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Abou Kamar S, Andrzejczyk K, Petersen TB, Chin JF, Aga YS, de Bakker M, Akkerhuis KM, Geleijnse M, Brugts JJ, Sorop O, de Boer RA, Rizopoulos D, Asselbergs FW, Boersma E, den Ruijter H, van Dalen BM, Kardys I. The plasma proteome is linked with left ventricular and left atrial function parameters in patients with chronic heart failure. Eur Heart J Cardiovasc Imaging 2024; 25:1206-1215. [PMID: 38597740 PMCID: PMC11346355 DOI: 10.1093/ehjci/jeae098] [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: 11/27/2023] [Revised: 02/26/2024] [Accepted: 03/30/2024] [Indexed: 04/11/2024] Open
Abstract
AIMS Examining the systemic biological processes in the heterogeneous syndrome of heart failure with reduced ejection fraction (HFrEF), as reflected by circulating proteins, in relation to echocardiographic characteristics, may provide insights into heart failure pathophysiology. We investigated the link of 4210 repeatedly measured circulating proteins with repeatedly measured echocardiographic parameters as well as with elevated left atrial pressure (LAP), in patients with HFrEF, to provide insights into underlying mechanisms. METHODS AND RESULTS In 173 patients with HFrEF, we performed 6-monthly echocardiography and trimonthly blood sampling during a median follow-up of 2.7 (inter-quartile range: 2.5-2.8) years. We investigated circulating proteins in relation to echocardiographic parameters of left ventricular [left ventricular ejection fraction (LVEF), global longitudinal strain (GLS)] and left atrial function [left atrial reservoir strain (LASr)] and elevated LAP (E/e' ratio >15) and used gene enrichment analyses to identify underlying pathophysiological processes. We found 723, 249, 792, and 427 repeatedly measured proteins, with significant associations with LVEF, GLS, LASr, and E/e' ratio, respectively. Proteins associated with LASr reflected pathophysiological mechanisms mostly related to the extracellular matrix. Proteins associated with GLS reflected cardiovascular biological processes and diseases, whereas those associated with LVEF reflected processes involved in the sympathetic nervous system. Moreover, 49 proteins were associated with elevated LAP; after correction for LVEF, three proteins remained: cystatin-D, fibulin-5, and HSP40. CONCLUSION Circulating proteins show varying associations with different echocardiographic parameters in patients with HFrEF. These findings suggest that pathways involved in atrial and ventricular dysfunction, as reflected by the plasma proteome, are distinct.
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Affiliation(s)
- S Abou Kamar
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
- The Netherlands Heart Institute, Moreelsepark 1, 3511 EP Utrecht, The Netherlands
- Department of Cardiology, Franciscus Gasthuis & Vlietland, Kleiweg 500, 3045 PM Rotterdam, The Netherlands
| | - K Andrzejczyk
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - T B Petersen
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
- Department of Biostatistics, University Medical Center Rotterdam, Erasmus University, Dr. Molewaterplein 40, 3000 CA Rotterdam, The Netherlands
| | - J F Chin
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
- Department of Cardiology, Franciscus Gasthuis & Vlietland, Kleiweg 500, 3045 PM Rotterdam, The Netherlands
| | - Y S Aga
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
- Department of Cardiology, Franciscus Gasthuis & Vlietland, Kleiweg 500, 3045 PM Rotterdam, The Netherlands
| | - M de Bakker
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - K M Akkerhuis
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - M Geleijnse
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - J J Brugts
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - O Sorop
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - R A de Boer
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - D Rizopoulos
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
- Department of Biostatistics, University Medical Center Rotterdam, Erasmus University, Dr. Molewaterplein 40, 3000 CA Rotterdam, The Netherlands
| | - F W Asselbergs
- Department of Cardiology, Amsterdam Medical Center, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - E Boersma
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
| | - H den Ruijter
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - B M van Dalen
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
- Department of Cardiology, Franciscus Gasthuis & Vlietland, Kleiweg 500, 3045 PM Rotterdam, The Netherlands
| | - I Kardys
- Department of Cardiology, Erasmus MC, Thorax Center, Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, PO Box 2040 3000 CA Rotterdam, The Netherlands
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Sun BB, Suhre K, Gibson BW. Promises and Challenges of populational Proteomics in Health and Disease. Mol Cell Proteomics 2024; 23:100786. [PMID: 38761890 PMCID: PMC11193116 DOI: 10.1016/j.mcpro.2024.100786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 05/13/2024] [Accepted: 05/15/2024] [Indexed: 05/20/2024] Open
Abstract
Advances in proteomic assay technologies have significantly increased coverage and throughput, enabling recent increases in the number of large-scale population-based proteomic studies of human plasma and serum. Improvements in multiplexed protein assays have facilitated the quantification of thousands of proteins over a large dynamic range, a key requirement for detecting the lowest-ranging, and potentially the most disease-relevant, blood-circulating proteins. In this perspective, we examine how populational proteomic datasets in conjunction with other concurrent omic measures can be leveraged to better understand the genomic and non-genomic correlates of the soluble proteome, constructing biomarker panels for disease prediction, among others. Mass spectrometry workflows are discussed as they are becoming increasingly competitive with affinity-based array platforms in terms of speed, cost, and proteome coverage due to advances in both instrumentation and workflows. Despite much success, there remain considerable challenges such as orthogonal validation and absolute quantification. We also highlight emergent challenges associated with study design, analytical considerations, and data integration as population-scale studies are run in batches and may involve longitudinal samples collated over many years. Lastly, we take a look at the future of what the nascent next-generation proteomic technologies might provide to the analysis of large sets of blood samples, as well as the difficulties in designing large-scale studies that will likely require participation from multiple and complex funding sources and where data sharing, study designs, and financing must be solved.
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Affiliation(s)
- Benjamin B Sun
- Human Genetics, Informatics and Predictive Sciences, Bristol-Myers Squibb, Cambridge, Massachusetts, USA.
| | - Karsten Suhre
- Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar; Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, New York, USA
| | - Bradford W Gibson
- Pharmaceutical Chemistry, University of California, San Francisco, California, USA
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3
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Kim T, Rhee EP. Aptamer-Based Proteomics in CKD. Am J Kidney Dis 2024; 83:825-828. [PMID: 38281681 DOI: 10.1053/j.ajkd.2024.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 01/13/2024] [Indexed: 01/30/2024]
Affiliation(s)
- Taesoo Kim
- Nephrology Division, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Eugene P Rhee
- Nephrology Division, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts; Endocrine Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts.
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Turizo MJF, Patell R, Zwicker JI. Identifying novel biomarkers using proteomics to predict cancer-associated thrombosis. BLEEDING, THROMBOSIS AND VASCULAR BIOLOGY 2024; 3:120. [PMID: 38828226 PMCID: PMC11143428 DOI: 10.4081/btvb.2024.120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 04/08/2024] [Indexed: 06/05/2024]
Abstract
Comprehensive protein analyses of plasma are made possible by high-throughput proteomic screens, which may help find new therapeutic targets and diagnostic biomarkers. Patients with cancer are frequently affected by venous thromboembolism (VTE). The limited predictive accuracy of current VTE risk assessment tools highlights the need for new, more targeted biomarkers. Although coagulation biomarkers for the diagnosis, prognosis, and treatment of VTE have been investigated, none of them have the necessary clinical validation or diagnostic accuracy. Proteomics holds the potential to uncover new biomarkers and thrombotic pathways that impact the risk of thrombosis. This review explores the fundamental methods used in proteomics and focuses on particular biomarkers found in VTE and cancer-associated thrombosis.
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Affiliation(s)
- Maria J Fernandez Turizo
- Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Rushad Patell
- Division of Medical Oncology and Hematology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Jeffrey I Zwicker
- Department of Medicine, Hematology Service, Memorial Sloan Kettering Cancer Center, New York, NY
- Weil Cornell Medical College, New York, NY, United States
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Hernández ÁP, Chaparro-González L, Garzo-Sánchez O, Arias-Hidalgo C, Juanes-Velasco P, García PA, Castro MÁ, Fuentes M. Podophyllic Aldehyde, a Podophyllotoxin Derivate, Elicits Different Cell Cycle Profiles Depending on the Tumor Cell Line: A Systematic Proteomic Analysis. Int J Mol Sci 2024; 25:4631. [PMID: 38731850 PMCID: PMC11083757 DOI: 10.3390/ijms25094631] [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: 03/15/2024] [Revised: 04/16/2024] [Accepted: 04/19/2024] [Indexed: 05/13/2024] Open
Abstract
When new antitumor therapy drugs are discovered, it is essential to address new target molecules from the point of view of chemical structure and to carry out efficient and systematic evaluation. In the case of natural products and derived compounds, it is of special importance to investigate chemomodulation to further explore antitumoral pharmacological activities. In this work, the compound podophyllic aldehyde, a cyclolignan derived from the chemomodulation of the natural product podophyllotoxin, has been evaluated for its viability, influence on the cell cycle, and effects on intracellular signaling. We used functional proteomics characterization for the evaluation. Compared with the FDA-approved drug etoposide (another podophyllotoxin derivative), we found interesting results regarding the cytotoxicity of podophyllic aldehyde. In addition, we were able to observe the effect of mitotic arrest in the treated cells. The use of podophyllic aldehyde resulted in increased cytotoxicity in solid tumor cell lines, compared to etoposide, and blocked the cycle more successfully than etoposide. High-throughput analysis of the deregulated proteins revealed a selective antimitotic mechanism of action of podophyllic aldehyde in the HT-29 cell line, in contrast with other solid and hematological tumor lines. Also, the apoptotic profile of podophyllic aldehyde was deciphered. The cell death mechanism is activated independently of the cell cycle profile. The results of these targeted analyses have also shown a significant response to the signaling of kinases, key proteins involved in signaling cascades for cell proliferation or metastasis. Thanks to this comprehensive analysis of podophyllic aldehyde, remarkable cytotoxic, antimitotic, and other antitumoral features have been discovered that will repurpose this compound for further chemical transformations and antitumoral analysis.
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Affiliation(s)
- Ángela-Patricia Hernández
- Department of Medicine and General Cytometry Service-Nucleus, CIBERONC CB16/12/00400, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), IBSAL, University of Salamanca-CSIC, Campus Miguel de Unamuno s/n, 37007 Salamanca, Spain; (L.C.-G.); (O.G.-S.); (C.A.-H.); (P.J.-V.); (M.F.)
- Department of Pharmaceutical Sciences, Laboratory of Medicinal Chemistry, Faculty of Pharmacy, University of Salamanca, Campus Miguel de Unamuno s/n, 37007 Salamanca, Spain; (P.A.G.); (M.Á.C.)
| | - Lorea Chaparro-González
- Department of Medicine and General Cytometry Service-Nucleus, CIBERONC CB16/12/00400, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), IBSAL, University of Salamanca-CSIC, Campus Miguel de Unamuno s/n, 37007 Salamanca, Spain; (L.C.-G.); (O.G.-S.); (C.A.-H.); (P.J.-V.); (M.F.)
| | - Olga Garzo-Sánchez
- Department of Medicine and General Cytometry Service-Nucleus, CIBERONC CB16/12/00400, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), IBSAL, University of Salamanca-CSIC, Campus Miguel de Unamuno s/n, 37007 Salamanca, Spain; (L.C.-G.); (O.G.-S.); (C.A.-H.); (P.J.-V.); (M.F.)
| | - Carlota Arias-Hidalgo
- Department of Medicine and General Cytometry Service-Nucleus, CIBERONC CB16/12/00400, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), IBSAL, University of Salamanca-CSIC, Campus Miguel de Unamuno s/n, 37007 Salamanca, Spain; (L.C.-G.); (O.G.-S.); (C.A.-H.); (P.J.-V.); (M.F.)
| | - Pablo Juanes-Velasco
- Department of Medicine and General Cytometry Service-Nucleus, CIBERONC CB16/12/00400, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), IBSAL, University of Salamanca-CSIC, Campus Miguel de Unamuno s/n, 37007 Salamanca, Spain; (L.C.-G.); (O.G.-S.); (C.A.-H.); (P.J.-V.); (M.F.)
| | - Pablo A. García
- Department of Pharmaceutical Sciences, Laboratory of Medicinal Chemistry, Faculty of Pharmacy, University of Salamanca, Campus Miguel de Unamuno s/n, 37007 Salamanca, Spain; (P.A.G.); (M.Á.C.)
| | - Mª Ángeles Castro
- Department of Pharmaceutical Sciences, Laboratory of Medicinal Chemistry, Faculty of Pharmacy, University of Salamanca, Campus Miguel de Unamuno s/n, 37007 Salamanca, Spain; (P.A.G.); (M.Á.C.)
| | - Manuel Fuentes
- Department of Medicine and General Cytometry Service-Nucleus, CIBERONC CB16/12/00400, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), IBSAL, University of Salamanca-CSIC, Campus Miguel de Unamuno s/n, 37007 Salamanca, Spain; (L.C.-G.); (O.G.-S.); (C.A.-H.); (P.J.-V.); (M.F.)
- Proteomics Unit, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, Spain
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Lee C, Liang LW, Hasegawa K, Maurer MS, Tower-Rader A, Fifer MA, Reilly M, Shimada YJ. Signaling Pathways Associated With Prior Cardiovascular Events in Hypertrophic Cardiomyopathy. J Card Fail 2024; 30:462-472. [PMID: 37562580 PMCID: PMC10853480 DOI: 10.1016/j.cardfail.2023.07.010] [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: 02/27/2023] [Revised: 07/14/2023] [Accepted: 07/17/2023] [Indexed: 08/12/2023]
Abstract
BACKGROUND Hypertrophic cardiomyopathy (HCM) is the most common genetic cardiomyopathy. A subset of patients experience major adverse cardiovascular events (MACEs), including arrhythmias, strokes and heart failure. However, the molecular mechanisms underlying MACEs in HCM are still not well understood. Therefore, we conducted a multicenter case-control study of patients with HCM, comparing those with and without prior histories of MACEs to identify dysregulated signaling pathways through plasma proteomics profiling. METHODS We performed plasma proteomics profiling of 4986 proteins. We developed a proteomics-based discrimination model in patients enrolled at 1 institution (training set) and externally validated the model in patients enrolled at another institution (test set). We performed pathway analysis of proteins dysregulated in patients with prior MACEs. RESULTS A total of 402 patients were included, with 278 in the training set and 124 in the test set. In this cohort, 257 (64%) patients had prior MACEs (172 in the training set and 85 in the test set). Using the proteomics-based model from the training set, the area under the receiver operating characteristic curve was 0.82 (95% confidence interval, 0.75-0.90) in the test set. Patients with prior MACEs demonstrated dysregulation in pathways known to be associated with MACEs (eg, TGF-β) and novel pathways (eg, Ras-MAPK and associated pathways). CONCLUSIONS In this multicenter study of 402 patients with HCM, we identified both known and novel pathways dysregulated in a subset of patients with more advanced disease.
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Affiliation(s)
- Charlotte Lee
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Lusha W Liang
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Kohei Hasegawa
- Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Mathew S Maurer
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Albree Tower-Rader
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Michael A Fifer
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Muredach Reilly
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY; Irving Institute for Clinical and Translational Research, Columbia University Irving Medical Center, New York, NY
| | - Yuichi J Shimada
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY.
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Yu G, Tam HCH, Huang C, Shi M, Lim CKP, Chan JCN, Ma RCW. Lessons and Applications of Omics Research in Diabetes Epidemiology. Curr Diab Rep 2024; 24:27-44. [PMID: 38294727 PMCID: PMC10874344 DOI: 10.1007/s11892-024-01533-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/04/2024] [Indexed: 02/01/2024]
Abstract
PURPOSE OF REVIEW Recent advances in genomic technology and molecular techniques have greatly facilitated the identification of disease biomarkers, advanced understanding of pathogenesis of different common diseases, and heralded the dawn of precision medicine. Much of these advances in the area of diabetes have been made possible through deep phenotyping of epidemiological cohorts, and analysis of the different omics data in relation to detailed clinical information. In this review, we aim to provide an overview on how omics research could be incorporated into the design of current and future epidemiological studies. RECENT FINDINGS We provide an up-to-date review of the current understanding in the area of genetic, epigenetic, proteomic and metabolomic markers for diabetes and related outcomes, including polygenic risk scores. We have drawn on key examples from the literature, as well as our own experience of conducting omics research using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank, as well as other cohorts, to illustrate the potential of omics research in diabetes. Recent studies highlight the opportunity, as well as potential benefit, to incorporate molecular profiling in the design and set-up of diabetes epidemiology studies, which can also advance understanding on the heterogeneity of diabetes. Learnings from these examples should facilitate other researchers to consider incorporating research on omics technologies into their work to advance the field and our understanding of diabetes and its related co-morbidities. Insights from these studies would be important for future development of precision medicine in diabetes.
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Affiliation(s)
- Gechang Yu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Henry C H Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Chuiguo Huang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Mai Shi
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Cadmon K P Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China.
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China.
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China.
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Shahjahan, Dey JK, Dey SK. Translational bioinformatics approach to combat cardiovascular disease and cancers. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2024; 139:221-261. [PMID: 38448136 DOI: 10.1016/bs.apcsb.2023.11.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Bioinformatics is an interconnected subject of science dealing with diverse fields including biology, chemistry, physics, statistics, mathematics, and computer science as the key fields to answer complicated physiological problems. Key intention of bioinformatics is to store, analyze, organize, and retrieve essential information about genome, proteome, transcriptome, metabolome, as well as organisms to investigate the biological system along with its dynamics, if any. The outcome of bioinformatics depends on the type, quantity, and quality of the raw data provided and the algorithm employed to analyze the same. Despite several approved medicines available, cardiovascular disorders (CVDs) and cancers comprises of the two leading causes of human deaths. Understanding the unknown facts of both these non-communicable disorders is inevitable to discover new pathways, find new drug targets, and eventually newer drugs to combat them successfully. Since, all these goals involve complex investigation and handling of various types of macro- and small- molecules of the human body, bioinformatics plays a key role in such processes. Results from such investigation has direct human application and thus we call this filed as translational bioinformatics. Current book chapter thus deals with diverse scope and applications of this translational bioinformatics to find cure, diagnosis, and understanding the mechanisms of CVDs and cancers. Developing complex yet small or long algorithms to address such problems is very common in translational bioinformatics. Structure-based drug discovery or AI-guided invention of novel antibodies that too with super-high accuracy, speed, and involvement of considerably low amount of investment are some of the astonishing features of the translational bioinformatics and its applications in the fields of CVDs and cancers.
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Affiliation(s)
- Shahjahan
- Laboratory for Structural Biology of Membrane Proteins, Dr. B.R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India
| | - Joy Kumar Dey
- Central Council for Research in Homoeopathy, Ministry of Ayush, Govt. of India, New Delhi, Delhi, India
| | - Sanjay Kumar Dey
- Laboratory for Structural Biology of Membrane Proteins, Dr. B.R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India.
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Shah AM, Myhre PL, Arthur V, Dorbala P, Rasheed H, Buckley LF, Claggett B, Liu G, Ma J, Nguyen NQ, Matsushita K, Ndumele C, Tin A, Hveem K, Jonasson C, Dalen H, Boerwinkle E, Hoogeveen RC, Ballantyne C, Coresh J, Omland T, Yu B. Large scale plasma proteomics identifies novel proteins and protein networks associated with heart failure development. Nat Commun 2024; 15:528. [PMID: 38225249 PMCID: PMC10789789 DOI: 10.1038/s41467-023-44680-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 12/21/2023] [Indexed: 01/17/2024] Open
Abstract
Heart failure (HF) causes substantial morbidity and mortality but its pathobiology is incompletely understood. The proteome is a promising intermediate phenotype for discovery of novel mechanisms. We measured 4877 plasma proteins in 13,900 HF-free individuals across three analysis sets with diverse age, geography, and HF ascertainment to identify circulating proteins and protein networks associated with HF development. Parallel analyses in Atherosclerosis Risk in Communities study participants in mid-life and late-life and in Trøndelag Health Study participants identified 37 proteins consistently associated with incident HF independent of traditional risk factors. Mendelian randomization supported causal effects of 10 on HF, HF risk factors, or left ventricular size and function, including matricellular (e.g. SPON1, MFAP4), senescence-associated (FSTL3, IGFBP7), and inflammatory (SVEP1, CCL15, ITIH3) proteins. Protein co-regulation network analyses identified 5 modules associated with HF risk, two of which were influenced by genetic variants that implicated trans hotspots within the VTN and CFH genes.
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Affiliation(s)
- Amil M Shah
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, MA, USA.
| | - Peder L Myhre
- Akershus University Hospital and K.G. Jebsen Center for Cardiac Biomarkers, University of Oslo, Oslo, Norway
| | - Victoria Arthur
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Pranav Dorbala
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Humaira Rasheed
- Akershus University Hospital and K.G. Jebsen Center for Cardiac Biomarkers, University of Oslo, Oslo, Norway
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Public Health and Nursing, HUNT Research Center, Norwegian University of Science and Technology, Trondheim, Norway
| | - Leo F Buckley
- Department of Pharmacy, Brigham and Women's Hospital, Boston, MA, USA
| | - Brian Claggett
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Guning Liu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Sciences Center at Houston, Houston, TX, USA
| | - Jianzhong Ma
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Sciences Center at Houston, Houston, TX, USA
| | - Ngoc Quynh Nguyen
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Sciences Center at Houston, Houston, TX, USA
| | - Kunihiro Matsushita
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Chiadi Ndumele
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Adrienne Tin
- University of Mississippi Medical Center, Jackson, MS, USA
| | - Kristian Hveem
- Department of Public Health and Nursing, HUNT Research Center, Norwegian University of Science and Technology, Trondheim, Norway
| | - Christian Jonasson
- Department of Public Health and Nursing, HUNT Research Center, Norwegian University of Science and Technology, Trondheim, Norway
| | - Håvard Dalen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Cardiology, St Olavs University Hospital, Trondheim, Norway
- Department of Internal Medicine, Levanger Hospital, Levanger, Norway
| | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Sciences Center at Houston, Houston, TX, USA
| | - Ron C Hoogeveen
- Division of Cardiology, Baylor College of Medicine, Houston, TX, USA
| | | | - Josef Coresh
- Departments of Medicine and Population Health, NYU Langone Health, New York, NY, USA
| | - Torbjørn Omland
- Akershus University Hospital and K.G. Jebsen Center for Cardiac Biomarkers, University of Oslo, Oslo, Norway
| | - Bing Yu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Sciences Center at Houston, Houston, TX, USA
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10
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Kuku KO, Shearer JJ, Hashemian M, Oyetoro R, Park H, Dulek B, Bielinski SJ, Larson NB, Ganz P, Levy D, Psaty BM, Joo J, Roger VL. Development and Validation of a Protein Risk Score for Mortality in Heart Failure : A Community Cohort Study. Ann Intern Med 2024; 177:39-49. [PMID: 38163367 PMCID: PMC10958437 DOI: 10.7326/m23-2328] [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] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND Heart failure (HF) is a complex clinical syndrome with high mortality. Current risk stratification approaches lack precision. High-throughput proteomics could improve risk prediction. Its use in clinical practice to guide the management of patients with HF depends on validation and evidence of clinical benefit. OBJECTIVE To develop and validate a protein risk score for mortality in patients with HF. DESIGN Community-based cohort. SETTING Southeast Minnesota. PARTICIPANTS Patients with HF enrolled between 2003 and 2012 and followed through 2021. MEASUREMENTS A total of 7289 plasma proteins in 1351 patients with HF were measured using the SomaScan Assay (SomaLogic). A protein risk score was derived using least absolute shrinkage and selection operator regression and temporal validation in patients enrolled between 2003 and 2007 (development cohort) and 2008 and 2012 (validation cohort). Multivariable Cox regression was used to examine the association between the protein risk score and mortality. The performance of the protein risk score to predict 5-year mortality risk was assessed using calibration plots, decision curves, and relative utility analyses and compared with a clinical model, including the Meta-Analysis Global Group in Chronic Heart Failure mortality risk score and N-terminal pro-B-type natriuretic peptide. RESULTS The development (n = 855; median age, 78 years; 50% women; 29% with ejection fraction <40%) and validation cohorts (n = 496; median age, 76 years; 45% women; 33% with ejection fraction <40%) were mostly similar. In the development cohort, 38 unique proteins were selected for the protein risk score. Independent of ejection fraction, the protein risk score demonstrated good calibration, reclassified mortality risk particularly at the extremes of the risk distribution, and showed greater clinical utility compared with the clinical model. LIMITATION Participants were predominantly of European ancestry, potentially limiting the generalizability of the findings to different patient populations. CONCLUSION Validation of the protein risk score demonstrated good calibration and evidence of predicted benefits to stratify the risk for death in HF superior to that of clinical methods. Further studies are needed to prospectively evaluate the score's performance in diverse populations and determine risk thresholds for interventions. PRIMARY FUNDING SOURCE Division of Intramural Research at the National Heart, Lung, and Blood Institute of the National Institutes of Health.
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Affiliation(s)
- Kayode O Kuku
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Joseph J. Shearer
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Maryam Hashemian
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Rebecca Oyetoro
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Hoyoung Park
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Brittany Dulek
- Integrated Data Science Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Suzette, J. Bielinski
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Nicholas B. Larson
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Peter Ganz
- Zuckerberg San Francisco General Hospital, University of California, San Francisco, San Francisco, CA, USA
| | - Daniel Levy
- Laboratory for Cardiovascular Epidemiology and Genomics, Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology and Health Systems and Population Health, University of Washington, Seattle, Washington, USA
| | - Jungnam Joo
- Office of Biostatistics Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Véronique L. Roger
- Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
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11
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Li J, Lu X. Cardiovascular risk assessment: The key path toward precision prevention. Chronic Dis Transl Med 2023; 9:273-276. [PMID: 37915392 PMCID: PMC10617312 DOI: 10.1002/cdt3.90] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 07/08/2023] [Accepted: 07/13/2023] [Indexed: 11/03/2023] Open
Affiliation(s)
- Jianxin Li
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Key Laboratory of Cardiovascular EpidemiologyChinese Academy of Medical SciencesBeijingChina
| | - Xiangfeng Lu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Key Laboratory of Cardiovascular EpidemiologyChinese Academy of Medical SciencesBeijingChina
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12
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Russo MA, Garaci E, Frustaci A, Fini M, Costantini C, Oikonomou V, Nunzi E, Puccetti P, Romani L. Host-microbe tryptophan partitioning in cardiovascular diseases. Pharmacol Res 2023; 198:106994. [PMID: 37972721 DOI: 10.1016/j.phrs.2023.106994] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/27/2023] [Accepted: 11/13/2023] [Indexed: 11/19/2023]
Abstract
The functional interdependencies between the molecular components of a biological process demand for a network medicine platform that integrates systems biology and network science, to explore the interactions among biological components in health and disease. Access to large-scale omics datasets (genomics, transcriptomics, proteomics, metabolomics, metagenomics, phenomics, etc.) has significantly advanced our opportunity along this direction. Studies utilizing these techniques have begun to provide us with a deeper understanding of how the interaction between the intestinal microbes and their host affects the cardiovascular system in health and disease. Within the framework of a multiomics network approach, we highlight here how tryptophan metabolism may orchestrate the host-microbes interaction in cardiovascular diseases and the implications for precision medicine and therapeutics, including nutritional interventions.
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Affiliation(s)
- Matteo Antonio Russo
- University San Raffaele and Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele, 00166 Rome, Italy
| | - Enrico Garaci
- University San Raffaele and Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele, 00166 Rome, Italy
| | - Andrea Frustaci
- University San Raffaele and Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele, 00166 Rome, Italy
| | - Massimo Fini
- University San Raffaele and Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele, 00166 Rome, Italy
| | - Claudio Costantini
- Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy
| | - Vasileios Oikonomou
- Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy
| | - Emilia Nunzi
- Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy
| | - Paolo Puccetti
- Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy
| | - Luigina Romani
- University San Raffaele and Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele, 00166 Rome, Italy; Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy.
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13
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de Bakker M, Petersen TB, Rueten-Budde AJ, Akkerhuis KM, Umans VA, Brugts JJ, Germans T, Reinders MJT, Katsikis PD, van der Spek PJ, Ostroff R, She R, Lanfear D, Asselbergs FW, Boersma E, Rizopoulos D, Kardys I. Machine learning-based biomarker profile derived from 4210 serially measured proteins predicts clinical outcome of patients with heart failure. EUROPEAN HEART JOURNAL. DIGITAL HEALTH 2023; 4:444-454. [PMID: 38045440 PMCID: PMC10689916 DOI: 10.1093/ehjdh/ztad056] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 09/06/2023] [Accepted: 10/03/2023] [Indexed: 12/05/2023]
Abstract
Aims Risk assessment tools are needed for timely identification of patients with heart failure (HF) with reduced ejection fraction (HFrEF) who are at high risk of adverse events. In this study, we aim to derive a small set out of 4210 repeatedly measured proteins, which, along with clinical characteristics and established biomarkers, carry optimal prognostic capacity for adverse events, in patients with HFrEF. Methods and results In 382 patients, we performed repeated blood sampling (median follow-up: 2.1 years) and applied an aptamer-based multiplex proteomic approach. We used machine learning to select the optimal set of predictors for the primary endpoint (PEP: composite of cardiovascular death, heart transplantation, left ventricular assist device implantation, and HF hospitalization). The association between repeated measures of selected proteins and PEP was investigated by multivariable joint models. Internal validation (cross-validated c-index) and external validation (Henry Ford HF PharmacoGenomic Registry cohort) were performed. Nine proteins were selected in addition to the MAGGIC risk score, N-terminal pro-hormone B-type natriuretic peptide, and troponin T: suppression of tumourigenicity 2, tryptophanyl-tRNA synthetase cytoplasmic, histone H2A Type 3, angiotensinogen, deltex-1, thrombospondin-4, ADAMTS-like protein 2, anthrax toxin receptor 1, and cathepsin D. N-terminal pro-hormone B-type natriuretic peptide and angiotensinogen showed the strongest associations [hazard ratio (95% confidence interval): 1.96 (1.17-3.40) and 0.66 (0.49-0.88), respectively]. The multivariable model yielded a c-index of 0.85 upon internal validation and c-indices up to 0.80 upon external validation. The c-index was higher than that of a model containing established risk factors (P = 0.021). Conclusion Nine serially measured proteins captured the most essential prognostic information for the occurrence of adverse events in patients with HFrEF, and provided incremental value for HF prognostication beyond established risk factors. These proteins could be used for dynamic, individual risk assessment in a prospective setting. These findings also illustrate the potential value of relatively 'novel' biomarkers for prognostication. Clinical Trial Registration https://clinicaltrials.gov/ct2/show/NCT01851538?term=nCT01851538&draw=2&rank=1 24.
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Affiliation(s)
- Marie de Bakker
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Teun B Petersen
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
- Department of Biostatistics, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Anja J Rueten-Budde
- Department of Biostatistics, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - K Martijn Akkerhuis
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Victor A Umans
- Department of Cardiology, Northwest Clinics, Wilhelminalaan 12, 1815 JD, Alkmaar, The Netherlands
| | - Jasper J Brugts
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Tjeerd Germans
- Department of Cardiology, Northwest Clinics, Wilhelminalaan 12, 1815 JD, Alkmaar, The Netherlands
| | - Marcel J T Reinders
- Delft Bioinformatics Lab, Delft University of Technology, Van Mourik Broekmanweg 6, 2628 XE, Delft, The Netherlands
| | - Peter D Katsikis
- Department of Immunology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Peter J van der Spek
- Department of Pathology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Rachel Ostroff
- SomaLogic, Inc., 2945 Wilderness Pl., Boulder, CO 80301, USA
| | - Ruicong She
- Department of Public Health Sciences, Henry Ford Health System, 1 Ford Pl, Detroit, MI 48202, USA
| | - David Lanfear
- Center for Individualized and Genomic Medicine Research (CIGMA), Henry Ford Hospital, 2799 W. Grand Boulevard, Detroit MI, 48202, USA
- Heart and Vascular Institute, Henry Ford Hospital, 2799 W. Grand Boulevard, Detroit, MI 48202, USA
| | - Folkert W Asselbergs
- Amsterdam University Medical Centers, Department of Cardiology, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
- Health Data Research UK and Institute of Health Informatics, University College London, Gower St, London, WC1E 6BT, UK
| | - Eric Boersma
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Dimitris Rizopoulos
- Department of Biostatistics, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Isabella Kardys
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molenwaterplein 40, 3015GD, Rotterdam, The Netherlands
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14
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Ji SX, Zheng YF, Li X, Li BX, Zou JX, Wang YT, Xia XY, Chen X, Hu QN, Wan TJ, Wen L, Feng QS. Epidemiological investigation and proteomic profiling of typical TCM syndrome in HIV/AIDS immunological nonresponders. Anat Rec (Hoboken) 2023; 306:3106-3119. [PMID: 35775967 DOI: 10.1002/ar.25018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Revised: 05/11/2022] [Accepted: 06/02/2022] [Indexed: 11/09/2022]
Abstract
HIV/AIDS pandemic remains the world's most severe public health challenge, especially for HIV/AIDS immunological nonresponders (HIV/AIDS-INRs), who tend to have higher mortality. Due to the advantages in promoting patients' immune reconstitution, Traditional Chinese medicine (TCM) has become one of the mainstays of complementary treatments for HIV/AIDS-INRs. Given that effective TCM treatments largely depend on precise syndrome differentiation, there is an increasing interest in exploring biological evidence for the classification of TCM syndromes in HIV/AIDS-INRs. In our study, to identify the typical HIV/AIDS-INRs syndrome, an epidemiological survey was first conducted in the Liangshan prefecture (China), a high HIV/AIDS prevalence region. The key TCM syndrome, Yang deficiency of spleen and kidney (YDSK), was evaluated by using a tandem mass tag combined with liquid chromatography-tandem mass spectrometry (TMT-LC-MS/MS). A total of 62 differentially expressed proteins (DEPs) of YDSK syndrome compared with healthy people were screened out. Comparative bioinformatics analyses showed that DEPs in YDSK syndrome were mainly associated with response to wounding and acute inflammatory response in the biological process. The pathway annotation is mainly enriched in complement and coagulation cascades. Finally, the YDSK syndrome-specific DEPs such as HP and S100A9 were verified by ELISA, and confirmed as potential biomarkers for YDSK syndrome. Our study may lay the biological and scientific basis for the specificity of TCM syndromes in HIV/AIDs-INRs, and may provide more opportunities for the deep understanding of TCM syndromes and the developing more effective and stable TCM treatment for HIV/AIDS-INRs.
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Affiliation(s)
- Shao-Xiu Ji
- College of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China
- Yinchuan Hospital of Traditional Chinese Medicine, Yinchuan, Ningxia, People's Republic of China
| | - Yan-Feng Zheng
- College of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China
| | - Xia Li
- College of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China
| | - Bai-Xue Li
- College of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China
| | - Jia-Xi Zou
- College of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China
| | - Yi-Ting Wang
- College of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China
| | - Xin-Yi Xia
- College of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China
| | - Xin Chen
- College of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China
| | - Qian-Nan Hu
- College of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China
| | - Ting-Jun Wan
- College of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China
| | - Li Wen
- College of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China
| | - Quan-Sheng Feng
- College of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China
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15
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Siegbahn A, Eriksson N, Assarsson E, Lundberg M, Ballagi A, Held C, Stewart RAH, White HD, Åberg M, Wallentin L. Development and validation of a quantitative Proximity Extension Assay instrument with 21 proteins associated with cardiovascular risk (CVD-21). PLoS One 2023; 18:e0293465. [PMID: 37963145 PMCID: PMC10645335 DOI: 10.1371/journal.pone.0293465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 10/12/2023] [Indexed: 11/16/2023] Open
Abstract
BACKGROUND Treatment of cardiovascular diseases (CVD) is a substantial burden to healthcare systems worldwide. New tools are needed to improve precision of treatment by optimizing the balance between efficacy, safety, and cost. We developed a high-throughput multi-marker decision support instrument which simultaneously quantifies proteins associated with CVD. METHODS AND FINDINGS Candidate proteins independently associated with different clinical outcomes were selected from clinical studies by the screening of 368 circulating biomarkers. We then custom-designed a quantitative PEA-panel with 21 proteins (CVD-21) by including recombinant antigens as calibrator samples for normalization and absolute quantification of the proteins. The utility of the CVD-21 tool was evaluated in plasma samples from a case-control cohort of 4224 patients with chronic coronary syndrome (CCS) using multivariable Cox regression analyses and machine learning techniques. The assays in the CVD-21 tool gave good precision and high sensitivity with lower level of determination (LOD) between 0.03-0.7 pg/ml for five of the biomarkers. The dynamic range for the assays was sufficient to accurately quantify the biomarkers in the validation study except for troponin I, which in the modeling was replaced by high-sensitive cardiac troponin T (hs-TnT). We created seven different multimarker models, including a reference model with NT-proBNP, hs-TnT, GDF-15, IL-6, and cystatin C and one model with only clinical variables, for the comparison of the discriminative value of the CVD-21 tool. All models with biomarkers including hs-TnT provided similar discrimination for all outcomes, e.g. c-index between 0.68-0.86 and outperformed models using only clinical variables. Most important prognostic biomarkers were MMP-12, U-PAR, REN, VEGF-D, FGF-23, TFF3, ADM, and SCF. CONCLUSIONS The CVD-21 tool is the very first instrument which with PEA simultaneously quantifies 21 proteins with associations to different CVD. Novel pathophysiologic and prognostic information beyond that of established biomarkers were identified by a number of proteins.
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Affiliation(s)
- Agneta Siegbahn
- Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden
- Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden
- Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Niclas Eriksson
- Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden
| | | | | | | | - Claes Held
- Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden
- Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden
| | - Ralph A. H. Stewart
- Green Lane Cardiovascular Service, Te Whatu Ora Health New Zealand, Te Toka Tumai Auckland and University of Auckland, Auckland, New Zealand
| | - Harvey D. White
- Green Lane Cardiovascular Service, Te Whatu Ora Health New Zealand, Te Toka Tumai Auckland and University of Auckland, Auckland, New Zealand
| | - Mikael Åberg
- Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden
- Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Lars Wallentin
- Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden
- Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden
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16
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Reitz CJ, Kuzmanov U, Gramolini AO. Multi-omic analyses and network biology in cardiovascular disease. Proteomics 2023; 23:e2200289. [PMID: 37691071 DOI: 10.1002/pmic.202200289] [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: 03/17/2023] [Revised: 08/11/2023] [Accepted: 08/22/2023] [Indexed: 09/12/2023]
Abstract
Heart disease remains a leading cause of death in North America and worldwide. Despite advances in therapies, the chronic nature of cardiovascular diseases ultimately results in frequent hospitalizations and steady rates of mortality. Systems biology approaches have provided a new frontier toward unraveling the underlying mechanisms of cell, tissue, and organ dysfunction in disease. Mapping the complex networks of molecular functions across the genome, transcriptome, proteome, and metabolome has enormous potential to advance our understanding of cardiovascular disease, discover new disease biomarkers, and develop novel therapies. Computational workflows to interpret these data-intensive analyses as well as integration between different levels of interrogation remain important challenges in the advancement and application of systems biology-based analyses in cardiovascular research. This review will focus on summarizing the recent developments in network biology-level profiling in the heart, with particular emphasis on modeling of human heart failure. We will provide new perspectives on integration between different levels of large "omics" datasets, including integration of gene regulatory networks, protein-protein interactions, signaling networks, and metabolic networks in the heart.
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Affiliation(s)
- Cristine J Reitz
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Translational Biology and Engineering Program, Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada
| | - Uros Kuzmanov
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Translational Biology and Engineering Program, Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada
| | - Anthony O Gramolini
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Translational Biology and Engineering Program, Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada
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17
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Lovell JP, Bermea K, Yu J, Rousseau S, Cohen CD, Bhalodia A, Zita MD, Head RD, Blumenthal RS, Alharethi R, Damp J, Boehmer J, Alexis J, McNamara DM, Sharma G, Adamo L. Serum Proteomic Analysis of Peripartum Cardiomyopathy Reveals Distinctive Dysregulation of Inflammatory and Cholesterol Metabolism Pathways. JACC. HEART FAILURE 2023; 11:1231-1242. [PMID: 37542511 DOI: 10.1016/j.jchf.2023.05.031] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 05/26/2023] [Accepted: 05/30/2023] [Indexed: 08/07/2023]
Abstract
BACKGROUND The pathophysiology of peripartum cardiomyopathy (PPCM) and its distinctive biological features remain incompletely understood. High-throughput serum proteomic profiling, a powerful tool to gain insights into the pathophysiology of diseases at a systems biology level, has never been used to investigate PPCM relative to nonischemic cardiomyopathy. OBJECTIVES The aim of this study was to characterize the pathophysiology of PPCM through serum proteomic analysis. METHODS Aptamer-based proteomic analysis (SomaScan 7K) was performed on serum samples from women with PPCM (n = 67), women with nonischemic nonperipartum cardiomyopathy (NPCM) (n = 31), and age-matched healthy peripartum and nonperipartum women (n = 10 each). Serum samples were obtained from the IPAC (Investigation of Pregnancy-Associated Cardiomyopathy) and IMAC2 (Intervention in Myocarditis and Acute Cardiomyopathy) studies. RESULTS Principal component analysis revealed unique clustering of each patient group (P for difference <0.001). Biological pathway analyses of differentially measured proteins in PPCM relative to NPCM, before and after normalization to pertinent healthy controls, highlighted specific dysregulation of inflammatory pathways in PPCM, including the upregulation of the cholesterol metabolism-related anti-inflammatory pathway liver-X receptor/retinoid-X receptor (LXR/RXR) (P < 0.01, Z-score 1.9-2.1). Cardiac recovery by 12 months in PPCM was associated with the downregulation of pro-inflammatory pathways and the upregulation of LXR/RXR, and an additional RXR-dependent pathway involved in the regulation of inflammation and metabolism, peroxisome proliferator-activated receptor α/RXRα signaling. CONCLUSIONS Serum proteomic profiling of PPCM relative to NPCM and healthy controls indicated that PPCM is a distinct disease entity characterized by the unique dysregulation of inflammation-related pathways and cholesterol metabolism-related anti-inflammatory pathways. These findings provide insight into the pathophysiology of PPCM and point to novel potential therapeutic targets.
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Affiliation(s)
- Jana P Lovell
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Kevin Bermea
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jinsheng Yu
- Department of Genetics, McDonnell Genome Institute, Washington University, St. Louis, Missouri, USA
| | - Sylvie Rousseau
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Charles D Cohen
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Aashik Bhalodia
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Marcelle Dina Zita
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Richard D Head
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Roger S Blumenthal
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | | | - Julie Damp
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - John Boehmer
- Penn State Milton S. Hershey Medical Center, Hershey, Pennsylvania, USA
| | - Jeffrey Alexis
- Division of Cardiology, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - Dennis M McNamara
- Heart and Vascular Institute, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Garima Sharma
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, Maryland, USA. https://twitter.com/GarimaVSharmaMD
| | - Luigi Adamo
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
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Shields PG. Role of untargeted omics biomarkers of exposure and effect for tobacco research. ADDICTION NEUROSCIENCE 2023; 7:100098. [PMID: 37396411 PMCID: PMC10310069 DOI: 10.1016/j.addicn.2023.100098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Tobacco research remains a clear priority to improve individual and population health, and has recently become more complex with emerging combustible and noncombustible tobacco products. The use of omics methods in prevention and cessation studies are intended to identify new biomarkers for risk, compared risks related to other products and never use, and compliance for cessation and reinitation. to assess the relative effects of tobacco products to each other. They are important for the prediction of reinitiation of tobacco use and relapse prevention. In the research setting, both technical and clinical validation is required, which presents a number of complexities in the omics methodologies from biospecimen collection and sample preparation to data collection and analysis. When the results identify differences in omics features, networks or pathways, it is unclear if the results are toxic effects, a healthy response to a toxic exposure or neither. The use of surrogate biospecimens (e.g., urine, blood, sputum or nasal) may or may not reflect target organs such as the lung or bladder. This review describes the approaches for the use of omics in tobacco research and provides examples of prior studies, along with the strengths and limitations of the various methods. To date, there is little consistency in results, likely due to small number of studies, limitations in study size, the variability in the analytic platforms and bioinformatic pipelines, differences in biospecimen collection and/or human subject study design. Given the demonstrated value for the use of omics in clinical medicine, it is anticipated that the use in tobacco research will be similarly productive.
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Affiliation(s)
- Peter G. Shields
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, Columbus, OH
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Muse O, Patell R, Peters CG, Yang M, El-Darzi E, Schulman S, Falanga A, Marchetti M, Russo L, Zwicker JI, Flaumenhaft R. The unfolded protein response links ER stress to cancer-associated thrombosis. JCI Insight 2023; 8:e170148. [PMID: 37651191 PMCID: PMC10629814 DOI: 10.1172/jci.insight.170148] [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: 03/01/2023] [Accepted: 08/29/2023] [Indexed: 09/02/2023] Open
Abstract
Thrombosis is a common complication of advanced cancer, yet the cellular mechanisms linking malignancy to thrombosis are poorly understood. The unfolded protein response (UPR) is an ER stress response associated with advanced cancers. A proteomic evaluation of plasma from patients with gastric and non-small cell lung cancer who were monitored prospectively for venous thromboembolism demonstrated increased levels of UPR-related markers in plasma of patients who developed clots compared with those who did not. Release of procoagulant activity into supernatants of gastric, lung, and pancreatic cancer cells was enhanced by UPR induction and blocked by antagonists of the UPR receptors inositol-requiring enzyme 1α (IRE1α) and protein kinase RNA-like endoplasmic reticulum kinase (PERK). Release of extracellular vesicles bearing tissue factor (EVTFs) from pancreatic cancer cells was inhibited by siRNA-mediated knockdown of IRE1α/XBP1 or PERK pathways. Induction of UPR did not increase tissue factor (TF) synthesis, but rather stimulated localization of TF to the cell surface. UPR-induced TF delivery to EVTFs was inhibited by ADP-ribosylation factor 1 knockdown or GBF1 antagonism, verifying the role of vesicular trafficking. Our findings show that UPR activation resulted in increased vesicular trafficking leading to release of prothrombotic EVTFs, thus providing a mechanistic link between ER stress and cancer-associated thrombosis.
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Affiliation(s)
- Oluwatoyosi Muse
- Division of Hemostasis and Thrombosis, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Rushad Patell
- Division of Hemostasis and Thrombosis, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Christian G. Peters
- Division of Hemostasis and Thrombosis, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Moua Yang
- Division of Hemostasis and Thrombosis, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Emale El-Darzi
- Division of Hemostasis and Thrombosis, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Sol Schulman
- Division of Hemostasis and Thrombosis, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Anna Falanga
- Immunohematology and Transfusion Medicine, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Marina Marchetti
- Immunohematology and Transfusion Medicine, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Laura Russo
- Immunohematology and Transfusion Medicine, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Jeffrey I. Zwicker
- Hematology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Robert Flaumenhaft
- Division of Hemostasis and Thrombosis, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
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Schlosser P, Grams ME, Rhee EP. Proteomics: Progress and Promise of High-Throughput Proteomics in Chronic Kidney Disease. Mol Cell Proteomics 2023; 22:100550. [PMID: 37076045 PMCID: PMC10326701 DOI: 10.1016/j.mcpro.2023.100550] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 03/20/2023] [Accepted: 03/28/2023] [Indexed: 04/21/2023] Open
Abstract
Current proteomic tools permit the high-throughput analysis of the blood proteome in large cohorts, including those enriched for chronic kidney disease (CKD) or its risk factors. To date, these studies have identified numerous proteins associated with cross-sectional measures of kidney function, as well as with the longitudinal risk of CKD progression. Representative signals that have emerged from the literature include an association between levels of testican-2 and favorable kidney prognosis and an association between levels of TNFRSF1A and TNFRSF1B and worse kidney prognosis. For these and other associations, however, understanding whether the proteins play a causal role in kidney disease pathogenesis remains a fundamental challenge, especially given the strong impact that kidney function can have on blood protein levels. Prior to investing in dedicated animal models or randomized trials, methods that leverage the availability of genotyping in epidemiologic cohorts-including Mendelian randomization, colocalization analyses, and proteome-wide association studies-can add evidence for causal inference in CKD proteomics research. In addition, integration of large-scale blood proteome analyses with urine and tissue proteomics, as well as improved assessment of posttranslational protein modifications (e.g., carbamylation), represent important future directions. Taken together, these approaches seek to translate progress in large-scale proteomic profiling into the promise of improved diagnostic tools and therapeutic target identification in kidney disease.
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Affiliation(s)
- Pascal Schlosser
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
| | - Morgan E Grams
- Division of Precision Medicine, Department of Medicine, New York University, New York, New York, USA
| | - Eugene P Rhee
- Nephrology Division and Endocrine Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
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de Bakker M, Petersen TB, Akkerhuis KM, Harakalova M, Umans VA, Germans T, Caliskan K, Katsikis PD, van der Spek PJ, Suthahar N, de Boer RA, Rizopoulos D, Asselbergs FW, Boersma E, Kardys I. Sex-based differences in cardiovascular proteomic profiles and their associations with adverse outcomes in patients with chronic heart failure. Biol Sex Differ 2023; 14:29. [PMID: 37198662 DOI: 10.1186/s13293-023-00516-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 05/05/2023] [Indexed: 05/19/2023] Open
Abstract
BACKGROUND Studies focusing on sex differences in circulating proteins in patients with heart failure with reduced ejection fraction (HFrEF) are scarce. Insight into sex-specific cardiovascular protein profiles and their associations with the risk of adverse outcomes may contribute to a better understanding of the pathophysiological processes involved in HFrEF. Moreover, it could provide a basis for the use of circulating protein measurements for prognostication in women and men, wherein the most relevant protein measurements are applied in each of the sexes. METHODS In 382 patients with HFrEF, we performed tri-monthly blood sampling (median follow-up: 25 [13-31] months). We selected all baseline samples and two samples closest to the primary endpoint (PEP: composite of cardiovascular death, heart transplantation, left ventricular assist device implantation, and HF hospitalization) or censoring. We then applied an aptamer-based multiplex proteomic assay identifying 1105 proteins previously associated with cardiovascular disease. We used linear regression models and gene-enrichment analysis to study sex-based differences in baseline levels. We used time-dependent Cox models to study differences in the prognostic value of serially measured proteins. All models were adjusted for the MAGGIC HF mortality risk score and p-values for multiple testing. RESULTS In 104 women and 278 men (mean age 62 and 64 years, respectively) cumulative PEP incidence at 30 months was 25% and 35%, respectively. At baseline, 55 (5%) out of the 1105 proteins were significantly different between women and men. The female protein profile was most strongly associated with extracellular matrix organization, while the male profile was dominated by regulation of cell death. The association of endothelin-1 (Pinteraction < 0.001) and somatostatin (Pinteraction = 0.040) with the PEP was modified by sex, independent of clinical characteristics. Endothelin-1 was more strongly associated with the PEP in men (HR 2.62 [95%CI, 1.98, 3.46], p < 0.001) compared to women (1.14 [1.01, 1.29], p = 0.036). Somatostatin was positively associated with the PEP in men (1.23 [1.10, 1.38], p < 0.001), but inversely associated in women (0.33 [0.12, 0.93], p = 0.036). CONCLUSION Baseline cardiovascular protein levels differ between women and men. However, the predictive value of repeatedly measured circulating proteins does not seem to differ except for endothelin-1 and somatostatin.
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Affiliation(s)
- Marie de Bakker
- Department of Cardiology, Erasmus MC Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Teun B Petersen
- Department of Cardiology, Erasmus MC Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands
- Department of Biostatistics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - K Martijn Akkerhuis
- Department of Cardiology, Erasmus MC Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Magdalena Harakalova
- Department of Cardiology, Division Heart and Lungs, Circulatory Health Research Center, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
- Regenerative Medicine Center Utrecht, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Victor A Umans
- Department of Cardiology, Northwest Clinics, Alkmaar, The Netherlands
| | - Tjeerd Germans
- Department of Cardiology, Northwest Clinics, Alkmaar, The Netherlands
| | - Kadir Caliskan
- Department of Cardiology, Erasmus MC Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Peter D Katsikis
- Department of Immunology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Peter J van der Spek
- Department of Pathology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Navin Suthahar
- Department of Cardiology, Erasmus MC Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Rudolf A de Boer
- Department of Cardiology, Erasmus MC Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Dimitris Rizopoulos
- Department of Biostatistics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Folkert W Asselbergs
- Amsterdam University Medical Centers, Department of Cardiology, University of Amsterdam, Amsterdam, The Netherlands
- Health Data Research UK and Institute of Health Informatics, University College London, London, UK
| | - Eric Boersma
- Department of Cardiology, Erasmus MC Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Isabella Kardys
- Department of Cardiology, Erasmus MC Cardiovascular Institute, University Medical Center Rotterdam, Room Na-316, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands.
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Girerd N, Levy D, Duarte K, Ferreira JP, Ballantyne C, Collier T, Pizard A, Björkman J, Butler J, Clark A, Cleland JG, Delles C, Diez J, González A, Hazebroek M, Ho J, Huby AC, Hwang SJ, Latini R, Mariottoni B, Mebazaa A, Pellicori P, Sattar N, Sever P, Staessen JA, Verdonschot J, Heymans S, Rossignol P, Zannad F. Protein Biomarkers of New-Onset Heart Failure: Insights From the Heart Omics and Ageing Cohort, the Atherosclerosis Risk in Communities Study, and the Framingham Heart Study. Circ Heart Fail 2023; 16:e009694. [PMID: 37192292 DOI: 10.1161/circheartfailure.122.009694] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 03/03/2023] [Indexed: 05/18/2023]
Abstract
BACKGROUND We sought to identify protein biomarkers of new-onset heart failure (HF) in 3 independent cohorts (HOMAGE cohort [Heart Omics and Ageing], ARIC study [Atherosclerosis Risk in Communities], and FHS [Framingham Heart Study]) and assess if and to what extent they improve HF risk prediction compared to clinical risk factors alone. METHODS A nested case-control design was used with cases (incident HF) and controls (without HF) matched on age and sex within each cohort. Plasma concentrations of 276 proteins were measured at baseline in ARIC (250 cases/250 controls), FHS (191/191), and HOMAGE cohort (562/871). RESULTS In single protein analysis, after adjusting for matching variables and clinical risk factors (and correcting for multiple testing), 62 proteins were associated with incident HF in ARIC, 16 in FHS, and 116 in HOMAGE cohort. Proteins associated with incident HF in all cohorts were BNP (brain natriuretic peptide), NT-proBNP (N-terminal pro-B-type natriuretic peptide), eukaryotic translation initiation factor 4E-BP1 (4E-binding protein 1), hepatocyte growth factor (HGF), Gal-9 (galectin-9), TGF-alpha (transforming growth factor alpha), THBS2 (thrombospondin-2), and U-PAR (urokinase plasminogen activator surface receptor). The increment in C-index for incident HF based on a multiprotein biomarker approach, in addition to clinical risk factors and NT-proBNP, was 11.1% (7.5%-14.7%) in ARIC, 5.9% (2.6%-9.2%) in FHS, and 7.5% (5.4%-9.5%) in HOMAGE cohort, all P<0.001), each of which was a larger increase than that for NT-proBNP on top of clinical risk factors. Complex network analysis revealed a number of overrepresented pathways related to inflammation (eg, tumor necrosis factor and interleukin) and remodeling (eg, extracellular matrix and apoptosis). CONCLUSIONS A multiprotein biomarker approach improves prediction of incident HF when added to natriuretic peptides and clinical risk factors.
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Affiliation(s)
- Nicolas Girerd
- Université de Lorraine, Inserm, Centre d'Investigations Cliniques- Plurithématique 14-33, and Inserm U1116, CHRU, F-CRIN INI-CRCT (Cardiovascular and Renal Clinical Trialists), Nancy, France (N.G., K.D., J.P.F., A.P., A.-C.H., P.R., F.Z.)
| | - Daniel Levy
- National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA (D.L., J.H., S.-J.H)
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD (D.L., J.H., S.-J.H.)
| | - Kevin Duarte
- Université de Lorraine, Inserm, Centre d'Investigations Cliniques- Plurithématique 14-33, and Inserm U1116, CHRU, F-CRIN INI-CRCT (Cardiovascular and Renal Clinical Trialists), Nancy, France (N.G., K.D., J.P.F., A.P., A.-C.H., P.R., F.Z.)
| | - Joao Pedro Ferreira
- Université de Lorraine, Inserm, Centre d'Investigations Cliniques- Plurithématique 14-33, and Inserm U1116, CHRU, F-CRIN INI-CRCT (Cardiovascular and Renal Clinical Trialists), Nancy, France (N.G., K.D., J.P.F., A.P., A.-C.H., P.R., F.Z.)
| | | | - Timothy Collier
- London School of Hygiene and Tropical Medicine, United Kingdom (T.C.)
| | - Anne Pizard
- Université de Lorraine, Inserm, Centre d'Investigations Cliniques- Plurithématique 14-33, and Inserm U1116, CHRU, F-CRIN INI-CRCT (Cardiovascular and Renal Clinical Trialists), Nancy, France (N.G., K.D., J.P.F., A.P., A.-C.H., P.R., F.Z.)
- Inserm 1024, Institut de Biologie de l'École Normale Supérieure (IBENS), PSL University of Paris, France (A.P.)
| | | | - Javed Butler
- Department of Medicine, University of Mississippi School of Medicine, Jackson (J.B.)
| | - Andrew Clark
- Hull York Medical School, Castle Hill Hospital, Cottingham, United Kingdom (A.C.)
| | - John G Cleland
- Robertson Centre for Biostatistics and Clinical Trials, Institute of Health and Wellbeing, University of Glasgow, United Kingdom (J.G.C., P.P.)
- National Heart and Lung Institute, Royal Brompton and Harefield Hospitals, Imperial College, London, United Kingdom (J.G.C.)
| | - Christian Delles
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom (C.D.C.)
| | - Javier Diez
- Program of Cardiovascular Diseases, Centre for Applied Medical Research, University of Navarra, Pamplona, Spain (J.D.C., A.G.C.)
- CIBERCV, Carlos III Institute of Health, Madrid, Spain (J.D.C., A.G.C.)
| | - Arantxa González
- CIBERCV, Carlos III Institute of Health, Madrid, Spain (J.D.C., A.G.C.)
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Spain (J.D.C., A.G.C.)
- Departments of Nephrology, and Cardiology and Cardiac Surgery, University of Navarra Clinic, Pamplona, Spain (A.G.C.)
| | - Mark Hazebroek
- Department of Cardiology, Maastricht University Medical Centre, Center for Heart Failure Research, Cardiovascular Research Institute Maastricht (CARIM), University Hospital Maastricht, the Netherlands (M.H.C.)
| | - Jennifer Ho
- National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA (D.L., J.H., S.-J.H)
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD (D.L., J.H., S.-J.H.)
| | - Anne-Cécile Huby
- Université de Lorraine, Inserm, Centre d'Investigations Cliniques- Plurithématique 14-33, and Inserm U1116, CHRU, F-CRIN INI-CRCT (Cardiovascular and Renal Clinical Trialists), Nancy, France (N.G., K.D., J.P.F., A.P., A.-C.H., P.R., F.Z.)
| | - Shih-Jen Hwang
- National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA (D.L., J.H., S.-J.H)
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD (D.L., J.H., S.-J.H.)
| | - Roberto Latini
- IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy (R.L.)
| | | | - Alexandre Mebazaa
- UMRS 942; University Paris Diderot; APHP, University Hospitals Saint Louis Lariboisière, France (A.M.)
| | - Pierpaolo Pellicori
- Robertson Centre for Biostatistics and Clinical Trials, Institute of Health and Wellbeing, University of Glasgow, United Kingdom (J.G.C., P.P.)
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom (N.S.)
| | - Peter Sever
- International Centre for Circulatory Health, National Heart and Lung Institute, Imperial College London, United Kingdom (P.S.)
| | - Jan A Staessen
- Studies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Belgium (J.A.S.)
| | - Job Verdonschot
- Studies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Belgium (J.A.S.)
| | - Stephane Heymans
- Department of Cardiovascular Research, University of Leuven, UZ Herestraat, Belgium (S.H.)
- Netherlands Heart Institute (ICIN), Utrecht, the Netherlands (S.H.)
- Department of Clinical Genetics, Maastricht University Medical Center, the Netherlands (S.H.)
| | - Patrick Rossignol
- Université de Lorraine, Inserm, Centre d'Investigations Cliniques- Plurithématique 14-33, and Inserm U1116, CHRU, F-CRIN INI-CRCT (Cardiovascular and Renal Clinical Trialists), Nancy, France (N.G., K.D., J.P.F., A.P., A.-C.H., P.R., F.Z.)
| | - Faiez Zannad
- Université de Lorraine, Inserm, Centre d'Investigations Cliniques- Plurithématique 14-33, and Inserm U1116, CHRU, F-CRIN INI-CRCT (Cardiovascular and Renal Clinical Trialists), Nancy, France (N.G., K.D., J.P.F., A.P., A.-C.H., P.R., F.Z.)
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Sîrbe C, Badii M, Crişan TO, Bența G, Grama A, Joosten LAB, Rednic S, Pop TL. Detection of Novel Biomarkers in Pediatric Autoimmune Hepatitis by Proteomic Profiling. Int J Mol Sci 2023; 24:ijms24087479. [PMID: 37108648 PMCID: PMC10141667 DOI: 10.3390/ijms24087479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 04/14/2023] [Accepted: 04/16/2023] [Indexed: 04/29/2023] Open
Abstract
Autoimmune hepatitis (AIH) is characterized by immune-mediated hepatocyte injury resulting in the destruction of liver cells, causing inflammation, liver failure, and fibrosis. Pediatric (AIH) is an autoimmune inflammatory disease that usually requires immunosuppression for an extended period. Frequent relapses after treatment discontinuation demonstrate that current therapies do not control intrahepatic immune processes. This study describes targeted proteomic profiling data in patients with AIH and controls. A total of 92 inflammatory and 92 cardiometabolic plasma markers were assessed for (i) pediatric AIH versus controls, (ii) AIH type 1 versus type 2, (iii) AIH and AIH-autoimmune sclerosing cholangitis overlapping syndrome and (iv) correlations with circulating vitamin D levels in AIH. A total of 16 proteins showed a nominally significant differential abundance in pediatric patients with AIH compared to controls. No clustering of AIH subphenotypes based on all protein data was observed, and no significant correlation of vitamin D levels was observed for the identified proteins. The proteins that showed variable expression include CA1, CA3, GAS6, FCGR2A, 4E-BP1 and CCL19, which may serve as potential biomarkers for patients with AIH. CX3CL1, CXCL10, CCL23, CSF1 and CCL19 showed homology to one another and may be coexpressed in AIH. CXCL10 seems to be the central intermediary link for the listed proteins. These proteins were involved in relevant mechanistic pathways for liver diseases and immune processes in AIH pathogenesis. This is the first report on the proteomic profile of pediatric AIH. The identified markers could potentially lead to new diagnostic and therapeutic tools. Nevertheless, considering the complex pathogenesis of AIH, more extensive studies are warranted to replicate and validate the present study's findings.
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Affiliation(s)
- Claudia Sîrbe
- 2nd Pediatric Discipline, Department of Mother and Child, "Iuliu Hațieganu" University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
- 2nd Pediatric Clinic, Center of Expertise in Pediatric Liver Rare Disorders, Emergency Clinical Hospital for Children, 400177 Cluj-Napoca, Romania
| | - Medeea Badii
- Department of Medical Genetics, "Iuliu Hațieganu" University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
- Department of Internal Medicine, Radboud University Medical Centre, 6525 XZ Nijmegen, The Netherlands
| | - Tania O Crişan
- Department of Medical Genetics, "Iuliu Hațieganu" University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
- Department of Internal Medicine, Radboud University Medical Centre, 6525 XZ Nijmegen, The Netherlands
| | - Gabriel Bența
- 2nd Pediatric Discipline, Department of Mother and Child, "Iuliu Hațieganu" University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
- 2nd Pediatric Clinic, Center of Expertise in Pediatric Liver Rare Disorders, Emergency Clinical Hospital for Children, 400177 Cluj-Napoca, Romania
| | - Alina Grama
- 2nd Pediatric Discipline, Department of Mother and Child, "Iuliu Hațieganu" University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
- 2nd Pediatric Clinic, Center of Expertise in Pediatric Liver Rare Disorders, Emergency Clinical Hospital for Children, 400177 Cluj-Napoca, Romania
| | - Leo A B Joosten
- Department of Internal Medicine, Radboud University Medical Centre, 6525 XZ Nijmegen, The Netherlands
| | - Simona Rednic
- Rheumatology Department, Emergency County Hospital Cluj, 400347 Cluj-Napoca, Romania
- Rheumatology Discipline, "Iuliu Hațieganu" University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
| | - Tudor Lucian Pop
- 2nd Pediatric Discipline, Department of Mother and Child, "Iuliu Hațieganu" University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
- 2nd Pediatric Clinic, Center of Expertise in Pediatric Liver Rare Disorders, Emergency Clinical Hospital for Children, 400177 Cluj-Napoca, Romania
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24
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Gebreyesus ST, Muneer G, Huang CC, Siyal AA, Anand M, Chen YJ, Tu HL. Recent advances in microfluidics for single-cell functional proteomics. LAB ON A CHIP 2023; 23:1726-1751. [PMID: 36811978 DOI: 10.1039/d2lc01096h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Single-cell proteomics (SCP) reveals phenotypic heterogeneity by profiling individual cells, their biological states and functional outcomes upon signaling activation that can hardly be probed via other omics characterizations. This has become appealing to researchers as it enables an overall more holistic view of biological details underlying cellular processes, disease onset and progression, as well as facilitates unique biomarker identification from individual cells. Microfluidic-based strategies have become methods of choice for single-cell analysis because they allow facile assay integrations, such as cell sorting, manipulation, and content analysis. Notably, they have been serving as an enabling technology to improve the sensitivity, robustness, and reproducibility of recently developed SCP methods. Critical roles of microfluidics technologies are expected to further expand rapidly in advancing the next phase of SCP analysis to reveal more biological and clinical insights. In this review, we will capture the excitement of the recent achievements of microfluidics methods for both targeted and global SCP, including efforts to enhance the proteomic coverage, minimize sample loss, and increase multiplexity and throughput. Furthermore, we will discuss the advantages, challenges, applications, and future prospects of SCP.
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Affiliation(s)
- Sofani Tafesse Gebreyesus
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Nano Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
| | - Gul Muneer
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | | | - Asad Ali Siyal
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
| | - Mihir Anand
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan
| | - Hsiung-Lin Tu
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Nano Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan
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25
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Using Artificial Intelligence to Better Predict and Develop Biomarkers. Clin Lab Med 2023; 43:99-114. [PMID: 36764811 DOI: 10.1016/j.cll.2022.09.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
Advancements in technology have improved biomarker discovery in the field of heart failure (HF). What was once a slow and laborious process has gained efficiency through use of high-throughput omics platforms to phenotype HF at the level of genes, transcripts, proteins, and metabolites. Furthermore, improvements in artificial intelligence (AI) have made the interpretation of large omics data sets easier and improved analysis. Use of omics and AI in biomarker discovery can aid clinicians by identifying markers of risk for developing HF, monitoring care, determining prognosis, and developing druggable targets. Combined, AI has the power to improve HF patient care.
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26
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Extracellular Vesicle-Associated TWEAK Contributes to Vascular Inflammation and Remodeling During Acute Cellular Rejection. JACC Basic Transl Sci 2023. [DOI: 10.1016/j.jacbts.2022.09.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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27
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Shimada YJ, Raita Y, Liang LW, Maurer MS, Hasegawa K, Fifer MA, Reilly MP. Prediction of Major Adverse Cardiovascular Events in Patients With Hypertrophic Cardiomyopathy Using Proteomics Profiling. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2022; 15:e003546. [PMID: 36252118 PMCID: PMC9771902 DOI: 10.1161/circgen.121.003546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 06/24/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Hypertrophic cardiomyopathy often causes major adverse cardiovascular events (MACE), for example, arrhythmias, stroke, heart failure, and sudden cardiac death. Currently, there are no models available to predict MACE. Furthermore, it remains unclear which signaling pathways mediate MACE. Therefore, we aimed to prospectively determine protein biomarkers that predict MACE in hypertrophic cardiomyopathy and to identify signaling pathways differentially regulated in patients who subsequently develop MACE. METHODS In this multi-centre prospective cohort study of patients with hypertrophic cardiomyopathy, we conducted plasma proteomics profiling of 4979 proteins upon enrollment. We developed a proteomics-based model to predict MACE using data from one institution (training set). We tested the predictive ability in independent samples from the other institution (test set) and performed time-to-event analysis. Additionally, we executed pathway analysis of predictive proteins using a false discovery rate threshold of <0.001. RESULTS The study included 245 patients (n=174 in the training set and n=71 in the test set). Using the proteomics-based model to predict MACE derived from the training set, the area under the receiver-operating-characteristic curve was 0.81 (95% CI, 0.68-0.93) in the test set. In the test set, the high-risk group determined by the proteomics-based predictive model had a significantly higher rate of developing MACE (hazard ratio, 13.6 [95% CI, 1.7-107]; P=0.01). The Ras-MAPK (mitogen-activated protein kinase) pathway was upregulated in patients who subsequently developed MACE (false discovery rate<1.0×10-7). Pathways involved in inflammation and fibrosis-for example, the TGF (transforming growth factor)-β pathway-were also upregulated. CONCLUSIONS This study serves as the first to demonstrate the ability of proteomics profiling to predict MACE in hypertrophic cardiomyopathy, exhibiting both novel (eg, Ras-MAPK) and known (eg, TGF-β) pathways differentially regulated in patients who subsequently experience MACE.
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Affiliation(s)
- Yuichi J. Shimada
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Yoshihiko Raita
- Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Lusha W. Liang
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Mathew S. Maurer
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Kohei Hasegawa
- Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Michael A. Fifer
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Muredach P. Reilly
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY
- Irving Institute for Clinical and Translational Research, Columbia University Irving Medical Center, New York, NY
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28
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Chen X, Ma Y, Xie Y, Pu J. Aptamer-based applications for cardiovascular disease. Front Bioeng Biotechnol 2022; 10:1002285. [PMID: 36312558 PMCID: PMC9606242 DOI: 10.3389/fbioe.2022.1002285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
Cardiovascular disease (especially atherosclerosis) is a major cause of death worldwide, and novel diagnostic tools and treatments for this disease are urgently needed. Aptamers are single-stranded oligonucleotides that specifically recognize and bind to the targets by forming unique structures in vivo, enabling them to rival antibodies in cardiac applications. Chemically synthesized aptamers can be readily modified in a site-specific way, so they have been engineered in the diagnosis of cardiac diseases and anti-thrombosis therapeutics. Von Willebrand Factor plays a unique role in the formation of thrombus, and as an aptamer targeting molecule, has shown initial success in antithrombotic treatment. A combination of von Willebrand Factor and nucleic acid aptamers can effectively inhibit the progression of blood clots, presenting a positive diagnosis and therapeutic effect, as well as laying a novel theory and strategy to improve biocompatibility paclitaxel drug balloon or implanted stent in the future. This review summarizes aptamer-based applications in cardiovascular disease, including biomarker discovery and future management strategy. Although relevant applications are relatively new, the significant advancements achieved have demonstrated that aptamers can be promising agents to realize the integration of diagnosis and therapy in cardiac research.
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Affiliation(s)
| | | | | | - Jun Pu
- *Correspondence: Yuquan Xie, ; Jun Pu,
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29
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Attogram-level light-induced antigen-antibody binding confined in microflow. Commun Biol 2022; 5:1053. [PMID: 36203087 PMCID: PMC9537419 DOI: 10.1038/s42003-022-03946-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 09/02/2022] [Indexed: 11/28/2022] Open
Abstract
The analysis of trace amounts of proteins based on immunoassays and other methods is essential for the early diagnosis of various diseases such as cancer, dementia, and microbial infections. Here, we propose a light-induced acceleration of antigen-antibody reaction of attogram-level proteins at the solid-liquid interface by tuning the laser irradiation area comparable to the microscale confinement geometry for enhancing the collisional probability of target molecules and probe particles with optical force and fluidic pressure. This principle was applied to achieve a 102-fold higher sensitivity and ultrafast specific detection in comparison with conventional protein detection methods (a few hours) by omitting any pretreatment procedures; 47–750 ag of target proteins were detected in 300 nL of sample after 3 minutes of laser irradiation. Our findings can promote the development of proteomics and innovative platforms for high-throughput bio-analyses under the control of a variety of biochemical reactions. Attogram-level of proteins can be detected using light-induced acceleration of antigen-antibody interactions in a microchannel platform.
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30
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Appiah D, Schreiner PJ, Pankow JS, Brock G, Tang W, Norby FL, Michos ED, Ballantyne CM, Folsom AR. Long-term changes in plasma proteomic profiles in premenopausal and postmenopausal Black and White women: the Atherosclerosis Risk in Communities study. Menopause 2022; 29:1150-1160. [PMID: 35969495 PMCID: PMC9509415 DOI: 10.1097/gme.0000000000002031] [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] [Indexed: 11/25/2022]
Abstract
OBJECTIVE The activity, localization, and turnover of proteins within cells and plasma may contribute to physiologic changes during menopause and may influence disease occurrence. We examined cross-sectional differences and long-term changes in plasma proteins between premenopausal and naturally postmenopausal women. METHODS We used data from 4,508 (19% Black) women enrolled in the Atherosclerosis Risk in Communities study. SOMAscan multiplexed aptamer technology was used to measure 4,697 plasma proteins. Linear regression models were used to compare differences in proteins at baseline (1993-1995) and 18-year change in proteins from baseline to 2011-2013. RESULTS At baseline, 472 women reported being premenopausal and 4,036 women reported being postmenopausal, with average ages of 52.3 and 61.4 years, respectively. A greater proportion of postmenopausal women had diabetes (15 vs 9%), used hypertension (38 vs 27%) and lipid-lowering medications (10 vs 3%), and had elevated total cholesterol and waist girth. In multivariable adjusted models, 38 proteins differed significantly between premenopausal and postmenopausal women at baseline, with 29 of the proteins also showing significantly different changes between groups over the 18-year follow-up as the premenopausal women also reached menopause. These proteins were associated with various molecular/cellular functions (cellular development, growth, proliferation and maintenance), physiological system development (skeletal and muscular system development, and cardiovascular system development and function), and diseases/disorders (hematological and metabolic diseases and developmental disorders). CONCLUSIONS We observed significantly different changes between premenopausal and postmenopausal women in several plasma proteins that reflect many biological processes. These processes may help to understand disease development during the postmenopausal period.
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Affiliation(s)
- Duke Appiah
- Department of Public Health, Texas Tech University Health Sciences Center, Lubbock TX
| | - Pamela J. Schreiner
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN
| | - James S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN
| | - Guy Brock
- Department of Biostatistics, The Ohio State University, Columbus OH
| | - Weihong Tang
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN
| | - Faye L. Norby
- Department of Cardiology, Cedars-Sinai Smidt Heart Institute, Los Angeles, CA
| | - Erin D. Michos
- Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MA
| | | | - Aaron R. Folsom
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN
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31
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Yu H, Wang S, Huang J, Fu Y, Wagner M, Weil T, Zhong F, Zhao W, Wu Y. Light-Controlled Traceless Protein Labeling via Decaging Thio- o-naphthoquinone Methide Chemistry. Org Lett 2022; 24:6816-6821. [PMID: 36099167 DOI: 10.1021/acs.orglett.2c02742] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We report the molecular design of a novel multifunctional reagent and its application for light-controlled selective protein labeling. This molecule integrates functions of protein-ligand recognition, bioconjugation, ligand cleavage, and photoactivation by merging the photochemistries of 2-nitrophenylpropyloxycarbonyl and 3-hydroxymethyl-2-naphthol with an affinity ligand and fluorescein. Highly electrophilic o-naphthoquinone methide was photochemically released and underwent proximity-driven selective labeling with the protein of interest (e.g., carbonic anhydrases), which retains its native function after labeling.
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Affiliation(s)
- Huaibin Yu
- Key Laboratory of Material Chemistry for Energy Conversion and Storage, Ministry of Education, Hubei Engineering Research Center for Biomaterials and Medical Protective Materials, Hubei Key Laboratory of Bioinorganic Chemistry & Materia Medica, School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology (HUST), 1037 Luoyu Road, Wuhan 430074, China
| | - Shuangshuang Wang
- Key Laboratory of Material Chemistry for Energy Conversion and Storage, Ministry of Education, Hubei Engineering Research Center for Biomaterials and Medical Protective Materials, Hubei Key Laboratory of Bioinorganic Chemistry & Materia Medica, School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology (HUST), 1037 Luoyu Road, Wuhan 430074, China
| | - Jianjian Huang
- Key Laboratory of Material Chemistry for Energy Conversion and Storage, Ministry of Education, Hubei Engineering Research Center for Biomaterials and Medical Protective Materials, Hubei Key Laboratory of Bioinorganic Chemistry & Materia Medica, School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology (HUST), 1037 Luoyu Road, Wuhan 430074, China
| | - Yu Fu
- Key Laboratory of Material Chemistry for Energy Conversion and Storage, Ministry of Education, Hubei Engineering Research Center for Biomaterials and Medical Protective Materials, Hubei Key Laboratory of Bioinorganic Chemistry & Materia Medica, School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology (HUST), 1037 Luoyu Road, Wuhan 430074, China
- College of Pharmacy, Shenzhen Technology University, Shenzhen 518118, China
| | - Manfred Wagner
- Max Planck Institute for Polymer Research, Ackermannweg 10, 55128 Mainz, Germany
| | - Tanja Weil
- Max Planck Institute for Polymer Research, Ackermannweg 10, 55128 Mainz, Germany
| | - Fangrui Zhong
- Key Laboratory of Material Chemistry for Energy Conversion and Storage, Ministry of Education, Hubei Engineering Research Center for Biomaterials and Medical Protective Materials, Hubei Key Laboratory of Bioinorganic Chemistry & Materia Medica, School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology (HUST), 1037 Luoyu Road, Wuhan 430074, China
| | - Weining Zhao
- College of Pharmacy, Shenzhen Technology University, Shenzhen 518118, China
| | - Yuzhou Wu
- Key Laboratory of Material Chemistry for Energy Conversion and Storage, Ministry of Education, Hubei Engineering Research Center for Biomaterials and Medical Protective Materials, Hubei Key Laboratory of Bioinorganic Chemistry & Materia Medica, School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology (HUST), 1037 Luoyu Road, Wuhan 430074, China
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32
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Leukotriene A4 Hydrolase and Hepatocyte Growth Factor Are Risk Factors of Sudden Cardiac Death Due to First-Ever Myocardial Infarction. Int J Mol Sci 2022; 23:ijms231810251. [PMID: 36142157 PMCID: PMC9499415 DOI: 10.3390/ijms231810251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 09/03/2022] [Indexed: 11/16/2022] Open
Abstract
Patients at a high risk for sudden cardiac death (SCD) without previous history of cardiovascular disease remain a challenge to identify. Atherosclerosis and prothrombotic states involve inflammation and non-cardiac tissue damage that may play active roles in SCD development. Therefore, we hypothesized that circulating proteins implicated in inflammation and tissue damage are linked to the future risk of SCD. We conducted a prospective nested case–control study of SCD cases with verified myocardial infarction (N = 224) and matched controls without myocardial infarction (N = 224), aged 60 ± 10 years time and median time to event was 8 years. Protein concentrations (N = 122) were measured using a proximity extension immunoassay. The analyses revealed 14 proteins significantly associated with an increased risk of SCD, from which two remained significant after adjusting for smoking status, systolic blood pressure, BMI, cholesterol, and glucose levels. We identified leukotriene A4 hydrolase (LTA4H, odds ratio 1.80, corrected confidence interval (CIcorr) 1.02–3.17) and hepatocyte growth factor (HGF; odds ratio 1.81, CIcorr 1.06–3.11) as independent risk markers of SCD. Elevated LTA4H may reflect increased systemic and pulmonary neutrophilic inflammatory processes that can contribute to atherosclerotic plaque instability. Increased HGF levels are linked to obesity-related metabolic disturbances that are more prevalent in SCD cases than the controls.
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33
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Chavez‐Pineda OG, Rodriguez‐Moncayo R, Cedillo‐Alcantar DF, Guevara‐Pantoja PE, Amador‐Hernandez JU, Garcia‐Cordero JL. Microfluidic systems for the analysis of blood‐derived molecular biomarkers. Electrophoresis 2022; 43:1667-1700. [DOI: 10.1002/elps.202200067] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 06/18/2022] [Accepted: 06/22/2022] [Indexed: 12/19/2022]
Affiliation(s)
- Oriana G. Chavez‐Pineda
- Laboratory of Microtechnologies Applied to Biomedicine (LMAB) Centro de Investigación y de Estudios Avanzados (Cinvestav) Monterrey Nuevo León Mexico
| | - Roberto Rodriguez‐Moncayo
- Laboratory of Microtechnologies Applied to Biomedicine (LMAB) Centro de Investigación y de Estudios Avanzados (Cinvestav) Monterrey Nuevo León Mexico
| | - Diana F. Cedillo‐Alcantar
- Laboratory of Microtechnologies Applied to Biomedicine (LMAB) Centro de Investigación y de Estudios Avanzados (Cinvestav) Monterrey Nuevo León Mexico
| | - Pablo E. Guevara‐Pantoja
- Laboratory of Microtechnologies Applied to Biomedicine (LMAB) Centro de Investigación y de Estudios Avanzados (Cinvestav) Monterrey Nuevo León Mexico
| | - Josue U. Amador‐Hernandez
- Laboratory of Microtechnologies Applied to Biomedicine (LMAB) Centro de Investigación y de Estudios Avanzados (Cinvestav) Monterrey Nuevo León Mexico
| | - Jose L. Garcia‐Cordero
- Laboratory of Microtechnologies Applied to Biomedicine (LMAB) Centro de Investigación y de Estudios Avanzados (Cinvestav) Monterrey Nuevo León Mexico
- Roche Institute for Translational Bioengineering (ITB) Roche Pharma Research and Early Development, Roche Innovation Center Basel Basel Switzerland
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Katz DH, Robbins JM, Deng S, Tahir UA, Bick AG, Pampana A, Yu Z, Ngo D, Benson MD, Chen ZZ, Cruz DE, Shen D, Gao Y, Bouchard C, Sarzynski MA, Correa A, Natarajan P, Wilson JG, Gerszten RE. Proteomic profiling platforms head to head: Leveraging genetics and clinical traits to compare aptamer- and antibody-based methods. SCIENCE ADVANCES 2022; 8:eabm5164. [PMID: 35984888 PMCID: PMC9390994 DOI: 10.1126/sciadv.abm5164] [Citation(s) in RCA: 60] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Accepted: 07/07/2022] [Indexed: 05/10/2023]
Abstract
High-throughput proteomic profiling using antibody or aptamer-based affinity reagents is used increasingly in human studies. However, direct analyses to address the relative strengths and weaknesses of these platforms are lacking. We assessed findings from the SomaScan1.3K (N = 1301 reagents), the SomaScan5K platform (N = 4979 reagents), and the Olink Explore (N = 1472 reagents) profiling techniques in 568 adults from the Jackson Heart Study and 219 participants in the HERITAGE Family Study across four performance domains: precision, accuracy, analytic breadth, and phenotypic associations leveraging detailed clinical phenotyping and genetic data. Across these studies, we show evidence supporting more reliable protein target specificity and a higher number of phenotypic associations for the Olink platform, while the Soma platforms benefit from greater measurement precision and analytic breadth across the proteome.
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Affiliation(s)
- Daniel H. Katz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Jeremy M. Robbins
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Shuliang Deng
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Usman A. Tahir
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | - Akhil Pampana
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Zhi Yu
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Debby Ngo
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Mark D. Benson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Zsu-Zsu Chen
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Daniel E. Cruz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Dongxiao Shen
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Yan Gao
- University of Mississippi Medical Center, Jackson, MS, USA
| | - Claude Bouchard
- Human Genomic Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA
| | - Mark A. Sarzynski
- Department of Exercise Science, University of South Carolina, Columbia, SC, USA
| | - Adolfo Correa
- University of Mississippi Medical Center, Jackson, MS, USA
| | - Pradeep Natarajan
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - James G. Wilson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Robert E. Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
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35
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Meng H, Ruan J, Yan Z, Chen Y, Liu J, Li X, Meng F. New Progress in Early Diagnosis of Atherosclerosis. Int J Mol Sci 2022; 23:ijms23168939. [PMID: 36012202 PMCID: PMC9409135 DOI: 10.3390/ijms23168939] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 07/30/2022] [Accepted: 08/06/2022] [Indexed: 11/18/2022] Open
Abstract
Coronary atherosclerosis is a potentially chronic circulatory condition that endangers human health. The biological cause underpinning cardiovascular disease is coronary atherosclerosis, and acute cardiovascular events can develop due to thrombosis, platelet aggregation, and unstable atherosclerotic plaque rupture. Coronary atherosclerosis is progressive, and three specific changes appear, with fat spots and stripes, atherosclerosis and thin-walled fiber atherosclerosis, and then complex changes in arteries. The progression and severity of cardiovascular disease are correlated with various levels of calcium accumulation in the coronary artery. The therapy and diagnosis of coronary atherosclerosis benefit from the initial assessment of the size and degree of calcification. This article will discuss the new progress in the early diagnosis of coronary atherosclerosis in terms of three aspects: imaging, gene and protein markers, and trace elements. This study intends to present the latest methods for diagnosing patients with early atherosclerosis through a literature review.
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Affiliation(s)
- Heyu Meng
- Jilin Provincial Precision Medicine Key Laboratory for Cardiovascular Genetic Diagnosis, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
- Jilin Provincial Engineering Laboratory for Endothelial Function and Genetic Diagnosis of Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
- Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
| | - Jianjun Ruan
- Jilin Provincial Precision Medicine Key Laboratory for Cardiovascular Genetic Diagnosis, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
- Jilin Provincial Engineering Laboratory for Endothelial Function and Genetic Diagnosis of Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
- Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
| | - Zhaohan Yan
- Jilin Provincial Precision Medicine Key Laboratory for Cardiovascular Genetic Diagnosis, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
- Jilin Provincial Engineering Laboratory for Endothelial Function and Genetic Diagnosis of Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
- Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
| | - Yanqiu Chen
- Jilin Provincial Precision Medicine Key Laboratory for Cardiovascular Genetic Diagnosis, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
- Jilin Provincial Engineering Laboratory for Endothelial Function and Genetic Diagnosis of Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
- Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
| | - Jinsha Liu
- Jilin Provincial Precision Medicine Key Laboratory for Cardiovascular Genetic Diagnosis, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
- Jilin Provincial Engineering Laboratory for Endothelial Function and Genetic Diagnosis of Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
- Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
| | - Xiangdong Li
- Jilin Provincial Precision Medicine Key Laboratory for Cardiovascular Genetic Diagnosis, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
- Jilin Provincial Engineering Laboratory for Endothelial Function and Genetic Diagnosis of Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
- Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
| | - Fanbo Meng
- Jilin Provincial Precision Medicine Key Laboratory for Cardiovascular Genetic Diagnosis, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
- Jilin Provincial Engineering Laboratory for Endothelial Function and Genetic Diagnosis of Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
- Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute, Jilin University, Changchun 130033, China
- Correspondence: ; Tel.: +86-15948346855
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Morfino P, Aimo A, Castiglione V, Vergaro G, Emdin M, Clerico A. Biomarkers of HFpEF: Natriuretic Peptides, High-Sensitivity Troponins and Beyond. J Cardiovasc Dev Dis 2022; 9:jcdd9080256. [PMID: 36005420 PMCID: PMC9409788 DOI: 10.3390/jcdd9080256] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/02/2022] [Accepted: 08/04/2022] [Indexed: 11/28/2022] Open
Abstract
Heart failure (HF) is a significant cause of morbidity and mortality worldwide. HF with preserved ejection fraction (HFpEF) is a complex syndrome, often participated by several cardiac and extracardiac conditions, including chronic kidney disease, pulmonary disease, anaemia and advanced age. Circulating biomarkers reflecting pathophysiological pathways involved in HFpEF development and progression may assist clinicians in early diagnosis and management of this condition. Natriuretic peptides (NPs) are cardioprotective hormones released by cardiomyocytes in response to pressure or volume overload and in response to activation of neuro-endocrine-immune system. The relevance of B-type NP (BNP) and N-terminal pro-B-type NP (NT-proBNP) for diagnosis and risk stratification has been extensively demonstrated, and these biomarkers are emerging tools for population screening and as guides to the start of treatment in subclinical HF. On the contrary, conflicting evidence exists on the value of NPs to guide HF therapy. Among the other biomarkers, high-sensitivity troponins and soluble suppression of tumorigenesis-2 are the most promising biomarkers for risk stratification, predicting outcome independently from NPs. In this review, some novel biomarkers are being tested in such clinical scenario, more tightly linked to specific pathophysiological processes of cardiac damage.
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Affiliation(s)
- Paolo Morfino
- Interdisciplinary Center of Health Sciences, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
| | - Alberto Aimo
- Interdisciplinary Center of Health Sciences, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
- Cardiology Division, Fondazione Toscana Gabriele Monasterio, 56127 Pisa, Italy
| | - Vincenzo Castiglione
- Interdisciplinary Center of Health Sciences, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
- Cardiology Division, Fondazione Toscana Gabriele Monasterio, 56127 Pisa, Italy
| | - Giuseppe Vergaro
- Interdisciplinary Center of Health Sciences, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
- Cardiology Division, Fondazione Toscana Gabriele Monasterio, 56127 Pisa, Italy
| | - Michele Emdin
- Interdisciplinary Center of Health Sciences, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
- Cardiology Division, Fondazione Toscana Gabriele Monasterio, 56127 Pisa, Italy
| | - Aldo Clerico
- Interdisciplinary Center of Health Sciences, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
- Cardiology Division, Fondazione Toscana Gabriele Monasterio, 56127 Pisa, Italy
- Correspondence:
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37
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Rhee EP. Proteomic discovery in diabetic kidney disease-to what end? Kidney Int 2022; 102:236-238. [PMID: 35870813 DOI: 10.1016/j.kint.2022.05.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 05/05/2022] [Accepted: 05/11/2022] [Indexed: 11/25/2022]
Abstract
Emerging approaches that enable high-throughput analysis of the plasma proteome have been increasingly deployed in nephrology research. Kobayashi et al. provide a valuable addition to this literature, describing an untargeted proteomic analysis of diabetic kidney disease progression to end-stage kidney disease. This commentary places the study's findings in the context of the broader literature and outlines potential avenues toward biological insight and clinical utility.
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Affiliation(s)
- Eugene P Rhee
- Nephrology Division and Endocrine Unit, Massachusetts General Hospital, Boston, Massachusetts, USA.
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38
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Dar MA, Arafah A, Bhat KA, Khan A, Khan MS, Ali A, Ahmad SM, Rashid SM, Rehman MU. Multiomics technologies: role in disease biomarker discoveries and therapeutics. Brief Funct Genomics 2022; 22:76-96. [PMID: 35809340 DOI: 10.1093/bfgp/elac017] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 05/21/2022] [Accepted: 06/14/2022] [Indexed: 11/13/2022] Open
Abstract
Medical research has been revolutionized after the publication of the full human genome. This was the major landmark that paved the way for understanding the biological functions of different macro and micro molecules. With the advent of different high-throughput technologies, biomedical research was further revolutionized. These technologies constitute genomics, transcriptomics, proteomics, metabolomics, etc. Collectively, these high-throughputs are referred to as multi-omics technologies. In the biomedical field, these omics technologies act as efficient and effective tools for disease diagnosis, management, monitoring, treatment and discovery of certain novel disease biomarkers. Genotyping arrays and other transcriptomic studies have helped us to elucidate the gene expression patterns in different biological states, i.e. healthy and diseased states. Further omics technologies such as proteomics and metabolomics have an important role in predicting the role of different biological molecules in an organism. It is because of these high throughput omics technologies that we have been able to fully understand the role of different genes, proteins, metabolites and biological pathways in a diseased condition. To understand a complex biological process, it is important to apply an integrative approach that analyses the multi-omics data in order to highlight the possible interrelationships of the involved biomolecules and their functions. Furthermore, these omics technologies offer an important opportunity to understand the information that underlies disease. In the current review, we will discuss the importance of omics technologies as promising tools to understand the role of different biomolecules in diseases such as cancer, cardiovascular diseases, neurodegenerative diseases and diabetes. SUMMARY POINTS
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Haslam DE, Li J, Dillon ST, Gu X, Cao Y, Zeleznik OA, Sasamoto N, Zhang X, Eliassen AH, Liang L, Stampfer MJ, Mora S, Chen ZZ, Terry KL, Gerszten RE, Hu FB, Chan AT, Libermann TA, Bhupathiraju SN. Stability and reproducibility of proteomic profiles in epidemiological studies: comparing the Olink and SOMAscan platforms. Proteomics 2022; 22:e2100170. [PMID: 35598103 PMCID: PMC9923770 DOI: 10.1002/pmic.202100170] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 05/02/2022] [Accepted: 05/03/2022] [Indexed: 01/14/2023]
Abstract
Limited data exist on the performance of high-throughput proteomics profiling in epidemiological settings, including the impact of specimen collection and within-person variability over time. Thus, the Olink (972 proteins) and SOMAscan7Kv4.1 (7322 proteoforms of 6596 proteins) assays were utilized to measure protein concentrations in archived plasma samples from the Nurses' Health Studies and Health Professionals Follow-Up Study. Spearman's correlation coefficients (r) and intraclass correlation coefficients (ICCs) were used to assess agreement between (1) 42 triplicate samples processed immediately, 24-h or 48-h after blood collection from 14 participants; and (2) 80 plasma samples from 40 participants collected 1-year apart. When comparing samples processed immediately, 24-h, and 48-h later, 55% of assays had an ICC/r ≥ 0.75 and 87% had an ICC/r ≥ 0.40 in Olink compared to 44% with an ICC/r ≥ 0.75 and 72% with an ICC/r ≥ 0.40 in SOMAscan7K. For both platforms, >90% of the assays were stable (ICC/r ≥ 0.40) in samples collected 1-year apart. Among 817 proteins measured with both platforms, Spearman's correlations were high (r > 0.75) for 14.7% and poor (r < 0.40) for 44.8% of proteins. High-throughput proteomics profiling demonstrated reproducibility in archived plasma samples and stability after delayed processing in epidemiological studies, yet correlations between proteins measured with the Olink and SOMAscan7K platforms were highly variable.
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Affiliation(s)
- Danielle E. Haslam
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA,Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Jun Li
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA,Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Simon T. Dillon
- Genomics, Proteomics, Bioinformatics and Systems Biology Center, Department of Medicine, Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Xuesong Gu
- Genomics, Proteomics, Bioinformatics and Systems Biology Center, Department of Medicine, Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Yin Cao
- Division of Public Health Sciences, Department of Surgery, Washington University in St. Louis, St. Louis, Missouri, USA,Alvin J. Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, USA,Division of Gastroenterology, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Oana A. Zeleznik
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Naoko Sasamoto
- Department of Obstetrics and Gynecology, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Xuehong Zhang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA,Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
| | - A. Heather Eliassen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA,Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA,Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Liming Liang
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA,Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Meir J. Stampfer
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA,Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA,Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Samia Mora
- Division of Preventive Medicine and Cardiovascular Division of Medicine and Center for Lipid Metabolomics, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Zsu-Zsu Chen
- Department of Internal Medicine, Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Kathryn L. Terry
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA,Department of Obstetrics and Gynecology, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Robert E. Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA,Broad Institute of MIT and Harvard Program in Metabolism, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Frank B. Hu
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA,Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA,Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Andrew T. Chan
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA,Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA,Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Towia A. Libermann
- Genomics, Proteomics, Bioinformatics and Systems Biology Center, Department of Medicine, Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Shilpa N. Bhupathiraju
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA,Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
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Austin TR, McHugh CP, Brody JA, Bis JC, Sitlani CM, Bartz TM, Biggs ML, Bansal N, Buzkova P, Carr SA, deFilippi CR, Elkind MSV, Fink HA, Floyd JS, Fohner AE, Gerszten RE, Heckbert SR, Katz DH, Kizer JR, Lemaitre RN, Longstreth WT, McKnight B, Mei H, Mukamal KJ, Newman AB, Ngo D, Odden MC, Vasan RS, Shojaie A, Simon N, Smith GD, Davies NM, Siscovick DS, Sotoodehnia N, Tracy RP, Wiggins KL, Zheng J, Psaty BM. Proteomics and Population Biology in the Cardiovascular Health Study (CHS): design of a study with mentored access and active data sharing. Eur J Epidemiol 2022; 37:755-765. [PMID: 35790642 PMCID: PMC9255954 DOI: 10.1007/s10654-022-00888-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 06/03/2022] [Indexed: 11/08/2022]
Abstract
BACKGROUND In the last decade, genomic studies have identified and replicated thousands of genetic associations with measures of health and disease and contributed to the understanding of the etiology of a variety of health conditions. Proteins are key biomarkers in clinical medicine and often drug-therapy targets. Like genomics, proteomics can advance our understanding of biology. METHODS AND RESULTS In the setting of the Cardiovascular Health Study (CHS), a cohort study of older adults, an aptamer-based method that has high sensitivity for low-abundance proteins was used to assay 4979 proteins in frozen, stored plasma from 3188 participants (61% women, mean age 74 years). CHS provides active support, including central analysis, for seven phenotype-specific working groups (WGs). Each CHS WG is led by one or two senior investigators and includes 10 to 20 early or mid-career scientists. In this setting of mentored access, the proteomic data and analytic methods are widely shared with the WGs and investigators so that they may evaluate associations between baseline levels of circulating proteins and the incidence of a variety of health outcomes in prospective cohort analyses. We describe the design of CHS, the CHS Proteomics Study, characteristics of participants, quality control measures, and structural characteristics of the data provided to CHS WGs. We additionally highlight plans for validation and replication of novel proteomic associations. CONCLUSION The CHS Proteomics Study offers an opportunity for collaborative data sharing to improve our understanding of the etiology of a variety of health conditions in older adults.
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Affiliation(s)
- Thomas R Austin
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA. .,Department of Epidemiology, University of Washington, Seattle, WA, USA.
| | | | - Jennifer A Brody
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Department of Medicine, University of Washington, Seattle, WA, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Department of Medicine, University of Washington, Seattle, WA, USA
| | - Colleen M Sitlani
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Department of Medicine, University of Washington, Seattle, WA, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Department of Medicine, University of Washington, Seattle, WA, USA.,Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Mary L Biggs
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Nisha Bansal
- Division of Nephrology, University of Washington, Seattle, WA, USA
| | - Petra Buzkova
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | | | | | | | - Howard A Fink
- Geriatric Research Education & Clinical Center, Minneapolis VA Healthcare System, Minneapolis, MN, USA
| | - James S Floyd
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Department of Epidemiology, University of Washington, Seattle, WA, USA.,Department of Medicine, University of Washington, Seattle, WA, USA
| | - Alison E Fohner
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Department of Epidemiology, University of Washington, Seattle, WA, USA.,Institute of Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Susan R Heckbert
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Daniel H Katz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Jorge R Kizer
- Cardiology Section, San Francisco VA Health Care System, San Francisco, CA, USA.,Department of Biostatistics, University of California San Francisco, San Francisco, CA, USA.,Department of Epidemology, University of California San Francisco, San Francisco, CA, USA.,Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Rozenn N Lemaitre
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Department of Medicine, University of Washington, Seattle, WA, USA
| | - W T Longstreth
- Department of Epidemiology, University of Washington, Seattle, WA, USA.,Department of Neurology, University of Washington, Seattle, WA, USA
| | - Barbara McKnight
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Hao Mei
- Department of Data Science, University of Mississippi Medical Center, Jackson, MS, USA
| | | | - Anne B Newman
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Debby Ngo
- Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Michelle C Odden
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA
| | - Ramachandran S Vasan
- Department of Epidemiology, School of Public Health, Boston University, Boston, MA, USA.,Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Ali Shojaie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Noah Simon
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
| | - Neil M Davies
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK.,K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Norwegian, Norway.,Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | | | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Russell P Tracy
- Departments of Pathology & Laboratory Medicine, and Biochemistry, Larner College of Medicine, University of Vermont, Burlington, VT, USA
| | - Kerri L Wiggins
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jie Zheng
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Department of Epidemiology, University of Washington, Seattle, WA, USA.,Department of Medicine, University of Washington, Seattle, WA, USA.,Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
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Xue T, Chiao B, Xu T, Li H, Shi K, Cheng Y, Shi Y, Guo X, Tong S, Guo M, Chew SH, Ebstein RP, Cui D. The heart-brain axis: A proteomics study of meditation on the cardiovascular system of Tibetan Monks. EBioMedicine 2022; 80:104026. [PMID: 35576643 PMCID: PMC9118669 DOI: 10.1016/j.ebiom.2022.104026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 04/10/2022] [Accepted: 04/11/2022] [Indexed: 11/29/2022] Open
Abstract
Background There have been mixed reports on the beneficial effects of meditation in cardiovascular disease (CVD), which is widely considered the leading cause of death worldwide. Methods To clarify the role of meditation in modulating the heart-brain axis, we implemented an extreme phenotype strategy, i.e., Tibetan monks (BMI > 30) who practised 19.20 ± 7.82 years of meditation on average and their strictly matched non-meditative Tibetan controls. Hypothesis-free advanced proteomics strategies (Data Independent Acquisition and Targeted Parallel Reaction Monitoring) were jointly applied to systematically investigate and target the plasma proteome underlying meditation. Total cholesterol, low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (Apo B) and lipoprotein (a) [Lp(a)] as the potential cardiovascular risk factors were evaluated. Heart rate variability (HRV) was assessed by electrocardiogram. Findings Obesity, hypertension, and reduced HRV is offset by long-term meditation. Notably, meditative monks have blood pressure and HRV comparable to their matched Tibetan controls. Meditative monks have a protective plasma proteome, related to decreased atherosclerosis, enhanced glycolysis, and oxygen release, that confers resilience to the development of CVD. In addition, clinical risk factors in plasma were significantly decreased in monks compared with controls, including total cholesterol, LDL-C, Apo B, and Lp(a). Interpretation To our knowledge, this work is the first well-controlled proteomics investigation of long-term meditation, which opens up a window for individuals characterized by a sedentary lifestyle to improve their cardiovascular health with an accessible method practised for more than two millennia. Funding See the Acknowledgements section.
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Affiliation(s)
- Ting Xue
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 201108, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai 201108, China
| | - Benjamin Chiao
- China Center for Behavioral Economics and Finance, Southwestern University of Finance and Economics, Chengdu, Sichuan 610074, China; Paris School of Technology and Business, Paris 75011, France
| | - Tianjiao Xu
- Nursing Department, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 201108, China
| | - Han Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 201108, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai 201108, China
| | - Kai Shi
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 201108, China
| | - Ying Cheng
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 201108, China
| | - Yuan Shi
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 201108, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai 201108, China
| | - Xiaoli Guo
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Shanbao Tong
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Menglin Guo
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Soo Hong Chew
- China Center for Behavioral Economics and Finance, Southwestern University of Finance and Economics, Chengdu, Sichuan 610074, China; Department of Economics, National University of Singapore, 117570, Singapore.
| | - Richard P Ebstein
- China Center for Behavioral Economics and Finance, Southwestern University of Finance and Economics, Chengdu, Sichuan 610074, China.
| | - Donghong Cui
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 201108, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai 201108, China; Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai 201108, China.
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Henry A, Gordillo-Marañón M, Finan C, Schmidt AF, Ferreira JP, Karra R, Sundström J, Lind L, Ärnlöv J, Zannad F, Mälarstig A, Hingorani AD, Lumbers RT. Therapeutic Targets for Heart Failure Identified Using Proteomics and Mendelian Randomization. Circulation 2022; 145:1205-1217. [PMID: 35300523 PMCID: PMC9010023 DOI: 10.1161/circulationaha.121.056663] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Accepted: 02/09/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Heart failure (HF) is a highly prevalent disorder for which disease mechanisms are incompletely understood. The discovery of disease-associated proteins with causal genetic evidence provides an opportunity to identify new therapeutic targets. METHODS We investigated the observational and causal associations of 90 cardiovascular proteins, which were measured using affinity-based proteomic assays. First, we estimated the associations of 90 cardiovascular proteins with incident heart failure by means of a fixed-effect meta-analysis of 4 population-based studies, composed of a total of 3019 participants with 732 HF events. The causal effects of HF-associated proteins were then investigated by Mendelian randomization, using cis-protein quantitative loci genetic instruments identified from genomewide association studies in more than 30 000 individuals. To improve the precision of causal estimates, we implemented an Mendelian randomization model that accounted for linkage disequilibrium between instruments and tested the robustness of causal estimates through a multiverse sensitivity analysis that included up to 120 combinations of instrument selection parameters and Mendelian randomization models per protein. The druggability of candidate proteins was surveyed, and mechanism of action and potential on-target side effects were explored with cross-trait Mendelian randomization analysis. RESULTS Forty-four of ninety proteins were positively associated with risk of incident HF (P<6.0×10-4). Among these, 8 proteins had evidence of a causal association with HF that was robust to multiverse sensitivity analysis: higher CSF-1 (macrophage colony-stimulating factor 1), Gal-3 (galectin-3) and KIM-1 (kidney injury molecule 1) were positively associated with risk of HF, whereas higher ADM (adrenomedullin), CHI3L1 (chitinase-3-like protein 1), CTSL1 (cathepsin L1), FGF-23 (fibroblast growth factor 23), and MMP-12 (matrix metalloproteinase-12) were protective. Therapeutics targeting ADM and Gal-3 are currently under evaluation in clinical trials, and all the remaining proteins were considered druggable, except KIM-1. CONCLUSIONS We identified 44 circulating proteins that were associated with incident HF, of which 8 showed evidence of a causal relationship and 7 were druggable, including adrenomedullin, which represents a particularly promising drug target. Our approach demonstrates a tractable roadmap for the triangulation of population genomic and proteomic data for the prioritization of therapeutic targets for complex human diseases.
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Affiliation(s)
- Albert Henry
- Institute of Cardiovascular Science (A.H., M.G.-M., C.F., A.F.S., A.D.H.), University College London, United Kingdom
- British Heart Foundation Research Accelerator (A.H., M.G.-M., C.F., A.F.S., A.D.H., R.T.L.), University College London, United Kingdom
- Institute of Health Informatics (A.H., R.T.L.), University College London, United Kingdom
| | - María Gordillo-Marañón
- Institute of Cardiovascular Science (A.H., M.G.-M., C.F., A.F.S., A.D.H.), University College London, United Kingdom
- British Heart Foundation Research Accelerator (A.H., M.G.-M., C.F., A.F.S., A.D.H., R.T.L.), University College London, United Kingdom
| | - Chris Finan
- Institute of Cardiovascular Science (A.H., M.G.-M., C.F., A.F.S., A.D.H.), University College London, United Kingdom
- British Heart Foundation Research Accelerator (A.H., M.G.-M., C.F., A.F.S., A.D.H., R.T.L.), University College London, United Kingdom
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, The Netherlands (C.F., A.F.S.)
| | - Amand F. Schmidt
- Institute of Cardiovascular Science (A.H., M.G.-M., C.F., A.F.S., A.D.H.), University College London, United Kingdom
- British Heart Foundation Research Accelerator (A.H., M.G.-M., C.F., A.F.S., A.D.H., R.T.L.), University College London, United Kingdom
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, The Netherlands (C.F., A.F.S.)
| | - João Pedro Ferreira
- Unidade de Investigação e Desenvolvimento Cardiovascular, Rede de Investigação em Saúde, Department of Surgery and Physiology, Faculty of Medicine of the University of Porto, Portugal (J.P.F.)
- Université de Lorraine, Inserm, Centre d’Investigations Cliniques - Plurithématique 14-33, and Inserm U1116, Centre Hospitalier Régional Universitaire, French Clinical Research Infrastructure Network, Investigation Network Initiative - Cardiovascular and Renal Clinical Trialists, Nancy, France (J.P.F., F.Z.)
| | - Ravi Karra
- Division of Cardiology, Department of Medicine (R.K.), Duke University Medical Center, Durham, NC
- Department of Pathology (R.K.), Duke University Medical Center, Durham, NC
| | - Johan Sundström
- Department of Medical Sciences, Uppsala University, Sweden (J.S., L.L.)
- The George Institute for Global Health, University of New South Wales, Sydney, Australia (J.S.)
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Sweden (J.S., L.L.)
| | - Johan Ärnlöv
- School of Health and Social Studies, Dalarna University, Falun, Sweden (J.Ä.)
- Division of Family Medicine and Primary Care, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Huddinge, Sweden (J.Ä.)
| | - Faiez Zannad
- Université de Lorraine, Inserm, Centre d’Investigations Cliniques - Plurithématique 14-33, and Inserm U1116, Centre Hospitalier Régional Universitaire, French Clinical Research Infrastructure Network, Investigation Network Initiative - Cardiovascular and Renal Clinical Trialists, Nancy, France (J.P.F., F.Z.)
| | - Anders Mälarstig
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Solna‚ Sweden (A.M.)
- Emerging Science and Innovation, Pfizer Worldwide Research, Development and Medical, Cambridge, MA (A.M.)
| | - Aroon D. Hingorani
- Institute of Cardiovascular Science (A.H., M.G.-M., C.F., A.F.S., A.D.H.), University College London, United Kingdom
- British Heart Foundation Research Accelerator (A.H., M.G.-M., C.F., A.F.S., A.D.H., R.T.L.), University College London, United Kingdom
| | - R. Thomas Lumbers
- British Heart Foundation Research Accelerator (A.H., M.G.-M., C.F., A.F.S., A.D.H., R.T.L.), University College London, United Kingdom
- Institute of Health Informatics (A.H., R.T.L.), University College London, United Kingdom
- Health Data Research UK London (R.T.L.), University College London, United Kingdom
| | - HERMES and SCALLOP Consortia
- Institute of Cardiovascular Science (A.H., M.G.-M., C.F., A.F.S., A.D.H.), University College London, United Kingdom
- British Heart Foundation Research Accelerator (A.H., M.G.-M., C.F., A.F.S., A.D.H., R.T.L.), University College London, United Kingdom
- Institute of Health Informatics (A.H., R.T.L.), University College London, United Kingdom
- Health Data Research UK London (R.T.L.), University College London, United Kingdom
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, The Netherlands (C.F., A.F.S.)
- Unidade de Investigação e Desenvolvimento Cardiovascular, Rede de Investigação em Saúde, Department of Surgery and Physiology, Faculty of Medicine of the University of Porto, Portugal (J.P.F.)
- Université de Lorraine, Inserm, Centre d’Investigations Cliniques - Plurithématique 14-33, and Inserm U1116, Centre Hospitalier Régional Universitaire, French Clinical Research Infrastructure Network, Investigation Network Initiative - Cardiovascular and Renal Clinical Trialists, Nancy, France (J.P.F., F.Z.)
- Division of Cardiology, Department of Medicine (R.K.), Duke University Medical Center, Durham, NC
- Department of Pathology (R.K.), Duke University Medical Center, Durham, NC
- Department of Medical Sciences, Uppsala University, Sweden (J.S., L.L.)
- The George Institute for Global Health, University of New South Wales, Sydney, Australia (J.S.)
- School of Health and Social Studies, Dalarna University, Falun, Sweden (J.Ä.)
- Division of Family Medicine and Primary Care, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Huddinge, Sweden (J.Ä.)
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Solna‚ Sweden (A.M.)
- Emerging Science and Innovation, Pfizer Worldwide Research, Development and Medical, Cambridge, MA (A.M.)
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43
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Michelhaugh SA, Januzzi JL. Using Artificial Intelligence to Better Predict and Develop Biomarkers. Heart Fail Clin 2022; 18:275-285. [PMID: 35341540 DOI: 10.1016/j.hfc.2021.11.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Advancements in technology have improved biomarker discovery in the field of heart failure (HF). What was once a slow and laborious process has gained efficiency through use of high-throughput omics platforms to phenotype HF at the level of genes, transcripts, proteins, and metabolites. Furthermore, improvements in artificial intelligence (AI) have made the interpretation of large omics data sets easier and improved analysis. Use of omics and AI in biomarker discovery can aid clinicians by identifying markers of risk for developing HF, monitoring care, determining prognosis, and developing druggable targets. Combined, AI has the power to improve HF patient care.
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44
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Emilsson V, Gudmundsdottir V, Gudjonsson A, Jonmundsson T, Jonsson BG, Karim MA, Ilkov M, Staley JR, Gudmundsson EF, Launer LJ, Lindeman JH, Morton NM, Aspelund T, Lamb JR, Jennings LL, Gudnason V. Coding and regulatory variants are associated with serum protein levels and disease. Nat Commun 2022; 13:481. [PMID: 35079000 PMCID: PMC8789809 DOI: 10.1038/s41467-022-28081-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Accepted: 01/07/2022] [Indexed: 12/20/2022] Open
Abstract
Circulating proteins can be used to diagnose and predict disease-related outcomes. A deep serum proteome survey recently revealed close associations between serum protein networks and common disease. In the current study, 54,469 low-frequency and common exome-array variants were compared to 4782 protein measurements in the serum of 5343 individuals from the AGES Reykjavik cohort. This analysis identifies a large number of serum proteins with genetic signatures overlapping those of many diseases. More specifically, using a study-wide significance threshold, we find that 2021 independent exome array variants are associated with serum levels of 1942 proteins. These variants reside in genetic loci shared by hundreds of complex disease traits, highlighting serum proteins' emerging role as biomarkers and potential causative agents of a wide range of diseases.
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Affiliation(s)
- Valur Emilsson
- Icelandic Heart Association, Holtasmari 1, IS-201 Kopavogur, Kopavogur, Iceland.
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Reykjavík, Iceland.
| | | | | | | | | | - Mohd A Karim
- Wellcome Trust Sanger Institute, Welcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Marjan Ilkov
- Icelandic Heart Association, Holtasmari 1, IS-201 Kopavogur, Kopavogur, Iceland
| | - James R Staley
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Elias F Gudmundsson
- Icelandic Heart Association, Holtasmari 1, IS-201 Kopavogur, Kopavogur, Iceland
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Bethesda, MD, 20892-9205, USA
| | - Jan H Lindeman
- Department of Surgery, Leiden University Medical Center, Leiden, Netherlands
| | - Nicholas M Morton
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Thor Aspelund
- Icelandic Heart Association, Holtasmari 1, IS-201 Kopavogur, Kopavogur, Iceland
| | - John R Lamb
- GNF Novartis, 10675 John Jay Hopkins Drive, San Diego, CA, 92121, USA
| | - Lori L Jennings
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Holtasmari 1, IS-201 Kopavogur, Kopavogur, Iceland.
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Reykjavík, Iceland.
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45
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de Jesus Santos AP, Oliveira-Giacomelli Á, de Sá VK, do Nascimento IC, de Simone Molina E, Ulrich H. Selection and Application of Aptamer Affinity for Protein Purification. Methods Mol Biol 2022; 2466:187-203. [PMID: 35585319 DOI: 10.1007/978-1-0716-2176-9_13] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Aptamers are affinity-based oligonucleotide ligands raised against a target molecule, which might be of proteic or other nature. Aptamers are developed by using a reiterative in vitro selection procedure, named SELEX, in which the target is exposed to a combinatorial oligonucleotide combinatorial library. Target bound oligonucleotides are eluted, and PCR amplified followed by the next SELEX round. The process is repeated until no further increase in target binding affinity and specificity is achieved. Selected aptamers are identified and immobilized for protein purification. In view of their stability against denaturation and capability of renaturation, low costs of production, easiness of modification and stabilization, oligonucleotide aptamers are excellent tools as high-affinity ligands for applications of protein purification.
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Affiliation(s)
| | | | - Vanessa Karen de Sá
- Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil
| | | | - Erika de Simone Molina
- Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil
| | - Henning Ulrich
- Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil.
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46
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Clark KC, Kwitek AE. Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome. Compr Physiol 2021; 12:3045-3084. [PMID: 34964118 PMCID: PMC9373910 DOI: 10.1002/cphy.c210010] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.
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Affiliation(s)
- Karen C Clark
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Anne E Kwitek
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
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47
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Qi F, Tan Y, Yao A, Yang X, He Y. Psoriasis to Psoriatic Arthritis: The Application of Proteomics Technologies. Front Med (Lausanne) 2021; 8:681172. [PMID: 34869404 PMCID: PMC8635007 DOI: 10.3389/fmed.2021.681172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 10/18/2021] [Indexed: 11/13/2022] Open
Abstract
Psoriatic disease (PsD) is a spectrum of diseases that affect both skin [cutaneous psoriasis (PsC)] and musculoskeletal features [psoriatic arthritis (PsA)]. A considerable number of patients with PsC have asymptomatic synovio-entheseal inflammations, and approximately one-third of those eventually progress to PsA with an enigmatic mechanism. Published studies have shown that early interventions to the very early-stage PsA would effectively prevent substantial bone destructions or deformities, suggesting an unmet goal for exploring early PsA biomarkers. The emergence of proteomics technologies brings a complete view of all involved proteins in PsA transitions, offers a unique chance to map all potential peptides, and allows a direct head-to-head comparison of interaction pathways in PsC and PsA. This review summarized the latest development of proteomics technologies, highlighted its application in PsA biomarker discovery, and discussed the possible clinical detectable PsA risk factors in patients with PsC.
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Affiliation(s)
- Fei Qi
- Department of Dermatology, Capital Medical University Affiliated Beijing Chaoyang Hospital, Beijing, China
| | - Yaqi Tan
- Department of Dermatology, Capital Medical University Affiliated Beijing Chaoyang Hospital, Beijing, China
| | - Amin Yao
- Department of Dermatology, Capital Medical University Affiliated Beijing Chaoyang Hospital, Beijing, China
| | - Xutong Yang
- Department of Dermatology, Capital Medical University Affiliated Beijing Chaoyang Hospital, Beijing, China
| | - Yanling He
- Department of Dermatology, Capital Medical University Affiliated Beijing Chaoyang Hospital, Beijing, China
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48
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Meng H, Ruan J, Chen Y, Yan Z, Shi K, Li X, Yang P, Meng F. Investigation of Specific Proteins Related to Different Types of Coronary Atherosclerosis. Front Cardiovasc Med 2021; 8:758035. [PMID: 34746269 PMCID: PMC8569131 DOI: 10.3389/fcvm.2021.758035] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 09/27/2021] [Indexed: 12/28/2022] Open
Abstract
Objective: Coronary heart disease (CHD) is a complex disease caused by multifaceted interaction between genetic and environmental factors, which makes identification of the most likely disease candidate proteins and their associated risk markers a big challenge. Atherosclerosis is presented by a broad spectrum of heart diseases, including stable coronary artery disease (SCAD) and acute myocardial infarction (AMI), which is the progressive stage of SCAD. As such, the correct and prompt diagnosis of atherosclerosis turns into imperative for precise and prompt disease diagnosis, treatment and prognosis. Methods: The current work aims to look for specific protein markers for differential diagnosis of coronary atherosclerosis. Thirty male patients between 45 and 55 years diagnosed with atherosclerosis were analyzed by tandem mass tag (TMT) mass spectrometry. The study excluded those who were additionally diagnosed with hypertension and type 1 and 2 diabetes. The Mufuzz analysis was applied to select target proteins for precise and prompt diagnosis of atherosclerosis, most of which were most related to high lipid metabolism. The parallel reaction monitoring (PRM) was used to verify the selected target proteins. Finally, The receiver operating characteristic curve (ROC) was calculated by a random forest experiment. Results: One thousand one hundred and forty seven proteins were identified in the TMT mass spectrometry, 907 of which were quantifiable. In the PRM study, six proteins related to lipid metabolism pathway were selected for verification and they were ALB, SHBG, APOC2, APOC3, APOC4, SAA4. Conclusion: Through the detected specific changes in these six proteins, our results provide accuracy in atherosclerosis patients' diagnosis, especially in cases with varying types of the disease.
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Affiliation(s)
- Heyu Meng
- Jilin Provincial Precision Medicine Key Laboratory for Cardiovascular Genetic Diagnosis (Jilin Provincial Engineering Laboratory for Endothelial Function and Genetic Diagnosis of Cardiovascular Disease, Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute), Department of Cardiology, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Jianjun Ruan
- Jilin Provincial Precision Medicine Key Laboratory for Cardiovascular Genetic Diagnosis (Jilin Provincial Engineering Laboratory for Endothelial Function and Genetic Diagnosis of Cardiovascular Disease, Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute), Department of Cardiology, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Yanqiu Chen
- Jilin Provincial Precision Medicine Key Laboratory for Cardiovascular Genetic Diagnosis (Jilin Provincial Engineering Laboratory for Endothelial Function and Genetic Diagnosis of Cardiovascular Disease, Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute), Department of Cardiology, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Zhaohan Yan
- Jilin Provincial Precision Medicine Key Laboratory for Cardiovascular Genetic Diagnosis (Jilin Provincial Engineering Laboratory for Endothelial Function and Genetic Diagnosis of Cardiovascular Disease, Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute), Department of Cardiology, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Kaiyao Shi
- Jilin Provincial Precision Medicine Key Laboratory for Cardiovascular Genetic Diagnosis (Jilin Provincial Engineering Laboratory for Endothelial Function and Genetic Diagnosis of Cardiovascular Disease, Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute), Department of Cardiology, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Xiangdong Li
- Jilin Provincial Precision Medicine Key Laboratory for Cardiovascular Genetic Diagnosis (Jilin Provincial Engineering Laboratory for Endothelial Function and Genetic Diagnosis of Cardiovascular Disease, Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute), Department of Cardiology, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Ping Yang
- Jilin Provincial Precision Medicine Key Laboratory for Cardiovascular Genetic Diagnosis (Jilin Provincial Engineering Laboratory for Endothelial Function and Genetic Diagnosis of Cardiovascular Disease, Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute), Department of Cardiology, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Fanbo Meng
- Jilin Provincial Precision Medicine Key Laboratory for Cardiovascular Genetic Diagnosis (Jilin Provincial Engineering Laboratory for Endothelial Function and Genetic Diagnosis of Cardiovascular Disease, Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, Jilin Provincial Cardiovascular Research Institute), Department of Cardiology, China-Japan Union Hospital of Jilin University, Changchun, China
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49
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Costa JZ, Del Pozo J, McLean K, Inglis N, Sourd P, Bordeianu A, Thompson KD. Proteomic characterization of serum proteins from Atlantic salmon (Salmo salar L.) from an outbreak with cardiomyopathy syndrome. JOURNAL OF FISH DISEASES 2021; 44:1697-1709. [PMID: 34224170 DOI: 10.1111/jfd.13488] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Revised: 06/18/2021] [Accepted: 06/21/2021] [Indexed: 06/13/2023]
Abstract
Cardiomyopathy syndrome (CMS), caused by piscine myocarditis virus (PMCV), is a serious challenge to Atlantic salmon (Salmo salar L.) aquaculture. Regrettably, husbandry techniques are the only tool to manage CMS outbreaks, and no prophylactic measures are available at present. Early diagnosis of CMS is therefore desirable, preferably with non-lethal diagnostic methods, such as serum biomarkers. To identify candidate biomarkers for CMS, the protein content of pools of sera (4 fish/pool) from salmon with a CMS outbreak (3 pools) and from clinically healthy salmon (3 pools) was compared using liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Overall, seven proteins were uniquely identified in the sera of clinically healthy fish, while 27 proteins were unique to the sera of CMS fish. Of the latter, 24 have been associated with cardiac disease in humans. These were grouped as leakage enzymes (creatine kinase, lactate dehydrogenase, glycogen phosphorylase and carbonic anhydrase); host reaction proteins (acute-phase response proteins-haptoglobin, fibrinogen, α2-macroglobulin and ceruloplasmin; and complement-related proteins); and regeneration/remodelling proteins (fibronectin, lumican and retinol). Clinical evaluation of the suitability of these proteins as biomarkers of CMS, either individually or as part of a panel, is a logical next step for the development of early diagnostic tools for CMS.
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Affiliation(s)
- Janina Z Costa
- Aquaculture Research Group, Moredun Research Institute, Pentlands Science Park, Penicuik (Edinburgh), UK
| | - Jorge Del Pozo
- Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | - Kevin McLean
- Proteomics Facilities, Moredun Research Institute, Pentlands Science Park, Penicuik (Edinburgh), UK
| | - Neil Inglis
- Proteomics Facilities, Moredun Research Institute, Pentlands Science Park, Penicuik (Edinburgh), UK
| | - Philippe Sourd
- Cooke Aquaculture Scotland, Willow House, Strathclyde Business Park, Bellshill, UK
| | - Andrei Bordeianu
- Cooke Aquaculture Scotland, Willow House, Strathclyde Business Park, Bellshill, UK
| | - Kim D Thompson
- Aquaculture Research Group, Moredun Research Institute, Pentlands Science Park, Penicuik (Edinburgh), UK
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50
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Abstract
The number of therapies for heart failure (HF) with reduced ejection fraction has nearly doubled in the past decade. In addition, new therapies for HF caused by hypertrophic and infiltrative disease are emerging rapidly. Indeed, we are on the verge of a new era in HF in which insights into the biology of myocardial disease can be matched to an understanding of the genetic predisposition in an individual patient to inform precision approaches to therapy. In this Review, we summarize the biology of HF, emphasizing the causal relationships between genetic contributors and traditional structure-based remodelling outcomes, and highlight the mechanisms of action of traditional and novel therapeutics. We discuss the latest advances in our understanding of both the Mendelian genetics of cardiomyopathy and the complex genetics of the clinical syndrome presenting as HF. In the phenotypic domain, we discuss applications of machine learning for the subcategorization of HF in ways that might inform rational prescribing of medications. We aim to bridge the gap between the biology of the failing heart, its diverse clinical presentations and the range of medications that we can now use to treat it. We present a roadmap for the future of precision medicine in HF.
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