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Success of new-generation metabolo-therapies in personalized medicine depends on
measuring bioenergetic health
November 2014
SHARING OPTIONS:
GUEST COMMENTARY
By Dr. David A. Ferrick of Seahorse Bioscience &
Dr. Victor Darley-Usmar of the University
of Alabama at Birmingham
It is now widely accepted that complex diseases associated with aging involve
dysfunctional metabolism. This growing healthcare problem includes obesity/diabetes, neurodegeneration, cancer and cardiovascular disease.1-3 The
major driver of age-related, metabolic dysfunction is the availability of low-cost, high-calorie foods, in combination with a contemporary sedentary
lifestyle. This modern era health epidemic is creating a “perfect storm” of risk factors that is increasingly manifesting as multiple diseases
within the human body and is straining, if not overwhelming, the capabilities and resources of healthcare systems worldwide. Defining metabolic health,
particularly the way cells use energy, or bioenergetics, has become a necessity for healthcare in the 21st century and at the present time there is no
clinical test available to assess this critical parameter.
At the crossroads of understanding cell physiology,
disease pathology and etiology is cell metabolism, which is widely known to be a common feature of these costly, debilitating and lethal diseases. This
association is in large part due to its central role in the life-sustaining and biosynthetic processes of the cell, specifically energy in the form of ATP,
sensing and reacting to cellular stress and providing the building blocks that make up the cells, tissues and organs of the body.
A new class of drugs
The next decade will witness the release of
a new class of drugs, known as “metabolo-therapeutics,” which will target metabolic pathways and the individual metabolites that are required for
the maintenance of normal health. Finally clinicians will be able to address the long overlooked area of metabolic liabilities in complex diseases.
Establishing metabolic phenotypes and their interdependency with specific signaling pathways has enabled researchers to reprogram them to affect disease
states and the result is a new generation of discoveries and metabolo-therapeutic approaches across the entire spectrum of age-related diseases.
Like many other classes of treatment, metabolo-therapies will probably be best utilized and result in better outcomes by
employing a personalized, targeted therapeutic approach for each patient. Chronic diseases have a complex interplay of genetic and environmental factors and
can take decades to cause harm. When they do, the resulting disease may take just as long to significantly disrupt a patient’s lifestyle and/or
threaten his or her life. Until now the ability to determine a true indication of a patient’s metabolic health (the key integrator of environmental
factors involved in disease etiology and progression) has not been possible. This is a huge gap that needs to be addressed as we start to target the
metabolic basis of diseases and as a result prescribe a new class of therapies that target metabolic pathways. We are in fact already behind, as many
existing therapies are dose-limited due to the off-target effects on bioenergetics.
Clinical tests aimed at
bioenergetic status should play a critical role in the selection and monitoring of those metabolo-therapies that have the greatest efficacy and safety
profile. Additionally, healthcare economics will more than likely favor approaches that identify the best therapeutics first and not the current “trial
and error” process that often results in patients going through a gauntlet of therapies until one is found that works.
The answer in our cells
To develop an index of bioenergetic function, one has to
look no further than the mitochondria. Mitochondria are the central organelle in cell metabolism that, along with producing the majority of energy for the
cell, are also the biosynthetic hub for manufacturing cellular building blocks. Based on this metabolic role, mitochondria are fundamental in determining
whether a cell will grow, mature or die. This explains why the study of cell metabolism has become so important in age-related diseases. Valuable insight
into mitochondrial function can be gained through measuring the rate of oxygen consumed by cells, as virtually all the oxygen is directed to the
mitochondria. Oxygen metabolism is the key step that enables mitochondria to perform many tasks and, therefore, measurement of the oxygen consumption rate
(OCR) can be used as a direct measure of mitochondrial activity. This realization provided the compelling rationale for exploring translational bioenergetics
several decades ago. However, expansion into the clinical arena is only now possible due to breakthrough advances in oxygen sensor chemistry, assay
throughput, workflow, ease-of-use and reliability of measuring OCR.
Using a well-validated test of mitochondrial
function, the Cell Mito Stress Test being an example, the OCR of a cell can be apportioned between the key factors that define bioenergetic health. The first
factor is the basal condition that reflects the patient’s current status, based on when the blood sample was drawn and is used to calculate various
changes from this “base” state. The second factor is the rate of energy production in the form of ATP, the energy currency of the cell. The third
factor is the proportion of the mitochondrial OCR that, rather than being used to make ATP, instead “leaks” through the system as its energy is
released as heat. This leak of mitochondrial energy can provide indications of metabolic efficiency. The fourth factor is the capacity of the mitochondria to
respond to an energetic, or stress-induced, demand. This is achieved by determining the maximal OCR rate of the cells and is analogous to revving a car
engine to its maximum rpm. The difference between basal and maximum OCR reveals the energetic capacity of the mitochondria and is perhaps the most sensitive
and earliest indication of impairment and/or metabolic stress. And lastly, the amount of oxygen consumed outside of the mitochondria often correlates with
negative aspects of cellular health, such as inflammation, that contribute to the progression of many age-related diseases.
Canary in the coal mine
In one test, a comprehensive measure of energetic health, or
its disease-related deterioration, can now be made. The prognostic and diagnostic value of bioenergetic measurements in patients is still unknown, but recent
findings support an emerging concept that circulating leukocytes and platelets can serve as the “canary in the coal mine” by acting as early
sensors or predictive biomarkers of metabolic function under conditions of chronic stress and disease.4-8 These studies prompted researchers at
the University of Alabama at Birmingham (UAB) to begin an integrated approach using cells isolated from human blood, to establish a quantitative assay of
bioenergetic function that they expect will have the power to predict disease progression and response to treatment.9
The two main challenges to achieving this goal are: 1) the establishment of an index of bioenergetic activity that accounts
for the complexity of metabolic function and can be appropriately weighted, based on the impairment(s) of a particular indication; and 2) the adaptation of a
technology platform and an assay that can directly measure metabolic activity. To address these challenges, UAB established the Mitochondrial Medicine
Laboratory to develop the clinical tests that can measure bioenergetics and partnered with Seahorse Bioscience to provide the technology platform and
informatics. The goal of the Mitochondrial Medicine Lab is to develop a mitochondrial biomarker-based approach to assessing health, called the bioenergetic
health index (BHI).
To facilitate development of the BHI, Seahorse Bioscience addressed both the difficulty of
obtaining functional metabolic measurements and the ability to interpret those results. This was accomplished by standardizing the direct measures of
metabolic flux using a proprietary technology called extracellular flux (XF). Early translational studies suggest that this platform may be amenable for
defining metabolic status and that assays may be developed to pinpoint metabolic liabilities in diseases that can instruct which drug is most likely to be
effective.
An early finding by the group at UAB is that the mitochondrial parameters generated in the test of
mitochondrial function are interactive. If integrated appropriately into a single value, they can serve as a sensitive indicator of the response of cells to
environmental stress and chronic disease progression.9 This is accomplished in the BHI equation by quantifying positive aspects of bioenergetic
function (reserve capacity and ATP-linked respiration) and contrasting these with potentially deleterious ones (non-mitochondrial oxygen consumption and
proton leak). For example, the larger the value for reserve capacity, which raises BHI, the more effectively mitochondria can meet both the normal energy
needs of the cell and the increased metabolic demand caused by stress and disease.10
Preliminary
studies in several indications are in progress at the Mitochondrial Medicine Laboratory at UAB and other institutions around the world. The overall goal is
to determine if BHI can be deployed as the first clinical test for assessing bioenergetic dysfunction. Can it be predictive early in disease progression
before significant pathology and/or acutely prior to life-threatening conditions? If successful, the BHI test could become an important approach to
integrating personalized medicine with state-of-the-art translational bioenergetics.
David Ferrick, Ph.D., is chief scientific officer at Seahorse Bioscience, a privately held Boston-area biotechnology company that designs and manufactures metabolic analyzers and assay kits for measuring cell metabolism in living cells. Victor Darley-Usmar, Ph.D., is the director of the Mitochondrial Medicine Laboratory at University of Alabama at Birmingham and has pioneered the application of the mitochondrial stress test to analysis of patient bioenergetic health. References
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