Prasinezumab slows motor progression in rapidly progressing early-stage Parkinson's disease.

Prasinezumab, a monoclonal antibody that binds aggregated α-synuclein, is being investigated as a potential disease-modifying therapy in early-stage Parkinson's disease. Although in the PASADENA phase 2 study, the primary endpoint (Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) sum of Parts I + II + III) was not met, prasinezumab-treated individuals exhibited slower progression of motor signs than placebo-treated participants (MDS-UPDRS Part III). We report here an exploratory analysis assessing whether prasinezumab showed greater benefits on motor signs progression in prespecified subgroups with faster motor progression. Prasinezumab's potential effects on disease progression were assessed in four prespecified and six exploratory subpopulations of PASADENA: use of monoamine oxidase B inhibitors at baseline (yes versus no); Hoehn and Yahr stage (2 versus 1); rapid eye movement sleep behavior disorder (yes versus no); data-driven subphenotypes (diffuse malignant versus nondiffuse malignant); age at baseline (≥60 years versus <60 years); sex (male versus female); disease duration (>12 months versus <12 months); age at diagnosis (≥60 years versus <60 years); motor subphenotypes (akinetic-rigid versus tremor-dominant); and motor subphenotypes (postural instability gait dysfunction versus tremor-dominant). In these subpopulations, the effect of prasinezumab on slowing motor signs progression (MDS-UPDRS Part III) was greater in the rapidly progressing subpopulations (for example, participants who were diffuse malignant or taking monoamine oxidase B inhibitors at baseline). This exploratory analysis suggests that, in a trial of 1-year duration, prasinezumab might reduce motor progression to a greater extent in individuals with more rapidly progressing Parkinson's disease. However, because this was a post hoc analysis, additional randomized clinical trials are needed to validate these findings.

Trial of Prasinezumab in Early-Stage Parkinson's Disease.

BACKGROUND: Aggregated α-synuclein plays an important role in the pathogenesis of Parkinson's disease. The monoclonal antibody prasinezumab, directed at aggregated α-synuclein, is being studied for its effect on Parkinson's disease. METHODS: In this phase 2 trial, we randomly assigned participants with early-stage Parkinson's disease in a 1:1:1 ratio to receive intravenous placebo or prasinezumab at a dose of 1500 mg or 4500 mg every 4 weeks for 52 weeks. The primary end point was the change from baseline to week 52 in the sum of scores on parts I, II, and III of the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS; range, 0 to 236, with higher scores indicating greater impairment). Secondary end points included the dopamine transporter levels in the putamen of the hemisphere ipsilateral to the clinically more affected side of the body, as measured by 123I-ioflupane single-photon-emission computed tomography (SPECT). RESULTS: A total of 316 participants were enrolled; 105 were assigned to receive placebo, 105 to receive 1500 mg of prasinezumab, and 106 to receive 4500 mg of prasinezumab. The baseline mean MDS-UPDRS scores were 32.0 in the placebo group, 31.5 in the 1500-mg group, and 30.8 in the 4500-mg group, and mean (±SE) changes from baseline to 52 weeks were 9.4±1.2 in the placebo group, 7.4±1.2 in the 1500-mg group (difference vs. placebo, -2.0; 80% confidence interval [CI], -4.2 to 0.2; P = 0.24), and 8.8±1.2 in the 4500-mg group (difference vs. placebo, -0.6; 80% CI, -2.8 to 1.6; P = 0.72). There was no substantial difference between the active-treatment groups and the placebo group in dopamine transporter levels on SPECT. The results for most clinical secondary end points were similar in the active-treatment groups and the placebo group. Serious adverse events occurred in 6.7% of the participants in the 1500-mg group and in 7.5% of those in the 4500-mg group; infusion reactions occurred in 19.0% and 34.0%, respectively. CONCLUSIONS: Prasinezumab therapy had no meaningful effect on global or imaging measures of Parkinson's disease progression as compared with placebo and was associated with infusion reactions. (Funded by F. Hoffmann-La Roche and Prothena Biosciences; PASADENA ClinicalTrials.gov number, NCT03100149.).

Reliability and validity of the Roche PD Mobile Application for remote monitoring of early Parkinson's disease.

Digital health technologies enable remote and therefore frequent measurement of motor signs, potentially providing reliable and valid estimates of motor sign severity and progression in Parkinson's disease (PD). The Roche PD Mobile Application v2 was developed to measure bradykinesia, bradyphrenia and speech, tremor, gait and balance. It comprises 10 smartphone active tests (with ½ tests administered daily), as well as daily passive monitoring via a smartphone and smartwatch. It was studied in 316 early-stage PD participants who performed daily active tests at home then carried a smartphone and wore a smartwatch throughout the day for passive monitoring (study NCT03100149). Here, we report baseline data. Adherence was excellent (96.29%). All pre-specified sensor features exhibited good-to-excellent test-retest reliability (median intraclass correlation coefficient = 0.9), and correlated with corresponding Movement Disorder Society-Unified Parkinson's Disease Rating Scale items (rho: 0.12-0.71). These findings demonstrate the preliminary reliability and validity of remote at-home quantification of motor sign severity with the Roche PD Mobile Application v2 in individuals with early PD.

Self-Report versus Clinician Examination in Early Parkinson's Disease.

BACKGROUND: Evaluating the discrepancies between patient-reported measures and clinician examination has implications for formulating individual treatment regimens. OBJECTIVE: This study investigated the association between health outcomes and level of self-reported motor-related function impairment relative to clinician-examined motor signs. METHODS: Recently 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. RESULTS: In 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). CONCLUSION: Self-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.

Hoehn and Yahr Stage and Striatal Dat-SPECT Uptake Are Predictors of Parkinson's Disease Motor Progression.

Currently, no treatments available for Parkinson's disease (PD) can slow PD progression. At the early stage of the disease, only a subset of individuals with PD progress quickly, while the majority have a slowly progressive form of the disease. In developing treatments that aim to slow PD progression, clinical trials aim to include individuals who are likely to progress faster, such that a treatment effect, if one exists, can be identified easier and earlier. The aim of the present study was to identify baseline predictors of clinical progression in early PD. We analyzed 12-month data acquired from the PASADENA trial Part 1 (NCT03100149, n = 76 participants who were allocated to the placebo arm and did not start symptomatic therapy) and the Parkinson's Progression Markers Initiative (PPMI) study (n = 139 demographically and clinically matched participants). By using ridge regression models including clinical characteristics, imaging, and non-imaging biomarkers, we found that Hoehn and Yahr stage and dopamine transporter single-photon emission computed tomography specific binding ratios (Dat-SPECT SBR) in putamen ipsilateral to the side of motor symptom onset predicted PD progression at the early stage of the disease. Further studies are needed to confirm the validity of these predictors to identify with high accuracy individuals with early PD with a faster progression phenotype.

A Phase II Study to Evaluate the Safety and Efficacy of Prasinezumab in Early Parkinson's Disease (PASADENA): Rationale, Design, and Baseline Data.

Background: Currently available treatments for Parkinson's disease (PD) do not slow clinical progression nor target alpha-synuclein, a key protein associated with the disease. Objective: The study objective was to evaluate the efficacy and safety of prasinezumab, a humanized monoclonal antibody that binds aggregated alpha-synuclein, in individuals with early PD. Methods: The PASADENA study is a multicenter, randomized, double-blind, placebo-controlled treatment study. Individuals with early PD, recruited across the US and Europe, received monthly intravenous doses of prasinezumab (1,500 or 4,500 mg) or placebo for a 52-week period (Part 1), followed by a 52-week extension (Part 2) in which all participants received active treatment. Key inclusion criteria were: aged 40-80 years; Hoehn & Yahr (H&Y) Stage I or II; time from diagnosis ≤2 years; having bradykinesia plus one other cardinal sign of PD (e.g., resting tremor, rigidity); DAT-SPECT imaging consistent with PD; and either treatment naïve or on a stable monoamine oxidase B (MAO-B) inhibitor dose. Study design assumptions for sample size and study duration were built using a patient cohort from the Parkinson's Progression Marker Initiative (PPMI). In this report, baseline characteristics are compared between the treatment-naïve and MAO-B inhibitor-treated PASADENA cohorts and between the PASADENA and PPMI populations. Results: Of the 443 patients screened, 316 were enrolled into the PASADENA study between June 2017 and November 2018, with an average age of 59.9 years and 67.4% being male. Mean time from diagnosis at baseline was 10.11 months, with 75.3% in H&Y Stage II. Baseline motor and non-motor symptoms (assessed using Movement Disorder Society-Unified Parkinson's Disease Rating Scale [MDS-UPDRS]) were similar in severity between the MAO-B inhibitor-treated and treatment-naïve PASADENA cohorts (MDS-UPDRS sum of Parts I + II + III [standard deviation (SD)]; 30.21 [11.96], 32.10 [13.20], respectively). The overall PASADENA population (63.6% treatment naïve and 36.4% on MAO-B inhibitor) showed a similar severity in MDS-UPDRS scores (e.g., MDS-UPDRS sum of Parts I + II + III [SD]; 31.41 [12.78], 32.63 [13.04], respectively) to the PPMI cohort (all treatment naïve). Conclusions: The PASADENA study population is suitable to investigate the potential of prasinezumab to slow disease progression in individuals with early PD. Trial Registration: NCT03100149.

Longitudinal Analysis of Multiple Neurotransmitter Metabolites in Cerebrospinal Fluid in Early Parkinson's Disease.

BACKGROUND: Cerebrospinal fluid (CSF) levels of monoamine metabolites may represent biomarkers of Parkinson's disease (PD). OBJECTIVE: The aim of this study was quantification of multiple metabolites in CSF from PD versus healthy control subjects (HCs), including longitudinal analysis. METHODS: Absolute levels of multiple monoamine metabolites in CSF were quantified by liquid chromatography coupled with tandem mass spectrometry from 161 individuals with early PD and 115 HCs from the Parkinson's Progression Marker Initiative and de novo PD (DeNoPA) studies. RESULTS: Baseline levels of homovanillic acid (HVA) and 3,4-dihydroxyphenylacetic acid (DOPAC) were lower in individuals with PD compared with HCs. HVA levels correlated with Movement Disorder Society Unified Parkinson's Disease Rating Scale total scores (P < 0.01). Both HVA/dopamine and DOPAC/dopamine levels correlated with caudate nucleus and raw DOPAC with putamen dopamine transporter single-photon emission computed tomography uptake ratios (P < 0.01). No metabolite changed over 2 years in drug-naive individuals, but some changed on starting levodopa treatment. CONCLUSIONS: HVA and DOPAC CSF levels mirrored nigrostriatal pathway damage, confirming the central role of dopaminergic degeneration in early PD. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Immunohistochemical Detection of Synuclein Pathology in Skin in Idiopathic Rapid Eye Movement Sleep Behavior Disorder and Parkinsonism.

BACKGROUND: Recent studies reported abnormal alpha-synuclein deposition in biopsy-accessible sites of the peripheral nervous system in Parkinson's disease (PD). This has considerable implications for clinical diagnosis. Moreover, if deposition occurs early, it may enable tissue diagnosis of prodromal PD. OBJECTIVE: The aim of this study was to develop and test an automated bright-field immunohistochemical assay of cutaneous pathological alpha-synuclein deposition in patients with idiopathic rapid eye movement sleep behavior disorder, PD, and atypical parkinsonism and in control subjects. METHODS: For assay development, postmortem skin biopsies were taken from 28 patients with autopsy-confirmed Lewy body disease and 23 control subjects. Biopsies were stained for pathological alpha-synuclein in automated stainers using a novel dual-immunohistochemical assay for serine 129-phosphorylated alpha-synuclein and pan-neuronal marker protein gene product 9.5. After validation, single 3-mm punch skin biopsies were taken from the cervical 8 paravertebral area from 79 subjects (28 idiopathic rapid eye movement sleep behavior disorder, 20 PD, 10 atypical parkinsonism, and 21 control subjects). Raters blinded to clinical diagnosis assessed the biopsies. RESULTS: The immunohistochemistry assay differentiated alpha-synuclein pathology from nonpathological-appearing alpha-synuclein using combined phosphatase and protease treatments. Among autopsy samples, 26 of 28 Lewy body samples and none of the 23 controls were positive. Among living subjects, punch biopsies were positive in 23 (82%) subjects with idiopathic rapid eye movement sleep behavior disorder, 14 (70%) subjects with PD, 2 (20%) subjects with atypical parkinsonism, and none (0%) of the control subjects. After a 3-year follow-up, eight idiopathic rapid eye movement sleep behavior disorder subjects phenoconverted to defined neurodegenerative syndromes, in accordance with baseline biopsy results. CONCLUSION: Even with a single 3-mm punch biopsy, there is considerable promise for using pathological alpha-synuclein deposition in skin to diagnose both clinical and prodromal PD. © 2020 International Parkinson and Movement Disorder Society.

Cats and Apples: Semantic Fluency Performance for Living Things Identifies Patients with Very Early Alzheimer's Disease.

OBJECTIVE: Reduced semantic memory performance is a known neuropsychological marker of very early Alzheimer's disease (AD), but the task format that best predicts disease status is an open question. The present study aimed to identify the semantic fluency task and measure that best discriminates early-stage AD patients (PATs) from cognitively healthy controls. METHOD: Semantic fluency performance for animals, fruits, tools, and vehicles was assessed in 70 early-stage AD PATs and 67 cognitively healthy participants. Logistic regressions and receiver operating characteristics were calculated for five total score semantic fluency measures. RESULTS: Compared with all other measures, living things (i.e., total correct animals + total correct fruits) achieved highest z-statistics, highest area under the curve and smallest difference between the upper and lower 95% confidence intervals. CONCLUSION: Living things total correct is a powerful tool to detect the earliest signs of incipient AD.

Outcome measures based on digital health technology sensor data: data- and patient-centric approaches.

Digital health technology tools (DHTT) are technologies such as apps, smartphones, and wearables that remotely acquire health-related information from individuals. They have the potential advantages of objectivity and sensitivity of measurement, richness of high-frequency sensor data, and opportunity for passive collection of health-related data. Thus, DHTTs promise to provide patient phenotyping at an order of granularity several times greater than is possible with traditional clinical research tools. While the conceptual development of novel DHTTs is keeping pace with technological and analytical advancements, an as yet unaddressed gap is how to develop robust and meaningful outcome measures based on sensor data. Here, we describe two roadmaps which were developed to generate outcome measures based on DHTT data: one using a data-centric approach and the second a patient-centric approach. The data-centric approach to develop digital outcome measures summarizes those sensor features maximally sensitive to the concept of interest, exemplified with the quantification of disease progression. The patient-centric approach summarizes those sensor features that are optimally relevant to patients' functioning in everyday life. Both roadmaps are exemplified for use in tracking disease progression in observational and clinical interventional studies, and with a DHTT designed to evaluate motor symptom severity and symptom experience in Parkinson's disease. Use cases other than disease progression (e.g., case-finding) are considered summarily. DHTT research requires methods to summarize sensor data into meaningful outcome measures. It is hoped that the concepts outlined here will encourage a scientific discourse and eventual consensus on the creation of novel digital outcome measures for both basic clinical research and clinical drug development.

Building a Machine-Learning Framework to Remotely Assess Parkinson's Disease Using Smartphones.

OBJECTIVE: Parkinson's disease (PD) is a neurodegenerative disorder that affects multiple neurological systems. Traditional PD assessment is conducted by a physician during infrequent clinic visits. Using smartphones, remote patient monitoring has the potential to obtain objective behavioral data semi-continuously, track disease fluctuations, and avoid rater dependency. METHODS: Smartphones collect sensor data during various active tests and passive monitoring, including balance (postural instability), dexterity (skill in performing tasks using hands), gait (the pattern of walking), tremor (involuntary muscle contraction and relaxation), and voice. Some of the features extracted from smartphone data are potentially associated with specific PD symptoms identified by physicians. To leverage large-scale cross-modality smartphone features, we propose a machine-learning framework for performing automated disease assessment. The framework consists of a two-step feature selection procedure and a generic model based on the elastic-net regularization. RESULTS: Using this framework, we map the PD-specific architecture of behaviors using data obtained from both PD participants and healthy controls (HCs). Utilizing these atlases of features, the framework shows promises to (a) discriminate PD participants from HCs, and (b) estimate the disease severity of individuals with PD. SIGNIFICANCE: Data analysis results from 437 behavioral features obtained from 72 subjects (37 PD and 35 HC) sampled from 17 separate days during a period of up to six months suggest that this framework is potentially useful for the analysis of remotely collected smartphone sensor data in individuals with PD.

Precompetitive Consensus Building to Facilitate the Use of Digital Health Technologies to Support Parkinson Disease Drug Development through Regulatory Science.

Innovative tools are urgently needed to accelerate the evaluation and subsequent approval of novel treatments that may slow, halt, or reverse the relentless progression of Parkinson disease (PD). Therapies that intervene early in the disease continuum are a priority for the many candidates in the drug development pipeline. There is a paucity of sensitive and objective, yet clinically interpretable, measures that can capture meaningful aspects of the disease. This poses a major challenge for the development of new therapies and is compounded by the considerable heterogeneity in clinical manifestations across patients and the fluctuating nature of many signs and symptoms of PD. Digital health technologies (DHT), such as smartphone applications, wearable sensors, and digital diaries, have the potential to address many of these gaps by enabling the objective, remote, and frequent measurement of PD signs and symptoms in natural living environments. The current climate of the COVID-19 pandemic creates a heightened sense of urgency for effective implementation of such strategies. In order for these technologies to be adopted in drug development studies, a regulatory-aligned consensus on best practices in implementing appropriate technologies, including the collection, processing, and interpretation of digital sensor data, is required. A growing number of collaborative initiatives are being launched to identify effective ways to advance the use of DHT in PD clinical trials. The Critical Path for Parkinson's Consortium of the Critical Path Institute is highlighted as a case example where stakeholders collectively engaged regulatory agencies on the effective use of DHT in PD clinical trials. Global regulatory agencies, including the US Food and Drug Administration and the European Medicines Agency, are encouraging the efficiencies of data-driven engagements through multistakeholder consortia. To this end, we review how the advancement of DHT can be most effectively achieved by aligning knowledge, expertise, and data sharing in ways that maximize efficiencies.

Progressive Decline in Gray and White Matter Integrity in de novo Parkinson's Disease: An Analysis of Longitudinal Parkinson Progression Markers Initiative Diffusion Tensor Imaging Data.

Background: Progressive neuronal loss in neurodegenerative diseases such as Parkinson's disease (PD) is associated with progressive degeneration of associated white matter tracts as measured by diffusion tensor imaging (DTI). These findings may have diagnostic and functional implications but their value in de novo PD remains unknown. Here we analyzed longitudinal DTI data from Parkinson's Progression Markers Initiative de novo PD patients for changes over time relative to healthy control (HC) participants. Methods: Baseline and 1-year follow-up DTI MRI data from 71 PD patients and 45 HC PPMI participants were included in the analyses. Whole-brain fractional anisotropy (FA) and mean diffusivity (MD) images were compared for baseline group differences and group-by-time interactions. Baseline and 1-year changes in DTI values were correlated with changes in DTI measures and symptom severity, respectively. Results: At baseline, PD patients showed significantly increased FA in brainstem, cerebellar, anterior corpus callosal, inferior frontal and inferior fronto-occipital white matter and increased MD in primary sensorimotor and supplementary motor regions. Over 1 year PD patients showed a significantly stronger decline in FA compared to HC in the optic radiation and corpus callosum and parietal, occipital, posterior temporal, posterior thalamic, and vermis gray matter. Significant increases in MD were observed in white matter of the midbrain, optic radiation and corpus callosum, while gray matter of prefrontal, insular and posterior thalamic regions. Baseline brainstem FA white matter (WM) values predicted 1-year changes in FA white matter and MD gray matter values. White but not gray matter changes in both FA and MD were significantly associated with changes in symptom severity. Conclusion: Significant gray and white matter DTI alterations are observable at the time of PD diagnosis and expand in the first year of de novo PD to other cortical and white matter regions. This pattern of DTI changes is in line with preclinical and neuroanatomical studies suggesting that the increased spatial spread of alpha-synuclein neuropathology is the key mechanism of PD progression. Taken together, these findings suggest that DTI may serve as a sensitive biomarker of disease progression in early-stage PD.

Evaluation of smartphone-based testing to generate exploratory outcome measures in a phase 1 Parkinson's disease clinical trial.

BACKGROUND: Ubiquitous digital technologies such as smartphone sensors promise to fundamentally change biomedical research and treatment monitoring in neurological diseases such as PD, creating a new domain of digital biomarkers. OBJECTIVES: The present study assessed the feasibility, reliability, and validity of smartphone-based digital biomarkers of PD in a clinical trial setting. METHODS: During a 6-month, phase 1b clinical trial with 44 Parkinson participants, and an independent, 45-day study in 35 age-matched healthy controls, participants completed six daily motor active tests (sustained phonation, rest tremor, postural tremor, finger-tapping, balance, and gait), then carried the smartphone during the day (passive monitoring), enabling assessment of, for example, time spent walking and sit-to-stand transitions by gyroscopic and accelerometer data. RESULTS: Adherence was acceptable: Patients completed active testing on average 3.5 of 7 times/week. Sensor-based features showed moderate-to-excellent test-retest reliability (average intraclass correlation coefficient = 0.84). All active and passive features significantly differentiated PD from controls with P < 0.005. All active test features except sustained phonation were significantly related to corresponding International Parkinson and Movement Disorder Society-Sponsored UPRDS clinical severity ratings. On passive monitoring, time spent walking had a significant (P = 0.005) relationship with average postural instability and gait disturbance scores. Of note, for all smartphone active and passive features except postural tremor, the monitoring procedure detected abnormalities even in those Parkinson participants scored as having no signs in the corresponding International Parkinson and Movement Disorder Society-Sponsored UPRDS items at the site visit. CONCLUSIONS: These findings demonstrate the feasibility of smartphone-based digital biomarkers and indicate that smartphone-sensor technologies provide reliable, valid, clinically meaningful, and highly sensitive phenotypic data in Parkinson's disease. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Parietal lobe critically supports successful paired immediate and single-item delayed memory for targets.

The parietal lobe is important for successful recognition memory, but its role is not yet fully understood. We investigated the parietal lobes' contribution to immediate paired-associate memory and delayed item-recognition memory separately for hits (targets) and correct rejections (distractors). We compared the behavioral performance of 56 patients with known parietal and medial temporal lobe dysfunction (i.e. early Alzheimer's Disease) to 56 healthy control participants in an immediate paired and delayed single item object memory task. Additionally, we performed voxel-based morphometry analyses to investigate the functional-neuroanatomic relationships between performance and voxel-based estimates of atrophy in whole-brain analyses. Behaviorally, all participants performed better identifying targets than rejecting distractors. The voxel-based morphometry analyses associated atrophy in the right ventral parietal cortex with fewer correct responses to familiar items (i.e. hits) in the immediate and delayed conditions. Additionally, medial temporal lobe integrity correlated with better performance in rejecting distractors, but not in identifying targets, in the immediate paired-associate task. Our findings suggest that the parietal lobe critically supports successful immediate and delayed target recognition memory, and that the ventral aspect of the parietal cortex and the medial temporal lobe may have complementary preferences for identifying targets and rejecting distractors, respectively, during recognition memory.

Neuropsychological Markers of Medial Perirhinal and Entorhinal Cortex Functioning are Impaired Twelve Years Preceding Diagnosis of Alzheimer's Dementia.

Neurofibrillary pathology in Alzheimer's dementia (AD) is associated with cognitive impairments and cortical thinning, and begins in medial perirhinal cortex (mPRC) before entering entorhinal cortex (ERC). Thus, mPRC dysfunction (e.g., semantic object memory impairments) may predate or accompany ERC (i.e., episodic memory) dysfunction in the preclinical course of typical AD. We developed formulae estimating mPRC and ERC integrity (i.e., cortical thickness) using common neuropsychological tests in 31 healthy individuals and 58 early AD patients. These formulae estimated the longitudinal courses of mPRC and ERC functioning in independent groups of 28 optimally healthy individuals who developed AD (NC-AD) over 2.8-13.4 years and 28 pairwise-matched, stable, healthy individuals (NC-NC). Mixed models demonstrated significantly worse NC-AD than NC-NC estimated mPRC and ERC functioning at the earliest observation, 12 years preceding diagnosis, and a significant decline 4 years preceding the AD diagnosis. These findings demonstrate that specific neuropsychological impairments occur early in the course of preclinical AD and that tasks measuring mPRC functioning may serve as additional, powerful markers of preclinical AD.

Cortical thinning of parahippocampal subregions in very early Alzheimer's disease.

The stereotypical pattern of neurofibrillary tangle spreading in the earliest stages of typical Alzheimer's dementia (AD) predicts that medial perirhinal cortex (mPRC) atrophy precedes entorhinal cortex (ERC) atrophy, whereas the status of the parahippocampal cortex (PHC) remains unclear. Atrophy studies have focused on more advanced rather than early AD patients, and usually segment the entire PRC as opposed to the mPRC versus lateral PRC (lPRC). The present study therefore determined the extent of ERC, mPRC, lPRC, and PHC atrophy in very early AD (mean Mini-Mental State Examination score = 26) patients and its presumed prodrome amnestic mild cognitive impairment (mean Mini-Mental State Examination score = 28) compared to demographically matched controls. PHG structures were manually segmented (blinded rater) and cortical thicknesses extracted. ERC and mPRC were similarly atrophied in both patient groups. The lPRC was atrophied in the AD group only. Thus, atrophic changes in very early AD broadly map onto the pattern of neurofibrillary tangle spreading and suggest that mPRC, ERC, and lPRC, but not PHC-associated functional impairments, characterize very early-stage AD.

Feature Statistics Modulate the Activation of Meaning During Spoken Word Processing.

Understanding spoken words involves a rapid mapping from speech to conceptual representations. One distributed feature-based conceptual account assumes that the statistical characteristics of concepts' features--the number of concepts they occur in (distinctiveness/sharedness) and likelihood of co-occurrence (correlational strength)--determine conceptual activation. To test these claims, we investigated the role of distinctiveness/sharedness and correlational strength in speech-to-meaning mapping, using a lexical decision task and computational simulations. Responses were faster for concepts with higher sharedness, suggesting that shared features are facilitatory in tasks like lexical decision that require access to them. Correlational strength facilitated responses for slower participants, suggesting a time-sensitive co-occurrence-driven settling mechanism. The computational simulation showed similar effects, with early effects of shared features and later effects of correlational strength. These results support a general-to-specific account of conceptual processing, whereby early activation of shared features is followed by the gradual emergence of a specific target representation.

The 12 Years Preceding Mild Cognitive Impairment Due to Alzheimer's Disease: The Temporal Emergence of Cognitive Decline.

BACKGROUND: The identification of the type and sequence of cognitive decline in preclinical mild cognitive impairment (MCI) prior to Alzheimer's disease (AD) is crucial for understanding AD pathogenesis and implementing therapeutic interventions. OBJECTIVE: To model the longitudinal courses of different neuropsychological functions in MCI due to AD. METHODS: We investigated the prodromal phase of MCI over a 12-year period in 27 initially healthy participants with subsequent MCI preceding AD (NC-MCI) and 60 demographically matched healthy individuals (NC-NC). The longitudinal courses of cognitive performance (verbal and visual episodic memory, semantic memory, executive functioning, constructional praxis, psychomotor speed, language, and informant-based reports) were analyzed with linear mixed effects models. RESULTS: The sequence with which different cognitive functions declined in the NC-MCI relative to the NC-NC group began with verbal memory and savings performance approximately eight years, and verbal episodic learning, visual memory, and semantic memory (animal fluency) circa four years prior to the MCI diagnosis. Executive functioning, psychomotor speed, and informant-based reports of the NC-MCI group declined approximately two years preceding the MCI diagnosis. CONCLUSIONS: Measurable neuropsychological deterioration occurs up to approximately eight years preceding MCI due to AD.

Varying strength of cognitive markers and biomarkers to predict conversion and cognitive decline in an early-stage-enriched mild cognitive impairment sample.

BACKGROUND: Several cognitive, neuroimaging, and cerebrospinal fluid (CSF) markers predict conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia. However, predictors might be more or less powerful depending on the characteristics of the MCI sample. OBJECTIVE: To investigate which cognitive markers and biomarkers predict conversion to AD dementia and course of cognitive functioning in a MCI sample with a high proportion of early-stage MCI patients. METHODS: Variables known to predict progression in MCI patients and hypothesized to predict progression in early-stage MCI patients were selected. Cognitive (long-delay free recall, regional primacy score), imaging (hippocampal and entorhinal cortex volumes, fornix fractional anisotropy), and CSF (Aß1-42/t-tau, Aß1-42) variables from 36 MCI patients were analyzed with Cox regression and mixed-effect models to determine their individual and combined abilities to predict time to conversion to AD dementia and course of global cognitive functioning, respectively. RESULTS: Those variables hypothesized to predict the course of early-stage MCI patients were most predictive for MCI progression. Specifically, regional primacy score (a measure of word-list position learning) most consistently predicted conversion to AD dementia and course of cognitive functioning. Both the prediction of conversion and course of cognitive functioning were maximized by including CSF Aß1-42 and fornix integrity biomarkers, respectively, indicating the complementary information carried by cognitive variables and biomarkers. CONCLUSION: Predictors of MCI progression need to be interpreted in light of the characteristics of the respective MCI sample. Future studies should aim to compare predictive strengths of markers between early-stage and late-stage MCI patients.