Developing Biomarkers for Early Diagnosis of Dementia Based on Alzheimerâs Disease.
Alzheimerâs disease (AD) and other forms of dementia are one of the major public health and social challenges of our time that affects several million people worldwide. Dementia describes a set of symptoms that can include memory loss, thinking, problem-solving and language difficulties. AD is the most common form of dementia. AD is progressive and in the early stages may appear likes mild memory loss, but in later stages it can lead to loss of awareness and ability to interact socially. The number of people living with AD is rapidly rising and this is creating a significant burden on families and on the health and social care systems.
There are no treatments that can cure ADs or any other type of dementia. However, medicines have been developed for AD that can temporarily mitigate symptoms, or slow down their progression. AD is complex, and it is unlikely that any one medicine or other remidation can successfully cure it.
Early diagnosis or prediction of AD may provide an adequate opportunity for specialists to develop medications or other treatments to delay or stop the AD progression before any significant damage happens in the brain cells. Moreover, the early prediction is widely recognised as vital for patients and their families to get higher benefits from a suitable access to available health and social care and to plan for the future.
The development of new medication for AD has become of increasing societal importance given our elderly population and increasing longevity, combined with the truth that this disease ideally begins late in life. The functions of brain cells are progressively affected by damage caused by dementia. The brain changes caused by the ADs start 10 to 20 years before any clinically diagnosable signs or symptoms of amnesia appear. Various biomarkers can be used in a different ways to allow new treatements to be developed more quickly and to increase the probability of success in the substantial trials eventually needed to gain new drug approval by regulatory agencies. Biomarkers are probabily very useful as tools in investigational drug trials of clinically diagnosed AD patients. Such markers could be used as indirect markers of disease severity, or might also be used as additional inclusion or exclusion criteria. A clinical diagnosis of AD is inexact even among experienced investigators in about 10% to 15% of cases, and biomarkers might increase the accuracy of diagnosis. Importantly for the improvement of putative disease modifying medications for AD, biomarkers might also serve as indirect measures of disease severity.
Dementia can be detected by analysing biomarkers derived from biomedical signals (e.g. Electroencephalography EEG), medical images (e.g. Magnetic resonance imaging MRI, and Positron emission tomography PET), and biochemical analysis (e.g. Cerebrospinal fluid (CSF) proteins, and Proteins in blood or other parts of the body). Some robust technologies provide powerful insights into the performance of the brainâs activities. Information theoretic methods have emerged as a potentially useful way to develop a robust biomarkers to detect dementia based on changing in the function of the brain cells.
The main aim of this project is to develop robust biomarkers for early diagnosis of AD by using some information theoretic methods such as: Tsallis entropy, zero crossing interval density (ZCI), and fractal dimension (FD). Real datasets collected from AD and normal people will be used in this development. Furthermore, we will investigate novel application of robust biomarkers in healthcare for early prediction of dementia. For example, we will investigate novel methods for predicting AD in its early stages and characterize different stages of dementia.