A comparison of prediction approaches for identifying prodromal Parkinson disease.
Ontology highlight
ABSTRACT:
SUBMITTER: Warden MN
PROVIDER: S-EPMC8389479 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The purpose of this study is to evaluate the relative risk of abnormal dopamine transporter (DAT) imaging for subjects with and without hyposmia and the feasibility of acquiring a large, community-based, 2-tiered biomarker assessment strategy to detect prodromal Parkinson disease (PD).In this observational study, individuals without a diagnosis of PD, recruited through 16 movement disorder clinics, underwent tier 1 assessments (olfactory testing, questionnaires). Tier 2 assessments (neurologic examination, DAT imaging, and other biomarker assessments) were completed by 303 subjects. The main outcome of the study is to compare age-expected [(123)I]?-CIT striatal binding ratio in hyposmic and normosmic subjects.Tier 1 assessments were mailed to 9,398 eligible subjects and returned by 4,999; 669 were hyposmic. Three hundred three subjects (203 hyposmic, 100 normosmic) completed baseline evaluations. DAT deficit was present in 11% of hyposmic subjects compared with 1% of normosmic subjects. Multiple logistic regression demonstrates hyposmia (odds ratio [OR] 12.4; 95% confidence interval [CI] 1.6, 96.1), male sex (OR 5.5; 95% CI 1.7, 17.2), and constipation (OR 4.3; 95% CI 1.6, 11.6) as factors predictive of DAT deficit. Combining multiple factors (hyposmia, male sex, and constipation) increased the percentage of subjects with a DAT deficit to >40%.Subjects with DAT deficit who do not meet criteria for a diagnosis of PD can be identified by olfactory testing. Sequential biomarker assessment may identify those at risk of PD. Selecting hyposmic individuals enriches the population for DAT deficit, and combining hyposmia with other potential risk factors (male sex, constipation) increases the percentage of subjects with a DAT deficit compatible with prodromal PD.
| S-EPMC4239830 | biostudies-literature
Project description:A prodromal phase of Parkinson's disease (PD) may precede motor manifestations by decades. PD patients' siblings are at higher risk for PD, but the prevalence and distribution of prodromal symptoms are unknown. The study objectives were (1) to assess motor and non-motor features estimating prodromal PD probability in PD siblings recruited within the European PROPAG-AGEING project; (2) to compare motor and non-motor symptoms to the well-established DeNoPa cohort. 340 PD siblings from three sites (Bologna, Seville, Kassel/Goettingen) underwent clinical and neurological evaluations of PD markers. The German part of the cohort was compared with German de novo PD patients (dnPDs) and healthy controls (CTRs) from DeNoPa. Fifteen (4.4%) siblings presented with subtle signs of motor impairment, with MDS-UPDRS-III scores not clinically different from CTRs. Symptoms of orthostatic hypotension were present in 47 siblings (13.8%), no different to CTRs (p = 0.072). No differences were found for olfaction and overall cognition; German-siblings performed worse than CTRs in visuospatial-executive and language tasks. 3/147 siblings had video-polysomnography-confirmed REM sleep behavior disorder (RBD), none was positive on the RBD Screening Questionnaire. 173/300 siblings had <1% probability of having prodromal PD; 100 between 1 and 10%, 26 siblings between 10 and 80%, one fulfilled the criteria for prodromal PD. According to the current analysis, we cannot confirm the increased risk of PD siblings for prodromal PD. Siblings showed a heterogeneous distribution of prodromal PD markers and probability. Additional parameters, including strong disease markers, should be investigated to verify if these results depend on validity and sensitivity of prodromal PD criteria, or if siblings' risk is not elevated.
| S-EPMC8423761 | biostudies-literature
Project description:INTRODUCTION:People with Parkinson disease (PD) may be at increased risk of delirium and associated adverse outcomes. Delirium is an acute neuropsychiatric syndrome defined by confusion and inattention and is common in older adults. Previous studies may have underestimated the prevalence of delirium in PD because of overlapping symptoms, lack of awareness, and poorly defined criteria. We aimed to identify the prevalence and incidence of delirium in inpatients with PD. MEASUREMENTS:Participants were inpatients with PD admitted over a 4-month period. Delirium prevalence was classified using a standardised assessment at a single visit on the basis of the Diagnostic and Statistical Manual of Mental Disorders fifth edition (DSM-5) criteria. To capture remaining time in hospital, incident delirium was diagnosed using detailed clinical vignettes and a validated consensus method. RESULTS:Forty-four PD patients consented to take part in the study, accounting for 53 admissions. Delirium prevalence was 34.0% (n = 18); reviewing participants over the duration of their hospital stay identified 30 (56.6%) incident delirium cases. The admitting team screened 24.5% for delirium, and delirium was documented in eight (14.8%) patients' medical notes. Patients with delirium were significantly older, had higher frailty scores, and had a longer hospital stay (P <?.05 for all). CONCLUSIONS:Delirium is common in PD inpatients at admission and incidence increases during hospital stay, but delirium is commonly missed. Our results highlight the importance of screening for delirium throughout patients' stay in hospital. Future studies should consider frequent evaluation over the duration of hospital stay to identify emergent delirium during the admission.
| S-EPMC7186820 | biostudies-literature
Project description:Numerically, the most important genetic risk factor for the development of Parkinson disease (PD) is the presence of a glucocerebrosidase gene (GBA) mutation.To evaluate longitudinally and clinically a GBA mutation-positive cohort and the evolution of the prodromal features of PD.Participants in a study of the etiology and prodrome of PD were reevaluated in this clinic-based 2-year follow-up report. Patients with type 1 Gaucher disease (GD) and heterozygous GBA mutation carriers were recruited in 2010 from the Lysosomal Storage Disorder Unit at the Royal Free Hospital, London, England. Thirty patients who previously received a diagnosis of type 1 GD, 28 heterozygous GBA mutation carriers, and 26 genetically unrelated controls were included. Exclusion criteria included a diagnosis of PD or dementia for both the patients with GD and the GBA mutation carriers and any existing neurological disease for the controls.Assessment was performed for clinical markers using standardized scales for hyposmia, rapid eye movement sleep behavior disorder, depression, autonomic dysfunction, cognitive function, and parkinsonian motor signs (using the Unified Parkinson's Disease Rating Scale motor subscale [UPDRS part III]).Over 2 years, depression scores were significantly worse for heterozygous carriers (mean baseline, 0.65; mean follow-up, 2.88; P?=?.01), rapid eye movement sleep behavior disorder scores were significantly worse for patients with GD (mean baseline, 0.93; mean follow-up, 2.93; P?<?.001) and heterozygotes (mean baseline, 0.10; mean follow-up, 2.30; P?<?.001), and UPDRS part III scores were significantly worse for patients with GD (mean baseline, 4.29; mean follow-up, 7.82; P?<?.001) and heterozygotes (mean baseline, 1.97; mean follow-up, 4.50; P?<?.001). For controls, there was a small but significant deterioration in the UPDRS part II (activities of daily living) score (mean baseline, 0.00; mean follow-up, 0.58; P?=?.006). At 2 years, olfactory and cognitive assessment scores were lower in patients with GD and heterozygotes compared with controls, but they did not differ significantly from baseline. When the results from the patients with GD and the heterozygotes were combined, a significant deterioration from baseline was observed, as reflected in the Rapid Eye Movement Sleep Behaviour Disorder Questionnaire (mean baseline, 0.51; mean follow-up, 2.63; P?<?.001), Beck Depression Inventory (mean baseline, 1.72; mean follow-up, 4.44; P?=?.002), and UPDRS part II (mean baseline, 0.88; mean follow-up, 2.01; P?<?.001) and part III scores (mean baseline, 3.09; mean follow-up, 6.10; P?<?.001) (all P?<?.01), and at 2 years, significant differences in University of Pennsylvania Smell Identification Test, Unified Multiple System Atrophy Rating Scale, Mini-Mental State Examination, Montreal Cognitive Assessment, and UPDRS part II and part III scores were observed between patients with GD/heterozygotes and controls (all P?<?.05).This study indicates that, as a group, GBA mutation-positive individuals show a deterioration in clinical markers consistent with the prodrome of PD. Within this group of individual, 10% appear to be evolving at a more rapid rate.
| S-EPMC4326672 | biostudies-literature
Project description:ImportanceDetecting individuals at risk for Parkinson disease (PD) during the prodromal phase could clarify disease mechanisms and allow for treatment earlier in the disease process to possibly slow or prevent the onset of motor PD.ObjectiveTo determine if the combination of smell identification testing followed by dopamine transporter (DAT) imaging can accurately and efficiently identify individuals from the general population at risk for conversion to a clinical diagnosis of PD.Design, setting, and participantsParticipants were identified from the community by olfactory testing assessed longitudinally with DAT imaging 2 and 4 years after baseline and by annual clinical follow-up to determine whether they had clinical evidence to establish a PD diagnosis. Participants were contacted by mail and completed olfactory testing at home. Longitudinal follow-up of clinical measures and DAT imaging occurred at specialty centers. There were 203 hyposmic and 100 normosmic participants. A total of 185 hyposmic and 95 normosmic individuals had at least 1 follow-up visit, and 152 hyposmic participants (82.2%) were either observed for 4 years or converted to PD during follow-up.Main outcomes and measuresPercentage of individuals with hyposmia and a DAT deficit that converted to PD and the change in PD clinical scale scores (Unified Parkinson's Disease Rating Scale) and DAT imaging during 4-year follow-up.ResultsOf 280 total participants, 140 (50.0%) were male, and the mean (SD) age of the cohort was 63 (8.7) years. Among 21 participants with hyposmia and a DAT deficit (65% or less of age-expected lowest putamen binding ratio) at baseline, 14 (67%) converted to PD at 4 years compared with 2 of 22 participants (9%) with a DAT in an indeterminate range (greater than 65%-80%) and 3 of 109 participants (2.8%) with no DAT deficit (greater than 80%) at baseline. Individuals with a baseline DAT deficit experienced a 4-year decline in DAT binding of 20.23% (SD, 15.04%) compared with 3.68% (SD, 18.36%) and 5.45% (SD, 13.58%) for participants with an indeterminate and no DAT deficit, respectively (P = .002). The relative risk of conversion to a diagnosis of PD in hyposmic individuals with a DAT deficit was 17.47 (95% CI, 7.02-43.45) compared with individuals with either indeterminate or no DAT deficit.Conclusions and relevanceThe combination of hyposmia and DAT deficit was highly predictive of conversion to PD within 4 years of clinical follow-up. Individuals with hyposmia and a DAT deficit had a 5% reduction in DAT binding annually, similar to early PD. These results provide a framework for planning disease prevention studies in PD.
| S-EPMC5710321 | biostudies-literature
Project description:Parkinson disease (PD) treatment options have conventionally focused on dopamine replacement and provision of symptomatic relief. Current treatments cause undesirable adverse effects, and a large unmet clinical need remains for treatments that offer disease modification and that address symptoms resistant to levodopa. Advances in high-throughput drug screening methods for small molecules, developments in disease modelling and improvements in analytical technologies have collectively contributed to the emergence of novel compounds, repurposed drugs and new technologies. In this Review, we focus on disease-modifying and symptomatic therapies under development for PD. We review cellular therapies and repurposed drugs, such as nilotinib, inosine, isradipine, iron chelators and anti-inflammatories, and discuss how their success in preclinical models has paved the way for clinical trials. We provide an update on immunotherapies and vaccines. In addition, we review non-pharmacological interventions targeting motor symptoms, including gene therapy, adaptive deep brain stimulation (DBS) and optogenetically inspired DBS. Given the many clinical phenotypes of PD, individualization of therapy and precision of treatment are likely to become important in the future.
| S-EPMC7758837 | biostudies-literature
Project description:The aim of this study was to evaluate the risk of Parkinson disease using clinical and demographic data alone and when combined with information from genes associated with Parkinson disease.A total of 1,967 participants in the dbGAP NeuroGenetics Research Consortium data set were included. Single-nucleotide polymorphisms associated with Parkinson disease at a genome-wide significance level in previous genome-wide association studies were included in risk prediction. Risk allele scores were calculated as the weighted count of the minor alleles. Five models were constructed. Discriminatory capability was evaluated using the area under the curve.Both family history and genetic risk scores increased risk for Parkinson disease. Although the fullest model, which included both family history and genetic risk information, resulted in the highest area under the curve, there were no significant differences between models using family history alone and those using genetic information alone.Adding genome-wide association study-derived genotypes, family history information, or both to standard demographic risk factors for Parkinson disease resulted in an improvement in discriminatory capacity. In the full model, the contributions of genotype data and family history information to discriminatory capacity were similar, and both were statistically significant. This suggests that there is limited overlap between genetic risk factors identified through genome-wide association study and unmeasured susceptibility variants captured by family history. Our results are similar to those of studies of other complex diseases and indicate that genetic risk prediction for Parkinson disease requires identification of additional genetic risk factors and/or better methods for risk prediction in order to achieve a degree of risk prediction that is clinically useful.Genet Med 2013:15(5):361-367.
| S-EPMC3687522 | biostudies-literature
Project description:Orthostatic hypotension (OH) is common in multiple system atrophy (MSA) and Parkinson disease (PD), generally assessed through a lying-to-standing orthostatic test. However, standing blood pressure may not be available due to orthostatic intolerance or immobilization for such patients. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were successively measured in supine, sitting, and standing positions in patients with MSA and PD. Receiver operating characteristic analysis was used to evaluate diagnostic performance of the drops of sitting SBP or DBP. OH and severe OH were respectively regarded as "gold standard". The drops of SBP in standing position were associated with increased disease severity for MSA and correlated with age for PD. In MSA group, drops in sitting SBP ≥ 14 mmHg or DBP ≥ 6 mmHg had highest validity for prediction of OH, and drops in sitting SBP ≥ 18 mmHg or DBP ≥ 8 mmHg for severe OH. In PD group, drops in sitting SBP ≥ 10 mmHg or DBP ≥ 6 mmHg had highest validity for prediction of OH. The lying-to-sitting orthostatic test is an alternative method for detection of OH in MSA and PD, especially when standing BP could not be validly measured due to various reasons.
| S-EPMC4751507 | biostudies-other
Project description:Public health interventions guided by clustering of HIV-1 molecular sequences may be impacted by choices of analytical approaches. We identified commonly-used clustering analytical approaches, applied them to 1886 HIV-1 Rhode Island sequences from 2004-2018, and compared concordance in identifying molecular HIV-1 clusters within and between approaches. We used strict (topological support ≥ 0.95; distance 0.015 substitutions/site) and relaxed (topological support 0.80-0.95; distance 0.030-0.045 substitutions/site) thresholds to reflect different epidemiological scenarios. We found that clustering differed by method and threshold and depended more on distance than topological support thresholds. Clustering concordance analyses demonstrated some differences across analytical approaches, with RAxML having the highest (91%) mean summary percent concordance when strict thresholds were applied, and three (RAxML-, FastTree regular bootstrap- and IQ-Tree regular bootstrap-based) analytical approaches having the highest (86%) mean summary percent concordance when relaxed thresholds were applied. We conclude that different analytical approaches can yield diverse HIV-1 clustering outcomes and may need to be differentially used in diverse public health scenarios. Recognizing the variability and limitations of commonly-used methods in cluster identification is important for guiding clustering-triggered interventions to disrupt new transmissions and end the HIV epidemic.
| S-EPMC7596705 | biostudies-literature
Project description:Predicting Retinal Pigment Epithelium (RPE) cell functions in stem cell implants using non-invasive bright field microscopy imaging is a critical task for clinical deployment of stem cell therapies. Such cell function predictions can be carried out using Artificial Intelligence (AI) based models. In this paper we used Traditional Machine Learning (TML) and Deep Learning (DL) based AI models for cell function prediction tasks. TML models depend on feature engineering and DL models perform feature engineering automatically but have higher modeling complexity. This work aims at exploring the tradeoffs between three approaches using TML and DL based models for RPE cell function prediction from microscopy images and at understanding the accuracy relationship between pixel-, cell feature-, and implant label-level accuracies of models. Among the three compared approaches to cell function prediction, the direct approach to cell function prediction from images is slightly more accurate in comparison to indirect approaches using intermediate segmentation and/or feature engineering steps. We also evaluated accuracy variations with respect to model selections (five TML models and two DL models) and model configurations (with and without transfer learning). Finally, we quantified the relationships between segmentation accuracy and the number of samples used for training a model, segmentation accuracy and cell feature error, and cell feature error and accuracy of implant labels. We concluded that for the RPE cell data set, there is a monotonic relationship between the number of training samples and image segmentation accuracy, and between segmentation accuracy and cell feature error, but there is no such a relationship between segmentation accuracy and accuracy of RPE implant labels.
| S-EPMC7450761 | biostudies-literature