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Zhang X, Xiao J, Yang F, Qu H, Ye C, Chen S, Guo Y. Identification of sudden cardiac death from human blood using ATR-FTIR spectroscopy and machine learning. Int J Legal Med 2024; 138:1139-1148. [PMID: 38047927 DOI: 10.1007/s00414-023-03118-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 10/25/2023] [Indexed: 12/05/2023]
Abstract
OBJECTIVE The aim of this study is to identify a rapid, sensitive, and non-destructive auxiliary approach for postmortem diagnosis of SCD, addressing the challenges faced in forensic practice. METHODS ATR-FTIR spectroscopy was employed to collect spectral features of blood samples from different cases, combined with pathological changes. Mixed datasets were analyzed using ANN, KNN, RF, and SVM algorithms. Evaluation metrics such as accuracy, precision, recall, F1-score and confusion matrix were used to select the optimal algorithm and construct the postmortem diagnosis model for SCD. RESULTS A total of 77 cases were collected, including 43 cases in the SCD group and 34 cases in the non-SCD group. A total of 693 spectrogram were obtained. Compared to other algorithms, the SVM algorithm demonstrated the highest accuracy, reaching 95.83% based on spectral biomarkers. Furthermore, by combing spectral biomarkers with age, gender, and cardiac histopathological changes, the accuracy of the SVM model could get 100%. CONCLUSION Integrating artificial intelligence technology, pathology, and physical chemistry analysis of blood components can serve as an effective auxiliary method for postmortem diagnosis of SCD.
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Affiliation(s)
- Xiangyan Zhang
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha, China
| | - Jiao Xiao
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha, China
| | - Fengqin Yang
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha, China
| | - Hongke Qu
- Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Cancer Research Institute and School of Basic Medicine Sciences, Central South University, Changsha, Hunan, China
| | - Chengxin Ye
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha, China
| | - Sile Chen
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha, China
| | - Yadong Guo
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha, China.
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2
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Tolstik E, Lehnart SE, Soeller C, Lorenz K, Sacconi L. Cardiac multiscale bioimaging: from nano- through micro- to mesoscales. Trends Biotechnol 2024; 42:212-227. [PMID: 37806897 DOI: 10.1016/j.tibtech.2023.08.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 08/23/2023] [Accepted: 08/24/2023] [Indexed: 10/10/2023]
Abstract
Cardiac multiscale bioimaging is an emerging field that aims to provide a comprehensive understanding of the heart and its functions at various levels, from the molecular to the entire organ. It combines both physiologically and clinically relevant dimensions: from nano- and micrometer resolution imaging based on vibrational spectroscopy and high-resolution microscopy to assess molecular processes in cardiac cells and myocardial tissue, to mesoscale structural investigations to improve the understanding of cardiac (patho)physiology. Tailored super-resolution deep microscopy with advanced proteomic methods and hands-on experience are thus strategically combined to improve the quality of cardiovascular research and support future medical decision-making by gaining additional biomolecular information for translational and diagnostic applications.
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Affiliation(s)
- Elen Tolstik
- Department of Cardiovascular Pharmacology, Translational Research, Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V. Bunsen-Kirchhoff-Strasse 11, 44139 Dortmund, Germany.
| | - Stephan E Lehnart
- Department of Cardiology and Pneumology, Cellular Biophysics and Translational Cardiology Section, Heart Research Center Göttingen, University Medical Center Göttingen, Georg-August University Göttingen, Robert-Koch-Strasse 42a, 37075 Göttingen, Germany; Cluster of Excellence Multiscale Bioimaging: from Molecular Machines to Networks of Excitable Cells (MBExC2067), University of Göttingen, 37073 Göttingen, Germany; Collaborative Research Center SFB1190 Compartmental Gates and Contact Sites in Cells, University of Göttingen, 37073 Göttingen, Germany
| | - Christian Soeller
- Department of Physiology, University of Bern, Bühlplatz 5, 3012 Bern, Switzerland
| | - Kristina Lorenz
- Department of Cardiovascular Pharmacology, Translational Research, Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V. Bunsen-Kirchhoff-Strasse 11, 44139 Dortmund, Germany; Institute of Pharmacology and Toxicology, University of Würzburg, Versbacher Strasse 9, 97078 Würzburg, Germany
| | - Leonardo Sacconi
- Institute of Clinical Physiology, National Research Council, Rome, Italy; Institute for Experimental Cardiovascular Medicine, University Freiburg, Elsässer Strasse 2q, 79110 Freiburg, Germany.
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3
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Olbrich K, Setkowicz Z, Kawon K, Czyzycki M, Janik-Olchawa N, Carlomagno I, Aquilanti G, Chwiej J. Vibrational spectroscopy methods for investigation of the animal models of glioblastoma multiforme. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 303:123230. [PMID: 37586277 DOI: 10.1016/j.saa.2023.123230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 06/26/2023] [Accepted: 08/01/2023] [Indexed: 08/18/2023]
Abstract
Glioblastoma multiforme (GBM) is the most common and devastating primary brain tumor among adults. It is highly lethal disease, as only 25% of patients survive longer than 1 year and only 5% more than 5 years from the diagnosis. To search for the new, more effective methods of treatment, the understanding of mechanisms underlying the process of tumorigenesis is needed. The new light on this problem may be shed by the analysis of biochemical anomalies of tissues affected by tumor growth. Therefore, in the present work, we applied the Fourier transform infrared (FTIR) and Raman microspectroscopy to evaluate changes in the distribution and structure of biomolecules appearing in the rat brain as a result of glioblastoma development. In turn, synchrotron X-ray fluorescence microscopy was utilized to determine the elemental anomalies appearing in the nervous tissue. To achieve the assumed goals of the study animal models of GBM were used. The rats were subjected to the intracranial implantation of glioma cells with different degree of invasiveness. For spectroscopic investigation brain slices taken from the area of cancer cells administration were used. The obtained results revealed, among others, the decrease content of lipids and compounds containing carbonyl groups, compositional and structural changes of proteins as well as abnormalities in the distribution of low atomic number elements within the region of tumor.
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Affiliation(s)
- Karolina Olbrich
- Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
| | - Zuzanna Setkowicz
- Institute of Zoology and Biomedical Research, Jagiellonian University, Krakow, Poland
| | - Kamil Kawon
- Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
| | - Mateusz Czyzycki
- Institute for Photon Science and Synchrotron Radiation, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
| | - Natalia Janik-Olchawa
- Institute of Zoology and Biomedical Research, Jagiellonian University, Krakow, Poland
| | | | | | - Joanna Chwiej
- Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland.
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4
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Sharma VJ, Green A, McLean A, Adegoke J, Gordon CL, Starkey G, D'Costa R, James F, Afara I, Lal S, Wood B, Raman J. Towards a point-of-care multimodal spectroscopy instrument for the evaluation of human cardiac tissue. Heart Vessels 2023; 38:1476-1485. [PMID: 37608153 PMCID: PMC10602956 DOI: 10.1007/s00380-023-02292-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 07/13/2023] [Indexed: 08/24/2023]
Abstract
To demonstrate that point-of-care multimodal spectroscopy using Near-Infrared (NIR) and Raman Spectroscopy (RS) can be used to diagnose human heart tissue. We generated 105 spectroscopic scans, which comprised 4 NIR and 3 RS scans per sample to generate a "multimodal spectroscopic scan" (MSS) for each heart, done across 15 patients, 5 each from the dilated cardiomyopathy (DCM), Ischaemic Heart Disease (IHD) and Normal pathologies. Each of the MSS scans was undertaken in 3 s. Data were entered into machine learning (ML) algorithms to assess accuracy of MSS in diagnosing tissue type. The median age was 50 years (IQR 49-52) for IHD, 47 (IQR 45-50) for DCM and 36 (IQR 33-52) for healthy patients (p = 0.35), 60% of which were male. MSS identified key differences in IHD, DCM and normal heart samples in regions typically associated with fibrosis and collagen (NIR wavenumbers: 1433, 1509, 1581, 1689 and 1725 nm; RS wavelengths: 1658, 1450 and 1330 cm-1). In principal component (PC) analyses, these differences explained 99.2% of the variation in 4 PCs for NIR, 81.6% in 10 PCs for Raman, and 99.0% in 26 PCs for multimodal spectroscopic signatures. Using a stack machine learning algorithm with combined NIR and Raman data, our model had a precision of 96.9%, recall of 96.6%, specificity of 98.2% and Area Under Curve (AUC) of 0.989 (Table 1). NIR and Raman modalities alone had similar levels of precision at 94.4% and 89.8% respectively (Table 1). MSS combined with ML showed accuracy of 90% for detecting dilated cardiomyopathy, 100% for ischaemic heart disease and 100% for diagnosing healthy tissue. Multimodal spectroscopic signatures, based on NIR and Raman spectroscopy, could provide cardiac tissue scans in 3-s to aid accurate diagnoses of fibrosis in IHD, DCM and normal hearts. Table 1 Machine learning performance metrics for validation data sets of (a) Near-Infrared (NIR), (b) Raman and (c and d) multimodal data using logistic regression (LR), stochastic gradient descent (SGD) and support vector machines (SVM), with combined "stack" (LR + SGD + SVM) AUC Precision Recall Specificity (a) NIR model Logistic regression 0.980 0.944 0.933 0.967 SGD 0.550 0.281 0.400 0.700 SVM 0.840 0.806 0.800 0.900 Stack 0.933 0.794 0.800 0.900 (b) Raman model Logistic regression 0.985 0.940 0.929 0.960 SGD 0.892 0.869 0.857 0.932 SVM 0.992 0.940 0.929 0.960 Stack 0.954 0.869 0.857 0.932 (c) MSS: multimodal (NIR + Raman) to detect DCM vs. IHD vs. normal patients Logistic regression 0.975 0.841 0.828 0.917 SGD 0.847 0.803 0.793 0.899 SVM 0.971 0.853 0.828 0.917 Stack 0.961 0.853 0.828 0.917 (d) MSS: multimodal (NIR + Raman) to detect pathological vs. normal patients Logistic regression 0.961 0.969 0.966 0.984 SGD 0.944 0.967 0.966 0.923 SVM 1.000 1.000 1.000 1.000 Stack 1.000 0.944 0.931 0.969 Bold values indicate values obtained from the stack algorithm and used for analyses.
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Affiliation(s)
- Varun J Sharma
- Department of Surgery, Melbourne Medical School, University of Melbourne, Melbourne, Australia.
- Brian F. Buxton Department of Cardiac Surgery, Austin Hospital, Melbourne, Australia.
- Spectromix Laboratory, Melbourne, VIC, Australia.
| | - Alexander Green
- Spectromix Laboratory, Melbourne, VIC, Australia
- Monash Biospectroscopy, Monash University, Melbourne, Australia
| | - Aaron McLean
- Spectromix Laboratory, Melbourne, VIC, Australia
- Monash Biospectroscopy, Monash University, Melbourne, Australia
| | - John Adegoke
- Spectromix Laboratory, Melbourne, VIC, Australia
- Monash Biospectroscopy, Monash University, Melbourne, Australia
| | - Claire L Gordon
- Department of Infectious Diseases, Austin Health, Melbourne, VIC, Australia
- Department of Microbiology and Immunology, The University of Melbourne, The Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
- North Eastern Public Health Unit, Austin Health, Melbourne, VIC, Australia
| | - Graham Starkey
- Liver Transplant Unit, Austin Hospital, Melbourne, Australia
| | - Rohit D'Costa
- DonateLife Victoria, Carlton, Melbourne, VIC, Australia
- Department of Intensive Care Medicine, Melbourne Health, Melbourne, VIC, Australia
| | - Fiona James
- Department of Infectious Diseases, Austin Health, Melbourne, VIC, Australia
- North Eastern Public Health Unit, Austin Health, Melbourne, VIC, Australia
| | - Isaac Afara
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia
| | - Sean Lal
- Department of Cardiology, Royal Prince Alfred Hospital, Sydney, Australia
- Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Bayden Wood
- Spectromix Laboratory, Melbourne, VIC, Australia
- Monash Biospectroscopy, Monash University, Melbourne, Australia
| | - Jaishankar Raman
- Department of Surgery, Melbourne Medical School, University of Melbourne, Melbourne, Australia
- Brian F. Buxton Department of Cardiac Surgery, Austin Hospital, Melbourne, Australia
- Spectromix Laboratory, Melbourne, VIC, Australia
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5
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Sigle M, Rohlfing AK, Kenny M, Scheuermann S, Sun N, Graeßner U, Haug V, Sudmann J, Seitz CM, Heinzmann D, Schenke-Layland K, Maguire PB, Walch A, Marzi J, Gawaz MP. Translating genomic tools to Raman spectroscopy analysis enables high-dimensional tissue characterization on molecular resolution. Nat Commun 2023; 14:5799. [PMID: 37726278 PMCID: PMC10509269 DOI: 10.1038/s41467-023-41417-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 09/04/2023] [Indexed: 09/21/2023] Open
Abstract
Spatial transcriptomics of histological sections have revolutionized research in life sciences and enabled unprecedented insights into genetic processes involved in tissue reorganization. However, in contrast to genomic analysis, the actual biomolecular composition of the sample has fallen behind, leaving a gap of potentially highly valuable information. Raman microspectroscopy provides untargeted spatiomolecular information at high resolution, capable of filling this gap. In this study we demonstrate spatially resolved Raman "spectromics" to reveal homogeneity, heterogeneity and dynamics of cell matrix on molecular levels by repurposing state-of-the-art bioinformatic analysis tools commonly used for transcriptomic analyses. By exploring sections of murine myocardial infarction and cardiac hypertrophy, we identify myocardial subclusters when spatially approaching the pathology, and define the surrounding metabolic and cellular (immune-) landscape. Our innovative, label-free, non-invasive "spectromics" approach could therefore open perspectives for a profound characterization of histological samples, while additionally allowing the combination with consecutive downstream analyses of the very same specimen.
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Affiliation(s)
- Manuel Sigle
- Department of Cardiology and Angiology, University Hospital Tuebingen, Eberhard Karls University Tuebingen, 72076, Tuebingen, Germany
| | - Anne-Katrin Rohlfing
- Department of Cardiology and Angiology, University Hospital Tuebingen, Eberhard Karls University Tuebingen, 72076, Tuebingen, Germany
| | - Martin Kenny
- UCD Conway SPHERE Research Group, Conway Institute, University College Dublin, Dublin, Ireland
- School of Biomolecular and Biomedical Science, University College Dublin, Dublin, Ireland
| | - Sophia Scheuermann
- Department of Pediatric Hematology and Oncology, University Children's Hospital Tuebingen, 72076, Tuebingen, Germany
- Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, 72076, Tuebingen, Germany
| | - Na Sun
- Research Unit Analytical Pathology, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Ulla Graeßner
- Department of Pediatric Hematology and Oncology, University Children's Hospital Tuebingen, 72076, Tuebingen, Germany
| | - Verena Haug
- Department of Cardiology and Angiology, University Hospital Tuebingen, Eberhard Karls University Tuebingen, 72076, Tuebingen, Germany
| | - Jessica Sudmann
- Department of Cardiology and Angiology, University Hospital Tuebingen, Eberhard Karls University Tuebingen, 72076, Tuebingen, Germany
| | - Christian M Seitz
- Department of Pediatric Hematology and Oncology, University Children's Hospital Tuebingen, 72076, Tuebingen, Germany
- Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, 72076, Tuebingen, Germany
| | - David Heinzmann
- Department of Cardiology and Angiology, University Hospital Tuebingen, Eberhard Karls University Tuebingen, 72076, Tuebingen, Germany
| | - Katja Schenke-Layland
- Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, 72076, Tuebingen, Germany
- Institute of Biomedical Engineering, Department for Medical Technologies and Regenerative Medicine, Eberhard Karls University Tuebingen, 72076, Tuebingen, Germany
- NMI Natural and Medical Sciences Institute at the University of Tuebingen, 72770, Reutlingen, Germany
| | - Patricia B Maguire
- UCD Conway SPHERE Research Group, Conway Institute, University College Dublin, Dublin, Ireland
- School of Biomolecular and Biomedical Science, University College Dublin, Dublin, Ireland
- Institute for Discovery, O'Brien Centre for Science, University College Dublin, Dublin, Ireland
| | - Axel Walch
- Research Unit Analytical Pathology, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Julia Marzi
- Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, 72076, Tuebingen, Germany
- Institute of Biomedical Engineering, Department for Medical Technologies and Regenerative Medicine, Eberhard Karls University Tuebingen, 72076, Tuebingen, Germany
- NMI Natural and Medical Sciences Institute at the University of Tuebingen, 72770, Reutlingen, Germany
| | - Meinrad Paul Gawaz
- Department of Cardiology and Angiology, University Hospital Tuebingen, Eberhard Karls University Tuebingen, 72076, Tuebingen, Germany.
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Pioppi L, Parvan R, Samrend A, Silva GJJ, Paolantoni M, Sassi P, Cataliotti A. Vibrational spectroscopy identifies myocardial chemical modifications in heart failure with preserved ejection fraction. J Transl Med 2023; 21:617. [PMID: 37697391 PMCID: PMC10496315 DOI: 10.1186/s12967-023-04465-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Accepted: 08/22/2023] [Indexed: 09/13/2023] Open
Abstract
BACKGROUND Vibrational spectroscopy can be a valuable tool to monitor the markers of cardiovascular diseases. In the present work, we explored the vibrational spectroscopy characteristics of the cardiac tissue in an experimental model of heart failure with preserved ejection fraction (HFpEF). The goal was to detect early cardiac chemical modifications associated with the development of HFpEF. METHODS We used the Fourier-transform infrared (FTIR) and Raman micro-spectroscopic techniques to provide complementary and objective tools for the histological assessment of heart tissues from an animal model of HFpEF. A new sampling technique was adopted (tissue print on a CaF2 disk) to characterize the extracellular matrix. RESULTS Several spectroscopic markers (lipids, carbohydrates, and glutamate bands) were recognized in the cardiac ventricles due to the comorbidities associated with the pathology, such as obesity and diabetes. Besides, abnormal collagen cross-linking and a decrease in tryptophan content were observed and related to the stiffening of ventricles and to the inflammatory state which is a favourable condition for HFpEF. CONCLUSIONS By the analyses of tissues and tissue prints, FTIR and Raman techniques were shown to be highly sensitive and selective in detecting changes in the chemistry of the heart in experimental HFpEF and its related comorbidities. Vibrational spectroscopy is a new approach that can identify novel biomarkers for early detection of HFpEF.
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Affiliation(s)
- Leonardo Pioppi
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06123, Perugia, Italy
| | - Reza Parvan
- Institute for Experimental Medical Research, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Alan Samrend
- Institute for Experimental Medical Research, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Gustavo Jose Justo Silva
- Institute for Experimental Medical Research, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Marco Paolantoni
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06123, Perugia, Italy
| | - Paola Sassi
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06123, Perugia, Italy.
| | - Alessandro Cataliotti
- Institute for Experimental Medical Research, Oslo University Hospital and University of Oslo, Oslo, Norway.
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Cutshaw G, Uthaman S, Hassan N, Kothadiya S, Wen X, Bardhan R. The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine. Chem Rev 2023; 123:8297-8346. [PMID: 37318957 PMCID: PMC10626597 DOI: 10.1021/acs.chemrev.2c00897] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Omics technologies have rapidly evolved with the unprecedented potential to shape precision medicine. Novel omics approaches are imperative toallow rapid and accurate data collection and integration with clinical information and enable a new era of healthcare. In this comprehensive review, we highlight the utility of Raman spectroscopy (RS) as an emerging omics technology for clinically relevant applications using clinically significant samples and models. We discuss the use of RS both as a label-free approach for probing the intrinsic metabolites of biological materials, and as a labeled approach where signal from Raman reporters conjugated to nanoparticles (NPs) serve as an indirect measure for tracking protein biomarkers in vivo and for high throughout proteomics. We summarize the use of machine learning algorithms for processing RS data to allow accurate detection and evaluation of treatment response specifically focusing on cancer, cardiac, gastrointestinal, and neurodegenerative diseases. We also highlight the integration of RS with established omics approaches for holistic diagnostic information. Further, we elaborate on metal-free NPs that leverage the biological Raman-silent region overcoming the challenges of traditional metal NPs. We conclude the review with an outlook on future directions that will ultimately allow the adaptation of RS as a clinical approach and revolutionize precision medicine.
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Affiliation(s)
- Gabriel Cutshaw
- Department of Chemical and Biological Engineering, Iowa State University, Ames, IA 50012, USA
- Nanovaccine Institute, Iowa State University, Ames, IA 50012, USA
| | - Saji Uthaman
- Department of Chemical and Biological Engineering, Iowa State University, Ames, IA 50012, USA
- Nanovaccine Institute, Iowa State University, Ames, IA 50012, USA
| | - Nora Hassan
- Department of Chemical and Biological Engineering, Iowa State University, Ames, IA 50012, USA
- Nanovaccine Institute, Iowa State University, Ames, IA 50012, USA
| | - Siddhant Kothadiya
- Department of Chemical and Biological Engineering, Iowa State University, Ames, IA 50012, USA
- Nanovaccine Institute, Iowa State University, Ames, IA 50012, USA
| | - Xiaona Wen
- Biologics Analytical Research and Development, Merck & Co., Inc., Rahway, NJ, 07065, USA
| | - Rizia Bardhan
- Department of Chemical and Biological Engineering, Iowa State University, Ames, IA 50012, USA
- Nanovaccine Institute, Iowa State University, Ames, IA 50012, USA
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FTIR Analysis of Renal Tissue for the Assessment of Hypertensive Organ Damage and proANP31–67 Treatment. Int J Mol Sci 2023; 24:ijms24065196. [PMID: 36982271 PMCID: PMC10049716 DOI: 10.3390/ijms24065196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 02/23/2023] [Accepted: 03/07/2023] [Indexed: 03/11/2023] Open
Abstract
The kidneys are one of the main end organs targeted by hypertensive disease. Although the central role of the kidneys in the regulation of high blood pressure has been long recognized, the detailed mechanisms behind the pathophysiology of renal damage in hypertension remain a matter of investigation. Early renal biochemical alterations due to salt-induced hypertension in Dahl/salt-sensitive rats were monitored by Fourier-Transform Infrared (FTIR) micro-imaging. Furthermore, FTIR was used to investigate the effects of proANP31–67, a linear fragment of pro-atrial natriuretic peptide, on the renal tissue of hypertensive rats. Different hypertension-induced alterations were detected in the renal parenchyma and blood vessels by the combination of FTIR imaging and principal component analysis on specific spectral regions. Changes in amino acids and protein contents observed in renal blood vessels were independent of altered lipid, carbohydrate, and glycoprotein contents in the renal parenchyma. FTIR micro-imaging was found to be a reliable tool for monitoring the remarkable heterogeneity of kidney tissue and its hypertension-induced alterations. In addition, FTIR detected a significant reduction in these hypertension-induced alterations in the kidneys of proANP31–67-treated rats, further indicating the high sensitivity of this cutting-edge imaging modality and the beneficial effects of this novel medication on the kidneys.
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Impaired Extracellular Proteostasis in Patients with Heart Failure. Arch Med Res 2023; 54:211-222. [PMID: 36797157 DOI: 10.1016/j.arcmed.2023.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 01/11/2023] [Accepted: 02/02/2023] [Indexed: 02/16/2023]
Abstract
BACKGROUND Proteostasis impairment and the consequent increase of amyloid burden in the myocardium have been associated with heart failure (HF) development and poor prognosis. A better knowledge of the protein aggregation process in biofluids could assist the development and monitoring of tailored interventions. AIM To compare the proteostasis status and protein's secondary structures in plasma samples of patients with HF with preserved ejection fraction (HFpEF), patients with HF with reduced ejection fraction (HFrEF), and age-matched individuals. METHODS A total of 42 participants were enrolled in 3 groups: 14 patients with HFpEF, 14 patients with HFrEF, and 14 age-matched individuals. Proteostasis-related markers were analyzed by immunoblotting techniques. Fourier Transform Infrared (FTIR) Spectroscopy in Attenuated Total Reflectance (ATR) was applied to assess changes in the protein's conformational profile. RESULTS Patients with HFrEF showed an elevated concentration of oligomeric proteic species and reduced clusterin levels. ATR-FTIR spectroscopy coupled with multivariate analysis allowed the discrimination of HF patients from age-matched individuals in the protein amide I absorption region (1700-1600 cm-1), reflecting changes in protein conformation, with a sensitivity of 73 and a specificity of 81%. Further analysis of FTIR spectra showed significantly reduced random coils levels in both HF phenotypes. Also, compared to the age-matched group, the levels of structures related to fibril formation were significantly increased in patients with HFrEF, whereas the β-turns were significantly increased in patients with HFpEF. CONCLUSION Both HF phenotypes showed a compromised extracellular proteostasis and different protein conformational changes, suggesting a less efficient protein quality control system.
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