Self-report data as a tool for subtype identification in genetically-defined Parkinson's Disease.
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ABSTRACT:
SUBMITTER: Winslow AR
PROVIDER: S-EPMC6113219 | biostudies-literature | 2018 Aug
REPOSITORIES: biostudies-literature
Publications
Self-report data as a tool for subtype identification in genetically-defined Parkinson's Disease.
Winslow Ashley R AR Hyde Craig L CL Wilk Jemma B JB Eriksson Nicholas N Cannon Paul P Miller Melissa R MR Hirst Warren D WD
Scientific reports 20180828 1
Through a targeted recruitment 23andMe has collected DNA and patient-reported symptoms from more than 10,000 subjects reporting a physician-verified diagnosis of PD. This study evaluated the potential of self-report, web-based questionnaires to rapidly assess disease natural history and symptomology in genetically-defined PD populations. While average age-at-diagnosis was significantly lower in GBA mutation carriers compared to idiopathic PD, or iPD (idiopathic PD, defined as no GBA mutations an ...[more]
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Project description:BackgroundEvaluating the discrepancies between patient-reported measures and clinician examination has implications for formulating individual treatment regimens.ObjectiveThis study investigated the association between health outcomes and level of self-reported motor-related function impairment relative to clinician-examined motor signs.MethodsRecently diagnosed PD patients were evaluated using the Parkinson's Progression Marker Initiative (PPMI, N = 420) and the PASADENA phase II clinical trial (N = 316). We calculated the average normalized difference between each participant's part II and III MDS-UPDRS (Movement Disorder Society Unified Parkinson's Disease Rating Scale) scores. Individuals with score differences <25th or >75th percentiles were labeled as low- and high-self-reporters, respectively (those between ranges were labeled intermediate-self-reporters). We compared a wide range of clinical/biomarker readouts among these three groups, using Kruskal-Wallis nonparametric and Pearson's χ2 tests. Spearman's correlations were tested for associations between MDS-UPDRS subscales.ResultsIn both cohorts, high-self-reporters reported the largest impairment/symptom experience for most motor and nonmotor patient-reported variables. By contrast, these high-self-reporters were similar to or less impaired on clinician-examined and biomarker measures. Patient-reported nonmotor symptoms on MDS-UPDRS part IB showed the strongest positive correlation with self-reported motor-related impairment (PPMI rs = 0.54, PASADENA rs = 0.52). This correlation was numerically stronger than the part II and clinician-examined MDS-UPDRS part III correlation (PPMI rs = 0.38, PASADENA rs = 0.28).ConclusionSelf-reported motor-related impairments reflect not only motor signs/symptoms but also other self-reported nonmotor measures. This may indicate (1) a direct impact of nonmotor symptoms on motor-related functioning and/or (2) the existence of general response tendencies in how patients self-rate symptoms. Our findings suggest further investigation into the suitability of MDS-UPDRS II to assess motor-related impairments. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Project description:BackgroundA 3-step clinical prediction tool including falling in the previous year, freezing of gait in the past month and self-selected gait speed <1.1 m/s has shown high accuracy in predicting falls in people with Parkinson's disease (PD). The accuracy of this tool when including only self-report measures is yet to be determined.ObjectivesTo validate the 3-step prediction tool using only self-report measures (3-step self-reported prediction tool), and to externally validate the 3-step clinical prediction tool.MethodsThe clinical tool was used with 137 individuals with PD. Participants also answered a question about self-reported gait speed, enabling scoring of the self-reported tool, and were followed-up for 6 months. An intraclass correlation coefficient (ICC2,1) was calculated to evaluate test-retest reliability of the 3-step self-reported prediction tool. Multivariate logistic regression models were used to evaluate the performance of both tools and their discriminative ability was determined using the area under the curve (AUC).ResultsForty-two participants (31%) reported ≥1 fall during follow-up. The 3-step self-reported tool had an ICC2,1 of 0.991 (95% CI 0.971-0.997; P < 0.001) and AUC = 0.68; 95% CI 0.59-0.77, while the 3-step clinical tool had an AUC = 0.69; 95% CI 0.60-0.78.ConclusionsThe 3-step self-reported prediction tool showed excellent test-retest reliability and was validated with acceptable accuracy in predicting falls in the next 6 months. The 3-step clinical prediction tool was externally validated with similar accuracy. The 3-step self-reported prediction tool may be useful to identify people with PD at risk of falls in e/tele-health settings.
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Project description:Parkinson's disease (PD) is the second most frequent neurogenic disease after Alzheimer's disease. The clinical manifestations include mostly motor disorders, such as bradykinesia, myotonia, and static tremors. Since the cause of this pathological features remain unclear, there is currently no radical treatment for PD. Environmental and genetic factors are thought to contribute to the pathology of PD. To identify the genetic factors, some studies employed the Genome-Wide Association Studies (GWAS) method and detected certain genes closely related to PD. However, the functions of these gene mutants in the development of PD are unknown. Combining GWAS and expression Quantitative Trait Loci (eQTL) analysis, the biological meaning of mutation could be explained to some extent. Therefore, the present investigation used Summary data-based Mendelian Randomization (SMR) analysis to integrate of two PD GWAS datasets and four eQTL datasets with the objective of identifying casual genes. Using this strategy, we found six Single Nucleotide Polymorphism (SNP) loci which could cause the development of PD through altering the susceptibility gene expression, and three risk genes: Synuclein Alpha (SNCA), Mitochondrial Poly(A) Polymerase (MTPAP), and RP11-305E6.4. We proved the accuracy of results through case studies and inferred the functions of these genes in PD. Overall, this study provides insights into the genetic mechanism behind PD, which is crucial for the study of the development of this disease and its diagnosis and treatment.
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Project description:Shame and embarrassment related to Parkinson's disease (PD) are rarely addressed in clinical practice nor studied in neuroscience research, partly because no specific tool exists to detect them in PD. Objective: To develop a self-applied assessment tool of shame and embarrassment specifically related to PD or its treatment, to promptly identify the presence and severity of these two emotions in PD. Methods: Identification and selection of relevant items were obtained from the collection of PD patients' opinions during support groups and interviews. Several further items were added following a literature review. Subsequently, a two-phase pilot study was performed for identification of ambiguous items and omissions, and to obtain preliminary data on acceptability, reliability, validity and relevance of the new scale (SPARK). Results: A total of 105 PD patients were enrolled in the study. Embarrassment was reported in 85% of patients, while shame was present in 26%. Fifteen percent of patients did not describe any shame or embarrassment. On average, the intensity of these two emotions was low with a marked floor effect in SPARK items and subscales. However, SPARK total score inter-individual variability was important (range 1-84 out of 99). Acceptability and quality of data were satisfactory with no floor or ceiling effects (2.9% each) or missing data. Internal consistency (Cronbach's alpha) was 0.94 for total score and 0.73-0.87 for subscales. The scale correlated ≥0.60 with instruments measuring related constructs. Content validity was satisfactory. SPARK total score strongly correlated with impaired health-related quality of life (rS = 0.81), the propensity to feel embarrassed or ashamed (rS = 0.68 and 0.66, respectively), and anxiety (rS = 0.72) and depression (rS = 0.63) levels. Moderate to high correlations were observed between SPARK total score and apathy (rS = 0.46) and a more pronounced personality trait directed toward harm avoidance (rS = 0.46). No significant differences in SPARK scores were found by sex, education level, PD duration, Hoehn and Yahr stages or PD phenotype. Conclusion: Preliminary analysis of psychometric properties suggests that SPARK could be an acceptable and reliable instrument for assessing shame and embarrassment in PD. SPARK could help healthcare professionals to identify and characterize PD-induced shame and embarrassment.
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Project description:IntroductionThe aim of this study was to evaluate odor identification testing as a quick, cheap, and reliable tool to identify PD.MethodsOdor identification with the 16-item Sniffin' Sticks test (SS-16) was assessed in a total of 646 PD patients and 606 controls from three European centers (A, B, and C), as well as 75 patients with atypical parkinsonism or essential tremor and in a prospective cohort of 24 patients with idiopathic rapid eye movement sleep behavior disorder (center A). Reduced odor sets most discriminative for PD were determined in a discovery cohort derived from a random split of PD patients and controls from center A using L1-regularized logistic regression. Diagnostic accuracy was assessed in the rest of the patients/controls as validation cohorts.ResultsOlfactory performance was lower in PD patients compared with controls and non-PD patients in all cohorts (each P < 0.001). Both the full SS-16 and a subscore of the top eight discriminating odors (SS-8) were associated with an excellent discrimination of PD from controls (areas under the curve ≥0.90; sensitivities ≥83.3%; specificities ≥82.0%) and from non-PD patients (areas under the curve ≥0.91; sensitivities ≥84.1%; specificities ≥84.0%) in all cohorts. This remained unchanged when patients with >3 years of disease duration were excluded from analysis. All 8 incident PD cases among patients with idiopathic rapid eye movement sleep behavior disorder were predicted with the SS-16 and the SS-8 (sensitivity, 100%; positive predictive value, 61.5%).ConclusionsOdor identification testing provides excellent diagnostic accuracy in the distinction of PD patients from controls and diagnostic mimics. A reduced set of eight odors could be used as a quick tool in the workup of patients presenting with parkinsonism and for PD risk indication. © 2016 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
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Project description:Apathy is a neurobehavioural symptom affecting Parkinson's disease patients of all disease stages. Apathy seems to be associated with a specific underlying non-motor disease subtype and reflects dysfunction of separate neural networks with distinct neurotransmitter systems. Due to the complicated neuropsychiatric aetiology of apathy, clinical assessment of this invalidating non-motor symptom remains challenging. We aim to summarize the current findings on apathy in Parkinson's disease and highlight knowledge gaps. We will discuss the prevalence rates across the different disease stages and suggest screening tools for clinically relevant apathetic symptoms. We will approach the fundamental knowledge on the neural networks implicated in apathy in a practical manner and formulate recommendations on patient-tailored treatment. We will discuss the Park apathy phenotype in detail, shedding light on different clinical manifestations and implications for prognosis. With this review, we strive to distil the vast available theoretical knowledge into a clinical and patient-oriented perspective.
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