Blood has the potential to serve as a window into normal and pathological function in human physiology. Blood is connected to all tissues in the human body through vessels and microvessels which serve as a conduit for transfer of components (and information) between blood and tissues. The constituents of human blood include red blood cells, leukocytes, platelets and serum—many of which are lately understood to play key roles in health and disease processes. For instance, serum contains a range of molecular components including proteins, nucleic acids and metabolites that report on the health of the individual. While these components are the actors mediating physiological states, these very factors can serve as indicators of normal physiology and pathology. Traditional examples include glucose as a marker for insulin resistance status and high cholesterol as a marker for cardiovascular risk.
There are technologies available today capable of detecting several thousand molecules in blood as well as isolating exosomes and multiple defined cell subsets from blood. However, to more fully realize blood’s potential to serve as a precisioned window into specific pathologies, there is a need for refinement of several newer technologies and methods which will enable creation of blood-based phenotypes (through markers) of “normal” and diseased states. If properly implemented using well defined cohorts of patients with targeted diseases and clinical phenotypes it will be possible to create libraries of information that can enable remarkably powerful diagnostics.
There are several challenges that face creation and broad application of blood-based diagnostics. While blood is the most easily accessible body tissue, its collection and preparation as an assayable sample has a unique set of challenges. A first issue is determining the smallest quantity of blood that would be necessary and sufficient to carry out contextual assays to diagnose the state of the individual. Second, storage and maintenance of blood is a complex problem with the possibility that degradation, oxidation, cellular breakdown, and other deleterious outcomes might lead to artefactual results. An ideal scenario could simply be a spot of dry blood that serves as the sample, though other approaches are possible. As such, techniques for storage and preservation of blood need to be developed and tested for their use in preserving the range of metabolites or features that might be implemented in a diagnostic creation and implementation.
Blood constituents contain components (cells, molecules and exosomes) whose importance ranges across disease states, and whose varied levels in the blood can span large dynamic ranges. The constituents are varied-- including small molecules, lipid, proteins, multi-protein compelxes, and nucleic acids, amongst others.
Therefore, technologies to measure such factors must be similarly diverse—and must quantitatively address the “expression” range represented in this diversity.
Examples of technology needs include
- Cell based technologies: wherein the multiplicity of cell types and their activation states in blood can be profiled
- Molecular detection technologies: Quantitatively measuring the varied “features” available from blood (genome, epigenome, proteome and metabolome), represents target related technical challenges. This is especially the case since the levels of various components in the blood can vary from a few molecules per microliter to 10s of thousands.
- Novel assay technologies. There is a need for new generation assays that will allow development of disease-specific assays as well as tissue-specific assays in blood. Examples include detection of sterols reflective of liver biology.
- Detection of vesicles and exosomes in blood (which appear to read on the health and metabolism of the varied tissues with which blood interacts) further warrants development of new technologies.
The last several years has shown that ‘omics measurements from blood can yield vast amounts of data. While there are tools available for the analysis of traditional omics data, integrative analysis across platforms (multi-parameter single cell protein analysis and more recently single cell RNASeq) is a burgeoning challenge. There is therefore a strong need for:
- Analysis tools for multiple data types and statistical solutions that drive confidence in the results.
- Computational tools that can provide, and visually represent, valuable data models
- Systems biology tools where it would be possible to obtain an integrated perspective on blood diagnostics
- Catalogs that would establish both normal and cognate disease reference sets for blood
The very nature of blood’s function makes it the single tissue that interacts most directly with nearly all of human physiology. It is becoming clear that evolution has built on this interaction by using blood as a vehicle for inter-tissue communication. Hence a systems understanding of blood and what its constituents represent is a compelling “target of opportunity” for biomedicine. Decoding how the varied blood constituents might reflect the physiology of the organs through which it passes will provide a novel window on tissue biology. While changes in tissues like liver and bone marrow are reflected easily in blood, the challenge is to attribute markers or changes in markers from blood to specific tissue-level changes.
This has the potential to provide a systems medicine view of human pathology. Several new approaches need to be developed. With the advent of tissue-specific gene expression, protein and metabolite profiles, it would be possible to identify fingerprints of these components in blood that arise in a tissue-specific manner. Further a longitudinal view of blood components will enable assessment of changes of these components accompanying onset or progression of disease. Tools developed in systems biology need to be applied to blood components. It should be pointed out that in order to map deviation from normalcy, the normal blood state of its constituents must be established. This includes longitudinal estimation in the normal or reference state and this can serve as an individual’s hematotype deviations from which can be related to specific pathologies. This view also brings the perspective of personalized systems medicine.