Abstract INTRODUCTION Parkinson’s disease (PD) presents with motor and non-motor symptoms, including dementia, but the severity and rate of cognitive decline are heterogeneous and difficult to predict clinically. METHODS We quantified baseline serum proteins with the high-throughput SomaScan ® assay in 834 PD individuals and performed Cox regression to identify proteins associated with subsequent development of dementia. Candidate biomarker proteins were replicated in 371 individuals from an independent cohort and meta-analysed. RESULTS Protein targets significantly associated with progression to dementia were predominantly involved in synaptic plasticity, protein degradation/lysosomal function and extracellular matrix organisation. Mendelian Randomisation further revealed that changes in the Nogo receptor RTN4R may be causally associated with the development of Lewy body dementia. DISCUSSION We identified several proteins predicting progression to dementia in PD, indicating changes in blood proteome that precede the development of clinical symptoms by several years, providing a window of opportunity to identify at-risk individuals early on.

The high dimensionality of the input data can pose multiple problems when implementing statistical techniques. The presence of many dimensions in the data can lead to challenges in visualizing the data, higher computational demands, and a higher probability of over-fitting or under-fitting in modeling. Furthermore, the curse of dimensionality contributes to these issues by stating that the necessary number of observations for accurate modeling increases exponentially as the number of dimensions increases. Dimension reduction tools help overcome this challenge. Principal Component Analysis (PCA) is the most widely used technique, intensively studied in classical linear spaces. However, in applied sciences such as biology, bioinformatics, astronomy and geology, there are many instances in which the data's support are non-Euclidean spaces. In fact, the available data often include elements of Riemannian manifolds such as the unit circle, torus, sphere, and their extensions. Therefore, the terms "manifold-valued" or "directional" data are used in the literature for these situations. When dealing with directional data, the linear nature of PCA might pose a challenge to achieve accurate data reduction. This paper therefore reviews and investigates the methodological aspects of PCA on directional data and their practical applications.

BACKGROUND:The prevalence of Parkinson's disease rises with age and so patients may also be living with multimorbidity, two or more long-term conditions, and frailty, a loss of physiological reserve. However, these individuals are typically under-represented in clinical research. The aim was to describe the prevalence and interrelationship of frailty, multimorbidity, disability, sarcopenia and polypharmacy in a representative sample of people with parkinsonism recruited to the PRIME-UK cross-sectional study. METHODS:In this single-centre cross-sectional study of people with parkinsonism, we supported the inclusion of typically under-represented groups including those with impaired capacity to consent to the research. Participants, or their representative, completed questionnaires including self-reported comorbidities, medications, a sarcopenia screening tool and measures of frailty and disability. Venn diagrams were used to show the overlap between these domains and a hierarchical cluster analysis was performed to explore clustering. RESULTS:Only 78 (16.8 %) were categorised as neither frail nor multimorbid nor disabled. Almost all patients living with frailty were additionally living with disability and/or multimorbidity. It was uncommon to have multimorbidity and frailty without disability. Only 6 (1.3 %) had frailty without probable sarcopenia. Individuals clustered into three groups based on co-occurrence of some or all of these five domains. CONCLUSIONS:Amongst a representative sample of people with parkinsonism, there was a high frequency and co-occurrence of pre-frailty/frailty, sarcopenia, multimorbidity, polypharmacy and disability. This has implications for the structuring of health services for people with parkinsonism. There may also be opportunities to intervene to stop or slow the trajectory towards disability.

Analyzing data in non-Euclidean spaces, such as bioinformatics, biology, and geology, where variables represent directions or angles, poses unique challenges. This type of data is known as circular data in univariate cases and can be termed spherical or toroidal in multivariate contexts. In this paper, we introduce a novel extension of Probabilistic Principal Component Analysis (PPCA) designed for toroidal (or torus) data, termed Torus Probabilistic PCA (TPPCA). We provide detailed algorithms for implementing TPPCA and demonstrate its applicability to torus data. To assess the efficacy of TPPCA, we perform comparative analyses using a simulation study and three real datasets. Our findings highlight the advantages and limitations of TPPCA in handling torus data. Furthermore, we propose statistical tests based on likelihood ratio statistics to determine the optimal number of components, enhancing the practical utility of TPPCA for real-world applications.

BACKGROUND:Lower urinary tract symptoms (LUTS) are common Parkinson's disease (PD), causing great impact. OBJECTIVE:The goal was to undertake a phase II randomized control trial of transcutaneous tibial nerve stimulation (TTNS) delivered by Geko device for LUTS related to overactive bladder (OAB) in PD, an easy to use of the shelf solution. METHODS:Participants were randomized to active/sham stimulation. Primary outcome measure was the International Consultation on Incontinence Questionnaire-Overactive Bladder score (ICIQ-OAB) at 12 weeks. RESULTS:A total of 148 participants were allocated to active (73) and sham arms (75). No difference was seen between arms (coefficient, 0.48; 95% CI, -0.2 to 1.2; P = 0.17), although both active and sham showed improvements over baseline. Pain was the most common adverse event. CONCLUSION:No difference was seen between active and sham arms. Symptom improvements seen in both groups are consistent with a placebo effect, however, we cannot exclude a biological effect from the sham intervention. Although negative, this result should be taken only in context of Geko use rather TTNS in general. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Introduction: Gastrointestinal (GI) symptoms are some of the most common non-motor symptoms in Parkinson's. Weight is a nutritional metric and can be affected by dysfunction of the gastrointestinal (GI) tract. This study aims to explore the change in trajectory of body mass index (BMI) in individuals with Parkinson's over the course of the disease including the prodromal and post-diagnostic periods. Methods: This was a retrospective longitudinal study of data from participants from the PRIME Parkinson UK cross-sectional study. Participants were included if they had had one or more weights and height recorded in the primary care electronic health record. Results: 287 patients were initially included but only 234 could be included in the analysis of BMI trajectory. Using a piecewise linear mixed model, we determined that there was a 'change point' in BMI trajectory. This occurred on average 3.73 years after diagnosis, when the mean BMI was 26.4 kg/m2. Prior to this change point, the estimated mean rate of change in BMI was -0.09 kg/m2 (95 % credible interval -0.20,0.00 kg/m2) per year. However, after the change point, we observed a more accelerated decline in BMI, with an estimated mean rate of change of -0.34 kg/m2 (95 % credible interval -0.70,-0.07 kg/m2) per year. Conclusion: There was a modest weight loss trajectory in the pre-diagnostic period consistent with clinically stable weight. However, after several years, post-diagnosis BMI loss became more marked. In clinical practice interventions could be targeted at this time point to optimize and maintain nutritional intake.

Background: Dopaminergic responsiveness is a defining feature of Parkinson's disease (PD). However, there is limited information on how this evolves over time. Objectives: To examine serial dopaminergic responses, if there are distinct patterns, and which factors predict these. Methods: We analyzed data from the Parkinson's Progression Markers Initiative on repeated dopaminergic challenge tests (>= 24.5% defined as a definite response). Growth-mixture modeling evaluated for different response patterns and multinomial logistic regression tested for predictors of these clusters. Results: 1525 dopaminergic challenge tests were performed in 336 patients. At enrolment, mean age was 61.2 years (SD 9.6), 66.4% were male and disease duration was 0.5 years (SD 0.5). 1 to 2 years after diagnosis, 48.0% of tests showed a definite response, but this proportion increased with longer disease duration (51.1-74.3%). We identified 3 response groups: "Striking" (n = 29, 8.7%); "Excellent" (n = 110; 32.7%) and "Modest" (n = 197, 58.6%). Significant differences were as follows: striking responders commenced treatment earlier (P = 0.02), were less likely to be on dopamine agonist monotherapy (P = 0.01), and had better cognition (P < 0.01) and activities of daily living (P = 0.01). Excellent responders had higher challenge doses (P = 0.03) and were more likely to be on combination therapy (P < 0.01). Conclusion: Three distinct patterns of the dopaminergic response were observed. As the proportion of PD cases with definite dopa responsiveness increased over time, the initial treatment response may be an unreliable diagnostic aid.

BackgroundMotor complications are well recognized in Parkinson's disease (PD), but their reported prevalence varies and functional impact has not been well studied.ObjectivesTo quantify the presence, severity, impact and associated factors for motor complications in PD.MethodsAnalysis of three large prospective cohort studies of recent-onset PD patients followed for up to 12 years. The MDS-UPDRS part 4 assessed motor complications and multivariable logistic regression tested for associations. Genetic risk score (GRS) for Parkinson's was calculated from 79 single nucleotide polymorphisms.Results3343 cases were included (64.7% male). Off periods affected 35.0% (95% CI 33.0, 37.0) at 4-6 years and 59.0% (55.6, 62.3) at 8-10 years. Dyskinesia affected 18.5% (95% CI 16.9, 20.2) at 4-6 years and 42.1% (38.7, 45.5) at 8-10 years. Dystonia affected 13.4% (12.1, 14.9) at 4-6 years and 22.8% (20.1, 25.9) at 8-10 years. Off periods consistently caused greater functional impact than dyskinesia. Motor complications were more common among those with higher drug doses, younger age at diagnosis, female gender, and greater dopaminergic responsiveness (in challenge tests), with associations emerging 2-4 years post-diagnosis. Higher Parkinson's GRS was associated with early dyskinesia (0.026 <= P <= 0.050 from 2 to 6 years).ConclusionsOff periods are more common and cause greater functional impairment than dyskinesia. We confirm previously reported associations between motor complications with several demographic and medication factors. Greater dopaminergic responsiveness and a higher genetic risk score are two novel and significant independent risk factors for the development of motor complications.

ABSTRACTBackgroundNeuropathological studies, based on small samples, suggest that symptoms of Parkinson's disease (PD) emerge when dopamine/nigrostriatal loss is around 50–80%. Functional neuroimaging can be applied in larger numbers during life, which allows analysis of the extent of dopamine loss more directly.ObjectiveTo quantify dopamine transporter (DaT) activity by neuroimaging in early PD.MethodsSystematic review and novel analysis of DaT imaging studies in early PD.ResultsIn our systematic review, in 423 unique cases from 27 studies with disease duration of less than 6 years, mean age 58.0 (SD 11.5) years, and mean disease duration 1.8 (SD 1.2) years, striatal loss was 43.5% (95% CI 41.6, 45.4) contralaterally, and 36.0% (95% CI 33.6, 38.3) ipsilaterally. For unilateral PD, in 436 unique cases, mean age 57.5 (SD 10.2) years, and mean disease duration 1.8 (SD 1.4) years, striatal loss was 40.6% (95% CI 38.8, 42.4) contralaterally, and 31.6% (95% CI 29.4, 33.8) ipsilaterally. In our novel analysis of the Parkinson's Progressive Marker Initiative study, 413 cases had 1436 scans performed. For a disease duration of less than 1 year, age was 61.8 (SD 9.8) years, and striatal loss was 51.2% (95% CI 49.1, 53.3) contralaterally and 39.5% (36.9, 42.1) ipsilaterally, giving an overall striatal loss of 45.3% (43.0, 47.6).ConclusionsLoss of striatal DaT activity in early PD is less at 35–45%, rather than the 50–80% striatal dopamine loss estimated to be present at the time of symptom onset, based on backwards extrapolation from autopsy studies.

This paper proposes a linear model that uses the principal component scores in shape data and fits the nominal responses in the tangent space of shapes. Multinomial logistic regression for multivariate data and logistic regression for binary responses are considered in this regard. Principal components in the tangent space are employed to improve the estimation of logistic model parameters under multicollinearity and to reduce the dimension of the input data. This paper improves the classification of shape data according to their different nominal groups. Furthermore, we assess the effectiveness of the proposed method using a comprehensive simulation and highlight the benefits of the new method using five real-world data sets.

Academic conferences offer scientists the opportunity to share their findings and knowledge with other researchers. However, the number of conferences is rapidly increasing globally and many unsolicited e-mails are received from conference organizers. These e-mails take time for researchers to read and ascertain their legitimacy. Because not every conference is of high quality, there is a need for young researchers and scholars to recognize the so-called “predatory conferences” which make a profit from unsuspecting researchers without the core purpose of advancing science or collaboration. Unlike journals that possess accreditation indices, there is no appropriate accreditation for international conferences. Here, a bibliometric measure is proposed that enables scholars to evaluate conference quality before attending.

Multivariate circular observations, i.e. points on a torus are nowadays very common. Multivariate wrapped models are often appropriate to describe data points scattered on p-dimensional torus. However, statistical inference based on this model is quite complicated since each contribution in the log likelihood involve an infinite sum of indices in Z^p where p is the dimension of the problem. To overcome this, two estimates procedures based on Expectation Maximization and Classification Expectation Maximization algorithms are proposed that worked well in moderate dimension size. The performance of the introduced methods are studied by Monte Carlo simulation and illustrated on three real data sets.

Statistics, as one of the applied sciences, has great impacts in vast area of other sciences. Prediction of protein structures with great emphasize on their geometrical features using dihedral angles has invoked the new branch of statistics, known as directional statistics. One of the available biological techniques to predict is molecular dynamics simulations producing high-dimensional molecular structure data. Hence, it is expected that the principal component analysis (PCA) can response some related statistical problems particulary to reduce dimensions of the involved variables. Since the dihedral angles are variables on non-Euclidean space (their locus is the torus), it is expected that direct implementation of PCA does not provide great information in this case. The principal geodesic analysis is one of the recent methods to reduce the dimensions in the non-Euclidean case. A procedure to utilize this technique for reducing the dimension of a set of dihedral angles is highlighted in this paper. We further propose an extension of this tool, implemented in such way the torus is approximated by the product of two unit circle and evaluate its application in studying a real data set. A comparison of this technique with some previous methods is also undertaken.

This chapter was contributed by Andrew Speedy, University of Oxford, UK. The objective is to assist researchers to compile and analyze data. To this end, use is made of one of the simpler statistics programs (MINITAB, Minitab Inc., Philadelphia, USA) as the model. More powerful statistical packages may be required for studies in plant and animal genetics and agricultural economics. But, in line with the general philosophy of this manual, it is considered that simplicity and ease of understanding are the principal attributes required of a computer program and, in this respect, Minitab has much to commend it and is therefore selected as the example. But obviously there are various other often more sophisticated statistical software packages available on the market.