Every 66 seconds, someone in the United States develops Alzheimer’sDisease (AD). In 2016, the costs of providing care to individuals with AD are expected to total more than $236 million. By mid-century, a new diagnosis will occur every 33 seconds, and costs are expected to exceed $1 trillion annually. Despite the dire public health implications of this, AD remains the only top-10 cause of mortality in the United States, without any disease modifying treatments available.
Understanding the complexity of AD is compounded by the long pre-clinical course of disease, with the earliest changes occurring in the most vulnerable brain regions perhaps three decades before clinical symptoms, such as memory loss, become apparent. By this stage, however, there are often profound changes in brain structure, including significant neuropathology and neuronal loss. An important step in making these questions addressable, is the widespread adoption of technologies that can efficiently generate rich, unbiased profiles of biological systems. Genome sequencing technologies allow the identification of changes in DNA that alter individual risk for AD, and give investigators clues about which parts of the cellular machinery are relevant to disease. RNA sequencing allows a high dimensional snapshot of gene expression, allowing the identification of networks of genes that are changed in AD. Electronic medical records can be studied to identify other diagnoses or pathology results that may associate with, or even precede AD.
Interpreted in isolation, technologies have lessons to offer, but increasingly, the most exciting advances are emerging from integrative views, that try to build systematic and coherent pictures of disease from as many different biological perspectives as possible.
Our work at INGH includes a major focus on developing and applying these sorts of integrative approaches to multiscale genomics data for the goal of improving therapeutic options for patients with neurodegenerative diseases, especially AD. This involves incorporating as many high quality data types as we can find (includingDNA sequence, transcriptomic, methylation, proteomic, metabolomic and clinical data), to build network models that capture important causal relationships that are important inAD. We are especially interested in understanding the basis of the earliest changes, seen in the most vulnerable brain regions, the hippocampus and entorhinal cortex.
Our studies into these nascent shadows of disease have indicated a complex web of interactions between the immune system, and a chronic response to common pathogens, all occurring in an organ system that has limited options for dealing which infection. Our investigations into this area has lead to the pursuit of novel mechanisms that appear to underlie widespread changes we see at the earliest phases of AD, as well as specific cellular targets that appear to mediate important molecular changes in AD. This has helped guide further efforts to characterize and validate these strategically important genes in experimental AD models, for the goal of accelerating drug discovery, drug repurposing and biomarker discovery in AD.