Genotype-phenotype studies have demonstrated that different types of GBA variants have differential effects on the phenotype. Variants could be classified as mild or severe depending on the type of Gaucher disease they cause in the biallelic state. It was shown that severe GBA variants, as compared to mild variants, are associated with higher risk of PD, earlier age at onset, and faster progression of motor and nonmotor symptoms. The observed difference in phenotype might be caused by a diversity of cellular mechanisms related to the particular variants. The lysosomal function of GCase is thought to play a significant role in the development of GBA-associated PD, and other mechanisms such as endoplasmic reticulum retention, mitochondrial dysfunction, and neuroinflammation have also been suggested. Moreover, genetic modifiers such as LRRK2, TMEM175, SNCA, and CTSB can either affect GCase activity or modulate risk and age at onset of GBA-associated PD. To achieve ideal outcomes with precision medicine, therapies will have to be tailored to individuals with specific variants, potentially in combination with known modifiers.

Association of GBA genotype with motor and cognitive decline in Chinese Parkinson's disease patients

Objective

Variants in the glucocerebrosidase (GBA) gene are the most common and significant risk factor for Parkinson's disease (PD). However, the impact of GBA variants on PD disease progression in the Chinese population remains unclear. This study aimed to explore the significance of GBA status on motor and cognitive impairment in a longitudinal cohort of Chinese patients with PD.

Methods

The entire GBA gene was screened by long-range polymerase chain reaction (LR-PCR) and next generation sequencing (NGS). A total of 43 GBA-related PD (GBA-PD) and 246 non-GBA-mutated PD (NM-PD) patients with complete clinical data at baseline and at least one follow-up were recruited for this study. The associations of GBA genotype with rate of motor and cognitive decline, as measured by Unified PD Rating Scale (UPDRS) motor and Montreal Cognitive Assessment (MoCA), were assessed by linear mixed-effect models.

Results

The estimated (standard error, SE) UPDRS motor [2.25 (0.38) points/year] and MoCA [-0.53 (0.11) points/year] progression rates in the GBA-PD group were significantly faster than those in the NM-PD group [1.35 (0.19); -0.29 (0.04) points/year; respectively]. In addition, the GBA-PD group showed significantly faster estimated (SE) bradykinesia [1.04 (0.18) points/year], axial impairment [0.38 (0.07) points/year], and visuospatial/executive [-0.15 (0.03) points/year] progression rates than the NM-PD group [0.62 (0.10); 0.17 (0.04); -0.07 (0.01) points/year; respectively].

Conclusion

GBA-PD is associated with faster motor and cognitive decline, specifically greater disability in terms of bradykinesia, axial impairment, and visuospatial/executive function. Better understanding of GBA-PD progression may help predict prognosis and improve clinical trial design.

Functionally Validating Evolutionary Conserved Risk Genes for Parkinson's Disease in Drosophila melanogaster

Parkinson's disease (PD) is a heterogeneous and complex neurodegenerative disorder and large-scale genetic studies have identified >130 genes associated with PD. Although genomic studies have been decisive for our understanding of the genetic contributions underlying PD, these associations remain as statistical associations. Lack of functional validation limits the biological interpretation; however, it is labour extensive, expensive, and time consuming. Therefore, the ideal biological system for functionally validating genetic findings must be simple. The study aim was to assess systematically evolutionary conserved PD-associated genes using Drosophila melanogaster. From a literature review, a total of 136 genes have found to be associated with PD in GWAS studies, of which 11 are strongly evolutionary conserved between Homo sapiens and D. melanogaster. By ubiquitous gene expression knockdown of the PD-genes in D. melanogaster, the flies' escape response was investigated by assessing their negative geotaxis response, a phenotype that has previously been used to investigate PD in D. melanogaster. Gene expression knockdown was successful in 9/11 lines, and phenotypic consequences were observed in 8/9 lines. The results provide evidence that genetically modifying expression levels of PD genes in D. melanogaster caused reduced climbing ability of the flies, potentially supporting their role in dysfunctional locomotion, a hallmark of PD.

Mitochondrial haplogroups and cognitive progression in Parkinson's disease

Mitochondria are a culprit in the onset of Parkinson's disease, but their role during disease progression is unclear. Here we used Cox proportional hazards models to exam the effect of variation in the mitochondrial genome on longitudinal cognitive and motor progression over time in 4064 patients with Parkinson's disease. Mitochondrial macro-haplogroup was associated with reduced risk of cognitive disease progression in the discovery and replication population. In the combined analysis, patients with the super macro-haplogroup J, T, U# had a 41% lower risk of cognitive progression with P = 2.42 × 10-6 compared to those with macro-haplogroup H. Exploratory analysis indicated that the common mitochondrial DNA variant, m.2706A>G, was associated with slower cognitive decline with a hazard ratio of 0.68 (95% confidence interval 0.56-0.81) and P = 2.46 × 10-5. Mitochondrial haplogroups were not appreciably linked to motor progression. This initial genetic survival study of the mitochondrial genome suggests that mitochondrial haplogroups may be associated with the pace of cognitive progression in Parkinson's disease over time.

Predictors of cognitive impairment in newly diagnosed Parkinson's disease with normal cognition at baseline: A 5-year cohort study

Background and objective

Cognitive impairment (CI) is a substantial contributor to the disability associated with Parkinson's disease (PD). We aimed to assess the clinical features and explore the underlying biomarkers as predictors of CI in patients with newly diagnosed PD (NDPD; less than 2 years).

Methods

We evaluated the cognitive function status using the Montreal Cognitive Assessment (MoCA) and a battery of neuropsychological tests at baseline and subsequent annual follow-up for 5 years from the Parkinson's Progression Markers Initiative (PPMI) database. We assessed the baseline clinical features, apolipoprotein (APO) E status, β-glucocerebrosidase (GBA) mutation status, cerebrospinal fluid findings, and dopamine transporter imaging results. Using a diagnosis of CI (combined mild cognitive impairment and dementia) developed during the 5-year follow-up as outcome measures, we assessed the predictive values of baseline clinical variables and biomarkers. We also constructed a predictive model for the diagnosis of CI using logistic regression analysis.

Results

A total of 409 patients with NDPD with 5-year follow-up were enrolled, 232 with normal cognitive function at baseline, and 94 patients developed CI during the 5-year follow-up. In multivariate analyses, age, current diagnosis of hypertension, baseline MoCA scores, Movement disorder society Unified PD Rating Scale part III (MDS-UPDRS III) scores, and APOE status were associated with the development of CI. Predictive accuracy of CI using age alone improved by the addition of clinical variables and biomarkers (current diagnosis of hypertension, baseline MoCA scores, and MDS-UPDRS III scores, APOE status; AUC 0.80 [95% CI 0.74-0.86] vs. 0.71 [0.64-0.77], p = 0.008). Cognitive domains that had higher frequencies of impairment were found in verbal memory (12.6 vs. 16.8%) and attention/processing speed (12.7 vs. 16.9%), however, no significant difference in the prevalence of CI at annual follow-up was found during the 5-year follow-up in NDPD patients.

Conclusion

In NDPD, the development of CI during the 5-year follow-up can be predicted with good accuracy using a model combining age, current diagnosis of hypertension, baseline MoCA scores, MDS-UPDRS III scores, and APOE status. Our study underscores the need for the earlier identification of CI in NDPD patients in our clinical practice.

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.

Association between Parkinson's Disease and Diabetes Mellitus: From Epidemiology, Pathophysiology and Prevention to Treatment

Diabetes mellitus (DM) and Parkinson's disease (PD) are both age-related diseases of global concern being among the most common chronic metabolic and neurodegenerative diseases, respectively. While both diseases can be genetically inherited, environmental factors play a vital role in their pathogenesis. Moreover, DM and PD have common underlying molecular mechanisms, such as misfolded protein aggregation, mitochondrial dysfunction, oxidative stress, chronic inflammation, and microbial dysbiosis. Recently, epidemiological and experimental studies have reported that DM affects the incidence and progression of PD. Moreover, certain antidiabetic drugs have been proven to decrease the risk of PD and delay its progression. In this review, we elucidate the epidemiological and pathophysiological association between DM and PD and summarize the antidiabetic drugs used in animal models and clinical trials of PD, which may provide reference for the clinical translation of antidiabetic drugs in PD treatment.

Genetic architecture of Parkinson’s disease subtypes – Review of the literature

The heterogeneity of Parkinson’s disease (PD) has been recognized since its description by James Parkinson over 200 years ago. The complexity of motor and non-motor PD manifestations has led to many attempts of PD subtyping with different prognostic outcomes; however, the pathophysiological foundations of PD heterogeneity remain elusive. Genetic contributions to PD may be informative in understanding the underpinnings of PD subtypes. As such, recognizing genotype-phenotype associations may be crucial for successful gene therapy. We review the state of knowledge on the genetic architecture underlying PD subtypes, discussing the monogenic forms, as well as oligo- and polygenic risk factors associated with various PD subtypes. Based on our review, we argue for the unification of PD subtyping classifications, the dichotomy of studies on genetic factors and genetic modifiers of PD, and replication of results from previous studies.

Changes in dynamic transitions between integrated and segregated states underlie visual hallucinations in Parkinson's disease

Hallucinations are a core feature of psychosis and common in Parkinson's. Their transient, unexpected nature suggests a change in dynamic brain states, but underlying causes are unknown. Here, we examine temporal dynamics and underlying structural connectivity in Parkinson's-hallucinations using a combination of functional and structural MRI, network control theory, neurotransmitter density and genetic analyses. We show that Parkinson's-hallucinators spent more time in a predominantly Segregated functional state with fewer between-state transitions. The transition from integrated-to-segregated state had lower energy cost in Parkinson's-hallucinators; and was therefore potentially preferable. The regional energy needed for this transition was correlated with regional neurotransmitter density and gene expression for serotoninergic, GABAergic, noradrenergic and cholinergic, but not dopaminergic, receptors. We show how the combination of neurochemistry and brain structure jointly shape functional brain dynamics leading to hallucinations and highlight potential therapeutic targets by linking these changes to neurotransmitter systems involved in early sensory and complex visual processing.

Opicapone, a Novel Catechol-O-methyl Transferase Inhibitor, for Treatment of Parkinson's Disease "Off" Episodes

Parkinson's Disease (PD) is a common neurodegenerative disorder and the leading cause of disability. It causes significant morbidity and disability through a plethora of symptoms, including movement disorders, sleep disturbances, and cognitive and psychiatric symptoms. The traditional pathogenesis theory of PD involves the loss of dopaminergic neurons in the substantia nigra (SN). Classically, treatment is pursued with an assortment of medications that are directed at overcoming this deficiency with levodopa being central to most treatment plans. Patients taking levodopa tend to experience "off episodes" with decreasing medication levels, causing large fluctuations in their symptoms. These off episodes are disturbing and a source of morbidity for these patients. Opicapone is a novel, peripherally acting Catechol-O-methyl transferase (COMT) inhibitor that is used as adjunctive therapy to carbidopa/levodopa for treatment and prevention of "off episodes." It has been approved for use as an adjunct to levodopa since 2016 in Europe and has recently (April 2020) gained FDA approval for use in the USA. By inhibiting COMT, opicapone slows levodopa metabolism and increases its availability. Several clinical studies demonstrated significant improvement in treatment efficacy and reduction in duration of "off episodes." The main side effect demonstrated was dyskinesia, mostly with the 100mg dose, which is higher than the approved, effective dose of 50mg. Post-marketing surveillance and analysis are required to further elucidate its safety profile and contribute to patient selection. This paper reviews the seminal and latest evidence in the treatment of PD "off episodes" with the novel drug Opicapone, including efficacy, safety, and clinical indications.

Glucocerebrosidase variant T369M is not a risk factor for Parkinson's disease in Sweden

INTRODUCTION

Genetic variants in the Beta-glucocerebrosidase gene (GBA1) is a known risk factor for Parkinson's disease. The GBA1 mutations L444P, N370S and many other have been shown to associate with the disease in populations with diverse background. Some GBA1 polymorphisms have a less pronounced effect, and their pathogenicity has been debated. We have previously found associations with L444P, N370S and E326K and Parkinson's disease in Sweden.

METHOD

In this study we used pyrosequencing to genotype the T369M variant in a large Swedish cohort consisting of 1,131 patients with idiopathic Parkinson's disease, and 1,594 control subjects to evaluate the possibility of this variant conferring an increased risk for Parkinson's disease.

RESULTS

The minor allele frequency was 2.15% in patients and 1.76% in controls. Statistical analysis showed that there was no significant difference in allele frequency between patients and control subjects, p-value 0.37, Odds Ratio 1.23 with a 95% confidence interval of 0.82-1.83.

CONCLUSION

Our results suggest that T369M is not a risk factor for Parkinson's disease in the Swedish population.

Current Progress in Aptasensor for Ultra-Low Level Monitoring of Parkinson's Disease Biomarkers

In today's world, Parkinson's disease (PD) has been introduced as a long-term degenerative disorder of the central nervous system which mainly affects approximately more than ten million people worldwide. The vast majority of diagnostic methods for PD have operated based on conventional sensing platforms, while the traditional laboratory tests are not efficient for diagnosis of PD in the early stage due to symptoms of this common neurodegenerative syndrome starting slowly. The advent of the aptasensor has revolutionized the early-stage diagnosis of PD by measuring related biomarkers due to the myriad advantages of originating from aptamers which can be able to sensitive and selective capture various types of related biomarkers. The progress of numerous sensing platforms and methodologies in terms of biosensors based on aptamer application for PD diagnosis has revealed promising results. In this review, we present the latest developments in myriad types of aptasensors for the determination of related PD biomarkers. Working strategies, advantages and limitations of these sensing approaches are also mentioned, followed by prospects and challenges.

Green Tea Intake and Parkinson's Disease Progression: A Mendelian Randomization Study

Epidemiological studies have suggested green tea intake was associated with a reduced risk of Parkinson's disease (PD). However, whether green tea intake has an effect on PD progression is unknown. To evaluate the role of green tea intake in PD progression, we conducted a two-sample Mendelian randomization analysis using summary statistics from genome-wide association studies of green tea intake (N = 64,949), age at onset (N = 28,568) and progression (N = 4,093) of PD. One standard deviation increase in genetically determined green tea intake was significantly associated with slower progression to dementia (OR: 0.87, 95% CI: 0.81-0.94, P: 3.48E-04) after the Bonferroni correction. Meanwhile, higher green tea intake was nominally associated with slower progression to depression, and lower risk of dementia, depression, hyposmia and insomnia at baseline. The results were robust under all sensitivity analyses. These results might facilitate novel therapeutic targets to slow down the progression of PD in clinical trials, and have clinical implications for patients with PD.

APOE4 exacerbates α-synuclein seeding activity and contributes to neurotoxicity in Alzheimer's disease with Lewy body pathology

Approximately half of Alzheimer's disease (AD) brains have concomitant Lewy pathology at autopsy, suggesting that α-synuclein (α-SYN) aggregation is a regulated event in the pathogenesis of AD. Genome-wide association studies revealed that the ε4 allele of the apolipoprotein E (APOE4) gene, the strongest genetic risk factor for AD, is also the most replicated genetic risk factor for Lewy body dementia (LBD), signifying an important role of APOE4 in both amyloid-β (Aβ) and α-SYN pathogenesis. How APOE4 modulates α-SYN aggregation in AD is unclear. In this study, we aimed to determine how α-SYN is associated with AD-related pathology and how APOE4 impacts α-SYN seeding and toxicity. We measured α-SYN levels and their association with other established AD-related markers in brain samples from autopsy-confirmed AD patients (N = 469), where 54% had concomitant LB pathology (AD + LB). We found significant correlations between the levels of α-SYN and those of Aβ40, Aβ42, tau and APOE, particularly in insoluble fractions of AD + LB. Using a real-time quaking-induced conversion (RT-QuIC) assay, we measured the seeding activity of soluble α-SYN and found that α-SYN seeding was exacerbated by APOE4 in the AD cohort, as well as a small cohort of autopsy-confirmed LBD brains with minimal Alzheimer type pathology. We further fractionated the soluble AD brain lysates by size exclusion chromatography (SEC) ran on fast protein liquid chromatography (FPLC) and identified the α-SYN species (~ 96 kDa) that showed the strongest seeding activity. Finally, using human induced pluripotent stem cell (iPSC)-derived neurons, we showed that amplified α-SYN aggregates from AD + LB brain of patients with APOE4 were highly toxic to neurons, whereas the same amount of α-SYN monomer was not toxic. Our findings suggest that the presence of LB pathology correlates with AD-related pathologies and that APOE4 exacerbates α-SYN seeding activity and neurotoxicity, providing mechanistic insight into how APOE4 affects α-SYN pathogenesis in AD.

Genetics of cognitive dysfunction in Parkinson's disease

Presentation and progression of cognitive symptoms in Parkinson's disease are highly variable. PD is a genetically complex disorder with multiple genetic risk factors and understanding the role that genes play in cognitive outcomes is important for patient counseling and treatment. Currently, there are seven well-described genes that increase the risk for PD, with variable levels of penetrance: SNCA, LRRK2, VPS35, PRKN, PINK1, DJ1 and GBA. In addition, large, genome-wide association studies have identified multiple loci in our DNA which increase PD risk. In this chapter, we summarize what is currently known about each of the seven strongly-associated PD genes and select PD risk variants, including PITX3, TMEM106B, SNCA Rep1, APOɛ4, COMT and MAPT H1/H1, along with their respective relationships to cognition.

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.

Genetic Stratification of Age-Dependent Parkinson's Disease Risk by Polygenic Hazard Score

BACKGROUND

Parkinson's disease (PD) is a highly age-related disorder, where common genetic risk variants affect both disease risk and age at onset. A statistical approach that integrates these effects across all common variants may be clinically useful for individual risk stratification. A polygenic hazard score methodology, leveraging a time-to-event framework, has recently been successfully applied in other age-related disorders.

OBJECTIVES

We aimed to develop and validate a polygenic hazard score model in sporadic PD.

METHODS

Using a Cox regression framework, we modeled the polygenic hazard score in a training data set of 11,693 PD patients and 9841 controls. The score was then validated in an independent test data set of 5112 PD patients and 5372 controls and a small single-study sample of 360 patients and 160 controls.

RESULTS

A polygenic hazard score predicts the onset of PD with a hazard ratio of 3.78 (95% confidence interval 3.49-4.10) when comparing the highest to the lowest risk decile. Combined with epidemiological data on incidence rate, we apply the score to estimate genetically stratified instantaneous PD risk across age groups.

CONCLUSIONS

We demonstrate the feasibility of a polygenic hazard approach in PD, integrating the genetic effects on disease risk and age at onset in a single model. In combination with other predictive biomarkers, the approach may hold promise for risk stratification in future clinical trials of disease-modifying therapies, which aim at postponing the onset of PD. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

A Critical Analysis of Intestinal Enteric Neuron Loss and Constipation in Parkinson's Disease

Constipation afflicts many patients with Parkinson's disease (PD) and significantly impacts on patient quality of life. PD-related constipation is caused by intestinal dysfunction, but the etiology of this dysfunction in patients is unknown. One possible cause is neuron loss within the enteric nervous system (ENS) of the intestine. This review aims to 1) Critically evaluate the evidence for and against intestinal enteric neuron loss in PD patients, 2) Justify why PD-related constipation must be objectively measured, 3) Explore the potential link between loss of enteric neurons in the intestine and constipation in PD, 4) Provide potential explanations for disparities in the literature, and 5) Outline data and study design considerations to improve future research. Before the connection between intestinal enteric neuron loss and PD-related constipation can be confidently described, future research must use sufficiently large samples representative of the patient population (majority diagnosed with idiopathic PD for at least 5 years), implement a consistent neuronal quantification method and study design, including standardized patient recruitment criteria, objectively quantify intestinal dysfunctions, publish with a high degree of data transparency and account for potential PD heterogeneity. Further investigation into other potential influencers of PD-related constipation is also required, including changes in the function, connectivity, mitochondria and/or α-synuclein proteins of enteric neurons and their extrinsic innervation. The connection between enteric neuron loss and other PD-related gastrointestinal (GI) issues, including gastroparesis and dysphagia, as well as changes in nutrient absorption and the microbiome, should be explored in future research.