Calorimetry is the science of measuring the heat absorbed or released in a chemical reaction or physical transition. It provides a direct physical measurement of what is perhaps the most fundamental property of chemical and biochemical reactions: the change in heat.^1,2 The field of calorimetry dates back to the late 18th century and the Scottish physician Joseph Black, whose work represents some of the early developments of modern thermodynamics.³ The first practical calorimeter was developed by Antoine Lavoisier and Pierre-Simon Laplace and described in a 1783 publication of a method to measure the heat produced by oxidation of various substances.⁴ In this design, the amount of heat exchanged during a reaction was monitored as it flowed into or out of a solution directly surrounding the reaction chamber.
 

Figure 1. A schematic of a differential scanning calorimeter. Sample and reference chambers are heated at a controlled rate under constant pressure (P). The temperature difference between the chambers (delta T) is monitored and kept in thermal balance by heaters controlled by feedback electronics.

Knowledge of the heat capacity of the surrounding material and accurate measurement of its change in temperature permitted direct and precise measurement of the quantity of heat released or absorbed during the reaction or transition. Because design characteristics of calorimeters have improved substantially over the years, improved accuracy in measuring heat changes of chemical reactions have occurred and have facilitated steady advances in the fields of thermodynamics and thermochemistry. These fields have contributed dramatically to the present understanding of chemical compounds and their reactions.

Differential Scanning Calorimetry (DSC)
The differential scanning calorimeter was first developed by E.S. Watson and M.J. O’Neill more than 50 years ago.⁵ This device consists of sample and reference chambers that are heated at a constant rate at a temperature range of interest. A generic schematic of the device is shown in Figure 1. The electrical power output to each chamber is computer-controlled in order to maintain the same temperature in both chambers throughout the analysis. When the test sample undergoes a reaction that produces a change in heat (either exothermic or endothermic), excess heat in the form of electrical power is transferred to or from the sample to maintain the thermal balance between the sample and reference chambers. This electrical power compensation is directly proportional to the excess heat capacity of the solution, and the resulting instrument output is known as a thermogram, which can be plotted as the excess heat capacity versus temperature.

Figure 2. Schematic of an ideal two-state protein denaturation thermogram.

Because of the high sensitivity of modern microcalorimeters, which can reliably measure heat changes as low as 0.1 microcalories, DSC is the method of choice for thermodynamic studies of protein denaturation, in which thermal-induced unfolding of proteins can be directly measured. A typical DSC thermogram for a simple and ideal protein denaturation reaction is depicted in Figure 2. The excess heat capacity of the reaction is plotted as a function of temperature, producing a curve with an essentially Gaussian shape. In order to simplify analytical procedures, it is often assumed that the melting transition occurs in a two-state manner (i.e., the protein is either fully folded or completely denatured).
The area under the thermogram is the enthalpy (ΔH) of the temperature-induced unfolding reaction. Integration of the curve yields a transition or melting curve from which the fractions of folded and unfolded molecules may be determined. Under a given set of buffer conditions, every protein has a characteristic denaturation thermogram that provides a fundamental thermodynamic signature for that protein. Many proteins have complex structures that can lead to a substantial departure from the ideal two-state behavior. Corresponding thermograms may have complex shapes (e.g., multiple peaks) that may reflect melting of individual structural domains in the tertiary structure. A majority of the most predominant proteins in blood plasma (e.g., albumin, IgG, fibrinogen, transferrin, IgA, α2-macroglobulin, α1-antitrypsin, complement C3, IgM, and haptoglobin) have complex structures with thermograms that deviate from the ideal two-state melting behavior.⁶
DSC thermograms are an extensive property of a protein solution and are directly related to the mass of proteins present. For example, if the weight concentration of a protein is doubled, the calorimetric heat response will also double. Likewise, in a solution containing mixtures of proteins, the relative heat response will correspond to the total mass of proteins present. Fundamentally, this property constitutes the basis for DSC-based diagnostic applications, since thermograms of protein mixtures can be resolved into characteristic melting curves of individual protein components. In a non-interacting mixture, each protein has a characteristic curve shape, melting temperature, and melting enthalpy. Thus, the thermogram observed for the mixture can be represented as the weighted sum of all constituent individual protein thermograms, weighted according to their relative molar mass and concentration.

DSC Applications
DSC’s high sensitivity and ability to evaluate sample purity and material properties have enabled wide applications of the technology in industrial settings, particularly as a quality control instrument. DSC analysis is commonly applied in food science research to help define and control processing parameters, and in the pharmaceutical industry to help characterize drug compounds.^7-9 The use of DSC in medical diagnostics is currently being developed, with promising potential applications for diagnostic analysis of human blood plasma.

The Plasma Proteome
In recent years, the emergence of numerous FDA-approved plasma/serum diagnostic assays has profoundly affected the world of medical diagnosis. Detecting a disturbance in the interrelationships among proteins in blood plasma is increasingly relied on to indicate the presence of infection, inflammation, malnutrition, or autoimmune disease. Human blood plasma is known to contain more than 3,000 unique proteins (the plasma proteome) with 10 proteins contributing 90% of plasma by weight and only 22 proteins comprising 99%. The remaining 1% is a complex mixture of low abundant proteins.^6,10 Disturbances among the major proteins can provide critical information early in the course of a disease, leading to improved patient outcomes and reduced costs for patient care.
Interest in the array of proteins and other biological molecules in plasma/serum have been primarily focused on the low molecular weight components of the serum or plasma proteome, or the peptidome, which has been touted as a “treasure trove of diagnostic information that has largely been ignored.”^11,12 Analytical methods such as mass spectrometry (in particular SELDI methods), protein electrophoresis, and immunochemical assays have made analysis of the peptidome possible. Both electrophoresis and mass spectrometry separate plasma proteins on the basis of size and charge.
In contrast, measuring the thermal properties of proteins present in plasma by DSC is independent from and complementary to these procedures. DSC thermograms of composite protein mixtures such as plasma provide an entirely new approach to analyzing the plasma proteome. DSC measurements of protein concentrations and interactions in human blood plasma have the potential to be powerful clinical tools for detecting, diagnosing, and monitoring diseases and associated pathophysiological processes.^2,6

The Interactome
Many components of the peptidome bind with the more abundant serum proteins, particularly albumin and immunoglobulins. This has led to the concept of the interactome, which for plasma/serum is “comprised of a network of protein-protein and peptide-protein interactions.”¹³ Proponents of the interactome concept believe that in disease states, low-molecular-weight proteins or peptides unique to that disease will increase in concentration in plasma or serum.¹³
Interactions of these biomarkers with the more abundant plasma proteins can alter their denaturation properties, producing characteristic changes of shape in observed thermograms. Interestingly, the original paper that introduced the interactome concept concluded that “the discovery of novel biomarkers in serum/plasma requires new biochemical and analytical approaches, and most importantly, it is clear that no single sample preparation or detection method will suffice if biomarker investigations are to be broadly successful using current technologies.”¹³
DSC assays are sensitive to binding interactions in ways that current electrophoresis and mass spectrometry assays are not. This is because binding interactions between small peptides and larger proteins can result in dramatic changes in thermal transitions, which can be detected by DSC, but result in only small changes in mass or charge, which can be challenging for electrophoresis or mass spectrometry to detect. While the denaturation of very small proteins and biomarkers themselves may not be observed directly by DSC, consequences of their interactions are seen indirectly through alterations of the melting properties of the more abundant proteins, to which the biomarkers bind. With proper calibration, changes in thermograms resulting from binding interactions can be related quantitatively to the biomarkers’ binding strengths.
Because they are sensitive to changes in protein composition both in a non-interacting mixture and as a consequence of interactions with other components, DSC thermograms are promising as a molecular diagnostics and biomarker discovery tool. Recent experiments have shown DSC thermograms to be sensitive to changes in plasma in relation to various pathological conditions.^2,6 Blood plasma thermograms were measured for patients suffering from various clinical diseases and revealed uniquely identifiable patterns associated with each disease state.
Louisville Bioscience Inc. has expanded such research and development efforts into activities aimed at commercializing the Plasma Thermogram technology. Ongoing clinical studies are directed toward characterizing thermograms for several different classes of disease. Thermograms for each disease type and stage are stored in an expanding database that is refined with every sample examined. The database provides a reference to which diagnostic thermograms can be compared and classified. As shown in several examples that follow, these promising results provide a compelling argument for the utility of DSC in clinical diagnostics.

Experimental Methods
In a typical Plasma Thermogram experiment, an aqueous plasma solution (at a concentration of approximately 2 mg/mL) is heated at a constant rate in the calorimeter sample cell alongside an identical reference cell containing only the solvent (buffer). An initial sample preparation step is performed before DSC data collection in order to standardize the sample buffer conditions. Only 100 µl of plasma is required, which allows for potential loss throughout the entire process. However, as little as 50 µl of sample can be used but would be considered the minimum sample volume required.
A major advantage of the DSC instrument is that it can be automated for higher sample throughput. For instance, multiple samples may be loaded into a 96-well plate, stored in a refrigerated compartment, and loaded into the calorimeter cells by a robotic system that also cleans the cells between runs. Calorimetric experiments are made serially with each DSC thermogram collected in approximately two hours. However, throughput of the system may be enhanced by increasing the scan rate or narrowing the range of temperatures scanned.
Initial data processing steps include a necessary baseline correction and thermogram normalization with respect to total protein concentration. Baseline-corrected and normalized thermograms are interpolated over a standardized temperature scale and stored in a database for easy access and future analysis. Statistical and chemometric analytical models have been developed to characterize and classify thermograms according to pattern and sample characteristics.¹⁴ Using these tools, unclassified thermograms can be compared to previously classified and characterized thermograms in the database to evaluate similarity in pattern. Based on this analysis, newly acquired thermograms can be assigned to established categories with associated probabilities or confidence levels.

Diagnostic Applications
The National Institutes of Health report of the Autoimmune Diseases Coordinating Committee (ADCC) states that as many as 24 million people in the United States are afflicted with autoimmune diseases.¹⁵ Diagnosing autoimmune diseases is particularly difficult due to the highly diverse clinical manifestations; symptoms are often not apparent until a disease has reached relatively advanced stages. The ADCC states that “autoimmune diseases present many complex challenges to the clinician. Prominent among these are the difficulties in establishing a diagnosis early in the course of disease and the lack of surrogate markers to monitor therapy and predict clinical outcomes. Thus, new tools are needed to ensure that the most promising experimental approaches will lead to better clinical outcomes.”¹⁵

Figure 3. Autoimmune disease Plasma Thermograms.

Measurements of blood plasma thermograms by DSC may provide an additional method for aiding in the differential diagnosis of autoimmune diseases. Plasma Thermogram assays from patients with the following four commonly misdiagnosed autoimmune diseases have been measured: lupus, rheumatoid arthritis, scleroderma, and myositis. The results showed clear differences between thermograms from healthy control subjects and thermograms from patients suffering from each of these diseases. Figure 3 shows the mean thermograms measured for each of the four disease categories and the mean normal thermogram collected from healthy subjects. These results show the potential utility of DSC technology in this medical area.

Improved Cancer Monitoring
New minimally invasive tools are imperative for improving therapeutic monitoring and early detection of cancer remission and relapse. The current methods for cancer detection and monitoring include surgical biopsy, serological testing, ultrasound, and imaging (x-ray, MRI, CT scan, PET, etc.). Although methods exist for detecting metastatic diseases at advanced stages, many suffer from limitations and drawbacks for early detection of disease relapse.¹⁶ In addition, FDA has recently announced an initiative to reduce unnecessary radiation exposure from medical imaging procedures. A noninvasive blood assay that can discriminate early from more advanced stages of carcinoma would highly benefit oncology diagnostics.

Figure 4. Comparison of Plasma Thermograms from diseased (red) and healthy (green) plasma. Diseased samples were taken from patients diagnosed with cervical cancer (top), melanoma (middle), and lung cancer (bottom).

DSC measurements of blood plasma could advance oncology diagnostics toward this goal. Figure 4 shows mean Plasma Thermogram assays obtained from patients who were diagnosed with cervical cancer, melanoma, and lung cancer. The thermograms for each disease category are significantly different in shape from the healthy control thermograms and from each other. Comparable results have been obtained for various other types of cancer, including ovarian, uterine, and endometrial cancer. These results suggest that DSC thermogram assays may be applicable to cancer detection and diagnosis. Thermograms from patients at different stages of cervical cancer and melanoma have also been measured. As Figure 5 indicates, the Plasma Thermogram assay could monitor disease progression through characteristic curve shapes associated with different stages of disease.

Biomarker Discovery
Applying DSC thermogram analysis to human plasma may also form the basis of a new, powerful, and broadly applicable biomarker discovery platform that is fundamentally different from standard biomarker assays. Differences in the shapes of plasma thermograms have been attributed to interactions of circulating components (e.g., peptides, proteins, metabolites, lipids, fatty acids, etc.) with the most abundant plasma proteins. Both experimental and clinical studies support the theory that in diseased states, concentrations of circulating low molecular weight proteins, peptides, or nucleic acids indicative and unique to a disease become elevated in plasma and other bodily fluids.
 

Figure 5. Comparison of Plasma Thermograms from stages of melanoma (red) with healthy samples (green). Diseased samples were taken from patients diagnosed with minimal (top) and advanced (bottom) stages of melanoma.

If they do indeed interact and bind with one or more of the abundant proteins in a fluid, such substances could prove to be viable biomarkers specific for particular diseases. Because they may alter the melting profile of any of the major proteins, interactions of candidate biomarkers may produce changes in observed thermograms relative to the characteristic normal signature. Plasma Thermogram assays may present a method for discovering or confirming the existence of disease specific biomarkers and understanding their role in disease pathology.

Conclusion
DSC has advanced during the past 200 years into a robust and reproducible physical technique with a multitude of potential applications. This article has presented recent research results that used DSC for the diagnostic characterization of human plasma for the detection, clinical diagnosis, and therapeutic monitoring of various clinical disease states including autoimmune diseases and cancers. Although the results presented in this article in the context of plasma analysis provide a compelling argument for the further development of DSC-based diagnostics, many significant challenges must be addressed before DSC diagnostics can be developed into a mainstream diagnostic tool.
For example, quantitative assessments of metrics such as sensitivity and specificity that define diagnostic performance will require the collection and analysis of many more samples, with disease incidence and prevalence within the population being critical parameters of the sample sets. Direct comparisons with gold-standard industry diagnostic techniques have yet to be established, which include clinically defined protein markers that are detected using antibody technology or physical-chemical techniques such as equilibrium dialysis, electrophoresis, and ultrafiltration. Ultimately, in order to gain market adoption, results of DSC diagnostics must be demonstrated to be comparable to more established, conventional techniques. The results presented in this article provide confidence that these comparisons are likely to yield favorable results. In addition, high-throughput capabilities of DSC must be fully demonstrated to achieve practical efficiency of the technique.
Promising additional applications beyond clinical diagnostics include biomarker discovery, and absorption, distribution, metabolism, excretion, and toxicity screening in which sensitive, robust, and reproducible screening of small molecule and protein interactions can provide valuable insights for drug discovery and development processes. For clinical diagnostic applications, further validation of DSC will be required through additional clinical studies and quantitative characterization of thermograms and their behaviors in the presence of small molecules or other potential therapeutic agents. Although many challenges remain, with strong results in future development trials, DSC could emerge as a central player in medical research and clinical diagnostics.

Conflict of interest statement: JBC, ASB, DJF, GPB, and NCG are coinventors on patent applications describing the DSC Plasma Thermogram technology. Louisville Bioscience Inc. holds an exclusive license from the Univ. of Louisville for the DSC Plasma Thermogram technology.

References
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2. NC Garbett, et al., “Interrogation of the Plasma Proteome with Differential Scanning Calorimetry,” Clinical Chemistry 53, no. 11 (2007): 2012-2014.
3. KJ Laider, The World of Physical Chemistry (Oxford University Press, 1993).
4. AC Buchholz and DA Schoeller, “Is a Calorie a Calorie?,” American Journal of Clinical Nutrition 79, no. 5 (2004): 899S–906S.
5. ES Watson and MJ O’Neill, “Differential Microcalorimeter,” U.S. Patent 3,263,484, August 2, 1966.
6. NC Garbett, et al., “Calorimetry Outside the Box: A New Window into the Plasma Proteome,” Journal of Biophysics 94, no. 4 (2008): 1377-1383.
7. JA Dean, The Analytical Chemistry Handbook (New York: McGraw Hill Inc., 1995), 15.1–15.5.
8. E Pungor, A Practical Guide to Instrumental Analysis (Boca Raton, FL: 1995), 181–191.
9. DA Skoog, FJ Holler, and T Nieman, Principles of Instrumental Analysis, 5th ed. (New York: 1998), 805–808.
10. S Surinova, et al., “On the Development of Plasma Protein Biomarkers,” Journal of Proteome Research 10, no. 1 (2010): 5-16.
11. LA Liotta and EF Petricoin, “Serum Peptidome for Cancer Detection: Spinning Biologic Trash into Diagnostic Gold,” The Journal of Clinical Investigation 11, no. 1 (2006): 26-30.
12. LA Liotta, M Ferrari, and E Petricoin, “Clinical Proteomics: Written in Blood,” Nature 425, no. 6961 (2003): 905.
13. M Zhou, et al., “An Investigation into the Human Serum Interactome,” Electrophoresis 25, no. 9 (2004): 1289-1298.
14. DJ Fish, et al., “Statistical Analysis of Plasma Thermograms Measured by Differential Scanning Calorimetry,” Biophysical Chemistry 152, no. 1-3 (2010): 184-90.
15. The Autoimmune Diseases Coordinating Committee, “Progress in Autoimmune Diseases Research,” Report to Congress, U.S. Department of Health and Human Services, National Institutes of Health, NIH Publication No. 05-5140, March 2005.
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Mark A. Wisniewski, MBA, is the Chief Operating Officer at Louisville Bioscience Inc.

Nichola C. Garbett, PhD, is Instructor of Medicine and Biophysical Core Facility Manager at James Graham Brown Cancer Ctr. at the Univ. of Louisville and a founder and director of Laboratory Operations of Louisville Bioscience Inc. She can be reached at nichola.garbett@louisville.edu.

Daniel J. Fish, PhD, is Vice President for Theoretical Development at Louisville Bioscience Inc. He can be reached at dfish@lbidx.com.

Greg P. Brewood, PhD, is Vice President for Product Development at Louisville Bioscience Inc. He can be reached at gbrewood@lbidx.com.

James J. Miller, PhD, is Professor of Pathology and Laboratory Medicine at the Univ. of Louisville and the Director of Clinical Chemistry and Toxicology at the Univ. of Louisville Hospital Laboratory. He is a principal advisor to Louisville Bioscience Inc. He can be reached at jmiller@louisville.edu.

Jonathan B. Chaires, PhD, is a Professor in the Dept. of Medicine at the Univ. of Louisville Health Sciences Center, a Senior Scientist in the James Graham Brown Cancer Center, and a founder of Louisville Bioscience Inc. He can be reached at j.chaires@louisville.edu.

Albert S. Benight, PhD, is the founder and President of Louisville Bioscience Inc. He can be reached at abenight@lbidx.com.
Mark A. Wisniewski, MBA, is the Chief Operating Officer at Louisville Bioscience Inc.