Making all the data count for disease diagnosis and discovery

Diagnosing diseases is a tricky business requiring a formidable breadth and depth of knowledge and the skill to apply it. The rarer the disease is, the harder it can be to diagnose: quality reference data may not exist and a physician might only see one such patient in her entire career. According to the National Institutes of Health, there are between 6000 and 7000 rare diseases affecting from 25 to 30 million Americans, making it likely that most, if not all, healthcare professionals have seen these patients in their practice but may not have known it. Oftentimes, a patient with a rare disease gets misdiagnosed as having a more common disease with a similar set of symptoms. In such cases, the misdiagnosis can lead to ineffective, or even harmful treatment; this is a danger even for patients who have rarer forms of a common disease. For a patient living with a rare disease, the mean time to diagnosis is 4.8 years and can take as long as 20 years. Moreover, the patient sees an average of 7.3 physicians during this time.

Melissa Haendel, Ph.D.
Melissa Haendel, Ph.D.

At OHSU, a team of researchers led by Melissa Haendel, Ph.D., associate professor in the Library and in the Department of Medical Informatics and Clinical Epidemiology, recently received two large grants to tackle grand challenges like these. The first grant is from the NIH Office of the Director to support OHSU’s ongoing efforts with the “Monarch Initiative,” and the second is through a novel award mechanism called the “BioMedical Data Translator” from the National Center for Advancing Translational Science (NCATS). These grants support the creation and application of software tools that combine data from multiple sources to help researchers and physicians accurately diagnose patients and better understand the underlying causes of their illness.

MonarchUsing Monarch funds, Haendel and colleagues will continue their work building a comprehensive database of disease signs and symptoms–linking that information to other types of data including clinical observations, patient genetics, and animal research. Many rare diseases have a suspected genetic cause that is so far unknown. Monarch is integrating data from diverse sources with the goal of uncovering the possible implicated genes which could aid the development of both diagnostics and treatments for patients.

OHSU’s Knight Diagnostic Lab Inherited Disorders group led by Sue Richards, Ph.D., has been using Monarch’s tools to support diagnosis of rare genetic diseases since 2015 with great success. “Whole exome sequencing generates datasets containing over 70,000 genetic variants. These tools have improved the efficiency and ability to find the “needle-in-the-haystack,” said Richards. The use of Monarch resources has ”..ended the diagnostic odyssey for a range of cases from neurological conditions to metabolic disorders.”

The Data Translator project aims to increase the breadth, connectedness, and accessibility of diverse data. One of the core components of the project is a data integration and modeling platform developed by Haendel’s group, described in their paper designated “breakthrough” in the Jan. 4, 2017 edition of Nucleic Acids Research. This freely available software resource has several possible applications: 1) A clinician who has a hard-to-diagnose patient could search for either known diseases with similar symptoms or for animal model research that could aid in the patient’s diagnosis, 2) A patient or researcher interested in learning more about a particular disease’s symptoms and all genes implicated with that disease, and 3) A researcher wanting to learn which  diseases are most similar to the manifestations seen in their model organisms.

“What is really surprising is how when you put data together from many different sources, you fill in knowledge gaps – it really is a story of the sum being greater than the parts with respect to discovering and understanding the causes of disease.” — Melissa Haendel


More about this work. Haendel is a founding member of the Monarch Initiative (established 2012); the cross-disciplinary work of Monarch involves collaboration not only across groups within OHSU, but also with Lawrence Berkeley National Laboratory, The Jackson Laboratory, the University of Pittsburgh, Sanger Institute, Charité – Universitätsmedizin Berlin, Garvan Institute of Medical Research, and William Harvey Research Institute, Barts & The London School of Medicine & Dentistry, Queen Mary University of London. A full list of the partnering organizations and the members of the team can be found at In addition to the Monarch consortium partners above, the NCATS Data Translator project also includes the team members from Johns Hopkins, Scripps Research Institute, Jackson Laboratory, and the Mayo Clinic; together they are combining their data and tools with other NCATS Translator awardees to advance our understanding of the genetic and environmental determinants of disease. Wherever possible, data and software generated by the consortium are open access and open-source; see the Monarch portal at for more information.