ObjectivesTo assess the neurobiological substrate of initial cognitive decline in Parkinson’s disease (PD) to inform patient management, clinical trial design, and development of treatments.MethodsWe longitudinally assessed, up to 3 years, 423 newly diagnosed patients with idiopathic PD, untreated at baseline, from 33 international movement disorder centers. Study outcomes were four determinations of cognitive impairment or decline, and biomarker predictors were baseline dopamine transporter (DAT) single photon emission computed tomography (SPECT) scan, structural magnetic resonance imaging (MRI; volume and thickness), diffusion tensor imaging (mean diffusivity and fractional anisotropy), cerebrospinal fluid (CSF; amyloid beta [Aβ], tau and alpha synuclein), and 11 single nucleotide polymorphisms (SNPs) previously associated with PD cognition. Additionally, longitudinal structural MRI and DAT scan data were included. Univariate analyses were run initially, with false discovery rate = 0.2, to select biomarker variables for inclusion in multivariable longitudinal mixed-effect models.ResultsBy year 3, cognitive impairment was diagnosed in 15–38% participants depending on the criteria applied. Biomarkers, some longitudinal, predicting cognitive impairment in multivariable models were: (1) dopamine deficiency (decreased caudate and putamen DAT availability); (2) diffuse, cortical decreased brain volume or thickness (frontal, temporal, parietal, and occipital lobe regions); (3) co-morbid Alzheimer’s disease Aβ amyloid pathology (lower CSF Aβ 1–42); and (4) genes (COMT val/val and BDNF val/val genotypes).ConclusionsCognitive impairment in PD increases in frequency 50–200% in the first several years of disease, and is independently predicted by biomarker changes related to nigrostriatal or cortical dopaminergic deficits, global atrophy due to possible widespread effects of neurodegenerative disease, co-morbid Alzheimer’s disease plaque pathology, and genetic factors.

The Self-Determined Learning Model of Instruction (SDLMI) is an evidence-based practice designed to enable teachers to teach students to self-regulate problem solving to set and attain educationally relevant goals. This study reports on findings and outcomes of the first year of a statewide implementation of the SDLMI by teachers working with students with intellectual disability to promote skills, knowledge, and beliefs that will lead to opportunities for meaningful, integrated employment. Data are reported on teacher fidelity of implementation of the SDLMI, student and teacher ratings of self-determination, student ratings of transition empowerment, and teacher ratings of student goal attainment. Data from the first year of the longitudinal implementation suggest that teachers can implement the SDLMI with fidelity, that students attain educationally relevant goals, and that teachers report changes in aspects of student self-determination, and that the SDLMI can be implemented statewide with school-, district-, and state-level supports. Recommendations for future research and policy-related implications for scaling-up efforts to promote self-determination are provided.

The Self-Determination Inventory: Student Report (SDI:SR) was developed to address a need in the field for tools to assess self-determination that are aligned with current best practices in assessment development and administration, and emerging research and best practices in promoting self-determination. The present study explored patterns of differences in self-determination scores across students with and without disabilities (i.e., no disability, learning disabilities, intellectual disability, autism spectrum disorder, and other health impairments) of varying racial-ethnic backgrounds (i.e., White, African American or Black, Hispanic or Latino[a], and Other) as well as the impact of receiving free and reduced price lunch (as a proxy for socioeconomic status) on self-determination scores in these groups. Findings suggest an interactive effect of disability, race-ethnicity, and free and reduced price lunch status on self-determination scores. Implications for future research and practice are discussed.

Parkinson's disease biomarkers are needed to increase diagnostic accuracy, to objectively monitor disease progression and to assess therapeutic efficacy as well as target engagement when evaluating novel drug and therapeutic strategies. This article summarizes perianalytical considerations for biomarker studies (based on immunoassays) in Parkinson's disease, with emphasis on quantifying total α‐synuclein protein in biological fluids. Current knowledge and pitfalls are discussed, and selected perianalytical variables are presented systematically, including different temperature of sample collection and types of collection tubes, gradient sampling, the addition of detergent, aliquot volume, the freezing time, and the different thawing methods. We also discuss analytical confounders. We identify gaps in the knowledge and delineate specific areas that require further investigation, such as the need to identify posttranslational modifications of α‐synuclein and antibody‐independent reference methods for quantification, as well as the analysis of potential confounders, such as comorbidities, medication, and phenotypes of Parkinson's disease in larger cohorts. This review could be used as a guideline for future Parkinson's disease biomarker studies and will require regular updating as more information arises in this growing field, including new technical developments as they become available. In addition to reviewing best practices, we also identify the current technical limitations and gaps in the knowledge that should be addressed to enable accurate and quantitative assessment of α‐synuclein levels in the clinical setting. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.