Uniting Data for Memory: Building Informatics against Alzheimer´s

In the absence of revolutionary therapeutics, the number of people afflicted with Alzheimer´s disease is expected to grow dramatically from an estimated 26 million today to more than 100 million world-wide in the next 40 years. This huge unmet need has spurred a large investment from the medical community, including both naturalistic, public studies and clinical trials within industry. Since it is widely accepted that the underlying disease pathology can start more than 10 years before a patient´s clinical determination of Alzheimer´s, these trials can include a large variety of biomarkers, including genetic, proteomic, and imaging outputs, in additional to a spectrum of clinical and functional scales. Leveraging the potential of all these studies requires a significant informatics effort to ingest, curate, store, and manipulate the data, such that they can be used effectively for data mining. One aspect of our own efforts in this area has centered on loading to a common database schema, from which tool sets and analyses routines can be standardized. This has allowed us to greatly accelerate hypothesis generation, making the selection of potential covariates a data driven, rather than theoretical, exercise. A second part of the effort has focused on the mapping of terms found in individual studies to public ontologies, which provides a framework for translating results across trials.