Report of the National Heart, Lung, and Blood Institute Working Group: An Integrated Network for Congenital Heart Disease Research.

The National Heart, Lung, and Blood Institute convened a working group in January 2015 to explore issues related to an integrated data network for congenital heart disease research. The overall goal was to develop a common vision for how the rapidly increasing volumes of data captured across numerous sources can be managed, integrated, and analyzed to improve care and outcomes. This report summarizes the current landscape of congenital heart disease data, data integration methodologies used across other fields, key considerations for data integration models in congenital heart disease, and the short- and long-term vision and recommendations made by the working group.

Common measures in mental health: a joint initiative by funders and journals.

There is notable heterogeneity in how clinical and phenotypic data are measured by mental health researchers. There is a proliferation of self-report measures (eg, over 280 for depression alone), meaning it is challenging for researchers to compare findings across different studies from different laboratories. To begin to address this issue, a consortium of mental health research funders and journals has launched the Common Measures in Mental Health Science Initiative. The purpose of this endeavour is to identify common measures for mental health conditions that funders and journals can require all researchers to collect, in addition to any other measures they require for their specific study. These measures would not necessarily capture the full range of experiences of a given condition but could be used to link and compare across studies with different designs in different contexts. This Health Policy outlines the rationale, objectives, and potential challenges of this initiative, which aims to enhance the rigour and comparability of mental health research by promoting the adoption of standardised measures.

A Collaborative Effort to Establish Common Metrics for Use in Mental Health.

This Viewpoint provides a summary of a new project launched by a coalition of research funders and journals to improve the measures used in mental health research.

Can data repositories help find effective treatments for complex diseases?

There are many challenges to developing treatments for complex diseases. This review explores the question of whether it is possible to imagine a data repository that would increase the pace of understanding complex diseases sufficiently well to facilitate the development of effective treatments. First, consideration is given to the amount of data that might be needed for such a data repository and whether the existing data storage infrastructure is enough. Several successful data repositories are then examined to see if they have common characteristics. An area of science where unsuccessful attempts to develop a data infrastructure is then described to see what lessons could be learned for a data repository devoted to complex disease. Then, a variety of issues related to sharing data are discussed. In some of these areas, it is reasonably clear how to move forward. In other areas, there are significant open questions that need to be addressed by all data repositories. Using that baseline information, the question of whether data archives can be effective in understanding a complex disease is explored. The major goal of such a data archive is likely to be identifying biomarkers that define sub-populations of the disease.

Digital biology: an emerging and promising discipline.

This article examines the role of computation and quantitative methods in modern biomedical research to identify emerging scientific, technical, policy and organizational trends. It identifies common concerns and practices in the emerging community of computationally-oriented bio-scientists by reviewing a national symposium, Digital Biology: the Emerging Paradigm, held at the National Institutes of Health in Bethesda, Maryland, November 6th and 7th 2003. This meeting showed how biomedical computing promises scientific breakthroughs that will yield significant health benefits. Three key areas that define the emerging discipline of digital biology are: scientific data integration, multi-scale modeling and networked science. Each area faces unique technical challenges and information policy issues that must be addressed as the field matures. Here we summarize the emergent challenges and offer suggestions to academia, industry and government on how best to expand the role of computation in their scientific activities.

Sharing heterogeneous data: the national database for autism research.

The National Database for Autism Research (NDAR) is a secure research data repository designed to promote scientific data sharing and collaboration among autism spectrum disorder investigators. The goal of the project is to accelerate scientific discovery through data sharing, data harmonization, and the reporting of research results. Data from over 25,000 research participants are available to qualified investigators through the NDAR portal. Summary information about the available data is available to everyone through that portal.

Core facilities: maximizing the return on investment.

To conduct high-quality state-of-the-art research, clinical and translational scientists need access to specialized core facilities and appropriately trained staff. In this time of economic constraints and increasing research costs, organized and efficient core facilities are essential for researchers who seek to investigate complex translational research questions. Here, we describe efforts at the U.S. National Institutes of Health and academic medical centers to enhance the utility of cores.

Crystal structures of human mitochondrial branched chain aminotransferase reaction intermediates: ketimine and pyridoxamine phosphate forms.

The three-dimensional structures of the isoleucine ketimine and the pyridoxamine phosphate forms of human mitochondrial branched chain aminotransferase (hBCATm) have been determined crystallographically at 1.9 A resolution. The hBCATm-catalyzed transamination can be described in molecular terms together with the earlier solved pyridoxal phosphate forms of the enzyme. The active site lysine, Lys202, undergoes large conformational changes, and the pyridine ring of the cofactor tilts by about 18 degrees during catalysis. A major determinant of the enzyme's substrate and stereospecificity for L-branched chain amino acids is a group of hydrophobic residues that form three hydrophobic surfaces and lock the side chain in place. Short-chain aliphatic amino acid side chains are unable to interact through van der Waals contacts with any of the surfaces whereas bulky aromatic side chains would result in significant steric hindrance. As shown by modeling, and in agreement with previous biochemical data, glutamate but not aspartate can form hydrogen bond interactions. The carboxylate group of the bound isoleucine is on the same side as the phosphate group of the cofactor. These active site interactions are largely retained in a model of the human cytosolic branched chain aminotransferase (hBCATc), suggesting that residues in the second tier of interactions are likely to determine the specificity of hBCATc for the drug gabapentin. Finally, the structures reveal a unique role for cysteine residues in the mammalian BCAT. Cys315 and Cys318, which immediately follow a beta-turn (residues 311-314) and are located just outside the active site, form an unusual thiol-thiolate hydrogen bond. This beta-turn positions Thr313 for its interaction with the pyridoxal phosphate oxygens and substrate alpha-carboxylate group.