Calorimetric analysis of the plasma proteome: identification of type 1 diabetes patients with early renal function decline

Characterization of myocardial injury phenotype by thermal liquid biopsy

Background and aims

With the advent and implementation of high-sensitivity cardiac troponin assays, differentiation of patients with distinct types of myocardial injuries, including acute thrombotic myocardial infarction (TMI), acute non-thrombotic myocardial injury (nTMi), and chronic coronary atherosclerotic disease (cCAD), is of pressing clinical importance. Thermal liquid biopsy (TLB) emerges as a valuable diagnostic tool, relying on identifying thermally induced conformational changes of biomolecules in blood plasma. While TLB has proven useful in detecting and monitoring several cancers and autoimmune diseases, its application in cardiovascular diseases remains unexplored. In this proof-of-concept study, we sought to determine and characterize TLB profiles in patients with TMI, nTMi, and cCAD at multiple acute-phase time points (T 0 h, T 2 h, T 4 h, T 24 h, T 48 h) as well as a follow-up time point (Tfu) when the patient was in a stable state.

Methods

TLB profiles were collected for 115 patients (60 with TMI, 35 with nTMi, and 20 with cCAD) who underwent coronary angiography at the event presentation and had subsequent follow-up. Medical history, physical, electrocardiographic, histological, biochemical, and angiographic data were gathered through medical records, standardized patient interviews, and core laboratory measurements.

Results

Distinctive signatures were noted in the median TLB profiles across the three patient types. TLB profiles for TMI and nTMi patients exhibited gradual changes from T0 to Tfu, with significant differences during the acute and quiescent phases. During the quiescent phase, all three patient types demonstrated similar TLB signatures. An unsupervised clustering analysis revealed a unique TLB signature for the patients with TMI. TLB metrics generated from specific features of TLB profiles were tested for differences between patient groups. The first moment temperature (TFM) metric distinguished all three groups at time of presentation (T0). In addition, 13 other TLB-derived metrics were shown to have distinct distributions between patients with TMI and those with cCAD.

Conclusion

Our findings demonstrated the use of TLB as a sensitive and data-rich technique to be explored in cardiovascular diseases, thus providing valuable insight into acute myocardial injury events.

Modification of the structural stability of human serum albumin in rheumatoid arthritis

Differential scanning calorimetry (DSC) can indicate changes in structure and/or concentration of the most abundant proteins in a biological sample via heat denaturation curves (HDCs). In blood serum for example, HDC changes result from either concentration changes or altered thermal stabilities for 7-10 proteins and has previously been shown capable of differentiating between sick and healthy human subjects. Here, we compare HDCs and proteomic profiles of 50 patients experiencing joint-inflammatory symptoms, 27 of which were clinically diagnosed with rheumatoid arthritis (RA). The HDC of all 50 subjects appeared significantly different from expected healthy curves, but comparison of additional differences between the RA and the non-RA subjects allowed more specific understanding of RA samples. We used mass spectrometry (MS) to investigate the reasons behind the additional HDC changes observed in RA patients. The HDC differences do not appear to be directly related to differences in the concentrations of abundant serum proteins. Rather, the differences can be attributed to modified thermal stability of some fraction of the human serum albumin (HSA) proteins in the sample. By quantifying differences in the frequency of artificially induced post translational modifications (PTMs), we found that HSA in RA subjects had a much lower surface accessibility, indicating potential ligand or protein binding partners in certain regions that could explain the shift in HSA melting temperature in the RA HDCs. Several low abundance proteins were found to have significant changes in concentration in RA subjects and could be involved in or related to binding of HSA. Certain amino acid sites clusters were found to be less accessible in RA subjects, suggesting changes in HSA structure that may be related to changes in protein-protein interactions. These results all support a change in behavior of HSA which may give insight into mechanisms of RA pathology.

Thermodynamic Sensitivity of Blood Plasma Components in Patients Afflicted with Skin, Breast and Pancreatic Forms of Cancer

According to the World Health Organization's 2018 Global Cancer Survey, cancer is the second leading cause of death. From this survey, the third most common is breast cancer, the fifth is melanoma malignum and pancreatic adenocarcinoma ranks twentieth. Undoubtedly, the early diagnosis and monitoring of these tumors and related research is important for aspects of patient care. The aim of our present review was to explain an impressive methodology that is deemed suitable in reference to studying blood sample deviations in the case of solid tumors. Essentially, we compared the heat denaturation responses of blood plasma components through differential scanning calorimetry (DSC). In the control, between five and seven separable components can be detected, in which the primary component was albumin, while in the case of tumorous patients, the peaks of immunoglobulins were dominant. Moreover, the shape of the plasma DSC curves changed with a shift in the higher temperature ranges; thus, their pattern can be used as a suitable marker of direct immunological responses. The further development of the analysis of DSC curves raises the possibility of the early diagnosis of a potential tumor, the monitoring of diseases, or testing the efficacy of the therapy from a single drop of blood.

Calorimetric Markers for Detection and Monitoring of Multiple Myeloma

Simple Summary

This review highlights the potential of differential scanning calorimetry for multiple myeloma diagnosis and monitoring of the treatment outcome. The thermodynamic signatures of blood sera from patients with multiple myeloma are strongly dependent on the concentration and isotype of the secreted monoclonal immunoglobulins. Mathematical methods developed to analyze the biocalorimetry data and distinguish “diseased” from “healthy” thermogram to stratify plasma calorimetric profiles and determine specific interrelations between calorimetric and biochemical/clinical data are discussed.

Abstract

This review summarizes data obtained thus far on the application of differential scanning calorimetry (DSC) for the analysis of blood sera from patients diagnosed with multiple myeloma (MM) with the secretion of the most common isotypes of monoclonal proteins (M-proteins), free light chains (FLC) and non-secretory MM, as well as Waldenström macroglobulinemia and the premalignant state monoclonal gammopathy of undetermined significance. The heterogeneous nature of MM is reflected in the thermal stability profiles of the blood serum proteome of MM patients found to depend on both the level and the isotype of the secreted M-proteins or FLC. Common calorimetric markers feature the vast majority of the different myeloma types, i.e., stabilization of the major serum proteins and decrease in the albumin/globulin heat capacity ratio. A unique calorimetric fingerprint of FLC molecules forming amorphous aggregates is the low-temperature transition centered at 57 °C for a calorimetric set of FLC MM and at 46–47 °C for a single FLC MM case for which larger aggregates were formed. The calorimetric assay proved particularly advantageous for non-secretory MM and is thus a suitable tool for monitoring such patients during treatment courses. Thus, DSC provides a promising blood-based approach as a complementary tool for MM detection and monitoring.

Saliva profiling with differential scanning calorimetry: A feasibility study with ex vivo samples

Differential scanning calorimetry (DSC) has been used widely to study various biomarkers from blood, less is known about the protein profiles from saliva. The aim of the study was to investigate the use DSC in order to detect saliva thermal profiles and determine the most appropriate sampling procedure to collect and process saliva. Saliva was collected from 25 healthy young individuals and processed using different protocols based on centrifugation and filtering. The most effective protocol was centrifugation at 5000g for 10 min at 4°C followed by filtration through Millex 0.45 μm filter. Prepared samples were transferred to 3 mL calorimetric ampoules and then loaded into TAM48 calibrated to 30°C until analysis. DSC scans were recorded from 30°C to 90°C at a scan rate of 1°C/h with a pre-conditioning the samples to starting temperature for 1 h. The results show that the peak distribution of protein melting points was clearly bimodal, and the majority of peaks appeared between 40–50°C. Another set of peaks is visible between 65°C– 75°C. Additionally, the peak amplitude and area under the peak are less affected by the concentration of protein in the sample than by the individual differences between people. In conclusion, the study shows that with right preparation of the samples, there is a possibility to have thermograms of salivary proteins that show peaks in similar temperature regions between different healthy volunteers.

Sample Processing Considerations for Protein Stability Studies of Low Concentration Biofluid Samples using Differential Scanning Calorimetry

Background:

The analysis of biofluid samples with low protein content (e.g., urine or saliva) can be challenging for downstream analysis methods with limited sensitivity. To circumvent this problem, sample processing methods are employed to increase the protein concentration in analyzed samples. However, for some techniques, like differential scanning calorimetry (DSC) that characterizes thermally-induced unfolding of biomolecules, sample processing must not affect native protein structure and stability.

Methods:

We evaluated centrifugal concentration and stirred cell ultrafiltration, two common methods of sample concentration characterized by a low risk of protein denaturation, with the goal of establishing a protocol for DSC analysis of low concentration biospecimens.

Results:

Our studies indicate that both methods can affect protein stability assessed by DSC and, even after optimization of several parameters, the obtained DSC profile (thermogram) suggested that sample processing affects the structure or intermolecular interactions of component proteins contributing to altered thermal stability detectable by DSC. We also found a relationship between changes in thermograms and low protein concentration, indicating that diluting biospecimens to concentrations below 0.1 mg/mL can perturb the intermolecular environment and affect the structure of proteins present in the solution.

Conclusions:

Dilution of samples below 0.1 mg/mL, as well as concentration of samples with low protein content, resulted in affected thermogram shapes suggesting changes in protein stability. This should be taken into account when concentrating dilute samples or employing techniques that lower the protein concentration (e.g., fractionation), when downstream applications include techniques, such as DSC, that require the preservation of native protein forms.

Red Blood Cells' Thermodynamic Behavior in Neurodegenerative Pathologies and Aging

The main trend of current research in neurodegenerative diseases (NDDs) is directed towards the discovery of novel biomarkers for disease diagnostics and progression. The pathological features of NDDs suggest that diagnostic markers can be found in peripheral fluids and cells. Herein, we investigated the thermodynamic behavior of the peripheral red blood cells (RBCs) derived from patients diagnosed with three common NDDs—Parkinson’s disease (PD), Alzheimer’s disease (AD), and amyotrophic lateral sclerosis (ALS) and compared it with that of healthy individuals, evaluating both fresh and aged RBCs. We established that NDDs can be differentiated from the normal healthy state on the basis of the variation in the thermodynamic parameters of the unfolding of major RBCs proteins—the cytoplasmic hemoglobin (Hb) and the membrane Band 3 (B3) protein. A common feature of NDDs is the higher thermal stability of both Hb and B3 proteins along the RBCs aging, while the calorimetric enthalpy can distinguish PD from ALS and AD. Our data provide insights into the RBCs thermodynamic behavior in two complex and tightly related phenomena—neurodegenerative pathologies and aging, and it suggests that the determined thermodynamic parameters are fingerprints of the altered conformation of Hb and B3 protein and modified RBCs’ aging in the studied NDDs.

Cell Temperature Measurement for Biometabolism Monitoring

Temperature is an important factor in the process of life, as thermal energy transfer participates in all biological events in organisms. Due to technical limitations, there is still a lot more information to be explored regarding the correlation between life activities and temperature changes. In recent years, the emergence of a variety of new temperature measurement methods has facilitated further research in this field. Here, we introduce the latest advances in temperature sensors for biological detection and their related applications in metabolic research. Various technologies are discussed in terms of their advantages and shortcomings, and future prospects are presented.

Nanocalorimeters for biomolecular analysis and cell metabolism monitoring

Nanocalorimeters, or microfabricated calorimeters, provide a promising way to characterize the thermal process of biological processes, such as biomolecule interactions and cellular metabolic activities. They enabled miniaturized heat measurement onto a chip device with potential benefits including low sample consumption, low cost, portability, and high throughput. Over the past few decades, researchers have tried to improve nanocalorimeters' performance, in terms of sensitivity, accuracy, and detection resolution, by exploring different sensing methods, thermal insulation techniques, and liquid handling methods. The enhanced devices resulted in new applications in recent years, and here we have summarized the performance parameters and applications based on categories. Finally, we have listed the current technical difficulties in nanocalorimeter research and hope for future solutions to overcome them.

Multi-group diagnostic classification of high-dimensional data using differential scanning calorimetry plasma thermograms

The thermoanalytical technique differential scanning calorimetry (DSC) has been applied to characterize protein denaturation patterns (thermograms) in blood plasma samples and relate these to a subject’s health status. The analysis and classification of thermograms is challenging because of the high-dimensionality of the dataset. There are various methods for group classification using high-dimensional data sets; however, the impact of using high-dimensional data sets for cancer classification has been poorly understood. In the present article, we proposed a statistical approach for data reduction and a parametric method (PM) for modeling of high-dimensional data sets for two- and three- group classification using DSC and demographic data. We compared the PM to the non-parametric classification method K-nearest neighbors (KNN) and the semi-parametric classification method KNN with dynamic time warping (DTW). We evaluated the performance of these methods for multiple two-group classifications: (i) normal versus cervical cancer, (ii) normal versus lung cancer, (iii) normal versus cancer (cervical + lung), (iv) lung cancer versus cervical cancer as well as for three-group classification: normal versus cervical cancer versus lung cancer. In general, performance for two-group classification was high whereas three-group classification was more challenging, with all three methods predicting normal samples more accurately than cancer samples. Moreover, specificity of the PM method was mostly higher or the same as KNN and DTW-KNN with lower sensitivity. The performance of KNN and DTW-KNN decreased with the inclusion of demographic data, whereas similar performance was observed for the PM which could be explained by the fact that the PM uses fewer parameters as compared to KNN and DTW-KNN methods and is thus less susceptible to the risk of overfitting. More importantly the accuracy of the PM can be increased by using a greater number of quantile data points and by the inclusion of additional demographic and clinical data, providing a substantial advantage over KNN and DTW-KNN methods.

Calorimetric markers for monitoring of multiple myeloma and Waldenström's macroglobulinemia patients

The blood proteome has been studied extensively for identification of novel reliable disease biomarkers. In recent years, differential scanning calorimetry has emerged as a new tool for characterization of the thermodynamic properties of the major serum/plasma proteins and for the establishment of calorimetric markers for a variety of diseases. Here we applied calorimetry to monitor the effect of treatment of patients diagnosed with multiple myeloma and Waldenström's macroglobulinemia on the calorimetric profiles of patients' blood sera. The parameters derived from the calorimetric profiles were compared with the primary serum biomarkers, monoclonal immunoglobulin (M protein) concentration, and κ/λ free light chain ratio. For the secretory cases, the calorimetric parameters thermogram's shape similarity and weighted average center strongly depended on the M protein level but had lower sensitivity and specificity. By contrast, for non-secretory cases, the calorimetric parameters did not depend on the κ/λ free light chains ratio and exhibited significantly higher sensitivity and specificity than M protein levels. A combination of the immunological and calorimetric tests was found to greatly improve the sensitivity and specificity of the clinical status evaluation. The pronounced differences in blood sera thermograms before and during monitoring reflected the individual patients' response to treatment received and showed maintenance of heterogeneity during the disease course.

Characterization and classification of lupus patients based on plasma thermograms

Objective

Plasma thermograms (thermal stability profiles of blood plasma) are being utilized as a new diagnostic approach for clinical assessment. In this study, we investigated the ability of plasma thermograms to classify systemic lupus erythematosus (SLE) patients versus non SLE controls using a sample of 300 SLE and 300 control subjects from the Lupus Family Registry and Repository. Additionally, we evaluated the heterogeneity of thermograms along age, sex, ethnicity, concurrent health conditions and SLE diagnostic criteria.

Methods

Thermograms were visualized graphically for important differences between covariates and summarized using various measures. A modified linear discriminant analysis was used to segregate SLE versus control subjects on the basis of the thermograms. Classification accuracy was measured based on multiple training/test splits of the data and compared to classification based on SLE serological markers.

Results

Median sensitivity, specificity, and overall accuracy based on classification using plasma thermograms was 86%, 83%, and 84% compared to 78%, 95%, and 86% based on a combination of five antibody tests. Combining thermogram and serology information together improved sensitivity from 78% to 86% and overall accuracy from 86% to 89% relative to serology alone. Predictive accuracy of thermograms for distinguishing SLE and osteoarthritis / rheumatoid arthritis patients was comparable. Both gender and anemia significantly interacted with disease status for plasma thermograms (p<0.001), with greater separation between SLE and control thermograms for females relative to males and for patients with anemia relative to patients without anemia.

Conclusion

Plasma thermograms constitute an additional biomarker which may help improve diagnosis of SLE patients, particularly when coupled with standard diagnostic testing. Differences in thermograms according to patient sex, ethnicity, clinical and environmental factors are important considerations for application of thermograms in a clinical setting.

Investigation of early and advanced stages in ovarian cancer using human plasma by differential scanning calorimetry and mass spectrometry

Ovarian cancer is recognized with high mortality due to asymptomatic nature of the disease and difficulties in diagnosing early stage of the cancer. The present study evaluates the use of differential scanning calorimetry (DSC) in differentiating the severity of ovarian cancer from healthy women. 47 diseased women were subdivided into four stages with respect to clinical relevance and severity. Stages I-II were regarded as early stages and stages III-IV were regarded as advanced stages. The two average transition temperatures (T m ) increased with disease severity from 64.84 and 70.32 °C (healthy) to 68.46 and 75.24 °C (stage IV), respectively. T m were increased depending on clinical groups. In addition, the change in heat capacity was also dependent on the disease severity. To further support and investigate the nature of the proposed interactions, matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis is employed. The results suggest the differences in peptide expression between early and advanced stage of ovarian cancer, affected abundant proteins in plasma. The combined DSC and MS approach was supportive in identifying a unique signature of ovarian cancer stages, and demonstrates the potential of DSC as a complementary diagnostic tool in the evaluation of early stage ovarian cancer.

Differential scanning calorimetry as a complementary diagnostic tool for the evaluation of biological samples

BACKGROUND

Differential scanning calorimetry (DSC) is a tool for measuring the thermal stability profiles of complex molecular interactions in biological fluids. DSC profiles (thermograms) of biofluids provide specific signatures which are being utilized as a new diagnostic approach for characterizing disease but the development of these approaches is still in its infancy.

METHODS

This article evaluates several approaches for the analysis of thermograms which could increase the utility of DSC for clinical application. Thermograms were analyzed using localized thermogram features and principal components (PCs). The performance of these methods was evaluated alongside six models for the classification of a data set comprised of 300 systemic lupus erythematosus (SLE) patients and 300 control subjects obtained from the Lupus Family Registry and Repository (LFRR).

RESULTS

Classification performance was substantially higher using the penalized algorithms relative to localized features/PCs alone. The models were grouped into two sets, the first having smoother solution vectors but lower classification accuracies than the second with seemingly noisier solution vectors.

CONCLUSIONS

Coupling thermogram technology with modern classification algorithms provides a powerful diagnostic approach for analysis of biological samples. The solution vectors from the models may reflect important information from the thermogram profiles for discriminating between clinical groups.

GENERAL SIGNIFICANCE

DSC thermograms show sensitivity to changes in the bulk plasma proteome that correlate with clinical status. To move this technology towards clinical application the development of new approaches is needed to extract discriminatory parameters from DSC profiles for the comparison and diagnostic classification of patients.

Characterization of monoclonal gammopathy of undetermined significance by calorimetric analysis of blood serum proteome

Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant proliferative disorder that may progress to multiple myeloma, a malignant plasma cell neoplasia. We evaluated differential scanning calorimetry (DSC) as an experimental tool for differentiating serum samples of MGUS patients from healthy individuals. DSC thermograms can be used for monitoring changes in the serum proteome associated with MGUS. MGUS patients showed great variability in serum thermogram characteristics, which depended on the IgG, IgA or IgM isotypes and/or the κ or λ light chains. Thermogram feature parameters distinguished patients with MGUS from healthy people. Serum samples, named as non-MGUS, were also collected from patients with subjacent immunological pathologies who were discarded of having MGUS through serum immunofixation. They were used to verify the sensitivity of DSC for discriminating MGUS from related blood dyscrasias. Only some DSC thermogram feature parameters differentiated, to a lesser extent, between MGUS and non-MGUS individuals. We contemplate DSC as a tool for early diagnosis and monitoring of MGUS.

Deconvolution analysis for classifying gastric adenocarcinoma patients based on differential scanning calorimetry serum thermograms

Recently, differential scanning calorimetry (DSC) has been acknowledged as a novel tool for diagnosing and monitoring several diseases. This highly sensitive technique has been traditionally used to study thermally induced protein folding/unfolding transitions. In previous research papers, DSC profiles from blood samples of patients were analyzed and they exhibited marked differences in the thermal denaturation profile. Thus, we investigated the use of this novel technology in blood serum samples from 25 healthy subjects and 30 patients with gastric adenocarcinoma (GAC) at different stages of tumor development with a new multiparametric approach. The analysis of the calorimetric profiles of blood serum from GAC patients allowed us to discriminate three stages of cancer development (I to III) from those of healthy individuals. After a multiparametric analysis, a classification of blood serum DSC parameters from patients with GAC is proposed. Certain parameters exhibited significant differences (P < 0.05) and allowed the discrimination of healthy subjects/patients from patients at different tumor stages. The results of this work validate DSC as a novel technique for GAC patient classification and staging, and offer new graphical tools and value ranges for the acquired parameters in order to discriminate healthy from diseased subjects with increased disease burden.

Calorimetric markers of Bence Jones and nonsecretory multiple myeloma serum proteome

The present work provides a thermodynamic description of blood serum from patients diagnosed with Bence Jones myeloma (BJMM) and nonsecretory myeloma (NSMM) by means of differential scanning calorimetry (DSC), serum protein electrophoresis, and free light chain assay. Specific alterations in the thermodynamic behavior of both BJMM and NSMM proteome have been revealed. On the basis of the transition temperature of the main transition in the calorimetric profiles and the shape similarity criterion, we defined BJMM and NSMM sets/subsets of thermograms with very similar thermodynamic features. We show that some of the BJMM and NSMM subsets correlate with previously defined secretory myeloma subsets (Todinova et al. Anal. Chem. 2011, 83, 7992). The established analogies strongly suggest that common molecular markers contribute to the calorimetric profiles of the different, secretory and nonsecretory, myeloma types; our data show robust evidence that these are ligands stabilizing the major serum proteins. We demonstrate that the DSC approach might be highly beneficial, especially for NSMM patients, since the characteristic modifications in the DSC profiles might serve as calorimetric markers when no monoclonal proteins can be detected in the bloodstream and the diagnosis heavily relies on invasive methods.

Clinical application of plasma thermograms. Utility, practical approaches and considerations

Differential scanning calorimetry (DSC) studies of blood plasma are part of an emerging area of the clinical application of DSC to biofluid analysis. DSC analysis of plasma from healthy individuals and patients with various diseases has revealed changes in the thermal profiles of the major plasma proteins associated with the clinical status of the patient. The sensitivity of DSC to the concentration of proteins, their interactions with other proteins or ligands, or their covalent modification underlies the potential utility of DSC analysis. A growing body of literature has demonstrated the versatility and performance of clinical DSC analysis across a range of biofluids and in a number of disease settings. The principles, practice and challenges of DSC analysis of plasma are described in this article.