Cognitive and behavioral heterogeneity in Alzheimer's disease: seeking the neurobiological basis

Abstract

Alzheimer's disease (AD) is manifested by core features of progressive memory impairment, visuospatial decline, aphasia, and loss of executive function. In addition, patients may evidence a variety of other cognitive and behavioral features. The neurobiological basis for this clinical heterogeneity is uncertain but corresponding abnormalities on functional imaging suggest that variations in the distribution of the pathogenic changes in AD account for some of the observed clinical differences. Behavioral as well as cognitive variability has been correlated with disturbances on positron emission tomography and single photon emission computerized tomography. Functional imaging can reveal characteristic brain activity changes in AD, distinguish AD from other dementia syndromes, assess the integrity of transmitter systems in AD, determine the effect of cognitive enhancing and psychotropic drugs on metabolism and transmitter system function in AD, and possibly predict treatment responsiveness. Animal models of AD may improve our understanding of clinical variations in human AD. Thus far, development of cognitive tests for transgenic mice with AD pathology has been limited. Evaluations paralleling human neuropsychological tests are needed. In addition, technologies facilitating behavioral observations relevant to psychosis, depression, apathy, and agitation in AD have not been developed for transgenic models. Application of experiments inducing animal equivalents of depression and psychosis to determine the vulnerability of animal models of AD to these conditions may provide additional insights into human neuropsychiatric symptoms in AD. The efficacy of psychotropic drugs can be assessed in animal models of AD subjected to the provocative stimuli used in experimental models of psychopathology. There are a plethora of opportunities for basic scientists to offer insights, develop strategies, and provide techniques and technologies relevant to understanding the clinical manifestations of AD.