Transforming 'big data' into knowledge
The first, a combined grant from both the National Human Genome Research Institute and the National Institute for Mental Health for $16.5 million, will establish a Center for Excellence in Genomic Science, or CEGS.
The second grant, for $11.3 million, is from the NIH Common Fund's Big Data to Knowledge (BD2K) initiative.
Isaac Kohane, director of the Center for Biomedical Informatics and the Lawrence J. Henderson Professor of Pediatrics at Boston Children's Hospital, is the principal investigator on both grants. Shawn Murphy, HMS associate professor of neurology at Massachusetts General Hospital, is co-principal investigator on the second grant.
For the Center for Excellence in Genomic Science grant, the CBMI is one of nine newly established centers. The primary aim of this program is to gain deeper insights into both the phenotyping, and ultimately diagnosing and treating, of neuropsychiatric illness—something which remains difficult despite the tremendous gains in biomedical technology over the decades.
Currently, much diagnosis of neuropsychiatric illness is, at best, vague, due to tremendous overlap of clinical symptoms among different conditions and other factors. The researchers will create a platform in which clinicians can merge information from a patient's electronic health records with genomic data gleaned from that same patient's own neurons.
Because neurons cannot be extracted from living persons, the researchers will use an approach common in regenerative biology, namely, taking skin biopsies from patients and transforming these samples into neurons that are genetically identical with the patient's own "natural" brain cells.
Having the ability to match individualized cells with a patient's health records will help researchers chart the trajectory from molecular manifestation to particular disease attributes and gain deeper understanding into how closely a clinical diagnosis matches the patient's genetic, and even epigenetic, cellular profile. This will also provide clues for potential therapies.
"This is individualized medicine in the truest sense of the word," said Kohane.
"This is a ground breaking project to develop precision medicine for psychiatry by classifying disorders based on cutting edge biology as well as clinical presentations. If successful, CEGS could transform the way we help people with mental disorders," said Thomas R. Insel, M.D., director of the National Institute of Mental Health.
Collaborators for this project include Michael Greenberg, the Nathan Marsh Pusey Professor of Neurobiology and head of the department of neurobiology at HMS, and Roy Perlis, HMS associate professor of psychiatry at Massachusetts General Hospital.
The second grant is part of the NIH Big Data to Knowledge program, or BD2K. The HMS Center for Biomedical Informatics is one of 12 centers awarded this grant for the purpose of analyzing and leveraging the explosion of increasingly complex biomedical data sets.
The BD2K program builds on an earlier project called i2b2 (Informatics for Integrating Biology and the Bedside) in which researchers developed a software platform that could translate clinical data from healthcare systems into an information data set for the research community to investigate—all while maintaining patient privacy.
For BD2K, they plan on growing this approach by an order of magnitude. The researchers will expand their software to include not only conventional data, sources such as electronic health records, but unconventional data sources that include all the commonly used consumer social media platforms. Just like i2b2, patient privacy is an essential component of the system.
"If you really want to understand where people stand diagnostically, you need to bring all these various elements together," said Kohane. "People say many important things about their health in social media, and if a critical mass of individuals grant their physicians permission to access this and we can then start matching information from tens of thousands of patients, meaningful patterns will emerge that could not have been ascertained through conventional means."
The researchers will develop a free, open-source software program that allows scientists to create virtual databases representing populations from a multidimensional perspective, a global common ground for sharing data that CBMI researchers refer to as the "information commons."
In addition to Murphy, collaborators for this project include Tianxi Cai, professor of biostatistics at the Harvard School of Public Health; Peter Szolovits, professor of computer science and engineering and health sciences and technology at Massachusetts Institute of Technology; and other members of the CBMI faculty.
"This work really helps facilitate the waltz between basic and translational science," said Kohane. "We want to do everything we can to support and further the work of all our colleagues by creating tools that effectively make sense out of big data sets, where everyone can play a role and contribute to this 'commons' writ large."
Provided by Harvard Medical School