MRI and cerebrospinal fluid biomarkers for predicting progression to Alzheimer's disease in patients with mild cognitive impairment: a diagnostic accuracy study

Controversial Past, Splendid Present, Unpredictable Future: A Brief Review of Alzheimer Disease History

Background: The concept of Alzheimer disease (AD)-since its histological discovery by Alzheimer to the present day-has undergone substantial modifications. Methods: We conducted a classical narrative review of this field with a bibliography selection (giving preference to Medline best match). Results: The following subjects are reviewed and discussed: Alzheimer's discovery, Kraepelin's creation of a new disease that was a rare condition until the 1970's, the growing interest and investment in AD as a major killer in a society with a large elderly population in the second half of the 20th century, the consolidation of the AD clinicopathological model, and the modern AD nosology based on the dominant amyloid hypothesis among many others. In the 21st century, the development of AD biomarkers has supported a novel biological definition of AD, although the proposed therapies have failed to cure this disease. The incidence of dementia/AD has shown a decrease in affluent countries (possibly due to control of risk factors), and mixed dementia has been established as the most frequent etiology in the oldest old. Conclusions: The current concept of AD lacks unanimity. Many hypotheses attempt to explain its complex physiopathology entwined with aging, and the dominant amyloid cascade has yielded poor therapeutic results. The reduction in the incidence of dementia/AD appears promising but it should be confirmed in the future. A reevaluation of the AD concept is also necessary.

Validation of the "Perceptions Regarding pRE-Symptomatic Alzheimer's Disease Screening" (PRE-ADS) Questionnaire in the German Population: Attitudes, Motivations, and Barriers to Pre-Symptomatic Dementia Screening

BACKGROUND

Attitudes, motivations, and barriers to pre-symptomatic screening for Alzheimer's disease (AD) in the general population are unclear, and validated measurement tools are lacking.

OBJECTIVE

Translation and validation of the German version of the "Perceptions regarding pRE-symptomatic Alzheimer's Disease Screening" (PRE-ADS) questionnaire.

METHODS

A convenience sample (N = 256) was recruited via an online platform. Validation of the PRE-ADS-D consisted of assessments of reliability, structural validity using Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) and construct validity using known-group tests. A subscale "Acceptability of Screening", with 5 PRE-ADS-D items, was extracted to measure acceptance of screening in clinical practice. The STROBE checklist was used for reporting.

RESULTS

EFA revealed a three-factor model for the PRE-ADS-D. Acceptable to good internal consistency was found for the 25-item scale (α= 0.78), as well as for the three factors "Concerns about Screening" (α= 0.85), "Intention to be Screened" (α= 0.87), and "Preventive Health Behaviors" (α= 0.81). Construct validity was confirmed for both the 25-item PRE-ADS-D and the "Acceptability of Screening" scale (α= 0.91). Overall, 51.2% of the participants showed a preference for screening. Non-parametric tests were conducted to further explore group differences of the sample.

CONCLUSIONS

The PRE-ADS-D is a reliable and valid tool to measure attitudes, motives, and barriers regarding pre-symptomatic dementia screening in the German-speaking general population. Additionally, the subscale "Acceptability of Screening" demonstrated good construct validity and reliability, suggesting its promising potential as a practical tool in clinical practice.

Amyloid Pathology Modulates the Associations of Neuropsychiatric Symptoms with Cognitive Impairments and Neurodegeneration in Non-Demented Elderly

BACKGROUND

The associations between neuropsychiatric symptoms (NPSs) and Alzheimer's disease (AD) have been well-studied, yet gaps remain.

OBJECTIVE

We aimed to examine the associations of four subsyndromes (hyperactivity, psychosis, affective symptoms, and apathy) of NPSs with cognition, neurodegeneration, and AD pathologies.

METHODS

Totally 1,040 non-demented elderly (48.07% males) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were included. We assessed the relationships between NPSs and AD neuropathologies, cognition, neurodegeneration, and clinical correlates in cross-sectional and longitudinal via multiple linear regression, linear mixed effects, and Cox proportional hazard models. Causal mediation analyses were conducted to explore the mediation effects of AD pathologies on cognition and neurodegeneration.

RESULTS

We found that individuals with hyperactivity, psychosis, affective symptoms, or apathy displayed a poorer cognitive status, a lower CSF amyloid-β (Aβ) level and a higher risk of clinical conversion (p < 0.05). Hyperactivity and affective symptoms were associated with increasing cerebral Aβ deposition (p < 0.05). Except psychosis, the other three subsyndromes accompanied with faster atrophy of hippocampal volume (p < 0.05). Specific NPSs were predominantly associated with different cognitive domains decline through an 8-year follow-up (p < 0.05). Moreover, the relationships between NPSs and cognitive decline, neurodegeneration might be associated with Aβ, the mediation percentage varied from 6.05% to 17.51% (p < 0.05).

CONCLUSIONS

NPSs could be strongly associated with AD. The influences of NPSs on cognitive impairments, neurodegeneration might be partially associated with Aβ.

Developing Early Markers of Cognitive Decline and Dementia Derived From Survey Response Behaviors: Protocol for Analyses of Preexisting Large-scale Longitudinal Data

BACKGROUND

Accumulating evidence shows that subtle alterations in daily functioning are among the earliest and strongest signals that predict cognitive decline and dementia. A survey is a small slice of everyday functioning; nevertheless, completing a survey is a complex and cognitively demanding task that requires attention, working memory, executive functioning, and short- and long-term memory. Examining older people's survey response behaviors, which focus on how respondents complete surveys irrespective of the content being sought by the questions, may represent a valuable but often neglected resource that can be leveraged to develop behavior-based early markers of cognitive decline and dementia that are cost-effective, unobtrusive, and scalable for use in large population samples.

OBJECTIVE

This paper describes the protocol of a multiyear research project funded by the US National Institute on Aging to develop early markers of cognitive decline and dementia derived from survey response behaviors at older ages.

METHODS

Two types of indices summarizing different aspects of older adults' survey response behaviors are created. Indices of subtle reporting mistakes are derived from questionnaire answer patterns in a number of population-based longitudinal aging studies. In parallel, para-data indices are generated from computer use behaviors recorded on the backend server of a large web-based panel study known as the Understanding America Study (UAS). In-depth examinations of the properties of the created questionnaire answer pattern and para-data indices will be conducted for the purpose of evaluating their concurrent validity, sensitivity to change, and predictive validity. We will synthesize the indices using individual participant data meta-analysis and conduct feature selection to identify the optimal combination of indices for predicting cognitive decline and dementia.

RESULTS

As of October 2022, we have identified 15 longitudinal ageing studies as eligible data sources for creating questionnaire answer pattern indices and obtained para-data from 15 UAS surveys that were fielded from mid-2014 to 2015. A total of 20 questionnaire answer pattern indices and 20 para-data indices have also been identified. We have conducted a preliminary investigation to test the utility of the questionnaire answer patterns and para-data indices for the prediction of cognitive decline and dementia. These early results are based on only a subset of indices but are suggestive of the findings that we anticipate will emerge from the planned analyses of multiple behavioral indices derived from many diverse studies.

CONCLUSIONS

Survey response behaviors are a relatively inexpensive data source, but they are seldom used directly for epidemiological research on cognitive impairment at older ages. This study is anticipated to develop an innovative yet unconventional approach that may complement existing approaches aimed at the early detection of cognitive decline and dementia.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/44627.

Predicting conversion from mild cognitive impairment to Alzheimer's disease with multimodal latent factors

INTRODUCTION

We studied the ability of latent factor scores to predict conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) and investigated whether multimodal factor scores improve predictive power, relative to single-modal factor scores.

METHOD

We conducted exploratory factor analyses (EFAs) and confirmatory factor analyses (CFAs) of the baseline data of MCI subjects in the Alzheimer's Disease Neuroimaging Initiative (ADNI) to generate factor scores for three data modalities: neuropsychological (NP), magnetic resonance imaging (MRI), and cerebrospinal fluid (CSF). Factor scores from single or multiple modalities were entered in logistic regression models to predict MCI to AD conversion for 160 ADNI subjects over a 2-year interval.

RESULTS

NP factors attained an area under the curve (AUC) of .80, with a sensitivity of .66 and a specificity of .77. MRI factors reached a comparable level of performance (AUC = .80, sensitivity = .66, specificity = .78), whereas CSF factors produced weaker prediction (AUC = .70, sensitivity = .56, specificity = .79). Combining NP factors with MRI or CSF factors produced better prediction than either MRI or CSF factors alone. Similarly, adding MRI factors to NP or CSF factors produced improvements in prediction relative to NP or CSF factors alone. However, adding CSF factors to either NP or MRI factors produced no improvement in prediction.

CONCLUSIONS

Latent factor scores provided good accuracy for predicting MCI to AD conversion. Adding NP or MRI factors to factors from other modalities enhanced predictive power but adding CSF factors did not.

Should Doctors Offer Biomarker Testing to Those Afraid to Develop Alzheimer's Dementia? : Applying the Method of Reflective Equilibrium for a Clinical Dilemma

An increasing number of people seek medical attention for mild cognitive symptoms at older age, worried that they might develop Alzheimer's disease. Some clinical practice guidelines suggest offering biomarker testing in such cases, using a brain scan or a lumbar puncture, to improve diagnostic certainty about Alzheimer's disease and enable an earlier diagnosis. Critics, on the other hand, point out that there is no effective Alzheimer treatment available and argue that biomarker tests lack clinical validity. The debate on the ethical desirability of biomarker testing is currently polarized; advocates and opponents tend to focus on their own line of arguments. In this paper, we show how the method of reflective equilibrium (RE) can be used to systematically weigh the relevant arguments on both sides of the debate to decide whether to offer Alzheimer biomarker testing. In the tradition of RE, we reflect upon these arguments in light of their coherence with other argumentative elements, including relevant facts (e.g. on the clinical validity of the test), ethical principles, and theories on societal ideals or relevant concepts, such as autonomy. Our stance in the debate therefore rests upon previously set out in-depth arguments and reflects a wide societal perspective.

Deep-Learning Radiomics for Discrimination Conversion of Alzheimer's Disease in Patients With Mild Cognitive Impairment: A Study Based on 18F-FDG PET Imaging

Objectives: Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the older people. Some types of mild cognitive impairment (MCI) are the clinical precursors of AD, while other MCI forms tend to remain stable over time and do not progress to AD. To discriminate MCI patients at risk of AD from stable MCI, we propose a novel deep-learning radiomics (DLR) model based on 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) images and combine DLR features with clinical parameters (DLR+C) to improve diagnostic performance. Methods: 18F-fluorodeoxyglucose positron emission tomography (PET) data from the Alzheimer's disease Neuroimaging Initiative database (ADNI) were collected, including 168 patients with MCI who converted to AD within 3 years and 187 patients with MCI without conversion within 3 years. These subjects were randomly partitioned into 90 % for the training/validation group and 10 % for the independent test group. The proposed DLR approach consists of three steps: base DL model pre-training, network features extraction, and integration of DLR+C, where a convolution network serves as a feature encoder, and a support vector machine (SVM) operated as the classifier. In comparative experiments, we compared our DLR+C method with four other methods: the standard uptake value ratio (SUVR) method, Radiomics-ROI method, Clinical method, and SUVR + Clinical method. To guarantee the robustness, 10-fold cross-validation was processed 100 times. Results: Under the DLR model, our proposed DLR+C was advantageous and yielded the best classification performance in the diagnosis of conversion with the accuracy, sensitivity, and specificity of 90.62 ± 1.16, 87.50 ± 0.00, and 93.39 ± 2.19%, respectively. In contrast, the respective accuracy of the other four methods reached 68.38 ± 1.27, 73.31 ± 6.93, 81.09 ± 1.97, and 85.35 ± 0.72 %. These results suggested the DLR approach could be used successfully in the prediction of conversion to AD, and that our proposed DLR-combined clinical information was effective. Conclusions: This study showed DLR+C could provide a novel and valuable method for the computer-assisted diagnosis of conversion to AD from MCI. This DLR+C method provided a quantitative biomarker which could predict conversion to AD in MCI patients.

The Framing of "Alzheimer's Disease": Differences Between Scientific and Lay Literature and Their Ethical Implications

BACKGROUND AND OBJECTIVES

The meaning of Alzheimer's disease (AD) is changing in research. It now refers to a pathophysiological process, regardless of whether clinical symptoms are present. In the lay literature, on the other hand, AD is understood as a form of dementia. This raises the question of whether researchers and the lay audience are still talking about the same thing. If not, how will these different understandings of AD shape perspectives on (societal) needs for people with AD?

RESEARCH DESIGN AND METHODS

We use framing analysis to retrieve the understandings of the term AD that are upheld in the research literature and in national Dutch newspaper articles. We make explicit how the framings of AD steer our normative attitudes toward the disease.

RESULTS

In the analyzed research articles, AD is framed as a pathological cascade, reflected by biomarkers, starting in cognitively healthy people and ending, inevitably, in dementia. In the lay literature, AD is used as a synonym for dementia, and an AD diagnosis is understood as an incentive to enjoy "the time that is left."

DISCUSSION AND IMPLICATIONS

The two different uses of the term AD in research and in the lay literature may result in misunderstandings, especially those research framings that falsely imply that people with AD biomarkers will inevitably develop dementia. Adoption of the research understanding of AD in clinical practice will have normative implications for our view on priority setting in health care. For example, it legitimizes biomarker testing in people without dementia as improving "diagnostic" certainty.

Influence of Social and Demographic Factors on the Montreal Cognitive Assessment (MoCA) Test in Rural Population of North-Eastern Greece

The current study aims to investigate the influence of socio-demographic factors on the Montreal Cognitive Assessment (MoCA) test results in a Greek-speaking population consisting of a sample of healthy older adults, individuals with mild cognitive impairment (MCI), and dementia patients in rural areas. In addition, the current research focuses on determining optimal cut-off scores for the clinical diagnoses of MCI and dementia. The data originated from 283 participants in an ongoing registry of the Neurology Department of Alexandroupolis University Hospital, recruited in different rural districts of north-eastern Greece, across a broad range of educational and occupational categories. Total and sub-domain scores for the MoCA varied significantly, according to sex, age, and education, among the three study groups. The optimal cut-off points of 25/26 for the MoCA total score was determined to classify healthy subjects from individuals with MCI, 24 to discriminate healthy participants from demented, and 21/22 to discriminate subjects with MCI from dementia. Overall, the clinical use of the MoCA test can be supported by demographically adjusted standard scores in a Greek-speaking rural population. These findings serve to improve the diagnostic accuracy and utility of the MoCA test.

Apathy and risk of probable incident dementia among community-dwelling older adults

OBJECTIVE

To evaluate the association between baseline apathy and probable incident dementia in a population-based sample of community-dwelling older adults.

METHODS

We studied 2,018 white and black community-dwelling older adults from the Health, Aging, and Body Composition (Health ABC) study. We measured apathy at year 6 (our study baseline) with the modified Apathy Evaluation Scale and divided participants into tertiles based on low, moderate, or severe apathy symptoms. Incident dementia was ascertained over 9 years by dementia medication use, hospital records, or clinically relevant cognitive decline on global cognition. We examined the association between apathy and probable incident dementia using a Cox proportional hazards model adjusting for demographics, cardiovascular risk factors, APOE4 status, and depressed mood. We also evaluated the association between the apathy group and cognitive change (as measured by the modified Mini-Mental State Examination and Digit Symbol Substitution Test over 5 years) using linear mixed effects models.

RESULTS

Over 9 years of follow-up, 381 participants developed probable dementia. Severe apathy was associated with an increased risk of dementia compared to low apathy (25% vs 14%) in unadjusted (hazard ratio [HR] 1.9, 95% confidence interval [CI] 1.5-2.5) and adjusted models (HR 1.7, 95% CI 1.3-2.2). Greater apathy was associated with worse cognitive score at baseline, but not rate of change over time.

CONCLUSION

In a diverse cohort of community-dwelling adults, apathy was associated with increased risk of developing probable dementia. This study provides novel evidence for apathy as a prodrome of dementia.

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.

Ethical Arguments Concerning the Use of Alzheimer's Disease Biomarkers in Individuals with No or Mild Cognitive Impairment: A Systematic Review and Framework for Discussion

BACKGROUND

The shift to defining Alzheimer's disease (AD) as a biological continuum, which is characterized by the presence of biomarkers instead of clinical symptoms, has sparked a widespread debate. Insight into the given arguments and their underlying moral values is crucial to ensure well-considered and appropriate AD biomarker testing in the future.

OBJECTIVE

To critically review the arguments in favor of or against AD biomarker testing in people with no or mild cognitive impairment and to explicate their underlying moral values.

METHODS

Seven databases were systematically searched for publications mentioning arguments of interest. Arguments are identified using qualitative data-analysis and evaluated within an ethical framework.

RESULTS

Our search yielded 3,657 articles of which 34 met the inclusion criteria. We discuss the clusters of arguments separate from their evaluation and the assessment of the debate as a whole. The right to know, which derives from the moral value of respect for autonomy, is a central argument in favor of biomarker testing. On the other hand, fear of the disease and lack of a disease-modifying treatment may result in a negative balance of good over inflicted harms, which argues against its use.

CONCLUSION

Critical evaluation and weighing of the given arguments in a specific context, within an ethical framework, demonstrates the necessity to differentiate between what we hope or expect from research and where we currently stand. While AD biomarkers may have an indispensable value for research, the current advantage for clinical practice appears limited.

The incremental value of neuropsychological assessment: A critical review

Objective: The purpose of this critical review was to evaluate the current state of research regarding the incremental value of neuropsychological assessment in clinical practice, above and beyond what can be accounted for on the basis of demographic, medical, and other diagnostic variables. The focus was on neurological and other medical conditions across the lifespan where there is known risk for presence or future development of cognitive impairment.Method: Eligible investigations were group studies that had been published after 01/01/2000 in English in peer-reviewed journals and that had used standardized neuropsychological measures and reported on objective outcome criterion variables. They were identified through PubMed and PsychInfo electronic databases on the basis of predefined specific selection criteria. Reference lists of identified articles were also reviewed to identify potential additional sources. The Grades of Recommendation, Assessment, Development and Evaluation Working Group's (GRADE) criteria were used to evaluate quality of studies.Results: Fifty-six studies met the final selection criteria, including 2 randomized-controlled trials, 9 prospective cohort studies, 12 retrospective cohort studies, 21 inception cohort studies, 2 case control studies, and 10 case series studies. The preponderance of the evidence was strongly supportive with regard to the incremental value of neuropsychological assessment in the care of persons with mild cognitive impairment/dementia and traumatic brain injury. Evidence was moderately supportive with regard to stroke, epilepsy, multiple sclerosis, and attention-deficit/hyperactivity disorder. Participation in neuropsychological evaluations was also associated with cost savings.Conclusions: Neuropsychological assessment can improve both diagnostic classification and prediction of long-term daily-life outcomes in patients across the lifespan. Future high-quality prospective cohort studies and randomized-controlled trials are necessary to demonstrate more definitively the incremental value of neuropsychological assessment in the management of patients with various neurological and other medical conditions.

When is Alzheimer's not dementia-Cochrane commentary on The National Institute on Ageing and Alzheimer's Association Research Framework for Alzheimer's Disease

Early 2018 saw the release of new diagnostic guidance on Alzheimer's disease from the National Institute on Ageing and the Alzheimer's Association (NIA-AA). This proposed research framework represents a fundamental change in how we think about Alzheimer's disease, moving from diagnosis based on clinical features to diagnosis based solely on biomarkers. These recommendations are contentious and have important implications for patients, clinicians, policy makers and the pharmaceutical industry. In this commentary, we offer a summary of the NIA-AA research framework. We then focus on five key areas: divorcing neuropathology from the clinical syndrome; the emphasis placed on one dementia subtype; validity of available biomarkers; the changing meaning of the term 'Alzheimer's disease'; and the potential for a research framework to influence clinical practice.

Dual-Model Radiomic Biomarkers Predict Development of Mild Cognitive Impairment Progression to Alzheimer's Disease

Predicting progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD) is clinically important. In this study, we propose a dual-model radiomic analysis with multivariate Cox proportional hazards regression models to investigate promising risk factors associated with MCI conversion to AD. T1 structural magnetic resonance imaging (MRI) and ¹⁸F-Fluorodeoxyglucose (FDG) positron emission tomography (PET) data, from the AD Neuroimaging Initiative database, were collected from 131 patients with MCI who converted to AD within 3 years and 132 patients with MCI without conversion within 3 years. These subjects were randomly partition into 70% training dataset and 30% test dataset with multiple times. We fused MRI and PET images by wavelet method. In a subset of subjects, a group comparison was performed using a two-sample t-test to determine regions of interest (ROIs) associated with MCI conversion. 172 radiomic features from ROIs for each individual were established using a published radiomics tool. Finally, L1-penalized Cox model was constructed and Harrell’s C index (C-index) was used to evaluate prediction accuracy of the model. To evaluate the efficacy of our proposed method, we used a same analysis framework to evaluate MRI and PET data separately. We constructed prognostic Cox models with: clinical data, MRI images, PET images, fused MRI/PET images, and clinical variables and fused MRI/PET images in combination. The experimental results showed that captured ROIs significantly associated with conversion to AD, such as gray matter atrophy in the bilateral hippocampus and hypometabolism in the temporoparietal cortex. Imaging model (MRI/PET/fused) provided significant enhancement in prediction of conversion compared to clinical models, especially the fused-modality Cox model. Moreover, the combination of fused-modality imaging and clinical variables resulted in the greatest accuracy of prediction. The average C-index for the clinical/MRI/PET/fused/combined model in the test dataset was 0.69, 0.73, 0.73 and 0.75, and 0.78, respectively. These results suggested that a combination of radiomic analysis and Cox model analyses could be used successfully in survival analysis and may be powerful tools for personalized precision medicine patients with potential to undergo conversion from MCI to AD.

On the personal utility of Alzheimer's disease-related biomarker testing in the research context

Many healthy volunteers choose to take part in Alzheimer's disease (AD) prevention studies because they want to know whether they will develop dementia-and what they can do to reduce their risk-and are therefore interested in learning the results of AD biomarker tests. Proponents of AD biomarker disclosure often refer to the personal utility of AD biomarkers, claiming that research participants will be able to use AD biomarker information for personal purposes, such as planning ahead or making important life decisions. In this paper, the claim that AD biomarkers have personal utility for asymptomatic individuals is critically assessed. It demonstrates that in the absence of clinical validity, AD biomarkers cannot have personal utility and do not serve research participants' autonomy. Over the next few years, many research groups will be confronted with participants' preferences to learn the results of AD biomarker tests. When researchers choose to make results available upon explicit request, they should ensure adequate information provision and education, notably on the uncertain clinical significance of AD biomarker information. Routine disclosure of AD biomarkers to cognitively unimpaired individuals in research settings cannot be justified with an appeal to the personal utility of AD biomarker information.

Association of Apathy With Risk of Incident Dementia: A Systematic Review and Meta-analysis

IMPORTANCE

Fear of dementia is pervasive in older people with cognitive concerns. Much research is devoted to finding prognostic markers for dementia risk. Studies suggest apathy in older people may be prodromal to dementia and could be a relevant, easily measurable predictor of increased dementia risk. However, evidence is fragmented and methods vary greatly between studies.

OBJECTIVE

To systematically review and quantitatively synthesize the evidence for an association between apathy in dementia-free older individuals and incident dementia.

DATA SOURCES

Two reviewers conducted a systematic search of Medline, Embase, and PsychINFO databases.

STUDY SELECTION

Inclusion criteria were (1) prospective cohort studies, (2) in general populations or memory clinic patients without dementia, (3) with clear definitions of apathy and dementia, and (4) reporting on the association between apathy and incident dementia.

DATA EXTRACTION AND SYNTHESIS

PRISMA and MOOSE guidelines were followed. Data were extracted by 1 reviewer and checked by a second.

MAIN OUTCOMES AND MEASURES

Main outcomes were pooled crude risk ratios, maximally adjusted reported hazard ratios (HR), and odds ratios (OR) using DerSimonian-Laird random effects models.

RESULTS

The mean age of the study populations ranged from 69.2 to 81.9 years (median, 71.6 years) and the percentage of women ranged from 35% to 70% (median, 53%). After screening 2031 titles and abstracts, 16 studies comprising 7365 participants were included. Apathy status was available for 7299 participants. Studies included populations with subjective cognitive concerns (n = 2), mild cognitive impairment (n = 11), cognitive impairment no dementia (n = 1), or mixed cognitive and no cognitive impairment (n = 2). Apathy was present in 1470 of 7299 participants (20.1%). Follow-up ranged from 1.2 to 5.4 years. In studies using validated apathy definitions (n = 12), the combined risk ratio of dementia for patients with apathy was 1.81 (95% CI, 1.32-2.50; I2 = 76%; n = 12), the hazard ratio was 2.39 (95% CI, 1.27-4.51; I2 = 90%; n = 7), and the odds ratio was 17.14 (95% CI, 1.91-154.0; I2 = 60%; n = 2). Subgroup analyses, meta-regression, and individual study results suggested the association between apathy and dementia weakened with increasing follow-up time, age, and cognitive impairment. Meta-regression adjusting for apathy definition and follow-up time explained 95% of heterogeneity in mild cognitive impairment.

CONCLUSIONS AND RELEVANCE

Apathy was associated with an approximately 2-fold increased risk of dementia in memory clinic patients. Moderate publication bias may have inflated some of these estimates. Apathy deserves more attention as a relevant, cheap, noninvasive, and easily measureable marker of increased risk of incident dementia with high clinical relevance, particularly because these vulnerable patients may forgo health care.

Differential chemokine expression under the control of peripheral blood mononuclear cells issued from Alzheimer's patients in a human blood brain barrier model

Growing evidence highlights the peripheral blood mononuclear cells (PBMCs) role and the chemokine involvement in the Alzheimer's disease (AD) physiopathology. However, few data are available about the impact of AD PBMCs in the chemokine signature in a brain with AD phenotype. Therefore, this study analyzed the chemokine levels in a human blood brain barrier model. A human endothelial cell line from the immortalized cerebral microvascular endothelial cell line (hCMEC/D3) and a human glioblastoma U-87 MG cell line, both with no AD phenotype were used while PBMCs came from AD at mild or moderate stage and control patients. PBMCs from moderate AD patients decreased CCL2 and CCL5 levels in endothelial, and also CXCL10 in abluminal compartments and in PBMCs compared to PBMCs from mild AD patients. The CX3CL1 expression increased in endothelial and abluminal compartments with PBMCs from mild AD patients compared to controls. AD PBMCs can convert the chemokine signature towards that found in AD brain, targeting some chemokines as new biomarkers in AD.

Review of Diagnostic Test Accuracy (DTA) studies in older people

Diagnostic Test Accuracy (DTA) describes a field of research that aims to assess how well a test is able to detect or exclude a condition of interest. Although geriatric medicine is not as reliant on investigations as other medical disciplines, almost all patient encounters with older adults will involve some form of diagnostic assessment. Thus, understanding the terminology and methods of DTA is essential for any clinician. In this review we use examples based around the diagnosis of dementia to highlight issues in DTA research. Some of these are generic to any DTA research and some are particularly pertinent to older adults. One can apply a test accuracy framework to a clinical question by defining four key components: the condition of interest; the index test(s) (i.e. the assessment(s) of interest); the reference standard (the best available method for assessing the condition of interest) and the population or healthcare setting in which testing takes place. Test accuracy is often described using complementary measures of sensitivity and specificity. However, many other metrics to describe test accuracy are available; in clinical practice predictive values may have greater utility. These and other descriptive statistics can be derived from a two by two table that cross-classifies the index test results with the reference standard results. Test performance and utility is not only determined by accuracy, other measures such as feasibility and acceptability should be considered and may be of particular importance when describing test performance in older adults with physical and cognitive impairments.

Progress and Challenges in the Diagnosis of Dementia: A Critical Review

Longer life expectancies have led to an increased number of neurodegenerative disease cases globally. Accurate diagnosis of this devastating disorder is of crucial importance but is still feasible only by a brain biopsy after death. An enormous amount of attention and research has been in place over the years toward the better understanding of the mechanisms, as well as the early diagnosis, of neurodegeneration. However, numerous studies have been contradictory from time to time, while new diagnostic methods are constantly developed in a tireless effort to tackle the disease. Nonetheless, there is not yet a conclusive report covering a broader range of techniques for the diagnosis of different types of dementia. In this paper, we critically review current knowledge on the different hypotheses about the pathogenesis of distinct types of dementia, as well as risk factors and current diagnostic approaches in a clinical setting, including neuroimaging, cerebrospinal (CSF), and blood tests. Encouraging research results for the diagnosis and investigation of neurodegenerative disorders are also reported. Particular attention is given to the field of spectroscopy as an emerging tool to detect dementias, follow-up patients, and potentially monitor the patients' response to a therapeutic approach. Spectroscopic techniques, such as infrared and Raman spectroscopy, have facilitated numerous disease-related studies, including neurodegenerative disorders, and are currently undergoing trials for clinical implementation. This review constitutes a comprehensive report with an in-depth focus on promising imaging, molecular biomarker and spectroscopic tests in the field of dementive diseases.

Using Neuropsychological Process Scores to Identify Subtle Cognitive Decline and Predict Progression to Mild Cognitive Impairment

BACKGROUND

We previously operationally-defined subtle cognitive decline (SCD) in preclinical Alzheimer's disease (AD) using total scores on neuropsychological (NP) tests. NP process scores (i.e., provide information about how a total NP score was achieved) may be a useful tool for identifying early cognitive inefficiencies prior to objective impairment seen in mild cognitive impairment (MCI) and dementia.

OBJECTIVE

We aimed to integrate process scores into the SCD definition to identify stages of SCD and improve early detection of those at risk for decline.

METHODS

Cognitively "normal" participants from the Alzheimer's Disease Neuroimaging Initiative were classified as "early" SCD (E-SCD; >1 SD below norm-adjusted mean on 2 process scores or on 1 process score plus 1 NP total score), "late" SCD (L-SCD; existing SCD criteria of >1 SD below norm-adjusted mean on 2 NP total scores in different domains), or "no SCD" (NC). Process scores considered in the SCD criteria were word-list intrusion errors, retroactive interference, and learning slope. Cerebrospinal fluid AD biomarkers were used to examine pathologic burden across groups.

RESULTS

E-SCD and L-SCD progressed to MCI 2.5-3.4 times faster than the NC group. Survival curves for E-SCD and L-SCD converged at 7-8 years after baseline. The combined (E-SCD+L-SCD) group had improved sensitivity to detect progression to MCI relative to L-SCD only. AD biomarker positivity increased across NC, SCD, and MCI groups.

CONCLUSIONS

Process scores can be integrated into the SCD criteria to allow for increased sensitivity and earlier identification of cognitively normal older adults at risk for decline prior to frank impairment on NP total scores.

Interpreting Biomarker Results in Individual Patients With Mild Cognitive Impairment in the Alzheimer's Biomarkers in Daily Practice (ABIDE) Project

Importance

Biomarkers do not determine conversion to Alzheimer disease (AD) perfectly, and criteria do not specify how to take patient characteristics into account. Consequently, biomarker use may be challenging for clinicians, especially in patients with mild cognitive impairment (MCI).

Objective

To construct biomarker-based prognostic models that enable determination of future AD dementia in patients with MCI.

Design, Setting, and Participants

This study is part of the Alzheimer's Biomarkers in Daily Practice (ABIDE) project. A total of 525 patients with MCI from the Amsterdam Dementia Cohort (longitudinal cohort, tertiary referral center) were studied. All patients had their baseline visit to a memory clinic from September 1, 1997, through August 31, 2014. Prognostic models were constructed by Cox proportional hazards regression with patient characteristics (age, sex, and Mini-Mental State Examination [MMSE] score), magnetic resonance imaging (MRI) biomarkers (hippocampal volume, normalized whole-brain volume), cerebrospinal fluid (CSF) biomarkers (amyloid-β1-42, tau), and combined biomarkers. Data were analyzed from November 1, 2015, to October 1, 2016.

Main Outcomes and Measures

Clinical end points were AD dementia and any type of dementia after 1 and 3 years.

Results

Of the 525 patients, 210 (40.0%) were female, and the mean (SD) age was 67.3 (8.4) years. On the basis of age, sex, and MMSE score only, the 3-year progression risk to AD dementia ranged from 26% (95% CI, 19%-34%) in younger men with MMSE scores of 29 to 76% (95% CI, 65%-84%) in older women with MMSE scores of 24 (1-year risk: 6% [95% CI, 4%-9%] to 24% [95% CI, 18%-32%]). Three- and 1-year progression risks were 86% (95% CI, 71%-95%) and 27% (95% CI, 17%-41%) when MRI results were abnormal, 82% (95% CI, 73%-89%) and 26% (95% CI, 20%-33%) when CSF test results were abnormal, and 89% (95% CI, 79%-95%) and 26% (95% CI, 18%-36%) when the results of both tests were abnormal. Conversely, 3- and 1-year progression risks were 18% (95% CI, 13%-27%) and 3% (95% CI, 2%-5%) after normal MRI results, 6% (95% CI, 3%-9%) and 1% (95% CI, 0.5%-2%) after normal CSF test results, and 4% (95% CI, 2%-7%) and 0.5% (95% CI, 0.2%-1%) after combined normal MRI and CSF test results. The prognostic value of models determining any type of dementia were in the same order of magnitude although somewhat lower. External validation in Alzheimer's Disease Neuroimaging Initiative 2 showed that our models were highly robust.

Conclusions and Relevance

This study provides biomarker-based prognostic models that may help determine AD dementia and any type of dementia in patients with MCI at the individual level. This finding supports clinical decision making and application of biomarkers in daily practice.

Clinical validity of delayed recall tests as a gateway biomarker for Alzheimer's disease in the context of a structured 5-phase development framework

Although Alzheimer's disease criteria promote the use of biomarkers, their maturity in clinical routine still needs to be assessed. In the light of the oncology framework, we conducted a literature review on measures used to assess delayed recall impairment due to medial temporal lobe dysfunction (i.e., free and cued word list recall tests). Ample evidence is available for phases 1 (rationale for use), 2 (discriminative ability), and 3 (early detection ability) for many of the tests in routine use. Evidence about phase 4 (performance in real world) and phase 5 (quantify impact and costs) is yet to come. Administration procedures have been standardized and cutoff scores are well validated in large Alzheimer's disease and mild cognitive impaired series. Some aspects (e.g., different task formats), however, hamper the comparability of results among different populations and the reproducibility between laboratories. No definite guideline for their use can thus be proposed at the moment. Accordingly, the maturity of such markers is not yet sufficient and requires future investigation to promote the proper use of memory measures in clinical settings.

Neuropsychological Measures that Predict Progression from Mild Cognitive Impairment to Alzheimer's type dementia in Older Adults: a Systematic Review and Meta-Analysis

This study aimed to determine the extent to which cognitive measures can predict progression from mild cognitive impairment (MCI) to Alzheimer’s type dementia (AD), assess the predictive accuracy of different cognitive domain categories, and determine whether accuracy varies as a function of age and length of follow-up. We systematically reviewed and meta-analyzed data from longitudinal studies reporting sensitivity and specificity values for neuropsychological tests to identify individuals with MCI who will develop AD. We searched articles in Medline, Cochrane, EMBASE, PsycINFO, and the Web of Science. Methodological quality was assessed using the STARDem and QUADAS standards. Twenty-eight studies met the eligibility criteria (2365 participants) and reported predictive values from 61 neuropsychological tests with a 31-month mean follow-up. Values were pooled to provide combined accuracy for 14 cognitive domains. Many domains showed very good predictive accuracy with high sensitivity and specificity values (≥ 0.7). Verbal memory measures and many language tests yielded very high predictive accuracy. Other domains (e.g., executive functions, visual memory) showed better specificity than sensitivity. Predictive accuracy was highest when combining memory measures with a small set of other domains or when relying on broad cognitive batteries. Cognitive tests are excellent at predicting MCI individuals who will progress to dementia and should be a critical component of any toolkit intended to identify AD at the pre-dementia stage. Some tasks are remarkable as early indicators, whereas others might be used to suggest imminent progression.

Alzheimer's Disease: Past, Present, and Future

Although dementia has been described in ancient texts over many centuries (e.g., "Be kind to your father, even if his mind fail him." - Old Testament: Sirach 3:12), our knowledge of its underlying causes is little more than a century old. Alzheimer published his now famous case study only 110 years ago, and our modern understanding of the disease that bears his name, and its neuropsychological consequences, really only began to accelerate in the 1980s. Since then we have witnessed an explosion of basic and translational research into the causes, characterizations, and possible treatments for Alzheimer's disease (AD) and other dementias. We review this lineage of work beginning with Alzheimer's own writings and drawings, then jump to the modern era beginning in the 1970s and early 1980s and provide a sampling of neuropsychological and other contextual work from each ensuing decade. During the 1980s our field began its foundational studies of profiling the neuropsychological deficits associated with AD and its differentiation from other dementias (e.g., cortical vs. subcortical dementias). The 1990s continued these efforts and began to identify the specific cognitive mechanisms affected by various neuropathologic substrates. The 2000s ushered in a focus on the study of prodromal stages of neurodegenerative disease before the full-blown dementia syndrome (i.e., mild cognitive impairment). The current decade has seen the rise of imaging and other biomarkers to characterize preclinical disease before the development of significant cognitive decline. Finally, we suggest future directions and predictions for dementia-related research and potential therapeutic interventions. (JINS, 2017, 23, 818-831).

Cascaded Multi-view Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer's Disease via Fusion of Clinical, Imaging and Omic Features

The introduction of mild cognitive impairment (MCI) as a diagnostic category adds to the challenges of diagnosing Alzheimer’s Disease (AD). No single marker has been proven to accurately categorize patients into their respective diagnostic groups. Thus, previous studies have attempted to develop fused predictors of AD and MCI. These studies have two main limitations. Most do not simultaneously consider all diagnostic categories and provide suboptimal fused representations using the same set of modalities for prediction of all classes. In this work, we present a combined framework, cascaded multiview canonical correlation (CaMCCo), for fusion and cascaded classification that incorporates all diagnostic categories and optimizes classification by selectively combining a subset of modalities at each level of the cascade. CaMCCo is evaluated on a data cohort comprising 149 patients for whom neurophysiological, neuroimaging, proteomic and genomic data were available. Results suggest that fusion of select modalities for each classification task outperforms (mean AUC = 0.92) fusion of all modalities (mean AUC = 0.54) and individual modalities (mean AUC = 0.90, 0.53, 0.71, 0.73, 0.62, 0.68). In addition, CaMCCo outperforms all other multi-class classification methods for MCI prediction (PPV: 0.80 vs. 0.67, 0.63).

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.

Biomarkers for Alzheimer Disease: Classical and Novel Candidates' Review

The biomarkers may be useful for predictive diagnosis of Alzheimer's disease (AD). The current challenge is to diagnose it in its preclinical phase. The combination of cerebrospinal fluid (CSF) biomarkers and imaging has been investigated extensively for a number of years. It can provide an increased diagnostic accuracy. This review discusses the contribution of classical biomarkers to predict AD and highlights novel candidates identified as potential markers for AD. We referred to the electronic databases PubMed/Medline and Web of Science to search for articles that were published until February 2016. Sixty-two records were included in qualitative synthesis. In the first section, the results show the contribution of biomarkers to predict and track AD considered as classical biomarkers. In the second section, the results highlight the involvement of novel candidates that should be considered for future evaluation in the characterization of the AD progression. Reported findings open prospect to define noninvasive biomarkers to predict AD before symptoms onset.

Alzheimer's biomarkers in daily practice (ABIDE) project: Rationale and design

Introduction

The Alzheimer's biomarkers in daily practice (ABIDE) project is designed to translate knowledge on diagnostic tests (magnetic resonance imaging [MRI], cerebrospinal fluid [CSF], and amyloid positron emission tomography [PET]) to daily clinical practice with a focus on mild cognitive impairment (MCI)

Methods

ABIDE is a 3-year project with a multifaceted design and is structured into interconnected substudies using both quantitative and qualitative research methods.

Results

Based on retrospective data, we develop personalized risk estimates for MCI patients. Prospectively, we collect MRI and CSF data from 200 patients from local memory clinics and amyloid PET from 500 patients in a tertiary setting, to optimize application of these tests in daily practice. Furthermore, ABIDE will develop strategies for optimal patient-clinician conversations.

Discussion

Ultimately, this will result in a set of practical tools for clinicians to support the choice of diagnostic tests and facilitate the interpretation and communication of their results.

Subtle Cognitive Decline and Biomarker Staging in Preclinical Alzheimer's Disease

The NIA-AA criteria for "preclinical" Alzheimer's disease (AD) propose a staging method in which AD biomarkers follow an invariable temporal sequence in accordance with the amyloid cascade hypothesis. However, recent findings do not align with the proposed temporal sequence and "subtle cognitive decline," which has not been definitively operationalized, may occur earlier than suggested in preclinical AD. We aimed to define "subtle cognitive decline" using sensitive and reliable neuropsychological tests, and to examine the number and sequence of biomarker abnormalities in the Alzheimer's Disease Neuroimaging Initiative (ADNI). 570 cognitively normal ADNI participants were classified based on NIA-AA criteria and separately based on the number of abnormal biomarkers/cognitive markers associated with preclinical AD that each individual possessed. Results revealed that neurodegeneration alone was 2.5 times more common than amyloidosis alone at baseline. For those who demonstrated only one abnormal biomarker at baseline and later progressed to mild cognitive impairment/AD, neurodegeneration alone was most common, followed by amyloidosis alone or subtle cognitive decline alone, which were equally common. Findings suggest that most individuals do not follow the temporal order proposed by NIA-AA criteria. We provide an operational definition of subtle cognitive decline that captures both cognitive and functional decline. Additionally, we offer a new approach for staging preclinical AD based on number of abnormal biomarkers, without regard to their temporal order of occurrence. This method of characterizing preclinical AD is more parsimonious than the NIA-AA staging system and does not presume that all patients follow a singular invariant expression of the disease.

BACE1 in the retina: a sensitive biomarker for monitoring early pathological changes in Alzheimer's disease

Because of a lack of sensitive biomarkers, the diagnosis of Alzheimer's disease (AD) cannot be made prior to symptom manifestation. Therefore, it is crucial to identify novel biomarkers for the presymptomatic diagnosis of AD. While brain lesions are a major feature of AD, retinal pathological changes also occur in patients. In this study, we investigated the temporal changes in β-site APP-cleaving enzyme 1 (BACE1) expression in the retina and brain to determine whether it could serve as a suitable biomarker for early monitoring of AD. APP/PS-1 transgenic mice, 3, 6 and 8 months of age, were used as an experimental group, and age-matched C57/BL6 wild-type mice served as the control group. In the Morris water maze test, there were no significant differences in escape latency or in the number of crossings in the target area among mice of different ages. Compared with wild-type mice, no changes in learning or memory abilities were detected in transgenic mice at 3 months of age. However, compared with wild-type mice, the escape latency was significantly increased in transgenic mice at 6 months, starting on day 3, and at 8 months, starting on day 2, during Morris water maze training. In addition, the number of crossings of the target area was significantly decreased in transgenic mice. The learning and memory abilities of transgenic mice were further worsened at 8 months of age. Immunohistochemical staining revealed no BACE1 plaques in wild-type mice at 3, 6 or 8 months or in transgenic mice at 3 months, but they were clearly found in the entorhinal cortex, hippocampus and prefrontal cortex of transgenic mice at 6 and 8 months. BACE1 expression was not detected in the retina of wild-type mice at 3 months, but weak BACE1 expression was detected in the ganglion cell layer, inner plexiform layer and outer plexiform layer at 6 and 8 months. In transgenic mice, BACE1 expression in the ganglion cell layer was increased at 3 months, and BACE1 expression in the ganglion cell layer, inner plexiform layer and outer plexiform layer was significantly increased at 6 and 8 months, compared with age-matched wild-type mice. Taken together, these results indicate that changes in BACE1 expression appear earlier in the retina than in the brain and precede behavioral deficits. Our findings suggest that abnormal expression of BACE1 in the retina is an early pathological change in APP/PS-1 transgenic mice, and that BACE1 might have potential as a biomarker for the early diagnosis of AD in humans.

A Genetics-based Biomarker Risk Algorithm for Predicting Risk of Alzheimer's Disease

Introduction

A straightforward, reproducible blood-based test that predicts age-dependent risk of Alzheimer's disease (AD) could be used as an enrichment tool for clinical development of therapies. This study evaluated the prognostic performance of a genetics-based biomarker risk algorithm (GBRA) established on a combination of apolipoprotein E (APOE)/translocase of outer mitochondrial membrane 40 homolog (TOMM40) genotypes and age, then compare it to cerebrospinal fluid (CSF) biomarkers, neuroimaging, and neurocognitive tests using data from two independent AD cohorts.

Methods

The GBRA was developed using data from the prospective Joseph and Kathleen Bryan, Alzheimer's Disease Research Center study (n = 407; 86 conversion events [mild cognitive impairment {MCI} or late-onset Alzheimer's disease {LOAD}]). The performance of the algorithm was tested using data from the Alzheimer's Disease Neuroimaging Initiative study (n = 660; 457 individuals categorized as MCI or LOAD).

Results

The positive predictive values and negative predictive values of the GBRA are in the range of 70%–80%. The relatively high odds ratio (approximately 3–5) and significant net reclassification index scores comparing the GBRA to a version based on APOE and age alone support the value of the GBRA in risk prediction for MCI due to LOAD. Performance of the GBRA compares favorably with CSF and imaging (functional magnetic resonance imaging) biomarkers. In addition, the GBRA “high” and “low” AD-risk categorizations correlated well with pathologic CSF biomarker levels, positron emission tomography amyloid burden, and neurocognitive scores.

Discussion

Unlike dynamic markers (i.e., imaging, protein, or lipid markers) that may be influenced by factors unrelated to disease, genomic DNA is easily collected, stable, and the technical methods for measurement are robust, inexpensive, and widely available. The performance characteristics of the GBRA support its use as a pharmacogenetic enrichment tool for LOAD delay-of-onset clinical trials and merit further evaluation for its clinical utility in evaluating therapeutic efficacy.

Multimodality Imaging Approach in Alzheimer disease. Part I: Structural MRI, Functional MRI, Diffusion Tensor Imaging and Magnetization Transfer Imaging

The authors make a complete review of the potential clinical applications of traditional and novel magnetic resonance imaging (MRI) techniques in the evaluation of patients with Alzheimer's disease, including structural MRI, functional MRI, diffusion tension imaging and magnetization transfer imaging.

Linking CSF and cognition in Alzheimer's disease: Reanalysis of clinical data

OBJECTIVES

Memory and executive deficits are important cognitive markers of Alzheimer's disease (AD). Moreover, in the past decade, cerebrospinal fluid (CSF) biomarkers have been increasingly utilized in clinical practice. Both cognitive and CSF markers can be used to differentiate between AD patients and healthy seniors with high diagnostic accuracy. However, the extent to which performance on specific mnemonic or executive tasks enables reliable estimations of the concentrations of different CSF markers and their ratios remains unclear.

METHODS

To address the above issues, we examined the association between neuropsychological data and CSF biomarkers in 51 AD patients using hierarchical multiple regression analyses. In the first step of these analyses, age, education and sex were entered as predictors to control for possible confounding effects. In the second step, data from a neuropsychological test battery assessing episodic memory, semantic memory and executive functioning were included to determine whether these variables significantly increased (compared to step 1) the explained variance in Aβ42 concentration, p-tau concentration, t-tau concentration, Aβ42/t-tau ratio, and Aβ42/Aβ40 ratio.

RESULTS

The different models explained 52% of the variance in Aβ42/t-tau ratio, 27% of the variance in Aβ42 concentration, and 28% of the variance in t-tau concentration. In particular, Aβ42/t-tau ratio was associated with verbal recognition and code shifting, with Aβ42 being related to verbal recognition and t-tau being related to code shifting. By contrast, the inclusion of neuropsychological data did not allow reliable estimations of Aβ42/Aβ40 ratio or p-tau concentration.

CONCLUSION

Our results showed that strong associations exist between the cognitive key symptoms of AD and the concentrations and ratios of specific CSF markers. In addition, we revealed a specific combination of neuropsychological tests that may facilitate reliable estimations of CSF concentrations, thereby providing important diagnostic information for non-invasive early AD detection.

Predicting Alzheimer's disease development: a comparison of cognitive criteria and associated neuroimaging biomarkers

Introduction

The definition of “objective cognitive impairment” in current criteria for mild cognitive impairment (MCI) varies considerably between research groups and clinics. This study aims to compare different methods of defining memory impairment to improve prediction models for the development of Alzheimer’s disease (AD) from baseline to 24 months.

Methods

The sensitivity and specificity of six methods of defining episodic memory impairment (< −1, −1.5 or −2 standard deviations [SD] on one or two memory tests) were compared in 494 non-demented seniors from the Alzheimer’s Disease Neuroimaging Initiative using the area under the curve (AUC) for receiver operating characteristic analysis. The added value of non-memory measures (language and executive function) and biomarkers (hippocampal and white-matter hyperintensity volume, brain parenchymal fraction [BPF], and APOEε4 status) was investigated using logistic regression.

Results

Baseline scores < −1 SD on two memory tests predicted AD with 75.91 % accuracy (AUC = 0.80). Only APOE ε4 status further improved prediction (B = 1.10, SE = 0.45, p = .016). A < −1.5 SD cut-off on one test had 66.60 % accuracy (AUC = 0.77). Prediction was further improved using Trails B/A ratio (B = 0.27, SE = 0.13, p = .033), BPF (B = −15.97, SE = 7.58, p = .035), and APOEε4 status (B = 1.08, SE = 0.45, p = .017). A cut-off of < −2 SD on one memory test (AUC = 0.77, SE = 0.03, 95 % CI 0.72-0.82) had 76.52 % accuracy in predicting AD. Trails B/A ratio (B = 0.31, SE = 0.13, p = .017) and APOE ε4 status (B = 1.07, SE = 0.46, p = .019) improved predictive accuracy.

Conclusions

Episodic memory impairment in MCI should be defined as scores < −1 SD below normative references on at least two measures. Clinicians or researchers who administer a single test should opt for a more stringent cut-off and collect and analyze whole-brain volume. When feasible, ascertaining APOE ε4 status can further improve prediction.

Cognitive, genetic, and brain perfusion factors associated with four year incidence of Alzheimer's disease from mild cognitive impairment

BACKGROUND

There is a range of factors that predict the development of Alzheimer's disease (AD) dementia among patients with amnestic mild cognitive impairment (MCI).

OBJECTIVES

To identify the neuropsychological, genetic, and functional brain imaging data that best predict conversion to AD dementia in patients with amnestic MCI.

METHODS

From an initial group of 42 amnestic MCI patients assessed with neurological, neuropsychological, and brain SPECT, 39 (25 converters, 14 non-converters) were followed for 4 years, and 36 had APOE ε4 genotyping. Baseline neuropsychological data and brain SPECT data were used to predict which of the MCI patients would develop dementia by the end of the 4 years of observation.

RESULTS

The MCI patients who had converted to AD dementia had poorer performance on long-term visual memory and Semantic Fluency tests. The MCI subjects who developed dementia were more likely to carry at least one copy of the APOE ε4 allele (Hazard Risk = 4.22). There was lower brain perfusion in converters than non-converters, mainly in postcentral gyrus. An additional analysis of the SPECT data found differences between the MCI subjects and controls in the posterior cingulate gyrus and the basal forebrain. When the brain imaging and neuropsychological test data were combined in the same Cox regression model, only the neuropsychological test data were significantly associated with time to dementia.

CONCLUSION

Although the presence of reduced brain perfusion in postcentral gyrus and basal forebrain indicated an at-risk condition, it was the extent of memory impairment that was linked to the speed of decline from MCI to AD.

Conventional and robust norming in identifying preclinical dementia

OBJECTIVE

To contrast four approaches to norming two widely used memory tests in older adults for the purpose of detecting preclinical dementia.

METHOD

The study sample included participants from the Einstein Aging Study who were over age 70, were free of dementia at baseline, and were followed for at least 5 years. Norms were derived from a conventional sample (excluding individuals with dementia at baseline but not those who developed dementia during follow-up) and a robust normative sample (excluding persons with dementia at baseline as well as those who developed dementia over 5 years of follow-up). Both normative samples were examined with and without adjustment for age and education. We contrasted the picture version of the Free and Cued Selective Reminding Test with Immediate Recall (pFCSRT+IR) and the Logical Memory (LM) test for their ability to identify persons with preclinical dementia, operationally defined by the development of diagnosable dementia over 5 years of follow-up, using these four approaches to developing norms for detecting preclinical dementia.

RESULTS

Of 418 participants included in the conventional normative sample, the mean age was 78.2 years, and 59% were female. There were 78 incident cases of dementia over 5 years leaving 340 participants in the robust normative sample. Means and standard deviations were defined for both the conventional and robust normative samples, and cut-scores with and without adjustment were set at 1.5 standard deviations below the mean of each test. As predicted, in comparison with the conventional sample, the robust sample had higher cut-scores, which provided higher sensitivity for detecting preclinical dementia. This effect persisted regardless of adjustment. The pFCSRT+IR was more sensitive than LM in detecting incident dementia cases.

CONCLUSION

When using cognitive test norms to identify preclinical dementia, robust norming procedures improves detection using both the pFCSRT+IR and LM.

Usefulness of data from magnetic resonance imaging to improve prediction of dementia: population based cohort study

OBJECTIVE

To determine whether the addition of data derived from magnetic resonance imaging (MRI) of the brain to a model incorporating conventional risk variables improves prediction of dementia over 10 years of follow-up.

DESIGN

Population based cohort study of individuals aged ≥ 65.

SETTING

The Dijon magnetic resonance imaging study cohort from the Three-City Study, France.

PARTICIPANTS

1721 people without dementia who underwent an MRI scan at baseline and with known dementia status over 10 years' follow-up.

MAIN OUTCOME MEASURE

Incident dementia (all cause and Alzheimer's disease).

RESULTS

During 10 years of follow-up, there were 119 confirmed cases of dementia, 84 of which were Alzheimer's disease. The conventional risk model incorporated age, sex, education, cognition, physical function, lifestyle (smoking, alcohol use), health (cardiovascular disease, diabetes, systolic blood pressure), and the apolipoprotein genotype (C statistic for discrimination performance was 0.77, 95% confidence interval 0.71 to 0.82). No significant differences were observed in the discrimination performance of the conventional risk model compared with models incorporating data from MRI including white matter lesion volume (C statistic 0.77, 95% confidence interval 0.72 to 0.82; P=0.48 for difference of C statistics), brain volume (0.77, 0.72 to 0.82; P=0.60), hippocampal volume (0.79, 0.74 to 0.84; P=0.07), or all three variables combined (0.79, 0.75 to 0.84; P=0.05). Inclusion of hippocampal volume or all three MRI variables combined in the conventional model did, however, lead to significant improvement in reclassification measured by using the integrated discrimination improvement index (P=0.03 and P=0.04) and showed increased net benefit in decision curve analysis. Similar results were observed when the outcome was restricted to Alzheimer's disease.

CONCLUSIONS

Data from MRI do not significantly improve discrimination performance in prediction of all cause dementia beyond a model incorporating demographic, cognitive, health, lifestyle, physical function, and genetic data. There were, however, statistical improvements in reclassification, prognostic separation, and some evidence of clinical utility.

The Q* Index: A Useful Global Measure of Dementia Screening Test Accuracy?

Background/Aims

Single, global or unitary, indicators of test diagnostic performance have intuitive appeal for clinicians. The Q* index, the point in receiver operating characteristic (ROC) curve space closest to the ideal top left-hand corner and where test sensitivity and specificity are equal, is one such measure.

Methods

Datasets from four pragmatic accuracy studies which examined the Mini-Mental State Examination, Addenbrooke's Cognitive Examination-Revised, Montreal Cognitive Assessment, Test Your Memory test, and Mini-Addenbrooke's Cognitive Examination were examined to calculate and compare the Q* index, the maximal correct classification accuracy, and the maximal Youden index, as well as the sensitivity and specificity at these cutoffs.

Results

Tests ranked similarly for the Q* index and the area under the ROC curve (AUC ROC). The Q* index cutoff was more sensitive (and less specific) than the maximal correct classification accuracy cutoff, and less sensitive (and more specific) than the maximal Youden index cutoff.

Conclusion

The Q* index may be a useful global parameter summarising the test accuracy of cognitive screening instruments, facilitating comparison between tests, and defining a possible test cutoff value. As the point of equal sensitivity and specificity, its use may be more intuitive and appealing for clinicians than AUC ROC.

The free and cued selective reminding test for predicting progression to Alzheimer's disease in patients with mild cognitive impairment: A prospective longitudinal study

Amnestic mild cognitive impairment (aMCI) patients carry a greater risk of conversion to Alzheimer's disease (AD). Therefore, the International Working Group (IWG) on AD aims to consider some cases of aMCI as symptomatic prodromal AD. The core diagnostic marker of AD is a significant and progressive memory deficit, and the Free and Cued Selective Reminding Test (FCSRT) was recommended by the IWG to test memory in cases of possible prodromal AD. This study aims to investigate whether the performance on the FCSRT would enhance the ability to predict conversion to AD in an aMCI group. A longitudinal study was conducted on 88 aMCI patients, and neuropsychological tests were analysed on the relative risk of conversion to AD. During follow-up (23.82 months), 33% of the aMCI population converted to AD. An impaired FCSRT TR was significantly associated with the risk of conversion to dementia, with a mean time to conversion of 25 months. The FCSRT demonstrates utility for detecting AD at its prodromal stage, thus supporting its use as a valid clinical marker.

T1rho MRI and CSF biomarkers in diagnosis of Alzheimer's disease

In the current study, we have evaluated the performance of magnetic resonance (MR) T1rho (T_1ρ) imaging and CSF biomarkers (T-tau, P-tau and Aβ-42) in characterization of Alzheimer's disease (AD) patients from mild cognitive impairment (MCI) and control subjects. With informed consent, AD (n = 27), MCI (n = 17) and control (n = 17) subjects underwent a standardized clinical assessment and brain MRI on a 1.5-T clinical-scanner. T_1ρ images were obtained at four different spin-lock pulse duration (10, 20, 30 and 40 ms). T_1ρ maps were generated by pixel-wise fitting of signal intensity as a function of the spin-lock pulse duration. T_1ρ values from gray matter (GM) and white matter (WM) of medial temporal lobe were calculated. The binary logistic regression using T_1ρ and CSF biomarkers as variables was performed to classify each group. T_1ρ was able to predict 77.3% controls and 40.0% MCI while CSF biomarkers predicted 81.8% controls and 46.7% MCI. T_1ρ and CSF biomarkers in combination predicted 86.4% controls and 66.7% MCI. When comparing controls with AD, T_1ρ predicted 68.2% controls and 73.9% AD, while CSF biomarkers predicted 77.3% controls and 78.3% for AD. Combination of T_1ρ and CSF biomarkers improved the prediction rate to 81.8% for controls and 82.6% for AD. Similarly, on comparing MCI with AD, T_1ρ predicted 35.3% MCI and 81.9% AD, whereas CSF biomarkers predicted 53.3% MCI and 83.0% AD. Collectively CSF biomarkers and T_1ρ were able to predict 59.3% MCI and 84.6% AD. On receiver operating characteristic analysis T_1ρ showed higher sensitivity while CSF biomarkers showed greater specificity in delineating MCI and AD from controls. No significant correlation between T_1ρ and CSF biomarkers, between T_1ρ and age, and between CSF biomarkers and age was observed. The combined use of T_1ρ and CSF biomarkers have promise to improve the early and specific diagnosis of AD. Furthermore, disease progression form MCI to AD might be easily tracked using these two parameters in combination.

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Increased T1rho was observed in MCI and AD compared to controls.

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Increased T-tau and P-tau and decreased Aβ1-42 were observed in MCI and AD.

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Combined biomarkers have promise to improve early and specific diagnosis of AD.

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MCI to AD progression might be tracked using these two biomarkers in combination.

Advances in the therapy of Alzheimer's disease: targeting amyloid beta and tau and perspectives for the future

Worldwide multidisciplinary translational research has led to a growing knowledge of the genetics and molecular pathogenesis of Alzheimer's disease (AD) indicating that pathophysiological brain alterations occur decades before clinical signs and symptoms of cognitive decline can be diagnosed. Consequently, therapeutic concepts and targets have been increasingly focused on early-stage illness before the onset of dementia; and distinct classes of compounds are now being tested in clinical trials. At present, there is a growing consensus that therapeutic progress in AD delaying disease progression would significantly decrease the expanding global burden. The evolving hypothesis- and evidence-based generation of new diagnostic research criteria for early-stage AD has positively impacted the development of clinical trial designs and the characterization of earlier and more specific target populations for trials in prodromal as well as in pre- and asymptomatic at-risk stages of AD.

Clinical workout for the early detection of cognitive decline and dementia

Aging is the major risk factor for the development of human neurodegenerative maladies such as Alzheimer's, Huntington's and Parkinson's diseases (PDs) and prion disorders, all of which stem from toxic protein aggregation. All of these diseases are correlated with cognitive decline. Cognitive Decline is a dynamic state from normal cognition of aging to dementia. According to the original criteria for Alzheimer's Disease (AD) (1984), a clinical diagnosis was possible only when someone was already demented. The prevalence rates of Cognitive Decline (mild cognitive impairment plus dementia) are very high now and will be higher in future because of the increasing survival time of people. Many neurological and psychiatric diseases are correlated with cognitive decline. Diagnosis of cognitive decline is mostly clinical (clinical criteria), but there are multiple biomarkers that could help us mostly in research programs such as short or long, paper and pencil or computerized neuropsychological batteries for cognition, activities of daily living and behavior, electroencephalograph, event-related potentials, and imaging-structural magnetic resonance imaging (MRI) and functional (fMRI, Pittsburgh bound positron emission tomography, FDG-PET, single photon emission computerized tomography and imaging of tau pathology)-cerebrospinal fluid proteins (Abeta, tau and phospho-tau in AD and α-synuclein (αSyn) for PD). Blood biomarkers need more studies to confirm their usefulness. Genetic markers are also studied but until now are not used in clinical praxis. Finally, in everyday clinical praxis and in research workout for early detection of cognitive decline, the combination of biomarkers is useful.

Mild cognitive impairment

Mild cognitive impairment is the term applied to the cognitive state that lies between normal aging and dementia. There has been significant controversy around describing, defining and characterizing mild cognitive impairment. This review will cover current understanding of the condition and discuss clinical features, research strategies and future directions.