Clinical Trials

People experiencing mild cognitive changes represent an epidemiologically major segment of the geriatric patient population. In the present proposal, we aim to measure how knowledge of cerebral metabolic information 1) influences working diagnoses and management of patients being evaluated for symptoms of early cognitive decline, and 2) impacts upon long-term clinical outcomes, particularly of subjects having metabolic patterns consistent with presence of Alzheimer's disease (AD)-like changes in their brains. A total of 710 patients suffering from documentable decline of cognitive function in the absence of overt dementia will be studied at nine U.S. institutions with extensive experience and infrastructure in place for the evaluation of Alzheimer's disease and related disorders, and for neuroimaging. In this prospective, investigation, subjects will undergo baseline neuropsychologic testing and neuroimaging with MRI and FDGPET. PET scan reports will be sealed and randomized with respect to whether they are released to patients' managing physicians at the time of interpretation, or two years after the time that scanning is performed. Working diagnoses of managing physicians will be recorded, as will the treatment decisions made by the managing physicians and their patients. Cognitive abilities, functional status, utilization of healthcare resources, and other clinical and social contact parameters will be assessed every six months. Our major hypotheses are that among patients whose PET results are immediately conveyed to their referring physicians, diagnoses and management plans will be positively affected, leading to more effective utilization of healthcare resources and to maintenance of cognitive and functional abilities at a higher level. This project will also provide a rich source of data that can be used to address questions outside of its major focus (e.g., prognostic accuracy of volumetric MRI data used instead of, or in conjunction with, FDG-PET data; incremental predictive value of applying statistically parameterizing and/or quantifying software tools to imaging data).

Dominantly inherited Alzheimer's disease (AD) represents less than 1% of all cases of AD and is an important model for study because the responsible mutations have known biochemical consequences that are believed to underlie the pathological basis of the disorder. Three major hypotheses will be tested: - First, that there is a period of preclinical (presymptomatic) AD in individuals who are destined to develop early-onset dementia (gene carriers) that can be detected by changes in biological fluids and in neuroimaging correlates in comparison with individuals who will not develop early-onset dementia (non-carriers). - Second, because all identified causative mutations for AD affect the normal processing of amyloid precursor protein (APP) and increase brain levels of amyloid-beta 42 (Aβ42), the sequence of preclinical changes initially will involve Aβ42 (production and clearance; reduced levels in cerebrospinal fluid [CSF]), followed by evidence for cerebral deposition of Aβ42 (amyloid imaging), followed by cerebral metabolic activity (functional imaging), and finally by regional atrophy (structural imaging). - Finally, that the phenotype of symptomatic early-onset familial AD, including its clinical course, is similar to that of late-onset "sporadic" AD. The following specific aims will be used to test these hypotheses: 1. Establish an international, multicenter registry of individuals (mutation carriers and non-carriers; pre-symptomatic and symptomatic) who are biological adult children of a parent with a known causative mutation for AD in the APP, PSEN1, or PSEN2 genes in which the individuals are evaluated in a uniform manner at entry and longitudinally thereafter with standardized instruments. 2. In pre-symptomatic individuals, compare mutation carriers and non-carriers to determine the order in which changes in clinical, cognitive, neuroimaging, and biomarker indicators of AD occur prior to the occurrence of dementia. 3. In symptomatic individuals, compare the clinical and neuropathological phenotypes of autosomal dominant AD to those of late-onset "sporadic" AD (using the data sets established by ADNI and by NACC). 4. Maintain the DIAN Central Archive, an integrated database incorporating all information obtained from individuals in the registry to permit analyses within, between, and among the various data domains and also to disseminate the data to qualified investigators in a user-friendly manner. 5. All DIAN participants who wish to know their mutation status will have the costs of genetic counseling and clinical mutation testing paid for by the grant. The clinical genetic counseling and testing is provided as an optional participant benefit and is not part of the DIAN research design.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) began in October 2004 as a landmark study with a public-private partnership that gathered and analyzed thousands of brain scans, genetic profiles and biomarkers in blood and cerebrospinal fluid (CSF). Although the original goal was to define biomarkers for use in clinical trials to determine the best way to measure treatment effects of Alzheimer's disease (AD), the goal has been expanded to using biomarkers to identify AD at a pre-dementia stage. ADNI1 involves scientists at 59 research centers, 54 in the U.S. and five in Canada. Originally 800 participants were enrolled. This group was comprised of 200 participants with AD, 400 with mild cognitive impairment (MCI) and 200 with normal cognition. In ADNI-GO, an estimated 200 participants with early amnestic MCI (EMCI) were enrolled to understand and characterize the mildest symptomatic phase of AD. An additional 650 participants will be enrolled under ADNI2. Some of the leading-edge technologies under study are brain-imaging techniques, such as positron emission tomography (PET), including FDG-PET (which measures glucose metabolism in the brain); PET using a radioactive compound (Florbetapir F 18) that measures brain beta-amyloid; and structural MRI. Brain scans are showing scientists how the brain's structure and function change as AD starts and progresses. Biomarkers in cerebrospinal fluid are revealing other changes that could identify which patients with MCI will develop Alzheimer's. Scientists are looking at levels of beta-amyloid and tau in cerebrospinal fluid. (Abnormal amounts of the amyloid and tau proteins in the brain are hallmarks of Alzheimer's disease.) ADNI2 extends the work of ADNI1 and ADNI GO to understand the progression of AD. The overall goal is to determine the relationships among the clinical, cognitive, imaging, genetic and biochemical biomarker characteristics of the entire spectrum of AD, as the pathology evolves from normal aging through very mild symptoms, to MCI, to dementia. The overall impact of this study will be increased knowledge concerning the sequence and timing of events leading to MCI and AD, development of better clinical and imaging/fluid biomarker methods for early detection and for monitoring the progression of these conditions, and facilitation of clinical trials to slow disease progression, ultimately contributing to the prevention of AD.

Aging is associated with a loss of brain function and conditions such as dementia and Alzheimer's disease. It is likely that decreased brain metabolism is contributing to the progression of age related degenerative diseases. Aerobic exercise training can increase brain volumes and is associated with decreased risk for degenerative brain conditions. However, little is know about the changes that occur to brain metabolism with aerobic training and aging.