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Late-onset Alzheimer's disease (LOAD) is the most common neurodegenerative disorder in older adults, affecting over 50% of those over age 85. Aging is the most important risk factor for the development of LOAD. Aging is associated with the decrease in the ability of cells to cope with cellular stress, especially protein aggregation. Here we describe how the process of aging affects pathways that control the processing and degradation of abnormal proteins including amyloid-β (Aβ). Genetic association studies in LOAD have successfully identified a large number of genetic variants involved in the development of the disease. However, there is a gap in understanding the interconnections between these pathomolecular events that prevent us from discovering therapeutic targets. We propose novel, pertinent links to elucidate how the biology of aging affects the sequence of events in the development of LOAD. Furthermore we analyze and synthesize the molecular-pathologic-clinical correlations of the aging process, involving the HSF1 and FOXO family pathways, Aβ metabolic pathway, and the different clinical stages of LOAD. Our new model postulates that the aging process would precede Aβ accumulation, and attenuation of HSF1 is an "upstream" event in the cascade that results in excess Aβ and synaptic dysfunction, which may lead to cognitive impairment and/or trigger "downstream" neurodegeneration and synaptic loss. Specific host factors, such as the activity of FOXO family pathways, would mediate the response to Aβ toxicity and the pace of progression toward the clinical manifestations of AD.

Diabetes, cardiovascular disease, hypertension, and other disorders have been unified within the metabolic syndrome. Recently, it has been proposed that Alzheimer's disease (AD) and other degenerative, age-related neurological disorders may also be etiologically linked to the metabolic syndrome in a metabolic-cognitive syndrome. We review current evidence in the field for this unification. In addition, we describe how the latent early-life associated regulation (LEARn) model provides specific mechanisms to predict genetic targets for both metabolic disorders, e.g., diabetes, and neurodegenerative disorders, e.g., AD. The LEARn model is based on environmental induction of latent epigenetic misregulation, which develops into disease upon suffering additional environmental insults. We review structural differences between gene sequences that are and are not susceptible to LEARn misregulation. In addition to suggesting research targets such as the IDE and SORCS1 genes, which are implicated in both AD and diabetes, LEARn suggests specific mechanisms for pre-disease remediation, based on nutritional adjustment of aberrant DNA methylation and oxidation. The possibility of a single metabolic-cognitive disorder opens up the possibility of unified preventative treatments that reduce monetary and social costs of disease. LEARn suggests specific, testable pathways within the large theory.

Alzheimer's disease is characterized by amyloid-beta peptide (Abeta)-loaded plaques in the brain. Abeta is a cleavage fragment of amyloid-beta protein precursor (APP) and over production of APP may lead to amyloidogenesis. The regulatory region of the APP gene contains consensus sites recognized by the transcription factor, specificity protein 1 (SP1), which has been shown to be required for the regulation of APP and Abeta. To understand the role of SP1 in APP biogenesis, herein we have characterized the relative distribution and localization of SP1, APP, and Abeta in various brain regions of rodent and primate models using immunohistochemistry. We observed that overall distribution and cellular localization of SP1, APP, and Abeta are similar and neuronal in origin. Their distribution is abundant in various layers of neocortex, but restricted to the Purkinje cell layer of the cerebellum, and the pyramidal cell layer of hippocampus. These findings suggest that overproduction of Abeta in vivo may be associated with transcriptional pathways involving SP1 and the APP gene.