Biomarkers for Alzheimer's disease therapeutic trials

Cerebrospinal fluid Aβ42, phosphorylated Tau181, and resting-state functional connectivity

IMPORTANCE

Resting-state functional connectivity magnetic resonance imaging has great potential for characterizing pathophysiological changes during the preclinical phase of Alzheimer disease.

OBJECTIVE

To assess the relationship between default mode network integrity and cerebrospinal fluid biomarkers of Alzheimer disease pathology in cognitively normal older individuals.

DESIGN, SETTING, AND PARTICIPANTS

Cross-sectional cohort study at The Charles F. and Joanne Knight Alzheimer's Disease Research Center at Washington University in St Louis, St Louis, Missouri, among 207 older adults with normal cognition (Clinical Dementia Rating, 0).

MAIN OUTCOMES AND MEASURES

Resting-state functional connectivity magnetic resonance imaging measures of default mode network integrity.

RESULTS

Decreased cerebrospinal fluid Aβ42 and increased cerebrospinal fluid phosphorylated tau181 were independently associated with reduced default mode network integrity, with the most prominent decreases in functional connectivity observed between the posterior cingulate and medial temporal regions. Observed reductions in functional connectivity were unattributable to age or structural atrophy in the posterior cingulate and medial temporal areas. Similar resting-state functional connectivity magnetic resonance imaging findings in relation to cerebrospinal fluid biomarkers were obtained using region-of-interest analyses and voxelwise correlation mapping.

CONCLUSIONS AND RELEVANCE

Both Aβ and tau pathology affect default mode network integrity before clinical onset of Alzheimer disease.

Network-based biomarkers in Alzheimer's disease: review and future directions

By 2050 it is estimated that the number of worldwide Alzheimer's disease (AD) patients will quadruple from the current number of 36 million people. To date, no single test, prior to postmortem examination, can confirm that a person suffers from AD. Therefore, there is a strong need for accurate and sensitive tools for the early diagnoses of AD. The complex etiology and multiple pathogenesis of AD call for a system-level understanding of the currently available biomarkers and the study of new biomarkers via network-based modeling of heterogeneous data types. In this review, we summarize recent research on the study of AD as a connectivity syndrome. We argue that a network-based approach in biomarker discovery will provide key insights to fully understand the network degeneration hypothesis (disease starts in specific network areas and progressively spreads to connected areas of the initial loci-networks) with a potential impact for early diagnosis and disease-modifying treatments. We introduce a new framework for the quantitative study of biomarkers that can help shorten the transition between academic research and clinical diagnosis in AD.

Fluid biomarkers for diagnosing dementia: rationale and the Canadian Consensus on Diagnosis and Treatment of Dementia recommendations for Canadian physicians

Fluid biomarkers improve the diagnostic accuracy in dementia and provide an objective measure potentially useful as a therapeutic response in clinical trials. The role of fluid biomarkers in patient care is a rapidly evolving field. Here, we provide a review and recommendations regarding the use of fluid biomarkers in clinical practice as discussed at the Fourth Canadian Consensus Conference on the Diagnosis and Treatment of Dementia (CCCDTD4) convened in Montreal, 4 to 5 May 2012. At present, there is no consensus regarding the optimal methodology for conducting quantification of plasma amyloid-beta (Aβ) peptides. In addition, since there is insufficient evidence supporting clinical applications for plasma Aβ-peptide measures, the CCCDTD4 does not recommended plasma biomarkers either for primary care or for specialists. Evidence for CSF Aβ1-42, total tau and phosphorylated tau in the diagnosis of Alzheimer pathology is much stronger, and can be considered at the tertiary care level for selected cases to improve diagnostic certainty, particularly in those cases presenting atypical clinical features.

Perspective on future role of biological markers in clinical therapy trials of Alzheimer's disease: a long-range point of view beyond 2020

Recent advances in understanding the molecular mechanisms underlying various paths toward the pathogenesis of Alzheimer's disease (AD) has begun to provide new insight for interventions to modify disease progression. The evolving knowledge gained from multidisciplinary basic research has begun to identify new concepts for treatments and distinct classes of therapeutic targets; as well as putative disease-modifying compounds that are now being tested in clinical trials. There is a mounting consensus that such disease modifying compounds and/or interventions are more likely to be effectively administered as early as possible in the cascade of pathogenic processes preceding and underlying the clinical expression of AD. The budding sentiment is that "treatments" need to be applied before various molecular mechanisms converge into an irreversible pathway leading to morphological, metabolic and functional alterations that characterize the pathophysiology of AD. In light of this, biological indicators of pathophysiological mechanisms are desired to chart and detect AD throughout the asymptomatic early molecular stages into the prodromal and early dementia phase. A major conceptual development in the clinical AD research field was the recent proposal of new diagnostic criteria, which specifically incorporate the use of biomarkers as defining criteria for preclinical stages of AD. This paradigm shift in AD definition, conceptualization, operationalization, detection and diagnosis represents novel fundamental opportunities for the modification of interventional trial designs. This perspective summarizes not only present knowledge regarding biological markers but also unresolved questions on the status of surrogate indicators for detection of the disease in asymptomatic people and diagnosis of AD.

Interpreting the effects of altered brain anatomical connectivity on fMRI functional connectivity: a role for computational neural modeling

Recently, there have been a large number of studies using resting state fMRI to characterize abnormal brain connectivity in patients with a variety of neurological, psychiatric, and developmental disorders. However, interpreting what the differences in resting state fMRI functional connectivity (rsfMRI-FC) actually reflect in terms of the underlying neural pathology has proved to be elusive because of the complexity of brain anatomical connectivity. The same is the case for task-based fMRI studies. In the last few years, several groups have used large-scale neural modeling to help provide some insight into the relationship between brain anatomical connectivity and the corresponding patterns of fMRI-FC. In this paper we review several efforts at using large-scale neural modeling to investigate the relationship between structural connectivity and functional/effective connectivity to determine how alterations in structural connectivity are manifested in altered patterns of functional/effective connectivity. Because the alterations made in the anatomical connectivity between specific brain regions in the model are known in detail, one can use the results of these simulations to determine the corresponding alterations in rsfMRI-FC. Many of these simulation studies found that structural connectivity changes do not necessarily result in matching changes in functional/effective connectivity in the areas of structural modification. Often, it was observed that increases in functional/effective connectivity in the altered brain did not necessarily correspond to increases in the strength of the anatomical connection weights. Note that increases in rsfMRI-FC in patients have been interpreted in some cases as resulting from neural plasticity. These results suggest that this interpretation can be mistaken. The relevance of these simulation findings to the use of functional/effective fMRI connectivity as biomarkers for brain disorders is also discussed.

Microvascular perfusion based on arterial spin labeled perfusion MRI as a measure of vascular risk in Alzheimer's disease

There is growing recognition of an interaction between cerebrovascular disease and Alzheimer's disease, but the mechanisms of this interaction remain poorly understood. While macroscopic stroke can clearly produce cognitive deficits and accelerate Alzheimer's disease, the prevalence and implications of microvascular disease in Alzheimer's disease pathogenesis has been harder to define. At present, white matter (WM) lesions, primarily defined as hyperintensities seen on T2-weighted magnetic resonance imaging (MRI), provide the best biomarker of cerebrovascular disease at the microvascular level. However, T2 hyperintensities in WM can also be caused by other mechanisms such as inflammation. Arterial spin labeled (ASL) perfusion MRI provides a noninvasive approach for quantifying cerebral blood flow (CBF). We explored CBF measurements with ASL in AD patients, mild cognitive impairment patients, and an age-matched control group to determine if CBF in gray matter or WM could be correlated with WM lesions, or to stratify patients by microvascular disease severity. In a retrospective sample, we were able to obtain credible measures of WM CBF using ASL MRI and observed trends suggesting that WM CBF may provide a useful biomarker of microvascular disease. Future prospective studies in larger cohorts with optimized ASL MRI protocols will be needed to validate these observations.

Was phenserine a failure or were investigators mislead by methods?

Over 200 Alzheimer's disease (AD) drug candidates have failed in development, and other neuropsychiatric trials have had their validity compromised. Studies suggest that methodological errors can be a source for these compromises and failures. We gained access to documentation for phenserine, an experimental AD drug that reached phase III clinical trials. The 06 Phase III trial was cited by the developers as grounds for their abandonment of the development. We compared evidence for interventions to control methodological errors and grounds for moving through phases of drug development to 40 other randomly selected AD developments we had studied. We analyzed methods and conditions of the 06 phenserine clinical trial, for biases able to account for its abandonment during development. The phenserine development failed to control error sources able to affect the outcomes. There are statistically significant relationships in the 06 clinical trial between outcomes at research sites and levels of variance, placebo group improvements and other factors. We conclude that phenserine was abandoned, at least in part, due to a clinical trial invalidated by relationships among its methods and outcomes.

CSF Aβ1-42 combined with neuroimaging biomarkers in the early detection, diagnosis and prediction of Alzheimer's disease

The development of validated, qualified, and standardized biomarkers for Alzheimer's disease (AD) that allow for an early presymptomatic diagnosis and discrimination (classification) from other types of dementia and neurodegenerative diseases is warranted to accelerate the successful development of novel disease-modifying therapies. Here, we focus on the value of the 42-residue-long amyloid β isoform (Aβ1-42) peptide in the cerebrospinal fluid as the core, feasible neurobiochemical marker for the amyloidogenic mechanisms in early-onset familial and late-onset sporadic AD. We discuss the role and use of Aβ1-42 in combination with evolving neuroimaging biomarkers in AD detection and diagnosis. Multimodal neuroimaging techniques, directly providing structural-functional-metabolic aspects of brain pathophysiology, are supportive to predict and monitor the progression of the disease. Advances in multimodal neuroimaging provide new insights into brain organization and enable the detection of specific proteins and/or protein aggregates associated with AD. The combination of biomarkers from different methodologies is believed to be of incrementally added risk-value to accurately identify asymptomatic and prodromal individuals who will likely progress to dementia and represent rational biomarker candidates for preventive and symptomatic pharmacological intervention trials.

Diagnosing Alzheimer's disease: are we any nearer to useful biomarker-based, non-invasive tests?

Background: Alzheimer’s disease (AD) accounts for 60–80% of cases of dementia and causes significant morbidity in patients and carers, and expense for health and social services. There is a need for a validated, non-invasive and cheap test to diagnose early AD, as diagnosis may enable prompt treatment and service planning.

Aim: To identify emerging biomarker-based tests for the early diagnosis of AD which could be available for use in primary or generalist care in the near future.

Design: Horizon scanning review.

Methods: We searched online sources to identify emerging non-invasive, biomarker-based tests. Tests were included if they used blood, saliva or urine; and there was evidence of use in trials in patients with AD. For tests licensed for use in clinical or research settings we requested information from the developer on the intended place of use and plans for availability in Europe.

Results: We identified 6 biomarker-based tests of which 5 are available for research or clinical use. The closest to market were AclarusDX™ (ExonHit Therapeutics) a gene signature test, and INNO-BIA plasma Aβ forms assay (Innogenetics N.V.) which may be CE marked for clinical use in 2015. We found no evidence of clinical utility or cost.

Conclusion: Although biomarker-based tests are nearing clinical availability and may have a future role to help target AD-specific treatment and guide prognosis, they are not yet ready for trials of clinical utility in primary care.

Imaging of glutamate neurotransmitter alterations in Alzheimer's disease

Glutamate (Glu) is a major excitatory neurotransmitter in the brain and has been shown to decrease in the early stages of Alzheimer's disease (AD). Using a glutamate chemical (amine) exchange saturation transfer (GluCEST) method, we imaged the change in [Glu] in the APP-PS1 transgenic mouse model of AD at high spatial resolution. Compared with wild-type controls, AD mice exhibited a notable reduction in GluCEST contrast (~30%) in all areas of the brain. The change in [Glu] was further validated through (1) H MRS. A positive correlation was observed between GluCEST contrast and (1) H MRS-measured Glu/total creatine ratio. This method potentially provides a novel noninvasive biomarker for the diagnosis of the disease in preclinical stages and enables the development of disease-modifying therapies for AD.

Low background and high contrast PET imaging of amyloid-β with [11C]AZD2995 and [11C]AZD2184 in Alzheimer's disease patients

PURPOSE

The aim of this study was to evaluate AZD2995 side by side with AZD2184 as novel PET radioligands for imaging of amyloid-β in Alzheimer's disease (AD).

METHODS

In vitro binding of tritium-labelled AZD2995 and AZD2184 was studied and compared with that of the established amyloid-β PET radioligand PIB. Subsequently, a first-in-human in vivo PET study was performed using [(11)C]AZD2995 and [(11)C]AZD2184 in three healthy control subjects and seven AD patients.

RESULTS

AZD2995, AZD2184 and PIB were found to share the same binding site to amyloid-β. [(3)H]AZD2995 had the highest signal-to-background ratio in brain tissue from patients with AD as well as in transgenic mice. However, [(11)C]AZD2184 had superior imaging properties in PET, as shown by larger effect sizes comparing binding potential values in cortical regions of AD patients and healthy controls. Nevertheless, probably due to a lower amount of nonspecific binding, the group separation of the distribution volume ratio values of [(11)C]AZD2995 was greater in areas with lower amyloid-β load, e.g. the hippocampus.

CONCLUSION

Both AZD2995 and AZD2184 detect amyloid-β with high affinity and specificity and also display a lower degree of nonspecific binding than that reported for PIB. Overall [(11)C]AZD2184 seems to be an amyloid-β radioligand with higher uptake and better group separation when compared to [(11)C]AZD2995. However, the very low nonspecific binding of [(11)C]AZD2995 makes this radioligand potentially interesting as a tool to study minute levels of amyloid-β. This sensitivity may be important in investigating, for example, early prodromal stages of AD or in the longitudinal study of a disease modifying therapy.

Plasma biomarkers for Alzheimer's disease: much needed but tough to find

Alzheimer's disease is a complex age-dependent neurodegenerative disease where definitive diagnosis is only possible after autopsy and where there is a long prodromal or preclinical phase. Biomarkers for both early diagnosis and prediction of disease progression are needed and extensive efforts to discover them have been undertaken. In this article, we have attempted to summarize the findings of current studies using proteomics and metabolomics approaches. We are also discussing how the use of emerging technologies and better study designs can support the identification of the much-needed Alzheimer's disease plasma biomarkers.

Use of biomarkers and imaging to assess pathophysiology, mechanisms of action and target engagement

Multidisciplinary basic research led to an evolving knowledge of the molecular pathogenesis of Alzheimer's disease (AD). These advances have been translated into defined therapeutic concepts and distinct classes of compounds with putative disease-modifying effects that are now being tested in clinical trials. There is a growing consensus that disease-modifying treatments may be most effective when commenced early in the course and progression of AD pathophysiology, before amyloid deposition and neurodegeneration become too widespread. Biological indicators of pathophysiological mechanisms are required to chart and identify AD in the prodromal phase or, preferably, in asymptomatic individuals. Biomarkers are becoming even more important, owing to the challenges in demonstrating efficacy of candidate-drugs that hit pathophysiological targets using clinical and cognitive outcomes in early AD trials with limited duration. Currently, there is emerging consensus that advances in therapeutic strategies for AD that delay predefined milestones or slow the cognitive and disease progression would considerably decrease the expanding global burden of the disease. To effectively test preventive compounds for AD and bring therapy to affected individuals as early as possible there is an urgent need for a concerted collaboration among worldwide academic institutions, industry, and regulatory bodies with the aim of establishing networks for the identification and qualification of multi-modal biological disease markers.

Intensive protein synthesis in neurons and phosphorylation of beta-amyloid precursor protein and tau-protein are triggering factors of neuronal amyloidosis and Alzheimer's disease

Recently the studies of Alzheimer’s disease have become particularly actual and have attracted scientists from all over the world to this problem as a result of dissemination of this dangerous disorder. The reason for such pathogenesis is not known, but the final image, for the first time obtained on microscopic brain sections from patients with this disease more than a hundred years ago, is well known to clinicists. This is the deposition of Ab amyloid in the brain tissue of senile plaques and fibrils. Many authors suppose that the deposition of beta-amyloid provokes secondary neuronal changes which are the reason of neuron death. Other authors associate the death of neurons with hyperphosphorylation of tau-proteins which form neurofibrillar coils inside nerve cells and lead to their death. For creation of methods of preclinical diagnostics and effective treatment of Alzheimer’s disease novel knowledge is required on the nature of triggering factors of sporadic isoforms of Alzheimer’s disease, on cause-effect relationships of phosphorylation of amyloid precursor protein with formation of pathogenic beta-amyloids, on the relationship with these factors of hyperphosphorylation of tau-protein and neuron death. In this review we analyze the papers describing the increasing of intensity of biosynthesis in neurons in normal conditions and under the stress, the possibility of development of energetic unbalanced neurons and activation of their protective systems. Phosphorylation and hyperphosphorylation of tau-proteins is also tightly connected with protective mechanisms of cells and with processes of evacuation of phosphates, adenosine mono-phosphates and pyrophosphates from the region of protein synthesis. Upon long and high intensity of protein synthesis the protective mechanisms are overloaded and the complementarity of metabolitic processes is disturbed. This results in dysfunction of neurons, transport collapse, and neuron death.

No diagnostic value of plasma clusterin in Alzheimer's disease

There is an urgent need for biomarkers to enable early diagnosis of Alzheimer's disease (AD). It has recently been shown that a variant within the clusterin gene is associated with increased risk of AD and plasma levels of clusterin have been found to be associated with the risk of AD. We, therefore, investigated the diagnostic value of clusterin by quantifying clusterin using an ELISA in plasma from 171 controls, 127 patients with AD, 82 patients with other dementias and 30 patients with depression. We observed similar plasma clusterin levels in controls, AD patients and patients with other dementias, suggesting that plasma clusterin levels have no diagnostic value for AD. There was a slight, but significant, increase in plasma clusterin in patients with depression compared to all other groups tested, which may warrant further investigation.

Development of biomarkers to chart all Alzheimer's disease stages: the royal road to cutting the therapeutic Gordian Knot

The aim of this perspective article is to stimulate radical shifts in thinking and foster further discussion on the effective discovery, development, validation, and qualification process of biological markers derived from all available technical modalities that meet the complex conceptual and pathophysiological challenges across all stages of the complex, nonlinear, dynamic, and chronically progressive sporadic Alzheimer's disease (AD). This perspective evaluates the current state of the science regarding a broad spectrum of hypothesis-driven and exploratory technologies and "markers" as candidates for all required biomarker functions, in particular, surrogate indicators of adaptive to maladaptive and compensatory to decompensatory, reversible to irreversible brain "systems failure." We stress the future importance of the systems biology (SB) paradigm (next to the neural network paradigm) for substantial progress in AD research. SB represents an integrated and deeper investigation of interacting biomolecules within cells and organisms. This approach has only recently become feasible as high-throughput technologies and mass spectrometric analyses of proteins and lipids, together with rigorous bioinformatics, have evolved. Existing high-content data derived from clinically and experimentally derived neural tissues point to convergent pathophysiological pathways during the course of AD, transcending traditional descriptive studies to reach a more integrated and comprehensive understanding of AD pathophysiology, derived systems biomarkers, and "druggable" system nodes. The discussion is continued on the premise that the lack of integration of advanced biomarker technologies and transfertilization from more mature translational research fields (e.g., oncology, immunology, cardiovascular), which satisfy regulatory requirements for an accurate, sensitive, and well-validated surrogate marker of specific pathophysiological processes and/or clinical outcomes, is a major rate-limiting factor for the successful development and approval of effective treatments for AD prevention. We consider the conceptual, scientific, and technical challenges for the discovery-development-validation-qualification process of biomarker tools and analytical algorithms for detection of the earliest pathophysiological processes in asymptomatic individuals at elevated risk during preclinical stages of AD. The most critical need for rapid translation of putative markers into validated (performance) and standardized (harmonized standard operating procedures) biomarker tools that fulfill regulatory requirements (qualify for use in treatment trials: e.g., safety, target engagement, mechanism of action, enrichment, stratification, secondary and primary outcome, surrogate outcome) is the availability of a large-scale worldwide comprehensive longitudinal database that includes the following cohorts: (a) healthy aging, (b) people at elevated risks (genetic/epigenetic/lifestyle/comorbid conditions), and (c) asymptomatic-preclinical/prodromal-mild cognitive impairment/syndromal mild, moderate, or severe AD. Our proposal, as initial strategic steps for integrating markers into future development of diagnostic and therapy trial technologies, is to work toward: (a) creating the essential research and development infrastructure as an international shared resource, (b) building the organizational structure for managing such a multinational shared resource, and (c) establishing an integrated transsectoral multidisciplinary global network of collaborating investigators to help build and use the shared research resource.

A model for improving the treatment and care of Alzheimer's disease patients through interdisciplinary research

The emerging global epidemic of Alzheimer's disease (AD) demands novel paradigms to address the two unmet needs of the field: (a) cost-effective health care delivery programs/services, and (b) clinical and basic research to accelerate therapy discovery/development. This report outlines a model demonstration project, the Marian S. Ware Alzheimer Program at the University of Pennsylvania, which was designed to achieve four specific aims: (1) improve the integration and continuity of AD care; (2) identify biomarkers that detect the earliest presence of AD and related neurodegenerative cognitive disorders; (3) enhance both the design and conduct of clinical trials as well as review their results to more effectively test new AD therapies and translate valuable therapies into clinical practice; and (4) discover and develop novel disease-modifying small molecule treatments for AD. The "Ware-UPenn" program has been presented in this report as a useful prototype for partnerships between private philanthropy and academia in planning and developing programs to address a major national public health problem.

Current application of neurochemical biomarkers in the prediction and differential diagnosis of Alzheimer's disease and other neurodegenerative dementias

In light of the dramatically increasing prevalence of Alzheimer's disease (AD) to be expected in the future, the development of novel therapeutics, improved differential and early diagnostics, and means for the identification of individuals at risk are urgently needed. At present, instruments for a reliable differential diagnosis in clinical dementia, mild cognitive impairment, or prodromal stages have direct practical implications for differentiating secondary dementias from neurodegenerative conditions and for treatment decisions. It may also be reasonable to enforce the incorporation of biomarkers into clinical studies as surrogate outcome parameters and as an attempt to optimize recruitment criteria. Recently, revised research criteria increasingly rely on the interpretation of biomarker patterns, including neuroimaging and CSF-based neurochemical dementia diagnosis (NDD) in supporting the clinical diagnosis. Here, we review the performance of current core CSF biomarkers (Aβ(42) peptide, total tau protein and phosphorylated tau species) and try to define objectives for prospective markers, also considering blood-based tests, which would increase the acceptance and wide application of NDD. Moreover, we evaluate the role and the limitations of genotyping in the predictive diagnosis of AD.

Alzheimer's disease biomarker discovery using in silico literature mining and clinical validation

Background

Alzheimer’s Disease (AD) is the most widespread form of dementia in the elderly but despite progress made in recent years towards a mechanistic understanding, there is still an urgent need for disease modification therapy and for early diagnostic tests. Substantial international efforts are being made to discover and validate biomarkers for AD using candidate analytes and various data-driven 'omics' approaches. Cerebrospinal fluid is in many ways the tissue of choice for biomarkers of brain disease but is limited by patient and clinician acceptability, and increasing attention is being paid to the search for blood-based biomarkers. The aim of this study was to use a novel in silico approach to discover a set of candidate biomarkers for AD.

Methods

We used an in silico literature mining approach to identify potential biomarkers by creating a summarized set of assertional metadata derived from relevant legacy information. We then assessed the validity of this approach using direct assays of the identified biomarkers in plasma by immunodetection methods.

Results

Using this in silico approach, we identified 25 biomarker candidates, at least three of which have subsequently been reported to be altered in blood or CSF from AD patients. Two further candidate biomarkers, indicated from the in silico approach, were choline acetyltransferase and urokinase-type plasminogen activator receptor. Using immunodetection, we showed that, in a large sample set, these markers are either altered in disease or correlate with MRI markers of atrophy.

Conclusions

These data support as a proof of concept the use of data mining and in silico analyses to derive valid biomarker candidates for AD and, by extension, for other disorders.

Muscle-directed anti-Aβ single-chain antibody delivery via AAV1 reduces cerebral Aβ load in an Alzheimer's disease mouse model

We previously reported that anti-amyloid-beta (Aβ) single-chain antibody (scFv59) brain delivery via recombinant adeno-associated virus (rAAV) was effective in reducing cerebral Aβ load in an Alzheimer's disease (AD) mouse model without inducing inflammation. Here, we investigated the prophylactic effects and mechanism of a muscle-directed gene therapy modality in an AD mouse model. We injected rAAV serotype 1 encoding scFv59 into the right thigh muscles of 3-month-old mice. Nine months later, high levels of scFv59 expression were confirmed in the thigh muscles by both immunoblotting and immunohistochemistry. As controls, model mice were similarly injected with rAAV1 encoding antihuman immunodeficiency virus Gag antibody (scFvGag). AAV1-mediated scFv59 gene delivery was effective in decreasing Aβ deposits in the brain. Compared with the scFvGag group, levels of Aβ in cerebrospinal fluid (CSF) decreased significantly while Aβ in serum tended to increase in the scFv59 group. AAV1-mediated scFv59 gene delivery may alter the equilibrium of Aβ between the blood and brain, resulting in an increased efflux of Aβ from the brain owing to antibody-mediated sequestration/clearance of peripheral Aβ. Our results suggest that muscle-directed scFv59 delivery via rAAV1 may be a prophylactic option for AD and that levels of CSF Aβ may be used to evaluate the efficacy of anti-Aβ immunotherapy.

Clinical data in early intervention

Research into early intervention for Alzheimer's disease (AD) and dementia has involved cohort data from large epidemiological studies and data from specifically designed intervention trials. Cohort data indicate that use of nootropics and Ginkgo biloba extract may be associated with a reduced incidence of dementia and death. Data from large trials have often been inconclusive due to issues with poor medication adherence. However, such trials do indicate potential benefits with Gingko biloba extract in terms of reduced incidence of dementia of the AD type, vascular dementia and mixed pathology, reduced progression in terms of the clinical dementia rating and improvements in attention and memory. Furthermore, Gingko biloba extract EGb 761® is a useful option for long-term intervention on the basis of decades of previous experience and an excellent safety record. However, benefits can be expected only with sufficient medication adherence and treatment duration, so clear evidence of a disease-modifying benefit of this extract is needed from adequately designed trials using modern methods to ensure high levels of adherence.

Upcoming candidate cerebrospinal fluid biomarkers of Alzheimer's disease

Dementia due to Alzheimer's disease (AD) is estimated to reach epidemic proportions by the year 2030. Given the limited accuracy of current AD clinical diagnosis, biomarkers of AD pathologies are currently being sought. Reductions in cerebrospinal fluid levels of β-amyloid 42 (a marker of amyloid plaques) and elevations in tau species (markers of neurofibrillary tangles and/or neurodegeneration) are well-established as biomarkers useful for AD diagnosis and prognosis. However, novel markers for other features of AD pathophysiology (e.g., β-amyloid processing, neuroinflammation and neuronal stress/dysfunction) and for other non-AD dementias are required to improve the accuracy of AD disease diagnosis, prognosis, staging and therapeutic monitoring (theragnosis). This article discusses the potential of several promising novel cerebrospinal fluid analytes, highlights the next steps critical for advancement in the field, and provides a prediction on how the field may evolve in 5-10 years.

Longitudinal plasma amyloid beta as a biomarker of Alzheimer's disease

Alzheimer's disease (AD) affects more than twenty-five million people worldwide and is the most common form of dementia. Symptomatic treatments have been developed, but effective intervention to alter disease progression is needed. Targets have been identified for disease-modifying drugs, but the results of clinical trials have been disappointing. Peripheral biomarkers of disease state may improve clinical trial design and analysis, increasing the likelihood of successful drug development. Amyloid-related measures, presumably reflecting principal pathology of AD, are among the leading cerebrospinal fluid and neuroimaging biomarkers, and measurement of plasma levels of amyloid peptides has been the focus of much investigation. In this review, we discuss recent data on plasma β-amyloid (Aβ) and examine the issues that have arisen in establishing it as a reliable biomarker of AD.

Alzheimer's disease therapeutic trials: EU/US Task Force report on recruitment, retention, and methodology

While we may not be able to find a cure for Alzheimer's disease (AD) in the near future, several drugs presently in trials have shown promise as possible modifiers of disease progression. However, we may not be able to demonstrate efficacy due to issues of recruitment, retention, site-to-site variability, and other methodological issues. It is thus incumbent on the scientific community to find solutions to these problems, particularly as the field moves toward preventing illness or treating the disease in its prodromal stages, where these methodological issues will become even more critical. We need to better understand why participants agree or refuse to enter drug trials, and why both primary care physicians and Alzheimer's specialists agree or refuse to involve their patients. We also need to quantify the impact of requiring imaging studies, extensive questionnaires, cognitive testing, and lumbar punctures on recruitment and retention. With these concerns in mind, an international task force meeting of experts from academia and industry in the United States, European Union, and Japan in San Diego, California on November 2, 2011 to focus on recruitment, retention and other methodological issues related to clinical trials for AD. Based on the recommendations of this Task force meeting, this Perspectives article critically reflects on the most critical and timely methodological issues related to recruitment and retention in prevention and therapeutic trials in AD, which are paralleled by a paradigm shift in the diagnostic conceptualization of this disease, as reflected by recently new proposed diagnostic criteria involving preclinical stages of the disease.

The challenges and promise of neuroimaging in psychiatry

Neuroimaging is central to the quest for a biological foundation of psychiatric diagnosis but so far has not yielded clinically relevant biomarkers for mental disorders. This review addresses potential reasons for this limitation and discusses refinements of paradigms and analytic techniques that may yield improved diagnostic and prognostic accuracy. Neuroimaging can also be used to probe genetically defined biological pathways underlying mental disorders, for example through the genetic imaging of variants discovered in genome-wide association studies. These approaches may ultimately reveal mechanisms through which genes contribute to psychiatric symptoms and how pharmacological and psychological interventions exert their effects.

The clinical value of large neuroimaging data sets in Alzheimer's disease

Rapid advances in neuroimaging and cyberinfrastructure technologies have brought explosive growth in the Web-based warehousing, availability, and accessibility of imaging data on a variety of neurodegenerative and neuropsychiatric disorders and conditions. There has been a prolific development and emergence of complex computational infrastructures that serve as repositories of databases and provide critical functionalities such as sophisticated image analysis algorithm pipelines and powerful three-dimensional visualization and statistical tools. The statistical and operational advantages of collaborative, distributed team science in the form of multisite consortia push this approach in a diverse range of population-based investigations.

Test sequence of CSF and MRI biomarkers for prediction of AD in subjects with MCI

Our aim was to identify the best diagnostic test sequence for predicting Alzheimer's disease (AD)-type dementia in subjects with mild cognitive impairment (MCI) using cerebrospinal fluid (CSF) and magnetic resonance imaging (MRI) biomarkers. We selected 153 subjects with mild cognitive impairment from a multicenter memory clinic-based cohort. We tested the CSF beta amyloid (Aβ)1-42/tau ratio using enzyme-linked immunosorbent assay (ELISA) and hippocampal volumes (HCVs) using the atlas-based learning embeddings for atlas propagation (LEAP) method. Outcome measure was progression to AD-type dementia in 2 years. At follow-up, 48 (31%) subjects converted to AD-type dementia. In multivariable analyses, CSF Aβ1-42/tau and HCV predicted AD-type dementia regardless of apolipoprotein E (APOE) genotype and cognitive scores. Test sequence analyses showed that CSF Aβ1-42/tau increased predictive accuracy in subjects with normal HCV (p < 0.001) and abnormal HCV (p = 0.025). HCV increased predictive accuracy only in subjects with normal CSF Aβ1-42/tau (p = 0.014). Slope analyses for annual cognitive decline yielded similar results. For selection of subjects for a prodromal AD trial, the best balance between sample size and number of subjects needed to screen was obtained with CSF markers. These results provide further support for the use of CSF and magnetic resonance imaging biomarkers to identify prodromal AD.

Functional biomarkers for neurodegenerative disorders based on the network paradigm

This commentary provides a brief introduction to the various uses that functional neuroimaging biomarkers can play in detecting, diagnosing, assessing treatment response and investigating neurodegenerative disorders. It then goes on to explain why the emphasis of much recent work has shifted to network-based biomarkers, as opposed to those that examine individual brain regions. A number of examples are referenced that illustrate the points made.

Staging Alzheimer's disease progression with multimodality neuroimaging

Rapid developments in medical neuroimaging have made it possible to reconstruct the trajectory of Alzheimer's disease (AD) as it spreads through the living brain. The current review focuses on the progressive signature of brain changes throughout the different stages of AD. We integrate recent findings on changes in cortical gray matter volume, white matter fiber tracts, neuropathological alterations, and brain metabolism assessed with molecular positron emission tomography (PET). Neurofibrillary tangles accumulate first in transentorhinal and cholinergic brain areas, and 4-D maps of cortical volume changes show early progressive temporo-parietal cortical thinning. Findings from diffusion tensor imaging (DTI) for assessment fiber tract integrity show cortical disconnection in corresponding brain networks. Importantly, the developmental trajectory of brain changes is not uniform and may be modulated by several factors such as onset of disease mechanisms, risk-associated and protective genes, converging comorbidity, and individual brain reserve. There is a general agreement between in vivo brain maps of cortical atrophy and amyloid pathology assessed through PET, reminiscent of post mortem histopathology studies that paved the way in the staging of AD. The association between in vivo and post mortem findings will clarify the temporal dynamics of pathophysiological alterations in the development of preclinical AD. This will be important in designing effective treatments that target specific underlying disease AD mechanisms.

Prevention trials in Alzheimer's disease: an EU-US task force report

Despite enormous financial and scientific efforts, still no approved disease-modifying therapies exist for Alzheimer's disease (AD). During the last decade all Phase III clinical trials on disease modifiers in AD have failed. The dementia stage of AD being probably too late in order to allow for successful disease modification has been identified as a possible culprit that could explain the failure of so many clinical trials. In parallel, a major development in the diagnostic research field of AD was achieved by the recent proposal of new diagnostic criteria for AD, which also specifically incorporate the use of biomarkers as defining criteria for preclinical stages of AD, thus extending the traditional definition of disease to very early stages that may be a more feasible target for various disease modifying therapeutic interventions. This ongoing paradigm shift in AD definition and diagnosis represents a fundamental basis for redefinition of interventional trials in AD, allowing to specifically focus on preventative measures during very early pathophysiologically confirmed stages of disease. This consensus paper reflects the outcome from a European Union and North American Task Force meeting comprised of experts from academia, industry, private foundations, and regulatory agencies that was convened in Toulouse, France on November 5, 2010 and that focused on prevention trials in AD. This position paper thoroughly analyzes prerequisites for successful preventative trials in AD and concludes with concrete recommendations on biomarkers, statistical tools and other variables important for improved study designs suitable for preventative as well as for early therapeutic interventional trials in AD.

Bridging the efficacy-effectiveness gap: a regulator's perspective on addressing variability of drug response

Drug regulatory agencies should ensure that the benefits of drugs outweigh their risks, but licensed medicines sometimes do not perform as expected in everyday clinical practice. Failure may relate to lower than anticipated efficacy or a higher than anticipated incidence or severity of adverse effects. Here we show that the problem of benefit-risk is to a considerable degree a problem of variability in drug response. We describe biological and behavioural sources of variability and how these contribute to the long-known efficacy-effectiveness gap. In this context, efficacy describes how a drug performs under conditions of clinical trials, whereas effectiveness describes how it performs under conditions of everyday clinical practice. We argue that a broad range of pre- and post-licensing technologies will need to be harnessed to bridge the efficacy-effectiveness gap. Successful approaches will not be limited to the current notion of pharmacogenomics-based personalized medicines, but will also entail the wider use of electronic health-care tools to improve drug prescribing and patient adherence.

Functional magnetic resonance imaging as a dynamic candidate biomarker for Alzheimer's disease

During the last two decades, imaging of neural activation has become an invaluable tool for assessing the functional organization of the human brain in vivo. Due to its widespread application in neuroscience, functional neuroimaging has raised the interest of clinical researchers in its possible use as a diagnostic biomarker. A hallmark feature of many neurodegenerative diseases is their chronic non-linear dynamic and highly complex preclinical course. Neurodegenerative diseases unfold over years to decades through clinically silent and asymptomatic stages of early adaptive, compensatory to pathophysiological (i.e. actively neurodegenerative) and decompensatory mechanisms in the brain - phases that are increasingly being considered as critical for primary and secondary preventive and therapeutic measures. Emerging evidence supports the concept of a potentially fully reversible functional phase that may precede the onset of micro- and macrostructural and cognitive decline, a potentially late-stage "neurodegenerative" phase of a primary neurodegenerative disorder. Alzheimer's disease serves as an ideal model to test this hypothesis supported by the neural network model of the healthy and diseased brain. Being highly dynamic in nature, brain activation and neuronal network functional connectivity represent not only candidate diagnostic but also candidate surrogate markers for interventional trials. Potential caveats of functional imaging are critically reviewed with focus on confound variables such as altered neurovascular coupling as well as parameters related to task- and study design.