Association between the LRP1B and APOE loci and the development of Parkinson's disease dementia.

Parkinson's disease is one of the most common age-related neurodegenerative disorders. Although predominantly a motor disorder, cognitive impairment and dementia are important features of Parkinson's disease, particularly in the later stages of the disease. However, the rate of cognitive decline varies among Parkinson's disease patients, and the genetic basis for this heterogeneity is incompletely understood. To explore the genetic factors associated with rate of progression to Parkinson's disease dementia, we performed a genome-wide survival meta-analysis of 3923 clinically diagnosed Parkinson's disease cases of European ancestry from four longitudinal cohorts. In total, 6.7% of individuals with Parkinson's disease developed dementia during study follow-up, on average 4.4 ± 2.4 years from disease diagnosis. We have identified the APOE ε4 allele as a major risk factor for the conversion to Parkinson's disease dementia [hazard ratio = 2.41 (1.94-3.00), P = 2.32 × 10-15], as well as a new locus within the ApoE and APP receptor LRP1B gene [hazard ratio = 3.23 (2.17-4.81), P = 7.07 × 10-09]. In a candidate gene analysis, GBA variants were also identified to be associated with higher risk of progression to dementia [hazard ratio = 2.02 (1.21-3.32), P = 0.007]. CSF biomarker analysis also implicated the amyloid pathway in Parkinson's disease dementia, with significantly reduced levels of amyloid ß42 (P = 0.0012) in Parkinson's disease dementia compared to Parkinson's disease without dementia. These results identify a new candidate gene associated with faster conversion to dementia in Parkinson's disease and suggest that amyloid-targeting therapy may have a role in preventing Parkinson's disease dementia.

Two sample Mendelian Randomisation using an outcome from a multilevel model of disease progression.

Identifying factors that are causes of disease progression, especially in neurodegenerative diseases, is of considerable interest. Disease progression can be described as a trajectory of outcome over time-for example, a linear trajectory having both an intercept (severity at time zero) and a slope (rate of change). A technique for identifying causal relationships between one exposure and one outcome in observational data whilst avoiding bias due to confounding is two sample Mendelian Randomisation (2SMR). We consider a multivariate approach to 2SMR using a multilevel model for disease progression to estimate the causal effect an exposure has on the intercept and slope. We carry out a simulation study comparing a naïve univariate 2SMR approach to a multivariate 2SMR approach with one exposure that effects both the intercept and slope of an outcome that changes linearly with time since diagnosis. The simulation study results, across six different scenarios, for both approaches were similar with no evidence against a non-zero bias and appropriate coverage of the 95% confidence intervals (for intercept 93.4-96.2% and the slope 94.5-96.0%). The multivariate approach gives a better joint coverage of both the intercept and slope effects. We also apply our method to two Parkinson's cohorts to examine the effect body mass index has on disease progression. There was no strong evidence that BMI affects disease progression, however the confidence intervals for both intercept and slope were wide.

Predicting Ambulatory Capacity in Parkinson's Disease to Analyze Progression, Biomarkers, and Trial Design.

BACKGROUND: In Parkinson's disease (PD), gait and balance is impaired, relatively resistant to available treatment and associated with falls and disability. Predictive models of ambulatory progression could enhance understanding of gait/balance disturbances and aid in trial design. OBJECTIVES: To predict trajectories of ambulatory abilities from baseline clinical data in early PD, relate trajectories to clinical milestones, compare biomarkers, and evaluate trajectories for enrichment of clinical trials. METHODS: Data from two multicenter, longitudinal, observational studies were used for model training (Tracking Parkinson's, n = 1598) and external testing (Parkinson's Progression Markers Initiative, n = 407). Models were trained and validated to predict individuals as having a "Progressive" or "Stable" trajectory based on changes of ambulatory capacity scores from the Movement Disorders Society Unified Parkinson's Disease Rating Scale parts II and III. Survival analyses compared time-to-clinical milestones and trial outcomes between predicted trajectories. RESULTS: On external evaluation, a support vector machine model predicted Progressive trajectories using baseline clinical data with an accuracy, weighted-F1 (proportionally weighted harmonic mean of precision and sensitivity), and sensitivity/specificity of 0.735, 0.799, and 0.688/0.739, respectively. Over 4 years, the predicted Progressive trajectory was more likely to experience impaired balance, loss of independence, impaired function and cognition. Baseline dopamine transporter imaging and select biomarkers of neurodegeneration were significantly different between predicted trajectory groups. For an 18-month, randomized (1:1) clinical trial, sample size savings up to 30% were possible when enrollment was enriched for the Progressive trajectory versus no enrichment. CONCLUSIONS: It is possible to predict ambulatory abilities from clinical data that are associated with meaningful outcomes in people with early PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Investigation of Autosomal Genetic Sex Differences in Parkinson's Disease.

OBJECTIVE: Parkinson's disease (PD) is a complex neurodegenerative disorder. Men are on average ~ 1.5 times more likely to develop PD compared to women with European ancestry. Over the years, genomewide association studies (GWAS) have identified numerous genetic risk factors for PD, however, it is unclear whether genetics contribute to disease etiology in a sex-specific manner. METHODS: In an effort to study sex-specific genetic factors associated with PD, we explored 2 large genetic datasets from the International Parkinson's Disease Genomics Consortium and the UK Biobank consisting of 13,020 male PD cases, 7,936 paternal proxy cases, 89,660 male controls, 7,947 female PD cases, 5,473 maternal proxy cases, and 90,662 female controls. We performed GWAS meta-analyses to identify distinct patterns of genetic risk contributing to disease in male versus female PD cases. RESULTS: In total, 19 genomewide significant regions were identified and no sex-specific effects were observed. A high genetic correlation between the male and female PD GWAS were identified (rg = 0.877) and heritability estimates were identical between male and female PD cases (~ 20%). INTERPRETATION: We did not detect any significant genetic differences between male or female PD cases. Our study does not support the notion that common genetic variation on the autosomes could explain the difference in prevalence of PD between males and females cases at least when considering the current sample size under study. Further studies are warranted to investigate the genetic architecture of PD explained by X and Y chromosomes and further evaluate environmental effects that could potentially contribute to PD etiology in male versus female patients. ANN NEUROL 2021;90:41-48.

Combining biomarkers for prognostic modelling of Parkinson's disease.

BACKGROUND: Patients with Parkinson's disease (PD) have variable rates of progression. More accurate prediction of progression could improve selection for clinical trials. Although some variance in clinical progression can be predicted by age at onset and phenotype, we hypothesise that this can be further improved by blood biomarkers. OBJECTIVE: To determine if blood biomarkers (serum neurofilament light (NfL) and genetic status (glucocerebrosidase, GBA and apolipoprotein E (APOE))) are useful in addition to clinical measures for prognostic modelling in PD. METHODS: We evaluated the relationship between serum NfL and baseline and longitudinal clinical measures as well as patients' genetic (GBA and APOE) status. We classified patients as having a favourable or an unfavourable outcome based on a previously validated model, and explored how blood biomarkers compared with clinical variables in distinguishing prognostic phenotypes . RESULTS: 291 patients were assessed in this study. Baseline serum NfL was associated with baseline cognitive status. Nfl predicted a shorter time to dementia, postural instability and death (dementia-HR 2.64; postural instability-HR 1.32; mortality-HR 1.89) whereas APOEe4 status was associated with progression to dementia (dementia-HR 3.12, 95% CI 1.63 to 6.00). NfL levels and genetic variables predicted unfavourable progression to a similar extent as clinical predictors. The combination of clinical, NfL and genetic data produced a stronger prediction of unfavourable outcomes compared with age and gender (area under the curve: 0.74-age/gender vs 0.84-ALL p=0.0103). CONCLUSIONS: Clinical trials of disease-modifying therapies might usefully stratify patients using clinical, genetic and NfL status at the time of recruitment.

Genetics of validated Parkinson's disease subtypes in the Oxford Discovery and Tracking Parkinson's cohorts.

OBJECTIVES: To explore the genetics of four Parkinson's disease (PD) subtypes that have been previously described in two large cohorts of patients with recently diagnosed PD. These subtypes came from a data-driven cluster analysis of phenotypic variables. METHODS: We looked at the frequency of genetic mutations in glucocerebrosidase (GBA) and leucine-rich repeat kinase 2 against our subtypes. Then we calculated Genetic Risk Scores (GRS) for PD, multiple system atrophy, progressive supranuclear palsy, Lewy body dementia, and Alzheimer's disease. These GRSs were regressed against the probability of belonging to a subtype in the two independent cohorts and we calculated q-values as an adjustment for multiple testing across four subtypes. We also carried out a Genome-Wide Association Study (GWAS) of belonging to a subtype. RESULTS: A severe disease subtype had the highest rates of patients carrying GBA mutations while the mild disease subtype had the lowest rates (p=0.009). Using the GRS, we found a severe disease subtype had a reduced genetic risk of PD (p=0.004 and q=0.015). In our GWAS no individual variants met genome wide significance (<5×10e-8) although four variants require further follow-up, meeting a threshold of <1×10e-6. CONCLUSIONS: We have found that four previously defined PD subtypes have different genetic determinants which will help to inform future studies looking at underlying disease mechanisms and pathogenesis in these different subtypes of disease.

The Impact of Type 2 Diabetes in Parkinson's Disease.

BACKGROUND: Type 2 diabetes (T2DM) is an established risk factor for developing Parkinson's disease (PD), but its effect on disease progression is not well understood. OBJECTIVE: The aim of this study was to investigate the influence of T2DM on aspects of disease progression in PD. METHODS: We analyzed data from the Tracking Parkinson's study to examine the effects of comorbid T2DM on PD progression and quality of life by comparing symptom severity scores assessing a range of motor and nonmotor symptoms. RESULTS: We identified 167 (8.7%) patients with PD and T2DM (PD + T2DM) and 1763 (91.3%) patients with PD without T2DM (PD). After controlling for confounders, patients with T2DM had more severe motor symptoms, as assessed by Movement Disorder Society Unified Parkinson's Disease Rating Scale, Part III (25.8 [0.9] vs. 22.5 [0.3] P = 0.002), and nonmotor symptoms, as assessed by Non-Motor Symptoms Scale total (38.4 [2.5] vs. 31.8 [0.7] P < 0.001), and were significantly more likely to report loss of independence (odds ratio, 2.08; 95% confidence interval [CI]: 1.34-3.25; P = 0.001) and depression (odds ratio, 1.62; CI: 1.10-2.39; P = 0.015). Furthermore, over time, patients with T2DM had significantly faster motor symptom progression (P = 0.012), developed worse mood symptoms (P = 0.041), and were more likely to develop substantial gait impairment (hazard ratio, 1.55; CI: 1.07-2.23; P = 0.020) and mild cognitive impairment (hazard ratio, 1.7; CI: 1.24-2.51; P = 0.002) compared with the PD group. CONCLUSIONS: In the largest study to date, T2DM is associated with faster disease progression in Parkinson's, highlighting an interaction between these two diseases. Because it is a potentially modifiable metabolic state, with multiple peripheral and central targets for intervention, it may represent a target for alleviating parkinsonian symptoms and slowing progression to disability and dementia. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

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.

Neuromelanin-MRI to Quantify and Track Nigral Depigmentation in Parkinson's Disease: A Multicenter Longitudinal Study Using Template-Based Standardized Analysis.

BACKGROUND: Clinical diagnosis and monitoring of Parkinson's disease (PD) remain challenging because of the lack of an established biomarker. Neuromelanin-magnetic resonance imaging (NM-MRI) is an emerging biomarker of nigral depigmentation indexing the loss of melanized neurons but has unknown prospective diagnostic and tracking performance in multicenter settings. OBJECTIVES: The aim was to investigate the diagnostic accuracy of NM-MRI in early PD in a multiprotocol setting and to determine and compare serial NM-MRI changes in PD and controls. METHODS: In this longitudinal case-control 3 T MRI study, 148 patients and 97 controls were included from six UK clinical centers, of whom 140 underwent a second scan after 1.5 to 3 years. An automated template-based analysis was applied for subregional substantia nigra NM-MRI contrast and volume assessment. A point estimate of the period of prediagnostic depigmentation was computed. RESULTS: All NM metrics performed well to discriminate patients from controls, with receiver operating characteristic showing 85% accuracy for ventral NM contrast and 83% for volume. Generalizability using a priori volume cutoff was good (79% accuracy). Serial MRI demonstrated accelerated NM loss in patients compared to controls. Ventral NM contrast loss was point estimated to start 5 to 6 years before clinical diagnosis. Ventral nigral depigmentation was greater in the most affected side, more severe cases, and nigral NM volume change correlated with change in motor severity. CONCLUSIONS: We demonstrate that NM-MRI provides clinically useful diagnostic information in early PD across protocols, platforms, and sites. It provides methods and estimated depigmentation rates that highlight the potential to detect preclinical PD and track progression for biomarker-enabled clinical trials. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Genome-Wide Association Studies of Cognitive and Motor Progression in Parkinson's Disease.

BACKGROUND: There are currently no treatments that stop or slow the progression of Parkinson's disease (PD). Case-control genome-wide association studies have identified variants associated with disease risk, but not progression. The objective of the current study was to identify genetic variants associated with PD progression. METHODS: We analyzed 3 large longitudinal cohorts: Tracking Parkinson's, Oxford Discovery, and the Parkinson's Progression Markers Initiative. We included clinical data for 3364 patients with 12,144 observations (mean follow-up 4.2 years). We used a new method in PD, following a similar approach in Huntington's disease, in which we combined multiple assessments using a principal components analysis to derive scores for composite, motor, and cognitive progression. These scores were analyzed in linear regression in genome-wide association studies. We also performed a targeted analysis of the 90 PD risk loci from the latest case-control meta-analysis. RESULTS: There was no overlap between variants associated with PD risk, from case-control studies, and PD age at onset versus PD progression. The APOE ε4 tagging variant, rs429358, was significantly associated with composite and cognitive progression in PD. Conditional analysis revealed several independent signals in the APOE locus for cognitive progression. No single variants were associated with motor progression. However, in gene-based analysis, ATP8B2, a phospholipid transporter related to vesicle formation, was nominally associated with motor progression (P = 5.3 × 10-6 ). CONCLUSIONS: We provide early evidence that this new method in PD improves measurement of symptom progression. We show that the APOE ε4 allele drives progressive cognitive impairment in PD. Replication of this method and results in independent cohorts are needed. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Genetic modifiers of risk and age at onset in GBA associated Parkinson's disease and Lewy body dementia.

Parkinson's disease is a genetically complex disorder. Multiple genes have been shown to contribute to the risk of Parkinson's disease, and currently 90 independent risk variants have been identified by genome-wide association studies. Thus far, a number of genes (including SNCA, LRRK2, and GBA) have been shown to contain variability across a spectrum of frequency and effect, from rare, highly penetrant variants to common risk alleles with small effect sizes. Variants in GBA, encoding the enzyme glucocerebrosidase, are associated with Lewy body diseases such as Parkinson's disease and Lewy body dementia. These variants, which reduce or abolish enzymatic activity, confer a spectrum of disease risk, from 1.4- to >10-fold. An outstanding question in the field is what other genetic factors that influence GBA-associated risk for disease, and whether these overlap with known Parkinson's disease risk variants. Using multiple, large case-control datasets, totalling 217 165 individuals (22 757 Parkinson's disease cases, 13 431 Parkinson's disease proxy cases, 622 Lewy body dementia cases and 180 355 controls), we identified 1691 Parkinson's disease cases, 81 Lewy body dementia cases, 711 proxy cases and 7624 controls with a GBA variant (p.E326K, p.T369M or p.N370S). We performed a genome-wide association study and analysed the most recent Parkinson's disease-associated genetic risk score to detect genetic influences on GBA risk and age at onset. We attempted to replicate our findings in two independent datasets, including the personal genetics company 23andMe, Inc. and whole-genome sequencing data. Our analysis showed that the overall Parkinson's disease genetic risk score modifies risk for disease and decreases age at onset in carriers of GBA variants. Notably, this effect was consistent across all tested GBA risk variants. Dissecting this signal demonstrated that variants in close proximity to SNCA and CTSB (encoding cathepsin B) are the most significant contributors. Risk variants in the CTSB locus were identified to decrease mRNA expression of CTSB. Additional analyses suggest a possible genetic interaction between GBA and CTSB and GBA p.N370S induced pluripotent cell-derived neurons were shown to have decreased cathepsin B expression compared to controls. These data provide a genetic basis for modification of GBA-associated Parkinson's disease risk and age at onset, although the total contribution of common genetics variants is not large. We further demonstrate that common variability at genes implicated in lysosomal function exerts the largest effect on GBA associated risk for disease. Further, these results have implications for selection of GBA carriers for therapeutic interventions.

Cognitive impairment in Parkinson's disease is multifactorial: A neuropsychological study.

BACKGROUND: In Parkinson's disease, mild cognitive impairment and dementia are associated with α-synuclein deposition and spread. However, coexistent Alzheimer's disease and cerebrovascular disease are common at autopsy, and may affect cognition. Our objective was to map cognitive impairment in Parkinson's disease to these different causes using clinical assessment. METHODS: Neuropsychological testing was performed in a cross-sectional sample of cognitively impaired patients with Parkinson's disease. The pattern of deficits in varying cognitive domains was mapped to the presentations that typify different diseases. Data were analysed by an expert multidisciplinary panel, referencing diagnostic criteria, to reach a consensus diagnosis for the cognitive dysfunction. RESULTS: There were 45 participants with Parkinson's disease and cognitive impairment, 73.3% male, mean age 69.1 years (SD 8.3). Twenty-seven (60.0%) had mild cognitive impairment, and 18 had dementia (40.0%). Cognitive impairment was primarily attributable to Lewy body disease alone in 19 of 45 patients (42.2%), to Lewy body disease plus Alzheimer's in 14 of 45 (31.1%), to Lewy body plus cerebrovascular disease in 6 of 45 (13.3%), and to Lewy body plus Alzheimer's and cerebrovascular disease in 1 of 45 (2.2%). The cognitive decline was not primarily Lewy-related in 5 of 45 patients (11.1%); in 4 of 45 (8.9%), it was primarily attributable to Alzheimer's disease, and 1 of 45 (2.2%) had behavioural-variant frontotemporal dementia. CONCLUSION: Neuropsychological testing identifies distinct patterns of cognitive impairment in Parkinson's disease that provide clear pointers to comorbid disease processes, the most common being Alzheimer's disease. This approach may prove useful in clinical practice and has implications for clinical trials that target α-synuclein.

Genetic analysis of Mendelian mutations in a large UK population-based Parkinson's disease study.

Our objective was to define the prevalence and clinical features of genetic Parkinson's disease in a large UK population-based cohort, the largest multicentre prospective clinico-genetic incident study in the world. We collected demographic data, Movement Disorder Society Unified Parkinson's Disease Rating Scale scores, and Montreal Cognitive Assessment scores. We analysed mutations in PRKN (parkin), PINK1, LRRK2 and SNCA in relation to age at symptom onset, family history and clinical features. Of the 2262 participants recruited to the Tracking Parkinson's study, 424 had young-onset Parkinson's disease (age at onset ≤ 50) and 1799 had late onset Parkinson's disease. A range of methods were used to genotype 2005 patients: 302 young-onset patients were fully genotyped with multiplex ligation-dependent probe amplification and either Sanger and/or exome sequencing; and 1701 late-onset patients were genotyped with the LRRK2 'Kompetitive' allele-specific polymerase chain reaction assay and/or exome sequencing (two patients had missing age at onset). We identified 29 (1.4%) patients carrying pathogenic mutations. Eighteen patients carried the G2019S or R1441C mutations in LRRK2, and one patient carried a heterozygous duplication in SNCA. In PRKN, we identified patients carrying deletions of exons 1, 4 and 5, and P113Xfs, R275W, G430D and R33X. In PINK1, two patients carried deletions in exon 1 and 5, and the W90Xfs point mutation. Eighteen per cent of patients with age at onset ≤30 and 7.4% of patients from large dominant families carried pathogenic Mendelian gene mutations. Of all young-onset patients, 10 (3.3%) carried biallelic mutations in PRKN or PINK1. Across the whole cohort, 18 patients (0.9%) carried pathogenic LRRK2 mutations and one (0.05%) carried an SNCA duplication. There is a significant burden of LRRK2 G2019S in patients with both apparently sporadic and familial disease. In young-onset patients, dominant and recessive mutations were equally common. There were no differences in clinical features between LRRK2 carriers and non-carriers. However, we did find that PRKN and PINK1 mutation carriers have distinctive clinical features compared to young-onset non-carriers, with more postural symptoms at diagnosis and less cognitive impairment, after adjusting for age and disease duration. This supports the idea that there is a distinct clinical profile of PRKN and PINK1-related Parkinson's disease. We estimate that there are approaching 1000 patients with a known genetic aetiology in the UK Parkinson's disease population. A small but significant number of patients carry causal variants in LRRK2, SNCA, PRKN and PINK1 that could potentially be targeted by new therapies, such as LRRK2 inhibitors.

Factor structure of the Montreal Cognitive Assessment in Parkinson disease.

OBJECTIVES: The Montreal Cognitive Assessment (MoCA) is a common tool for screening mild cognitive impairment (MCI) and dementia. Studies in multiple clinical groups provide evidence for various factor structures mapping to different cognitive domains. We tested the factor structure of the MoCA in a large cohort of early Parkinson disease (PD). MATERIALS AND METHODS: Complete MoCA data were available from an observational cohort study for 1738 patients with recent-onset PD (64.6% male, mean age 67.6, SD 9.2). Confirmatory factor analysis (CFA) was applied to test previously defined two-factor, six-factor, and three-factor models in the full sample and in a subgroup with possible cognitive impairment (MoCA < 26). Secondary analysis used exploratory factor analysis (EFA; principal factors with oblique rotation). RESULTS: The mean MoCA score was 25.3 (SD 3.4, range 10-30). Fit statistics in the six-factor model (χ2 /df 17.77, root mean square error of approximation [RMSEA] 0.10, comparative fit index [CFI] 0.74, Tucker-Lewis index [TLI] 0.69, standardised root mean square residual [SRMR] 0.07) indicated poorer fit than did previous studies. Findings were similar in the two-factor and three-factor models. EFA suggested an alternative six-factor solution (short-term recall, visuospatial-executive, attention/working memory, verbal-executive, orientation, and expressive language), although CFA did not support the validity of the new model. CONCLUSIONS: The factor structure of the MoCA in early PD was not consistent with that of previous research. This may reflect higher cognitive performance and differing demographics in our sample. The results do not support a clear, clinically relevant factor structure in an early PD group, suggesting that the MoCA should be followed with detailed assessment to obtain domain-specific cognitive profiles.

Neuropathology of dementia in patients with Parkinson's disease: a systematic review of autopsy studies.

BACKGROUND: Dementia is a common, debilitating feature of late Parkinson's disease (PD). PD dementia (PDD) is associated with α-synuclein propagation, but coexistent Alzheimer's disease (AD) pathology may coexist. Other pathologies (cerebrovascular, transactive response DNA-binding protein 43 (TDP-43)) may also influence cognition. We aimed to describe the neuropathology underlying dementia in PD. METHODS: Systematic review of autopsy studies published in English involving PD cases with dementia. Comparison groups included PD without dementia, AD, dementia with Lewy bodies (DLB) and healthy controls. RESULTS: 44 reports involving 2002 cases, 57.2% with dementia, met inclusion criteria. While limbic and neocortical α-synuclein pathology had the strongest association with dementia, between a fifth and a third of all PD cases in the largest studies had comorbid AD. In PD cases with dementia, tau pathology was moderate or severe in around a third, and amyloid-ß pathology was moderate or severe in over half. Amyloid-ß was associated with a more rapid cognitive decline and earlier mortality, and in the striatum, distinguished PDD from DLB. Positive correlations between multiple measures of α-synuclein, tau and amyloid-ß were found. Cerebrovascular and TDP-43 pathologies did not generally contribute to dementia in PD. TDP-43 and amyloid angiopathy correlated with coexistent Alzheimer pathology. CONCLUSIONS: While significant α-synuclein pathology is the main substrate of dementia in PD, coexistent pathologies are common. In particular, tau and amyloid-ß pathologies independently contribute to the development and pattern of cognitive decline in PD. Their presence should be assessed in future clinical trials where dementia is a key outcome measure. TRIAL REGISTRATION NUMBER: CRD42018088691.

The genetic and clinico-pathological profile of early-onset progressive supranuclear palsy.

BACKGROUND: Studies on early-onset presentations of progressive supranuclear palsy (PSP) have been limited to those where a rare monogenic cause has been identified. Here, we have defined early-onset PSP (EOPSP) and investigated its genetic and clinico-pathological profile in comparison with late-onset PSP (LOPSP) and Parkinson's disease (PD). METHODS: We included subjects from the Queen Square Brain Bank, PROSPECT-UK study, and Tracking Parkinson's study. Group comparisons of data were made using Welch's t-test and Kruskal-Wallis analysis of variance. EOPSP was defined as the youngest decile of motor age at onset (≤55 years) in the Queen Square Brain Bank PSP case series. RESULTS: We identified 33 EOPSP, 328 LOPSP, and 2000 PD subjects. The early clinical features of EOPSP usually involve limb parkinsonism and gait freezing, with 50% of cases initially misdiagnosed as having PD. We found that an initial clinical diagnosis of EOPSP had lower diagnostic sensitivity (33%) and positive predictive value (38%) in comparison with LOPSP (80% and 76%) using a postmortem diagnosis of PSP as the gold standard. 3/33 (9%) of the EOPSP group had an underlying monogenic cause. Using a PSP genetic risk score (GRS), we showed that the genetic risk burden in the EOPSP (mean z-score, 0.59) and LOPSP (mean z-score, 0.48) groups was significantly higher (P < 0.05) when compared with the PD group (mean z-score, -0.08). CONCLUSIONS: The initial clinical profile of EOPSP is often PD-like. At the group level, a PSP GRS was able to differentiate EOPSP from PD, and this may be helpful in future diagnostic algorithms. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Parkinson's disease age at onset genome-wide association study: Defining heritability, genetic loci, and α-synuclein mechanisms.

BACKGROUND: Increasing evidence supports an extensive and complex genetic contribution to PD. Previous genome-wide association studies (GWAS) have shed light on the genetic basis of risk for this disease. However, the genetic determinants of PD age at onset are largely unknown. OBJECTIVES: To identify the genetic determinants of PD age at onset. METHODS: Using genetic data of 28,568 PD cases, we performed a genome-wide association study based on PD age at onset. RESULTS: We estimated that the heritability of PD age at onset attributed to common genetic variation was ∼0.11, lower than the overall heritability of risk for PD (∼0.27), likely, in part, because of the subjective nature of this measure. We found two genome-wide significant association signals, one at SNCA and the other a protein-coding variant in TMEM175, both of which are known PD risk loci and a Bonferroni-corrected significant effect at other known PD risk loci, GBA, INPP5F/BAG3, FAM47E/SCARB2, and MCCC1. Notably, SNCA, TMEM175, SCARB2, BAG3, and GBA have all been shown to be implicated in α-synuclein aggregation pathways. Remarkably, other well-established PD risk loci, such as GCH1 and MAPT, did not show a significant effect on age at onset of PD. CONCLUSIONS: Overall, we have performed the largest age at onset of PD genome-wide association studies to date, and our results show that not all PD risk loci influence age at onset with significant differences between risk alleles for age at onset. This provides a compelling picture, both within the context of functional characterization of disease-linked genetic variability and in defining differences between risk alleles for age at onset, or frank risk for disease. © 2019 International Parkinson and Movement Disorder Society.

Features of GBA-associated Parkinson's disease at presentation in the UK Tracking Parkinson's study.

OBJECTIVES: To examine the influence of the glucocerebrosidase (GBA) mutation carrier state on age at onset of Parkinson's disease (PD), the motor phenotype and cognitive function at baseline assessment in a large cohort of UK patients. We also analysed the prevalence of mood and behavioural problems that may confound the assessment of cognitive function. METHODS: We prospectively recruited patients with PD in the Tracking Parkinson's study. We fully sequenced the GBA gene in all recently diagnosed patients (≤3.5 years). We examined cognitive (Montreal Cognitive Assessment) and motor (Movement Disorder Society Unified Parkinson's Disease Rating Scale part 3) function at a baseline assessment, at an average of 1.3 years after diagnosis. We used logistic regression to determine predictors of PD with mild cognitive impairment and PD with dementia. RESULTS: We studied 1893 patients with PD: 48 (2.5%) were heterozygous carriers for known Gaucher's disease (GD) causing pathogenic mutations; 117 (6.2%) had non-synonymous variants, previously associated with PD, and 28 (1.5%) patients carried variants of unknown significance in the GBA gene. L444P was the most common pathogenic GBA mutation. Patients with pathogenic GBA mutations were on average 5 years younger at disease onset compared with non-carriers (P=0.02). PD patients with GD-causing mutations did not have an increased family risk of PD. Patients with GBA mutations were more likely to present with the postural instability gait difficulty phenotype compared with non-carriers (P=0.02). Patients carrying pathogenic mutations in GBA had more advanced Hoehn and Yahr stage after adjustment for age and disease duration compared with non-carriers (P=0.005). There were no differences in cognitive function between GBA mutation carriers and non-carriers at this early disease stage. CONCLUSIONS: Our study confirms the influence of GBA mutations on the age of onset, disease severity and motor phenotype in patients with PD. Cognition did not differ between GBA mutation carriers and non-carriers at baseline, implying that cognitive impairment/dementia, reported in other studies at a later disease stage, is not present in recently diagnosed cases. This offers an important window of opportunity for potential disease-modifying therapy that may protect against the development of dementia in GBA-PD. CLINICAL TRIAL REGISTRATION: NCT02881099; Results.

Developing and validating Parkinson's disease subtypes and their motor and cognitive progression.

OBJECTIVES: To use a data-driven approach to determine the existence and natural history of subtypes of Parkinson's disease (PD) using two large independent cohorts of patients newly diagnosed with this condition. METHODS: 1601 and 944 patients with idiopathic PD, from Tracking Parkinson's and Discovery cohorts, respectively, were evaluated in motor, cognitive and non-motor domains at the baseline assessment. Patients were recently diagnosed at entry (within 3.5 years of diagnosis) and were followed up every 18 months. We used a factor analysis followed by a k-means cluster analysis, while prognosis was measured using random slope and intercept models. RESULTS: We identified four clusters: (1)  fast motor progression with symmetrical motor disease, poor olfaction, cognition and postural hypotension; (2) mild motor and non-motor disease with intermediate motor progression; (3) severe motor disease, poor psychological well-being and  poor sleep with an intermediate motor progression; (4) slow motor progression with tremor-dominant, unilateral disease. Clusters were moderately to substantially stable across the two cohorts (kappa 0.58). Cluster 1 had the fastest motor progression in Tracking Parkinson's at 3.2 (95% CI 2.8 to 3.6) UPDRS III points per year while cluster 4 had the slowest at 0.6 (0.1-1.1). In Tracking Parkinson's, cluster 2 had the largest response to levodopa 36.3% and cluster 4 the lowest 28.8%. CONCLUSIONS: We have found four novel clusters that replicated well across two independent early PD cohorts and were associated with levodopa response and motor progression rates. This has potential implications for better understanding disease pathophysiology and the relevance of patient stratification in future clinical trials.