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UCSD Using $12M NIH Grant to Expand 'One-Stop Shop' for Metabolomics Data


NEW YORK (GenomeWeb) – Researchers at the University of California, San Diego have received a four-year, $12 million grant from the National Institutes of Health to further develop the Metabolomics Workbench, a repository of metabolomics data, metadata, and other resources intended for research use and, eventually, clinical applications.

This new funding will allow the researchers expand the Workbench to include a wide range of clinical data including demographic information for patients and participants in clinical trials. They will also collect information on study size, the randomization process, nature and duration of interventions, and other critical information. These datasets will be collected and made available for use in accordance with existing IRB protocols and HIPAA regulations including offering controlled access to some datasets.

Motivated by recent technological advancements and the potential value of metabolite measurements for providing insights into pathological states, the NIH awarded $6 million to fund development of the Workbench in 2012, said Shankar Subramaniam, a bioengineering professor in the Jacobs School of Engineering at UC San Diego and the principal investigator of the project.

That initial grant was part of the NIH Common Fund Metabolomics Program which was launched in 2012 to facilitate metabolomics-focused biomedical research in the US. Furthermore, in 2016, the NIH earmarked an additional $1 million in funding to support six or seven projects aimed at fostering collaboration between computational scientists, metabolomics experts, and biomedical researchers to develop, pilot, and validate novel bioinformatics approaches for metabolomics data.

Subramaniam's lab focuses on research in systems biology and systems medicine, including diseases of the liver, muscles, brain and vascular system. In addition to metabolomics, his team works with transcriptomic, epigenomics, microRNA, and some proteomic data. Given the diverse data types they work with, they were interested in developing tools that would make it possible to integrate their datasets.

Technologies such as mass spectrometry have "evolved to a really sophisticated point to where people can measure thousands and thousands of metabolites concurrently from a sample whether it’s a cell or some fluid," he said. This means that metabolomics, which has largely taken a back seat to other omics technologies, can now move to the forefront. Recently, Nightingale Health and the UK Biobank announced plans to analyze metabolic biomarkers linked to heart disease, type 2 diabetes, and other common chronic diseases in 500,000 blood samples.

In 2016, UCSD researchers published a metabolomics-based study of patients with chronic fatigue syndrome. Their tests showed, among other findings, that patients with CFS showed a measurable decrease in 80 percent of 612 analytes and abnormalities in 20 pathways, including lipid, purine, cholesterol, and mitochondrial metabolism. Another 2016 study, this time performed by Austrian researchers, identified changes in blood metabolite levels in patients who had undergone weight loss surgery.

Over the last six years, Subramaniam and his team have gathered data from more than 1,000 metabolomics studies for the Workbench. Some of these studies involve hundreds and in some cases thousands of patient samples. The Workbench, which is housed in the cloud at the San Diego Supercomputer Center, currently contains over 50,000 experimentally annotated metabolites along with over 1 million computationally generated metabolites described in terms of their structure, classification, and computed spectra. Furthermore, "we developed a new ontology [and] a new classification system for understanding metabolites in a uniform context," Subramaniam said.

In 2016, he and his team published a paper in Nucleic Acids Research describing the platform. According to the paper, the Workbench includes data from more than 20 different species including metabolites from the date palm fruit. It also serves as a public data repository for metadata associated with metabolites as well as metabolite standards, structures, protocols, tutorials, and training material along with a series of statistical analysis tools. The paper also described a partnership with the European Bioinformatics Institute and its MetaboLights project team to facilitate metabolomics data exchange among different data repositories.

The repository currently holds metabolomic datasets in multiple formats, including spectrometric; spectrographic and chromatographic information derived from MS, NMR, and gas chromatographic platforms; and associated unique chemical entities and quantitative values where appropriate. Some experiments also offer access to ion mobility or other orthogonal chromatographic information; topological information with mass spec imaging; and isotopic information including isotopoloques and isotopomers. As metabolomic technologies continue to evolve, the developers plan to expand the Workbench to include new data formats and content.

For their next steps, the developers are looking to move the Workbench into clinical contexts where they believe it could help researchers and physicians develop better tools for using metabolite markers in blood, for example, to diagnose disease. Just as it's currently possible to genotype individuals, the hope is that the Workbench could be used to "metabotype" people at different time points, Subramaniam said. Since metabolite levels change depending on factors like disease, diet, and medications, characterizing the metabolome could offer useful insights into differences between disease versus normal states. This would be useful for clinicians trying to correlate changes in the metabolome with diseases. For example, an abnormal creatinine level may be correlated with an infection or some other medical phenotype, he said.

Over the next four years, Subramaniam and his team will work on gathering large quantities of human subject data from different clinical trials. This will include data gleaned from blood, urine, fecal, and saliva samples as well as some tissue-specific data. They will also work on annotating the information from these studies.

"We are already collaborating with a number of large-scale projects to facilitate this," he said. These studies focus on metabolomic activity in diseases like cancer, diabetes, and infectious diseases. Furthermore, he added, "we will try to provide tools and resources for researchers to map [these data] into metabolic pathways, functional pathways and disease pathways."

Other planned developments include adding functionality for researchers looking to customize the repository for internal use as well as tools to simplify the process of depositing, searching, and retrieving data. Specifically, they will develop interfaces and tools for easy access to querying and analyzing the data along with application programming interfaces to add or extend existing tools and interfaces. The developers also plan to make the Workbench available as a container for researchers who want to analyze data from the resource with their own tools. Researchers will also be able to combine their own data with the Workbench data and analyze the datasets in tandem.

The updated iteration of the Workbench will provide "a one-stop shop for understanding the context of metabolites with reference to human physiology," Subramaniam said. He also sees potential applications of the Workbench in the context of precision medicine. "Everybody has a certain homeostatic standard [so] if there is a deviation from the steady state, we can look at how it varies for John Doe versus Jane Smith," he said. "It really provides a powerful way for precision medicine [researchers] to understand what is normal and abnormal for the individual."

Since its development, researchers have used the Workbench to study metabolomic activity in diseases such as diabetes and cancer. Gabriel Haddad, chair of UC San Diego’s Department of Pediatrics and Chief Scientific Officer at Rady Children’s Hospital San Diego, noted in a statement that the additions to the Workbench "will allow us to ask better questions and pose new hypotheses." Haddad’s research focuses on cardiovascular disease and atherosclerosis. Key to his work is gaining access to information about the patient’s metabolome and microbiome, which the Workbench provides, he noted.