Hood Lab Overview

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“Systems biology and medicine – not only in the lab but in the everyday lives of people – challenges the imagination and will transform the 21st Century.”

–Lee Hood, MD, PhD, Chief Strategy Officer and Co-Founder
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The Hood Lab is integrating biology, technology and computational science to enable a predictive, personalized, preventive and participatory (P4) approach to medicine. This P4 health care will leverage a systems approach, using new computational modeling and high-tech experimental tools in order to analyze the enormous amounts of molecular, cellular, phenotypic and medical data that can now be generated for each individual. The future of medicine – like so many aspects of our lives – will be utterly transformed by the era of “big data.” However, transforming data into action must be driven by deep domain expertise in biology. Medicine will be driven by exponential rises in capabilities and exponential declines in costs of key technologies for 1) high-throughput biological data generation, 2) the accessible storage of data (cloud) and 3) computing power. By viewing medicine as an informational science, P4 health care will draw on an understanding of complex biological networks underlying health and disease. The goals are to treat and prevent disease by identifying perturbations in biological networks, and reversing those perturbations through therapeutic intervention. While these new possibilities open up tremendous potential, there are very significant challenges to making this vision a reality.

The Hood Lab is deeply interested in building tools to help address these challenges. Our efforts focus on such areas as: 1) pioneering the tools and strategies of systems medicine (treatment after disease) and scientific wellness (preventing disease and optimizing health); 2) identifying molecular fingerprints of wellness and disease, and developing screening diagnostics that can differentiate the major diseases of organ-systems simultaneously; 3) pioneering leading-edge technologies and strategies (e.g., genomics, proteomics and single-cell analyses); 4) building integrated network models for human cells and model organisms that can provide mechanistic underpinnings for interpreting large-scale datasets relevant to health and disease; 5) monitoring biological perturbations on humans to convert data into an understanding of biological mechanism and new approaches for the discovery of candidate biomarkers and drug targets); and 6) translating our work to clinical value through our affiliation with Providence.

There are enormous opportunities here to participate in leading-edge science, technology and analytics while becoming engaged with some of the leading biological and medical problems of the 21st century. We are pushing the idea that 21st century medicine (P4 health care, systems medicine and scientific wellness) through systems approaches will transform the U.S. health care system.

Research Overview

The premise of the work in the Hood Lab is that diseases result from perturbations of biological networks. These perturbations may arise from biological changes, such as mutations in the digital information of the genome; from lifestyle choices such as diet, smoking or sedentary behaviors; or from environmental exposures, such as toxins or microbes. These disease-perturbed networks both cause and reflect the progression of a disease. Thus, diseases can be diagnosed, treated and prevented by understanding and intervening in the networks that underlie health and illness.

P4 health care is enabling the creation of a virtual cloud of billions of data points around each individual that we call personal, dense, dynamic data (PD3) clouds. The Hood Lab uses basic and clinical experimental systems to develop the analytic tools needed to translate these enormous data clouds into personalized predictions about health, and prevent or reverse disease much earlier than is practiced by current medicine. The lab envisions a health care system focused on maintaining wellness and reversing most disease prior to the emergence of symptoms.

The research ongoing in the lab requires a cross-disciplinary mix of scientists, including: experimentalists using high dimensional, high throughput techniques to profile proteins, nucleic acids and small molecules from experimental systems; engineers developing new analytical technologies; computational biologists focused on genomics, proteomics, and transcriptional and metabolic network analyses; and bioinformaticists, computer scientists and software engineers developing new analytical software tools and algorithms. The lab also engages in important collaborations within ISB and across the Providence system to develop P4 medicine and bring clinical assays to patients at diverse medical centers. Finally, the lab has a history of seeding new companies based on technological advancements developed by the group and its’ collaborators.

Research Foci

The Hood Lab is working on several technology-driven projects that will help realize the promise of P4 medicine.

• We are analyzing personal, dense, dynamic data clouds for thousands of individuals, providing an immense data resource to learn about human biology and to invent the future of health. An ultimate goal of this work is to identify early warning signs for all the common human diseases and develop methods to predict and prevent them.
• Alzheimer’s disease clinical trials are in progress to revolutionize treatment and provide hope to patients and families. We are working with clinical leaders and visionaries to engage multi-omic diagnostic and multi-dimensional therapeutic approaches that we believe represent the most credible path forward to making progress with this highly complex disease.
• Post-traumatic stress disorder (PTSD) and traumatic brain injury (TBI) are other neurological research areas of focus for the lab. We are working with partners in the Department of Defense to understand the systems most effective by these disorders to identify actionable possibilities to reverse course back to wellness.
• Lyme Disease research is a highly collaborative and active area of research within ISB and externally. We seek to understand the molecular underpinnings of chronic Lyme Disease in order to push the underlying perturbed networks back to a well state to improve the lives of countless infected individuals.
• Cancer remains a focus of the lab to understand basic biology at the single cell level as well as systems approaches to facilitate recovery. We are working with partners in the Swedish Cancer Institute and leveraging highly sensitive laboratory assays and computational tools to improve treatment and recovery of various cancer pathologies.
• Establishing the computational infrastructure and creating new software tools needed to analyze the millions of human genome sequences that will become available over the next ten years. These computational tools are enabling rapid large-scale comparative analyses of human genomes and their attendant molecular, cellular and phenotypic data.
• Supporting a human proteome project that will parallel the human genome project. Using selected reaction monitoring (SRM) mass spectrometry, we have created targeted assays for virtually all human proteins, which opens up fascinating opportunities for identifying blood and tissue biomarkers.
• Pioneered the identification and diagnostic use of organ-specific blood proteins to serve as proxies to identify which organs have become disease-perturbed and what changes have occurred in these organs. These approaches are being applied to Lyme disease, liver disease, and to neurodegenerative diseases.
• Developing clinical assays that use genomic, proteomic and cellular analyses, including the use of induced pluripotent stem (iPS) cells, to explore development and to stratify disease.
• In silico biological network modeling. We are modeling the interaction of various data types in precisely defined ways such that predictions of cellular behavior can be made under novel conditions or perturbations. Failure modes of computational models point toward gaps in understanding and lead to directed lines of questioning from which understanding of the cell’s workings can be increased in a systematic fashion. Constructing and revising computational models based on data constitutes a powerful iterative model building approach that lies at the heart of systems biology. Our lab has expertise in modeling integrated biological networks of many types (e.g. metabolic networks, transcriptional regulatory networks, protein networks), as well as in large-scale analysis of large datasets for diagnostic discovery.