Worldwide Alzheimer's disease neuroimaging initiative

Down syndrome and Alzheimer's disease: Common pathways, common goals

In the United States, estimates indicate there are between 250,000 and 400,000 individuals with Down syndrome (DS), and nearly all will develop Alzheimer's disease (AD) pathology starting in their 30s. With the current lifespan being 55 to 60 years, approximately 70% will develop dementia, and if their life expectancy continues to increase, the number of individuals developing AD will concomitantly increase. Pathogenic and mechanistic links between DS and Alzheimer's prompted the Alzheimer's Association to partner with the Linda Crnic Institute for Down Syndrome and the Global Down Syndrome Foundation at a workshop of AD and DS experts to discuss similarities and differences, challenges, and future directions for this field. The workshop articulated a set of research priorities: (1) target identification and drug development, (2) clinical and pathological staging, (3) cognitive assessment and clinical trials, and (4) partnerships and collaborations with the ultimate goal to deliver effective disease-modifying treatments.

The Road Ahead to Cure Alzheimer's Disease: Development of Biological Markers and Neuroimaging Methods for Prevention Trials Across all Stages and Target Populations

Alzheimer's disease (AD) is a slowly progressing non-linear dynamic brain disease in which pathophysiological abnormalities, detectable in vivo by biological markers, precede overt clinical symptoms by many years to decades. Use of these biomarkers for the detection of early and preclinical AD has become of central importance following publication of two international expert working group's revised criteria for the diagnosis of AD dementia, mild cognitive impairment (MCI) due to AD, prodromal AD and preclinical AD. As a consequence of matured research evidence six AD biomarkers are sufficiently validated and partly qualified to be incorporated into operationalized clinical diagnostic criteria and use in primary and secondary prevention trials. These biomarkers fall into two molecular categories: biomarkers of amyloid-beta (Aβ) deposition and plaque formation as well as of tau-protein related hyperphosphorylation and neurodegeneration. Three of the six gold-standard ("core feasible) biomarkers are neuroimaging measures and three are cerebrospinal fluid (CSF) analytes. CSF Aβ1-42 (Aβ1-42), also expressed as Aβ1-42 : Aβ1-40 ratio, T-tau, and P-tau Thr181 & Thr231 proteins have proven diagnostic accuracy and risk enhancement in prodromal MCI and AD dementia. Conversely, having all three biomarkers in the normal range rules out AD. Intermediate conditions require further patient follow-up. Magnetic resonance imaging (MRI) at increasing field strength and resolution allows detecting the evolution of distinct types of structural and functional abnormality pattern throughout early to late AD stages. Anatomical or volumetric MRI is the most widely used technique and provides local and global measures of atrophy. The revised diagnostic criteria for "prodromal AD" and "mild cognitive impairment due to AD" include hippocampal atrophy (as the fourth validated biomarker), which is considered an indicator of regional neuronal injury. Advanced image analysis techniques generate automatic and reproducible measures both in regions of interest, such as the hippocampus and in an exploratory fashion, observer and hypothesis-indedendent, throughout the entire brain. Evolving modalities such as diffusion-tensor imaging (DTI) and advanced tractography as well as resting-state functional MRI provide useful additionally useful measures indicating the degree of fiber tract and neural network disintegration (structural, effective and functional connectivity) that may substantially contribute to early detection and the mapping of progression. These modalities require further standardization and validation. The use of molecular in vivo amyloid imaging agents (the fifth validated biomarker), such as the Pittsburgh Compound-B and markers of neurodegeneration, such as fluoro-2-deoxy-D-glucose (FDG) (as the sixth validated biomarker) support the detection of early AD pathological processes and associated neurodegeneration. How to use, interpret, and disclose biomarker results drives the need for optimized standardization. Multimodal AD biomarkers do not evolve in an identical manner but rather in a sequential but temporally overlapping fashion. Models of the temporal evolution of AD biomarkers can take the form of plots of biomarker severity (degree of abnormality) versus time. AD biomarkers can be combined to increase accuracy or risk. A list of genetic risk factors is increasingly included in secondary prevention trials to stratify and select individuals at genetic risk of AD. Although most of these biomarker candidates are not yet qualified and approved by regulatory authorities for their intended use in drug trials, they are nonetheless applied in ongoing clinical studies for the following functions: (i) inclusion/exclusion criteria, (ii) patient stratification, (iii) evaluation of treatment effect, (iv) drug target engagement, and (v) safety. Moreover, novel promising hypothesis-driven, as well as exploratory biochemical, genetic, electrophysiological, and neuroimaging markers for use in clinical trials are being developed. The current state-of-the-art and future perspectives on both biological and neuroimaging derived biomarker discovery and development as well as the intended application in prevention trials is outlined in the present publication.

Creation of the Argentina-Alzheimer's Disease Neuroimaging Initiative

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a multisite, longitudinal study that assesses clinical, imaging, genetic, and biospecimen biomarkers through the process of normal aging to mild cognitive impairment and dementia. We present the creation of the Argentina-ADNI - the first South American ADNI - and its effort to acquire data comparable with those gathered in other worldwide ADNI centers.

Biomarkers in psychosis: an approach to early identification and individualized treatment

Numerous biomarkers for somatic disorders are used in routine medical practice. Yet, despite remarkable advances in mental health research, we are not able to identify biomarkers with established clinical utility for mental disorders such as schizophrenia. While identification and characterization of biomarkers are crucial first steps in this process, their predictive diagnostic and treatment utility need to be better developed for clinical practice. The heterogeneity of psychotic disorders etiologically, pathologically and symptomatically presents both a challenge and an opportunity for the use of biomarkers in clinical practice. Simply said, a single biomarker might not exist that necessitates the search for a biomarker profile. In this review we discuss research findings in light of such an approach. We summarize some examples of emerging biomarkers in early psychosis research and delineate how these can be applied to a clinical setting to inform treatment on an individual basis fostering a personalized treatment approach.

Role of genomics in translational research for Parkinson's disease

Research on Parkinson's disease (PD) has made remarkable progress in recent decades, due largely to new genomic technologies, such as high throughput sequencing and microarray analyses. Since the discovery of a linkage of a missense mutation of the α-synuclein (αS) gene to a rare familial dominant form of PD in 1996, positional cloning and characterization of a number of familial PD risk factors have established a hypothesis that aggregation of αS may play a major role in the pathogenesis of PD. Furthermore, dozens of sensitizing alleles related to the disease have been identified by genome wide association studies (GWAS) and meta-GWAS, contributing to a better understanding of the pathological mechanisms of sporadic PD. Thus, the knowledge obtained from the association studies will be valuable for "the personal genome" of PD. Besides summarizing such progress, this paper focuses on the role of microRNAs in the field of PD research, since microRNAs might be promising as a biomarker and as a therapeutic reagent for PD. We further refer to a recent view that neurodegenerative diseases, including PD, coexist with metabolic disorders and are stimulated by type II diabetes, the most common disease among elderly populations. The development of genomic approaches may potentially contribute to therapeutic intervention for PD.

The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Whole-genome analyses of whole-brain data: working within an expanded search space

Large-scale comparisons of patients and healthy controls have unearthed genetic risk factors associated with a range of neurological and psychiatric illnesses. Meanwhile, brain imaging studies are increasing in size and scope, revealing disease and genetic effects on brain structure and function, and implicating neural pathways and causal mechanisms. With the advent of global neuroimaging consortia, imaging studies are now well powered to discover genetic variants that reliably affect the brain. Genetic analyses of brain measures from tens of thousands of people are being extended to test genetic associations with signals at millions of locations in the brain, and connectome-wide, genome-wide scans can jointly screen brain circuits and genomes; these analyses and others present new statistical challenges. There is a growing need for the community to establish and enforce standards in this developing field to ensure robust findings. Here we discuss how neuroimagers and geneticists have formed alliances to discover how genetic factors affect the brain. The field is rapidly advancing with ultra-high-resolution imaging and whole-genome sequencing. We recommend a rigorous approach to neuroimaging genomics that capitalizes on its recent successes and ensures the reliability of future discoveries.

Neuroimaging and the search for a cure for Alzheimer disease

As radiologists, our role in the workup of the dementia patient has long been limited by the sensitivity of our imaging tools and lack of effective treatment options. Over the past 30 years, we have made tremendous strides in understanding the genetic, molecular, and cellular basis of Alzheimer disease (AD). We now know that the pathologic features of AD are present 1 to 2 decades prior to development of symptoms, though currently approved symptomatic therapies are administered much later in the disease course. The search for true disease-modifying therapy continues and many clinical trials are underway. Current outcome measures, based on cognitive tests, are relatively insensitive to pathologic disease progression, requiring long, expensive trials with large numbers of participants. Biomarkers, including neuroimaging, have great potential to increase the power of trials by matching imaging methodology with therapeutic mechanism. One of the most important advances over the past decade has been the development of in vivo imaging probes targeted to amyloid beta protein, and one agent is already available for clinical use. Additional advances include automated volumetric imaging methods to quantitate cerebral volume loss. Use of such techniques in small, early phase trials are expected to significantly increase the number and quality of candidate drugs for testing in larger trials. In addition to a critical role in trials, structural, molecular, and functional imaging techniques can give us a window on the etiology of AD and other neurodegenerative diseases. This combination of developments has potential to bring diagnostic radiology to the forefront in AD research, therapeutic trials, and patient care.

The Women's Healthy Ageing Project: fertile ground for investigation of healthy participants 'at risk' for dementia

Alzheimer's disease neuropathology (amyloid, tauopathies) and brain atrophy are present decades prior to manifestation of clinical symptoms. With the failure of treatment trials it is becoming clearer that the window for prevention and therapeutic intervention is before significant neuronal loss and clinical deterioration of cognition has occurred. Early identification of those at risk of disease and optimizing their management to prevent disease in later life are crucial to delaying disease onset and improving people's quality of life. The Women's Healthy Aging Project (WHAP) is a longitudinal study of over 400 Australian-born women, epidemiologically randomly sampled in 1990. The WHAP aims to identify modifiable mid-life risk factors for the development of late-life cognitive decline, improve the understanding of the pathogenesis of dementia, and target early disease identification utilizing clinical, biomarker and health risk profiles. These aims are fortified by the ability to leverage the considerable database on health, lifestyle and socio-demographics collected prospectively from 1990 to date. This is the first study with a comprehensive neuropsychological battery, over a decade of cognitive follow-up, with all participants being offered amyloid imaging from 2012, and prospective longitudinal data including clinical and physical measures and bio-bank samples from over 20 years prior.

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.

COSMIC (Cohort Studies of Memory in an International Consortium): an international consortium to identify risk and protective factors and biomarkers of cognitive ageing and dementia in diverse ethnic and sociocultural groups

BACKGROUND

A large number of longitudinal studies of population-based ageing cohorts are in progress internationally, but the insights from these studies into the risk and protective factors for cognitive ageing and conditions like mild cognitive impairment and dementia have been inconsistent. Some of the problems confounding this research can be reduced by harmonising and pooling data across studies. COSMIC (Cohort Studies of Memory in an International Consortium) aims to harmonise data from international cohort studies of cognitive ageing, in order to better understand the determinants of cognitive ageing and neurocognitive disorders.

METHODS/DESIGN

Longitudinal studies of cognitive ageing and dementia with at least 500 individuals aged 60 years or over are eligible and invited to be members of COSMIC. There are currently 17 member studies, from regions that include Asia, Australia, Europe, and North America. A Research Steering Committee has been established, two meetings of study leaders held, and a website developed. The initial attempts at harmonising key variables like neuropsychological test scores are in progress.

DISCUSSION

The challenges of international consortia like COSMIC include efficient communication among members, extended use of resources, and data harmonisation. Successful harmonisation will facilitate projects investigating rates of cognitive decline, risk and protective factors for mild cognitive impairment, and biomarkers of mild cognitive impairment and dementia. Extended implications of COSMIC could include standardised ways of collecting and reporting data, and a rich cognitive ageing database being made available to other researchers. COSMIC could potentially transform our understanding of the epidemiology of cognitive ageing, and have a world-wide impact on promoting successful ageing.

Military risk factors for Alzheimer's disease

Traumatic brain injury (TBI) and post-traumatic stress disorder (PTSD) are signature injuries of the wars in Iraq and Afghanistan and have been linked to an increased risk of Alzheimer's disease (AD) and other dementias. A meeting hosted by the Alzheimer's Association and the Veterans' Health Research Institute (NCIRE) in May 2012 brought together experts from the U.S. military and academic medical centers around the world to discuss current evidence and hypotheses regarding the pathophysiological mechanisms linking TBI, PTSD, and AD. Studies underway in civilian and military populations were highlighted, along with new research initiatives such as a study to extend the Alzheimer's Disease Neuroimaging Initiative (ADNI) to a population of veterans exposed to TBI and PTSD. Greater collaboration and data sharing among diverse research groups is needed to advance an understanding and appropriate interventions in this continuum of military injuries and neurodegenerative disease in the aging veteran.

Progress in developing common data elements for traumatic brain injury research: version two--the end of the beginning

To accelerate data sharing and research on traumatic brain injury (TBI), several federal agencies have been collaborating to support the development and implementation of common data elements (CDEs). The first recommendations for CDEs were made in 2010, and were well suited for hospital-based studies of acute TBI in adults. To broaden the utility of the TBI CDEs, experts were asked to update the recommendations to make them relevant to all ages, levels of injury severity, and phases of recovery. The second version of the TBI CDEs (v.2) was organized around four major study types: 1) epidemiological research; 2) studies on acute, hospitalized patients; 3) studies of the rehabilitation for moderate/severe TBI; and 4) mild TBI/concussion research. Given the heterogeneity of TBI, only a small set of core CDEs were found to be relevant across all study types. However, within groups, a much larger set of highly relevant CDEs were identified, and these were called basic CDEs. In addition, an expanded number of supplemental CDEs were specified and recommended for use depending upon the study goals. Version 2 provides a rich data dictionary for TBI research with about 900 CDEs. Many of the CDEs overlap across the study types, which will facilitate comparisons and meta-analysis across studies. Further modifications of the CDEs should be based on evaluation of their usefulness following implementation across a range of studies.

Role of emerging neuroimaging modalities in patients with cognitive impairment: a review from the Canadian Consensus Conference on the Diagnosis and Treatment of Dementia 2012

The Fourth Canadian Consensus Conference on the Diagnosis and Treatment of Dementia (CCCDTD4) was held 3 to 4 May 2012 in Montreal, Quebec, Canada. A group of neuroimaging experts were assigned the task of reviewing and summarizing the literature on clinical and research applications of different neuroimaging modalities in cognitive disorders. This paper summarizes the literature and recommendations made to the conference regarding the role of several emerging neuroimaging modalities in cognitive disorders. Functional magnetic resonance imaging (MRI), magnetic resonance spectroscopy, and diffusion tensor imaging are discussed in detail within this paper. Other emergent neuroimaging modalities such as positron emission tomography with novel ligands, high-field MRI, arterial spin labeling MRI and noncerebral blood flow single-photon emission computerized tomography are only discussed briefly. Neuroimaging modalities that were recommended at the CCCDTD4 for both clinical and research applications such as amyloid and flurodeoxyglucose positron emission tomography, computerized tomography and structural MRI are discussed in a separate paper by the same authors. A literature search was conducted using the PubMed database including articles in English that involved human subjects and covered the period from the last CCCDTD publication (CCCDTD3; January 2006) until April 2012. Search terms included the name of the specific modality, dementia, Alzheimer's disease, and mild cognitive impairment. A separate search used the same parameters but was restricted to review articles to identify recent evidence-based reviews. Case studies and small case series were not included. Papers representing current evidence were selected, reviewed, and summarized, and the results were presented at the CCCDTD4 meeting with recommendations regarding the utility of various neuroimaging modalities in cognitive disorders. The evidence was graded according to the Oxford Centre for Evidence Based Medicine guidelines. Due to the limitations of current evidence, the neuroimaging modalities discussed in this paper were not recommended for clinical investigation of patients presenting with cognitive impairment. However, in the research setting, each modality provides a unique contribution to the understanding of basic mechanisms and neuropathological markers of cognitive disorders, to the identification of markers for early detection and for the risk of conversion to dementia in the at-risk populations, to the differentiation between different types of cognitive disorders, and to the identification of treatment targets and indicators of treatment response. In conclusion, for all of the neuroimaging modalities discussed in this paper, further studies are needed to establish diagnostic utility such as validity, reliability, and predictive and prognostic value. More multicenter studies are therefore needed with standardized image acquisition, experimental protocols, definition of the clinical population studied, larger numbers of participants, and longer duration of follow-up to allow generalizability of the results to the individual patient.

Dimensionality reduced cortical features and their use in predicting longitudinal changes in Alzheimer's disease

Neuroimaging features derived from the cortical surface provide important information in detecting changes related to the progression of Alzheimer's disease (AD). Recent widespread adoption of neuroimaging has allowed researchers to study longitudinal data in AD. We adopted cortical thickness and sulcal depth, parameterized by three-dimensional meshes, from magnetic resonance imaging as the surface features. The cortical feature is high-dimensional, and it is difficult to use directly with a classifier because of the "small sample size" problem. We applied manifold learning to reduce the dimensionality of the feature and then tested the usage of the dimensionality reduced feature with a support vector machine classifier. Principal component analysis (PCA) was chosen as the method of manifold learning. PCA was applied to a region of interest within the cortical surface. We used 30 normal, 30 mild cognitive impairment (MCI) and 12 conversion cases taken from the ADNI database. The classifier was trained using the cortical features extracted from normal and MCI patients. The classifier was tested for the 12 conversion patients only using the imaging data before the actual conversion. The conversion was predicted early with an accuracy of 83%.

A strategy for developing new treatment paradigms for neuropsychiatric and neurocognitive symptoms in Alzheimer's disease

Successful disease modifying drug development for Alzheimer's disease (AD) has hit a roadblock with the recent failures of amyloid-based therapies, highlighting the translational disconnect between preclinical animal models and clinical outcome. Although disease modifying therapies are the Holy Grail to pursue, symptomatic therapies addressing cognitive and neuropsychiatric aspects of the disease are also extremely important for the quality of life of patients and caregivers. Despite the fact that neuropsychiatric problems in Alzheimer patients are the major driver for costs associated with institutionalization, no good preclinical animal models with predictive validity have been documented. We propose a combination of quantitative systems pharmacology (QSP), phenotypic screening and preclinical animal models as a novel strategy for addressing the bottleneck in both cognitive and neuropsychiatric drug discovery and development for AD. Preclinical animal models such as transgene rats documenting changes in neurotransmitters with tau and amyloid pathology will provide key information that together with human imaging, pathology and clinical data will inform the virtual patient model. In this way QSP modeling can partially overcome the translational disconnect and reduce the attrition of drug programs in the clinical setting. This approach is different from target driven drug discovery as it aims to restore emergent properties of the networks and therefore likely will identify multitarget drugs. We review examples on how this hybrid humanized QSP approach has been helpful in predicting clinical outcomes in schizophrenia treatment and cognitive impairment in AD and expand on how this strategy could be applied to neuropsychiatric symptoms in dementia. We believe such an innovative approach when used carefully could change the Research and Development paradigm for symptomatic treatment in AD.