Predicting Progression in Parkinson's Disease Using Baseline and 1-Year Change Measures.

BackgroundImproved prediction of Parkinson's disease (PD) progression is needed to support clinical decision-making and to accelerate research trials.ObjectivesTo examine whether baseline measures and their 1-year change predict longer-term progression in early PD.MethodsParkinson's Progression Markers Initiative study data were used. Participants had disease duration ≤2 years, abnormal dopamine transporter (DAT) imaging, and were untreated with PD medications. Baseline and 1-year change in clinical, cerebrospinal fluid (CSF), and imaging measures were evaluated as candidate predictors of longer-term (up to 5 years) change in Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) score and DAT specific binding ratios (SBR) using linear mixed-effects models.ResultsAmong 413 PD participants, median follow-up was 5 years. Change in MDS-UPDRS from year-2 to last follow-up was associated with disease duration (β= 0.351; 95% CI = 0.146, 0.555), male gender (β= 3.090; 95% CI = 0.310, 5.869), and baseline (β= -0.199; 95% CI = -0.315, -0.082) and 1-year change (β= 0.540; 95% CI = 0.423, 0.658) in MDS-UPDRS; predictors in the model accounted for 17.6% of the variance in outcome. Predictors of percent change in mean SBR from year-2 to last follow-up included baseline rapid eye movement sleep behavior disorder score (β= -0.6229; 95% CI = -1.2910, 0.0452), baseline (β= 7.232; 95% CI = 2.268, 12.195) and 1-year change (β= 45.918; 95% CI = 35.994,55.843) in mean striatum SBR, and 1-year change in autonomic symptom score (β= -0.325;95% CI = -0.695, 0.045); predictors in the model accounted for 44.1% of the variance.ConclusionsBaseline clinical, CSF, and imaging measures in early PD predicted change in MDS-UPDRS and dopamine-transporter binding, but the predictive value of the models was low. Adding the short-term change of possible predictors improved the predictive value, especially for modeling change in dopamine-transporter binding

Disposition of Federally Owned Surpluses

PDZ domains are scaffolding modules in protein-protein interactions that mediate numerous physiological functions by interacting canonically with the C-terminus or non-canonically with an internal motif of protein ligands. A conserved carboxylate-binding site in the PDZ domain facilitates binding via backbone hydrogen bonds; however, little is known about the role of these hydrogen bonds due to experimental challenges with backbone mutations. Here we address this interaction by generating semisynthetic PDZ domains containing backbone amide-to-ester mutations and evaluating the importance of individual hydrogen bonds for ligand binding. We observe substantial and differential effects upon amide-to-ester mutation in PDZ2 of postsynaptic density protein 95 and other PDZ domains, suggesting that hydrogen bonding at the carboxylate-binding site contributes to both affinity and selectivity. In particular, the hydrogen-bonding pattern is surprisingly different between the non-canonical and canonical interaction. Our data provide a detailed understanding of the role of hydrogen bonds in protein-protein interactions

Feasibility and Safety of Multicenter Tissue and Biofluid Sampling for α-Synuclein in Parkinson's Disease: The Systemic Synuclein Sampling Study (S4)

BACKGROUND: α-synuclein is a lead Parkinson's disease (PD) biomarker. There are conflicting reports regarding accuracy of α-synuclein in different tissues and biofluids as a PD biomarker, and the within-subject anatomical distribution of α-synuclein is not well described. The Systemic Synuclein Sampling Study (S4) aims to address these gaps in knowledge. The S4 is a multicenter, cross-sectional, observational study evaluating α-synuclein in multiple tissues and biofluids in PD and healthy controls (HC). OBJECTIVE: To describe the baseline characteristics of the S4 cohort and safety and feasibility of this study. METHODS: Participants underwent motor and non-motor clinical assessments, dopamine transporter SPECT, biofluid collection (cerebrospinal fluid, saliva, and blood), and tissue biopsies (skin, sigmoid colon, and submandibular gland). Biopsy adequacy was determined based on presence of adequate target tissue. Tissue sections were stained with the 5C12 monoclonal antibody against unmodified α-synuclein. All specimens were acquired and processed in a standardized manner. Adverse events were systematically recorded. RESULTS: The final cohort consists of 82 participants (61 PD, 21 HC). In 68 subjects (83%), all types of specimens were obtained but only 50 (61%) of subjects had all specimens both collected and evaluable for α-synuclein. Mild adverse events were common, especially for submandibular gland biopsy, but only 1 severe adverse event occurred. CONCLUSION: Multicenter tissue and biofluid sampling for α-synuclein is feasible and generally safe. S4 will inform understanding of the concurrent distribution of α-synuclein pathology and biomarkers in biofluids and peripheral nervous system in PD

Development and Practical Use of a Medical Vocabulary-Thesaurus-Dictionary for Patient Empowerment

Health empowerment can be obtained through an informative and educational intervention to increase one's ability to think critically and act autonomously. Medical texts are usually written by professionals and can be difficulty understood by non-experts who do not have the same skills and vocabularies. Thus, it would be desirable to have an online medical vocabulary-thesaurus-dictionary that can help a non-expert to easily find the consumer equivalent of medical (technical) terms and additional consumer information. To this end, we have developed an online multilingual medical vocabulary-thesaurus-dictionary by interconnecting different online sources, i.e., medical vocabularies to create a list of technical terms, consumer health vocabularies (CHVs) for translating technical terms into their consumer equivalents and consumer dictionaries for finding explanations of the terms. In addition, we have built an online editor that allows to add new medical terms (with the related consumer information) and modify existing consumer terms and definitions. Furthermore, we have built some practical applications, on top of the medical vocabulary-thesaurus-dictionary, in order to facilitate the empowerment of patients or non-experts in general. The applications are located at the data, information and knowledge levels of the \u2018knowledge pyramid\u2019 that, in our case, contains the empowerment at the top leve

Predicting Progression in Parkinson's Disease Using Baseline and 1-Year Change Measures.

BackgroundImproved prediction of Parkinson's disease (PD) progression is needed to support clinical decision-making and to accelerate research trials.ObjectivesTo examine whether baseline measures and their 1-year change predict longer-term progression in early PD.MethodsParkinson's Progression Markers Initiative study data were used. Participants had disease duration ≤2 years, abnormal dopamine transporter (DAT) imaging, and were untreated with PD medications. Baseline and 1-year change in clinical, cerebrospinal fluid (CSF), and imaging measures were evaluated as candidate predictors of longer-term (up to 5 years) change in Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) score and DAT specific binding ratios (SBR) using linear mixed-effects models.ResultsAmong 413 PD participants, median follow-up was 5 years. Change in MDS-UPDRS from year-2 to last follow-up was associated with disease duration (β= 0.351; 95% CI = 0.146, 0.555), male gender (β= 3.090; 95% CI = 0.310, 5.869), and baseline (β= -0.199; 95% CI = -0.315, -0.082) and 1-year change (β= 0.540; 95% CI = 0.423, 0.658) in MDS-UPDRS; predictors in the model accounted for 17.6% of the variance in outcome. Predictors of percent change in mean SBR from year-2 to last follow-up included baseline rapid eye movement sleep behavior disorder score (β= -0.6229; 95% CI = -1.2910, 0.0452), baseline (β= 7.232; 95% CI = 2.268, 12.195) and 1-year change (β= 45.918; 95% CI = 35.994,55.843) in mean striatum SBR, and 1-year change in autonomic symptom score (β= -0.325;95% CI = -0.695, 0.045); predictors in the model accounted for 44.1% of the variance.ConclusionsBaseline clinical, CSF, and imaging measures in early PD predicted change in MDS-UPDRS and dopamine-transporter binding, but the predictive value of the models was low. Adding the short-term change of possible predictors improved the predictive value, especially for modeling change in dopamine-transporter binding