Plasma and cerebrospinal fluid amyloid beta for the diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI)

Mild cognitive impairment detection from facial video interviews by applying spatial-to-temporal attention module

Early detection of Mild Cognitive Impairment (MCI) leads to early interventions to slow the progression from MCI into dementia. Deep Learning (DL) algorithms could help achieve early non-invasive and low-cost detection of MCI. This paper presents the detection of MCI in older adults using DL models based only on facial features extracted from video-recorded conversations at home. We used the data collected from the I-CONECT behavioral intervention study (NCT02871921), where several sessions of semi-structured interviews between socially isolated older individuals and interviewers were video recorded. We develop a framework that extracts holistic spatial facial features using a convolutional autoencoder and temporal information using transformers. We proposed the Spatial-to-Temporal Attention Module (STAM) to detect the I-CONECT study participants' cognitive conditions (MCI vs. those with normal cognition (NC)) using facial and interaction features. The interaction features of the facial features improved the prediction performance compared with applying facial features solely. The detection accuracy using this combined method reached 88%, whereas the accuracy without applying the segments and sequences information of the facial features within a video on a certain theme was 84%. Overall, the results show that spatiotemporal facial features modeled using DL algorithms have a discriminating power for the detection of MCI.

Biomarkers in Alzheimer's Disease: Are Olfactory Neuronal Precursors Useful for Antemortem Biomarker Research?

Alzheimer's disease (AD), as the main cause of dementia, affects millions of people around the world, whose diagnosis is based mainly on clinical criteria. Unfortunately, the diagnosis is obtained very late, when the neurodegenerative damage is significant for most patients. Therefore, the exhaustive study of biomarkers is indispensable for diagnostic, prognostic, and even follow-up support. AD is a multifactorial disease, and knowing its underlying pathological mechanisms is crucial to propose new and valuable biomarkers. In this review, we summarize some of the main biomarkers described in AD, which have been evaluated mainly by imaging studies in cerebrospinal fluid and blood samples. Furthermore, we describe and propose neuronal precursors derived from the olfactory neuroepithelium as a potential resource to evaluate some of the widely known biomarkers of AD and to gear toward searching for new biomarkers. These neuronal lineage cells, which can be obtained directly from patients through a non-invasive and outpatient procedure, display several characteristics that validate them as a surrogate model to study the central nervous system, allowing the analysis of AD pathophysiological processes. Moreover, the ease of obtaining and harvesting endows them as an accessible and powerful resource to evaluate biomarkers in clinical practice.

Multiomics Blood-Based Biomarkers Predict Alzheimer's Predementia with High Specificity in a Multicentric Cohort Study

BACKGROUND

The primary criteria for diagnosing mild cognitive impairment (MCI) due to Alzheimer's Disease (AD) or probable mild AD dementia rely partly on cognitive assessments and the presence of amyloid plaques. Although these criteria exhibit high sensitivity in predicting AD among cognitively impaired patients, their specificity remains limited. Notably, up to 25% of non-demented patients with amyloid plaques may be misdiagnosed with MCI due to AD, when in fact they suffer from a different brain disorder. The introduction of anti-amyloid antibodies complicates this scenario. Physicians must prioritize which amyloid-positive MCI patients receive these treatments, as not all are suitable candidates. Specifically, those with non-AD amyloid pathologies are not primary targets for amyloid-modifying therapies. Consequently, there is an escalating medical necessity for highly specific blood biomarkers that can accurately detect pre-dementia AD, thus optimizing amyloid antibody prescription.

OBJECTIVES

The objective of this study was to evaluate a predictive model based on peripheral biomarkers to identify MCI and mild dementia patients who will develop AD dementia symptoms in cognitively impaired population with high specificity.

DESIGN

Peripheral biomarkers were identified in a gene transfer-based animal model of AD and then validated during a retrospective multi-center clinical study.

SETTING

Participants from 7 retrospective cohorts (US, EU and Australia).

PARTICIPANTS

This study followed 345 cognitively impaired individuals over up to 13 years, including 193 with MCI and 152 with mild dementia, starting from their initial visits. The final diagnoses, established during their last assessments, classified 249 participants as AD patients and 96 as having non-AD brain disorders, based on the specific diagnostic criteria for each disorder subtype. Amyloid status, assessed at baseline, was available for 82.9% of the participants, with 61.9% testing positive for amyloid. Both amyloid-positive and negative individuals were represented in each clinical group. Some of the AD patients had co-morbidities such as metabolic disorders, chronic diseases, or cardiovascular pathologies.

MEASUREMENTS

We developed targeted mass spectrometry assays for 81 blood-based biomarkers, encompassing 45 proteins and 36 metabolites previously identified in AAV-AD rats.

METHODS

We analyzed blood samples from study participants for the 81 biomarkers. The B-HEALED test, a machine learning-based diagnostic tool, was developed to differentiate AD patients, including 123 with Prodromal AD and 126 with mild AD dementia, from 96 individuals with non-AD brain disorders. The model was trained using 70% of the data, selecting relevant biomarkers, calibrating the algorithm, and establishing cutoff values. The remaining 30% served as an external test dataset for blind validation of the predictive accuracy.

RESULTS

Integrating a combination of 19 blood biomarkers and participant age, the B-HEALED model successfully distinguished participants that will develop AD dementia symptoms (82 with Prodromal AD and 83 with AD dementia) from non-AD subjects (71 individuals) with a specificity of 93.0% and sensitivity of 65.4% (AUROC=81.9%, p<0.001) during internal validation. When the amyloid status (derived from CSF or PET scans) and the B-HEALED model were applied in association, with individuals being categorized as AD if they tested positive in both tests, we achieved 100% specificity and 52.8% sensitivity. This performance was consistent in blind external validation, underscoring the model's reliability on independent datasets.

CONCLUSIONS

The B-HEALED test, utilizing multiomics blood-based biomarkers, demonstrates high predictive specificity in identifying AD patients within the cognitively impaired population, minimizing false positives. When used alongside amyloid screening, it effectively identifies a nearly pure prodromal AD cohort. These results bear significant implications for refining clinical trial inclusion criteria, facilitating drug development and validation, and accurately identifying patients who will benefit the most from disease-modifying AD treatments.

Digital Marker for Early Screening of Mild Cognitive Impairment Through Hand and Eye Movement Analysis in Virtual Reality Using Machine Learning: First Validation Study

BACKGROUND

With the global rise in Alzheimer disease (AD), early screening for mild cognitive impairment (MCI), which is a preclinical stage of AD, is of paramount importance. Although biomarkers such as cerebrospinal fluid amyloid level and magnetic resonance imaging have been studied, they have limitations, such as high cost and invasiveness. Digital markers to assess cognitive impairment by analyzing behavioral data collected from digital devices in daily life can be a new alternative. In this context, we developed a "virtual kiosk test" for early screening of MCI by analyzing behavioral data collected when using a kiosk in a virtual environment.

OBJECTIVE

We aimed to investigate key behavioral features collected from a virtual kiosk test that could distinguish patients with MCI from healthy controls with high statistical significance. Also, we focused on developing a machine learning model capable of early screening of MCI based on these behavioral features.

METHODS

A total of 51 participants comprising 20 healthy controls and 31 patients with MCI were recruited by 2 neurologists from a university hospital. The participants performed a virtual kiosk test-developed by our group-where we recorded various behavioral data such as hand and eye movements. Based on these time series data, we computed the following 4 behavioral features: hand movement speed, proportion of fixation duration, time to completion, and the number of errors. To compare these behavioral features between healthy controls and patients with MCI, independent-samples 2-tailed t tests were used. Additionally, we used these behavioral features to train and validate a machine learning model for early screening of patients with MCI from healthy controls.

RESULTS

In the virtual kiosk test, all 4 behavioral features showed statistically significant differences between patients with MCI and healthy controls. Compared with healthy controls, patients with MCI had slower hand movement speed (t49=3.45; P=.004), lower proportion of fixation duration (t49=2.69; P=.04), longer time to completion (t49=-3.44; P=.004), and a greater number of errors (t49=-3.77; P=.001). All 4 features were then used to train a support vector machine to distinguish between healthy controls and patients with MCI. Our machine learning model achieved 93.3% accuracy, 100% sensitivity, 83.3% specificity, 90% precision, and 94.7% F1-score.

CONCLUSIONS

Our research preliminarily suggests that analyzing hand and eye movements in the virtual kiosk test holds potential as a digital marker for early screening of MCI. In contrast to conventional biomarkers, this digital marker in virtual reality is advantageous as it can collect ecologically valid data at an affordable cost and in a short period (5-15 minutes), making it a suitable means for early screening of MCI. We call for further studies to confirm the reliability and validity of this approach.

Neuroimaging in Alzheimer's Disease for Early Diagnosis: A Comprehensive Review

Alzheimer's disease (AD) is the most common cause of dementia in the elderly, affecting roughly half of those over the age of 85. We briefly discussed the risk factors, epidemiology, and treatment options for AD. The development of therapeutic therapies operating very early in the disease cascade has been spurred by the realization that the disease process begins at least a decade or more before the manifestation of symptoms. Thus, the clinical significance of early diagnosis was emphasized. Using various keywords, a literature search was carried out using PubMed and other databases. For inclusion, pertinent articles were chosen and reviewed. This article has reviewed different neuroimaging techniques that are considered advanced tools to aid in establishing a diagnosis and highlighted the advantages as well as disadvantages of those techniques. Besides, the prevalence of several in vivo biomarkers aided in discriminating affected individuals from healthy controls in the early stages of the disease. Each imaging method has its advantages and disadvantages, hence no single imaging approach can be the optimum modality for diagnosis. This article also commented on a better approach to using these techniques to increase the likelihood of an early diagnosis.

Cortical hyperexcitability and plasticity in Alzheimer's disease: developments in understanding and management

INTRODUCTION

Transcranial magnetic stimulation (TMS) is a non-invasive neurophysiological tool that provides important insights into Alzheimer's Disease (AD). A significant body of work utilizing TMS techniques has explored the pathophysiological relevance of cortical hyperexcitability and plasticity in AD and their modulation in novel therapies.

AREAS COVERED

This review examines the technique of TMS, the use of TMS to examine specific features of cortical excitability and the use of TMS techniques to modulate cortical function. A search was performed utilizing the PubMed database to identify key studies utilizing TMS to examine cortical hyperexcitability and plasticity in Alzheimer's dementia. We then translate this understanding to the study of Alzheimer's disease pathophysiology, examining the underlying neurophysiologic links contributing to these twin signatures, cortical hyperexcitability and abnormal plasticity, in the cortical dysfunction characterizing AD. Finally, we examine utilization of TMS excitability to guide targeted therapies and, through the use of repetitive TMS (rTMS), modulate cortical plasticity.

EXPERT OPINION

The examination of cortical hyperexcitability and plasticity with TMS has potential to optimize and expand the window of therapeutic interventions in AD, though remains at relatively early stage of development.

Potential biomarkers of Alzheimer’s disease and cerebral small vessel disease

Background

Cerebral small vessel disease (CSVD) is associated with the pathogenesis of Alzheimer’s disease (AD). Effective treatments to alleviate AD are still not currently available. Hence, we explored markers and underlying molecular mechanisms associated with AD by utilizing gene expression profiles of AD and CSVD patients from public databases, providing more options for early diagnosis and its treatment.

Methods

Gene expression profiles were collected from GSE63060 (for AD) and GSE162790 (for CSVD). Differential analysis was performed between AD and mild cognitive impairment (MCI) or CSVD progression and CSVD no-progression. In both datasets, differentially expressed genes (DEGs) with the same expression direction were identified as common DEGs. Then protein-protein interaction (PPI) network was constructed for common DEGs. Differential immune cells and checkpoints were calculated between AD and MCI.

Results

A total of 146 common DEGs were identified. Common DEGs were mainly enriched in endocytosis and oxytocin signaling pathways. Interestingly, endocytosis and metabolic pathways were shown both from MCI to AD and from CSVD no-progression to CSVD progression. Moreover, SIRT1 was identified as a key gene by ranking degree of connectivity in the PPI network. SIRT1 was associated with obesity-related genes and metabolic disorders. Additionally, SIRT1 showed correlations with CD8 T cells, NK CD56 bright cells, and checkpoints in AD.

Conclusion

The study revealed that the progression of AD is associated with abnormalities in gene expression and metabolism and that the SIRT1 gene may serve as a promising therapeutic target for the treatment of AD.

A Systematic Review and Meta-Analysis of Cerebrospinal Fluid Amyloid and Tau Levels Identifies Mild Cognitive Impairment Patients Progressing to Alzheimer's Disease

Reported levels of amyloid-beta and tau in human cerebrospinal fluid (CSF) were evaluated to discover if these biochemical markers can predict the transition from Mild Cognitive Impairment (MCI) to Alzheimer’s disease (AD). A systematic review of the literature in PubMed and Web of Science (April 2021) was performed by a single researcher to identify studies reporting immunologically-based (xMAP or ELISA) measures of CSF analytes Aβ(1-42) and/or P-tau and/or T-tau in clinical studies with at least two timepoints and a statement of diagnostic criteria. Of 1137 screened publications, 22 met the inclusion criteria for CSF Aβ(1-42) measures, 20 studies included T-tau, and 17 included P-tau. Six meta-analyses were conducted to compare the analytes for healthy controls (HC) versus progressive MCI (MCI_AD) and for non-progressive MCI (Stable_MCI) versus MCI_AD; effect sizes were determined using random effects models. The heterogeneity of effect sizes across studies was confirmed with very high significance (p < 0.0001) for all meta-analyses except HC versus MCI_AD T-tau (p < 0.05) and P-tau (non-significant). Standard mean difference (SMD) was highly significant (p < 0.0001) for all comparisons (Stable_MCI versus MCI_AD: SMD [95%-CI] Aβ(1-42) = 1.19 [0.96,1.42]; T-tau = −1.03 [−1.24,−0.82]; P-tau = −1.03 [−1.47,−0.59]; HC versus MCI_AD: SMD Aβ(1-42) = 1.73 [1.39,2.07]; T-tau = −1.13 [−1.33,−0.93]; P-tau = −1.10 [−1.23,−0.96]). The follow-up interval in longitudinal evaluations was a critical factor in clinical study design, and the Aβ(1−42)/P-tau ratio most robustly differentiated progressive from non-progressive MCI. The value of amyloid-beta and tau as markers of patient outcome are supported by these findings.

PACTS-Assisted Thermal Proteome Profiling for Use in Identifying Peptide-Interacting Proteins

Bioactive peptides play important roles in various biological processes. However, the traditional methods for profiling the peptide-interacting proteins require modifications to the peptide molecules, often leading to false identifications. We found that the interaction between peptide ligands and protein receptors induced significant changes in the abundance of the interacting proteins, which is a signature indicating the interaction and providing complementary information for use in the classical thermal proteome profiling (TPP) technique. Herein, we developed a novel Peptide-ligand-induced Abundance Change of proTeinS (PACTS)-assisted TPP strategy for the identification of peptide-interacting proteins based on the peptide-ligand-induced change in protein abundance. The utility and efficacy of this approach were demonstrated by the identification of the interaction of the protein 3-phosphoinositide-dependent protein kinase 1 (PDPK1) and PDPK1-interacting fragment (PIF) pair and by large-scale profiling of the interacting proteins of PIF. The PACTS-assisted TPP approach was applied to describe the interactome of amyloid beta (Aβ) 1-42 in THP-1 cells and resulted in the identification of 103 interacting proteins. Validation experiments indicated that Aβ1-42 interacted directly with fatty acid synthase and inhibited its enzymatic activity, providing insights into fatty acid metabolic disorders in Alzheimer's disease (AD). Overall, PACTS-assisted TPP is an efficient approach, and the newly identified Aβ-interacting proteins provide rich resources for the research on AD.

Amyloid-β Oligomers: Multiple Moving Targets

Alzheimer’s Disease (AD) is a neurodegenerative disorder that is characterized clinically by progressive cognitive decline and pathologically by the β-sheet rich fibril plaque deposition of the amyloid-β (Aβ) peptide in the brain. While plaques are a hallmark of AD, plaque burden is not correlated with cognitive impairment. Instead, Aβ oligomers formed during the aggregation process represent the main agents of neurotoxicity, which occurs 10–20 years before patients begin to show symptoms. These oligomers are dynamic in nature and represented by a heterogeneous distribution of aggregates ranging from low- to high-molecular weight, some of which are toxic while others are not. A major difficulty in determining the pathological mechanism(s) of Aβ, developing reliable diagnostic markers for early-stage detection, as well as effective therapeutics for AD are the differentiation and characterization of oligomers formed throughout disease propagation based on their molecular features, effects on biological function, and relevance to disease propagation and pathology. Thus, it is critical to methodically identify the mechanisms of Aβ aggregation and toxicity, as well as describe the roles of different oligomers and aggregates in disease progression and molecular pathology. Here, we describe a variety of biophysical techniques used to isolate and characterize a range of Aβ oligomer populations, as well as discuss proposed mechanisms of toxicity and therapeutic interventions aimed at specific assemblies formed during the aggregation process. The approaches being used to map the misfolding and aggregation of Aβ are like what was done during the fundamental early studies, mapping protein folding pathways using combinations of biophysical techniques in concert with protein engineering. Such information is critical to the design and molecular engineering of future diagnostics and therapeutics for AD.

Brain Metabolite, Myo-inositol, Inhibits Catalase Activity: A Mechanism of the Distortion of the Antioxidant Defense System in Alzheimer's disease

A strong correlation between brain metabolite accumulation and oxidative stress has been observed in Alzheimer's disease (AD) patients. There are two central hypotheses for this correlation: (i) coaccumulation of toxic amyloid-β and Myo-inositol (MI), a significant brain metabolite, during presymptomatic stages of AD, and (ii) enhanced expression of MI transporter in brain cells during oxidative stress-induced volume changes in the brain. Identifying specific interactive effects of MI with cellular antioxidant enzymes would represent an essential step in understanding the oxidative stress-induced AD pathogenicity. This study demonstrated that MI inhibits catalase, an essential antioxidant enzyme primarily inefficient in AD, by decreasing its k _cat (turnover number) and increasing K _m (Michaelis-Menten constant) values. This inhibition of catalase by MI under in vivo studies increased cellular H₂O₂ levels, leading to decreased cell viability. Furthermore, MI induces distortion of the active heme center with an overall loss of structure and stability of catalase. MI also alters distances of the vital active site and substrate channel residues of catalase. The present study provides evidence for the involvement of MI in the inactivation of the antioxidant defense system during oxidative stress-induced pathogenesis of AD. Regulation of MI levels, during early presymptomatic stages of AD, might serve as a potential early-on therapeutic strategy for this disease.

Cognitive Impairment in Heart Failure: Landscape, Challenges, and Future Directions

Heart failure (HF) is a major global healthcare problem accounting for substantial deterioration of prognosis. As a complex clinical syndrome, HF often coexists with multi-comorbidities of which cognitive impairment (CI) is particularly important. CI is increasing in prevalence among patients with HF and is present in around 40%, even up to 60%, of elderly patients with HF. As a potent and independent prognostic factor, CI significantly increases the hospitalization and mortality and decreases quality of life in patients with HF. There has been a growing awareness of the complex bidirectional interaction between HF and CI as it shares a number of common pathophysiological pathways including reduced cerebral blood flow, inflammation, and neurohumoral activations. Research that focus on the precise mechanism for CI in HF is still ever insufficient. As the tremendous adverse consequences of CI in HF, effective early diagnosis of CI in HF and interventions for these patients may halt disease progression and improve prognosis. The current clinical guidelines in HF have begun to emphasize the importance of CI. However, nearly half of CI in HF is underdiagnosed, and few recommendations are available to guide clinicians about how to approach CI in patients with HF. This review aims to synthesize knowledge about the link between HF and cognitive dysfunction, issues pertaining to screening, diagnosis and management of CI in patients with HF, and emerging therapies for prevention. Based on data from current studies, critical gaps in knowledge of CI in HF are identified, and future research directions to guide the field forward are proposed.

Neurobiological Highlights of Cognitive Impairment in Psychiatric Disorders

This review is focused on several psychiatric disorders in which cognitive impairment is a major component of the disease, influencing life quality. There are plenty of data proving that cognitive impairment accompanies and even underlies some psychiatric disorders. In addition, sources provide information on the biological background of cognitive problems associated with mental illness. This scientific review aims to summarize the current knowledge about neurobiological mechanisms of cognitive impairment in people with schizophrenia, depression, mild cognitive impairment and dementia (including Alzheimer's disease).The review provides data about the prevalence of cognitive impairment in people with mental illness and associated biological markers.

Ethical Issues in Dementia Research

Dementia is a global public health issue with an urgent need for developing newer and more effective treatment strategies. Research in the area of dementia, however, poses unique ethical and legal challenges. Epidemiological studies, studies on pharmacological and non-pharmacological interventions have to deal with obtaining consent from persons with cognitive impairments, those from diverse cultural groups and need to contend with privacy and confidentiality issues. The caregiver support intervention research has not yet translated into policy change and effective clinical care. Biomedical research that involves invasive procedures may not translate into short- or long-term therapeutic benefits but is necessary research. Palliative care research in dementia has to deal with ethical issues involving people at end-of-life research. Proposed research may not receive approval, citing necessary safeguards to the vulnerable older people against invasive studies even when it is least invasive. This article aims to review the ethical aspects for safeguarding vulnerable older people with dementia and the potential challenges in conducting dementia research from a researcher's perspective. Some of the safeguards for ethical research include determining capacity to consent, obtaining advanced directives in early stages and proxy consent from caregivers, obtaining informed consent in cognitively impaired individuals. Future research policies need to consider the logistics of involving older people in research, enhancing caregiver support, and encouraging supportive decision-making. It will also need to address developing capacity assessment tools while addressing advanced care planning that will ensure the well-being of subjects in research.

BACKGROUND

Dementia has become a global public health issue, with hospitalization rates being 65% higher in seniors with dementia than others.^1,2 The pressures on healthcare systems mean an urgent need to develop robust preventive and treatment strategies for dementia, which requires multidisciplinary research. However, the patient's stage of illness and ability to engage in discussions around the merits of participating in research and caregiver concerns is an important aspect of dementia research.Hence, dementia research poses unique ethical challenges compared to populations with other diseases, which has led to the evolution of an ethical framework for dementia research. This article aims to review and give a viewpoint on the ethical aspects for safeguarding vulnerable older people with dementia and the potential challenges in conducting dementia research from a researcher's perspective.

What Should We Do With People Who Cannot or Do Not Want to Be Protected From Neurotechnological Threats?

Neurotechnologies can pose a threat to people's privacy and mental integrity. Hence the proposal of establishing neurorights (Ienca and Andorno, 2017) and technical principles for the implementation of these rights (Lavazza, 2018). However, concepts such as "the extended mind" and what might be called "the post-human objection" can be said to challenge this protection paradigm. On the one hand, it may be difficult to outline the cognitive boundaries between humans and machines (with the consequent ethical and legal implications). On the other hand, those who wish to make strong use of neurotechnologies, or even hybridize with them, reject the idea that privacy and mental integrity should be protected. However, from the latter view, issues may arise relating to the protection of persons entering into relationships with posthumanist people. This article will discuss these scenarios as well as the ethical, legal, social, and political issues that could follow from them.

Identifying Individuals With Mild Cognitive Impairment Using Working Memory-Induced Intra-Subject Variability of Resting-State EEGs

Individuals with mild cognitive impairment (MCI) are at high risk of developing into dementia (e. g., Alzheimer's disease, AD). A reliable and effective approach for early detection of MCI has become a critical challenge. Although compared with other costly or risky lab tests, electroencephalogram (EEG) seems to be an ideal alternative measure for early detection of MCI, searching for valid EEG features for classification between healthy controls (HCs) and individuals with MCI remains to be largely unexplored. Here, we design a novel feature extraction framework and propose that the spectral-power-based task-induced intra-subject variability extracted by this framework can be an encouraging candidate EEG feature for the early detection of MCI. In this framework, we extracted the task-induced intra-subject spectral power variability of resting-state EEGs (as measured by a between-run similarity) before and after participants performing cognitively exhausted working memory tasks as the candidate feature. The results from 74 participants (23 individuals with AD, 24 individuals with MCI, 27 HC) showed that the between-run similarity over the frontal and central scalp regions in the HC group is higher than that in the AD or MCI group. Furthermore, using a feature selection scheme and a support vector machine (SVM) classifier, the between-run similarity showed encouraging leave-one-participant-out cross-validation (LOPO-CV) classification performance for the classification between the MCI and HC (80.39%) groups and between the AD vs. HC groups (78%), and its classification performance is superior to other widely-used features such as spectral powers, coherence, and the complexity estimated by Katz's method extracted from single-run resting-state EEGs (a common approach in previous studies). The results based on LOPO-CV, therefore, suggest that the spectral-power-based task-induced intra-subject EEG variability extracted by the proposed feature extraction framework has the potential to serve as a neurophysiological feature for the early detection of MCI in individuals.

Mini-Mental State Examination (MMSE) for the early detection of dementia in people with mild cognitive impairment (MCI)

BACKGROUND

Dementia is a progressive global cognitive impairment syndrome. In 2010, more than 35 million people worldwide were estimated to be living with dementia. Some people with mild cognitive impairment (MCI) will progress to dementia but others remain stable or recover full function. There is great interest in finding good predictors of dementia in people with MCI. The Mini-Mental State Examination (MMSE) is the best-known and the most often used short screening tool for providing an overall measure of cognitive impairment in clinical, research and community settings.

OBJECTIVES

To determine the accuracy of the Mini Mental State Examination for the early detection of dementia in people with mild cognitive impairment SEARCH METHODS: We searched ALOIS (Cochrane Dementia and Cognitive Improvement Specialized Register of diagnostic and intervention studies (inception to May 2014); MEDLINE (OvidSP) (1946 to May 2014); EMBASE (OvidSP) (1980 to May 2014); BIOSIS (Web of Science) (inception to May 2014); Web of Science Core Collection, including the Conference Proceedings Citation Index (ISI Web of Science) (inception to May 2014); PsycINFO (OvidSP) (inception to May 2014), and LILACS (BIREME) (1982 to May 2014). We also searched specialized sources of diagnostic test accuracy studies and reviews, most recently in May 2014: MEDION (Universities of Maastricht and Leuven, www.mediondatabase.nl), DARE (Database of Abstracts of Reviews of Effects, via the Cochrane Library), HTA Database (Health Technology Assessment Database, via the Cochrane Library), and ARIF (University of Birmingham, UK, www.arif.bham.ac.uk). No language or date restrictions were applied to the electronic searches and methodological filters were not used as a method to restrict the search overall so as to maximize sensitivity. We also checked reference lists of relevant studies and reviews, tracked citations in Scopus and Science Citation Index, used searches of known relevant studies in PubMed to track related articles, and contacted research groups conducting work on MMSE for dementia diagnosis to try to locate possibly relevant but unpublished data.

SELECTION CRITERIA

We considered longitudinal studies in which results of the MMSE administered to MCI participants at baseline were obtained and the reference standard was obtained by follow-up over time. We included participants recruited and clinically classified as individuals with MCI under Petersen and revised Petersen criteria, Matthews criteria, or a Clinical Dementia Rating = 0.5. We used acceptable and commonly used reference standards for dementia in general, Alzheimer's dementia, Lewy body dementia, vascular dementia and frontotemporal dementia.

DATA COLLECTION AND ANALYSIS

We screened all titles generated by the electronic database searches. Two review authors independently assessed the abstracts of all potentially relevant studies. We assessed the identified full papers for eligibility and extracted data to create two by two tables for dementia in general and other dementias. Two authors independently performed quality assessment using the QUADAS-2 tool. Due to high heterogeneity and scarcity of data, we derived estimates of sensitivity at fixed values of specificity from the model we fitted to produce the summary receiver operating characteristic curve.

MAIN RESULTS

In this review, we included 11 heterogeneous studies with a total number of 1569 MCI patients followed for conversion to dementia. Four studies assessed the role of baseline scores of the MMSE in conversion from MCI to all-cause dementia and eight studies assessed this test in conversion from MCI to Alzheimer´s disease dementia. Only one study provided information about the MMSE and conversion from MCI to vascular dementia. For conversion from MCI to dementia in general, the accuracy of baseline MMSE scores ranged from sensitivities of 23% to 76% and specificities from 40% to 94%. In relationship to conversion from MCI to Alzheimer's disease dementia, the accuracy of baseline MMSE scores ranged from sensitivities of 27% to 89% and specificities from 32% to 90%. Only one study provided information about conversion from MCI to vascular dementia, presenting a sensitivity of 36% and a specificity of 80% with an incidence of vascular dementia of 6.2%. Although we had planned to explore possible sources of heterogeneity, this was not undertaken due to the scarcity of studies included in our analysis.

AUTHORS' CONCLUSIONS

Our review did not find evidence supporting a substantial role of MMSE as a stand-alone single-administration test in the identification of MCI patients who could develop dementia. Clinicians could prefer to request additional and extensive tests to be sure about the management of these patients. An important aspect to assess in future updates is if conversion to dementia from MCI stages could be predicted better by MMSE changes over time instead of single measurements. It is also important to assess if a set of tests, rather than an isolated one, may be more successful in predicting conversion from MCI to dementia.

Differences in structural and functional default mode network connectivity in amyloid positive mild cognitive impairment: a longitudinal study

PURPOSE

Default mode network (DMN) has emerged as a potential biomarker of Alzheimer's disease (AD); however, it is not clear whether it can differentiate amnestic mild cognitive impairment with altered amyloid (aMCI-Aβ +) who will evolve to AD. We evaluated if structural and functional connectivity (FC), hippocampal volumes (HV), and cerebrospinal fluid biomarkers (CSF-Aβ₄₂, p-Tau, and t-Tau) can differentiate aMCI-Aβ + converters from non-converters.

METHODS

Forty-eight individuals (18 normal controls and 30 aMCI subjects in the AD continuum - with altered Aβ₄₂ in the CSF) were followed up for an average of 13 months. We used MultiAtlas, UF²C, and Freesurfer software to evaluate diffusion tensor imaging, FC, and HV, respectively, INNOTEST® kits to measure CSF proteins, and neuropsychological tests. Besides, we performed different MANOVAs with further univariate analyses to differentiate groups.

RESULTS

During follow-up, 8/30 aMCI-Aβ + converted (26.6%) to AD dementia. There were no differences in multivariate analysis between groups in CSF biomarkers (p = 0.092) or at DMN functional connectivity (p = 0.814). aMCI-Aβ + converters had smaller right HV than controls (p = 0.013), and greater right cingulum parahippocampal bundle radial diffusivity than controls (p < 0.001) and non-converters (p = 0.036).

CONCLUSION

In this exploratory study, structural, but not functional, DMN connectivity alterations may differentiate aMCI-Aβ + subjects who converted to AD dementia.

Toward a Universal Readout for 18F-Labeled Amyloid Tracers: The CAPTAINs Study

To date, 3 18F-labeled PET tracers have been approved for assessing cerebral amyloid plaque pathology in the diagnostic workup of suspected Alzheimer disease (AD). Although scanning protocols are relatively similar across tracers, U.S. Food and Drug Administration- and the European Medicines Agency-approved visual rating protocols differ among the 3 tracers. This proof-of-concept study assessed the comparability of the 3 approved visual rating protocols to classify a scan as amyloid-positive or -negative, when applied by groups of experts and nonexperts to all 3 amyloid tracers. Methods: In an international multicenter approach, both expert (n = 4) and nonexpert raters (n = 3) rated scans acquired with 18F-florbetaben, 18F-florbetapir and 18F-flutemetamol. Scans obtained with each tracer were presented for reading according to all 3 approved visual rating protocols. In a randomized order, every single scan was rated by each reader according to all 3 protocols. Raters were blinded for the amyloid tracer used and asked to rate each scan as positive or negative, giving a confidence judgment after each response. Percentage of visual reader agreement, interrater reliability, and agreement of each visual read with binary quantitative measures (fixed SUV ratio threshold for positive or negative scans) were computed. These metrics were analyzed separately for expert and nonexpert groups. Results: No significant differences in using the different approved visual rating protocols were observed across the different metrics of agreement in the group of experts. Nominal differences suggested that the 18F-florbetaben visual rating protocol achieved the highest interrater reliability and accuracy especially under low confidence conditions. For the group of nonexpert raters, significant differences between the different visual rating protocols were observed with overall moderate-to-fair accuracy and with the highest reliability for the 18F-florbetapir visual rating protocol. Conclusion: We observed high interrater agreement despite applying different visual rating protocols for all 18F-labeled amyloid tracers. This implies that the results of the visual interpretation of amyloid imaging can be well standardized and do not depend on the rating protocol in experts. Consequently, the creation of a universal visual assessment protocol for all amyloid imaging tracers appears feasible, which could benefit especially the less-experienced readers.

Clinical diagnosis of Alzheimer's disease: recommendations of the International Working Group

In 2018, the US National Institute on Aging and the Alzheimer's Association proposed a purely biological definition of Alzheimer's disease that relies on biomarkers. Although the intended use of this framework was for research purposes, it has engendered debate and challenges regarding its use in everyday clinical practice. For instance, cognitively unimpaired individuals can have biomarker evidence of both amyloid β and tau pathology but will often not develop clinical manifestations in their lifetime. Furthermore, a positive Alzheimer's disease pattern of biomarkers can be observed in other brain diseases in which Alzheimer's disease pathology is present as a comorbidity. In this Personal View, the International Working Group presents what we consider to be the current limitations of biomarkers in the diagnosis of Alzheimer's disease and, on the basis of this evidence, we propose recommendations for how biomarkers should and should not be used for diagnosing Alzheimer's disease in a clinical setting. We recommend that Alzheimer's disease diagnosis be restricted to people who have positive biomarkers together with specific Alzheimer's disease phenotypes, whereas biomarker-positive cognitively unimpaired individuals should be considered only at-risk for progression to Alzheimer's disease.

Plasma Amyloid Concentration in Alzheimer's Disease: Performance of a High-Throughput Amyloid Assay in Distinguishing Alzheimer's Disease Cases from Controls

Background:

Collection of cerebrospinal fluid (CSF) for measurement of amyloid-β (Aβ) species is a gold standard in Alzheimer’s disease (AD) diagnosis, but has risks. Thus, establishing a low-risk blood Aβ test with high AD sensitivity and specificity is of outmost interest.

Objective:

We evaluated the ability of a commercially available plasma Aβ assay to distinguish AD patients from biomarker-healthy controls.

Method:

In a case-control design, we examined plasma samples from 44 AD patients (A + N+) and 49 controls (A–N–) from a memory clinic. AD was diagnosed using a combination of neuropsychological examination, CSF biomarker analysis and brain imaging. Total Aβ₄₀ and total Aβ₄₂ in plasma were measured through enzyme-linked immunosorbent assay (ELISA) technology using ABtest40 and ABtest42 test kits (Araclon Biotech Ltd.). Receiver operating characteristic (ROC) analyses with outcome AD were performed, and sensitivity and specificity were calculated.

Results:

Plasma Aβ_42/40 was weakly positively correlated with CSF Aβ_42/40 (Spearman’s rho 0.22; p = 0.037). Plasma Aβ_42/40 alone was not able to statistically significantly distinguish between AD patients and controls (AUC 0.58; 95% CI 0.46, 0.70). At a cut-point of 0.076 maximizing sensitivity and specificity, plasma Aβ_42/40 had a sensitivity of 61.2% and a specificity of 63.6%.

Conclusion:

In this sample, the high-throughput blood Aβ assay was not able to distinguish well between AD patients and controls. Whether or not the assay may be useful in large-scale epidemiological settings remains to be seen.

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.

microRNAs as Early Biomarkers of Alzheimer's Disease: A Synaptic Perspective

Pathogenic processes underlying Alzheimer's disease (AD) affect synaptic function from initial asymptomatic stages, long time before the onset of cognitive decline and neurodegeneration. Therefore, reliable biomarkers enabling early AD diagnosis and prognosis are needed to maximize the time window for therapeutic interventions. MicroRNAs (miRNAs) have recently emerged as promising cost-effective and non-invasive biomarkers for AD, since they can be readily detected in different biofluids, including cerebrospinal fluid (CSF) and blood. Moreover, a growing body of evidence indicates that miRNAs regulate synaptic homeostasis and plasticity processes, suggesting that they may be involved in early synaptic dysfunction during AD. Here, we review the current literature supporting a role of miRNAs during early synaptic deficits in AD, including recent studies evaluating their potential as AD biomarkers. Besides targeting genes related to Aβ and tau metabolism, several miRNAs also regulate synaptic-related proteins and transcription factors implicated in early synaptic deficits during AD. Furthermore, individual miRNAs and molecular signatures have been found to distinguish between prodromal AD and healthy controls. Overall, these studies highlight the relevance of considering synaptic-related miRNAs as potential biomarkers of early AD stages. However, further validation studies in large cohorts, including longitudinal studies, as well as implementation of standardized protocols, are needed to establish miRNA-based biomarkers as reliable diagnostic and prognostic tools.

Souvenaid for Alzheimer's disease

BACKGROUND

Souvenaid is a dietary supplement with a patented composition (Fortasyn Connect™)which is intended to be used by people with Alzheimer's disease (AD). It has been designed to support the formation and function of synapses in the brain, which are thought to be strongly correlated with cognitive function. If effective, it might improve symptoms of Alzheimer's disease and also prevent the progression from prodromal Alzheimer's disease to dementia. We sought in this review to examine the evidence for this proposition.

OBJECTIVES

To assess the effects of Souvenaid on incidence of dementia, cognition, functional performance, and safety in people with Alzheimer's disease.

SEARCH METHODS

We searched ALOIS, i.e. the specialised register of the Cochrane Dementia and Cognitive Improvement Group, MEDLINE (Ovid SP), Embase (Ovid SP), PsycINFO (Ovid SP), Web of Science (ISI Web of Science), Cinahl (EBSCOhost), Lilacs (BIREME), and clinical trials registries up to 24 June 2020. We also reviewed citations of reference lists of landmark papers, reviews, and included studies for additional studies and assessed their suitability for inclusion in the review.

SELECTION CRITERIA

We included randomised, placebo-controlled trials which evaluated Souvenaid in people diagnosed with mild cognitive impairment (MCI) due to AD (also termed prodromal AD) or with dementia due to AD, and with a treatment duration of at least 16 weeks.

DATA COLLECTION AND ANALYSIS

Our primary outcome measures were incidence of dementia, global and specific cognitive function, functional performance, combined cognitive-functional outcomes and adverse events. We selected studies, extracted data, assessed the quality of trials and intended to conduct meta-analyses according to the Cochrane Handbook for Systematic Reviews of Interventions. We rated the quality of the evidence using the GRADE approach. We present all outcomes grouped by stage of AD.

MAIN RESULTS

We included three randomised, placebo-controlled trials investigating Souvenaid in 1097 community-dwelling participants with Alzheimer's disease. One study each included participants with prodromal AD, mild AD dementia and mild-to-moderate AD dementia. We rated the risks of bias of all trials as low. One study (in prodromal AD) was funded by European grants. The other two studies were funded by the manufacturer of Souvenaid. One trial investigated the incidence of dementia in people with prodromal AD at baseline, and found little to no difference between the Souvenaid group and the placebo group after 24 months (RR 1.09, 95% CI 0.82 to 1.43; 1 trial, 311 participants; moderate quality of evidence). In prodromal AD, and in mild and mild-to-moderate Alzheimer's disease dementia, Souvenaid probably results in little or no difference in global or specific cognitive functions (moderate quality of evidence). Everyday function, or the ability to perform activities of daily living, were measured in mild and mild-to-moderate AD dementia. Neither study found evidence of a difference between the groups after 24 weeks of treatment (moderate quality of evidence). Two studies investigated combined cognitive-functional outcomes with the Clinical Dementia Rating Sum of Boxes and observed conflicting results. Souvenaid probably results in slight improvement, which is below estimates of meaningful change, in participants with prodromal Alzheimer's disease after 24 months (moderate quality of evidence), but probably has little to no effect in mild-to-moderate Alzheimer's disease dementia after 24 weeks (moderate quality of evidence). Adverse effects observed were low in all trials, and the available data were insufficient to determine any connection with Souvenaid.

AUTHORS' CONCLUSIONS

Two years of treatment with Souvenaid probably does not reduce the risk of progression to dementia in people with prodromal AD. There is no convincing evidence that Souvenaid affects other outcomes important to people with AD in the prodromal stage or mild-to-moderate stages of dementia. Conflicting evidence on combined cognitive-functional outcomes in prodromal AD and mild AD dementia warrants further investigation. Adverse effects of Souvenaid seem to be uncommon, but the evidence synthesised in this review does not permit us to make a definitive statement on the long-term tolerability of Souvenaid. The effects of Souvenaid in more severe AD dementia or in people with AD at risk of nutritional deficiencies remain unclear.

Blood-Based Biomarkers for Predictive Diagnosis of Cognitive Impairment in a Pakistani Population

Numerous studies have identified an association between age-related cognitive impairment (CI) and oxidative damage, accumulation of metals, amyloid levels, tau, and deranged lipid profile. There is a concerted effort to establish the reliability of these blood-based biomarkers for predictive diagnosis of CI and its progression. We assessed the serum levels of high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, triglycerides, total cholesterol, selected metals (Cu, Al, Zn, Pb, Mn, Cad), and total-tau and amyloid beta-42 protein in mild (n = 71), moderate (n = 86) and severe (n = 25) cognitively impaired patients and compared them with age-matched healthy controls (n = 90) from Pakistan. We found that a decrease in HDL cholesterol (correlation coefficient r = 0.467) and amyloid beta-42 (r = 0.451) were associated with increased severity of CI. On the other hand, an increase in cholesterol ratio (r = -0.562), LDL cholesterol (r = -0.428), triglycerides, and total-tau (r = -0.443) were associated with increased severity of CI. Increases in cholesterol ratio showed the strongest association and correlated with increases in tau concentration (r = 0.368), and increased triglycerides were associated with decreased amyloid beta-42 (r = -0.345). Increased Cu levels showed the strongest association with tau increase and increased Zn and Pb levels showed the strongest association with reduced amyloid beta-42 levels. Receiver Operating Characteristic (ROC) showed the cutoff values of blood metals (Al, Pb, Cu, Cad, Zn, and Mn), total-tau, and amyloid beta-42 with sensitivity and specificity. Our data show for the first time that blood lipids, metals (particularly Cu, Zn, Pb, and Al), serum amyloid-beta-42/tau proteins modulate each other's levels and can be collectively used as a predictive marker for CI.

Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment

BACKGROUND

Mild cognitive impairment (MCI) due to Alzheimer's disease is the symptomatic predementia phase of Alzheimer's disease dementia, characterised by cognitive and functional impairment not severe enough to fulfil the criteria for dementia. In clinical samples, people with amnestic MCI are at high risk of developing Alzheimer's disease dementia, with annual rates of progression from MCI to Alzheimer's disease estimated at approximately 10% to 15% compared with the base incidence rates of Alzheimer's disease dementia of 1% to 2% per year.

OBJECTIVES

To assess the diagnostic accuracy of structural magnetic resonance imaging (MRI) for the early diagnosis of dementia due to Alzheimer's disease in people with MCI versus the clinical follow-up diagnosis of Alzheimer's disease dementia as a reference standard (delayed verification). To investigate sources of heterogeneity in accuracy, such as the use of qualitative visual assessment or quantitative volumetric measurements, including manual or automatic (MRI) techniques, or the length of follow-up, and age of participants. MRI was evaluated as an add-on test in addition to clinical diagnosis of MCI to improve early diagnosis of dementia due to Alzheimer's disease in people with MCI.

SEARCH METHODS

On 29 January 2019 we searched Cochrane Dementia and Cognitive Improvement's Specialised Register and the databases, MEDLINE, Embase, BIOSIS Previews, Science Citation Index, PsycINFO, and LILACS. We also searched the reference lists of all eligible studies identified by the electronic searches.

SELECTION CRITERIA

We considered cohort studies of any size that included prospectively recruited people of any age with a diagnosis of MCI. We included studies that compared the diagnostic test accuracy of baseline structural MRI versus the clinical follow-up diagnosis of Alzheimer's disease dementia (delayed verification). We did not exclude studies on the basis of length of follow-up. We included studies that used either qualitative visual assessment or quantitative volumetric measurements of MRI to detect atrophy in the whole brain or in specific brain regions, such as the hippocampus, medial temporal lobe, lateral ventricles, entorhinal cortex, medial temporal gyrus, lateral temporal lobe, amygdala, and cortical grey matter.

DATA COLLECTION AND ANALYSIS

Four teams of two review authors each independently reviewed titles and abstracts of articles identified by the search strategy. Two teams of two review authors each independently assessed the selected full-text articles for eligibility, extracted data and solved disagreements by consensus. Two review authors independently assessed the quality of studies using the QUADAS-2 tool. We used the hierarchical summary receiver operating characteristic (HSROC) model to fit summary ROC curves and to obtain overall measures of relative accuracy in subgroup analyses. We also used these models to obtain pooled estimates of sensitivity and specificity when sufficient data sets were available.

MAIN RESULTS

We included 33 studies, published from 1999 to 2019, with 3935 participants of whom 1341 (34%) progressed to Alzheimer's disease dementia and 2594 (66%) did not. Of the participants who did not progress to Alzheimer's disease dementia, 2561 (99%) remained stable MCI and 33 (1%) progressed to other types of dementia. The median proportion of women was 53% and the mean age of participants ranged from 63 to 87 years (median 73 years). The mean length of clinical follow-up ranged from 1 to 7.6 years (median 2 years). Most studies were of poor methodological quality due to risk of bias for participant selection or the index test, or both. Most of the included studies reported data on the volume of the total hippocampus (pooled mean sensitivity 0.73 (95% confidence interval (CI) 0.64 to 0.80); pooled mean specificity 0.71 (95% CI 0.65 to 0.77); 22 studies, 2209 participants). This evidence was of low certainty due to risk of bias and inconsistency. Seven studies reported data on the atrophy of the medial temporal lobe (mean sensitivity 0.64 (95% CI 0.53 to 0.73); mean specificity 0.65 (95% CI 0.51 to 0.76); 1077 participants) and five studies on the volume of the lateral ventricles (mean sensitivity 0.57 (95% CI 0.49 to 0.65); mean specificity 0.64 (95% CI 0.59 to 0.70); 1077 participants). This evidence was of moderate certainty due to risk of bias. Four studies with 529 participants analysed the volume of the total entorhinal cortex and four studies with 424 participants analysed the volume of the whole brain. We did not estimate pooled sensitivity and specificity for the volume of these two regions because available data were sparse and heterogeneous. We could not statistically evaluate the volumes of the lateral temporal lobe, amygdala, medial temporal gyrus, or cortical grey matter assessed in small individual studies. We found no evidence of a difference between studies in the accuracy of the total hippocampal volume with regards to duration of follow-up or age of participants, but the manual MRI technique was superior to automatic techniques in mixed (mostly indirect) comparisons. We did not assess the relative accuracy of the volumes of different brain regions measured by MRI because only indirect comparisons were available, studies were heterogeneous, and the overall accuracy of all regions was moderate.

AUTHORS' CONCLUSIONS

The volume of hippocampus or medial temporal lobe, the most studied brain regions, showed low sensitivity and specificity and did not qualify structural MRI as a stand-alone add-on test for an early diagnosis of dementia due to Alzheimer's disease in people with MCI. This is consistent with international guidelines, which recommend imaging to exclude non-degenerative or surgical causes of cognitive impairment and not to diagnose dementia due to Alzheimer's disease. In view of the low quality of most of the included studies, the findings of this review should be interpreted with caution. Future research should not focus on a single biomarker, but rather on combinations of biomarkers to improve an early diagnosis of Alzheimer's disease dementia.

CSF and blood Kallikrein-8: a promising early biomarker for Alzheimer's disease

OBJECTIVE

There is still an urgent need for supportive minimally invasive and cost-effective biomarkers for early diagnosis of Alzheimer's disease (AD). Previous work in our lab has identified Kallikrein-8 (KLK8) as a potential candidate since it shows an excessive increase in human brain in preclinical disease stages. The aim of this study was to evaluate the diagnostic performance of cerebrospinal fluid (CSF) and blood KLK8 for AD and mild cognitive impairment (MCI) due to AD.

METHODS

In this multi-centre trans-sectional study, clinical and laboratory data as well as CSF and/or blood serum samples of 237 participants, including 98 patients with mild AD, 21 with MCI due to AD and 118 controls were collected. CSF and/or serum KLK8 levels were analysed by ELISA. The diagnostic accuracy of KLK8 in CSF and blood was determined using receiver operating characteristic (ROC) analyses and compared with that of CSF core biomarkers Aβ42, P-tau and T-tau.

RESULTS

The diagnostic accuracy of CSF KLK8 was as good as that of core CSF biomarkers for AD (area under the curve (AUC)=0.89) and in case of MCI (AUC=0.97) even superior to CSF Aβ42. Blood KLK8 was a similarly strong discriminator for MCI (AUC=0.94) but slightly weaker for AD (AUC=0.83).

CONCLUSIONS

This is the first study to demonstrate the potential clinical utility of blood and CSF KLK8 as a biomarker for incipient AD. Future prospective validation studies are warranted.

Methodological Issues in the Clinical Validation of Biomarkers for Alzheimer's Disease: The Paradigmatic Example of CSF

The use of biomarkers is profoundly transforming medical research and practice. Their adoption has triggered major advancements in the field of Alzheimer’s disease (AD) over the past years. For instance, the analysis of the cerebrospinal fluid (CSF) and neuroimaging changes indicative of neuronal loss and amyloid deposition has led to the understanding that AD is characterized by a long preclinical phase. It is also supporting the transition towards a biology-grounded framework and definition of the disease. Nevertheless, though sufficient evidence exists about the analytical validity (i.e., accuracy, reliability, and reproducibility) of the candidate AD biomarkers, their clinical validity (i.e., how well the test measures the clinical features, and the disease or treatment outcomes) and clinical utility (i.e., if and how the test improves the patient’s outcomes, confirms/changes the diagnosis, identifies at-risk individuals, influences therapeutic choices) have not been fully proven. In the present review, some of the methodological issues and challenges that should be addressed in order to better appreciate the potential benefits and limitations of AD biomarkers are discussed. The ultimate goal is to stimulate a constructive discussion aimed at filling the existing gaps and more precisely defining the directions of future research. Specifically, four main aspects of the clinical validation process are addressed and applied to the most relevant CSF biomarkers: (1) the definition of reference values; (2) the identification of reference standards for the disease of interest (i.e., AD); (3) the inclusion within the diagnostic process; and (4) the statistical process supporting the whole framework.

Brain Structural Correlates of Odor Identification in Mild Cognitive Impairment and Alzheimer's Disease Revealed by Magnetic Resonance Imaging and a Chinese Olfactory Identification Test

Alzheimer's disease (AD) is a common memory-impairment disorder frequently accompanied by olfactory identification (OI) impairments. In fact, OI is a valuable marker for distinguishing AD from normal age-related cognitive impairment and may predict the risk of mild cognitive impairment (MCI)-to-AD transition. However, current olfactory tests were developed based on Western social and cultural conditions, and are not very suitable for Chinese patients. Moreover, the neural substrate of OI in AD is still unknown. The present study investigated the utility of a newly developed Chinese smell identification test (CSIT) for OI assessment in Chinese AD and MCI patients. We then performed a correlation analysis of gray matter volume (GMV) at the voxel and region-of-interest (ROI) levels to reveal the neural substrates of OI in AD. Thirty-seven AD, 27 MCI, and 30 normal controls (NCs) completed the CSIT and MRI scans. Patients (combined AD plus MCI) scored significantly lower on the CSIT compared to NCs [F(2,91) = 62.597, p < 0.001)]. Voxel-level GMV analysis revealed strong relationships between CSIT score and volumes of the left precentral gyrus and left inferior frontal gyrus (L-IFG). In addition, ROI-level GMV analysis revealed associations between CSIT score and left amygdala volumes. Our results suggest the following: (1) OI, as measured by the CSIT, is impaired in AD and MCI patients compared with healthy controls in the Chinese population; (2) the severity of OI dysfunction can distinguish patients with cognitive impairment from controls and AD from MCI patients; and (3) the left-precentral cortex and L-IFG may be involved in the processing of olfactory cues.

Development of an interactive web-based tool to conduct and interrogate meta-analysis of diagnostic test accuracy studies: MetaDTA

Background

Recommended statistical methods for meta-analysis of diagnostic test accuracy studies require relatively complex bivariate statistical models which can be a barrier for non-statisticians. A further barrier exists in the software options available for fitting such models. Software accessible to non-statisticians, such as RevMan, does not support the fitting of bivariate models thus users must seek statistical support to use R, Stata or SAS. Recent advances in web technologies make analysis tool creation much simpler than previously. As well as accessibility, online tools can allow tailored interactivity not found in other packages allowing multiple perspectives of data to be displayed and information to be tailored to the user’s preference from a simple interface. We set out to: (i) Develop a freely available web-based “point and click” interactive tool which allows users to input their DTA study data and conduct meta-analyses for DTA reviews, including sensitivity analyses. (ii) Illustrate the features and benefits of the interactive application using an existing DTA meta-analysis for detecting dementia.

Methods

To create our online freely available interactive application we used the existing R packages lme4 and Shiny to analyse the data and create an interactive user interface respectively.

Results

MetaDTA, an interactive online application was created for conducting meta-analysis of DTA studies. The user interface was designed to be easy to navigate having different tabs for different functions. Features include the ability for users to enter their own data, customise plots, incorporate quality assessment results and quickly conduct sensitivity analyses. All plots produced can be exported as either .png or .pdf files to be included in report documents. All tables can be exported as .csv files.

Conclusions

MetaDTA, is a freely available interactive online application which meta-analyses DTA studies, plots the summary ROC curve, incorporates quality assessment results and allows for sensitivity analyses to be conducted in a timely manner. Due to the rich feature-set and user-friendliness of the software it should appeal to a wide audience including those without specialist statistical knowledge. We encourage others to create similar applications for specialist analysis methods to encourage broader uptake which in-turn could improve research quality.

Amyloid-Negative Dementia in the Elderly is Associated with High Accumulation of Tau in the Temporal Lobes

Background:

We previously reported that among cases clinically diagnosed with Alzheimer’s disease, the proportion of amyloid beta (Aβ) -negative case increases in the elderly population. Tauopathy including Argyrophilic Grain Disease (AGD) and Neurofibrillary Tangle-Predominant Dementia (NFTPD), may be the leading causes of such dementia.

Objective:

To evaluate the involvement of tau, we studied tau accumulation in Amyloid-Negative Dementia Cases in the Elderly (ANDE) with Positron Emission Tomography (PET).

Methods:

Seven cases with slowly progressive dementia who were older than 80 years and were negative for Aβ were studied. In one case, autopsy obtained 2 years after the PET examination revealed neurofibrillary tangles limited around the parahippocampal gyrus. Four cases showed strong laterality in magnetic resonance imaging atrophy (clinical AGD), while the other three cases had no significant laterality in atrophy (clinical NFTPD). Age-corrected PET data of healthy controls (HC; n = 12) were used as control. Tau accumulation was evaluated with [11C]PBB3-PET.

Results:

High accumulation was found in the lateral temporal cortex in ANDE. In autopsy case, scattered neurofibrillary tangles were found in the parahippocampal gyrus. In addition, there was a very high accumulation of PBB3 in the large area of bilateral parietal lobes, although no corresponding tau component was found in the autopsied case.

Conclusion:

Relatively high burden of tau deposition was commonly observed in the lateral temporal cortex and parietal cortex of ANDE, part of which may explain dementia in these subjects. [11C]PBB3 may be useful in detecting tauopathy in ANDE.

Cerebrospinal fluid and blood biomarkers for neurodegenerative dementias: An update of the Consensus of the Task Force on Biological Markers in Psychiatry of the World Federation of Societies of Biological Psychiatry

In the 12 years since the publication of the first Consensus Paper of the WFSBP on biomarkers of neurodegenerative dementias, enormous advancement has taken place in the field, and the Task Force takes now the opportunity to extend and update the original paper. New concepts of Alzheimer's disease (AD) and the conceptual interactions between AD and dementia due to AD were developed, resulting in two sets for diagnostic/research criteria. Procedures for pre-analytical sample handling, biobanking, analyses and post-analytical interpretation of the results were intensively studied and optimised. A global quality control project was introduced to evaluate and monitor the inter-centre variability in measurements with the goal of harmonisation of results. Contexts of use and how to approach candidate biomarkers in biological specimens other than cerebrospinal fluid (CSF), e.g. blood, were precisely defined. Important development was achieved in neuroimaging techniques, including studies comparing amyloid-β positron emission tomography results to fluid-based modalities. Similarly, development in research laboratory technologies, such as ultra-sensitive methods, raises our hopes to further improve analytical and diagnostic accuracy of classic and novel candidate biomarkers. Synergistically, advancement in clinical trials of anti-dementia therapies energises and motivates the efforts to find and optimise the most reliable early diagnostic modalities. Finally, the first studies were published addressing the potential of cost-effectiveness of the biomarkers-based diagnosis of neurodegenerative disorders.

Validity of the QUADAS-2 in Assessing Risk of Bias in Alzheimer's Disease Diagnostic Accuracy Studies

Accurate detection of Alzheimer's disease (AD) is of considerable clinical importance. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) is the current research standard for evaluating the quality of studies that validate diagnostic tests; however, its own construct validity has not yet been evaluated empirically. Our aim was to evaluate how well the proposed QUADAS-2 items and its domains converge to indicate the study quality criteria. This study applies confirmatory factor analysis to determine whether a measurement model would be consistent with meta-analytic data. Cochrane meta-analyses assessing the accuracy of AD diagnostic tests were identified. The seven ordinal QUADAS-2 items, intended to inform study quality based on risk of bias and applicability concerns, were extracted for each of the included studies. The QUADAS-2 pre-specified factor structure (i.e., four domains assessed in terms of risk of bias and applicability concerns) was not testable. An alternative model based on two correlated factors (i.e., risk of bias and applicability concerns) returned a poor fit model. Poor factor loadings were obtained, indicating that we cannot provide evidence that the indicators convergent validity markers in the context of AD diagnostic accuracy metanalyses, where normally the sample size is low (around 60 primary included studies). A Monte Carlo simulation suggested that such a model would require at least 90 primary studies to estimate these parameters with 80% power. The reliability of the QUADAS-2 items to inform a measurement model for study quality remains unconfirmed. Considerations for conceptualizing such a tool are discussed.

Are methodological quality and completeness of reporting associated with citation-based measures of publication impact? A secondary analysis of a systematic review of dementia biomarker studies

OBJECTIVE

To determine whether methodological and reporting quality are associated with surrogate measures of publication impact in the field of dementia biomarker studies.

METHODS

We assessed dementia biomarker studies included in a previous systematic review in terms of methodological and reporting quality using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) and Standards for Reporting of Diagnostic Accuracy (STARD), respectively. We extracted additional study and journal-related data from each publication to account for factors shown to be associated with impact in previous research. We explored associations between potential determinants and measures of publication impact in univariable and stepwise multivariable linear regression analyses.

OUTCOME MEASURES

We aimed to collect data on four measures of publication impact: two traditional measures-average number of citations per year and 5-year impact factor of the publishing journal and two alternative measures-the Altmetric Attention Score and counts of electronic downloads.

RESULTS

The systematic review included 142 studies. Due to limited data, Altmetric Attention Scores and electronic downloads were excluded from the analysis, leaving traditional metrics as the only analysed outcome measures. We found no relationship between QUADAS and traditional metrics. Citation rates were independently associated with 5-year journal impact factor (β=0.42; p<0.001), journal subject area (β=0.39; p<0.001), number of years since publication (β=-0.29; p<0.001) and STARD (β=0.13; p<0.05). Independent determinants of 5-year journal impact factor were citation rates (β=0.45; p<0.001), statement on conflict of interest (β=0.22; p<0.01) and baseline sample size (β=0.15; p<0.05).

CONCLUSIONS

Citation rates and 5-year journal impact factor appear to measure different dimensions of impact. Citation rates were weakly associated with completeness of reporting, while neither traditional metric was related to methodological rigour. Our results suggest that high publication usage and journal outlet is not a guarantee of quality and readers should critically appraise all papers regardless of presumed impact.

Geographical Variation in Dementia Mortality in Italy, New Zealand, and Chile: The Impact of Latitude, Vitamin D, and Air Pollution

BACKGROUND

Dementia risk is reported as being higher in the north compared to the south, which may be related to vitamin D deficiency. If this were the case, an opposite gradient of risk would be observed in the southern hemisphere, but this has not been investigated previously.

METHODS

We calculated standardised mortality ratios (SMRs) for deaths in 2012 where dementia (Alzheimer's disease, vascular or unspecified dementia) was recorded as the underlying cause for 20 regions in Italy, 20 District Health Board areas in New Zealand and 29 Health Service areas in Chile.

RESULTS

Dementia SMRs were higher in northern than central or southern Italy. The inverse pattern was seen in women in New Zealand, with rates higher on South Island than North Island. However, dementia risk was raised in eight regions in the north and centre of Chile in both men and women.

CONCLUSIONS

Geographical variation plays a key role in dementia risk, but patterns vary in men and women. In the northern hemisphere, dementia mortality is higher in the north, but the pattern in the southern hemisphere is more complex.

Fluid and imaging biomarkers for Alzheimer's disease: Where we stand and where to head to

There is increasing evidence that a number of potentially informative biomarkers for Alzheimer disease (AD) can improve the accuracy of diagnosing this form of dementia, especially when used as a panel of diagnostic assays and interpreted in the context of neuroimaging and clinical data. Moreover, by combining the power of CSF biomarkers with neuroimaging techniques to visualize Aβ deposits (or neurodegenerative lesions), it might be possible to better identify individuals at greatest risk for developing MCI and converting to AD. The objective of this article was to review recent progress in selected imaging and chemical biomarkers for prediction, early diagnosis and progression of AD. We present our view point of a scenario that places CSF and imaging markers on the verge of general utility based on accuracy levels that already match (or even surpass) current clinical precision.

Understanding the roles of mutations in the amyloid precursor protein in Alzheimer disease

Many models of disease progression in Alzheimer's disease (AD) have been proposed to help guide experimental design and aid the interpretation of results. Models focussing on the genetic evidence include the amyloid cascade (ACH) and presenilin (PSH) hypotheses and the amyloid precursor protein (APP) matrix approach (AMA), of which the ACH has held a dominant position for over two decades. However, the ACH has never been fully accepted and has not yet delivered on its therapeutic promise. We review the ACH, PSH and AMA in relation to levels of APP proteolytic fragments reported from AD-associated mutations in APP. Different APP mutations have diverse effects on the levels of APP proteolytic fragments. This evidence is consistent with at least three disease pathways that can differ between familial and sporadic AD and two pathways associated with cerebral amyloid angiopathy. We cannot fully evaluate the ACH, PSH and AMA in relation to the effects of mutations in APP as the APP proteolytic system has not been investigated systematically. The confounding effects of sequence homology, complexity of competing cleavages and antibody cross reactivities all illustrate limitations in our understanding of the roles these fragments and the APP proteolytic system as a whole in normal aging and disease play. Current experimental design should be refined to generate clearer evidence, addressing both aging and complex disorders with standardised reporting formats. A more flexible theoretical framework capable of accommodating the complexity of the APP proteolytic system is required to integrate available evidence.

Epidemiology of Dementia: The Burden on Society, the Challenges for Research

Dementia is among the leading causes of death and disability. Due to the ageing population, its prevalence is expected to nearly triple worldwide by 2050, urging the development of preventive and curative interventions. Various modifiable risk factors have been identified in community-based cohort studies, but insight into the underlying pathophysiological mechanisms is lacking. Clinical trials have thus far failed in the development of disease-modifying therapy in patients with dementia, thereby triggering a shift of focus toward the presymptomatic phase of disease. The extensive preclinical disease course of Alzheimer's disease warrants reliable, easily obtainable biomarkers to aid in timely application of preventive strategies, selecting participants for neuroprotective trials, and disease monitoring in trials and clinical practice. Biomarker and drug discovery may yield the fruits from technology-driven developments in the field of genomics, epigenetics, metabolomics, and brain imaging. In that context, bridging the gap between translational and population research may well prove a giant leap toward development of successful preventive and curative interventions against dementia.

Reproducibility of Alzheimer's Disease Cerebrospinal Fluid-Biomarker Measurements under Clinical Routine Conditions

Analysis of cerebrospinal fluid (CSF) is one of the key tools for the state-of-the-art differential diagnosis of dementias. Dementia due to Alzheimer's disease (AD) is characterized by elevated CSF levels of total Tau (tTau) and phospho-181-Tau (pTau) and low CSF amyloid-β42 (Aβ42). Discrepancies in the laboratory analysis of human materials are well known and much effort has been put into harmonization procedures. In this study, we measured CSF biomarkers of more than 100 patients obtained under clinical routine conditions in two different clinical laboratories. The CSF biomarker levels obtained from the two different sites were significantly correlated: R2 = 0.7129 (tTau, p < 0.001), 0.7914 (pTau, p < 0.001), 0.5078 (Aβ42, p < 0.001), 0.5739 (Aβ40, p < 0.001), and 0.4308 (Aβ42/40, p < 0.001). However, the diagnostic classifications of the Aβ42, tTau, and pTau levels of identical subjects into normal versus pathological range made by the two different sites showed substantial discrepancies (31.5%, 29.6%, and 25.0% discordant cases, respectively). Applying Aβ42/40, instead of CSF Aβ42 alone, lead to a reduction of the discordant cases to 16.8%. Our findings suggest that CSF Aβ42/40 can outperform Aβ42 as a biomarker for AD neuropathology, not only under well-controlled study conditions but also in real life clinical routine. Thus, we recommend the inclusion of Aβ42/40 as a CSF biomarker in the diagnostic procedure.

18F PET with florbetapir for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI)

BACKGROUND

¹⁸F-florbetapir uptake by brain tissue measured by positron emission tomography (PET) is accepted by regulatory agencies like the Food and Drug Administration (FDA) and the European Medicine Agencies (EMA) for assessing amyloid load in people with dementia. Its added value is mainly demonstrated by excluding Alzheimer's pathology in an established dementia diagnosis. However, the National Institute on Aging and Alzheimer's Association (NIA-AA) revised the diagnostic criteria for Alzheimer's disease and confidence in the diagnosis of mild cognitive impairment (MCI) due to Alzheimer's disease may be increased when using amyloid biomarkers tests like ¹⁸F-florbetapir. These tests, added to the MCI core clinical criteria, might increase the diagnostic test accuracy (DTA) of a testing strategy. However, the DTA of ¹⁸F-florbetapir to predict the progression from MCI to Alzheimer's disease dementia (ADD) or other dementias has not yet been systematically evaluated.

OBJECTIVES

To determine the DTA of the ¹⁸F-florbetapir PET scan for detecting people with MCI at time of performing the test who will clinically progress to ADD, other forms of dementia (non-ADD), or any form of dementia at follow-up.

SEARCH METHODS

This review is current to May 2017. We searched MEDLINE (OvidSP), Embase (OvidSP), PsycINFO (OvidSP), BIOSIS Citation Index (Thomson Reuters Web of Science), Web of Science Core Collection, including the Science Citation Index (Thomson Reuters Web of Science) and the Conference Proceedings Citation Index (Thomson Reuters Web of Science), LILACS (BIREME), CINAHL (EBSCOhost), ClinicalTrials.gov (https://clinicaltrials.gov), and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) (http://www.who.int/ictrp/search/en/). We also searched ALOIS, the Cochrane Dementia & Cognitive Improvement Group's specialised register of dementia studies (http://www.medicine.ox.ac.uk/alois/). We checked the reference lists of any relevant studies and systematic reviews, and performed citation tracking using the Science Citation Index to identify any additional relevant studies. No language or date restrictions were applied to the electronic searches.

SELECTION CRITERIA

We included studies that had prospectively defined cohorts with any accepted definition of MCI at time of performing the test and the use of ¹⁸F-florbetapir scan to evaluate the DTA of the progression from MCI to ADD or other forms of dementia. In addition, we only selected studies that applied a reference standard for Alzheimer's dementia diagnosis, for example, National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) or Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) criteria.

DATA COLLECTION AND ANALYSIS

We screened all titles and abstracts identified in electronic-database searches. Two review authors independently selected studies for inclusion and extracted data to create two-by-two tables, showing the binary test results cross-classified with the binary reference standard. We used these data to calculate sensitivities, specificities, and their 95% confidence intervals. Two independent assessors performed quality assessment using the QUADAS-2 tool plus some additional items to assess the methodological quality of the included studies.

MAIN RESULTS

We included three studies, two of which evaluated the progression from MCI to ADD, and one evaluated the progression from MCI to any form of dementia.Progression from MCI to ADD was evaluated in 448 participants. The studies reported data on 401 participants with 1.6 years of follow-up and in 47 participants with three years of follow-up. Sixty-one (15.2%) participants converted at 1.6 years follow-up; nine (19.1%) participants converted at three years of follow-up.Progression from MCI to any form of dementia was evaluated in five participants with 1.5 years of follow-up, with three (60%) participants converting to any form of dementia.There were concerns regarding applicability in the reference standard in all three studies. Regarding the domain of flow and timing, two studies were considered at high risk of bias. MCI to ADD;Progression from MCI to ADD in those with a follow-up between two to less than four years had a sensitivity of 67% (95% CI 30 to 93) and a specificity of 71% (95% CI 54 to 85) by visual assessment (n = 47, 1 study).Progression from MCI to ADD in those with a follow-up between one to less than two years had a sensitivity of 89% (95% CI 78 to 95) and a specificity of 58% (95% CI 53 to 64) by visual assessment, and a sensitivity of 87% (95% CI 76 to 94) and a specificity of 51% (95% CI 45 to 56) by quantitative assessment by the standardised uptake value ratio (SUVR)(n = 401, 1 study). MCI to any form of dementia;Progression from MCI to any form of dementia in those with a follow-up between one to less than two years had a sensitivity of 67% (95% CI 9 to 99) and a specificity of 50% (95% CI 1 to 99) by visual assessment (n = 5, 1 study). MCI to any other forms of dementia (non-ADD);There was no information regarding the progression from MCI to any other form of dementia (non-ADD).

AUTHORS' CONCLUSIONS

Although sensitivity was good in one included study, considering the poor specificity and the limited data available in the literature, we cannot recommend routine use of ¹⁸F-florbetapir PET in clinical practice to predict the progression from MCI to ADD.Because of the poor sensitivity and specificity, limited number of included participants, and the limited data available in the literature, we cannot recommend its routine use in clinical practice to predict the progression from MCI to any form of dementia.Because of the high financial costs of ¹⁸F-florbetapir, clearly demonstrating the DTA and standardising the process of this modality are important prior to its wider use.

18F PET with flutemetamol for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI)

BACKGROUND

¹⁸F-flutemetamol uptake by brain tissue, measured by positron emission tomography (PET), is accepted by regulatory agencies like the Food and Drug Administration (FDA) and the European Medicine Agencies (EMA) for assessing amyloid load in people with dementia. Its added value is mainly demonstrated by excluding Alzheimer's pathology in an established dementia diagnosis. However, the National Institute on Aging and Alzheimer's Association (NIA-AA) revised the diagnostic criteria for Alzheimer's disease and the confidence in the diagnosis of mild cognitive impairment (MCI) due to Alzheimer's disease may be increased when using some amyloid biomarkers tests like ¹⁸F-flutemetamol. These tests, added to the MCI core clinical criteria, might increase the diagnostic test accuracy (DTA) of a testing strategy. However, the DTA of ¹⁸F-flutemetamol to predict the progression from MCI to Alzheimer's disease dementia (ADD) or other dementias has not yet been systematically evaluated.

OBJECTIVES

To determine the DTA of the ¹⁸F-flutemetamol PET scan for detecting people with MCI at time of performing the test who will clinically progress to ADD, other forms of dementia (non-ADD) or any form of dementia at follow-up.

SEARCH METHODS

The most recent search for this review was performed in May 2017. We searched MEDLINE (OvidSP), Embase (OvidSP), PsycINFO (OvidSP), BIOSIS Citation Index (Thomson Reuters Web of Science), Web of Science Core Collection, including the Science Citation Index (Thomson Reuters Web of Science) and the Conference Proceedings Citation Index (Thomson Reuters Web of Science), LILACS (BIREME), CINAHL (EBSCOhost), ClinicalTrials.gov (https://clinicaltrials.gov), and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) (http://www.who.int/ictrp/search/en/). We also searched ALOIS, the Cochrane Dementia & Cognitive Improvement Group's specialised register of dementia studies (http://www.medicine.ox.ac.uk/alois/). We checked the reference lists of any relevant studies and systematic reviews, and performed citation tracking using the Science Citation Index to identify any additional relevant studies. No language or date restrictions were applied to the electronic searches.

SELECTION CRITERIA

We included studies that had prospectively defined cohorts with any accepted definition of MCI at time of performing the test and the use of ¹⁸F-flutemetamol scan to evaluate the DTA of the progression from MCI to ADD or other forms of dementia. In addition, we only selected studies that applied a reference standard for Alzheimer's dementia diagnosis, for example, National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) or Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) criteria.

DATA COLLECTION AND ANALYSIS

We screened all titles and abstracts identified in electronic-database searches. Two review authors independently selected studies for inclusion and extracted data to create two-by-two tables, showing the binary test results cross-classified with the binary reference standard. We used these data to calculate sensitivities, specificities, and their 95% confidence intervals. Two independent assessors performed quality assessment using the QUADAS-2 tool plus some additional items to assess the methodological quality of the included studies.

MAIN RESULTS

Progression from MCI to ADD was evaluated in 243 participants from two studies. The studies reported data on 19 participants with two years of follow-up and on 224 participants with three years of follow-up. Nine (47.4%) participants converted at two years follow-up and 81 (36.2%) converted at three years of follow-up.There were concerns about participant selection and sampling in both studies. The index test domain in one study was considered unclear and in the second study it was considered at low risk of bias. For the reference standard domain, one study was considered at low risk and the second study was considered to have an unclear risk of bias. Regarding the domains of flow and timing, both studies were considered at high risk of bias. MCI to ADD;Progression from MCI to ADD at two years of follow-up had a sensitivity of 89% (95% CI 52 to 100) and a specificity of 80% (95% CI 44 to 97) by quantitative assessment by SUVR (n = 19, 1 study).Progression from MCI to ADD at three years of follow-up had a sensitivity of 64% (95% CI 53 to 75) and a specificity of 69% (95% CI 60 to 76) by visual assessment (n = 224, 1 study).There was no information regarding the other two objectives in this systematic review (SR): progression from MCI to other forms of dementia and progression to any form of dementia at follow-up.

AUTHORS' CONCLUSIONS

Due to the varying sensitivity and specificity for predicting the progression from MCI to ADD and the limited data available, we cannot recommend routine use of ¹⁸F-flutemetamol in clinical practice. ¹⁸F-flutemetamol has high financial costs; therefore, clearly demonstrating its DTA and standardising the process of the ¹⁸F-flutemetamol modality is important prior to its wider use.

18F PET with florbetaben for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI)

BACKGROUND

18F-florbetaben uptake by brain tissue, measured by positron emission tomography (PET), is accepted by regulatory agencies like the Food and Drug Administration (FDA) and the European Medicine Agencies (EMA) for assessing amyloid load in people with dementia. Its added value is mainly demonstrated by excluding Alzheimer's pathology in an established dementia diagnosis. However, the National Institute on Aging and Alzheimer's Association (NIA-AA) revised the diagnostic criteria for Alzheimer's disease and confidence in the diagnosis of mild cognitive impairment (MCI) due to Alzheimer's disease may be increased when using some amyloid biomarkers tests like 18F-florbetaben. These tests, added to the MCI core clinical criteria, might increase the diagnostic test accuracy (DTA) of a testing strategy. However, the DTA of 18F-florbetaben to predict the progression from MCI to Alzheimer's disease dementia (ADD) or other dementias has not yet been systematically evaluated.

OBJECTIVES

To determine the DTA of the 18F-florbetaben PET scan for detecting people with MCI at time of performing the test who will clinically progress to ADD, other forms of dementia (non-ADD), or any form of dementia at follow-up.

SEARCH METHODS

The most recent search for this review was performed in May 2017. We searched MEDLINE (OvidSP), Embase (OvidSP), PsycINFO (OvidSP), BIOSIS Citation Index (Thomson Reuters Web of Science), Web of Science Core Collection, including the Science Citation Index (Thomson Reuters Web of Science) and the Conference Proceedings Citation Index (Thomson Reuters Web of Science), LILACS (BIREME), CINAHL (EBSCOhost), ClinicalTrials.gov (https://clinicaltrials.gov), and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) (http://www.who.int/ictrp/search/en/). We also searched ALOIS, the Cochrane Dementia & Cognitive Improvement Group's specialised register of dementia studies (http://www.medicine.ox.ac.uk/alois/). We checked the reference lists of any relevant studies and systematic reviews, and performed citation tracking using the Science Citation Index to identify any additional relevant studies. No language or date restrictions were applied to electronic searches.

SELECTION CRITERIA

We included studies that had prospectively defined cohorts with any accepted definition of MCI at time of performing the test and the use of 18F-florbetaben scan to evaluate the DTA of the progression from MCI to ADD or other forms of dementia. In addition, we only selected studies that applied a reference standard for Alzheimer's dementia diagnosis, for example, the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) or Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) criteria.

DATA COLLECTION AND ANALYSIS

We screened all titles and abstracts identified in electronic-database searches. Two review authors independently selected studies for inclusion and extracted data to create two-by-two tables, showing the binary test results cross-classified with the binary reference standard. We used these data to calculate sensitivities, specificities, and their 95% confidence intervals. Two independent assessors performed quality assessment using the QUADAS-2 tool plus some additional items to assess the methodological quality of the included studies.

MAIN RESULTS

Progression from MCI to ADD, any other form of dementia, and any form of dementia was evaluated in one study (Ong 2015). It reported data on 45 participants at four years of follow-up; 21 participants met NINCDS-ADRDA criteria for Alzheimer's disease dementia at four years of follow-up, the proportion converting to ADD was 47% of the 45 participants, and 11% of the 45 participants met criteria for other types of dementias (three cases of FrontoTemporal Dementia (FTD), one of Dementia with Lewy body (DLB), and one of Progressive Supranuclear Palsy (PSP)). We considered the study to be at high risk of bias in the domains of the reference standard, flow, and timing (QUADAS-2). MCI to ADD; 18F-florbetaben PET scan analysed visually: the sensitivity was 100% (95% confidence interval (CI) 84% to 100%) and the specificity was 83% (95% CI 63% to 98%) (n = 45, 1 study). Analysed quantitatively: the sensitivity was 100% (95% CI 84% to 100%) and the specificity was 88% (95% CI 68% to 97%) for the diagnosis of ADD at follow-up (n = 45, 1 study). MCI to any other form of dementia (non-ADD); 18F-florbetaben PET scan analysed visually: the sensitivity was 0% (95% CI 0% to 52%) and the specificity was 38% (95% CI 23% to 54%) (n = 45, 1 study). Analysed quantitatively: the sensitivity was 0% (95% CI 0% to 52%) and the specificity was 40% (95% CI 25% to 57%) for the diagnosis of any other form of dementia at follow-up (n = 45, 1 study). MCI to any form of dementia;18F-florbetaben PET scan analysed visually: the sensitivity was 81% (95% CI 61% to 93%) and the specificity was 79% (95% CI 54% to 94%) (n = 45, 1 study). Analysed quantitatively: the sensitivity was 81% (95% CI 61% to 93%) and the specificity was 84% (95% CI 60% to 97%) for the diagnosis of any form of dementia at follow-up (n = 45, 1 study).

AUTHORS' CONCLUSIONS

Although we were able to calculate one estimation of DTA in, especially, the prediction of progression from MCI to ADD at four years follow-up, the small number of participants implies imprecision of sensitivity and specificity estimates. We cannot make any recommendation regarding the routine use of 18F-florbetaben in clinical practice based on one single study with 45 participants. 18F-florbetaben has high financial costs, therefore, clearly demonstrating its DTA and standardising the process of the 18F-florbetaben modality are important prior to its wider use.

Tau Protein in Oral Mucosa and Cognitive State: A Cross-sectional Study

Neurodegenerative diseases are characterized by the presence of abnormal aggregates of proteins in brain tissue. Among them, the presence of aggregates of phosphorylated Tau protein (p-Tau) is the hallmark of Alzheimer’s disease (AD) and other major neurodegenerative disorders such as corticobasal degeneration and frontotemporal dementia among others. Although Tau protein has previously been assumed to be exclusive to the central nervous system, it is also found in peripheral tissues. The purpose of this study was to determine whether there is a differential Tau expression in oral mucosa cells according to cognitive impairment. Eighty-one subjects were enrolled in the study and classified per Mini-Mental State Examination test score into control, mild cognitive impairment (MCI), and severe cognitive impairment (SCI) groups. Immunocytochemistry and immunofluorescence revealed the presence of Tau and four p-Tau forms in the cytoplasm and nucleus of oral mucosa cells. More positivity was present in subjects with cognitive impairment than in control subjects, both in the nucleus and cytoplasm, in a speckle pattern. The mRNA expression of Tau by quantitative real-time polymerase chain reaction was higher in SCI as compared with the control group (P < 0.01). A significantly higher percentage of immunopositive cells in the SCI group was found via flow cytometry in comparison to controls and the MCI group (P < 0.01). These findings demonstrate the higher presence of p-Tau and Tau transcript in the oral mucosa of cognitively impaired subjects when compared with healthy subjects. The feasibility of p-Tau quantification by flow cytometry supports the prospective analysis of oral mucosa as a support tool for screening of proteinopathies in cognitively impaired patients.

The Edinburgh Consensus: preparing for the advent of disease-modifying therapies for Alzheimer's disease

CONTEXT

This commentary discusses the implications of disease-modifying treatments for Alzheimer's disease which seem likely to appear in the next few years and results from a meeting of British experts in neurodegenerative diseases in Edinburgh. The availability of such treatments would help change public and professional attitudes and accelerate engagement with the prodromal and preclinical populations who might benefit from them. However, this would require an updated understanding of Alzheimer's disease, namely the important distinction between Alzheimer's disease and Alzheimer's dementia.

CONSENSUS

Since treatments are likely to be most effective in the early stages, identification of clinically relevant brain changes (for example, amyloid burden using imaging or cerebrospinal fluid biomarkers) will be crucial. While current biomarkers could be useful in identifying eligibility for new therapies, trial data are not available to aid decisions about stopping or continuing treatment in clinical practice. Therefore, effective monitoring of safety and effectiveness when these treatments are introduced into clinical practice will be necessary to inform wide-scale use. Equity of access is key but there is a tension between universal access for everyone with a diagnosis of Alzheimer's disease and specifying an eligible population most likely to respond. We propose the resources necessary for an optimal care pathway as well as the necessary education and training for primary and secondary care.

CONCLUSION

The majority of current services in the UK and elsewhere would not be able to accommodate the specialist investigations required to select patients and prescribe these therapies. Therefore, a stepped approach would be necessary: from innovating sentinel clinical-academic centres that already have capacity to deliver the necessary phase IV trials, through early adoption in a hub and spoke model, to nationwide adoption for true equity of access. The optimism generated by recent and anticipated developments in the understanding and treatment of Alzheimer's disease presents a great opportunity to innovate and adapt our services to incorporate the next exciting development in the field of dementia.

Olfactory Dysfunction Predicts Subsequent Dementia in Older U.S. Adults

OBJECTIVES

To investigate the relationship between olfactory dysfunction and subsequent diagnosis of dementia.

DESIGN

Longitudinal study of a population representative of U.S. older adults.

SETTING

Home interviews (National Social Life, Health, and Aging Project).

PARTICIPANTS

Men and women aged 57 to 85 (N = 2,906).

MEASUREMENTS

Objective odor identification ability was measured at baseline using a validated five-item test. Five years later, the respondent, or a proxy if the respondent was too sick to interview or had died, reported physician diagnosis of dementia. The association between baseline olfactory dysfunction and an interval dementia diagnosis was tested using multivariate logistic regression, controlling for age, sex, race and ethnicity, education, comorbidities (modified Charlson Comorbidity Index), and cognition at baseline (Short Portable Mental Status Questionnaire).

RESULTS

Older adults with olfactory dysfunction had more than twice the odds of having developed dementia 5 years later (odds ratio = 2.13, 95% confidence interval = 1.32-3.43), controlling for the above covariates. Having more odor identification errors was associated with greater probability of an interval dementia diagnosis (P = .04, 1-degree of freedom linear-trend test).

CONCLUSION

We show for the first time in a nationally representative sample that home-dwelling older adults with normal cognition and difficulty identifying odors face higher odds of being diagnosed with dementia 5 years later, independent of other significant risk factors. This validated five-item odor identification test is an efficient, low-cost component of the physical examination that can provide useful information while assessing individuals' risk of dementia. Use of such testing may provide an opportunity for early interventions to reduce the attendant morbidity and public health burden of dementia.

Diagnosis in vascular dementia, applying 'Cochrane diagnosis rules' to 'dementia diagnostic tools'

In this issue of Clinical Science, Biesbroek and colleagues describe recent work on magnetic resonance imaging (MRI)-based cerebral lesion location and its association with cognitive decline. The authors conclude that diagnostic neuroimaging in dementia should shift from whole-brain evaluation to focused quantitative analysis of strategic brain areas. This commentary uses the review of lesion location mapping to discuss broader issues around studies of dementia test strategies. We draw upon work completed by the Cochrane Dementia and Cognitive Improvement Group designed to improve design, conduct and reporting of dementia biomarker studies.

A multivariate predictive modeling approach reveals a novel CSF peptide signature for both Alzheimer's Disease state classification and for predicting future disease progression

To determine if a multi-analyte cerebrospinal fluid (CSF) peptide signature can be used to differentiate Alzheimer’s Disease (AD) and normal aged controls (NL), and to determine if this signature can also predict progression from mild cognitive impairment (MCI) to AD, analysis of CSF samples was done on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. The profiles of 320 peptides from baseline CSF samples of 287 subjects over a 3–6 year period were analyzed. As expected, the peptide most able to differentiate between AD vs. NL was found to be Apolipoprotein E. Other peptides, some of which are not classically associated with AD, such as heart fatty acid binding protein, and the neuronal pentraxin receptor, also differentiated disease states. A sixteen-analyte signature was identified which differentiated AD vs. NL with an area under the receiver operating characteristic curve of 0.89, which was better than any combination of amyloid beta (1–42), tau, and phospho-181 tau. This same signature, when applied to a new and independent data set, also strongly predicted both probability and rate of future progression of MCI subjects to AD, better than traditional markers. These data suggest that multivariate peptide signatures from CSF predict MCI to AD progression, and point to potentially new roles for certain proteins not typically associated with AD.

Comparison of the Quick Mild Cognitive Impairment (Qmci) screen to the Montreal Cognitive Assessment (MoCA) in an Australian geriatrics clinic

INTRODUCTION

The Montreal Cognitive Assessment (MoCA) accurately differentiates mild cognitive impairment (MCI) from mild dementia and normal controls (NC). While the MoCA is validated in multiple clinical settings, few studies compare it with similar tests also designed to detect MCI. We sought to investigate how the shorter Quick Mild Cognitive Impairment (Qmci) screen compares with the MoCA.

METHODS

Consecutive referrals presenting with cognitive complaints to a teaching hospital geriatric clinic (Fremantle, Western Australia) underwent a comprehensive assessment and were classified as MCI (n = 72) or dementia (n = 109). NC (n = 41) were a sample of convenience. The Qmci and MoCA were scored by trained geriatricians, in random order, blind to the diagnosis.

RESULTS

Median Qmci scores for NC, MCI and dementia were 69 (+/-19), 52.5 (+/-12) and 36 (+/-14), respectively, compared with 27 (+/-5), 22 (+/-4) and 15 (+/-7) for the MoCA. The Qmci more accurately identified cognitive impairment (MCI or dementia), area under the curve (AUC) 0.97, than the MoCA (AUC 0.92), p = 0.04. The Qmci was non-significantly more accurate in distinguishing MCI from controls (AUC 0.91 vs 0.84, respectively = 0.16). Both instruments had similar accuracy for differentiating MCI from dementia (AUC of 0.91 vs 0.88, p = 0.35). At the optimal cut-offs, calculated from receiver operating characteristic curves, the Qmci (≤57) had a sensitivity of 91% and specificity of 93% for cognitive impairment, compared with 87% sensitivity and 80% specificity for the MoCA (≤23).

CONCLUSION

While both instruments are accurate in detecting MCI, the Qmci is shorter and arguably easier to complete, suggesting that it is a useful instrument in an Australian geriatric outpatient population. Copyright © 2016 John Wiley & Sons, Ltd.

CSF tau and the CSF tau/ABeta ratio for the diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI)

BACKGROUND

Research suggests that measurable change in cerebrospinal fluid (CSF) biomarkers occurs years in advance of the onset of clinical symptoms (Beckett 2010). In this review, we aimed to assess the ability of CSF tau biomarkers (t-tau and p-tau) and the CSF tau (t-tau or p-tau)/ABeta ratio to enable the detection of Alzheimer's disease pathology in patients with mild cognitive impairment (MCI). These biomarkers have been proposed as important in new criteria for Alzheimer's disease dementia that incorporate biomarker abnormalities.

OBJECTIVES

To determine the diagnostic accuracy of 1) CSF t-tau, 2) CSF p-tau, 3) the CSF t-tau/ABeta ratio and 4) the CSF p-tau/ABeta ratio index tests for detecting people with MCI at baseline who would clinically convert to Alzheimer's disease dementia or other forms of dementia at follow-up.

SEARCH METHODS

The most recent search for this review was performed in January 2013. We searched MEDLINE (OvidSP), Embase (OvidSP), BIOSIS Previews (Thomson Reuters Web of Science), Web of Science Core Collection, including Conference Proceedings Citation Index (Thomson Reuters Web of Science), PsycINFO (OvidSP), and LILACS (BIREME). We searched specialized sources of diagnostic test accuracy studies and reviews. We checked reference lists of relevant studies and reviews for additional studies. We contacted researchers for possible relevant but unpublished data. We did not apply any language or data restriction to the electronic searches. We did not use any methodological filters as a method to restrict the search overall.

SELECTION CRITERIA

We selected those studies that had prospectively well-defined cohorts with any accepted definition of MCI and with CSF t-tau or p-tau and CSF tau (t-tau or p-tau)/ABeta ratio values, documented at or around the time the MCI diagnosis was made. We also included studies which looked at data from those cohorts retrospectively, and which contained sufficient data to construct two by two tables expressing those biomarker results by disease status. Moreover, studies were only selected if they applied a reference standard for Alzheimer's disease dementia diagnosis, for example, the NINCDS-ADRDA or Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria.

DATA COLLECTION AND ANALYSIS

We screened all titles generated by the electronic database searches. Two review authors independently assessed the abstracts of all potentially relevant studies, and the full papers for eligibility. Two independent assessors performed data extraction and quality assessment. Where data allowed, we derived estimates of sensitivity at fixed values of specificity from the model we fitted to produce the summary receiver operating characteristic (ROC) curve.

MAIN RESULTS

In total, 1282 participants with MCI at baseline were identified in the 15 included studies of which 1172 had analysable data; 430 participants converted to Alzheimer's disease dementia and 130 participants to other forms of dementia. Follow-up ranged from less than one year to over four years for some participants, but in the majority of studies was in the range one to three years. Conversion to Alzheimer's disease dementia The accuracy of the CSF t-tau was evaluated in seven studies (291 cases and 418 non-cases).The sensitivity values ranged from 51% to 90% while the specificity values ranged from 48% to 88%. At the median specificity of 72%, the estimated sensitivity was 75% (95% CI 67 to 85), the positive likelihood ratio was 2.72 (95% CI 2.43 to 3.04), and the negative likelihood ratio was 0.32 (95% CI 0.22 to 0.47).Six studies (164 cases and 328 non-cases) evaluated the accuracy of the CSF p-tau. The sensitivities were between 40% and 100% while the specificities were between 22% and 86%. At the median specificity of 47.5%, the estimated sensitivity was 81% (95% CI: 64 to 91), the positive likelihood ratio was 1.55 (CI 1.31 to 1.84), and the negative likelihood ratio was 0.39 (CI: 0.19 to 0.82).Five studies (140 cases and 293 non-cases) evaluated the accuracy of the CSF p-tau/ABeta ratio. The sensitivities were between 80% and 96% while the specificities were between 33% and 95%. We did not conduct a meta-analysis because the studies were few and small. Only one study reported the accuracy of CSF t-tau/ABeta ratio.Our findings are based on studies with poor reporting. A significant number of studies had unclear risk of bias for the reference standard, participant selection and flow and timing domains. According to the assessment of index test domain, eight of 15 studies were of poor methodological quality.The accuracy of these CSF biomarkers for 'other dementias' had not been investigated in the included primary studies. Investigation of heterogeneity The main sources of heterogeneity were thought likely to be reference standards used for the target disorders, sources of recruitment, participant sampling, index test methodology and aspects of study quality (particularly, inadequate blinding).We were not able to formally assess the effect of each potential source of heterogeneity as planned, due to the small number of studies available to be included.

AUTHORS' CONCLUSIONS

The insufficiency and heterogeneity of research to date primarily leads to a state of uncertainty regarding the value of CSF testing of t-tau, p-tau or p-tau/ABeta ratio for the diagnosis of Alzheimer's disease in current clinical practice. Particular attention should be paid to the risk of misdiagnosis and overdiagnosis of dementia (and therefore over-treatment) in clinical practice. These tests, like other biomarker tests which have been subject to Cochrane DTA reviews, appear to have better sensitivity than specificity and therefore might have greater utility in ruling out Alzheimer's disease as the aetiology to the individual's evident cognitive impairment, as opposed to ruling it in. The heterogeneity observed in the few studies awaiting classification suggests our initial summary will remain valid. However, these tests may have limited clinical value until uncertainties have been addressed. Future studies with more uniformed approaches to thresholds, analysis and study conduct may provide a more homogenous estimate than the one that has been available from the included studies we have identified.