An Alzheimer's Disease-Derived Biomarker Signature Identifies Parkinson's Disease Patients with Dementia

Cognitive heterogeneity in Parkinson's disease: A mechanistic view

Cognitive impairment occurs in most individuals with Parkinson's disease (PD), exacting a high toll on patients, their caregivers, and the healthcare system. In this review, we begin by summarizing the current clinical landscape surrounding cognition in PD. We then discuss how cognitive impairment and dementia may develop in PD based on the spread of the pathological protein alpha-synuclein (aSyn) from neurons in brainstem regions to those in the cortical regions of the brain responsible for higher cognitive functions, as first proposed in the Braak hypothesis. We appraise the Braak hypothesis from molecular (conformations of aSyn), cell biological (cell-to-cell spread of pathological aSyn), and organ-level (region-to-region spread of aSyn pathology at the whole brain level) viewpoints. Finally, we argue that individual host factors may be the most poorly understood aspect of this pathological process, accounting for substantial heterogeneity in the pattern and pace of cognitive decline in PD.

Prediction of Cognitive Degeneration in Parkinson's Disease Patients Using a Machine Learning Method

This study developed a predictive model for cognitive degeneration in patients with Parkinson's disease (PD) using a machine learning method. The clinical data, plasma biomarkers, and neuropsychological test results of patients with PD were collected and utilized as model predictors. Machine learning methods comprising support vector machines (SVMs) and principal component analysis (PCA) were applied to obtain a cognitive classification model. Using 32 comprehensive predictive parameters, the PCA-SVM classifier reached 92.3% accuracy and 0.929 area under the receiver operating characteristic curve (AUC). Furthermore, the accuracy could be increased to 100% and the AUC to 1.0 in a PCA-SVM model using only 13 carefully chosen features.

Quantitative detection of α-Synuclein and Tau oligomers and other aggregates by digital single particle counting

The pathological hallmark of neurodegenerative diseases is the formation of toxic oligomers by proteins such as alpha-synuclein (aSyn) or microtubule-associated protein tau (Tau). Consequently, such oligomers are promising biomarker candidates for diagnostics as well as drug development. However, measuring oligomers and other aggregates in human biofluids is still challenging as extreme sensitivity and specificity are required. We previously developed surface-based fluorescence intensity distribution analysis (sFIDA) featuring single-particle sensitivity and absolute specificity for aggregates. In this work, we measured aSyn and Tau aggregate concentrations of 237 cerebrospinal fluid (CSF) samples from five cohorts: Parkinson’s disease (PD), dementia with Lewy bodies (DLB), Alzheimer’s disease (AD), progressive supranuclear palsy (PSP), and a neurologically-normal control group. aSyn aggregate concentration discriminates PD and DLB patients from normal controls (sensitivity 73%, specificity 65%, area under the receiver operating curve (AUC) 0.68). Tau aggregates were significantly elevated in PSP patients compared to all other groups (sensitivity 87%, specificity 70%, AUC 0.76). Further, we found a tight correlation between aSyn and Tau aggregate titers among all patient cohorts (Pearson coefficient of correlation r = 0.81). Our results demonstrate that aSyn and Tau aggregate concentrations measured by sFIDA differentiate neurodegenerative disease diagnostic groups. Moreover, sFIDA-based Tau aggregate measurements might be particularly useful in distinguishing PSP from other parkinsonisms. Finally, our findings suggest that sFIDA can improve pre-clinical and clinical studies by identifying those individuals that will most likely respond to compounds designed to eliminate specific oligomers or to prevent their formation.

Appropriateness of Applying Cerebrospinal Fluid Biomarker Cutoffs from Alzheimer's Disease to Parkinson's Disease

BACKGROUND

While cutoffs for abnormal levels of the cerebrospinal fluid (CSF) biomarkers amyloid-β 1-42 (Aβ142), total tau (t-tau), phosphorylated tau (p-tau), and the ratios of t-tau/Aβ142 and p-tau/Aβ142, have been established in Alzheimer's disease (AD), biologically relevant cutoffs have not been studied extensively in Parkinson's disease (PD).

OBJECTIVE

Assess the suitability and diagnostic accuracy of established AD-derived CSF biomarker cutoffs in the PD population.

METHODS

Baseline and longitudinal data on CSF biomarkers, cognitive diagnoses, and PET amyloid imaging in 423 newly diagnosed patients with PD from the Parkinson's Progression Markers Initiative (PPMI) cohort were used to evaluate established AD biomarker cutoffs compared with optimal cutoffs derived from the PPMI cohort.

RESULTS

Using PET amyloid imaging as the gold standard for AD pathology, the optimal cutoff of Aβ142 was higher than the AD cutoff, the optimal cutoffs of t-tau/Aβ142 and p-tau/Aβ142 were lower than the AD cutoffs, and their confidence intervals (CIs) did not overlap with the AD cutoffs. Optimal cutoffs for t-tau and p-tau to predict cognitive impairment were significantly lower than the AD cutoffs, and their CIs did not overlap with the AD cutoffs.

CONCLUSION

Optimal cutoffs for the PPMI cohort for Aβ142, t-tau/Aβ142, and p-tau/Aβ142 to predict amyloid-PET positivity and for t-tau and p-tau to predict cognitive impairment differ significantly from cutoffs derived from AD populations. The presence of additional pathologies such as alpha-synuclein in PD may lead to disease-specific CSF biomarker characteristics.

The APOE ε4 variant and hippocampal atrophy in Alzheimer's disease and Lewy body dementia: a systematic review of magnetic resonance imaging studies and therapeutic relevance

Introduction: The apolipoprotein E ɛ4-allele (APOE-ɛ4) increases the risk not only for Alzheimer's disease (AD) but also for Parkinson's disease dementia and dementia with Lewy bodies (collectively, Lewy body dementia [LBD]). Hippocampal volume is an important neuroimaging biomarker for AD and LBD, although its association with APOE-ɛ4 is inconsistently reported. We investigated the association of APOE-ε4 with hippocampal atrophy quantified using magnetic resonance imaging in AD and LBD.Areas covered: Databases were searched for volumetric and voxel-based morphometric studies published up until December 31^st, 2020. Thirty-nine studies (25 cross-sectional, 14 longitudinal) were included. We observed that (1) APOE-ε4 was associated with greater rate of hippocampal atrophy in longitudinal studies in AD and in those who progressed from mild cognitive impairment to AD, (2) association of APOE-ε4 with hippocampal atrophy in cross-sectional studies was inconsistent, (3) APOE-ɛ4 may influence hippocampal atrophy in dementia with Lewy bodies, although longitudinal investigations are needed. We comprehensively discussed methodological aspects, APOE-based therapeutic approaches, and the association of APOE-ε4 with hippocampal sub-regions and cognitive performance.Expert opinion: The role of APOE-ɛ4 in modulating hippocampal phenotypes may be further clarified through more homogenous, well-powered, and pathology-proven, longitudinal investigations. Understanding the underlying mechanisms will facilitate the development of prevention strategies targeting APOE-ɛ4.

A Comparison of Serial Position Effects in Patients with Mild Cognitive Impairment due to Parkinson's Disease or to Alzheimer's Disease

OBJECTIVE

The first (primacy region) and last (recency region) items of a word list are generally better memorized than items from the middle region. The recency effect depends on short-term memory (STM) and the primacy effect on long-term memory (LTM), where verbal information is transferred from STM into LTM by maintenance rehearsal. We compared the serial position effects (SPE) between patients with mild cognitive impairment (MCI) due to Parkinson's disease (PD), i.e., PD-MCI, and patients with MCI due to Alzheimer's disease (AD-MCI), and evaluated the influence of SPE and frontostriatal deficits on verbal memory recall.

METHODS

Four similar groups of subjects participated in the study: 26 PD-MCI patients, 26 cognitively normal patients with PD (PD-CN), 26 AD-MCI patients, and 26 normal controls (NC). Verbal episodic memory, verbal span, attentional capacity, executive functions, and verbal working memory performance were assessed. Measures for primacy and recency regions were defined at the first trial of a 16-items word list. Hierarchical regression models were used to investigate the contribution of frontostriatal deficits beyond SPE on verbal memory recall performance ("long-delay free recall") in PD and AD patients.

RESULTS

Primacy effects were significantly diminished in both PD-MCI and AD-MCI patients relative to NC and PD-CN (all p < 0.01). Compared to PD-MCI patients, AD-MCI patients exhibited significantly worse "delayed-recall 'savings'." Reduced primacy effect was predictive for decreased recall performance in PD and AD. The conducted hierarchical regression model revealed that in PD, but not in AD patients, performance of attention and executive function significantly increased the prediction of free recalled words.

CONCLUSIONS

Reduced recall performance is likely due to impaired transition of newly learned material from STM into LTM in AD and in PD. Whereas AD-MCI patients suffer from a storage deficit, the similarly reduced recall performance found in patients with PD-MCI may additionally be related to deficient attentional and executive capacity.

Plasma and cerebrospinal fluid ABeta42 for the differential diagnosis of Alzheimer's disease dementia in participants diagnosed with any dementia subtype in a specialist care setting

BACKGROUND

Dementia is a syndrome that comprises many differing pathologies, including Alzheimer's disease dementia (ADD), vascular dementia (VaD) and frontotemporal dementia (FTD). People may benefit from knowing the type of dementia they live with, as this could inform prognosis and may allow for tailored treatment. Beta-amyloid (1-42) (ABeta42) is a protein which decreases in both the plasma and cerebrospinal fluid (CSF) of people living with ADD, when compared to people with no dementia. However, it is not clear if changes in ABeta42 are specific to ADD or if they are also seen in other types of dementia. It is possible that ABeta42 could help differentiate ADD from other dementia subtypes.

OBJECTIVES

To determine the accuracy of plasma and CSF ABeta42 for distinguishing ADD from other dementia subtypes in people who meet the criteria for a dementia syndrome.

SEARCH METHODS

We searched MEDLINE, and nine other databases up to 18 February 2020. We checked reference lists of any relevant systematic reviews to identify additional studies.

SELECTION CRITERIA

We considered cross-sectional studies that differentiated people with ADD from other dementia subtypes. Eligible studies required measurement of participant plasma or CSF ABeta42 levels and clinical assessment for dementia subtype.

DATA COLLECTION AND ANALYSIS

Seven review authors working independently screened the titles and abstracts generated by the searches. We collected data on study characteristics and test accuracy. We used the second version of the 'Quality Assessment of Diagnostic Accuracy Studies' (QUADAS-2) tool to assess internal and external validity of results. We extracted data into 2 x 2 tables, cross-tabulating index test results (ABeta42) with the reference standard (diagnostic criteria for each dementia subtype). We performed meta-analyses using bivariate, random-effects models. We calculated pooled estimates of sensitivity, specificity, positive predictive values, positive and negative likelihood ratios, and corresponding 95% confidence intervals (CIs). In the primary analysis, we assessed accuracy of plasma or CSF ABeta42 for distinguishing ADD from other mixed dementia types (non-ADD). We then assessed accuracy of ABeta42 for differentiating ADD from specific dementia types: VaD, FTD, dementia with Lewy bodies (DLB), alcohol-related cognitive disorder (ARCD), Creutzfeldt-Jakob disease (CJD) and normal pressure hydrocephalus (NPH). To determine test-positive cases, we used the ABeta42 thresholds employed in the respective primary studies. We then performed sensitivity analyses restricted to those studies that used common thresholds for ABeta42.

MAIN RESULTS

We identified 39 studies (5000 participants) that used CSF ABeta42 levels to differentiate ADD from other subtypes of dementia. No studies of plasma ABeta42 met the inclusion criteria. No studies were rated as low risk of bias across all QUADAS-2 domains. High risk of bias was found predominantly in the domains of patient selection (28 studies) and index test (25 studies). The pooled estimates for differentiating ADD from other dementia subtypes were as follows: ADD from non-ADD: sensitivity 79% (95% CI 0.73 to 0.85), specificity 60% (95% CI 0.52 to 0.67), 13 studies, 1704 participants, 880 participants with ADD; ADD from VaD: sensitivity 79% (95% CI 0.75 to 0.83), specificity 69% (95% CI 0.55 to 0.81), 11 studies, 1151 participants, 941 participants with ADD; ADD from FTD: sensitivity 85% (95% CI 0.79 to 0.89), specificity 72% (95% CI 0.55 to 0.84), 17 studies, 1948 participants, 1371 participants with ADD; ADD from DLB: sensitivity 76% (95% CI 0.69 to 0.82), specificity 67% (95% CI 0.52 to 0.79), nine studies, 1929 participants, 1521 participants with ADD. Across all dementia subtypes, sensitivity was greater than specificity, and the balance of sensitivity and specificity was dependent on the threshold used to define test positivity.

AUTHORS' CONCLUSIONS

Our review indicates that measuring ABeta42 levels in CSF may help differentiate ADD from other dementia subtypes, but the test is imperfect and tends to misdiagnose those with non-ADD as having ADD. We would caution against the use of CSF ABeta42 alone for dementia classification. However, ABeta42 may have value as an adjunct to a full clinical assessment, to aid dementia diagnosis.

Exploring the Etiological Links behind Neurodegenerative Diseases: Inflammatory Cytokines and Bioactive Kynurenines

Alzheimer's disease (AD) and Parkinson's disease (PD) are the most common neurodegenerative diseases (NDs), presenting a broad range of symptoms from motor dysfunctions to psychobehavioral manifestations. A common clinical course is the proteinopathy-induced neural dysfunction leading to anatomically corresponding neuropathies. However, current diagnostic criteria based on pathology and symptomatology are of little value for the sake of disease prevention and drug development. Overviewing the pathomechanism of NDs, this review incorporates systematic reviews on inflammatory cytokines and tryptophan metabolites kynurenines (KYNs) of human samples, to present an inferential method to explore potential links behind NDs. The results revealed increases of pro-inflammatory cytokines and neurotoxic KYNs in NDs, increases of anti-inflammatory cytokines in AD, PD, Huntington's disease (HD), Creutzfeldt-Jakob disease, and human immunodeficiency virus (HIV)-associated neurocognitive disorders, and decreases of neuromodulatory KYNs in AD, PD, and HD. The results reinforced a strong link between inflammation and neurotoxic KYNs, confirmed activation of adaptive immune response, and suggested a possible role in the decrease of neuromodulatory KYNs, all of which may contribute to the development of chronic low grade inflammation. Commonalities of multifactorial NDs were discussed to present a current limit of diagnostic criteria, a need for preclinical biomarkers, and an approach to search the initiation factors of NDs.

Apolipoprotein E Polymorphisms and Parkinson Disease With or Without Dementia: A Meta-Analysis Including 6453 Participants

A large number of case-control studies have investigated the association of apolipoprotein E ( APOE) polymorphisms with Parkinson disease (PD) and Parkinson disease dementia (PDD), with inconsistent results. This meta-analysis aimed to evaluate the relationship between APOE polymorphisms and PD/PDD risk. We searched for published studies in PubMed, Web of Science, WanFang Data (in Chinese), and CNKI (in Chinese) from inception to June 2017. Case-control studies reporting part or complete APOE genotype and allele frequency data were included. Pooled odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated using RevMan 5.3 software. A total of 39 studies involving 6453 cases with PD, with 461 cases with PDD, and 6855 controls were included in this meta-analysis. The results showed that the APOE ε3 allele was a protective factor for PD (OR = 0.90, 95% CI: 0.81-0.99; P = .04), whereas no significant differences in PD risk among all cases compared to controls were found for APOE ε2 and ε4. In Asian subgroups, the APOE ε4 allele was shown to be a risk factor for PD (OR = 1.22, 95% CI: 1.01-1.46; P = .04). Additionally, APOE polymorphisms were significantly associated with PDD risk in the entire case group (ε3: OR = 0.72, 95% CI: 0.58-0.89, P = .003; ε4: OR = 1.46, 95% CI: 1.12-1.88, P = .004) and in Asian subgroups.

Finding useful biomarkers for Parkinson's disease

The recent advent of an "ecosystem" of shared biofluid sample biorepositories and data sets will focus biomarker efforts in Parkinson's disease, boosting the therapeutic development pipeline and enabling translation with real-world impact.

Office-Based Screening for Dementia in Parkinson Disease: The Montreal Parkinson Risk of Dementia Scale in 4 Longitudinal Cohorts

Importance

Parkinson disease dementia dramatically increases mortality rates, patient expenditures, hospitalization risk, and caregiver burden. Currently, predicting Parkinson disease dementia risk is difficult, particularly in an office-based setting, without extensive biomarker testing.

Objective

To appraise the predictive validity of the Montreal Parkinson Risk of Dementia Scale, an office-based screening tool consisting of 8 items that are simply assessed.

Design, Setting, and Participants

This multicenter study (Montreal, Canada; Tottori, Japan; and Parkinson Progression Markers Initiative sites) used 4 diverse Parkinson disease cohorts with a prospective 4.4-year follow-up. A total of 717 patients with Parkinson disease were recruited between May 2005 and June 2016. Of these, 607 were dementia-free at baseline and followed-up for 1 year or more and so were included. The association of individual baseline scale variables with eventual dementia risk was calculated. Participants were then randomly split into cohorts to investigate weighting and determine the scale's optimal cutoff point. Receiver operating characteristic curves were calculated and correlations with selected biomarkers were investigated.

Main Outcomes and Measures

Dementia, as defined by Movement Disorder Society level I criteria.

Results

Of the 607 patients (mean [SD] age, 63.4 [10.1]; 376 men [62%]), 70 (11.5%) converted to dementia. All 8 items of the Montreal Parkinson Risk of Dementia Scale independently predicted dementia development at the 5% significance level. The annual conversion rate to dementia in the high-risk group (score, >5) was 14.9% compared with 5.8% in the intermediate group (score, 4-5) and 0.6% in the low-risk group (score, 0-3). The weighting procedure conferred no significant advantage. Overall predictive validity by the area under the receiver operating characteristic curve was 0.877 (95% CI, 0.829-0.924) across all cohorts. A cutoff of 4 or greater yielded a sensitivity of 77.1% (95% CI, 65.6-86.3) and a specificity of 87.2% (95% CI, 84.1-89.9), with a positive predictive value (as of 4.4 years) of 43.90% (95% CI, 37.76-50.24) and a negative predictive value of 96.70% (95% CI, 95.01-97.85). Positive and negative likelihood ratios were 5.94 (95% CI, 4.08-8.65) and 0.26 (95% CI, 0.17-0.40), respectively. Scale results correlated with markers of Alzheimer pathology and neuropsychological test results.

Conclusions and Relevance

Despite its simplicity, the Montreal Parkinson Risk of Dementia Scale demonstrated predictive validity equal or greater to previously described algorithms using biomarker assessments. Future studies using head-to-head comparisons or refinement of weighting would be of interest.

Cerebrospinal Fluid Biomarkers for Alzheimer's Disease: A View of the Regulatory Science Qualification Landscape from the Coalition Against Major Diseases CSF Biomarker Team

Alzheimer's disease (AD) drug development is burdened with the current requirement to conduct large, lengthy, and costly trials to overcome uncertainty in patient progression and effect size on treatment outcome measures. There is an urgent need for the discovery, development, and implementation of novel, objectively measured biomarkers for AD that would aid selection of the appropriate subpopulation of patients in clinical trials, and presumably, improve the likelihood of successfully evaluating innovative treatment options. Amyloid deposition and tau in the brain, which are most commonly assessed either in cerebrospinal fluid (CSF) or by molecular imaging, are consistently and widely accepted. Nonetheless, a clear gap still exists in the accurate identification of subjects that truly have the hallmarks of AD. The Coalition Against Major Diseases (CAMD), one of 12 consortia of the Critical Path Institute (C-Path), aims to streamline drug development for AD and related dementias by advancing regulatory approved drug development tools for clinical trials through precompetitive data sharing and adoption of consensus clinical data standards. This report focuses on the regulatory process for biomarker qualification, briefly comments on how it contrasts with approval or clearance of companion diagnostics, details the qualifications currently available to the field of AD, and highlights the current challenges facing the landscape of CSF biomarkers qualified as hallmarks of AD. Finally, it recommends actions to accelerate regulatory qualification of CSF biomarkers that would, in turn, improve the efficiency of AD therapeutic development.

Regulatory-accepted drug development tools are needed to accelerate innovative CNS disease treatments

Central Nervous System (CNS) diseases represent one of the most challenging therapeutic areas for successful drug approvals. Developing quantitative biomarkers as Drug Development Tools (DDTs) can catalyze the path to innovative treatments, and improve the chances of drug approvals. Drug development and healthcare management requires sensitive, reliable, validated, and regulatory accepted biomarkers and endpoints. This review highlights the regulatory paths and considerations for developing DDTs required to advance biomarker and endpoint use in clinical development (e.g., consensus CDISC [Clinical Data Interchange Standards Consortium] data standards, precompetitive sharing of anonymized patient-level data, and continual alignment with regulators). Summarized is the current landscape of biomarkers in a range of CNS diseases including Alzheimer disease, Parkinson Disease, Amyotrophic Lateral Sclerosis, Autism Spectrum Disorders, Depression, Huntington's disease, Multiple Sclerosis and Traumatic Brain Injury. Advancing DDTs for these devastating diseases that are both validated and qualified will require an integrated, cross-consortium approach to accelerate the delivery of innovative CNS therapeutics.

The C677T variant in MTHFR modulates associations between blood-based and cerebrospinal fluid biomarkers of neurodegeneration

The C677T functional variant in the methylene-tetrahydrofolate reductase (MTHFR) gene results in reduced enzymatic activity and elevated blood levels of homocysteine. Plasma levels of apolipoprotein E (ApoE) are negatively correlated with cerebral amyloid burden, but plasma homocysteine concentrations are associated with increased amyloid-β (Aβ) deposition in the brain. Here, we sought to determine whether associations between low plasma ApoE levels and elevated in-vivo amyloid burden were modulated by carrying the C677T variant. We tested this hypothesis in a large sample of elderly participants from the Alzheimer's Disease Neuroimaging Initiative. We used general linear models to examine associations between plasma homocysteine concentrations, circulating ApoE levels, cerebrospinal fluid concentrations of Aβ, and their modulation by MTHFR and ApoE genotype. Age, sex, and dementia status were included as covariates in all analyses. Higher circulating levels of ApoE predicted increased cerebrospinal fluid concentrations of Aβ, indicating lower in-vivo burden, in C-allele carriers, but not in homozygotes at the C677T variant, who showed significant elevations in plasma homocysteine levels. This modulation by the MTHFR genotype did not remain significant after controlling for ApoE genotype. In T-homozygotes who do not carry the ApoE-ε4 allele, the relationship between low plasma ApoE levels and an increased risk of dementia is likely obscured by the presence of elevated plasma homocysteine. This report suggests the value of genotyping patients at the C677T functional variant when using plasma ApoE levels as a preclinical biomarker for Alzheimer's disease.

Dementia with Lewy bodies and Parkinson's disease-dementia: current concepts and controversies

Dementia with Lewy bodies (DLB) and Parkinson's disease-dementia (PDD), although sharing many clinical, neurochemical and morphological features, according to DSM-5, are two entities of major neurocognitive disorders with Lewy bodies of unknown etiology. Despite considerable clinical overlap, their diagnosis is based on an arbitrary distinction between the time of onset of motor and cognitive symptoms: dementia often preceding parkinsonism in DLB and onset of cognitive impairment after onset of motor symptoms in PDD. Both are characterized morphologically by widespread cortical and subcortical α-synuclein/Lewy body plus β-amyloid and tau pathologies. Based on recent publications, including the fourth consensus report of the DLB Consortium, a critical overview is given. The clinical features of DLB and PDD include cognitive impairment, parkinsonism, visual hallucinations, and fluctuating attention. Intravitam PET and post-mortem studies revealed more pronounced cortical atrophy, elevated cortical and limbic Lewy pathologies (with APOE ε4), apart from higher prevalence of Alzheimer pathology in DLB than PDD. These changes may account for earlier onset and greater severity of cognitive defects in DLB, while multitracer PET studies showed no differences in cholinergic and dopaminergic deficits. DLB and PDD sharing genetic, neurochemical, and morphologic factors are likely to represent two subtypes of an α-synuclein-associated disease spectrum (Lewy body diseases), beginning with incidental Lewy body disease-PD-nondemented-PDD-DLB (no parkinsonism)-DLB with Alzheimer's disease (DLB-AD) at the most severe end, although DLB does not begin with PD/PDD and does not always progress to DLB-AD, while others consider them as the same disease. Both DLB and PDD show heterogeneous pathology and neurochemistry, suggesting that they share important common underlying molecular pathogenesis with AD and other proteinopathies. Cognitive impairment is not only induced by α-synuclein-caused neurodegeneration but by multiple regional pathological scores. Recent animal models and human post-mortem studies have provided important insights into the pathophysiology of DLB/PDD showing some differences, e.g., different spreading patterns of α-synuclein pathology, but the basic pathogenic mechanisms leading to the heterogeneity between both disorders deserve further elucidation. In view of the controversies about the nosology and pathogenesis of both syndromes, there remains a pressing need to differentiate them more clearly and to understand the processes leading these synucleinopathies to cause one disorder or the other. Clinical management of both disorders includes cholinesterase inhibitors, other pharmacologic and nonpharmacologic strategies, but these have only a mild symptomatic effect. Currently, no disease-modifying therapies are available.

APOE, thought disorder, and SPARE-AD predict cognitive decline in established Parkinson's disease

BACKGROUND

People with PD are at high risk of developing cognitive impairment and dementia. Cross-sectional studies have identified candidate biomarkers associated with cognitive decline. However, longitudinal studies on this topic are rarer, and few have investigated the use of biomarker panels encompassing multiple modalities. The objective of this study was to find baseline predictors of cognitive decline in longitudinally followed, nondemented Parkinson's disease patients.

METHODS

We performed a prospective cohort study of 100 PD patients with a median disease duration of 6.4 years. All participants were nondemented at baseline. We examined 16 baseline biomarkers from clinical, genetic, biochemical, and MRI-based imaging modalities for their association with longitudinal cognitive decline for up to 8 years. We investigated biomarkers individually, as well as in a multivariate linear mixed-effects model encompassing multimodal biomarkers, with change in the Mattis Dementia Rating Scale-2 over time as the primary outcome. Annual consensus process-derived cognitive diagnosis was used for Cox proportional hazards modeling of risk for cognitive decline.

RESULTS

In multivariate analysis, the presence of the APOE E4 allele, thought disorder, and an Alzheimer's disease pattern of brain atrophy (spatial pattern of abnormality for recognition of early Alzheimer's disease index) best predicted cognitive decline, with APOE E4 genotype exerting the greatest effect. The presence of the APOE E4 allele was associated with a 3.5 times higher risk of worsening cognitive diagnosis over time (HR, 3.53; 95% CI, 1.52-8.24; P < 0.05). The APOE genotype effect was not specific to any Mattis Dementia Rating Scale-2 domain.

CONCLUSIONS

Our results confirm the importance of Alzheimer's disease biomarkers as risk factors for cognitive decline in established Parkinson's disease. © 2017 International Parkinson and Movement Disorder Society.

Biomarkers for cognitive dysfunction in Parkinson's disease

INTRODUCTION

Cognitive dysfunction is among the most prevalent and debilitating non-motor features of Parkinson's disease (PD). The neuropathological correlates of cognitive dysfunction in PD are being revealed by clinicopathological correlation studies. These findings are fostering the development of candidate biomarkers to facilitate diagnosis of cognitive impairment and dementia, and to predict cognitive decline and onset of dementia in PD.

METHODS

A literature review of candidate biomarkers for cognitive dysfunction in PD was performed based on a PubMed search for peer-reviewed articles published from 1997 to June 2017 using the search terms "biomarker", "parkinson", and "dementia".

RESULTS

Based on the neuropathological correlates of cognitive dysfunction in PD, significant efforts are underway to identify biomarkers that reflect the presence and degree of 1) proteinopathy (i.e., abnormal protein aggregation), 2) neurodegeneration, including neuronal loss and axonal degeneration (i.e., involvement of gray matter and white matter, respectively), 3) neurotransmitter deficiency (e.g., acetylcholine and dopamine), and 4) abnormalities of brain function and connectivity.

CONCLUSION

The complexity of multiple substrates of cognitive impairment and dementia in PD will likely preclude the simplicity of a single biomarker. Thus, increased efforts to develop and validate combined biomarkers and predictive algorithms are anticipated.

White Matter Tract Integrity in Alzheimer's Disease vs. Late Onset Bipolar Disorder and Its Correlation with Systemic Inflammation and Oxidative Stress Biomarkers

Background: Late Onset Bipolar Disorder (LOBD) is the development of Bipolar Disorder (BD) at an age above 50 years old. It is often difficult to differentiate from other aging dementias, such as Alzheimer's Disease (AD), because they share cognitive and behavioral impairment symptoms.

Objectives: We look for WM tract voxel clusters showing significant differences when comparing of AD vs. LOBD, and its correlations with systemic blood plasma biomarkers (inflammatory, neurotrophic factors, and oxidative stress).

Materials: A sample of healthy controls (HC) (n = 19), AD patients (n = 35), and LOBD patients (n = 24) was recruited at the Alava University Hospital. Blood plasma samples were obtained at recruitment time and analyzed to extract the inflammatory, oxidative stress, and neurotrophic factors. Several modalities of MRI were acquired for each subject,

Methods: Fractional anisotropy (FA) coefficients are obtained from diffusion weighted imaging (DWI). Tract based spatial statistics (TBSS) finds FA skeleton clusters of WM tract voxels showing significant differences for all possible contrasts between HC, AD, and LOBD. An ANOVA F-test over all contrasts is carried out. Results of F-test are used to mask TBSS detected clusters for the AD > LOBD and LOBD > AD contrast to select the image clusters used for correlation analysis. Finally, Pearson's correlation coefficients between FA values at cluster sites and systemic blood plasma biomarker values are computed.

Results: The TBSS contrasts with by ANOVA F-test has identified strongly significant clusters in the forceps minor, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, and cingulum gyrus. The correlation analysis of these tract clusters found strong negative correlation of AD with the nerve growth factor (NGF) and brain derived neurotrophic factor (BDNF) blood biomarkers. Negative correlation of AD and positive correlation of LOBD with inflammation biomarker IL6 was also found.

Conclusion: TBSS voxel clusters tract atlas localizations are consistent with greater behavioral impairment and mood disorders in LOBD than in AD. Correlation analysis confirms that neurotrophic factors (i.e., NGF, BDNF) play a great role in AD while are absent in LOBD pathophysiology. Also, correlation results of IL1 and IL6 suggest stronger inflammatory effects in LOBD than in AD.

Parkinson's disease biomarkers: perspective from the NINDS Parkinson's Disease Biomarkers Program

Biomarkers for Parkinson's disease (PD) diagnosis, prognostication and clinical trial cohort selection are an urgent need. While many promising markers have been discovered through the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) and other mechanisms, no single PD marker or set of markers are ready for clinical use. Here we discuss the current state of biomarker discovery for platforms relevant to PDBP. We discuss the role of the PDBP in PD biomarker identification and present guidelines to facilitate their development. These guidelines include: harmonizing procedures for biofluid acquisition and clinical assessments, replication of the most promising biomarkers, support and encouragement of publications that report negative findings, longitudinal follow-up of current cohorts including the PDBP, testing of wearable technologies to capture readouts between study visits and development of recently diagnosed (de novo) cohorts to foster identification of the earliest markers of disease onset.

Update on ultrasensitive technologies to facilitate research on blood biomarkers for central nervous system disorders

Most research on fluid biomarkers for central nervous system (CNS) disorders has so far been performed using cerebrospinal fluid (CSF) as the biomarker source. CSF has the advantage of being closer to the brain than serum or plasma with a relative enrichment of CNS-specific proteins that are present at very low concentrations in the blood and thus difficult to reliably quantify using standard immunochemical technologies. Recent technical breakthroughs in the field of ultrasensitive assays have started to change this. Here, we review the most established ultrasensitive quantitative technologies that are currently available to general biomarker laboratories and discuss their use in research on biomarkers for CNS disorders.