Early diagnosis of Alzheimer dementia based on clinical and biological factors
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Alzheimer’s disease (AD) is common in elderly individuals; it causes distress for the patients and their relatives as well as large costs for the society. With the advent of symptomatic treatment at present and probable etiology-based cures in the future, it will be possible to relieve and put an end to these negative effects. Therefore, it is necessary to diagnose the disease as early as possible. In this review, we briefly summarize the state-of-the-art concerning various available clinical and biochemical methods for identifying AD. Increasing age, heritage, and presence of ApoE e4 allele have been confirmed as risk factors for AD as well as some putative factors (e.g., low education, hypertension, hypotension) based on epidemiological recent research. Selective impairment of episodic memory has been found to be a preclinical marker for future development of AD based on convergent data from asymptomatic AD-related mutation carriers, longitudinal studies of patients with mild cognitive impairment (MCI), and epidemiological studies of incident AD cases. Neurophysiological methods are inexpensive and useful for the identification of changes in brain dysfunction in AD and new promising methods are under development. Using magnetic resonance imaging (MRT), structural measurements of brain atrophy and specific brain structures such as the hippocampus have been reported to detect dementia development early in the course of disease. Similarly, functional measurements of brain activity (e.g., blood flow) have revealed that hypometabolism in bilateral parietotemporal brain areas early in the disease course. Finally, biochemical studies have demonstrated that certain proteins (e.g., tau the Aβ1-42/43 metabolite of the amyloid precursor protein) may be associated with the disease process in AD, although the specificity of these markers remains to be established. It is concluded that still no single marker of AD exists, which makes it necessary to rely on data from multiple sources in order to arrive at the best possible diagnosis of AD.