Baseline genetic associations in the Parkinson's Progression Markers Initiative (PPMI)

Predictors of the Rapid Progression in Prodromal Parkinson's Disease: A Longitudinal Follow-Up Study

INTRODUCTION

Parkinson's disease (PD) is characterized by a prodromal phase preceding the onset of classic motor symptoms. The duration and clinical manifestations of prodromal PD vary widely, indicating underlying heterogeneity within this stage. This discrepancy prompts the question of whether specific factors contribute to the divergent rates of progression in prodromal PD.

METHODS

This study included prodromal PD patients from the Parkinson's progression marker initiative. They were followed up to assess the disease progression. The data collected during the follow-up period were analyzed to identify potential predictors of rapid disease progression in prodromal PD.

RESULTS

In this study, 61 individuals with prodromal PD were enrolled. Among them, 43 patients presented with both RBD and hyposmia, 17 had hyposmia alone, and 1 had RBD alone at baseline. 13 (21.3%) prodromal PD participants exhibited rapid disease progression, with two of these cases advancing to non-neurological diseases. Significant differences were observed between the rapid progression group and no rapid progression group in terms of MDS-UPDRS II score and UPSIT score. Longitudinal analysis showed a significant increase in the MDS-UPDRS III score and MDS-UPDRS total score in the rapid progression group. Regression analyses identified the MDS-UPDRS II score and UPSIT score as predictors of rapid disease progression in prodromal PD.

CONCLUSION

Our study findings suggest that the MDS-UPDRS II score and UPSIT score may serve as clinical markers associated with rapid disease progression. Further research and development of precise biomarkers and advanced assessment methods are needed to enhance our understanding of prodromal PD and its progression patterns.

Association of Family History and Polygenic Risk Score With Longitudinal Prognosis in Parkinson Disease

Background and Objectives

Evidence suggests that either family history or polygenic risk score (PRS) is associated with developing Parkinson disease (PD). However, little is known about the longitudinal prognosis of PD according to family history and higher PRS.

Methods

From the Parkinson's Progression Markers Initiative database, 395 patients with PD who followed up for more than 2 years were grouped into those with family history within first-degree, second-degree, and third-degree relatives (N = 127 [32.2%]) vs those without (N = 268 [67.8%]). The PRS of 386 patients was computed using whole-genome sequencing data. Longitudinal assessment of motor, cognition, and imaging based on dopaminergic degeneration was conducted during the regular follow-up period. Effects of family history, PRS, or both on longitudinal changes of cognition, motor severity, and nigrostriatal degeneration were tested using a linear mixed model. The risk of freezing of gait (FOG) according to family history was assessed using the Kaplan-Meier analysis and Cox regression models.

Results

During a median follow-up of 9.1 years, PD with positive family history showed a slower decline of caudate dopamine transporter uptake (β estimate of family history × time = 0.02, 95% CI = 0.002-0.036, p = 0.027). Family history of PD and higher PRS were independently associated with a slower decline of Montreal Cognitive Assessment (β estimate of family history × time = 0.12, 95% CI = 0.02-0.22, p = 0.017; β estimate of PRS × time = 0.09, 95% CI = 0.03-0.16, p = 0.006). In those 364 patients without FOG at baseline, PD with positive family history had a lower risk of FOG (hazard ratio of family history = 0.57, 95% CI = 0.38-0.84, p = 0.005).

Discussion

Having a family history of PD predicts slower progression of cognitive decline and caudate dopaminergic degeneration, and less FOG compared with those without a family history independent of PRS. Taken together, information on family history could be used as a proxy for the clinical heterogeneity of PD.

Trial Registration Information

The study was registered at clinicaltrials.gov (NCT01141023), and the enrollment began June 1, 2010.

A mitochondrial inside-out iron-calcium signal reveals drug targets for Parkinson's disease

Dysregulated iron or Ca2+ homeostasis has been reported in Parkinson's disease (PD) models. Here, we discover a connection between these two metals at the mitochondria. Elevation of iron levels causes inward mitochondrial Ca2+ overflow, through an interaction of Fe2+ with mitochondrial calcium uniporter (MCU). In PD neurons, iron accumulation-triggered Ca2+ influx across the mitochondrial surface leads to spatially confined Ca2+ elevation at the outer mitochondrial membrane, which is subsequently sensed by Miro1, a Ca2+-binding protein. A Miro1 blood test distinguishes PD patients from controls and responds to drug treatment. Miro1-based drug screens in PD cells discover Food and Drug Administration-approved T-type Ca2+-channel blockers. Human genetic analysis reveals enrichment of rare variants in T-type Ca2+-channel subtypes associated with PD status. Our results identify a molecular mechanism in PD pathophysiology and drug targets and candidates coupled with a convenient stratification method.

Two distinct trajectories of clinical and neurodegeneration events in Parkinson's disease

Increasing evidence suggests that Parkinson's disease (PD) exhibits disparate spatial and temporal patterns of progression. Here we used a machine-learning technique-Subtype and Stage Inference (SuStaIn) - to uncover PD subtypes with distinct trajectories of clinical and neurodegeneration events. We enrolled 228 PD patients and 119 healthy controls with comprehensive assessments of olfactory, autonomic, cognitive, sleep, and emotional function. The integrity of substantia nigra (SN), locus coeruleus (LC), amygdala, hippocampus, entorhinal cortex, and basal forebrain were assessed using diffusion and neuromelanin-sensitive MRI. SuStaIn model with above clinical and neuroimaging variables as input was conducted to identify PD subtypes. An independent dataset consisting of 153 PD patients and 67 healthy controls was utilized to validate our findings. We identified two distinct PD subtypes: subtype 1 with rapid eye movement sleep behavior disorder (RBD), autonomic dysfunction, and degeneration of the SN and LC as early manifestations, and cognitive impairment and limbic degeneration as advanced manifestations, while subtype 2 with hyposmia, cognitive impairment, and limbic degeneration as early manifestations, followed later by RBD and degeneration of the LC in advanced disease. Similar subtypes were shown in the validation dataset. Moreover, we found that subtype 1 had weaker levodopa response, more GBA mutations, and poorer prognosis than subtype 2. These findings provide new insights into the underlying disease biology and might be useful for personalized treatment for patients based on their subtype.

The systematic comparison between Gaussian mirror and Model-X knockoff models

While the high-dimensional biological data have provided unprecedented data resources for the identification of biomarkers, consensus is still lacking on how to best analyze them. The recently developed Gaussian mirror (GM) and Model-X (MX) knockoff-based methods have much related model assumptions, which makes them appealing for the detection of new biomarkers. However, there are no guidelines for their practical use. In this research, we systematically compared the performance of MX-based and GM methods, where the impacts of the distribution of explanatory variables, their relatedness and the signal-to-noise ratio were evaluated. MX with knockoff generated using the second-order approximates (MX-SO) has the best performance as compared to other MX-based methods. MX-SO and GM have similar levels of power and computational speed under most of the simulations, but GM is more robust in the control of false discovery rate (FDR). In particular, MX-SO can only control the FDR well when there are weak correlations among explanatory variables and the sample size is at least moderate. On the contrary, GM can have the desired FDR as long as explanatory variables are not highly correlated. We further used GM and MX-based methods to detect biomarkers that are associated with the Alzheimer's disease-related PET-imaging trait and the Parkinson's disease-related T-tau of cerebrospinal fluid. We found that MX-based and GM methods are both powerful for the analysis of big biological data. Although genes selected from MX-based methods are more similar as compared to those from the GM method, both MX-based and GM methods can identify the well-known disease-associated genes for each disease. While MX-based methods can have a slightly higher power than that of the GM method, it is less robust, especially for data with small sample sizes, unknown distributions, and high correlations.

Impact of GBA variants on longitudinal freezing of gait progression in early Parkinson's disease

BACKGROUND

Freezing of gait (FOG) is a common disabling gait disturbance among patients with Parkinson's disease (PD), but the influence of genetic variants on the incidence of FOG has been poorly studied to date.

OBJECTIVES

We aimed to evaluate the association of GBA variants with the risk of FOG development in a large early PD cohort.

METHODS

This study included 371 early PD patients from the Parkinson's Progression Markers Initiative (PPMI) who were divided into a GBA variant carrier group (GBA-PD group, n = 44) and an idiopathic PD group without GBA variants (iPD group, n = 327). They were followed up for up to 5 years to examine the progression of FOG. The cumulative incidence of FOG and risk factors for FOG were assessed using Kaplan‒Meier and Cox regression analyses.

RESULTS

At baseline, the GBA-PD group had lower CSF β-amyloid 1-42 (Aβ₄₂) levels and more severe motor and nonmotor symptoms than the iPD group. During the 5-year follow-up, the GBA-PD group had a higher incidence of FOG than the iPD group, and the FOG progression rate was related to GBA variant severity. In the multivariable Cox model without CSF Aβ₄₂, GBA variants were significant predictors of future FOG, and the association remained significant after adding CSF Aβ₄₂ to the model. In the subgroup analyses, the effect of GBA variants was not observed in the "low-level" group. However, in the "high-level" group, GBA variants independently increased the risk of FOG, and this association was stronger than the association with CSF Aβ₄₂.

CONCLUSION

GBA variants are novel genetic risk factors for future FOG development in early PD patients. This association seemed to be mediated by both Aβ-dependent pathways and Aβ-independent pathways.

Age-Related Association Between APOE ɛ4 and Cognitive Progression in de novo Parkinson's Disease

BACKGROUND

APOE ɛ4 genotype was correlated with exacerbation of pathology and higher risk of dementia in Parkinson's disease (PD). Meanwhile, the differential influence of APOE ɛ4 on cognition in young and old individuals interpreted as antagonistic pleiotropy.

OBJECTIVE

To examine whether the effect of APOE ɛ4 on cognitive progression in de novo PD is age dependent.

METHODS

In this study, 613 de novo PD patients were recruited from Parkinson's Progression Markers Initiative (PPMI). To examine the age-dependent relationship between APOE ɛ4 and cognitive changes, we added 3-way interaction of APOE ɛ4*baseline age*time to the linear mixed-effect (LME) models and evaluated the specific roles of APOE ɛ4 in the middle age group and elderly group separately. Cox regression was utilized to examine the progression of cognition in age-stratified PD participants.

RESULTS

Age significantly modified relationship between APOE ɛ4 and cognitive changes in most cognitive domains (pinteraction <0.05). In the elderly group, APOE ɛ4 carriers showed steeper decline in global cognition (p = 0.001) as well as in most cognitive domains, and they had a greater risk of cognitive progression (adjusted HR 1.625, 95% CI 1.143-2.310, p = 0.007), compared with non-carriers. However, in the middle age group, no significant relationships between APOE ɛ4 and cognitive decline can be detected.

CONCLUSION

Our results indicated that the APOE ɛ4 allele has an age-dependent effect on cognitive decline in PD patients. The underlying mechanisms need to be investigated in the future.

Universal clinical Parkinson's disease axes identify a major influence of neuroinflammation

BACKGROUND

There is large individual variation in both clinical presentation and progression between Parkinson's disease patients. Generation of deeply and longitudinally phenotyped patient cohorts has enormous potential to identify disease subtypes for prognosis and therapeutic targeting.

METHODS

Replicating across three large Parkinson's cohorts (Oxford Discovery cohort (n = 842)/Tracking UK Parkinson's study (n = 1807) and Parkinson's Progression Markers Initiative (n = 472)) with clinical observational measures collected longitudinally over 5-10 years, we developed a Bayesian multiple phenotypes mixed model incorporating genetic relationships between individuals able to explain many diverse clinical measurements as a smaller number of continuous underlying factors ("phenotypic axes").

RESULTS

When applied to disease severity at diagnosis, the most influential of three phenotypic axes "Axis 1" was characterised by severe non-tremor motor phenotype, anxiety and depression at diagnosis, accompanied by faster progression in cognitive function measures. Axis 1 was associated with increased genetic risk of Alzheimer's disease and reduced CSF Aβ1-42 levels. As observed previously for Alzheimer's disease genetic risk, and in contrast to Parkinson's disease genetic risk, the loci influencing Axis 1 were associated with microglia-expressed genes implicating neuroinflammation. When applied to measures of disease progression for each individual, integration of Alzheimer's disease genetic loci haplotypes improved the accuracy of progression modelling, while integrating Parkinson's disease genetics did not.

CONCLUSIONS

We identify universal axes of Parkinson's disease phenotypic variation which reveal that Parkinson's patients with high concomitant genetic risk for Alzheimer's disease are more likely to present with severe motor and non-motor features at baseline and progress more rapidly to early dementia.

Machine learning-based prediction of cognitive outcomes in de novo Parkinson's disease

Cognitive impairment is a debilitating symptom in Parkinson's disease (PD). We aimed to establish an accurate multivariate machine learning (ML) model to predict cognitive outcome in newly diagnosed PD cases from the Parkinson's Progression Markers Initiative (PPMI). Annual cognitive assessments over an 8-year time span were used to define two cognitive outcomes of (i) cognitive impairment, and (ii) dementia conversion. Selected baseline variables were organized into three subsets of clinical, biofluid and genetic/epigenetic measures and tested using four different ML algorithms. Irrespective of the ML algorithm used, the models consisting of the clinical variables performed best and showed better prediction of cognitive impairment outcome over dementia conversion. We observed a marginal improvement in the prediction performance when clinical, biofluid, and epigenetic/genetic variables were all included in one model. Several cerebrospinal fluid measures and an epigenetic marker showed high predictive weighting in multiple models when included alongside clinical variables.

Multi-predictor modeling for predicting early Parkinson’s disease and non-motor symptoms progression

Background

Identifying individuals with high-risk Parkinson’s disease (PD) at earlier stages is an urgent priority to delay disease onset and progression. In the present study, we aimed to develop and validate clinical risk models using non-motor predictors to distinguish between early PD and healthy individuals. In addition, we constructed prognostic models for predicting the progression of non-motor symptoms [cognitive impairment, Rapid-eye-movement sleep Behavior Disorder (RBD), and depression] in de novo PD patients at 5 years of follow-up.

Methods

We retrieved the data from the Parkinson’s Progression Markers Initiative (PPMI) database. After a backward variable selection approach to identify predictors, logistic regression analyses were applied for diagnosis model construction, and cox proportional-hazards models were used to predict non-motor symptom progression. The predictive models were internally validated by correcting measures of predictive performance for “optimism” or overfitting with the bootstrap resampling approach.

Results

For constructing diagnostic models, the final model reached a high accuracy with an area under the curve (AUC) of 0.93 (95% CI: 0.91–0.96), which included eight variables (age, gender, family history, University of Pennsylvania Smell Inventory Test score, Montreal Cognitive Assessment score, RBD Screening Questionnaire score, levels of cerebrospinal fluid α-synuclein, and SNCA rs356181 polymorphism). For the construction of prognostic models, our results showed that the AUC of the three prognostic models improved slightly with increasing follow-up time. The overall AUCs fluctuated around 0.70. The model validation established good discrimination and calibration for predicting PD onset and progression of non-motor symptoms.

Conclusion

The findings of our study facilitate predicting the individual risk at an early stage based on the predictors derived from these models. These predictive models provide relatively reliable information to prevent PD onset and progression. However, future validation analysis is still needed to clarify these findings and provide more insight into the predictive models over more extended periods of disease progression in more diverse samples.

SNCA rs3910105 Is Associated With Development of Rapid Eye Movement Sleep Behavior Disorder in Parkinson’s Disease

Background and Purpose

Rapid eye movement (REM) Rapid eye movement sleep behavior disorder (RBD) is a common non-motor symptom of PD. However, the association between the SNCA rs3910105 genotype and RBD in Parkinson’s disease (PD) remains unclear.

Methods

This study used Parkinson’s Progression Markers Initiative (PPMI) data and included 270 patients with newly diagnosed PD without RBD who were divided into SNCA rs3910105 C carriers (CC+CT; n = 187) and TT carriers (n = 83). They were followed up for 5 years to identify the development of RBD. To investigate the influence of cerebrospinal fluid (CSF) alpha-synuclein (α-syn) and β-amyloid 1–42 (Aβ₄₂) in the association between rs3910105 and RBD, the patients were additionally classified into “high-level” and “low-level” groups using cutoff values for CSF α-syn and Aβ₄₂ levels.

Results

At baseline, the rs3910105 C allele group had lower CSF α-syn and Aβ₄₂ levels than the TT group. During the 5.0-year follow-up, the rs3910105 C allele group had a higher incidence of RBD than the TT group. In the subgroup analyses, the effect of the rs3910105 C allele was not found in the “low-level” group. However, in the “high-level” group, the rs3910105 C allele independently increased the risk of RBD.

Conclusion

The SNCA rs3910105 C allele might be a novel genetic risk factor for RBD development in PD, α-syn pathways might have a role in this association and more basic research would be needed to elucidate the mechanism in the future.

Parkinson Disease and Subthalamic Nucleus Deep Brain Stimulation: Cognitive Effects in GBA Mutation Carriers

OBJECTIVE

This study was undertaken to compare the rate of change in cognition between glucocerebrosidase (GBA) mutation carriers and noncarriers with and without subthalamic nucleus deep brain stimulation (STN-DBS) in Parkinson disease.

METHODS

Clinical and genetic data from 12 datasets were examined. Global cognition was assessed using the Mattis Dementia Rating Scale (MDRS). Subjects were examined for mutations in GBA and categorized as GBA carriers with or without DBS (GBA+DBS+, GBA+DBS-), and noncarriers with or without DBS (GBA-DBS+, GBA-DBS-). GBA mutation carriers were subcategorized according to mutation severity (risk variant, mild, severe). Linear mixed modeling was used to compare rate of change in MDRS scores over time among the groups according to GBA and DBS status and then according to GBA severity and DBS status.

RESULTS

Data were available for 366 subjects (58 GBA+DBS+, 82 GBA+DBS-, 98 GBA-DBS+, and 128 GBA-DBS- subjects), who were longitudinally followed (range = 36-60 months after surgery). Using the MDRS, GBA+DBS+ subjects declined on average 2.02 points/yr more than GBA-DBS- subjects (95% confidence interval [CI] = -2.35 to -1.69), 1.71 points/yr more than GBA+DBS- subjects (95% CI = -2.14 to -1.28), and 1.49 points/yr more than GBA-DBS+ subjects (95% CI = -1.80 to -1.18).

INTERPRETATION

Although not randomized, this composite analysis suggests that the combined effects of GBA mutations and STN-DBS negatively impact cognition. We advise that DBS candidates be screened for GBA mutations as part of the presurgical decision-making process. We advise that GBA mutation carriers be counseled regarding potential risks associated with STN-DBS so that alternative options may be considered. ANN NEUROL 2022;91:424-435.

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.

Predictors of Conversion to α-Synucleinopathy Diseases in Idiopathic Rapid Eye Movement Sleep Behavior Disorder

BACKGROUND

Idiopathic rapid eye movement sleep behavior disorder (iRBD) often precedes the development of α-synucleinopathy diseases.

OBJECTIVE

We aimed to assess the predictive value of clinical variables and biomarkers for the early development of α-synucleinopathy diseases in subjects with iRBD.

METHODS

56 patients with RBD Screening Questionnaire (RBDSQ) scores ≥5 at baseline and subsequent visit were enrolled as probable iRBD from the Parkinson's Progression Markers Initiative (PPMI) database. Baseline clinical data and biomarkers were analyzed. The endpoint was defined as disease progression to α-synucleinopathy diseases. Cox proportional hazard and Kaplan-Meier analyses were used to evaluate the predictive values of the indicators.

RESULTS

During a mean follow-up duration of 5.1 years, 15 of 56 patients (26.8%) developed α-synucleinopathy diseases. Baseline clinical variables, including University of Pennsylvania Smell Identification Test (UPSIT, HR = 26.18, p = 0.004), 15-item Geriatric Depression Scale (GDS, HR = 14.26, p = 0.001), Montreal Cognitive Assessment (MoCA, HR = 3.56, p = 0.025), and Hopkins Verbal Learning Test Total recall (HVLT-TR, HR = 3.70, p = 0.014); genotype status of TMEM175 (HR = 3.74, p = 0.017), SCN3A (HR = 5.81, p = 0.022) and NUCKS1 (HR = 0.342, p = 0.049); ratio of phosphorylated tau to total tau (p-tau/t-tau, HR = 8.36, p = 0.001) in cerebrospinal fluid; and gray matter atrophy in inferior frontal gyrus (IFG, HR = 15.49, p = 0.001) were associated with phenoconversion to α-synucleinopathy diseases. A model combined the three independent variables (UPSIT, TMEM175 and gray matter atrophy in IFG) exhibited significantly improved predictive performance.

CONCLUSION

For patients with iRBD, progression to α-synucleinopathy diseases can be predicted with good accuracy using a model combining clinical variables and biomarkers, which could form a basis for future disease prevention.

Accelerating Medicines Partnership: Parkinson's Disease. Genetic Resource

BACKGROUND

Whole-genome sequencing data are available from several large studies across a variety of diseases and traits. However, massive storage and computation resources are required to use these data, and to achieve sufficient power for discoveries, harmonization of multiple cohorts is critical.

OBJECTIVES

The Accelerating Medicines Partnership Parkinson's Disease program has developed a research platform for Parkinson's disease (PD) that integrates the storage and analysis of whole-genome sequencing data, RNA expression data, and clinical data, harmonized across multiple cohort studies.

METHODS

The version 1 release contains whole-genome sequencing data derived from 3941 participants from 4 cohorts. Samples underwent joint genotyping by the TOPMed Freeze 9 Variant Calling Pipeline. We performed descriptive analyses of these whole-genome sequencing data using the Accelerating Medicines Partnership Parkinson's Disease platform.

RESULTS

The clinical diagnosis of participants in version 1 release includes 2005 idiopathic PD patients, 963 healthy controls, 64 prodromal subjects, 62 clinically diagnosed PD subjects without evidence of dopamine deficit, and 705 participants of genetically enriched cohorts carrying PD risk-associated GBA variants or LRRK2 variants, of whom 304 were affected. We did not observe significant enrichment of pathogenic variants in the idiopathic PD group, but the polygenic risk score was higher in PD both in nongenetically enriched cohorts and genetically enriched cohorts. The population analysis showed a correlation between genetically enriched cohorts and Ashkenazi Jewish ancestry.

CONCLUSIONS

We describe the genetic component of the Accelerating Medicines Partnership Parkinson's Disease platform, a solution to democratize data access and analysis for the PD research community. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article is a U.S. Government work and is in the public domain in the USA.

RNA sequencing of whole blood reveals early alterations in immune cells and gene expression in Parkinson's disease

Changes in the blood-based RNA transcriptome have the potential to inform biomarkers of Parkinson's disease (PD) progression. Here we sequenced a discovery set of whole-blood RNA species in 4,871 longitudinally collected samples from 1,570 clinically phenotyped individuals from the Parkinson's Progression Marker Initiative (PPMI) cohort. Samples were sequenced to an average of 100 million read pairs to create a high-quality transcriptome. Participants with PD in the PPMI had significantly altered RNA expression (>2,000 differentially expressed genes), including an early and persistent increase in neutrophil gene expression, with a concomitant decrease in lymphocyte cell counts. This was validated in a cohort from the Parkinson's Disease Biomarkers Program (PDBP) consisting of 1,599 participants and by alterations in immune cell subtypes. This publicly available transcriptomic dataset, coupled with available detailed clinical data, provides new insights into PD biological processes impacting whole blood and new paths for developing diagnostic and prognostic PD biomarkers.

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

OBJECTIVE

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

METHODS

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

RESULT

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

CONCLUSION

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

Development and Validation of a Prognostic Model for Cognitive Impairment in Parkinson's Disease With REM Sleep Behavior Disorder

The presentation and progression of Parkinson’s disease (PD) are not uniform, but the presence of rapid eye movement sleep behavior disorder (RBD) in PD patients may indicate a worse prognosis than isolated PD. Increasing evidence suggests that patients with comorbid PD and RBD (PD-RBD) are more likely to develop cognitive impairment (CI) than those with isolated PD; however, the predictors of CI in PD-RBD patients are not well understood. This study aimed to develop a prognostic model for predicting mild cognitive impairment (MCI) in PD-RBD patients. The data of PD-RBD patients were extracted from the Parkinson’s Progression Markers Initiative study (PPMI), and the sample was randomly divided into a training set (n = 96) and a validation set (n = 24). PD-MCI as defined by the level II Movement Disorder Society (MDS) diagnostic criteria was the outcome of interest. The demographic features, clinical assessments, dopamine transporter (DAT) imaging data, cerebrospinal fluid (CSF) analyses and genetic data of PD patients were considered candidate predictors. We found that performance on the University of Pennsylvania Smell Identification Test (UPSIT), the mean signal and asymmetry index of the putamen on DAT imaging, p-tau/α-syn and p-tau in CSF, and rs55785911 genotype were predictors of PD-MCI in PD-RBD patients. A C-index of 0.81 was obtained with this model, and a C-index of 0.73 was obtained in the validation set. Favorable results of calibrations and decision curve analysis demonstrated the efficacy and feasibility of this model. In conclusion, we developed a prognostic model for predicting MCI in PD-RBD patients; the model displayed good discrimination and calibration and may be a convenient tool for clinical application. Larger samples and external validation sets are needed to validate this model.

Common X-Chromosome Variants Are Associated with Parkinson Disease Risk

OBJECTIVE

The objective of this study was to identify genetic variants on the X-chromosome associated with Parkinson disease (PD) risk.

METHODS

We performed an X-chromosome-wide association study (XWAS) of PD risk by meta-analyzing results from sex-stratified analyses. To avoid spurious associations, we designed a specific harmonization pipeline for the X-chromosome and focused on a European ancestry sample. We included 11,142 cases, 280,164 controls, and 5,379 proxy cases, based on parental history of PD. Additionally, we tested the association of significant variants with (1) PD risk in an independent replication with 1,561 cases and 2,465 controls and (2) putamen volume in 33,360 individuals from the UK Biobank.

RESULTS

In the discovery meta-analysis, we identified rs7066890 (odds ratio [OR] = 1.10, 95% confidence interval [CI] = 1.06-1.14, p = 2.2 × 10-9 ), intron of GPM6B, and rs28602900 (OR = 1.10, 95% CI = 1.07-1.14, p = 1.6 × 10-8 ) in a high gene density region including RPL10, ATP6A1, FAM50A, and PLXNA3. The rs28602900 association with PD was replicated (OR = 1.16, 95% CI = 1.03-1.30, p = 0.016) and shown to colocalize with a significant expression quantitative locus (eQTL) regulating RPL10 expression in the putamen and other brain tissues in the Genotype-Tissue Expression Project. Additionally, the rs28602900 locus was found to be associated with reduced brain putamen volume. No results reached genome-wide significance in the sex-stratified analyses.

INTERPRETATION

We report the first XWAS of PD and identify 2 genome-wide significant loci. The rs28602900 association was replicated in an independent PD dataset and showed concordant effects in its association with putamen volume. Critically, rs26802900 is a significant eQTL of RPL10. These results support a role for ribosomal proteins in PD pathogenesis and show that the X-chromosome contributes to PD genetic risk. ANN NEUROL 2021;90:22-34.

Association of Dual LRRK2 G2019S and GBA Variations With Parkinson Disease Progression

Importance

Despite a hypothesis that harboring a leucine-rich repeat kinase 2(LRRK2) G2019S variation and a glucocerebrosidase (GBA) variant would have a combined deleterious association with disease pathogenesis, milder clinical phenotypes have been reported in dual LRRK2 and GBA variations Parkinson disease (PD) than in GBA variation PD alone.

Objective

To evaluate the association of LRRK2 G2019S and GBA variants with longitudinal cognitive and motor decline in PD.

Design, Setting, and Participants

This longitudinal cohort study of continuous measures in LRRK2 PD, GBA PD, LRRK2/GBA PD, and wild-type idiopathic PD used pooled annual visit data ranging from 2004 to 2019 from the Mount Sinai Beth Israel, Parkinson Disease Biomarker Program, Harvard Biomarkers Study, Ashkenazi Jewish-LRRK2-Consortium, Parkinson Progression Marker Initiative, and SPOT-PD studies. Patients who were screened for GBA and LRRK2 variations and completed either a motor or cognitive assessment were included. Data were analyzed from May to July 2020.

Main Outcomes and Measures

The associations of LRRK2 G2019S and GBA genotypes on the rate of decline in Montreal Cognitive Assessment (MoCA) and Movement Disorders Society-Unified Parkinson Disease Rating Scale-Part III scores were examined using linear mixed effects models with PD duration as the time scale.

Results

Among 1193 individuals with PD (mean [SD] age, 66.6 [9.9] years; 490 [41.2%] women), 128 (10.7%) had GBA PD, 155 (13.0%) had LRRK2 PD, 21 (1.8%) had LRRK2/GBA PD, and 889 (74.5%) had idiopathic PD. Patients with GBA PD had faster decline in MoCA than those with LRRK2/GBA PD (B [SE], -0.31 [0.09] points/y; P < .001), LRRK2 PD (B [SE], -0.33 [0.09] points/y; P < .001), or idiopathic PD (B [SE], -0.23 [0.08] points/y; P = .005). There was a LRRK2 G2019S × GBA interaction in MoCA decline (B [SE], 0.22 [0.11] points/y; P = .04), but not after excluding severe GBA variations (B [SE], 0.12 [0.11] points/y; P = .28). Patients with GBA PD had significantly worse motor progression compared with those with idiopathic PD (B [SE], 0.49 [0.22] points/y; P = .03) or LRRK2 PD (B [SE], 0.77 [0.26] points/y; P = .004).

Conclusions and Relevance

These findings suggest that longitudinal cognitive decline in patients with GBA PD was more severe than in those with LRRK2/GBA PD, which more closely resembled LRRK2 PD. This further supports the notion of a dominant association of LRRK2 on GBA in individuals who carry both and raises the possibility of an LRRK2 × GBA interaction. However, the biological basis of a dominant association or interaction is not clear and is apparently contrary to basic investigations. Study of a larger cohort of individuals with severe GBA variation is warranted.

Association of Physical Activity and APOE Genotype With Longitudinal Cognitive Change in Early Parkinson Disease

OBJECTIVE

To determine whether greater physical activity could modify the negative association of APOE ε4 with longitudinal cognitive changes in early Parkinson disease (PD) and to uncover the disease-specific mechanism for explaining such benefits of physical activity.

METHODS

We used data from the Parkinson's Progression Markers Initiative cohort. Because self-reported physical activity, measured by the Physical Activity Scale of the Elderly, was initiated at 2 years after enrollment, this longitudinal analysis was based on assessments performed at years 2, 3, and 4. Cognitive function was measured annually with the Montreal Cognitive Assessment (MoCA). Dopamine transporter (DAT) imaging was performed at years 2 and 4. We assessed the interactive associations between physical activity and the APOE ε4 allele on the longitudinal changes in MoCA scores and striatal DAT activities.

RESULTS

A total of 173 patients with early PD (age 63.3 ± 10.0 years, 27% APOE ε4 carriers) were included. The APOE ε4 allele showed a steeper rate of cognitive decline than the non-APOE ε4 allele (estimate -1.33, 95% confidence interval [CI] -2.12 to -0.47, p = 0.002). However, there was a significant interaction between physical activity and APOE ε4 such that higher physical activity was related to slower APOE ε4-related cognitive decline (estimate 0.007, 95% CI 0.003-0.011, p = 0.001). No significant interaction was found between physical activity and the APOE ε4 allele regarding the change in striatal DAT activities.

CONCLUSION

Increased physical activity attenuated APOE ε4-related vulnerability to early cognitive decline in patients with PD. This protective effect did not appear to be mediated by striatal dopaminergic function.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov Identifier: NCT01141023.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that increased physical activity was associated with decreased APOE ε4-related early cognitive decline in patients with PD.

Impact of the apolipoprotein E ε4 allele on early Parkinson's disease progression

OBJECTIVE

Emerging evidence shows that apolipoprotein E (APOE) ε4 exacerbates alpha-synuclein pathology. We aimed to investigate whether the APOE ε4 allele contributes to early Parkinson's disease (PD) progression.

METHODS

This cohort study included 361 early PD patients who were classified as APOE ε4 carriers (n = 90) and noncarriers (n = 271). The patients underwent yearly motor and nonmotor assessments covering neuropsychiatric, sleep-related, and autonomic symptoms over 5 years of follow-up. Dopamine transporter (DAT) imaging was conducted at baseline and the 1-, 2-, and 4-year follow-up visits.

RESULTS

The APOE ε4 carriers had steeper declines in the Montreal Cognitive Assessment score (p=0.005) and the semantic fluency test score (p=0.012) than the noncarriers. No significant between-group differences in the longitudinal changes in motor, other nonmotor, and DAT imaging variables were observed.

CONCLUSIONS

Our exploratory analyses show that only cognitive performance was negatively affected by the APOE ε4 allele in the progression of early PD. More specifically, this allele was associated with poorer performance in semantic verbal fluency among cognitive domains.

Polygenic Score Models for Alzheimer's Disease: From Research to Clinical Applications

The high prevalence of Alzheimer's disease (AD) among the elderly population and its lack of effective treatments make this disease a critical threat to human health. Recent epidemiological and genetics studies have revealed the polygenic nature of the disease, which is possibly explainable by a polygenic score model that considers multiple genetic risks. Here, we systemically review the rationale and methods used to construct polygenic score models for studying AD. We also discuss the associations of polygenic risk scores (PRSs) with clinical outcomes, brain imaging findings, and biochemical biomarkers from both the brain and peripheral system. Finally, we discuss the possibility of incorporating polygenic score models into research and clinical practice along with potential challenges.

Potential Sex-Specific Effects of Apolipoprotein E ɛ4 on Cognitive Decline in Early Parkinson's Disease

BACKGROUND/OBJECTIVE

To compare the longitudinal trajectories of cognition according to the presence of the apolipoprotein E (APOE) ɛ4 allele in male and female Parkinson's disease (PD) patients.

METHODS

This study included a total of 361 patients with recently diagnosed de novo PD (mean age [standard deviation], 61.4 [9.8] years). The patients were classified into the following groups: APOEɛ4 + /M (n = 65), APOEɛ4-/M (n = 173), APOEɛ4 + /F (n = 25), and APOEɛ4-/F (n = 98). Cognitive decline was assessed annually over 5 years of follow-up using the Montreal Cognitive Assessment (MoCA). To assess the sex-specific impacts of the APOEɛ4 status on cognitive decline, we used generalized linear mixed effects (GLME) models separately for men, women, and the two sexes combined.

RESULTS

In the sex-stratified GLME models adjusted for covariates, the interaction results showed that the males with APOEɛ4 had a steeper rate of cognitive decline than those without APOEɛ4. In contrast, there was no significant interaction between APOEɛ4 and time on longitudinal MoCA performance in the females. The main effect of APOEɛ4 on the change in the MoCA score was not significant for either men or women. When the data from both men and women were used, the APOEɛ4 + /M group exhibited a steeper rate of cognitive decline than did the APOEɛ4 + /F and APOEɛ4-/F groups. These results were consistent with those of sensitivity analyses.

CONCLUSION

Sex may be considered when APOEɛ4-related vulnerability to early cognitive decline is evaluated in PD patients.

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.

Extrastriatal SPECT-DAT uptake correlates with clinical and biological features of de novo Parkinson's disease

Striatal dopamine transporter (DAT) uptake assessment through I¹²³-Ioflupane Single-Pphoton Emission Computed Tomography (SPECT) provides valuable information about the dopaminergic denervation occurring in Parkinson's disease (PD). However, little is known about the clinical or biological relevance of extrastriatal DAT uptake in PD. Here, from the Parkinson's Progression Markers Initiative, we studied 623 participants (431 PD and 192 healthy controls) with available SPECT data. Even though striatal denervation was undoubtedly the imaging hallmark of PD, extrastriatal DAT uptake was also reduced in patients with PD. Topographically, widespread frontal but also temporal and posterior cortical regions showed lower DAT uptake in PD patients with respect to healthy controls. Importantly, a longitudinal voxelwise analysis confirmed an active one-year loss of extrastriatal DAT uptake within the PD group. Extrastriatal DAT uptake also correlated with the severity of motor symptoms, cognitive performance, and cerebrospinal fluid α-synuclein levels. In addition, we found an association between the Catechol-O-methyltransferase val¹⁵⁸met genotype and extrastriatal DAT uptake. These results highlight the clinical and biological relevance of extrastriatal SPECT-DAT uptake in PD.

Association of PICALM with Cognitive Impairment in Parkinson's Disease

BACKGROUND

Cognitive impairment is one of the most disabling nonmotor symptoms in Parkinson's disease (PD). Recently, a genome-wide association study in Alzheimer's disease has identified the PICALM rs3851179 polymorphism as one of the most significant susceptibility genes for Alzheimer's disease after APOE. The aim of this study was to determine the potential role of PICALM and its genetic interaction with APOE in the development of cognitive decline in PD.

METHODS

A discovery cohort of 712 patients with PD were genotyped for PICALM (rs3851179) and APOE (rs429358 and rs7412) polymorphisms. The association of PICALM and APOE-PICALM genetic interaction with cognitive dysfunction in PD was studied using logistic regression models, and the relationship of PICALM with cognitive decline onset was assessed with Cox regression analysis. PICALM effect was then replicated in an international, independent cohort (Parkinson's Progression Markers Initiative, N = 231).

RESULTS

PICALM rs3851179 TT genotype was significantly associated with a decreased risk of cognitive impairment in PD (TT vs. CC + CT, P = 0.041, odds ratio = 0.309). Replication studies further demonstrated its protective effect on cognitive impairment in PD. In addition, the protective effect of the PICALM rs3851179 TT genotype was more pronounced in the APOE ε4 (-) carriers from the discovery cohort (P = 0.037, odds ratio = 0.241), although these results were not replicated in the Parkinson's Progression Markers Initiative cohort.

CONCLUSIONS

Our results support the fact that PICALM is associated with cognitive impairment in PD. The understanding of its contribution to cognitive decline in PD could provide new targets for the development of novel therapies. © 2020 International Parkinson and Movement Disorder Society.

Longitudinal Measurements of Glucocerebrosidase activity in Parkinson's patients

Objective

Reduction in glucocerebrosidase (GCase; encoded by GBA) enzymatic activity has been linked to Parkinson’s disease (PD). Here, we correlated GCase activity and PD phenotype in the Parkinson’s Progression Markers Initiative (PPMI) cohort.

Methods

We measured GCase activity in dried blood spots from 1559 samples of participants in the inception PPMI cohort, collected in four annual visits (from baseline visit to Year‐3). Participants (PD, n = 392; controls, n = 175) were fully sequenced for GBA variants by means of genome‐wide genotyping arrays, whole‐exome sequencing, whole‐genome sequencing, Sanger sequencing, and RNA‐sequencing.

Results

Fifty‐two PD participants (13.4%) and 13 (7.4%) controls carried a GBA variant. GBA status was strongly associated with GCase activity. Among noncarriers, GCase activity was similar between PD and controls. Among GBA p.E326K carriers (PD, n = 20; controls, n = 5), activity was significantly lower in PD carriers than control carriers (9.53 µmol/L/h vs. 11.68 µmol/L/h, P = 0.035). Glucocerebrosidase activity was moderately (r = 0.45) associated with white blood cell (WBC) count. Next, we divided the noncarriers with PD to tertiles based on WBC count‐corrected enzymatic activity. Members of the lower tertile had higher MDS‐Unified Parkinson’s Disease Rating Scale motor score in the “off” medication examination at year‐III exam. Longitudinal analyses demonstrated slight reduction of activity in samples collected earlier on in the study, likely because of longer storage time.

Interpretation

GCase activity is associated with GBA genotype, WBC count, and among p.E326K variant carriers, with PD status. Reduced activity may also be associated with worse phenotype but longer follow up is required to confirm this observation.

DaTSCAN (123I-FP-CIT SPECT) imaging in early versus mid and late onset Parkinson's disease: Longitudinal data from the PPMI study

INTRODUCTION

It has been reported that early onset Parkinson's Disease (PD) patients have a less profound dopaminergic degeneration. The aim of the current study was to determine whether there are longitudinal differences in dopaminergic denervation [signal reduction in 123I-FP-CIT SPECT] in early versus mid and late onset PD.

METHODS

DaTSCAN (123I-FP-CIT SPECT) imaging was acquired at Parkinson's Progression Markers Initiative (PPMI) imaging centers and sent to the imaging core for calculation of striatal binding ratios. Data from the PPMI database of 58 early de novo PD patients (age ≤ 50 years) were compared to those of 362 mid and late onset PD patients (age > 50 years).

RESULTS

Although raw striatal binding ratios were higher in early onset versus mid/late onset PD, especially on the ipsilateral side, such differences were not observed, and were in fact reversed in the contralateral putamen, after age correction. The rate of signal decline was similar between the two groups. Interestingly, based on both raw and age-adjusted data, caudate nucleus and putamen asymmetry (contralateral/ipsilateral ratio) was more pronounced in early onset PD. Striatal asymmetry also significantly correlated with age at onset as a continuous variable.

CONCLUSION

Early onset PD patients exhibited similar rates of decline of dopaminergic denervation compared to mid/late onset PD. These results are not supportive of a more benign disease in this subgroup. The more pronounced asymmetry in early onset PD may however signify a qualitatively different pattern of neurodegeneration compared to mid/late onset PD.

Excess of singleton loss-of-function variants in Parkinson's disease contributes to genetic risk

BACKGROUND

Parkinson's disease (PD) is a neurodegenerative disorder with complex genetic architecture. Besides rare mutations in high-risk genes related to monogenic familial forms of PD, multiple variants associated with sporadic PD were discovered via association studies.

METHODS

We studied the whole-exome sequencing data of 340 PD cases and 146 ethnically matched controls from the Parkinson's Progression Markers Initiative (PPMI) and performed burden analysis for different rare variant classes. Disease prediction models were built based on clinical, non-clinical and genetic features, including both common and rare variants, and two machine learning methods.

RESULTS

We observed a significant exome-wide burden of singleton loss-of-function variants (corrected p=0.037). Overall, no exome-wide burden of rare amino acid changing variants was detected. Finally, we built a disease prediction model combining singleton loss-of-function variants, a polygenic risk score based on common variants, and family history of PD as features and reached an area under the curve of 0.703 (95% CI 0.698 to 0.708). By incorporating a rare variant feature, our model increased the performance of the state-of-the-art classification model for the PPMI dataset, which reached an area under the curve of 0.639 based on common variants alone.

CONCLUSION

The main finding of this study is to highlight the contribution of singleton loss-of-function variants to the complex genetics of PD and that disease risk prediction models combining singleton and common variants can improve models built solely on common variants.

Parkinson's disease prognostic scores for progression of cognitive decline

Clinical and biochemical diversity of Parkinson’s disease (PD) presents a major challenge for accurate diagnosis and prediction of its progression. We propose, develop and optimize PD clinical scores as efficient integrated progression biomarkers for prediction of the likely rate of cognitive decline in PD patients. We considered 269 drug-naïve participants from the Parkinson’s Progression Marker Initiative database, diagnosed with idiopathic PD and observed between 4 and 6 years. Nineteen baseline clinical and pathological measures were systematically considered. Relative variable importance and logistic regressions were used to optimize combinations of significant baseline measures as integrated biomarkers. Parkinson’s disease cognitive decline scores were designed as new clinical biomarkers using optimally categorized baseline measures. Specificities and sensitivities of the biomarkers reached ~93% for prediction of severe rate of cognitive decline (with more than 5 points decline in 4 years on the Montreal Cognitive Assessment scale), and up to ~73% for mild-to-moderate decline (between 1 and 5 points decline). The developed biomarkers and clinical scores could resolve the long-standing clinical problem about reliable prediction of PD progression into cognitive deterioration. The outcomes also provide insights into the contributions of individual clinical and pathological measures to PD progression, and will assist with better-targeted treatment regiments, stratification of clinical trial and their evaluation.

Longitudinal analyses of cerebrospinal fluid α-Synuclein in prodromal and early Parkinson's disease

BACKGROUND

Aggregation of α-synuclein is central to the pathophysiology of PD. Biomarkers related to α-synuclein may be informative for PD diagnosis/progression.

OBJECTIVES

To analyze α-synuclein in CSF in drug-naïve PD, healthy controls, and prodromal PD in the Parkinson's Progression Markers Initiative.

METHODS

Over up to 36-month follow-up, CSF total α-synuclein and its association with MDS-UPDRS motor scores, cognitive assessments, and dopamine transporter imaging were assessed.

RESULTS

The inception cohort included PD (n = 376; age [mean {standard deviation} years]: 61.7 [9.62]), healthy controls (n = 173; age, 60.9 [11.3]), hyposmics (n = 16; age, 68.3 [6.15]), and idiopathic rapid eye movement sleep behavior disorder (n = 32; age, 69.3 [4.83]). Baseline CSF α-synuclein was lower in manifest and prodromal PD versus healthy controls. Longitudinal α-synuclein decreased significantly in PD at 24 and 36 months, did not change in prodromal PD over 12 months, and trended toward an increase in healthy controls. The decrease in PD was not shown when CSF samples with high hemoglobin concentration were removed from the analysis. CSF α-synuclein changes did not correlate with longitudinal MDS-UPDRS motor scores or dopamine transporter scan.

CONCLUSIONS

CSF α-synuclein decreases early in the disease, preceding motor PD. CSF α-synuclein does not correlate with progression and therefore does not reflect ongoing dopaminergic neurodegeneration. Decreased CSF α-synuclein may be an indirect index of changes in the balance between α-synuclein secretion, solubility, or aggregation in the brain, reflecting its overall turnover. Additional biomarkers more directly related to α-synuclein pathophysiology and disease progression and other markers to be identified by, for example, proteomics and metabolomics are needed. © 2019 International Parkinson and Movement Disorder Society.

The Personalized Parkinson Project: examining disease progression through broad biomarkers in early Parkinson's disease

BACKGROUND

Our understanding of the etiology, pathophysiology, phenotypic diversity, and progression of Parkinson's disease has stagnated. Consequently, patients do not receive the best care, leading to unnecessary disability, and to mounting costs for society. The Personalized Parkinson Project (PPP) proposes an unbiased approach to biomarker development with multiple biomarkers measured longitudinally. Our main aims are: (a) to perform a set of hypothesis-driven analyses on the comprehensive dataset, correlating established and novel biomarkers to the rate of disease progression and to treatment response; and (b) to create a widely accessible dataset for discovery of novel biomarkers and new targets for therapeutic interventions in Parkinson's disease.

METHODS/DESIGN

This is a prospective, longitudinal, single-center cohort study. The cohort will comprise 650 persons with Parkinson's disease. The inclusion criteria are purposely broad: age ≥ 18 years; and disease duration ≤5 years. Participants are followed for 2 years, with three annual assessments at the study center. Outcomes include a clinical assessment (including motor and neuro-psychological tests), collection of biospecimens (stool, whole blood, and cerebrospinal fluid), magnetic resonance imaging (both structural and functional), and ECG recordings (both 12-lead and Holter). Additionally, collection of physiological and environmental data in daily life over 2 years will be enabled through the Verily Study Watch. All data are stored with polymorphic encryptions and pseudonyms, to guarantee the participants' privacy on the one hand, and to enable data sharing on the other. The data and biospecimens will become available for scientists to address Parkinson's disease-related research questions.

DISCUSSION

The PPP has several distinguishing elements: all assessments are done in a single center; inclusion of "real life" subjects; deep and repeated multi-dimensional phenotyping; and continuous monitoring with a wearable device for 2 years. Also, the PPP is powered by privacy and security by design, allowing for data sharing with scientists worldwide respecting participants' privacy. The data are expected to open the way for important new insights, including identification of biomarkers to predict differences in prognosis and treatment response between patients. Our long-term aim is to improve existing treatments, develop new therapeutic approaches, and offer Parkinson's disease patients a more personalized disease management approach.

TRIAL REGISTRATION

Clinical Trials NCT03364894 . Registered December 6, 2017 (retrospectively registered).

Effect of polygenic load on striatal dopaminergic deterioration in Parkinson disease

OBJECTIVE

To investigate the effect of polygenic load on the progression of striatal dopaminergic dysfunction in patients with Parkinson disease (PD).

METHODS

Using data from 335 patients with PD in the Parkinson's Progression Markers Initiative (PPMI) database, we investigated the longitudinal association of PD-associated polygenic load with changes in striatal dopaminergic activity as measured by ¹²³I-N-3-fluoropropyl-2-β-carboxymethoxy-3β-(4-iodophenyl) nortropane (¹²³I-FP-CIT) SPECT over 4 years. PD-associated polygenic load was estimated by calculating weighted genetic risk scores (GRS) using 1) all available 27 PD-risk single nucleotide polymorphisms (SNPs) in the PPMI database (GRS1) and 2) 23 SNPs with minor allele frequency >0.05 (GRS2).

RESULTS

GRS1 and GRS2 were correlated with younger age at onset in patients with PD (GRS1, Spearman ρ = -0.128, p = 0.019; GRS2, Spearman ρ = -0.109, p = 0.047). Although GRS1 did not show an association with changes in striatal ¹²³I-FP-CIT availability, GRS2 was associated with a slower decline of striatal dopaminergic activity (interactions with disease duration in linear mixed model; caudate nucleus, estimate = 0.399, SE = 0.165, p = 0.028; putamen, estimate = 0.396, SE = 0.137, p = 0.016).

CONCLUSIONS

Our results suggest that genetic factors for PD risk may have heterogeneous effects on striatal dopaminergic degeneration, and some factors may be associated with a slower decline of dopaminergic activity. Composition of PD progression-specific GRS may be useful in predicting disease progression in patients.

TMEM106B Effect on cognition in Parkinson disease and frontotemporal dementia

OBJECTIVE

Common variants near TMEM106B associate with risk of developing frontotemporal dementia (FTD). Emerging evidence suggests a role for TMEM106B in neurodegenerative processes beyond FTD. We evaluate the effect of TMEM106B genotype on cognitive decline across multiple neurogenerative diseases.

METHODS

We longitudinally followed 870 subjects with diagnoses of Parkinson disease (PD; n = 179), FTD (n = 179), Alzheimer disease (AD; n = 300), memory-predominant mild cognitive impairment (MCI; n = 75), or neurologically normal control subjects (NC; n = 137) at the University of Pennsylvania (UPenn). All participants had annual Mini-Mental State Examination (MMSE; median follow-up duration = 3.0 years) and were genotyped at TMEM106B index single nucleotide polymorphism rs1990622. Genotype effects on cognition were confirmed by extending analyses to additional cognitive instruments (Mattis Dementia Rating Scale-2 [DRS-2] and Montreal Cognitive Assessment [MoCA]) and to an international validation cohort (Parkinson's Progression Markers Initiative [PPMI], N = 371).

RESULTS

The TMEM106B rs1990622T allele, linked to increased risk of FTD, associated with greater MMSE decline over time in PD subjects but not in AD or MCI subjects. For FTD subjects, rs1990622T associated with more rapid decrease in MMSE only under the minor-allele, rs1990622C , dominant model. Among PD patients, rs1990622T carriers from the UPenn cohort demonstrated more rapid longitudinal decline in DRS-2 scores. Finally, in the PPMI cohort, TMEM106B risk allele carriers demonstrated more rapid longitudinal decline in MoCA scores.

INTERPRETATION

Irrespective of cognitive instrument or cohort assessed, TMEM106B acts as a genetic modifier for cognitive trajectory in PD. Our results implicate lysosomal dysfunction in the pathogenesis of cognitive decline in 2 different proteinopathies. ANN NEUROL 2019;85:801-811.

Selecting variants of unknown significance through network-based gene-association significantly improves risk prediction for disease-control cohorts

Variants of unknown/uncertain significance (VUS) pose a huge dilemma in current genetic variation screening methods and genetic counselling. Driven by methods of next generation sequencing (NGS) such as whole exome sequencing (WES), a plethora of VUS are being detected in research laboratories as well as in the health sector. Motivated by this overabundance of VUS, we propose a novel computational methodology, termed VariantClassifier (VarClass), which utilizes gene-association networks and polygenic risk prediction models to shed light into this grey area of genetic variation in association with disease. VarClass has been evaluated using numerous validation steps and proves to be very successful in assigning significance to VUS in association with specific diseases of interest. Notably, using VUS that are deemed significant by VarClass, we improved risk prediction accuracy in four large case-studies involving disease-control cohorts from GWAS as well as WES, when compared to traditional odds ratio analysis. Biological interpretation of selected high scoring VUS revealed interesting biological themes relevant to the diseases under investigation. VarClass is available as a standalone tool for large-scale data analyses, as well as a web-server with additional functionalities through a user-friendly graphical interface.

An increased rate of longitudinal cognitive decline is observed in Parkinson's disease patients with low CSF Aß42 and an APOE ε4 allele

OBJECTIVE

Low concentrations of cerebrospinal fluid (CSF) amyloid-beta (Aβ-42) are associated with increased risk of cognitive decline in Parkinson's disease (PD). We sought to determine whether APOE genotype modifies the rate of cognitive decline in PD patients with low CSF Aβ-42 compared to patients with normal levels.

METHODS

The Parkinson's Progression Markers Initiative is a longitudinal, ongoing study of de novo PD participants, which includes APOE genotyping, CSF Aβ-42 determinations, and neuropsychological assessments. We used linear mixed effects models in three PD groups (PD participants with low CSF Aβ at baseline, PD participants with normal CSF Aβ, and both groups combined). Having at least one copy of the APOE ɛ4 allele, time, and the interaction of APOE ɛ4 and time were predictor variables for cognitive change, adjusting for age, gender and education.

RESULTS

423 de novo PD participants were followed up to 5 years with annual cognitive assessments. 103 participants had low baseline CSF Aβ-42 (39 APOE ε4+, 64 APOE ε4-). Compared to participants with normal CSF Aβ-42, those with low CSF Aβ-42 declined faster on most cognitive tests. Within the low CSF Aβ-42 group, APOE ε4+ participants had faster rates of decline on the Montreal Cognitive Assessment (primary outcome; 0.57 points annual decline, p = .005; 5-year standardized change of 1.2) and the Symbol Digit Modalities Test (1.4 points annual decline, p = .002; 5-year standardized change of 0.72).

DISCUSSION

PD patients with low CSF Aβ-42 and APOE ε4+ showed a higher rate of cognitive decline early in the disease. Tests of global cognition (Montreal Cognitive Assessment) and processing speed (Symbol Digit Modalities Test) were the most sensitive to early cognitive decline. Results suggest that CSF Aβ-42 and APOE ε4 might interact to promote early cognitive changes in PD patients.

Effectiveness of imaging genetics analysis to explain degree of depression in Parkinson's disease

Depression is one of the most common and important neuropsychiatric symptoms in Parkinson's disease and often becomes worse as Parkinson's disease progresses. However, the underlying mechanisms of depression in Parkinson's disease are not clear. The aim of our study was to find genetic features related to depression in Parkinson's disease using an imaging genetics approach and to construct an analytical model for predicting the degree of depression in Parkinson's disease. The neuroimaging and genotyping data were obtained from an openly accessible database. We computed imaging features through connectivity analysis derived from tractography of diffusion tensor imaging. The imaging features were used as intermediate phenotypes to identify genetic variants according to the imaging genetics approach. We then constructed a linear regression model using the genetic features from imaging genetics approach to describe clinical scores indicating the degree of depression. As a comparison, we constructed other models using imaging features and genetic features based on references to demonstrate the effectiveness of our imaging genetics model. The models were trained and tested in a five-fold cross-validation. The imaging genetics approach identified several brain regions and genes known to be involved in depression, with the potential to be used as meaningful biomarkers. Our proposed model using imaging genetic features predicted and explained the degree of depression in Parkinson's disease appropriately (adjusted R2 larger than 0.6 over five training folds) and with a lower error and higher correlation than with other models over five test folds.

Risk factors of levodopa-induced dyskinesia in Parkinson's disease: results from the PPMI cohort

Levodopa-induced dyskinesias (LID) negatively impact on the quality of life of patients with Parkinson's disease (PD). We assessed the risk factors for LID in a cohort of de-novo PD patients enrolled in the Parkinson's Progression Markers Initiative (PPMI). This retrospective cohort study included all PD patients enrolled in the PPMI cohort. Main outcome was the incidence rate of dyskinesia, defined as the first time the patient reported a non-zero score in the item "Time spent with dyskinesia" of the MDS-UPDRS part IV. Predictive value for LID development was assessed for clinical and demographical features, dopamine transporter imaging (DaTscan) pattern, cerebrospinal fluid (CSF) biomarkers (Aβ42, total tau, phosphorylated tau, total α synuclein) and genetic risk score for PD. Overall, data from 423 PD patients were analyzed. The cumulative incidence rate of LID was 27.4% (95% CI = 23.2-32.0%), with a mean onset time of 5.81 years from PD diagnosis. Multivariate Cox regression analysis showed several factors predicting LID development, including female gender (HR = 1.61, 95% CI = 1.05-2.47), being not completely functional independent as measured by the modified Schwab & England ADL scale (HR = 1.81, 95% CI = 0.98-3.38), higher MDS-UPDRS part III score (HR = 1.03, 95% CI = 1.00-1.05), postural instability gait disturbances or intermediate phenotypes (HR = 1.95, 95% CI = 1.28-2.96), higher DaTscan caudate asymmetry index (HR = 1.02, 95% CI = 1.00-1.03), higher polygenic genetic risk score (HR = 1.39, 95% CI = 1.08-1.78), and an anxiety trait (HR = 1.02, 95% CI = 1.00-1.04). In PD patients, cumulative levodopa exposure, female gender, severity of motor and functional impairment, non-tremor dominant clinical phenotype, genetic risk score, anxiety, and marked caudate asymmetric pattern at DaTscan at baseline represent independent risk factors for developing LID.

No evidence for DNM3 as genetic modifier of age at onset in idiopathic Parkinson's disease

Parkinson's disease (PD) is a disorder with highly variable clinical phenotype. The identification of genetic variants modifying age at onset and other traits is of great interest because it may provide insight into disease mechanisms and potential therapeutic targets. A variant in the DNM3 gene (rs2421947) has been reported as a genetic modifier of age at onset in LRRK2-associated PD. To test the possible effect of genetic variation in DNM3 on age at onset in idiopathic PD, we examined rs2421947 in a total of 5918 patients with PD from seven data sets. We also assessed the potential effect of all common variants in the DNM3 locus. There was no significant association between rs2421947 and age at onset in any of the individual studies. Meta-analysis of the seven studies was nonsignificant and the between-study heterogeneity was minimal. No other common variants within the DNM3 locus affected age at onset. In conclusion, we find no evidence of an association between DNM3 variants and age at onset in idiopathic PD.

A comprehensive analysis of SNCA-related genetic risk in sporadic parkinson disease

OBJECTIVE

The goal of this study was to refine our understanding of disease risk attributable to common genetic variation in SNCA, a major locus in Parkinson disease, with potential implications for clinical trials targeting α-synuclein. We aimed to dissect the multiple independent association signals, stratify individuals by SNCA-specific risk profiles, and explore expression quantitative trait loci.

METHODS

We analyzed participant-level data from 12,503 patients and 12,502 controls, optimizing a risk model and assessing SNCA-specific risk scores and haplotypes as predictors of individual risk. We also explored hypotheses about functional mechanisms and correlated risk variants to gene expression in human brain and protein levels in cerebrospinal fluid.

RESULTS

We report and replicate a novel, third independent association signal at genome-wide significance level downstream of SNCA (rs2870004, p = 3.0*10^-8 , odds ratio [OR] = 0.88, 95% confidence interval [CI] = 0.84-0.92). SNCA risk score stratification showed a 2-fold difference in disease susceptibility between top and bottom quintiles (OR = 1.99, 95% CI = 1.78-2.23). Contrary to previous reports, we provide evidence supporting top variant rs356182 as functional in itself and associated with a specific SNCA 5' untranslated region transcript isoform in frontal cortex.

INTERPRETATION

The SNCA locus harbors a minimum of 3 independent association signals for Parkinson disease. We demonstrate a fine-grained stratification of α-synuclein-related genetic burden in individual patients of potential future clinical relevance. Further efforts to pinpoint the functional mechanisms are warranted, including studies of the likely causal top variant rs356182 and its role in regulating levels of specific SNCA mRNA transcript variants. Ann Neurol 2018;83:117-129.

Joint genome-wide association study of progressive supranuclear palsy identifies novel susceptibility loci and genetic correlation to neurodegenerative diseases

Background

Progressive supranuclear palsy (PSP) is a rare neurodegenerative disease for which the genetic contribution is incompletely understood.

Methods

We conducted a joint analysis of 5,523,934 imputed SNPs in two newly-genotyped progressive supranuclear palsy cohorts, primarily derived from two clinical trials (Allon davunetide and NNIPPS riluzole trials in PSP) and a previously published genome-wide association study (GWAS), in total comprising 1646 cases and 10,662 controls of European ancestry.

Results

We identified 5 associated loci at a genome-wide significance threshold P < 5 × 10^− 8, including replication of 3 loci from previous studies and 2 novel loci at 6p21.1 and 12p12.1 (near RUNX2 and SLCO1A2, respectively). At the 17q21.31 locus, stepwise regression analysis confirmed the presence of multiple independent loci (localized near MAPT and KANSL1). An additional 4 loci were highly suggestive of association (P < 1 × 10^− 6). We analyzed the genetic correlation with multiple neurodegenerative diseases, and found that PSP had shared polygenic heritability with Parkinson’s disease and amyotrophic lateral sclerosis.

Conclusions

In total, we identified 6 additional significant or suggestive SNP associations with PSP, and discovered genetic overlap with other neurodegenerative diseases. These findings clarify the pathogenesis and genetic architecture of PSP.

Electronic supplementary material

The online version of this article (10.1186/s13024-018-0270-8) contains supplementary material, which is available to authorized users.

Selective cognitive impairment and hyposmia in p.A53T SNCA PD vs typical PD

Objective

To evaluate nonmotor symptoms in early SNCA/p.A53T Parkinson disease (PD) (A53T PD) compared to typical PD (tPD).

Methods

The presence of hyposmia, neuropsychiatric, dysautonomic, and sleep disturbances was assessed by standardized questionnaires and validated scales in 18 patients with A53T PD and 18 patients with tPD, matched for age, sex, and disease duration. All patients were enrolled into the Parkinson's Progression Markers Initiative study.

Results

The levodopa equivalent daily dose was higher in the A53T PD (p = 0.018) group vs the tPD group. Scores on the University of Pennsylvania Smell Identification Test (p = 0.001), Benton Judgement of Line Orientation test (p = 0.001), Letter Number Sequencing Test (p = 0.002), and phonemic verbal fluency (p = 0.002) were lower in the A53T PD group vs the tPD group. In contrast, overall cognition, verbal memory, and semantic fluency were similar between groups.

Conclusion

The observed selective cognitive impairment reflecting frontal-parietal network dysfunction, together with impaired olfaction, define a set of nonmotor dysfunctions related to A53T PD. These results have implications for the prognosis of patients with A53T PD. Moreover, as the archetypal α-synucleinopathy, such results may give insights into tPD.

Parkinson disease polygenic risk score is associated with Parkinson disease status and age at onset but not with alpha-synuclein cerebrospinal fluid levels

BACKGROUND

The genetic architecture of Parkinson's Disease (PD) is complex and not completely understood. Multiple genetic studies to date have identified multiple causal genes and risk loci. Nevertheless, most of the expected genetic heritability remains unexplained. Polygenic risk scores (PRS) may provide greater statistical power and inform about the genetic architecture of multiple phenotypes. The aim of this study was to test the association between PRS and PD risk, age at onset and cerebrospinal fluid (CSF) biomarkers (α-synuclein, Aβ_1-42, t-tau and p-tau).

METHODS

The weighted PRS was created using the genome-wide loci from Nalls et al., 2014 PD GWAs meta-analysis. The PRS was tested for association with PD status, age at onset and CSF biomarker levels in 829 cases and 432 controls of European ancestry.

RESULTS

The PRS was associated with PD status (p = 5.83×10^-08) and age at onset (p = 5.70×10^-07). The CSF t-tau levels showed a nominal association with the PRS (p = 0.02). However, CSF α-synuclein, amyloid beta and phosphorylated tau were not found to be associated with the PRS.

CONCLUSION

Our study suggests that there is an overlap in the genetic architecture of PD risk and onset, although the different loci present different weights for those phenotypes. In our dataset we found a marginal association of the PRS with CSF t-tau but not with α-synuclein CSF levels, suggesting that the genetic architecture for the CSF biomarker levels is different from that of PD risk.

Longitudinal CSF biomarkers in patients with early Parkinson disease and healthy controls

OBJECTIVE

To analyze longitudinal levels of CSF biomarkers in drug-naive patients with Parkinson disease (PD) and healthy controls (HC), examine the extent to which these biomarker changes relate to clinical measures of PD, and identify what may influence them.

METHODS

CSF α-synuclein (α-syn), total and phosphorylated tau (t- and p-tau), and β-amyloid 1-42 (Aβ42) were measured at baseline and 6 and 12 months in 173 patients with PD and 112 matched HC in the international multicenter Parkinson's Progression Marker Initiative. Baseline clinical and demographic variables, PD medications, neuroimaging, and genetic variables were evaluated as potential predictors of CSF biomarker changes.

RESULTS

CSF biomarkers were stable over 6 and 12 months, and there was a small but significant increase in CSF Aβ42 in both patients with patients with PD and HC from baseline to 12 months. The t-tau remained stable. The p-tau increased marginally more in patients with PD than in HC. α-syn remained relatively stable in patients with PD and HC. Ratios of p-tau/t-tau increased, while t-tau/Aβ42 decreased over 12 months in patients with PD. CSF biomarker changes did not correlate with changes in Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale motor scores or dopamine imaging. CSF α-syn levels at 12 months were lower in patients with PD treated with dopamine replacement therapy, especially dopamine agonists.

CONCLUSIONS

These core CSF biomarkers remained stable over 6 and 12 months in patients with early PD and HC. PD medication use may influence CSF α-syn. Novel biomarkers are needed to better profile progressive neurodegeneration in PD.

Latent Cognitive Phenotypes in De Novo Parkinson's Disease: A Person-Centered Approach

OBJECTIVES

Cognitive impairment is an important aspect of Parkinson's disease (PD), but there is considerable heterogeneity in its presentation. This investigation aims to identify and characterize latent cognitive phenotypes in early PD.

METHODS

Latent class analysis, a data-driven, person-centered, cluster analysis was performed on cognitive data from the Parkinson's Progressive Markers Initiative baseline visit. This analytic method facilitates identification of naturally occurring endophenotypes. Resulting classes were compared across biomarker, symptom, and demographic data.

RESULTS

Six cognitive phenotypes were identified. Three demonstrated consistent performance across indicators, representing poor ("Weak-Overall"), average ("Typical-Overall"), and strong ("Strong-Overall") cognition. The remaining classes demonstrated unique patterns of cognition, characterized by "Strong-Memory," "Weak-Visuospatial," and "Amnestic" profiles. The Amnestic class evidenced greater tremor severity and anosmia, but was unassociated with biomarkers linked with Alzheimer's disease. The Weak-Overall class was older and reported more non-motor features associated with cognitive decline, including anxiety, depression, autonomic dysfunction, anosmia, and REM sleep behaviors. The Strong-Overall class was younger, more female, and reported less dysautonomia and anosmia. Classes were unrelated to disease duration, functional independence, or available biomarkers.

CONCLUSIONS

Latent cognitive phenotypes with focal patterns of impairment were observed in recently diagnosed individuals with PD. Cognitive profiles were found to be independent of traditional biomarkers and motoric indices of disease progression. Only globally impaired class was associated with previously reported indicators of cognitive decline, suggesting this group may drive the effects reported in studies using variable-based analysis. Longitudinal and neuroanatomical characterization of classes will yield further insight into the evolution of cognitive change in the disease. (JINS, 2017, 23, 551-563).

Multiple modality biomarker prediction of cognitive impairment in prospectively followed de novo Parkinson disease

OBJECTIVES

To assess the neurobiological substrate of initial cognitive decline in Parkinson's disease (PD) to inform patient management, clinical trial design, and development of treatments.

METHODS

We longitudinally assessed, up to 3 years, 423 newly diagnosed patients with idiopathic PD, untreated at baseline, from 33 international movement disorder centers. Study outcomes were four determinations of cognitive impairment or decline, and biomarker predictors were baseline dopamine transporter (DAT) single photon emission computed tomography (SPECT) scan, structural magnetic resonance imaging (MRI; volume and thickness), diffusion tensor imaging (mean diffusivity and fractional anisotropy), cerebrospinal fluid (CSF; amyloid beta [Aβ], tau and alpha synuclein), and 11 single nucleotide polymorphisms (SNPs) previously associated with PD cognition. Additionally, longitudinal structural MRI and DAT scan data were included. Univariate analyses were run initially, with false discovery rate = 0.2, to select biomarker variables for inclusion in multivariable longitudinal mixed-effect models.

RESULTS

By year 3, cognitive impairment was diagnosed in 15-38% participants depending on the criteria applied. Biomarkers, some longitudinal, predicting cognitive impairment in multivariable models were: (1) dopamine deficiency (decreased caudate and putamen DAT availability); (2) diffuse, cortical decreased brain volume or thickness (frontal, temporal, parietal, and occipital lobe regions); (3) co-morbid Alzheimer's disease Aβ amyloid pathology (lower CSF Aβ 1-42); and (4) genes (COMT val/val and BDNF val/val genotypes).

CONCLUSIONS

Cognitive impairment in PD increases in frequency 50-200% in the first several years of disease, and is independently predicted by biomarker changes related to nigrostriatal or cortical dopaminergic deficits, global atrophy due to possible widespread effects of neurodegenerative disease, co-morbid Alzheimer's disease plaque pathology, and genetic factors.