Biomarker-based prognosis for people with mild cognitive impairment (ABIDE): a modelling study

Blood-based biomarkers for Alzheimer's disease: towards clinical implementation

For many years, blood-based biomarkers for Alzheimer's disease seemed unattainable, but recent results have shown that they could become a reality. Convincing data generated with new high-sensitivity assays have emerged with remarkable consistency across different cohorts, but also independent of the precise analytical method used. Concentrations in blood of amyloid and phosphorylated tau proteins associate with the corresponding concentrations in CSF and with amyloid-PET or tau-PET scans. Moreover, other blood-based biomarkers of neurodegeneration, such as neurofilament light chain and glial fibrillary acidic protein, appear to provide information on disease progression and potential for monitoring treatment effects. Now the question emerges of when and how we can bring these biomarkers to clinical practice. This step would pave the way for blood-based biomarkers to support the diagnosis of, and development of treatments for, Alzheimer's disease and other dementias.

Societal and equity challenges for Brain Health Services. A user manual for Brain Health Services-part 6 of 6

Brain Health Services are a novel approach to the personalized prevention of dementia. In this paper, we consider how such services can best reflect their social, cultural, and economic context and, in doing so, deliver fair and equitable access to risk reduction. We present specific areas of challenge associated with the social context for dementia prevention. The first concentrates on how Brain Health Services engage with the "at-risk" individual, recognizing the range of factors that shape an individual's risk of dementia and the efficacy of risk reduction measures. The second emphasizes the social context of Brain Health Services themselves and their ability to provide equitable access to risk reduction. We then elaborate proposals for meeting or mitigating these challenges. We suggest that considering these challenges will enable Brain Health Services to address two fundamental questions: the balance between an individualized "high-risk" and population focus for public health prevention and the ability of services to meet ethical standards of justice and health equity.

Dementia risk communication. A user manual for Brain Health Services-part 3 of 6

Growing evidence suggests dementia incidence can be reduced through prevention programs targeting risk factors. To accelerate the implementation of such prevention programs, a new generation of brain health services (BHS) is envisioned, involving risk profiling, risk communication, risk reduction, and cognitive enhancement. The purpose of risk communication is to enable individuals at risk to make informed decisions and take action to protect themselves and is thus a crucial step in tailored prevention strategies of the dementia incidence. However, communicating about dementia risk is complex and challenging.In this paper, we provide an overview of (i) perspectives on communicating dementia risk from an ethical, clinical, and societal viewpoint; (ii) insights gained from memory clinical practice; (iii) available evidence on the impact of disclosing APOE and Alzheimer's disease biomarker test results gathered from clinical trials and observational studies; (iv) the value of established registries in light of BHS; and (v) practical recommendations regarding effective strategies for communicating about dementia risk.In addition, we identify challenges, i.e., the current lack of evidence on what to tell on an individual level-the actual risk-and on how to optimally communicate about dementia risk, especially concerning worried yet cognitively unimpaired individuals. Ideally, dementia risk communication strategies should maximize the desired impact of risk information on individuals' understanding of their health/disease status and risk perception and minimize potential harms. More research is thus warranted on the impact of dementia risk communication, to (1) evaluate the merits of different approaches to risk communication on outcomes in the cognitive, affective and behavioral domains, (2) develop an evidence-based, harmonized dementia risk communication protocol, and (3) develop e-tools to support and promote adherence to this protocol in BHSs.Based on the research reviewed, we recommend that dementia risk communication should be precise; include the use of absolute risks, visual displays, and time frames; based on a process of shared decision-making; and address the inherent uncertainty that comes with any probability.

Abnormal tau in amyloid PET negative individuals

We examined the characteristics of individuals with biomarker evidence of tauopathy but without β-amyloid (Aβ) (A-T+) in relation to individuals with (A+T+) and without (A-T-) evidence of Alzheimer's disease (AD). We included 561 participants with Aβ and tau PET from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We compared A-T- (n = 316), A-T+ (n = 63), and A+T+ (n = 182) individuals on demographics, amyloid, tau, hippocampal volumes, and cognition. A-T+ individuals were low on apolipoprotein E ɛ4 prevalence (17%) and had no evidence of subtly elevated brain Aβ within the negative range. The severity of tau deposition, hippocampal atrophy, and cognitive dysfunction in the A-T+ group was intermediate between A-T- and A+T+ (all p < 0.001). Tau uptake patterns in A-T+ individuals were heterogeneous, but approximately 29% showed tau deposition in the medial temporal lobe only, consistent with primary age-related tauopathy and an additional 32% showed a pattern consistent with AD. A-T+ individuals also share other features that are characteristic of AD such as cognitive impairment and neurodegeneration, but this group is heterogeneous and likely reflects more than one disorder.

Personalized prediction of progression in pre-dementia patients based on individual biomarker profile: A development and validation study

INTRODUCTION

The prognosis of patients at the pre-dementia stage is difficult to define. The aim of this study is to develop and validate a biomarker-based continuous model for predicting the individual cognitive level at any future moment. In addition to personalized prognosis, such a model could reduce trial sample size requirements by allowing inclusion of a homogenous patient population.

METHODS

Disease-progression modeling of longitudinal cognitive scores of pre-dementia patients (baseline Clinical Dementia Rating ≤ 0.5) was used to derive a biomarker profile that was predictive of patient's cognitive progression along the dementia continuum. The biomarker profile model was developed and validated in the MEMENTO cohort and externally validated in the Alzheimer's Disease Neuroimaging Initiative.

RESULTS

Of nine candidate biomarkers in the development analysis, three cerebrospinal fluid and two magnetic resonance imaging measures were selected to form the final biomarker profile. The model-based prognosis of individual future cognitive deficit was shown to significantly improve when incorporating biomarker information on top of cognition and demographic data. In trial power calculations, adjusting the primary analysis for the baseline biomarker profile reduced sample size requirements by ≈10%. Compared to conventional cognitive cut-offs, inclusion criteria based on biomarker-profile cut-offs resulted in up to 28% reduced sample size requirements due to increased homogeneity in progression patterns.

DISCUSSION

The biomarker profile allows prediction of personalized trajectories of future cognitive progression. This enables accurate personalized prognosis in clinical care and better selection of patient populations for clinical trials. A web-based application for prediction of patients' future cognitive progression is available online.

Identifying relevant outcomes in the progression of Alzheimer's disease; what do patients and care partners want to know about prognosis?

BACKGROUND

Prognostic studies in the context of Alzheimer's disease (AD) mainly predicted time to dementia. However, it is questionable whether onset of dementia is the most relevant outcome along the AD disease trajectory from the perspective of patients and their care partners. Therefore, we aimed to identify the most relevant outcomes from the viewpoint of patients and care partners.

METHODS

We used a two-step, mixed-methods approach. As a first step we conducted four focus groups in the Netherlands to elicit a comprehensive list of outcomes considered important by patients (n = 12) and care partners (n = 14) in the prognosis of AD. The focus groups resulted in a list of 59 items, divided into five categories. Next, in an online European survey, we asked participants (n = 232; 99 patients, 133 care partners) to rate the importance of all 59 items (5-point Likert scale). As participants were likely to rate a large number of outcomes as "important" (4) or "very important" (5), we subsequently asked them to select the three items they considered most important.

RESULTS

The top-10 lists of items most frequently mentioned as "most important" by patients and care partners were merged into one core outcome list, comprising 13 items. Both patients and care partners selected outcomes from the category "cognition" most often, followed by items in the categories "functioning and dependency" and "physical health." No items from the category "behavior and neuropsychiatry" and "social environment" ended up in our core list of relevant outcomes.

CONCLUSION

We identified a core list of outcomes relevant to patients and care partner, and found that prognostic information related to cognitive decline, dependency, and physical health are considered most relevant by both patients and their care partners.

F-18 ML-104 tau PET imaging in mild cognitive impairment

OBJECTIVE

This study was undertaken to evaluate the tau distribution patterns in patients with amnestic mild cognitive impairment (aMCI) using PET radiotracer F-18 ML-104.

MATERIALS AND METHODS

Thirty patients, clinically diagnosed as aMCI [mini mental state evaluation ≥24] in the neurology or geriatric memory clinics, were included in the study. Each aMCI patient underwent F-18 fluorodeoxyglucose and F-18 ML-104 tau PET. Standardized uptake value ratios for cortical gray matter regions were evaluated for F-18 ML-104 tau PET and compared with normal controls and with early Alzheimer's disease (AD) patients (used from a previous study).

RESULTS

aMCI revealed significantly higher standardized uptake value ratios in both medial temporal cortices, precuneus and posterior cingulate cortices in comparison to normal controls and a significantly lesser binding in bilateral medial and lateral temporal, precuneus and posterior cingulate cortices in comparison to early AD. A negative correlation was noted between F-18 fluorodeoxyglucose uptake and F-18 ML-104 retention in the precuneus and posterior cingulate cortices in aMCI, while F-18 ML-104 retention and mini mental state evaluation scores revealed a moderate negative correlation in the posterior cingulate cortices.

CONCLUSION

We could demonstrate a significant increase in cortical tau deposition in aMCI patients in comparison to normal controls, thus providing in vivo evidence of the underlying pathological process in this subgroup of patients with high probability of conversion to AD.

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

BACKGROUND AND PURPOSE

Careful counseling through the diagnostic process and adequate postdiagnostic support in patients with mild cognitive impairment (MCI) is important. Previous studies have indicated heterogeneity in practice and the need for guidance for clinicians.

METHODS

A joint European Academy of Neurology/European Alzheimer's Disease Consortium panel of dementia specialists was appointed. Through online meetings and emails, positions were developed regarding disclosing a syndrome diagnosis of MCI, pre- and postbiomarker sampling counseling, and postdiagnostic support.

RESULTS

Prior to diagnostic evaluation, motives and wishes of the patient should be sought. Diagnostic disclosure should be carried out by a dementia specialist taking the ethical principles of "the right to know" versus "the wish not to know" into account. Disclosure should be accompanied by written information and a follow-up plan. It should be made clear that MCI is not dementia. Prebiomarker counseling should always be carried out if biomarker sampling is considered and postbiomarker counseling if sampling is carried out. A dementia specialist knowledgeable about biomarkers should inform about pros and cons, including alternatives, to enable an autonomous and informed decision. Postbiomarker counseling will depend in part on the results of biomarkers. Follow-up should be considered for all patients with MCI and include brain-healthy advice and possibly treatment for specific underlying causes. Advice on advance directives may be relevant.

CONCLUSIONS

Guidance to clinicians on various aspects of the diagnostic process in patients with MCI is presented here as position statements. Further studies are needed to enable more evidence-based and standardized recommendations in the future.

Plasma biomarkers of Alzheimer's disease improve prediction of cognitive decline in cognitively unimpaired elderly populations

Plasma biomarkers of amyloid, tau, and neurodegeneration (ATN) need to be characterized in cognitively unimpaired (CU) elderly individuals. We therefore tested if plasma measurements of amyloid-β (Aβ)42/40, phospho-tau217 (P-tau217), and neurofilament light (NfL) together predict clinical deterioration in 435 CU individuals followed for an average of 4.8 ± 1.7 years in the BioFINDER study. A combination of all three plasma biomarkers and basic demographics best predicted change in cognition (Pre-Alzheimer's Clinical Composite; R2 = 0.14, 95% CI [0.12-0.17]; P < 0.0001) and subsequent AD dementia (AUC = 0.82, 95% CI [0.77-0.91], P < 0.0001). In a simulated clinical trial, a screening algorithm combining all three plasma biomarkers would reduce the required sample size by 70% (95% CI [54-81]; P < 0.001) with cognition as trial endpoint, and by 63% (95% CI [53-70], P < 0.001) with subsequent AD dementia as trial endpoint. Plasma ATN biomarkers show usefulness in cognitively unimpaired populations and could make large clinical trials more feasible and cost-effective.

Developing an Explainable Machine Learning-Based Personalised Dementia Risk Prediction Model: A Transfer Learning Approach With Ensemble Learning Algorithms

Alzheimer's disease (AD) has its onset many decades before dementia develops, and work is ongoing to characterise individuals at risk of decline on the basis of early detection through biomarker and cognitive testing as well as the presence/absence of identified risk factors. Risk prediction models for AD based on various computational approaches, including machine learning, are being developed with promising results. However, these approaches have been criticised as they are unable to generalise due to over-reliance on one data source, poor internal and external validations, and lack of understanding of prediction models, thereby limiting the clinical utility of these prediction models. We propose a framework that employs a transfer-learning paradigm with ensemble learning algorithms to develop explainable personalised risk prediction models for dementia. Our prediction models, known as source models, are initially trained and tested using a publicly available dataset (n = 84,856, mean age = 69 years) with 14 years of follow-up samples to predict the individual risk of developing dementia. The decision boundaries of the best source model are further updated by using an alternative dataset from a different and much younger population (n = 473, mean age = 52 years) to obtain an additional prediction model known as the target model. We further apply the SHapely Additive exPlanation (SHAP) algorithm to visualise the risk factors responsible for the prediction at both population and individual levels. The best source model achieves a geometric accuracy of 87%, specificity of 99%, and sensitivity of 76%. In comparison to a baseline model, our target model achieves better performance across several performance metrics, within an increase in geometric accuracy of 16.9%, specificity of 2.7%, and sensitivity of 19.1%, an area under the receiver operating curve (AUROC) of 11% and a transfer learning efficacy rate of 20.6%. The strength of our approach is the large sample size used in training the source model, transferring and applying the "knowledge" to another dataset from a different and undiagnosed population for the early detection and prediction of dementia risk, and the ability to visualise the interaction of the risk factors that drive the prediction. This approach has direct clinical utility.

Alzheimer's disease

In this Seminar, we highlight the main developments in the field of Alzheimer's disease. The most recent data indicate that, by 2050, the prevalence of dementia will double in Europe and triple worldwide, and that estimate is 3 times higher when based on a biological (rather than clinical) definition of Alzheimer's disease. The earliest phase of Alzheimer's disease (cellular phase) happens in parallel with accumulating amyloid β, inducing the spread of tau pathology. The risk of Alzheimer's disease is 60-80% dependent on heritable factors, with more than 40 Alzheimer's disease-associated genetic risk loci already identified, of which the APOE alleles have the strongest association with the disease. Novel biomarkers include PET scans and plasma assays for amyloid β and phosphorylated tau, which show great promise for clinical and research use. Multidomain lifestyle-based prevention trials suggest cognitive benefits in participants with increased risk of dementia. Lifestyle factors do not directly affect Alzheimer's disease pathology, but can still contribute to a positive outcome in individuals with Alzheimer's disease. Promising pharmacological treatments are poised at advanced stages of clinical trials and include anti-amyloid β, anti-tau, and anti-inflammatory strategies.

Recent Advances in Imaging of Preclinical, Sporadic, and Autosomal Dominant Alzheimer's Disease

Observing Alzheimer's disease (AD) pathological changes in vivo with neuroimaging provides invaluable opportunities to understand and predict the course of disease. Neuroimaging AD biomarkers also allow for real-time tracking of disease-modifying treatment in clinical trials. With recent neuroimaging advances, along with the burgeoning availability of longitudinal neuroimaging data and big-data harmonization approaches, a more comprehensive evaluation of the disease has shed light on the topographical staging and temporal sequencing of the disease. Multimodal imaging approaches have also promoted the development of data-driven models of AD-associated pathological propagation of tau proteinopathies. Studies of autosomal dominant, early sporadic, and late sporadic courses of the disease have shed unique insights into the AD pathological cascade, particularly with regard to genetic vulnerabilities and the identification of potential drug targets. Further, neuroimaging markers of b-amyloid, tau, and neurodegeneration have provided a powerful tool for validation of novel fluid cerebrospinal and plasma markers. This review highlights some of the latest advances in the field of human neuroimaging in AD across these topics, particularly with respect to positron emission tomography and structural and functional magnetic resonance imaging.

Evaluation of the ATN model in a longitudinal memory clinic sample with different underlying disorders

INTRODUCTION

To evaluate the usefulness of the 2018 NIA-AA (National Institute on Aging and Alzheimer's Association) research framework in a longitudinal memory clinic study with different clinical outcomes and underlying disorders.

METHODS

We included 420 patients with mild cognitive impairment or subjective cognitive impairment. During the follow up, 27% of the patients converted to dementia, with the majority converting to Alzheimer's disease (AD) or mixed dementia. Based on the baseline values of the cerebrospinal fluid biomarkers, the patients were classified into one of the eight possible ATN groups (amyloid beta [Aβ] aggregation [A], tau aggregation reflecting neurofibrillary tangles [T], and neurodegeneration [N]).

RESULTS

The majority of the patients converting to AD and mixed dementia were in ATN groups positive for A (71%). The A+T+N+ group was highly overrepresented among converters to AD and mixed dementia. Patients converting to dementias other than AD or mixed dementia were evenly distributed across the ATN groups.

DISCUSSION

Our findings provide support for the usefulness of the ATN system to detect incipient AD or mixed dementia.

2020 update on the clinical validity of cerebrospinal fluid amyloid, tau, and phospho-tau as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework

Purpose

In the last decade, the research community has focused on defining reliable biomarkers for the early detection of Alzheimer’s disease (AD) pathology. In 2017, the Geneva AD Biomarker Roadmap Initiative adapted a framework for the systematic validation of oncological biomarkers to cerebrospinal fluid (CSF) AD biomarkers—encompassing the 42 amino-acid isoform of amyloid-β (Aβ42), phosphorylated-tau (P-tau), and Total-tau (T-tau)—with the aim to accelerate their development and clinical implementation. The aim of this work is to update the current validation status of CSF AD biomarkers based on the Biomarker Roadmap methodology.

Methods

A panel of experts in AD biomarkers convened in November 2019 at a 2-day workshop in Geneva. The level of maturity (fully achieved, partly achieved, preliminary evidence, not achieved, unsuccessful) of CSF AD biomarkers was assessed based on the Biomarker Roadmap methodology before the meeting and presented and discussed during the workshop.

Results

By comparison to the previous 2017 Geneva Roadmap meeting, the primary advances in CSF AD biomarkers have been in the area of a unified protocol for CSF sampling, handling and storage, the introduction of certified reference methods and materials for Aβ42, and the introduction of fully automated assays. Additional advances have occurred in the form of defining thresholds for biomarker positivity and assessing the impact of covariates on their discriminatory ability.

Conclusions

Though much has been achieved for phases one through three, much work remains in phases four (real world performance) and five (assessment of impact/cost). To a large degree, this will depend on the availability of disease-modifying treatments for AD, given these will make accurate and generally available diagnostic tools key to initiate therapy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05258-7.

Association of Klotho-VS Heterozygosity With Risk of Alzheimer Disease in Individuals Who Carry APOE4

Importance

Identification of genetic factors that interact with the apolipoprotein e4 (APOE4) allele to reduce risk for Alzheimer disease (AD) would accelerate the search for new AD drug targets. Klotho-VS heterozygosity (KL-VSHET+ status) protects against aging-associated phenotypes and cognitive decline, but whether it protects individuals who carry APOE4 from AD remains unclear.

Objectives

To determine if KL-VSHET+ status is associated with reduced AD risk and β-amyloid (Aβ) pathology in individuals who carry APOE4.

Design, Setting, and Participants

This study combined 25 independent case-control, family-based, and longitudinal AD cohorts that recruited referred and volunteer participants and made data available through public repositories. Analyses were stratified by APOE4 status. Three cohorts were used to evaluate conversion risk, 1 provided longitudinal measures of Aβ CSF and PET, and 3 provided cross-sectional measures of Aβ CSF. Genetic data were available from high-density single-nucleotide variant microarrays. All data were collected between September 2015 and September 2019 and analyzed between April 2019 and December 2019.

Main Outcomes and Measures

The risk of AD was evaluated through logistic regression analyses under a case-control design. The risk of conversion to mild cognitive impairment (MCI) or AD was evaluated through competing risks regression. Associations with Aβ, measured from cerebrospinal fluid (CSF) or brain positron emission tomography (PET), were evaluated using linear regression and mixed-effects modeling.

Results

Of 36 530 eligible participants, 13 782 were excluded for analysis exclusion criteria or refusal to participate. Participants were men and women aged 60 years and older who were non-Hispanic and of Northwestern European ancestry and had been diagnosed as being cognitively normal or having MCI or AD. The sample included 20 928 participants in case-control studies, 3008 in conversion studies, 556 in Aβ CSF regression analyses, and 251 in PET regression analyses. The genotype KL-VSHET+ was associated with reduced risk for AD in individuals carrying APOE4 who were 60 years or older (odds ratio, 0.75 [95% CI, 0.67-0.84]; P = 7.4 × 10-7), and this was more prominent at ages 60 to 80 years (odds ratio, 0.69 [95% CI, 0.61-0.79]; P = 3.6 × 10-8). Additionally, control participants carrying APOE4 with KL-VS heterozygosity were at reduced risk of converting to MCI or AD (hazard ratio, 0.64 [95% CI, 0.44-0.94]; P = .02). Finally, in control participants who carried APOE4 and were aged 60 to 80 years, KL-VS heterozygosity was associated with higher Aβ in CSF (β, 0.06 [95% CI, 0.01-0.10]; P = .03) and lower Aβ on PET scans (β, -0.04 [95% CI, -0.07 to -0.00]; P = .04).

Conclusions and Relevance

The genotype KL-VSHET+ is associated with reduced AD risk and Aβ burden in individuals who are aged 60 to 80 years, cognitively normal, and carrying APOE4. Molecular pathways associated with KL merit exploration for novel AD drug targets. The KL-VS genotype should be considered in conjunction with the APOE genotype to refine AD prediction models used in clinical trial enrichment and personalized genetic counseling.

Biomarker testing in MCI patients-deciding who to test

BACKGROUND

We aimed to derive an algorithm to define the optimal proportion of patients with mild cognitive impairment (MCI) in whom cerebrospinal fluid (CSF) testing is of added prognostic value.

METHODS

MCI patients were selected from the Amsterdam Dementia Cohort (n = 402). Three-year progression probabilities to dementia were predicted using previously published models with and without CSF data (amyloid-beta1-42 (Abeta), phosphorylated tau (p-tau)). We incrementally augmented the proportion of patients undergoing CSF, starting with the 10% patients with prognostic probabilities based on clinical data around the median (percentile 45-55), until all patients received CSF. The optimal proportion was defined as the proportion where the stepwise algorithm showed similar prognostic discrimination (Harrell's C) and accuracy (three-year Brier scores) compared to CSF testing of all patients. We used the BioFINDER study (n = 221) for validation.

RESULTS

The optimal proportion of MCI patients to receive CSF testing selected by the stepwise approach was 50%. CSF testing in only this proportion improved the performance of the model with clinical data only from Harrell's C = 0.60, Brier = 0.198 (Harrell's C = 0.61, Brier = 0.197 if the information on magnetic resonance imaging was available) to Harrell's C = 0.67 and Brier = 0.190, and performed similarly to a model in which all patients received CSF testing. Applying the stepwise approach in the BioFINDER study would again select half of the MCI patients and yielded robust results with respect to prognostic performance.

INTERPRETATION

CSF biomarker testing adds prognostic value in half of the MCI patients. As such, we achieve a CSF saving recommendation while simultaneously retaining optimal prognostic accuracy.

Validation of the Alzheimer Disease Dementia Conversion-Related Pattern as an ATN Biomarker of Neurodegeneration

OBJECTIVE

To determine whether the Alzheimer disease (AD) dementia conversion-related pattern (ADCRP) on [¹⁸F]FDG PET can serve as a valid predictor for the development of AD dementia, the individual expression of the ADCRP (subject score) and its prognostic value were examined in patients with mild cognitive impairment (MCI) and biologically defined AD.

METHODS

A total of 269 patients with available [¹⁸F]FDG PET, [¹⁸F]AV-45 PET, phosphorylated and total tau in CSF, and neurofilament light chain in plasma were included. Following the AT(N) classification scheme, where AD is defined biologically by in vivo biomarkers of β-amyloid (Aβ) deposition ("A") and pathologic tau ("T"), patients were categorized to the A-T-, A+T-, A+T+ (AD), and A-T+ groups.

RESULTS

The mean subject score of the ADCRP was significantly higher in the A+T+ group compared to each of the other group (all p < 0.05) but was similar among the latter (all p > 0.1). Within the A+T+ group, the subject score of ADCRP was a significant predictor of conversion to dementia (hazard ratio, 2.02 per z score increase; p < 0.001), with higher predictive value than of alternative biomarkers of neurodegeneration (total tau and neurofilament light chain). Stratification of A+T+ patients by the subject score of ADCRP yielded well-separated groups of high, medium, and low conversion risks.

CONCLUSIONS

The ADCRP is a valuable biomarker of neurodegeneration in patients with MCI and biologically defined AD. It shows great potential for stratifying the risk and estimating the time to conversion to dementia in patients with MCI and underlying AD (A+T+).

CLASSIFICATION OF EVIDENCE

This study provides Class I evidence that [¹⁸F]FDG PET predicts the development of AD dementia in individuals with MCI and underlying AD as defined by the AT(N) framework.

Individualized prognosis of cognitive decline and dementia in mild cognitive impairment based on plasma biomarker combinations

We developed models for individualized risk prediction of cognitive decline in mild cognitive impairment (MCI) using plasma biomarkers of β-amyloid (Aβ), tau and neurodegeneration. A total of 573 patients with MCI from the Swedish BioFINDER study and the Alzheimer's Disease Neuroimaging Initiative (ADNI) were included in the study. The primary outcomes were longitudinal cognition and conversion to Alzheimer's disease (AD) dementia. A model combining tau phosphorylated at threonine 181 (P-tau181) and neurofilament light (NfL), but not Aβ₄₂/Aβ₄₀, had the best prognosis performance of all models (area under the curve = 0.88 for 4-year conversion to AD in BioFINDER, validated in ADNI), was stronger than a basic model of age, sex, education and baseline cognition, and performed similarly to cerebrospinal fluid biomarkers. A publicly available online tool for individualized prognosis in MCI based on our combined plasma biomarker models is introduced. Combination of plasma biomarkers may be of high value to identify individuals with MCI who will progress to AD dementia in clinical trials and in clinical practice.

[Early detection of Alzheimer's disease and dementia prediction in patients with mild cognitive impairment : Summary of current recommendations]

Mild cognitive impairment (MCI) is characterized by cognitive deficits but essentially preserved competence in activities of daily living. It is a risk factor for the development of dementia and can reflect a prodromal predementia state of Alzheimer's disease (AD). The pathology of AD is defined by cerebral deposition of amyloid-beta-1-42 protein and aggregation of phosphorylated tau protein, which can be identified in vivo by biomarkers for these alterations. As a result of advances in the field of biomarker-based early detection of AD, it is possible to differentiate between MCI patients with and without a pathological AD condition and therefore, between patients with a low and those with a high risk for the development of dementia. At present there are no specific guideline recommendations in Germany for the diagnostic use of biomarkers in predementia detection of AD and for dementia risk assessment in patients with MCI. This article summarizes the current recommendations of a European expert consensus publication and a multidisciplinary working group of the Alzheimer's Association on the clinical application of cerebrospinal fluid (CSF) biomarkers for the diagnostics of AD in patients with MCI. If the clinical diagnostic criteria for MCI are fulfilled according to the medical history and neuropsychological testing, it is recommended to carry out further diagnostics (blood test, brain imaging) in order to more precisely define the differential diagnostic classification. Counseling on the potential benefits, limits and risks of biomarker testing for early AD detection and dementia risk prediction should always precede assessment of CSF biomarkers. Information about the individual risk of developing dementia has potential consequences for the psychological well-being and life planning; therefore, clinical follow-up visits are recommended.

Use of Cerebrospinal Fluid Biomarkers of Alzheimer's Disease Risk in Mild Cognitive Impairment and Subjective Cognitive Decline in Routine Clinical Care in Germany

BACKGROUND

The National Institute of Aging and Alzheimer's Association's diagnostic recommendations for preclinical Alzheimer's disease (AD) and mild cognitive impairment (MCI) define AD by pathological processes which can be detected by biomarkers. These criteria were established as part of a research framework intended for research purposes but progressively enter the clinical practice.

OBJECTIVE

We investigated the availability, frequency of use, interpretation, and therapeutic implications of biomarkers for the etiologic diagnosis and prognosis in MCI and subjective cognitive decline (SCD) in routine clinical care.

METHODS

We conducted a cross-sectional questionnaire survey among 215 expert dementia centers (hospitals and memory clinics) in Germany.

RESULTS

From the 98 centers (45.6% of contacted centers) included, two-thirds reported use of the cerebrospinal fluid (CSF) biomarkers Aβ42, tau, and phospho-tau in the diagnostic workup of MCI and one third in SCD. CSF biomarker analysis was more often employed by neurological (MCI 84%; SCD 42%) compared to psychiatric institutions (MCI 61%; SCD 33%; p≤0.001). Although dementia experts disagreed on the risk of progression associated with different CSF biomarker constellations, CSF biomarker results guided therapeutic decisions: ∼40% of responders reported to initiate cholinesterase inhibitor therapy in MCI and 18% in SCD (p = 0.006), given that all CSF biomarkers were in the pathological range.

CONCLUSION

Considering the vast heterogeneity among dementia expert centers in use of CSF biomarker analysis, interpretation of results, and therapeutic consequences, a standardization of biomarker-based diagnosis practice in pre-dementia stages is needed.

[Memory clinics in Germany-structural requirements and areas of responsibility]

Hintergrund

Gedächtnisambulanzen (GA) sind auf (Differenzial‑)Diagnostik, Therapie, Aufklärung, Management und Beratung von kognitiven Störungen im Alter und deren Risikostadien spezialisierte Einrichtungen. In der Praxis haben sie sehr unterschiedliche Organisationsformen. Aufgrund der wachsenden diagnostischen Möglichkeiten bei neurodegenerativen Erkrankungen, dem steigenden Bedarf an Früherkennung und Prädiktion sowie absehbaren neuen diagnostischen Verfahren und krankheitsmodifizierenden Therapien ist eine Vereinheitlichung der strukturellen Voraussetzungen und Aufgabenbereiche für GA sinnvoll.

Ziel der Arbeit

Der Artikel macht Vorschläge für strukturelle und organisatorische Voraussetzungen, Aufgaben sowie einheitliche Arbeitsweisen von GA in Deutschland.

Methoden

Expertenkonsens von Psychiatern, Neurologen und Geriatern aus universitären und außeruniversitären Einrichtungen.

Ergebnisse

Gedächtnisambulanzen sollen den Facharztstandard für Psychiatrie und/oder Neurologie vorhalten und sich in ihrer Arbeitsweise bez. (Differenzial‑)Diagnostik und Therapie von Demenzen eng an der S3-Leitlinie (S3LL-)Demenz orientieren. In Bezug auf Früherkennung und Prädiktion neurodegenerativer Erkrankungen gehen sie über die S3LL-Demenz hinaus. So werden leichte kognitive Störungen (MCI) als Risiko- oder auch Prodromalstadien neurodegenerativer Demenzen verstanden und Biomarker regelhaft für eine ätiologische (Früh- und Differenzial‑)Diagnostik eingesetzt. Es soll eine enge Vernetzung mit den diagnostischen Fachdisziplinen bestehen. Ferner sollen sie Beratung zu sozialen und rechtlichen Fragen sowie Angehörigenberatung anbieten. Aktuelle Erkenntnisse aus der Forschung sollen durch sie frühzeitig in die Versorgung integriert werden. GA sind damit regionale Expertenzentren.

Diskussion

Gedächtnisambulanzen implementieren den evidenzbasierten Standard in Diagnostik und Therapie in die klinische Versorgung von Patienten mit kognitiven Störungen im Alter. Zusätzlich führen sie diagnostische und therapeutische Innovationen in die Versorgung dieser Patienten ein. Ihre Rolle in der Regelversorgung muss gestärkt werden, wobei auch Finanzierungsfragen geklärt werden müssen, da die derzeitigen Finanzierungsmodelle in der Regel nicht kostendeckend sind.

Functional cognitive disorder: dementia's blind spot

An increasing proportion of cognitive difficulties are recognized to have a functional cause, the chief clinical indicator of which is internal inconsistency. When these symptoms are impairing or distressing, and not better explained by other disorders, this can be conceptualized as a cognitive variant of functional neurological disorder, termed functional cognitive disorder (FCD). FCD is likely very common in clinical practice but may be under-diagnosed. Clinicians in many settings make liberal use of the descriptive term mild cognitive impairment (MCI) for those with cognitive difficulties not impairing enough to qualify as dementia. However, MCI is an aetiology-neutral description, which therefore includes patients with a wide range of underlying causes. Consequently, a proportion of MCI cases are due to non-neurodegenerative processes, including FCD. Indeed, significant numbers of patients diagnosed with MCI do not 'convert' to dementia. The lack of diagnostic specificity for MCI 'non-progressors' is a weakness inherent in framing MCI primarily within a deterministic neurodegenerative pathway. It is recognized that depression, anxiety and behavioural changes can represent a prodrome to neurodegeneration; empirical data are required to explore whether the same might hold for subsets of individuals with FCD. Clinicians and researchers can improve study efficacy and patient outcomes by viewing MCI as a descriptive term with a wide differential diagnosis, including potentially reversible components such as FCD. We present a preliminary definition of functional neurological disorder-cognitive subtype, explain its position in relation to other cognitive diagnoses and emerging biomarkers, highlight clinical features that can lead to positive diagnosis (as opposed to a diagnosis of exclusion), and red flags that should prompt consideration of alternative diagnoses. In the research setting, positive identifiers of FCD will enhance our recognition of individuals who are not in a neurodegenerative prodrome, while greater use of this diagnosis in clinical practice will facilitate personalized interventions.

Digital biomarker-based individualized prognosis for people at risk of dementia

Background

Research investigating treatments and interventions for cognitive decline fail due to difficulties in accurately recognizing behavioral signatures in the presymptomatic stages of the disease. For this validation study, we took our previously constructed digital biomarker‐based prognostic models and focused on generalizability and robustness of the models.

Method

We validated prognostic models characterizing subjects using digital biomarkers in a longitudinal, multi‐site, 40‐month prospective study collecting data in memory clinics, general practitioner offices, and home environments.

Results

Our models were able to accurately discriminate between healthy subjects and individuals at risk to progress to dementia within 3 years. The model was also able to differentiate between people with or without amyloid neuropathology and classify fast and slow cognitive decliners with a very good diagnostic performance.

Conclusion

Digital biomarker prognostic models can be a useful tool to assist large‐scale population screening for the early detection of cognitive impairment and patient monitoring over time.

Blood-based biomarkers for Alzheimer's pathology and the diagnostic process for a disease-modifying treatment: Projecting the impact on the cost and wait times

INTRODUCTION

Concerns have been raised about the limited health system capacity for identification of patients who are eligible for a disease-modifying Alzheimer's treatment (DMT). Blood-based biomarker (BBBM) tests are a promising tool to improve triaging at the primary care level. We projected their impact on cost of and wait times during the diagnostic process.

METHODS

We compare four scenarios for triaging patients at the primary care level from the perspective of the U.S. health care system: (1) cognitive test only (Mini Mental State Examination [MMSE]), (2) BBBM test only, (3) MMSE followed by BBBM if positive, and (4) BBBM followed by MMSE if positive.

RESULTS

Referring patients to dementa specialists based on MMSE or BBBM results alone would continuously require more specialist appointments than projected to be available until 2050. Combining MMSE and BBBM would eliminate wait lists after the first 3 years and reduce average annual cost by $400 to 700 million, while increasing correctly identified cases by about 120,000 per year.

DISCUSSION

The combination BBBM with MMSE is projected to increase the efficiency and value of the triage process for DMT eligibility.

Longitudinal evaluation of the natural history of amyloid-β in plasma and brain

Plasma amyloid-β peptide concentration has recently been shown to have high accuracy to predict amyloid-β plaque burden in the brain. These amyloid-β plasma markers will allow wider screening of the population and simplify and reduce screening costs for therapeutic trials in Alzheimer's disease. The aim of this study was to determine how longitudinal changes in blood amyloid-β track with changes in brain amyloid-β. Australian Imaging, Biomarker and Lifestyle study participants with a minimum of two assessments were evaluated (111 cognitively normal, 7 mild cognitively impaired, 15 participants with Alzheimer's disease). Amyloid-β burden in the brain was evaluated through PET and was expressed in Centiloids. Total protein amyloid-β 42/40 plasma ratios were determined using ABtest® assays. We applied our method for obtaining natural history trajectories from short term data to measures of total protein amyloid-β 42/40 plasma ratios and PET amyloid-β. The natural history trajectory of total protein amyloid-β 42/40 plasma ratios appears to approximately mirror that of PET amyloid-β, with both spanning decades. Rates of change of 7.9% and 8.8%, were observed for total protein amyloid-β 42/40 plasma ratios and PET amyloid-β, respectively. The trajectory of plasma amyloid-β preceded that of brain amyloid-β by a median value of 6 years (significant at 88% confidence interval). These findings, showing the tight association between changes in plasma and brain amyloid-β, support the use of plasma total protein amyloid-β 42/40 plasma ratios as a surrogate marker of brain amyloid-β. Also, that plasma total protein amyloid-β 42/40 plasma ratios has potential utility in monitoring trial participants, and as an outcome measure.

Progression to dementia in memory clinic patients with mild cognitive impairment and normal β-amyloid

Background

Determination of β-amyloid (Aβ) positivity and likelihood of underlying Alzheimer’s disease (AD) relies on dichotomous biomarker cut-off values. Individuals with mild cognitive impairment (MCI) and Aβ within the normal range may still have a substantial risk of developing dementia, primarily of Alzheimer type. Their prognosis, as well as predictors of clinical progression, are not fully understood. The aim of this study was to explore the associations of cerebrospinal fluid (CSF) biomarkers (Aβ42, total tau, phosphorylated tau) and other characteristics, including modifiable vascular factors, with the risk of progression to dementia among patients with MCI and normal CSF Aβ42.

Methods

Three hundred eighteen memory clinic patients with CSF and clinical data, and at least 1-year follow-up, were included. Patients had normal CSF Aβ42 levels based on clinical cut-offs. Cox proportional hazard models with age as time scale and adjusted for sex, education, and cognition (Mini-Mental State Examination) were used to investigate predictors of progression to dementia and Alzheimer-type dementia. Potential predictors included CSF biomarkers, cognitive performance (verbal learning and memory), apolipoprotein E (APOE) ε4 genotype, medial temporal lobe atrophy, family history of dementia, depressive symptoms, and vascular factors, including the Cardiovascular Risk Factors, Aging and Dementia (CAIDE) risk score. Predictive performance of patient characteristics was further explored with Harrell C statistic.

Results

Lower normal Aβ42 and higher total tau and phosphorylated tau were associated with higher dementia risk, and the association was not driven by Aβ42 values close to cut-off. Additional predictors included poorer cognition, APOE ε4 genotype, higher systolic blood pressure, and lower body mass index, but not the CAIDE dementia risk score. Aβ42 individually and in combination with other CSF biomarkers improved the risk prediction compared to age and cognition alone. Medial temporal lobe atrophy or vascular factors did not increase the predictive performance.

Conclusions

Possibility of underlying AD pathology and increased dementia risk should not be ruled out among MCI patients with CSF Aβ42 within the normal range. While cut-offs may be useful in clinical practice to identify high-risk individuals, personalized risk prediction tools incorporating continuous biomarkers may be preferable among individuals with intermediate risk. The role of modifiable vascular factors could be explored in this context.