Genome-wide analyses reveal a potential role for the MAPT, MOBP, and APOE loci in sporadic frontotemporal dementia.

Frontotemporal dementia (FTD) is the second most common cause of early-onset dementia after Alzheimer disease (AD). Efforts in the field mainly focus on familial forms of disease (fFTDs), while studies of the genetic etiology of sporadic FTD (sFTD) have been less common. In the current work, we analyzed 4,685 sFTD cases and 15,308 controls looking for common genetic determinants for sFTD. We found a cluster of variants at the MAPT (rs199443; p = 2.5 × 10-12, OR = 1.27) and APOE (rs6857; p = 1.31 × 10-12, OR = 1.27) loci and a candidate locus on chromosome 3 (rs1009966; p = 2.41 × 10-8, OR = 1.16) in the intergenic region between RPSA and MOBP, contributing to increased risk for sFTD through effects on expression and/or splicing in brain cortex of functionally relevant in-cis genes at the MAPT and RPSA-MOBP loci. The association with the MAPT (H1c clade) and RPSA-MOBP loci may suggest common genetic pleiotropy across FTD and progressive supranuclear palsy (PSP) (MAPT and RPSA-MOBP loci) and across FTD, AD, Parkinson disease (PD), and cortico-basal degeneration (CBD) (MAPT locus). Our data also suggest population specificity of the risk signals, with MAPT and APOE loci associations mainly driven by Central/Nordic and Mediterranean Europeans, respectively. This study lays the foundations for future work aimed at further characterizing population-specific features of potential FTD-discriminant APOE haplotype(s) and the functional involvement and contribution of the MAPT H1c haplotype and RPSA-MOBP loci to pathogenesis of sporadic forms of FTD in brain cortex.

Metabolic network alterations as a supportive biomarker in dementia with Lewy bodies with preserved dopamine transmission.

PURPOSE: Metabolic network analysis of FDG-PET utilizes an index of inter-regional correlation of resting state glucose metabolism and has been proven to provide complementary information regarding the disease process in parkinsonian syndromes. The goals of this study were (i) to evaluate pattern similarities of glucose metabolism and network connectivity in dementia with Lewy bodies (DLB) subjects with subthreshold dopaminergic loss compared to advanced disease stages and to (ii) investigate metabolic network alterations of FDG-PET for discrimination of patients with early DLB from other neurodegenerative disorders (Alzheimer's disease, Parkinson's disease, multiple system atrophy) at individual patient level via principal component analysis (PCA). METHODS: FDG-PETs of subjects with probable or possible DLB (n = 22) without significant dopamine deficiency (z-score < 2 in putamen binding loss on DaT-SPECT compared to healthy controls (HC)) were scaled by global-mean, prior to volume-of-interest-based analyses of relative glucose metabolism. Single region metabolic changes and network connectivity changes were compared against HC (n = 23) and against DLB subjects with significant dopamine deficiency (n = 86). PCA was applied to test discrimination of patients with DLB from disease controls (n = 101) at individual patient level. RESULTS: Similar patterns of hypo- (parietal- and occipital cortex) and hypermetabolism (basal ganglia, limbic system, motor cortices) were observed in DLB patients with and without significant dopamine deficiency when compared to HC. Metabolic connectivity alterations correlated between DLB patients with and without significant dopamine deficiency (R2 = 0.597, p < 0.01). A PCA trained by DLB patients with dopamine deficiency and HC discriminated DLB patients without significant dopaminergic loss from other neurodegenerative parkinsonian disorders at individual patient level (area-under-the-curve (AUC): 0.912). CONCLUSION: Disease-specific patterns of altered glucose metabolism and altered metabolic networks are present in DLB subjects without significant dopaminergic loss. Metabolic network alterations in FDG-PET can act as a supporting biomarker in the subgroup of DLB patients without significant dopaminergic loss at symptoms onset.

Change in cardiovascular health and rate of cognitive decline in older adults: a 15-year population-based study.

BACKGROUND: Previous research on associations between cardiovascular health, measured at a single timepoint, and rate of age-related cognitive decline shows divergent findings dependent on the participants' age and the health metric studied. The aim of this study was to add to the knowledge in this field by investigating whether change in cardiovascular health, assessed with Life's Simple 7 (LS7) score, is associated with rate of cognitive change in young-old and old-old adults. METHODS: The study included 1022 participants aged ≥ 60 years from the Swedish National Study on Aging and Care-Kungsholmen (SNAC-K), who underwent repeated neuropsychological testing (episodic memory, semantic memory, verbal fluency, and perceptual speed) across up to 15 years. LS7, composed of seven cardiovascular health metrics (smoking, diet, physical activity, body mass index, plasma glucose, total serum cholesterol, and blood pressure), was assessed at baseline and at the 6-year follow-up. Change in LS7 was calculated as the difference between baseline and 6 years (range - 5 to 8 points) and categorised into worse (-5 to -2 points), stable (-1 to 1 points), and improved (2 to 8 points). Change in cognitive performance as a function of LS7 change categories was estimated using linear mixed-effects models. RESULTS: Participants were classified as stable (67.1%), improved (21.0%), or worse (11.8%) according to changes in LS7 score. Both the worse and improved categories were associated with faster cognitive decline. Age-stratified analyses revealed that worsening of LS7 was clearly associated with faster cognitive decline in the old-old (≥ 78 years), whereas improvement tended be associated with faster cognitive decline in the young-old (< 78 years) group. CONCLUSIONS: Change in cardiovascular health in old age may lead to accelerated cognitive decline, particularly in late senescence. These results suggest that it is important to monitor and maintain cardiovascular health status in very old adults.

Sex differences in brain atrophy in dementia with Lewy bodies.

INTRODUCTION: Sex influences neurodegeneration, but it has been poorly investigated in dementia with Lewy bodies (DLB). We investigated sex differences in brain atrophy in DLB using magnetic resonance imaging (MRI). METHODS: We included 436 patients from the European-DLB consortium and the Mayo Clinic. Sex differences and sex-by-age interactions were assessed through visual atrophy rating scales (n = 327; 73 ± 8 years, 62% males) and automated estimations of regional gray matter volume and cortical thickness (n = 165; 69 ± 9 years, 72% males). RESULTS: We found a higher likelihood of frontal atrophy and smaller volumes in six cortical regions in males and thinner olfactory cortices in females. There were significant sex-by-age interactions in volume (six regions) and cortical thickness (seven regions) across the entire cortex. DISCUSSION: We demonstrate that males have more widespread cortical atrophy at younger ages, but differences tend to disappear with increasing age, with males and females converging around the age of 75. HIGHLIGHTS: Male DLB patients had higher odds for frontal atrophy on radiological visual rating scales. Male DLB patients displayed a widespread pattern of cortical gray matter alterations on automated methods. Sex differences in gray matter measures in DLB tended to disappear with increasing age.

A 3D deep learning model to predict the diagnosis of dementia with Lewy bodies, Alzheimer's disease, and mild cognitive impairment using brain 18F-FDG PET.

PURPOSE: The purpose of this study is to develop and validate a 3D deep learning model that predicts the final clinical diagnosis of Alzheimer's disease (AD), dementia with Lewy bodies (DLB), mild cognitive impairment due to Alzheimer's disease (MCI-AD), and cognitively normal (CN) using fluorine 18 fluorodeoxyglucose PET (18F-FDG PET) and compare model's performance to that of multiple expert nuclear medicine physicians' readers. MATERIALS AND METHODS: Retrospective 18F-FDG PET scans for AD, MCI-AD, and CN were collected from Alzheimer's disease neuroimaging initiative (556 patients from 2005 to 2020), and CN and DLB cases were from European DLB Consortium (201 patients from 2005 to 2018). The introduced 3D convolutional neural network was trained using 90% of the data and externally tested using 10% as well as comparison to human readers on the same independent test set. The model's performance was analyzed with sensitivity, specificity, precision, F1 score, receiver operating characteristic (ROC). The regional metabolic changes driving classification were visualized using uniform manifold approximation and projection (UMAP) and network attention. RESULTS: The proposed model achieved area under the ROC curve of 96.2% (95% confidence interval: 90.6-100) on predicting the final diagnosis of DLB in the independent test set, 96.4% (92.7-100) in AD, 71.4% (51.6-91.2) in MCI-AD, and 94.7% (90-99.5) in CN, which in ROC space outperformed human readers performance. The network attention depicted the posterior cingulate cortex is important for each neurodegenerative disease, and the UMAP visualization of the extracted features by the proposed model demonstrates the reality of development of the given disorders. CONCLUSION: Using only 18F-FDG PET of the brain, a 3D deep learning model could predict the final diagnosis of the most common neurodegenerative disorders which achieved a competitive performance compared to the human readers as well as their consensus.

Continuous Dopaminergic Stimulation Improves Cortical Maladaptive Changes in Advanced Parkinson's Disease.

BACKGROUND: With the progression of Parkinson's disease (PD), pulsatile treatment with oral levodopa causes maladaptive changes within basal ganglia-thalamo-cortical circuits, which are clinically expressed as motor fluctuations and dyskinesias. At the level of the motor cortex, these changes may be detected using transcranial magnetic stimulation (TMS), as abnormal corticospinal and intracortical excitability and absent response to plasticity protocols. OBJECTIVE: We investigated the effect of continuous dopaminergic stimulation on cortical maladaptive changes related to oral levodopa treatment. METHODS: Twenty patients with advanced PD were tested using TMS within 1 week before and again 6 months after the introduction of levodopa-carbidopa intestinal gel. We measured resting and active motor thresholds, input/output curve, short interval intracortical inhibition curve, cortical silent period, and response to intermittent theta burst stimulation. Patients were clinically assessed with Part III and Part IV of the Movement Disorders Society Unified Parkinson's Disease Rating Scale. RESULTS: Six months after the introduction of levodopa-carbidopa intestinal gel, motor fluctuations scores (P = 0.001) and dyskinesias scores (P < 0.001) were reduced. Resting and active motor threshold (P = 0.012 and P = 0.015) and x-intercept of input/output curve (P = 0.005) were also decreased, while short-interval intracortical inhibition and response to intermittent theta bust stimulation were improved (P = 0.026 and P = 0.031, respectively). Changes in these parameters correlated with clinical improvement. CONCLUSIONS: In patients with advanced PD, switching from intermittent to continuous levodopa delivery increased corticospinal excitability and improved deficient intracortical inhibition and abnormal motor cortex plasticity, along with amelioration of motor fluctuations and dyskinesias. Continuous dopaminergic stimulation ameliorates maladaptive changes inflicted by chronic pulsatile dopaminergic stimulation. © 2022 International Parkinson and Movement Disorder Society.

Adverse effects of levodopa/carbidopa intrajejunal gel treatment: A single-center long-term follow-up study.

OBJECTIVES: Levodopa/carbidopa intrajejunal gel (LCIG) is an effective therapeutic strategy to overcome levodopa-induced motor complications in advanced Parkinson's disease (PD). However, it requires invasive percutaneous endoscopic gastrojejunostomy (PEG-J) and may be associated with serious adverse effects (AE). In this study, we aimed to evaluate long-term AEs related to LCIG treatment in a large homogenous cohort of advanced PD patients. METHODS: One hundred three consecutive PD patients were regularly monitored for LCIG-related, PEG-J-related, and device-related AEs up to 14 years. Incidence of AEs was studied in time applying a time-to-event analysis and Cox proportional hazard model with age, disease duration, gender, and recurrent AE as covariates. Health-related quality of life (HRQoL) was estimated at each visit and compared to HRQoL before the LCIG treatment. RESULTS: Among 296 AEs noted, 48.8% were LCIG-related, 32.4% PEG-J-related, and 19.6% device-related. While most of the studied AEs steadily accumulated throughout the follow-up period, 24.3% of the patients (95% CI 10.1%-36.3%) experienced PEG-J-related AE already within the first days after the PEG-J insertion. Cox model revealed that older patients had higher probability of psychosis, PEG-J- and device-related AEs (p < .05, p < .05, and p = .02) and suggested increased recurrence risk in those with early PEG-J and device-related AEs. Despite relatively high incidence of AEs, HRQoL significantly increased in the follow-up period (p < .0001). CONCLUSION: AEs related to LCIG treatment are common. Therefore, careful patient selection and monitoring throughout the treatment is recommended, especially in those with early side effects. Nevertheless, LCIG significantly improves HRQoL in advanced PD patients on a long term.

Adopting transfer learning for neuroimaging: a comparative analysis with a custom 3D convolution neural network model.

BACKGROUND: In recent years, neuroimaging with deep learning (DL) algorithms have made remarkable advances in the diagnosis of neurodegenerative disorders. However, applying DL in different medical domains is usually challenged by lack of labeled data. To address this challenge, transfer learning (TL) has been applied to use state-of-the-art convolution neural networks pre-trained on natural images. Yet, there are differences in characteristics between medical and natural images, also image classification and targeted medical diagnosis tasks. The purpose of this study is to investigate the performance of specialized and TL in the classification of neurodegenerative disorders using 3D volumes of 18F-FDG-PET brain scans. RESULTS: Results show that TL models are suboptimal for classification of neurodegenerative disorders, especially when the objective is to separate more than two disorders. Additionally, specialized CNN model provides better interpretations of predicted diagnosis. CONCLUSIONS: TL can indeed lead to superior performance on binary classification in timely and data efficient manner, yet for detecting more than a single disorder, TL models do not perform well. Additionally, custom 3D model performs comparably to TL models for binary classification, and interestingly perform better for diagnosis of multiple disorders. The results confirm the superiority of the custom 3D-CNN in providing better explainable model compared to TL adopted ones.

Complementary pre-screening strategies to uncover hidden prodromal and mild Alzheimer's disease: Results from the MOPEAD project.

INTRODUCTION: The Models of Patient Engagement for Alzheimer's Disease (MOPEAD) project was conceived to explore innovative complementary strategies to uncover hidden prodromal and mild Alzheimer's disease (AD) dementia cases and to raise awareness both in the general public and among health professionals about the importance of early diagnosis. METHODS: Four different strategies or RUNs were used: (a) a web-based (WB) prescreening tool, (2) an open house initiative (OHI), (3) a primary care-based protocol for early detection of cognitive decline (PC), and (4) a tertiary care-based pre-screening at diabetologist clinics (DC). RESULTS: A total of 1129 patients at high risk of having prodromal AD or dementia were identified of 2847 pre-screened individuals (39.7%). The corresponding proportion for the different initiatives were 36.8% (WB), 35.6% (OHI), 44.4% (PC), and 58.3% (DC). CONCLUSION: These four complementary pre-screening strategies were useful for identifying individuals at high risk of having prodromal or mild AD.

European Academy of Neurology/European Alzheimer's Disease Consortium position statement on diagnostic disclosure, biomarker counseling, and management of patients with mild cognitive impairment.

BACKGROUND AND PURPOSE: Careful counseling through the diagnostic process and adequate postdiagnostic support in patients with mild cognitive impairment (MCI) is important. Previous studies have indicated heterogeneity in practice and the need for guidance for clinicians. METHODS: A joint European Academy of Neurology/European Alzheimer's Disease Consortium panel of dementia specialists was appointed. Through online meetings and emails, positions were developed regarding disclosing a syndrome diagnosis of MCI, pre- and postbiomarker sampling counseling, and postdiagnostic support. RESULTS: Prior to diagnostic evaluation, motives and wishes of the patient should be sought. Diagnostic disclosure should be carried out by a dementia specialist taking the ethical principles of "the right to know" versus "the wish not to know" into account. Disclosure should be accompanied by written information and a follow-up plan. It should be made clear that MCI is not dementia. Prebiomarker counseling should always be carried out if biomarker sampling is considered and postbiomarker counseling if sampling is carried out. A dementia specialist knowledgeable about biomarkers should inform about pros and cons, including alternatives, to enable an autonomous and informed decision. Postbiomarker counseling will depend in part on the results of biomarkers. Follow-up should be considered for all patients with MCI and include brain-healthy advice and possibly treatment for specific underlying causes. Advice on advance directives may be relevant. CONCLUSIONS: Guidance to clinicians on various aspects of the diagnostic process in patients with MCI is presented here as position statements. Further studies are needed to enable more evidence-based and standardized recommendations in the future.

Biomarker counseling, disclosure of diagnosis and follow-up in patients with mild cognitive impairment: A European Alzheimer's disease consortium survey.

OBJECTIVES: Mild cognitive impairment (MCI) is associated with an increased risk of further cognitive decline, partly depending on demographics and biomarker status. The aim of the present study was to survey the clinical practices of physicians in terms of biomarker counseling, management, and follow-up in European expert centers diagnosing patients with MCI. METHODS: An online email survey was distributed to physicians affiliated with European Alzheimer's disease Consortium centers (Northern Europe: 10 centers; Eastern and Central Europe: 9 centers; and Southern Europe: 15 centers) with questions on attitudes toward biomarkers and biomarker counseling in MCI and dementia. This included postbiomarker counseling and the process of diagnostic disclosure of MCI, as well as treatment and follow-up in MCI. RESULTS: The response rate for the survey was 80.9% (34 of 42 centers) across 20 countries. A large majority of physicians had access to biomarkers and found them useful. Pre- and postbiomarker counseling varied across centers, as did practices for referral to support groups and advice on preventive strategies. Less than half reported discussing driving and advance care planning with patients with MCI. CONCLUSIONS: The variability in clinical practices across centers calls for better biomarker counseling and better training to improve communication skills. Future initiatives should address the importance of communicating preventive strategies and advance planning.

Associations among education, age, and the dementia with Lewy bodies (DLB) metabolic pattern: A European-DLB consortium project.

INTRODUCTION: We assessed the influence of education as a proxy of cognitive reserve and age on the dementia with Lewy bodies (DLB) metabolic pattern. METHODS: Brain 18F-fluorodeoxyglucose positron emission tomography and clinical/demographic information were available in 169 probable DLB patients included in the European DLB-consortium database. Principal component analysis identified brain regions relevant to local data variance. A linear regression model was applied to generate age- and education-sensitive maps corrected for Mini-Mental State Examination score, sex (and either education or age). RESULTS: Age negatively covaried with metabolism in bilateral middle and superior frontal cortex, anterior and posterior cingulate, reducing the expression of the DLB-typical cingulate island sign (CIS). Education negatively covaried with metabolism in the left inferior parietal cortex and precuneus (making the CIS more prominent). DISCUSSION: These findings point out the importance of tailoring interpretation of DLB biomarkers considering the concomitant effect of individual, non-disease-related variables such as age and cognitive reserve.

Metabolic patterns across core features in dementia with lewy bodies.

OBJECTIVE: To identify brain regions whose metabolic impairment contributes to dementia with Lewy bodies (DLB) clinical core features expression and to assess the influence of severity of global cognitive impairment on the DLB hypometabolic pattern. METHODS: Brain fluorodeoxyglucose positron emission tomography and information on core features were available in 171 patients belonging to the imaging repository of the European DLB Consortium. Principal component analysis was applied to identify brain regions relevant to the local data variance. A linear regression model was applied to generate core-feature-specific patterns controlling for the main confounding variables (Mini-Mental State Examination [MMSE], age, education, gender, and center). Regression analysis to the locally normalized intensities was performed to generate an MMSE-sensitive map. RESULTS: Parkinsonism negatively covaried with bilateral parietal, precuneus, and anterior cingulate metabolism; visual hallucinations (VH) with bilateral dorsolateral-frontal cortex, posterior cingulate, and parietal metabolism; and rapid eye movement sleep behavior disorder (RBD) with bilateral parieto-occipital cortex, precuneus, and ventrolateral-frontal metabolism. VH and RBD shared a positive covariance with metabolism in the medial temporal lobe, cerebellum, brainstem, basal ganglia, thalami, and orbitofrontal and sensorimotor cortex. Cognitive fluctuations negatively covaried with occipital metabolism and positively with parietal lobe metabolism. MMSE positively covaried with metabolism in the left superior frontal gyrus, bilateral-parietal cortex, and left precuneus, and negatively with metabolism in the insula, medial frontal gyrus, hippocampus in the left hemisphere, and right cerebellum. INTERPRETATION: Regions of more preserved metabolism are relatively consistent across the variegate DLB spectrum. By contrast, core features were associated with more prominent hypometabolism in specific regions, thus suggesting a close clinical-imaging correlation, reflecting the interplay between topography of neurodegeneration and clinical presentation in DLB patients. Ann Neurol 2019;85:715-725.

Metabolic Correlates of Dopaminergic Loss in Dementia with Lewy Bodies.

BACKGROUND: Striatal dopamine deficiency and metabolic changes are well-known phenomena in dementia with Lewy bodies and can be quantified in vivo by 123 I-Ioflupane brain single-photon emission computed tomography of dopamine transporter and 18 F-fluorodesoxyglucose PET. However, the linkage between both biomarkers is ill-understood. OBJECTIVE: We used the hitherto largest study cohort of combined imaging from the European consortium to elucidate the role of both biomarkers in the pathophysiological course of dementia with Lewy bodies. METHODS: We compared striatal dopamine deficiency and glucose metabolism of 84 dementia with Lewy body patients and comparable healthy controls. After normalization of data, we tested their correlation by region-of-interest-based and voxel-based methods, controlled for study center, age, sex, education, and current cognitive impairment. Metabolic connectivity was analyzed by inter-region coefficients stratified by dopamine deficiency and compared to healthy controls. RESULTS: There was an inverse relationship between striatal dopamine availability and relative glucose hypermetabolism, pronounced in the basal ganglia and in limbic regions. With increasing dopamine deficiency, metabolic connectivity showed strong deteriorations in distinct brain regions implicated in disease symptoms, with greatest disruptions in the basal ganglia and limbic system, coincident with the pattern of relative hypermetabolism. CONCLUSIONS: Relative glucose hypermetabolism and disturbed metabolic connectivity of limbic and basal ganglia circuits are metabolic correlates of dopamine deficiency in dementia with Lewy bodies. Identification of specific metabolic network alterations in patients with early dopamine deficiency may serve as an additional supporting biomarker for timely diagnosis of dementia with Lewy bodies. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Predicting progression to dementia in persons with mild cognitive impairment using cerebrospinal fluid markers.

INTRODUCTION: We aimed to determine the added value of cerebrospinal fluid (CSF) to clinical and imaging tests to predict progression from mild cognitive impairment (MCI) to any type of dementia. METHODS: The risk of progression to dementia was estimated using two logistic regression models based on 250 MCI participants: the first included standard clinical measures (demographic, clinical, and imaging test information) without CSF biomarkers, and the second included standard clinical measures with CSF biomarkers. RESULTS: Adding CSF improved predictive accuracy with 0.11 (scale from 0-1). Of all participants, 136 (54%) had a change in risk score of 0.10 or higher (which was considered clinically relevant), of whom in 101, it was in agreement with their dementia status at follow-up. DISCUSSION: An individual person's risk of progression from MCI to dementia can be improved by relying on CSF biomarkers in addition to recommended clinical and imaging tests for usual care.

Recommendations for CSF AD biomarkers in the diagnostic evaluation of dementia.

This article presents recommendations, based on the Grading of Recommendations, Assessment, Development, and Evaluation method, for the clinical application of cerebrospinal fluid (CSF) amyloid-ß1-42, tau, and phosphorylated tau in the diagnostic evaluation of patients with dementia. The recommendations were developed by a multidisciplinary working group based on the available evidence and consensus from focused discussions for (i) identification of Alzheimer's disease (AD) as the cause of dementia, (ii) prediction of rate of decline, (iii) cost-effectiveness, and (iv) interpretation of results. The working group found sufficient evidence to support a recommendation to use CSF AD biomarkers as a supplement to clinical evaluation, particularly in uncertain and atypical cases, to identify or exclude AD as the cause of dementia. Because of insufficient evidence, it was uncertain whether CSF AD biomarkers outperform imaging biomarkers. Operational recommendations for the interpretation of ambiguous CSF biomarker results were also provided.

Recommendations for cerebrospinal fluid Alzheimer's disease biomarkers in the diagnostic evaluation of mild cognitive impairment.

This article presents recommendations, based on the Grading of Recommendations, Assessment, Development, and Evaluation method, for the clinical application of cerebrospinal fluid (CSF) amyloid-ß1-42, tau, and phosphorylated tau in the diagnostic evaluation of patients with mild cognitive impairment (MCI). The recommendations were developed by a multidisciplinary working group and based on the available evidence and consensus from focused group discussions for 1) prediction of clinical progression to Alzheimer's disease (AD) dementia, 2) cost-effectiveness, 3) interpretation of results, and 4) patient counseling. The working group recommended using CSF AD biomarkers in the diagnostic workup of MCI patients, after prebiomarker counseling, as an add-on to clinical evaluation to predict functional decline or conversion to AD dementia and to guide disease management. Because of insufficient evidence, it was uncertain whether CSF AD biomarkers outperform imaging biomarkers. Furthermore, the working group provided recommendations for interpretation of ambiguous CSF biomarker results and for pre- and post-biomarker counseling.

The impact of automated hippocampal volumetry on diagnostic confidence in patients with suspected Alzheimer's disease: A European Alzheimer's Disease Consortium study.

INTRODUCTION: Hippocampal volume is a core biomarker of Alzheimer's disease (AD). However, its contribution over the standard diagnostic workup is unclear. METHODS: Three hundred fifty-six patients, under clinical evaluation for cognitive impairment, with suspected AD and Mini-Mental State Examination ≥20, were recruited across 17 European memory clinics. After the traditional diagnostic workup, diagnostic confidence of AD pathology (DCAD) was estimated by the physicians in charge. The latter were provided with the results of automated hippocampal volumetry in standardized format and DCAD was reassessed. RESULTS: An increment of one interquartile range in hippocampal volume was associated with a mean change of DCAD of -8.0% (95% credible interval: [-11.5, -5.0]). Automated hippocampal volumetry showed a statistically significant impact on DCAD beyond the contributions of neuropsychology, 18F-fluorodeoxyglucose positron emission tomography/single-photon emission computed tomography, and cerebrospinal fluid markers (-8.5, CrI: [-11.5, -5.6]; -14.1, CrI: [-19.3, -8.8]; -10.6, CrI: [-14.6, -6.1], respectively). DISCUSSION: There is a measurable effect of hippocampal volume on DCAD even when used on top of the traditional diagnostic workup.

Biological confounders for the values of cerebrospinal fluid proteins in Parkinson's disease and related disorders.

Cerebrospinal fluid (CSF) has been extensively studied to explore biochemical alterations in subjects with neurodegenerative disorders. In Alzheimer's disease, levels of increased CSF tau protein and decreased levels of ß-amyloid 1-42 (Aß42) have been shown to correlate with brain plaque formation and tangle pathology. Intracellular Lewy inclusions containing aggregated α-synuclein (α-syn) represent a pathological hallmark of Parkinson's disease (PD). In most - but not all - studies published to date total CSF α-syn concentrations have been found to be decreased in disorders related to α-syn pathology, that is, PD, dementia with Lewy bodies and multiple system atrophy. However, these reports show extensive signal overlap among tested individuals, thereby diminishing its potential for routine use in clinical practice. To investigate potential biological (i.e., non-technical) confounders of reported CSF levels for α-syn, Aß42, and tau in PD and related disorders, we carried out a methodical review of known factors that underlie signal variability and speculate on those that have not yet been tested. We discuss several biological factors, such as neuropathology, demographics, clinical phenotype, progression and duration of disease, concomitant illnesses and, last but not least, pharmacotherapy, which in isolation or combination can substantially alter values for CSF proteins of interest. Enhanced implementation of standardized clinical protocols, streamlined operating procedures, and further progress in the development of validated assays for CSF proteins have the potential to (i) inform us as to the pathogenesis of disease, (ii) support the laboratory-based diagnosis for symptomatic subjects in the future, and (iii) facilitate breakthrough therapies to alter the course of neurodegenerative disorders, such as PD and Alzheimer's disease. Cerebrospinal fluid (CSF) has been extensively studied to explore biochemical alterations in subjects with neurodegenerative disorders. To investigate potential biological confounders of reported CSF levels for α-synuclein (α-Syn), amyloid-ß 1-42(Aß42) and tau protein in Parkinson's disease and related disorders, we reviewed the current literature for known factors that underlie signal variability and speculate on those that have not yet been tested. This article is part of a special issue on Parkinson disease.

Alzheimer's disease cerebrospinal fluid biomarkers predict cognitive decline in lewy body dementia.

INTRODUCTION: Alzheimer's disease pathologies are common in dementia with Lewy bodies, but their clinical relevance is not clear. CSF biomarkers amyloid beta 1-42, total tau, and tau phosphorylated at threonine 181 reflect Alzheimer's disease neuropathology antemortem. In PD, low CSF amyloid beta 1-42 predict long-term cognitive decline, but little is known about these biomarkers as predictors for cognitive decline in Lewy body dementia. The aim of this study was to assess whether Alzheimer's disease CSF biomarkers predict cognitive decline in Lewy body dementia. METHODS: From a large European dementia with Lewy bodies multicenter study, we analyzed baseline Alzheimer's disease CSF biomarkers and serial MMSE (baseline and 1- and 2-year follow-up) in 100 patients with Lewy body dementia. Linear mixed-effects analyses, adjusted for sex, age, baseline MMSE, and education, were performed to model the association between CSF biomarkers and rate of cognitive decline measured with MMSE. An Alzheimer's disease CSF profile was defined as pathological amyloid beta 1-42 plus pathological total tau or phosphorylated tau. RESULTS: The Alzheimer's disease CSF profile, and pathological levels of amyloid beta 1-42, were associated with a more rapid decline in MMSE (2.2 [P < 0.05] and 2.9 points difference [P < 0.01], respectively). Higher total tau values showed a trend toward association without statistical significance (2.0 points difference; P = 0.064), whereas phosphorylated tau was not associated with decline. CONCLUSIONS: Reduced levels of CSF amyloid beta 1-42 were associated with more rapid cognitive decline in Lewy body dementia patients. Future prospective studies should include larger samples, centralized CSF analyses, longer follow-up, and biomarker-pathology correlation. © 2016 International Parkinson and Movement Disorder Society.