Alzheimer's Research & Therapy - Most accessed articles

Resting state functional MRI in Alzheimer's Disease

Prashanthi Vemuri — 2012-01-10T00:00:00Z

Resting-state functional magnetic resonance imaging (fMRI) is emerging as an interesting biomarker for measuring connectivity of the brain in patients with Alzheimer's disease (AD). In this review, we discuss the origins of resting-state fMRI, common methodologies used to extract information from these four-dimensional fMRI scans, and important considerations for the analysis of these scans. Then we present the current state of knowledge in this area by summarizing various AD resting-state fMRI studies presented in the first section and end with a discussion of future developments and open questions in the field.

Review of Alzheimer's disease scales: is there a need for a new multi-domain scale for therapy evaluation in medical practice?

Philippe Robert — 2010-08-26T00:00:00Z

IntroductionThe present review of Alzheimer's disease (AD) rating scales aims to outline the need for a new rating scale to be used in routine clinical practice for long-term medical care of AD patients. An ideal scale would be: 1) practical, easy and quick to administer for an experienced clinician; 2) validated for AD; 3) multi-domain: covering the AD-relevant areas of cognition, activities of daily living, behavior, communication/social interaction, and quality of life; 4) applicable to all AD severity stages; 5) able to monitor disease progression; and 6) sensitive to measure therapy effects. Methods: The National Library of Medicines' MEDLINE database was searched for the years 1981 to September 2008, using a set of keywords aiming to select instruments which cover at least some of the requirements for an ideal practical AD scale for therapy evaluation. Measures for AD staging and screening tests were not considered for review. Results: Of 1,902 articles resulting from the literature search, 68 relevant AD scales were identified. Most of them were scales that predominantly measure the severity of major dysfunctions in particular AD domains. Only five scales met some of the requirements for a practical multi-domain AD scale, but did not possess all required characteristics. Conclusions: Despite the multitude of AD scales for various purposes, there remains a need for a new multi-domain and easy to administer AD scale for assessment of disease progression and response to therapy in daily medical practice.

Vascular risk factors and Alzheimer's disease: are these risk factors for plaques and tangles or for concomitant vascular pathology that increases the likelihood of dementia? An evidence-based review

Helena Chui — 2012-01-04T00:00:00Z

Recent epidemiologic studies have noted that risk factors for atherosclerosis (for example, diabetes mellitus, hypertension, and hyperlipidemia) are associated with increased risk of incident Alzheimer's disease (AD). In this evidence-based review, we frame the proposition as a question: are vascular risk factors also risk factors for plaques and tangles or just for concomitant vascular pathology that increases the likelihood of dementia? To date, no representative, prospective studies with autopsy (evidence level A) show significant positive associations between diabetes mellitus, hypertension, or intracranial atherosclerosis and plaques or tangles. Some prospective, representative, epidemiologic studies (evidence level B) show associations between diabetes, hypertension, hyperlipidemia, and aggregated risk factors with clinically diagnosed incident AD. However, the strength of association diminishes in the following order: vascular dementia (VaD) > AD + VaD > AD. This pattern is arguably more consistent with the hypothesis that atherosclerosis promotes subclinical vascular brain injury, thereby increasing the likelihood of dementia and in some cases making symptoms present earlier. Several autopsy studies from AD brain banks (evidence level C) have observed positive associations between intracranial atherosclerosis and severity of plaques and tangles. However, these studies may reflect selection bias; these associations are not confirmed when cases are drawn from non-dementia settings. We conclude that, at the present time, there is no consistent body of evidence to show that vascular risk factors increase AD pathology.

Statins and Therapy of Alzheimer's disease: Questions of Efficacy versus Trial Design

Benjamin Wolozin — 2012-01-16T00:00:00Z

Recent trials of statins produced no benefit for subjects with Alzheimer's disease. These negative studies add to a growing list of negative clinical trials. These data point to a need for reevaluating the pathophysiology of late-onset Alzheimer's disease. Late-onset Alzheimer's disease might result from the cumulative effects of at least four different factors: β-amyloid accumulation, cardiovascular disease, aging and the associated loss of synaptic plasticity, and inflammation. Successful therapy of subjects with overt dementia might require approaches targeting all four pathophysiological domains.

Predicting progression of Alzheimer's disease

Rachelle Doody — 2010-02-23T00:00:00Z

IntroductionClinicians need to predict prognosis of Alzheimer's disease (AD), and researchers need models of progression to develop biomarkers and clinical trials designs. We tested a calculated initial progression rate to see whether it predicted performance on cognition, function and behavior over time, and to see whether it predicted survival. Methods: We used standardized approaches to assess baseline characteristics and to estimate disease duration, and calculated the initial (pre-progression) rate in 597 AD patients followed for up to 15 years. We designated slow, intermediate and rapidly progressing groups. Using mixed effects regression analysis, we examined the predictive value of a pre-progression group for longitudinal performance on standardized measures. We used Cox survival analysis to compare survival time by progression group. Results: Patients in the slow and intermediate groups maintained better performance on the cognitive (ADAScog and VSAT), global (CDR-SB) and complex activities of daily living measures (IADL) (P values < 0.001 slow versus fast; P values < 0.003 to 0.03 intermediate versus fast). Interaction terms indicated that slopes of ADAScog and PSMS change for the slow group were smaller than for the fast group, and that rates of change on the ADAScog were also slower for the intermediate group, but that CDR-SB rates increased in this group relative to the fast group. Slow progressors survived longer than fast progressors (P = 0.024). Conclusions: A simple, calculated progression rate at the initial visit gives reliable information regarding performance over time on cognition, global performance and activities of daily living. The slowest progression group also survives longer. This baseline measure should be considered in the design of long duration Alzheimer's disease clinical trials.

A Quick Test of cognitive speed is sensitive in detecting early treatment response in Alzheimer's disease

Sebastian Palmqvist — 2010-10-15T00:00:00Z

IntroductionThere is a great need for quick tests that identify treatment response in Alzheimer's disease (AD) to determine who benefits from the treatment. In this study, A Quick Test of cognitive speed (AQT) was compared with the mini-mental state examination (MMSE) in the evaluation of treatment outcome in AD. Methods: 75 patients with mild to moderate AD at a memory clinic were assessed with AQT and the MMSE at a pretreatment visit, at baseline and after 8 weeks of treatment with cholinesterase inhibitors (ChEI) initiated at baseline. Changes in the mean test scores before and after treatment were compared, as well as the number of treatment responders detected by each test, according to a reliable change index (RCI). Results: After 8 weeks of treatment, the AQT improvement, expressed as a percentage, was significantly greater than that of the MMSE (P = 0.026). According to the RCI, the cut-offs to define a responder were ≥16 seconds improvement on AQT and ≥3 points on the MMSE after 8 weeks. With these cut-offs, both tests falsely classified ≤5% as responders during the pretreatment period. After 8 weeks of treatment, AQT detected significantly more responders than the MMSE (34% compared with 17%; P = 0.024). After 6 months of treatment, the 8-week AQT responders still showed a significantly better treatment response than the AQT nonresponders (22.3 seconds in mean difference; P < 0.001). Conclusions: AQT detects twice as many treatment responders as the MMSE. It seems that AQT can, already after 8 weeks, identify the AD patients who will continue to benefit from ChEI treatment.

Lipidomics of Alzheimer's disease: Current status.

Paul Wood — 2012-02-01T00:00:00Z

Alzheimer's disease (AD) is a cognitive disorder with a number of complex neuropathologies, including, but not limited to, neurofibrillary tangles, neuritic plaques, neuronal shrinkage, hypomyelination, neuroinflammation and cholinergic dysfunction. The role of underlying pathological processes in the evolution of the cholinergic deficit responsible for cognitive decline has not been elucidated. Furthermore, generation of testable hypotheses for defining points of pharmacological intervention in AD are complicated by the large scale occurrence of older individuals dying with no cognitive impairment despite having a high burden of AD pathology (plaques and tangles). To further complicate these research challenges, there is no animal model that reproduces the combined hallmark neuropathologies of AD. These research limitations have stimulated the application of 'omics' technologies in AD research with the goals of defining biologic markers of disease and disease progression and uncovering potential points of pharmacological intervention for the design of AD therapeutics. In the case of sporadic AD, the dominant form of dementia, genomics has revealed that the ε4 allele of apolipoprotein E, a lipid transport/chaperone protein, is a susceptibility factor. This seminal observation points to the importance of lipid dynamics as an area of investigation in AD. In this regard, lipidomics studies have demonstrated that there are major deficits in brain structural glycerophospholipids and sphingolipids, as well as alterations in metabolites of these complex structural lipids, which act as signaling molecules. Peroxisomal dysfunction appears to be a key component of the changes in glycerophospholipid deficits. In this review, lipid alterations and their potential roles in the pathophysiology of AD are discussed.

Progranulin axis and recent developments in frontotemporal lobar degeneration

Alexandra Nicholson — 2012-01-23T00:00:00Z

Frontotemporal lobar degeneration (FTLD) is a devastating neurodegenerative disease that is the second most common form of dementia affecting individuals under age 65. The most common pathological subtype, FTLD with transactive response DNA-binding protein with a molecular weight of 43 kDa inclusions (FTLD-TDP), is often caused by autosomal dominant mutations in the progranulin gene (GRN) encoding the progranulin protein (PGRN). GRN pathogenic mutations result in haploinsufficiency, usually by nonsense-mediated decay of the mRNA. Since the discovery of these mutations in 2006, several groups have published data and animal models that provide further insight into the genetic and functional relevance of PGRN in the context of FTLD-TDP. These studies were critical in initiating our understanding of the role of PGRN in neural development, degeneration, synaptic transmission, cell signaling, and behavior. Furthermore, recent publications have now identified the receptors for PGRN, which will hopefully lead to additional therapeutic targets. Additionally, drug screens have been conducted to identify pharmacological regulators of PGRN levels to be used as potential treatments for PGRN haploinsufficiency. Here we review recent literature describing relevant data on GRN genetics, cell culture experiments describing the potential role and regulators of PGRN in the central nervous system, animal models of PGRN deficiency, and potential PGRN-related FTLD therapies that are currently underway. The present review aims to underscore the necessity of further elucidation of PGRN biology in FTLD-related neurodegeneration.

Molecular imaging in Alzheimer's disease: new perspectives on biomarkers for early diagnosis and drug development

Agneta Nordberg — 2011-12-02T00:00:00Z

Recent progress in molecular imaging has provided new important knowledge for further understanding the time course of early pathological disease processes in Alzheimer's disease (AD). Positron emission tomography (PET) amyloid beta (Aβ) tracers such as Pittsburgh Compound B detect increasing deposition of fibrillar Aβ in the brain at the prodromal stages of AD, while the levels of fibrillar Aβ appear more stable at high levels in clinical AD. There is a need for PET ligands to visualize smaller forms of Aβ, oligomeric forms, in the brain and to understand how they interact with synaptic activity and neurodegeneration. The inflammatory markers presently under development might provide further insight into the disease mechanism as well as imaging tracers for tau. Biomarkers measuring functional changes in the brain such as regional cerebral glucose metabolism and neurotransmitter activity seem to strongly correlate with clinical symptoms of cognitive decline. Molecular imaging biomarkers will have a clinical implication in AD not only for early detection of AD but for selecting patients for certain drug therapies and to test disease-modifying drugs. PET fibrillar Aβ imaging together with cerebrospinal fluid biomarkers are promising as biomarkers for early recognition of subjects at risk for AD, for identifying patients for certain therapy and for quantifying anti-amyloid effects. Functional biomarkers such as regional cerebral glucose metabolism together with measurement of the brain volumes provide valuable information about disease progression and outcome of drug treatment.

Predicting Alzheimer's risk: Why and how?

Deborah Barnes — 2011-11-25T00:00:00Z

Because the pathologic processes that underlie Alzheimer's disease (AD) appear to start 10 to 20 years before symptoms develop, there is currently intense interest in developing techniques to accurately predict which individuals are most likely to become symptomatic. Several AD risk prediction strategies - including identification of biomarkers and neuroimaging techniques and development of risk indices that combine traditional and non-traditional risk factors - are being explored. Most AD risk prediction strategies developed to date have had moderate prognostic accuracy but are limited by two key issues. First, they do not explicitly model mortality along with AD risk and, therefore, do not differentiate individuals who are likely to develop symptomatic AD prior to death from those who are likely to die of other causes. This is critically important so that any preventive treatments can be targeted to maximize the potential benefit and minimize the potential harm. Second, AD risk prediction strategies developed to date have not explored the full range of predictive variables (biomarkers, imaging, and traditional and non-traditional risk factors) over the full preclinical period (10 to 20 years). Sophisticated modeling techniques such as hidden Markov models may enable the development of a more comprehensive AD risk prediction algorithm by combining data from multiple cohorts. As the field moves forward, it will be critically important to develop techniques that simultaneously model the risk of mortality as well as the risk of AD over the full preclinical spectrum and to consider the potential harm as well as the benefit of identifying and treating high-risk older patients.