View clinical trials related to Prodromal Alzheimer's Disease.
Filter by:A 2-arm (sequence), 2-period, 2-treatments, single blinded (outcome assessor), randomized crossover-trial (12+12 weeks with immediate contrast) comparing a low-carbohydrate-high-fat diet (LCHF) with a high-carbohydrate-low-fat diet (HCLF) among individuals with prodromal Alzheimer's disease.
This single-blind, three-arm, randomized, controlled trial will assess the impact of messages and financial incentives on the enrollment of demographically diverse individuals to the Alzheimer Prevention Trials (APT) Webstudy. The APT Webstudy is a novel, online registry that employs quarterly cognitive testing using validated platforms. The APT Webstudy implements fully remote assessments, coordinated by the Alzheimer's Therapeutic Research Institute (ATRI) under USC IRB #HS-17-00746. The purpose of the current study is to test whether we can increase enrollment of diverse individuals into the registry. To do this, we will work with Contra Costa Regional Medical Center (CCRMC), the county public hospital and its affiliated health centers in Contra Costa County, California, to test whether sending messages with and without financial incentives to patients who receive primary care with the health system can increase enrollment to the APT Webstudy. The investigators hypothesize that 1) a certain small financial incentive and an award opportunity based incentive (or a drawing with a prize) will increase enrollment rates of CCHS members into the APT Webstudy relative to the control group. The investigators further hypothesize that the award opportunity incentive will increase the enrollment rate of CCRMC patients into the APT Webstudy more than a certain financial incentive with the same expected value.
The primary objective of the study is to evaluate the efficacy of AGB101 on slowing cognitive and functional impairment as measured by reduction in neuronal injury in participants with mild cognitive impairment due to Alzheimer's Disease. Participants will be randomized to receive placebo or AGB101 (220 mg), once daily for 78 weeks. Secondary objectives are to assess the effect of AGB101 compared with placebo on clinical progression as measured by the Clinical Dementia Rating Scale- Sum of Boxes and Memory Box score.
Neurodegenerative diseases are a major health concern due to their growing societal implications and economic costs. The identification of early markers of pathogenic mechanisms is one of the current main challenges. The gut-brain axis has become a primary target because of its transversal role across the neurodegenerative spectrum and its effect on cognition. However, despite recent progress, how changes in the gut-microbiota composition can affect the human brain is still unclear. The goal of this observational study is to characterise the gut-microbiota composition associated with alterations in brain structure and function during the ageing process and across neurodegenerative disorders. This is based on recent studies showing that changes in the human brain and in the microbiota composition, can indicate very sensitively and in a predictive way pathological development and, consequently, be used as markers of neurodegenerative diseases. The main questions it aims to answer are: - How variation in the gut-microbiota composition correlates with the normal brain ageing trajectory? - How dysregulation in the gut-microbiota correlates with pathological changes in brain regions in specific neurodegenerative disorders? - Can the impact of the gut-microbiota on the brain be modulated by blood biomarkers? The investigators will recruit 40 young healthy participants, 40 old healthy participants, 40 participants with prodromal Alzheimer's Disease, 40 participants with Parkinson's Disease and 40 participants with Multiple Sclerosis. Participants will undergo the following examinations: - Magnetic Resonance Imaging - Analysis of a stool sample - Analysis of a blood sample - Neuropsychological assessment - Questionnaires on eating habits
The purpose of this study is to assess the safety, tolerability, immunogenicity and pharmacodynamic effects of ACI-24.060 in subjects with prodromal Alzheimer's disease and in non-demented adults with Down syndrome.
Alzheimer´s disease is a devastating illness that effects the patients as well as their family members. Its prevalence increases exponentially and the burden on the healthcare system is enormous. AD neuropathology begins 15-20 years before the occurrence of cognitive symptoms, which ranges from preclinical stage to mild cognitive impairment (MCI) to dementia. Prodromal AD is an early stage of the disease which is characterized by positive biomarkers and MCI. To this day, there is no medication that can cure or halt the progression of the disease and most studies focus on finding reversible risk factors and changing their influence. Several aetiologies have been proposed, like the deposition of amyloid and tau proteins, neuroinflammation and cerebral ischemia due to cerebrovascular factors. The Amyloid deposition, which serves as the biological marker of AD, was originally thought to be the main cause of the disease, however, recent data suggests that it is not the cause and that it might actually has a protective role. On the other hand, it is known today that vascular changes with related tissue ischemia and neuroinflammation have a crucial role in the development of AD in many patients. These pathologies, ischemia & neuroinflammation, can be improved by the use of hyperbaric oxygen therapy (HBOT). The goal of this study is to explore the potential beneficial effect of HBOT on prodromal AD.
A longitudinal observational neuroimaging study of individuals with Early Onset Alzheimer's disease during the prodromal phase, and matched control group - Ultrahigh Field MRI study at 7T
The primary objective of the study is to evaluate whether a set of algorithms analysing acoustic and linguistic patterns of speech, can predict change in Preclinical Alzheimer's Clinical Composite with semantic processing (PACC5) between baseline and +12 month follow up across all four Arms, as measured by the coefficient of individual agreement (CIA) between the change in PACC5 and the corresponding regression model, trained on baseline speech data to predict it. Secondary objectives include (1) evaluating whether similar algorithms can predict change in PACC5 between baseline and +12 month follow up in the cognitively normal (CN) and MCI populations separately; (2) evaluating whether similar algorithms trained to regress against PACC5 scores at baseline, still regress significantly against PACC5 scores at +12 month follow-up, as measured by the coefficient of individual agreement (CIA) between the PACC5 composite at +12 months and the regression model, trained on baseline speech data to predict PACC5 scores at baseline; (3) evaluating whether similar algorithms can classify converters vs non-converters in the cognitively normal Arms (Arm 3 + 4), and fast vs slow decliners in the MCI Arms (Arm 1 + 2), as measured by the Area Under the Curve (AUC) of the receiver operating characteristic curve, sensitivity, specificity and Cohen's kappa of the corresponding binary classifiers. Secondary objectives include the objectives above, but using time points of +24 months and +36 months; and finally to evaluate whether the model performance for the objectives and outcomes above improved if the model has access to speech data at 1 week, 1 month, and 3 month timepoints.
The primary objective of the study is to evaluate whether a set of algorithms analysing acoustic and linguistic patterns of speech can detect amyloid-specific cognitive impairment in early stage Alzheimer's disease, based on archival spoken or written language samples, as measured by the area under the curve (AUC) of the receiver operating characteristic curve of the binary classifier distinguishing between amyloid positive and amyloid negative arms. Secondary objectives include (1) evaluating how many years before diagnosis of Mild Cognitive Impairment (MCI) such algorithms work, as measured on binary classifier performance of the classifiers trained to classify MCI vs cognitively normal (CN) arms using archival material from the following time bins before MCI diagnosis: 0-5 years, 5-10 years, 10-15 years, 15-20 years, 20-25 years; (2) evaluating at what age such algorithms can detect later amyloid positivity, as measured on binary classifier performance of the classifiers trained to classify amyloid positive vs amyloid negative arms using archival material from the following age bins: younger than 50, 50-55, 55-60, 65-70, 70-75 years old.
The primary objective of the study is to evaluate whether a set of algorithms analysing acoustic and linguistic patterns of speech can detect amyloid-specific cognitive impairment in early stage Alzheimer's disease, as measured by the AUC of the receiver operating characteristic (ROC) curve of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) Arms. Secondary objectives include (1) evaluating whether similar algorithms can detect amyloid-specific cognitive impairment in the cognitively normal (CN) and MCI Arms respectively, as measured on binary classifier performance; (2) whether they can detect MCI, as measured on binary classifier performance (AUC, sensitivity, specificity, Cohen's kappa), and the agreement between the PACC5 composite and the corresponding regression model predicting it in all Arms pooled (Wilcoxon signed-rank test, CIA); (3) evaluating variables that can impact performance of such algorithms of covariates from the speaker (age, gender, education level) and environment (measures of acoustic quality).