To begin to resolve conflicts among current competing taxonomies of child and adolescent psychopathology, the authors developed an interview covering the symptoms of anxiety, depression, inattention, and disruptive behavior used in the Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994), the International Statistical Classification of Diseases and Related Health Problems (ICD-10; World Health Organization, 1992), and several implicit taxonomies. This interview will be used in the future to compare the internal and external validity of alternative taxonomies. To provide an informative framework for future hypothesis-testing studies, the authors used principal factor analysis to induce new testable hypotheses regarding the structure of this item pool in a representative sample of 1,358 children and adolescents ranging in age from 4 to 17 years. The resulting hypotheses differed from the DSM-IV, particularly in suggesting that some anxiety symptoms are part of the same syndrome as depression, whereas separation anxiety, fears, and compulsions constitute a separate anxiety dimension.

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Background Accurate diagnosis and early detection of complex disease has the potential to be of enormous benefit to clinical trialists, patients, and researchers alike. We sought to create a non-invasive, low-cost, and accurate classification model for diagnosing Parkinson’s disease risk to serve as a basis for future disease prediction studies in prospective longitudinal cohorts. Methods We developed a simple disease classifying model within 367 patients with Parkinson’s disease and phenotypically typical imaging data and 165 controls without neurological disease of the Parkinson’s Progression Marker Initiative (PPMI) study. Olfactory function, genetic risk, family history of PD, age and gender were algorithmically selected as significant contributors to our classifying model. This model was developed using the PPMI study then tested in 825 patients with Parkinson’s disease and 261 controls from five independent studies with varying recruitment strategies and designs including the Parkinson’s Disease Biomarkers Program (PDBP), Parkinson’s Associated Risk Study (PARS), 23andMe, Longitudinal and Biomarker Study in PD (LABS-PD), and Morris K. Udall Parkinson’s Disease Research Center of Excellence (Penn-Udall). Findings Our initial model correctly distinguished patients with Parkinson’s disease from controls at an area under the curve (AUC) of 0.923 (95% CI = 0.900 – 0.946) with high sensitivity (0.834, 95% CI = 0.711 – 0.883) and specificity (0.903, 95% CI = 0.824 – 0.946) in PPMI at its optimal AUC threshold (0.655). The model is also well-calibrated with all Hosmer-Lemeshow simulations suggesting that when parsed into random subgroups, the actual data mirrors that of the larger expected data, demonstrating that our model is robust and fits well. Likewise external validation shows excellent classification of PD with AUCs of 0.894 in PDBP, 0.998 in PARS, 0.955 in 23andMe, 0.929 in LABS-PD, and 0.939 in Penn-Udall. Additionally, when our model classifies SWEDD as PD, they convert within one year to typical PD more than would be expected by chance, with 4 out of 17 classified as PD converting to PD during brief follow-up; while SWEDD not classified as PD showed one conversion to PD out of 38 participants (test of proportions, p-value = 0.003). Interpretation This model may serve as a basis for future investigations into the classification, prediction and treatment of Parkinson’s disease, particularly those planning on attempting to identify prodromal or preclinical etiologically typical PD cases in prospective cohorts for efficient interventional and biomarker studies. Funding Please see the acknowledgements and funding section at the end of the manuscript.

Objective: To report the rates and predictors of progression from normal cognition to either mild cognitive impairment (MCI) or dementia using standardized neuropsychological methods.Methods: A prospective cohort of patients diagnosed with Parkinson disease (PD) and baseline normal cognition was assessed for cognitive decline, performance, and function for a minimum of 2 years, and up to 6. A panel of movement disorders experts classified patients as having normal cognition, MCI, or dementia, with 55/68 (80.9%) of eligible patients seen at year 6. Kaplan-Meier curves and Cox proportional hazard models were used to examine cognitive decline and its predictors. Results:We enrolled 141 patients, who averaged 68.8 years of age, 63% men, who had PD on average for 5 years. The cumulative incidence of cognitive impairment was 8.5% at year 1, increasing to 47.4% by year 6. All incident MCI cases had progressed to dementia by year 5. In a multivariate analysis, predictors of future decline were male sex (p 5 0.02), higher Unified Parkinson's Disease Rating Scale motor score (p # 0.001), and worse global cognitive score (p , 0.001).Conclusions: Approximately half of patients with PD with normal cognition at baseline develop cognitive impairment within 6 years and all new MCI cases progress to dementia within 5 years. Our results show that the transition from normal cognition to cognitive impairment, including dementia, occurs frequently and quickly. Certain clinical and cognitive variables may be useful in predicting progression to cognitive impairment in PD. Nonmotor symptoms are common in Parkinson disease (PD), 1 including mild cognitive impairment (MCI) and dementia (PDD).2 Up to 80% of patients with PD develop dementia long-term, 3 and 20%-30% of patients with PD without dementia meet criteria for MCI. 4 Both PD-MCI and PDD impact negatively on patient quality of life, cost of care, and caregiver burden. 5,6 Longitudinal reports on patients with early PD-MCI show that more than 25% will develop dementia within 3 years, 7 and MCI at disease onset increases risk for development of dementia. 8Another study reported that up to 50% of patients with early PD developed cognitive decline within 5 years, 9 although the sample size was relatively small and lack of cognitive impairment at baseline was defined by Mini-Mental State Examination score only.Structural MRI, and plasma and CSF biomarkers, are associated with cognitive functioning and predict future cognitive decline in PD.1 However, many biomarkers are invasive, costly, and done mainly at academic centers conducting research. Demographic and clinical factors such as age, 10 motor subtypes, 11 and early visuospatial, language, and fluency deficits 12,13 have also been shown to predict future cognitive decline. However, to our knowledge, no research has focused on those patients defined as having normal cognition (NC) at baseline, which allows for examination of the course of cognitive decline from its clinical onset.

Background Several reports have identified different patterns of Parkinson's disease progression in individuals carrying missense variants in GBA or LRRK2 genes. The overall contribution of genetic factors to the severity and progression of Parkinson's disease, however, has not been well studied. Objectives To test the association between genetic variants and the clinical features of Parkinson's disease on a genomewide scale. Methods We accumulated individual data from 12 longitudinal cohorts in a total of 4093 patients with 22,307 observations for a median of 3.81 years. Genomewide associations were evaluated for 25 cross‐sectional and longitudinal phenotypes. Specific variants of interest, including 90 recently identified disease‐risk variants, were also investigated post hoc for candidate associations with these phenotypes. Results Two variants were genomewide significant. Rs382940(T>A), within the intron of SLC44A1, was associated with reaching Hoehn and Yahr stage 3 or higher faster (hazard ratio 2.04 [1.58–2.62]; P value = 3.46E‐8). Rs61863020(G>A), an intergenic variant and expression quantitative trait loci for α‐2A adrenergic receptor, was associated with a lower prevalence of insomnia at baseline (odds ratio 0.63 [0.52–0.75]; P value = 4.74E‐8). In the targeted analysis, we found 9 associations between known Parkinson's risk variants and more severe motor/cognitive symptoms. Also, we replicated previous reports of GBA coding variants (rs2230288: p.E365K; rs75548401: p.T408M) being associated with greater motor and cognitive decline over time, and an APOE E4 tagging variant (rs429358) being associated with greater cognitive deficits in patients. Conclusions We identified novel genetic factors associated with heterogeneity of Parkinson's disease. The results can be used for validation or hypothesis tests regarding Parkinson's disease. © 2019 International Parkinson and Movement Disorder Society

Cognitive impairment is one of the earliest, most common, and most disabling non-motor symptoms in Parkinson’s disease (PD). Thus, routine screening of global cognitive abilities is important for the optimal management of PD patients. Few global cognitive screening instruments have been developed for or validated in PD patients. The Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Dementia Rating Scale-2 (DRS-2) have been used extensively for cognitive screening in both clinical and research settings. Determining how to convert the scores between instruments would facilitate the longitudinal assessment of cognition in clinical settings and the comparison and synthesis of cognitive data in multicenter and longitudinal cohort studies. The primary aim of this study was to apply a simple and reliable algorithm for the conversion of MoCA to MMSE scores in PD patients. A secondary aim was to apply this algorithm for the conversion of DRS-2 to both MMSE and MoCA scores. The cognitive performance of a convenience sample of 360 patients with idiopathic PD was assessed by at least two of these cognitive screening instruments. We then developed conversion scores between the MMSE, MoCA, and DRS-2 using equipercentile equating and log-linear smoothing. The conversion score tables reported here enable direct and easy comparison of three routinely used cognitive screening assessments in PD patients.

ObjectiveTo determine if any association between previously identified alleles that confer risk for Parkinson disease and variables measuring disease progression.MethodsWe evaluated the association between 31 risk variants and variables measuring disease progression. A total of 23,423 visits by 4,307 patients of European ancestry from 13 longitudinal cohorts in Europe, North America, and Australia were analyzed.ResultsWe confirmed the importance of GBA on phenotypes. GBA variants were associated with the development of daytime sleepiness (p.N370S: hazard ratio [HR] 3.28 [1.69–6.34]) and possible REM sleep behavior (p.T408M: odds ratio 6.48 [2.04–20.60]). We also replicated previously reported associations of GBA variants with motor/cognitive declines. The other genotype-phenotype associations include an intergenic variant near LRRK2 and the faster development of motor symptom (Hoehn and Yahr scale 3.0 HR 1.33 [1.16–1.52] for the C allele of rs76904798) and an intronic variant in PMVK and the development of wearing-off effects (HR 1.66 [1.19–2.31] for the C allele of rs114138760). Age at onset was associated with TMEM175 variant p.M393T (−0.72 [−1.21 to −0.23] in years), the C allele of rs199347 (intronic region of GPNMB, 0.70 [0.27–1.14]), and G allele of rs1106180 (intronic region of CCDC62, 0.62 [0.21–1.03]).ConclusionsThis study provides evidence that alleles associated with Parkinson disease risk, in particular GBA variants, also contribute to the heterogeneity of multiple motor and nonmotor aspects. Accounting for genetic variability will be a useful factor in understanding disease course and in minimizing heterogeneity in clinical trials.

Objective The objective of this study was to determine the frequency and impact of subjective cognitive complaint (SCC) in Parkinson's disease (PD) patients with normal cognition. Methods Patients with PD with expert consensus‐determined normal cognition at baseline were asked a single question regarding the presence of SCC. Baseline (N = 153) and longitudinal (up to 4 follow‐up visits during a 5‐year period; N = 121) between‐group differences in patients with PD with (+SCC) and without (−SCC) cognitive complaint were examined, including cognitive test performance and self‐rated and informant‐rated functional abilities. Results A total of 81 (53%) participants reported a cognitive complaint. There were no between‐group differences in global cognition at baseline. Longitudinally, the +SCC group declined more than the −SCC group on global cognition (Mattis Dementia Rating Scale–2 total score, F1,431 = 5.71, P = 0.02), processing speed (Symbol Digit Modalities Test, F1,425 = 7.52, P = 0.006), and executive function (Trail Making Test Part B, F1,419 = 4.48, P = 0.04), although the results were not significant after correction for multiple testing. In addition, the +SCC group was more likely to progress to a diagnosis of cognitive impairment over time (hazard ratio = 2.61, P = 0.02). The +SCC group also demonstrated significantly lower self‐reported and knowledgeable informant–reported cognition‐related functional abilities at baseline, and declined more on an assessment of global functional abilities longitudinally. Conclusions Patients with PD with normal cognition, but with SCC, report poorer cognition‐specific functional abilities, and are more likely to be diagnosed with cognitive impairment and experience global functional ability decline long term. These findings suggest that SCC and worse cognition‐related functional abilities may be sensitive indicators of initial cognitive decline in PD. © 2020 International Parkinson and Movement Disorder Society