Identifying Parkinson's disease subtypes with motor and non-motor symptoms via model-based multi-partition clustering.
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ABSTRACT:
SUBMITTER: Rodriguez-Sanchez F
PROVIDER: S-EPMC8654994 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Chronic medical conditions show substantial heterogeneity in their clinical features and progression. We develop the novel data-driven, network-based Trajectory Profile Clustering (TPC) algorithm for 1) identification of disease subtypes and 2) early prediction of subtype/disease progression patterns. TPC is an easily generalizable method that identifies subtypes by clustering patients with similar disease trajectory profiles, based not only on Parkinson's Disease (PD) variable severity, but also on their complex patterns of evolution. TPC is derived from bipartite networks that connect patients to disease variables. Applying our TPC algorithm to a PD clinical dataset, we identify 3 distinct subtypes/patient clusters, each with a characteristic progression profile. We show that TPC predicts the patient's disease subtype 4 years in advance with 72% accuracy for a longitudinal test cohort. Furthermore, we demonstrate that other types of data such as genetic data can be integrated seamlessly in the TPC algorithm. In summary, using PD as an example, we present an effective method for subtype identification in multidimensional longitudinal datasets, and early prediction of subtypes in individual patients.
| S-EPMC7299311 | biostudies-literature
Project description:Parkinson's disease is now considered a complex, multi-peptide, central, and peripheral nervous system disorder with considerable clinical heterogeneity. Non-motor symptoms play a key role in the trajectory of Parkinson's disease, from prodromal premotor to end stages. To understand the clinical heterogeneity of Parkinson's disease, this study used cluster analysis to search for subtypes from a large, multi-center, international, and well-characterized cohort of Parkinson's disease patients across all motor stages, using a combination of cardinal motor features (bradykinesia, rigidity, tremor, axial signs) and, for the first time, specific validated rater-based non-motor symptom scales. Two independent international cohort studies were used: (a) the validation study of the Non-Motor Symptoms Scale (n = 411) and (b) baseline data from the global Non-Motor International Longitudinal Study (n = 540). k-means cluster analyses were performed on the non-motor and motor domains (domains clustering) and the 30 individual non-motor symptoms alone (symptoms clustering), and hierarchical agglomerative clustering was performed to group symptoms together. Four clusters are identified from the domains clustering supporting previous studies: mild, non-motor dominant, motor-dominant, and severe. In addition, six new smaller clusters are identified from the symptoms clustering, each characterized by clinically-relevant non-motor symptoms. The clusters identified in this study present statistical confirmation of the increasingly important role of non-motor symptoms (NMS) in Parkinson's disease heterogeneity and take steps toward subtype-specific treatment packages.
| S-EPMC5611404 | biostudies-literature
Project description:ObjectivesTo compare non-motor symptoms (NMSs) among patients with essential tremor (ET), Parkinson's disease (PD) subtypes (akinetic-rigid type (ART) and tremor-dominant type (TDT)), and healthy controls.Patients and methodsThis retrospective study included 129 participants, 72 PD (33 PD-ART, 33 PD-TDT, and 6 Mixed), 29 ET patients, and 28 controls. PD patients were assessed by the unified Parkinson's disease rating scale (UPDRS), Hoehn, and Yahr scale (H&Y), while ET patients were evaluated by the Fahn Tolosa Marin Tremor Rating Scale. All subjects were evaluated by non-motor symptoms scale (NMSS) for NMSs and Beck depression inventory (BDI) for depression.ResultsPD subtypes groups, ET, and controls were age and gender-matched. Compared to controls, all PD, PD subtypes, and ET showed significantly worse most of NMSs (p<0.001) and depression. Compared to ET, all PD and PD-ART had significantly worse gastrointestinal (p = 0.002), urinary symptoms (p = 0.001, p = 0.003) and depression (p = 0.002) and PD-TDT worse depression, while ET patients showed worse memory/attention than PD subtypes. Total NMSS of ET is highly correlated to depression and moderately to tremor severity and age of onset, while total of NMSS is highly correlated to depression, disease severity, and disability.ConclusionThe current study demonstrated several comparable domains of NMSs of PD subtypes and ET, except worse gastrointestinal and urinary symptoms among PD-ART. Identifying different NMSs profiles is important for predicting, better assessing, and tailoring management of ET and PD subtypes.
| S-EPMC7840014 | biostudies-literature
Project description:BackgroundIdentifying 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.MethodsWe 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.ResultsFor 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.ConclusionThe 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.
| S-EPMC9459236 | biostudies-literature
Project description:ObjectiveWe wished to explore Parkinson's disease (PD) subtypes by clustering analysis based on the multimodal magnetic resonance imaging (MRI) indices amplitude of low-frequency fluctuation (ALFF) and gray matter volume (GMV). Then, we analyzed the differences between PD subtypes.MethodsEighty-six PD patients and 44 healthy controls (HCs) were recruited. We extracted ALFF and GMV according to the Anatomical Automatic Labeling (AAL) partition using Data Processing and Analysis for Brain Imaging (DPABI) software. The Ward linkage method was used for hierarchical clustering analysis. DPABI was employed to compare differences in ALFF and GMV between groups.ResultsTwo subtypes of PD were identified. The "diffuse malignant subtype" was characterized by reduced ALFF in the visual-related cortex and extensive reduction of GMV with severe impairment in motor function and cognitive function. The "mild subtype" was characterized by increased ALFF in the frontal lobe, temporal lobe, and sensorimotor cortex, and a slight decrease in GMV with mild impairment of motor function and cognitive function.ConclusionHierarchical clustering analysis based on multimodal MRI indices could be employed to identify two PD subtypes. These two PD subtypes showed different neurodegenerative patterns upon imaging.
| S-EPMC9372337 | biostudies-literature
Project description:Background: Non-motor symptoms (NMS), including neuropsychiatric, sleep, autonomic, and sensory domains, are an integral aspect of the clinical presentation of Parkinson disease (PD) and affect neurocognitive functioning as well as patients' and caregivers' well-being. Objective: To describe the occurrence of NMS in PD patients with motor fluctuations in real-life condition. Methods: The present study is a secondary analysis of a previous multinational, multicenter, retrospective-prospective cohort observational study (SYNAPSES). Patients with PD diagnosis and motor fluctuations aged ≥18 years were included. Data collected at the baseline visit were used for this study, and descriptive analyzes were conducted to describe the distribution of NMS in motor-fluctuating PD patients distributed according to different clinical characteristics. Results: Of the 1,610 patients enrolled, 1,589 were included for the analysis (978 males and 611 females), with a mean age of 68.4 (SD = 9.6). Most patients had at least one NMS (88.5%). Sleep problems and psychiatric symptoms were the most prevalent NMS in motor fluctuating PD patients in all H and Y stages. Psychiatric disorders were more frequent in older patients and in patients with a larger number of years of PD diagnosis, while sleep problems were more preeminent in younger patients and with inferior disease duration. Conclusions: The present findings further support the high prevalence of NMS in PD patients with motor fluctuations, thus reinforcing the need for assessing them for diagnostic accuracy and for delivering holistic care.
| S-EPMC8276257 | biostudies-literature
Project description:BackgroundsSleep disorders are the most common and disabling symptoms in patients with Parkinson's disease (PD). Understanding the associations between sleep characteristics and motor and non-motor symptoms (NMSs) in PD can provide evidence to guide therapeutic interventions and nursing strategies. We aimed to investigate the association between sleep characteristics and motor function and NMSs in PD using multiple approaches.MethodsA total of 328 participants were included, and all participants underwent Pittsburgh Sleep Quality Index (PSQI) evaluation and clinical assessments of PD symptoms. We conducted Spearman's correlation to evaluate the associations between sleep and PD symptoms, nonlinear regression to assess the relationships between sleep habits and PD, and mediated analyses to test the effects of NMSs on global PSQI and PD severity, quality of life, and motor symptoms.ResultsPoor sleep was associated with more severe PD symptoms. In addition, the reflection point for bedtime was around 21:52, associated with motor symptoms, and insufficient and excessive total time spent in bed and nocturnal sleep duration were correlated with higher NMS burdens. The optimal points were 8-9.2 and 6.2-6.9 h, respectively. It was also discovered that NMSs played the mediating roles in global sleep with the quality of life, PD stages, and motor symptoms to a varying range of 6.8-95.4%.ConclusionsSleep disorders have a significant effect on the burden of PD symptoms. The current findings provide new insights into the monitoring and management of sleep and PD and need to be further explored in the future studies.
| S-EPMC9226540 | biostudies-literature
Project description:OBJECTIVE:The objective of this study was to assess the efficacy and safety of nabilone, a synthetic tetrahydrocannabinol analogue, as a treatment for non-motor symptoms (NMS) in Parkinson's disease (PD). METHODS:This was a phase II placebo-controlled, double-blind, parallel-group, enriched enrollment randomized withdrawal trial conducted at the Medical University Innsbruck. A random sample of 47 patients with PD with stable motor disease and disturbing NMS defined by a score of ?4 points on the Movement Disorder Society - Unified PD Rating Scale-I (MDS-UPDRS-I) underwent open-label nabilone titration (0.25 mg once daily to 1 mg twice daily, phase I). Responders were randomized 1:1 to continue with nabilone or switch to placebo for 4?weeks (phase II). The primary efficacy criterion was the change of the MDS-UPDRS-I between randomization and week 4. Safety was analyzed in all patients who received at least one nabilone dose. RESULTS:Between October 2017 and July 2019, 19 patients received either nabilone (median dose = 0.75 mg) or placebo. At week 4, mean change of the MDS-UPDRS-I was 2.63 (95% confidence interval [CI] 1.53 to 3.74, p =?0.002, effect size = 1.15) in the placebo versus 1.00 (95% CI -0.16 to 2.16, p =?0.280, effect size = 0.42) in the nabilone-group (difference: 1.63, 95% CI 0.09 to 3.18, p =?0.030, effect size = 0.66). Seventy-seven percent of patients had adverse events (AEs) during open-label titration, most of them were transient. In the double-blind phase, similar proportions of patients in each group had AEs (42% in the placebo group and 32% in the nabilone group). There were no serious AEs. INTERPRETATION:Our results highlight the potential efficacy of nabilone for patients with PD with disturbing NMS, which appears to be driven by positive effects on anxious mood and night-time sleep problems. TRIAL REGISTRY:ClinicalTrials.gov (NCT03769896) and EudraCT (2017-000192-86). ANN NEUROL 2020;88:712-722.
| S-EPMC7540547 | biostudies-literature
Project description:BackgroundNon-motor symptoms (NMS) are frequent in Parkinson's disease (PD).ObjectivesTo estimate the prevalence of NMS and of non-motor fluctuations (NMF) using the Movement Disorders Society-Non-Motor Rating Scale (MDS-NMS) and other scales assessing NMS, and their relationship with sex and PD severity.MethodsCross-sectional study with a sample of 402 PD patients. The Hoehn and Yahr staging system (HY), Clinical Impression of Severity Index for PD (CISI-PD), MDS-NMS (including NMF- subscale), Non-Motor Symptoms scale (NMSS), and MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) were applied. A NMS was considered present when scored ≥1. Differences in scores by sex and HY, CISI-PD, and MDS-UPDRS severity levels were calculated using Fisher's exact and chi-squared tests.ResultsUsing the MDS-NMS, NMS were present in 99.7% of patients and the mean number of NMS was 16.13 (SD: 9.36). The most prevalent NMS was muscle, joint or back pain (67.4% of the sample) and the least prevalent was dopamine dysregulation syndrome (2.2%). Feeling sad or depressed was significantly more prevalent in women. Using the MDS-NMS revealed more NMS than the other scales assessing NMS. NMF were present in 41% of the sample, with fatigue being the most prevalent symptom (68.5% patients with NMF), and no differences by sex. Patients with greater PD severity had higher prevalence of NMS than patients with lower severity.ConclusionsAlmost all patients with PD experience NMS, and many experience NMF. Prevalence rates for NMS using the MDS-NMS are higher than on other scales used and increase with higher disease severity.
| S-EPMC7853195 | biostudies-literature
Project description:Background and objectiveSex plays a role in Parkinson's disease (PD) mechanisms. We analyzed sex difference manifestations among Spanish patients with PD.Patients and methodsPD patients who were recruited from the Spanish cohort COPPADIS from January 2016 to November 2017 were included. A cross-sectional and a two-year follow-up analysis were conducted. Univariate analyses and general linear model repeated measure were used.ResultsAt baseline, data from 681 PD patients (mean age 62.54 ± 8.93) fit the criteria for analysis. Of them, 410 (60.2%) were males and 271 (39.8%) females. There were no differences between the groups in mean age (62.36 ± 8.73 vs. 62.8 ± 9.24; p = 0.297) or in the time from symptoms onset (5.66 ± 4.65 vs. 5.21 ± 4.11; p = 0.259). Symptoms such as depression (p < 0.0001), fatigue (p < 0.0001), and pain (p < 0.00001) were more frequent and/or severe in females, whereas other symptoms such as hypomimia (p < 0.0001), speech problems (p < 0.0001), rigidity (p < 0.0001), and hypersexuality (p < 0.0001) were more noted in males. Women received a lower levodopa equivalent daily dose (p = 0.002). Perception of quality of life was generally worse in females (PDQ-39, p = 0.002; EUROHIS-QOL8, p = 0.009). After the two-year follow-up, the NMS burden (Non-Motor Symptoms Scale total score) increased more significantly in males (p = 0.012) but the functional capacity (Schwab and England Activities of Daily Living Scale) was more impaired in females (p = 0.001).ConclusionThe present study demonstrates that there are important sex differences in PD. Long-term prospective comparative studies are needed.
| S-EPMC9960095 | biostudies-literature