Advancing therapeutics depends on an improved understanding of the molecular biology and pathophysiology of AD. Target identification is a necessary step in developing new treatments. Transgenic models have been particularly informative for understanding disease pathways and signaling cascades and providing preliminary treatment target validation. The predictive validity of mouse models of AD has not been established but compounds that lack effects in these models would usually not be advanced to human testing. Investigators at UCLA have studied transgenic mouse models, transgenic rat models, and tau transgenic
Drosophila [
55]. The latter model is used as a bioassay to discover compounds potentially active in modifying tau pathology [
56,
57].
Greg Cole, Ph.D., is Associate Director of the UCLA-Easton Alzheimer’s Center and Associate Director for Research at the Geriatric Research, Education and Clinical Center for the Greater Los Angeles Veterans Administration System. Dr. Cole conducts research centered on the production and role of A
β in AD. He worked with Dr. Karen Hsiao to develop the first successful academic transgenic mouse model for AD [
58]. Based in part on a series of screens in pre-clinical models from his group, four compounds – ibuprofen [
59], R-flurbiprofen [
60], curcumin [
61], and docosahexaenoic acid (DHA) [
62,
63] – have advanced to clinical trials for AD. Dr. Cole and colleagues investigate the potential for AD prevention with DHA and their role in preventing amyloid formation and A
β toxicity, notably through induction of the AD protective gene, SorLA [
64]. Dr. Cole is exploring the efficacy of the curry spice extract curcumin to control inflammation and oxidative damage and to act directly on insoluble amyloid fibrils in plaques and on more soluble toxic A
β species
in vitro and
in vivo. Together with his colleague, Dr. Sally Frautschy, he developed a more bioavailable formulation of curcumin that is in current clinical trials for cancer [
65], and has planned for trials in AD. Dr. Cole works with Bruce Teter, Ph.D. on the role of apolipoprotein E as a risk factor for AD using transgenic mouse models and with Karen Gylys, R.N., Ph.D. on synaptic A
β analyzed by flow cytometry. They are currently evaluating agents from a variety of sources including the Easton Drug Discovery Consortium using multiple animal models for AD. Dr. Cole’s primary goal is to develop safe and widely available methods for the prevention of AD and possibly other degenerative diseases of aging.
Dr. David Teplow’s laboratory uses computational methods to identify structures in A
β that could be useful targets for therapeutic drugs. In the past, target identification has been problematic because A
β does not possess a stably folded structure. However,
in silico approaches allow atomic resolution of conformer structure, and importantly, an assessment of the thermodynamics of the A
β conformer space [
66,
67]. This latter achievement enables the targeting of steps in the A
β assembly process that should be amenable to drug intervention. Using this approach, simulations have revealed important differences between the conformational spaces of the shorter A
β40 peptide and the longer and more pathogenic A
β42 peptide. Multiple conformers have been revealed that may be involved in peptide oligomerization, a process postulated to be the key pathogenetic event in AD [
68]. The identification of these conformers provides a starting point both for subsequent simulations of A
β oligomerization and for experimental studies of the process. Dr. Teplow also has demonstrated that polyphenols derived from grape seed extracts inhibit the oligomerization of A
β [
69] and are promising treatment candidates.
Gal Bitan, Ph.D., currently focuses on the development of aggregation inhibitors using detailed knowledge of the three dimensional structure of the A
β peptide to develop rational pharmacotherapies that will prevent the aggregation of monomers into oligomers [
70,
71].
Hong-Wei Dong, Ph.D., has contributed to mapping gene expression in the normal mouse brain [
72,
73] and is now using these techniques to address gene expression in transgenic AD mouse models. These findings will be compared to gene expression observations in humans to determine the fidelity with which the transgenic model recapitulates the intracellular genetic activity of human AD.