1
|
Patel‐Murray NL, Zhang L, Claggett BL, Xu D, Serrano‐Fernandez P, Healey M, Wandel S, Chen C, Jacob J, Xu H, Turner GM, Chutkow W, Yates DP, O'Donnell CJ, Prescott MF, Lefkowitz M, Gimpelewicz CR, Beste MT, Zhao F, Gou L, Desai AS, Jhund PS, Packer M, Pfeffer MA, Redfield MM, Rouleau JL, Zannad F, Zile MR, McMurray JJV, Mendelson MM, Solomon SD, Cunningham JW. Aptamer Proteomics for Biomarker Discovery in Heart Failure With Preserved Ejection Fraction: The PARAGON-HF Proteomic Substudy. J Am Heart Assoc 2024; 13:e033544. [PMID: 38904251 PMCID: PMC11255700 DOI: 10.1161/jaha.123.033544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 04/15/2024] [Indexed: 06/22/2024]
Abstract
BACKGROUND Prognostic markers and biological pathways linked to detrimental clinical outcomes in heart failure with preserved ejection fraction (HFpEF) remain incompletely defined. METHODS AND RESULTS We measured serum levels of 4123 unique proteins in 1117 patients with HFpEF enrolled in the PARAGON-HF (Efficacy and Safety of LCZ696 Compared to Valsartan, on Morbidity and Mortality in Heart Failure Patients With Preserved Ejection Fraction) trial using a modified aptamer proteomic assay. Baseline circulating protein concentrations significantly associated with the primary end point and the timing and occurrence of total heart failure hospitalization and cardiovascular death were identified by recurrent events regression, accounting for multiple testing, adjusted for age, sex, treatment, and anticoagulant use, and compared with published analyses in 2515 patients with heart failure with reduced ejection fraction from the PARADIGM-HF (Prospective Comparison of ARNI With ACEI to Determine Impact on Global Mortality and Morbidity in Heart Failure) and ATMOSPHERE (Efficacy and Safety of Aliskiren and Aliskiren/Enalapril Combination on Morbidity-Mortality in Patients With Chronic Heart Failure) clinical trials. We identified 288 proteins that were robustly associated with the risk of heart failure hospitalization and cardiovascular death in patients with HFpEF. The baseline proteins most strongly related to outcomes included B2M (β-2 microglobulin), TIMP1 (tissue inhibitor of matrix metalloproteinase 1), SERPINA4 (serpin family A member 4), and SVEP1 (sushi, von Willebrand factor type A, EGF, and pentraxin domain containing 1). Overall, the protein-outcome associations in patients with HFpEF did not markedly differ as compared with patients with heart failure with reduced ejection fraction. A proteomic risk score derived in patients with HFpEF was not superior to a previous proteomic score derived in heart failure with reduced ejection fraction nor to clinical risk factors, NT-proBNP (N-terminal pro-B-type natriuretic peptide), or high-sensitivity cardiac troponin. CONCLUSIONS Numerous serum proteins linked to metabolic, coagulation, and extracellular matrix regulatory pathways were associated with worse HFpEF prognosis in the PARAGON-HF proteomic substudy. Our results demonstrate substantial similarities among serum proteomic risk markers for heart failure hospitalization and cardiovascular death when comparing clinical trial participants with heart failure across the ejection fraction spectrum. REGISTRATION URL: https://www.clinicaltrials.gov; Unique Identifiers: NCT01920711, NCT01035255, NCT00853658.
Collapse
Affiliation(s)
| | - Luqing Zhang
- Novartis Institutes for Biomedical ResearchCambridgeMAUSA
| | - Brian L. Claggett
- Cardiovascular Division, Brigham and Women’s HospitalHarvard Medical SchoolBostonMAUSA
| | - Dongchu Xu
- Cardiovascular Division, Brigham and Women’s HospitalHarvard Medical SchoolBostonMAUSA
| | | | | | | | | | - Jaison Jacob
- Novartis Institutes for Biomedical ResearchCambridgeMAUSA
| | - Huilei Xu
- Novartis Institutes for Biomedical ResearchCambridgeMAUSA
| | | | | | | | | | | | | | | | | | - Faye Zhao
- Novartis Institutes for Biomedical ResearchCambridgeMAUSA
| | - Liangke Gou
- Novartis Pharmaceuticals CorporationEast HanoverNJUSA
| | - Akshay S. Desai
- Cardiovascular Division, Brigham and Women’s HospitalHarvard Medical SchoolBostonMAUSA
| | - Pardeep S. Jhund
- BHF Glasgow Cardiovascular Research Center, School of Cardiovascular and Metabolic HealthUniversity of GlasgowGlasgowUK
| | | | - Marc A. Pfeffer
- Cardiovascular Division, Brigham and Women’s HospitalHarvard Medical SchoolBostonMAUSA
| | | | - Jean L. Rouleau
- Institut de Cardiologie de MontréalUniversité de MontréalQBCanada
| | - Faiez Zannad
- Inserm, Centre d’Investigation Clinique Plurithématique 1433, U1116, CHRU de Nancy, F‐CRIN INI‐CRCTUniversité de LorraineNancyFrance
| | - Michael R. Zile
- Medical University of South Carolina and RHJ Department of Veterans Administration Medical CenterCharlestonSCUSA
| | - John J. V. McMurray
- BHF Glasgow Cardiovascular Research Center, School of Cardiovascular and Metabolic HealthUniversity of GlasgowGlasgowUK
| | | | - Scott D. Solomon
- Cardiovascular Division, Brigham and Women’s HospitalHarvard Medical SchoolBostonMAUSA
| | | |
Collapse
|
2
|
Rao P, Keyes MJ, Mi MY, Barber JL, Tahir UA, Deng S, Clish CB, Shen D, Farrell LA, Wilson JG, Gao Y, Yimer WK, Ekunwe L, Hall ME, Muntner PM, Guo X, Taylor KD, Tracy RP, Rich SS, Rotter JI, Xanthakis V, Vasan RS, Bouchard C, Sarzynski MA, Gerszten RE, Robbins JM. Plasma Proteomics of Exercise Blood Pressure and Incident Hypertension. JAMA Cardiol 2024:2820069. [PMID: 38865108 PMCID: PMC11170454 DOI: 10.1001/jamacardio.2024.1397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 04/10/2024] [Indexed: 06/13/2024]
Abstract
Importance Blood pressure response during acute exercise (exercise blood pressure [EBP]) is associated with the future risk of hypertension and cardiovascular disease (CVD). Biochemical characterization of EBP could inform disease biology and identify novel biomarkers of future hypertension. Objective To identify protein markers associated with EBP and test their association with incident hypertension. Design, Setting, and Participants This study assayed 4977 plasma proteins in 681 healthy participants (from 763 assessed) of the Health, Risk Factors, Exercise Training and Genetics (HERITAGE; data collection from January 1993 to December 1997 and plasma proteomics from January 2019 to January 2020) Family Study at rest who underwent 2 cardiopulmonary exercise tests. Individuals were free of CVD at the time of recruitment. Individuals with resting SBP ≥160 mm Hg or DBP ≥100 mm Hg or taking antihypertensive drug therapy were excluded from the study. The association between resting plasma protein levels to both resting BP and EBP was evaluated. Proteins associated with EBP were analyzed for their association with incident hypertension in the Framingham Heart Study (FHS; n = 1177) and validated in the Jackson Heart Study (JHS; n = 772) and Multi-Ethnic Study of Atherosclerosis (MESA; n = 1367). Proteins associated with incident hypertension were tested for putative causal links in approximately 700 000 individuals using cis-protein quantitative loci mendelian randomization (cis-MR). Data were analyzed from January 2023 to January 2024. Exposures Plasma proteins. Main Outcomes and Measures EBP was defined as the BP response during a fixed workload (50 W) on a cycle ergometer. Hypertension was defined as BP ≥140/90 mm Hg or taking antihypertensive medication. Results Among the 681 participants in the HERITAGE Family Study, the mean (SD) age was 34 (13) years; 366 participants (54%) were female; 238 (35%) were self-reported Black and 443 (65%) were self-reported White. Proteomic profiling of EBP revealed 34 proteins that would not have otherwise been identified through profiling of resting BP alone. Transforming growth factor β receptor 3 (TGFBR3) and prostaglandin D2 synthase (PTGDS) had the strongest association with exercise systolic BP (SBP) and diastolic BP (DBP), respectively (TGFBR3: exercise SBP, β estimate, -3.39; 95% CI, -4.79 to -2.00; P = 2.33 × 10-6; PTGDS: exercise DBP β estimate, -2.50; 95% CI, -3.29 to -1.70; P = 1.18 × 10-9). In fully adjusted models, TGFBR3 was inversely associated with incident hypertension in FHS, JHS, and MESA (hazard ratio [HR]: FHS, 0.86; 95% CI, 0.75-0.97; P = .01; JHS, 0.87; 95% CI, 0.77-0.97; P = .02; MESA, 0.84; 95% CI, 0.71-0.98; P = .03; pooled cohort, 0.86; 95% CI, 0.79-0.92; P = 6 × 10-5). Using cis-MR, genetically predicted levels of TGFBR3 were associated with SBP, hypertension, and CVD events (SBP: β, -0.38; 95% CI, -0.64 to -0.11; P = .006; hypertension: odds ratio [OR], 0.99; 95% CI, 0.98-0.99; P < .001; heart failure with hypertension: OR, 0.86; 95% CI, 0.77-0.97; P = .01; CVD: OR, 0.84; 95% CI, 0.77-0.92; P = 8 × 10-5; cerebrovascular events: OR, 0.77; 95% CI, 0.70-0.85; P = 5 × 10-7). Conclusions and Relevance Plasma proteomic profiling of EBP identified a novel protein, TGFBR3, which may protect against elevated BP and long-term CVD outcomes.
Collapse
Affiliation(s)
- Prashant Rao
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Michelle. J. Keyes
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Michael Y. Mi
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Jacob L. Barber
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia
| | - Usman A. Tahir
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Shuliang Deng
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Clary B. Clish
- Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge
| | - Dongxiao Shen
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Laurie. A. Farrell
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - James G. Wilson
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Yan Gao
- Department of Data Sciences, University of Mississippi Medical Center, Jackson
| | - Wondwosen K. Yimer
- Department of Data Sciences, University of Mississippi Medical Center, Jackson
| | - Lynette Ekunwe
- Jackson Heart Study Field Center, University of Mississippi Medical Center, Jackson
| | - Michael E. Hall
- Department of Medicine, Division of Cardiology, University of Mississippi Medical Center, Jackson
| | - Paul M. Muntner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, the Lundquist Institute for Biomedical Innovation at Harbor–University of California, Los Angeles Medical Center, Torrance
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, the Lundquist Institute for Biomedical Innovation at Harbor–University of California, Los Angeles Medical Center, Torrance
| | - Russell P. Tracy
- Department of Pathology Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, the Lundquist Institute for Biomedical Innovation at Harbor–University of California, Los Angeles Medical Center, Torrance
| | - Vanessa Xanthakis
- Boston University’s and National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts
- Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
| | - Ramachandran S. Vasan
- Boston University’s and National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts
- Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana
| | - Mark A. Sarzynski
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia
| | - Robert E. Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge
| | - Jeremy M. Robbins
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| |
Collapse
|
3
|
Hota M, Barber JL, Ruiz-Ramie JJ, Schwartz CS, Lam DTUH, Rao P, Mi MY, Katz DH, Robbins JM, Clish CB, Gerszten RE, Sarzynski MA, Ghosh S, Bouchard C. Omics-driven investigation of the biology underlying intrinsic submaximal working capacity and its trainability. Physiol Genomics 2023; 55:517-543. [PMID: 37661925 PMCID: PMC11178266 DOI: 10.1152/physiolgenomics.00163.2022] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 07/21/2023] [Accepted: 08/31/2023] [Indexed: 09/05/2023] Open
Abstract
Submaximal exercise capacity is an indicator of cardiorespiratory fitness with clinical and public health implications. Submaximal exercise capacity and its response to exercise programs are characterized by heritability levels of about 40%. Using physical working capacity (power output) at a heart rate of 150 beats/min (PWC150) as an indicator of submaximal exercise capacity in subjects of the HERITAGE Family Study, we have undertaken multi-omics and in silico explorations of the underlying biology of PWC150 and its response to 20 wk of endurance training. Our goal was to illuminate the biological processes and identify panels of genes associated with human variability in intrinsic PWC150 (iPWC150) and its trainability (dPWC150). Our bioinformatics approach was based on a combination of genome-wide association, skeletal muscle gene expression, and plasma proteomics and metabolomics experiments. Genes, proteins, and metabolites showing significant associations with iPWC150 or dPWC150 were further queried for the enrichment of biological pathways. We compared genotype-phenotype associations of emerging candidate genes with reported functional consequences of gene knockouts in mouse models. We investigated the associations between DNA variants and multiple muscle and cardiovascular phenotypes measured in HERITAGE subjects. Two panels of prioritized genes of biological relevance to iPWC150 (13 genes) and dPWC150 (6 genes) were identified, supporting the hypothesis that genes and pathways associated with iPWC150 are different from those underlying dPWC150. Finally, the functions of these genes and pathways suggested that human variation in submaximal exercise capacity is mainly driven by skeletal muscle morphology and metabolism and red blood cell oxygen-carrying capacity.NEW & NOTEWORTHY Multi-omics and in silico explorations of the genes and underlying biology of submaximal exercise capacity and its response to 20 wk of endurance training were undertaken. Prioritized genes were identified: 13 genes for variation in submaximal exercise capacity in the sedentary state and 5 genes for the response level to endurance training, with no overlap between them. Genes and pathways associated with submaximal exercise capacity in the sedentary state are different from those underlying trainability.
Collapse
Affiliation(s)
- Monalisa Hota
- Centre for Computational Biology, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Jacob L Barber
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States
| | - Jonathan J Ruiz-Ramie
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States
- Department of Kinesiology, Augusta University, Augusta, Georgia, United States
| | - Charles S Schwartz
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States
| | - Do Thuy Uyen Ha Lam
- Centre for Computational Biology, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Prashant Rao
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States
| | - Michael Y Mi
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States
| | - Daniel H Katz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States
| | - Jeremy M Robbins
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States
| | - Clary B Clish
- Metabolomics Platform, Broad Institute, Boston, Massachusetts, United States
| | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States
| | - Mark A Sarzynski
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States
| | - Sujoy Ghosh
- Centre for Computational Biology, Duke-National University of Singapore Medical School, Singapore, Singapore
- Bioinformatics Section, Human Genomics Core, Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States
| |
Collapse
|
4
|
Richards SM, Guo F, Zou H, Nigsch F, Baiges A, Pachori A, Zhang Y, Lens S, Pitts R, Finkel N, Loureiro J, Mongeon D, Ma S, Watkins M, Polus F, Albillos A, Tellez L, Martinez-González J, Bañares R, Turon F, Ferrusquía-Acosta J, Perez-Campuzano V, Magaz M, Forns X, Badman M, Sailer AW, Ukomadu C, Hernández-Gea V, Garcia-Pagán JC. Non-invasive candidate protein signature predicts hepatic venous pressure gradient reduction in cirrhotic patients after sustained virologic response. Liver Int 2023; 43:1984-1994. [PMID: 37443448 DOI: 10.1111/liv.15657] [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: 01/23/2023] [Revised: 06/02/2023] [Accepted: 06/12/2023] [Indexed: 07/15/2023]
Abstract
BACKGROUND AND AIMS A reduction in hepatic venous pressure gradient (HVPG) is the most accurate marker for assessing the severity of portal hypertension and the effectiveness of intervention treatments. This study aimed to evaluate the prognostic potential of blood-based proteomic biomarkers in predicting HVPG response amongst cirrhotic patients with portal hypertension due to Hepatitis C virus (HCV) and had achieved sustained virologic response (SVR). METHODS The study comprised 59 patients from two cohorts. Patients underwent paired HVPG (pretreatment and after SVR), liver stiffness (LSM), and enhanced liver fibrosis scores (ELF) measurements, as well as proteomics-based profiling on serum samples using SomaScan® at baseline (BL) and after SVR (EOS). Machine learning with feature selection (Caret, Random Forest and RPART) methods were performed to determine the proteins capable of classifying HVPG responders. Model performance was evaluated using AUROC (pROC R package). RESULTS Patients were stratified by a change in HVPG (EOS vs. BL) into responders (greater than 20% decline in HVPG from BL, or <10 mmHg at EOS with >10 mmHg at BL) and non-responders. LSM and ELF decreased markedly after SVR but did not correlate with HVPG response. SomaScan (SomaLogic, Inc., Boulder, CO) analysis revealed a substantial shift in the peripheral proteome composition, reflected by 82 significantly differentially abundant proteins. Twelve proteins accurately distinguished responders from non-responders, with an AUROC of .86, sensitivity of 83%, specificity of 83%, accuracy of 83%, PPV of 83%, and NPV of 83%. CONCLUSIONS A combined non-invasive soluble protein signature was identified, capable of accurately predicting HVPG response in HCV liver cirrhosis patients after achieving SVR.
Collapse
Affiliation(s)
| | - Fang Guo
- Novartis Institutes for Biomedical Research, East Hannover, New Jersey, USA
| | - Heng Zou
- Novartis Institutes for Biomedical Research, East Hannover, New Jersey, USA
| | - Florian Nigsch
- Novartis Institutes of Biomedical Research, Basel, Switzerland
| | - Anna Baiges
- Barcelona Hepatic Hemodynamic Laboratory, Barcelona Health Care Provider of the European Reference Network on Rare Liver, Barcelona, Spain
- CIBEREHD (Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas), Barcelona, Spain
- Liver Unit, Hospital Clínic, Institut de Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Departament de Medicina. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona., Barcelona, Spain
| | - Alok Pachori
- Novartis Institutes for Biomedical Research, East Hannover, New Jersey, USA
| | - Yiming Zhang
- Novartis Institutes for Biomedical Research, East Hannover, New Jersey, USA
| | - Sabela Lens
- CIBEREHD (Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas), Barcelona, Spain
- Liver Unit, Hospital Clínic, Institut de Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Departament de Medicina. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona., Barcelona, Spain
| | - Rebecca Pitts
- Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA
| | - Nancy Finkel
- Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA
| | - Joseph Loureiro
- Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA
| | - Dale Mongeon
- Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA
| | - Shenglin Ma
- Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA
| | - Mollie Watkins
- Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA
| | - Florine Polus
- Novartis Institutes of Biomedical Research, Basel, Switzerland
| | - Agustin Albillos
- CIBEREHD (Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas), Barcelona, Spain
- Servicio de Gastroenterología y Hepatología, Hospital Universitario Ramón y Cajal, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain
| | - Luis Tellez
- CIBEREHD (Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas), Barcelona, Spain
- Servicio de Gastroenterología y Hepatología, Hospital Universitario Ramón y Cajal, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain
| | - Javier Martinez-González
- CIBEREHD (Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas), Barcelona, Spain
- Servicio de Gastroenterología y Hepatología, Hospital Universitario Ramón y Cajal, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain
| | - Rafael Bañares
- CIBEREHD (Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas), Barcelona, Spain
- Hospital General Universitario Gregorio Marañón, Facultad de Medicina, Universidad Complutense, Madrid, Spain
| | - Fanny Turon
- Barcelona Hepatic Hemodynamic Laboratory, Barcelona Health Care Provider of the European Reference Network on Rare Liver, Barcelona, Spain
- CIBEREHD (Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas), Barcelona, Spain
- Liver Unit, Hospital Clínic, Institut de Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Departament de Medicina. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona., Barcelona, Spain
| | - José Ferrusquía-Acosta
- Barcelona Hepatic Hemodynamic Laboratory, Barcelona Health Care Provider of the European Reference Network on Rare Liver, Barcelona, Spain
| | - Valeria Perez-Campuzano
- Barcelona Hepatic Hemodynamic Laboratory, Barcelona Health Care Provider of the European Reference Network on Rare Liver, Barcelona, Spain
- CIBEREHD (Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas), Barcelona, Spain
- Liver Unit, Hospital Clínic, Institut de Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Departament de Medicina. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona., Barcelona, Spain
| | - Marta Magaz
- Barcelona Hepatic Hemodynamic Laboratory, Barcelona Health Care Provider of the European Reference Network on Rare Liver, Barcelona, Spain
- CIBEREHD (Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas), Barcelona, Spain
- Liver Unit, Hospital Clínic, Institut de Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Departament de Medicina. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona., Barcelona, Spain
| | - Xavier Forns
- CIBEREHD (Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas), Barcelona, Spain
- Liver Unit, Hospital Clínic, Institut de Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Departament de Medicina. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona., Barcelona, Spain
| | - Michael Badman
- Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA
| | | | - Chinweike Ukomadu
- Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA
| | - Virginia Hernández-Gea
- Barcelona Hepatic Hemodynamic Laboratory, Barcelona Health Care Provider of the European Reference Network on Rare Liver, Barcelona, Spain
- CIBEREHD (Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas), Barcelona, Spain
- Liver Unit, Hospital Clínic, Institut de Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Departament de Medicina. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona., Barcelona, Spain
| | - Juan Carlos Garcia-Pagán
- Barcelona Hepatic Hemodynamic Laboratory, Barcelona Health Care Provider of the European Reference Network on Rare Liver, Barcelona, Spain
- CIBEREHD (Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas), Barcelona, Spain
- Liver Unit, Hospital Clínic, Institut de Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Departament de Medicina. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona., Barcelona, Spain
| |
Collapse
|
5
|
Li Y, Tam WW, Yu Y, Zhuo Z, Xue Z, Tsang C, Qiao X, Wang X, Wang W, Li Y, Tu Y, Gao Y. The application of Aptamer in biomarker discovery. Biomark Res 2023; 11:70. [PMID: 37468977 DOI: 10.1186/s40364-023-00510-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 06/29/2023] [Indexed: 07/21/2023] Open
Abstract
Biomarkers are detectable molecules that can reflect specific physiological states of cells, organs, and organisms and therefore be regarded as indicators for specific diseases. And the discovery of biomarkers plays an essential role in cancer management from the initial diagnosis to the final treatment regime. Practically, reliable clinical biomarkers are still limited, restricted by the suboptimal methods in biomarker discovery. Nucleic acid aptamers nowadays could be used as a powerful tool in the discovery of protein biomarkers. Nucleic acid aptamers are single-strand oligonucleotides that can specifically bind to various targets with high affinity. As artificial ssDNA or RNA, aptamers possess unique advantages compared to conventional antibodies. They can be flexible in design, low immunogenicity, relative chemical/thermos stability, as well as modifying convenience. Several SELEX (Systematic Evolution of Ligands by Exponential Enrichment) based methods have been generated recently to construct aptamers for discovering new biomarkers in different cell locations. Secretome SELEX-based aptamers selection can facilitate the identification of secreted protein biomarkers. The aptamers developed by cell-SELEX can be used to unveil those biomarkers presented on the cell surface. The aptamers from tissue-SELEX could target intracellular biomarkers. And as a multiplexed protein biomarker detection technology, aptamer-based SOMAScan can analyze thousands of proteins in a single run. In this review, we will introduce the principle and workflow of variations of SELEX-based methods, including secretome SELEX, ADAPT, Cell-SELEX and tissue SELEX. Another powerful proteome analyzing tool, SOMAScan, will also be covered. In the second half of this review, how these methods accelerate biomarker discovery in various diseases, including cardiovascular diseases, cancer and neurodegenerative diseases, will be discussed.
Collapse
Affiliation(s)
- Yongshu Li
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China.
- Shenzhen Institute for Technology Innovation, National Institute of Metrology, Shenzhen, China.
| | - Winnie Wailing Tam
- Law Sau Fai Institute for Advancing Translational Medicine in Bone and Joint Diseases (TMBJ), School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
| | - Yuanyuan Yu
- Law Sau Fai Institute for Advancing Translational Medicine in Bone and Joint Diseases (TMBJ), School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China
| | - Zhenjian Zhuo
- State Key Laboratory of Chemical Oncogenomic, Peking University Shenzhen Graduate School, Shenzhen, China
- Laboratory Animal Center, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
| | - Zhichao Xue
- Shenzhen Institute for Technology Innovation, National Institute of Metrology, Shenzhen, China
| | - Chiman Tsang
- Department of Anatomical and Cellular Pathology, State Key Laboratory of Translational Oncology, The Chinese University of Hong Kong, Hong Kong, China
| | - Xiaoting Qiao
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China
| | - Xiaokang Wang
- Department of Pharmacy, Shenzhen Longhua District Central Hospital, Shenzhen, China
| | - Weijing Wang
- Shantou University Medical College, Shantou, China
| | - Yongyi Li
- Laboratory Animal Center, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
| | - Yanyang Tu
- Research Center, Huizhou Central People's Hospital, Guangdong Medical University, Huizhou City, China.
| | - Yunhua Gao
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China.
- Shenzhen Institute for Technology Innovation, National Institute of Metrology, Shenzhen, China.
| |
Collapse
|
6
|
Vorn R, Devoto C, Meier TB, Lai C, Yun S, Broglio SP, Mithani S, McAllister TW, Giza CC, Kim HS, Huber D, Harezlak J, Cameron KL, McGinty G, Jackson J, Guskiewicz KM, Mihalik JP, Brooks A, Duma S, Rowson S, Nelson LD, Pasquina P, McCrea MA, Gill JM. Are EPB41 and alpha-synuclein diagnostic biomarkers of sport-related concussion? Findings from the NCAA and Department of Defense CARE Consortium. JOURNAL OF SPORT AND HEALTH SCIENCE 2023; 12:379-387. [PMID: 36403906 DOI: 10.1016/j.jshs.2022.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Revised: 07/15/2022] [Accepted: 10/08/2022] [Indexed: 05/17/2023]
Abstract
BACKGROUND Current protein biomarkers are only moderately predictive at identifying individuals with mild traumatic brain injury or concussion. Therefore, more accurate diagnostic markers are needed for sport-related concussion. METHODS This was a multicenter, prospective, case-control study of athletes who provided blood samples and were diagnosed with a concussion or were a matched non-concussed control within the National Collegiate Athletic Association-Department of Defense Concussion Assessment, Research, and Education Consortium conducted between 2015 and 2019. The blood was collected within 48 h of injury to identify protein abnormalities at the acute and subacute timepoints. Athletes with concussion were divided into 6 h post-injury (0-6 h post-injury) and after 6 h post-injury (7-48 h post-injury) groups. We applied a highly multiplexed proteomic technique that used a DNA aptamers assay to target 1305 proteins in plasma samples from athletes with and without sport-related concussion. RESULTS A total of 140 athletes with concussion (79.3% males; aged 18.71 ± 1.10 years, mean ± SD) and 21 non-concussed athletes (76.2% males; 19.14 ± 1.10 years) were included in this study. We identified 338 plasma proteins that significantly differed in abundance (319 upregulated and 19 downregulated) in concussed athletes compared to non-concussed athletes. The top 20 most differentially abundant proteins discriminated concussed athletes from non-concussed athletes with an area under the curve (AUC) of 0.954 (95% confidence interval: 0.922‒0.986). Specifically, after 6 h of injury, the individual AUC of plasma erythrocyte membrane protein band 4.1 (EPB41) and alpha-synuclein (SNCA) were 0.956 and 0.875, respectively. The combination of EPB41 and SNCA provided the best AUC (1.000), which suggests this combination of candidate plasma biomarkers is the best for diagnosing concussion in athletes after 6 h of injury. CONCLUSION Our data suggest that proteomic profiling may provide novel diagnostic protein markers and that a combination of EPB41 and SNCA is the most predictive biomarker of concussion after 6 h of injury.
Collapse
Affiliation(s)
- Rany Vorn
- Johns Hopkins School of Nursing and Medicine, Baltimore, MD 21205, USA; National Institutes of Health, Bethesda, MD 20892, USA
| | | | - Timothy B Meier
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Chen Lai
- National Institutes of Health, Bethesda, MD 20892, USA
| | - Sijung Yun
- Predictiv Care, Inc., Mountain View, CA 94086, USA
| | - Steven P Broglio
- Michigan Concussion Center, University of Michigan, Ann Arbor, MI 48109, USA
| | - Sara Mithani
- National Institutes of Health, Bethesda, MD 20892, USA
| | - Thomas W McAllister
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Christopher C Giza
- Departments of Pediatrics and Neurosurgery, University of California at Los Angeles (UCLA), Los Angeles, CA 90024, USA
| | - Hyung-Suk Kim
- National Institutes of Health, Bethesda, MD 20892, USA
| | - Daniel Huber
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Jaroslaw Harezlak
- Department of Epidemiology and Biostatistics School of Public Health - Bloomington, Indiana University, Bloomington, IN 47405, USA
| | - Kenneth L Cameron
- John A. Feagin Sports Medicine Fellowship, Keller Army Community Hospital, West Point, NY 10996, USA
| | - Gerald McGinty
- United States Air Force Academy, Colorado Springs, CO 80840, USA
| | - Jonathan Jackson
- United States Air Force Academy, Colorado Springs, CO 80840, USA
| | - Kevin M Guskiewicz
- Mathew Gfeller Center, Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| | - Jason P Mihalik
- Mathew Gfeller Center, Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| | - Alison Brooks
- Department of Orthopedics, Division of Sports Medicine, School of Medicine and Public Health, University of Wisconsin, Madison, WI 53705, USA
| | - Stefan Duma
- Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA 24061, USA
| | - Steven Rowson
- Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA 24061, USA
| | - Lindsay D Nelson
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Paul Pasquina
- Center for Neuroscience & Regenerative Medicine, Uniformed Services University, Bethesda, MD 20814, USA
| | - Michael A McCrea
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Jessica M Gill
- Johns Hopkins School of Nursing and Medicine, Baltimore, MD 21205, USA.
| |
Collapse
|
7
|
Chen ZZ, Gao Y, Keyes MJ, Deng S, Mi M, Farrell LA, Shen D, Tahir UA, Cruz DE, Ngo D, Benson MD, Robbins JM, Correa A, Wilson JG, Gerszten RE. Protein Markers of Diabetes Discovered in an African American Cohort. Diabetes 2023; 72:532-543. [PMID: 36630488 PMCID: PMC10033249 DOI: 10.2337/db22-0710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 01/05/2023] [Indexed: 01/13/2023]
Abstract
Proteomics has been used to study type 2 diabetes, but the majority of available data are from White participants. Here, we extend prior work by analyzing a large cohort of self-identified African Americans in the Jackson Heart Study (n = 1,313). We found 325 proteins associated with incident diabetes after adjusting for age, sex, and sample batch (false discovery rate q < 0.05) measured using a single-stranded DNA aptamer affinity-based method on fasting plasma samples. A subset was independent of established markers of diabetes development pathways, such as adiposity, glycemia, and/or insulin resistance, suggesting potential novel biological processes associated with disease development. Thirty-six associations remained significant after additional adjustments for BMI, fasting plasma glucose, cholesterol levels, hypertension, statin use, and renal function. Twelve associations, including the top associations of complement factor H, formimidoyltransferase cyclodeaminase, serine/threonine-protein kinase 17B, and high-mobility group protein B1, were replicated in a meta-analysis of two self-identified White cohorts-the Framingham Heart Study and the Malmö Diet and Cancer Study-supporting the generalizability of these biomarkers. A selection of these diabetes-associated proteins also improved risk prediction. Thus, we uncovered both novel and broadly generalizable associations by studying a diverse population, providing a more complete understanding of the diabetes-associated proteome.
Collapse
Affiliation(s)
- Zsu-Zsu Chen
- Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA
- Harvard School of Medicine, Boston, MA
| | - Yan Gao
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS
| | - Michelle J. Keyes
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Shuliang Deng
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Michael Mi
- Harvard School of Medicine, Boston, MA
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Laurie A. Farrell
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Dongxiao Shen
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Usman A. Tahir
- Harvard School of Medicine, Boston, MA
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Daniel E. Cruz
- Harvard School of Medicine, Boston, MA
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Debby Ngo
- Harvard School of Medicine, Boston, MA
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Mark D. Benson
- Harvard School of Medicine, Boston, MA
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Jeremy M. Robbins
- Harvard School of Medicine, Boston, MA
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Adolfo Correa
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS
| | - James G. Wilson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Robert E. Gerszten
- Harvard School of Medicine, Boston, MA
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
- Broad Institute of MIT and Harvard, Boston, MA
| |
Collapse
|
8
|
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.
Collapse
Affiliation(s)
| | | | | | - Jun Pu
- *Correspondence: Yuquan Xie, ; Jun Pu,
| |
Collapse
|
9
|
Hédou J, Cederberg KL, Ambati A, Lin L, Farber N, Dauvilliers Y, Quadri M, Bourgin P, Plazzi G, Andlauer O, Hong SC, Huang YS, Leu-Semenescu S, Arnulf I, Taheri S, Mignot E. Proteomic biomarkers of Kleine-Levin syndrome. Sleep 2022; 45:zsac097. [PMID: 35859339 PMCID: PMC9453623 DOI: 10.1093/sleep/zsac097] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Revised: 03/21/2022] [Indexed: 07/23/2023] Open
Abstract
STUDY OBJECTIVES Kleine-Levin syndrome (KLS) is characterized by relapsing-remitting episodes of hypersomnia, cognitive impairment, and behavioral disturbances. We quantified cerebrospinal fluid (CSF) and serum proteins in KLS cases and controls. METHODS SomaScan was used to profile 1133 CSF proteins in 30 KLS cases and 134 controls, while 1109 serum proteins were profiled in serum from 26 cases and 65 controls. CSF and serum proteins were both measured in seven cases. Univariate and multivariate analyses were used to find differentially expressed proteins (DEPs). Pathway and tissue enrichment analyses (TEAs) were performed on DEPs. RESULTS Univariate analyses found 28 and 141 proteins differentially expressed in CSF and serum, respectively (false discovery rate <0.1%). Upregulated CSF proteins included IL-34, IL-27, TGF-b, IGF-1, and osteonectin, while DKK4 and vWF were downregulated. Pathway analyses revealed microglial alterations and disrupted blood-brain barrier permeability. Serum profiles show upregulation of Src-family kinases (SFKs), proteins implicated in cellular growth, motility, and activation. TEA analysis of up- and downregulated proteins revealed changes in brain proteins (p < 6 × 10-5), notably from the pons, medulla, and midbrain. A multivariate machine-learning classifier performed robustly, achieving a receiver operating curve area under the curve of 0.90 (95% confidence interval [CI] = 0.78-1.0, p = 0.0006) in CSF and 1.0 (95% CI = 1.0-1.0, p = 0.0002) in serum in validation cohorts, with some commonality across tissues, as the model trained on serum sample also discriminated CSF samples of controls versus KLS cases. CONCLUSIONS Our study identifies proteomic KLS biomarkers with diagnostic potential and provides insight into biological mechanisms that will guide future research in KLS.
Collapse
Affiliation(s)
- Julien Hédou
- Department of Psychiatry and Behavioral Sciences, Center for Sleep Sciences and Medicine, Stanford University, Palo Alto, CA, USA
| | - Katie L Cederberg
- Department of Psychiatry and Behavioral Sciences, Center for Sleep Sciences and Medicine, Stanford University, Palo Alto, CA, USA
| | - Aditya Ambati
- Department of Psychiatry and Behavioral Sciences, Center for Sleep Sciences and Medicine, Stanford University, Palo Alto, CA, USA
| | - Ling Lin
- Department of Psychiatry and Behavioral Sciences, Center for Sleep Sciences and Medicine, Stanford University, Palo Alto, CA, USA
| | - Neal Farber
- Kleine-Levin Syndrome Foundation, Boston, MA, USA
| | - Yves Dauvilliers
- National Reference Centre for Orphan Diseases, Narcolepsy-Rare Hypersomnias, Sleep Unit, Department of Neurology, CHU Montpellier, Univ Montpellier, Montpellier, France
- Department of Neurology, Institute for Neurosciences of Montpellier INM, Univ Montpellier, INSERM, Montpellier, France
| | | | - Patrice Bourgin
- Sleep Disorders Center, Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | - Giuseppe Plazzi
- Department of Biomedical and Neuromotor Sciences, University of Bologna and IRCCS Institute of Neurological Sciences, Bologna, Italy
| | | | - Seung-Chul Hong
- Department of Psychiatry, St. Vincent’s Hospital, Catholic University of Korea, Seoul, South Korea
| | - Yu-Shu Huang
- Department of Child Psychiatry and Sleep Center, Chang Gung Memorial Hospital and University, Taoyuan, Taiwan
| | - Smaranda Leu-Semenescu
- Sleep Disorders, Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris-Sorbonne, National Reference Center for Narcolepsy, Idiopathic Hypersomnia and Kleine-Levin Syndrome, Paris, France
| | - Isabelle Arnulf
- Sleep Disorders, Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris-Sorbonne, National Reference Center for Narcolepsy, Idiopathic Hypersomnia and Kleine-Levin Syndrome, Paris, France
- Sorbonne University, Institut Hospitalo-Universitaire, Institut du Cerveau et de la Moelle, Paris, France
| | - Shahrad Taheri
- Department of Medicine and Clinical Research Core, Weill Cornell Medicine—Qatar, Qatar Foundation—Education City, Doha, Qatar
| | - Emmanuel Mignot
- Corresponding author. Emmanuel Mignot, Center for Narcolepsy and Related Disorders, Stanford University, 3165 Porter Drive, Palo Alto, CA 94305, USA.
| |
Collapse
|
10
|
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: 53] [Impact Index Per Article: 26.5] [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.
Collapse
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
| |
Collapse
|
11
|
Cederberg KLJ, Hanif U, Peris Sempere V, Hédou J, Leary EB, Schneider LD, Lin L, Zhang J, Morse AM, Blackman A, Schweitzer PK, Kotagal S, Bogan R, Kushida CA, Ju YES, Petousi N, Turnbull CD, Mignot E. Proteomic Biomarkers of the Apnea Hypopnea Index and Obstructive Sleep Apnea: Insights into the Pathophysiology of Presence, Severity, and Treatment Response. Int J Mol Sci 2022; 23:7983. [PMID: 35887329 PMCID: PMC9317550 DOI: 10.3390/ijms23147983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 07/11/2022] [Accepted: 07/17/2022] [Indexed: 11/16/2022] Open
Abstract
Obstructive sleep apnea (OSA), a disease associated with excessive sleepiness and increased cardiovascular risk, affects an estimated 1 billion people worldwide. The present study examined proteomic biomarkers indicative of presence, severity, and treatment response in OSA. Participants (n = 1391) of the Stanford Technology Analytics and Genomics in Sleep study had blood collected and completed an overnight polysomnography for scoring the apnea−hypopnea index (AHI). A highly multiplexed aptamer-based array (SomaScan) was used to quantify 5000 proteins in all plasma samples. Two separate intervention-based cohorts with sleep apnea (n = 41) provided samples pre- and post-continuous/positive airway pressure (CPAP/PAP). Multivariate analyses identified 84 proteins (47 positively, 37 negatively) associated with AHI after correction for multiple testing. Of the top 15 features from a machine learning classifier for AHI ≥ 15 vs. AHI < 15 (Area Under the Curve (AUC) = 0.74), 8 were significant markers of both AHI and OSA from multivariate analyses. Exploration of pre- and post-intervention analysis identified 5 of the 84 proteins to be significantly decreased following CPAP/PAP treatment, with pathways involving endothelial function, blood coagulation, and inflammatory response. The present study identified PAI-1, tPA, and sE-Selectin as key biomarkers and suggests that endothelial dysfunction and increased coagulopathy are important consequences of OSA, which may explain the association with cardiovascular disease and stroke.
Collapse
Affiliation(s)
- Katie L. J. Cederberg
- Department of Psychiatry and Behavioral Sciences, Stanford University, 3165 Porter Drive, Stanford, CA 94304, USA; (K.L.J.C.); (U.H.); (V.P.S.); (J.H.); (E.B.L.); (L.D.S.); (L.L.); (J.Z.); (C.A.K.)
| | - Umaer Hanif
- Department of Psychiatry and Behavioral Sciences, Stanford University, 3165 Porter Drive, Stanford, CA 94304, USA; (K.L.J.C.); (U.H.); (V.P.S.); (J.H.); (E.B.L.); (L.D.S.); (L.L.); (J.Z.); (C.A.K.)
- Biomedical Signal Processing & AI Research Group, Department of Health Technology, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
- Danish Center for Sleep Medicine, Department of Clinical Neurophysiology, 2600 Glostrup, Denmark
| | - Vicente Peris Sempere
- Department of Psychiatry and Behavioral Sciences, Stanford University, 3165 Porter Drive, Stanford, CA 94304, USA; (K.L.J.C.); (U.H.); (V.P.S.); (J.H.); (E.B.L.); (L.D.S.); (L.L.); (J.Z.); (C.A.K.)
| | - Julien Hédou
- Department of Psychiatry and Behavioral Sciences, Stanford University, 3165 Porter Drive, Stanford, CA 94304, USA; (K.L.J.C.); (U.H.); (V.P.S.); (J.H.); (E.B.L.); (L.D.S.); (L.L.); (J.Z.); (C.A.K.)
| | - Eileen B. Leary
- Department of Psychiatry and Behavioral Sciences, Stanford University, 3165 Porter Drive, Stanford, CA 94304, USA; (K.L.J.C.); (U.H.); (V.P.S.); (J.H.); (E.B.L.); (L.D.S.); (L.L.); (J.Z.); (C.A.K.)
- Jazz Pharmaceuticals, 3170 Porter Drive, Palo Alto, CA 94304, USA
| | - Logan D. Schneider
- Department of Psychiatry and Behavioral Sciences, Stanford University, 3165 Porter Drive, Stanford, CA 94304, USA; (K.L.J.C.); (U.H.); (V.P.S.); (J.H.); (E.B.L.); (L.D.S.); (L.L.); (J.Z.); (C.A.K.)
- Alphabet, Inc., 1600 Amphitheater Parkway Mountain View, Palo Alto, CA 94043, USA
- Stanford/VA Alzheimer’s Research Center, 3801 Miranda Ave, Building 4, C-141, Mail Code 116F-PAD, Palo Alto, CA 94304, USA
| | - Ling Lin
- Department of Psychiatry and Behavioral Sciences, Stanford University, 3165 Porter Drive, Stanford, CA 94304, USA; (K.L.J.C.); (U.H.); (V.P.S.); (J.H.); (E.B.L.); (L.D.S.); (L.L.); (J.Z.); (C.A.K.)
| | - Jing Zhang
- Department of Psychiatry and Behavioral Sciences, Stanford University, 3165 Porter Drive, Stanford, CA 94304, USA; (K.L.J.C.); (U.H.); (V.P.S.); (J.H.); (E.B.L.); (L.D.S.); (L.L.); (J.Z.); (C.A.K.)
| | - Anne M. Morse
- Division of Child Neurology and Pediatric Sleep Medicine, Geisinger, Janet Weis Children’s Hospital, 100 N Academy Ave, Danville, PA 17822, USA;
| | - Adam Blackman
- Department of Psychiatry, University of Toronto, Toronto, ON M5G 1L5, Canada;
| | - Paula K. Schweitzer
- Sleep Medicine & Research Center, St. Lukes Hospital, 232 S. Woods Mill Road, Chesterfield, MO 63017, USA;
| | - Suresh Kotagal
- Department of Neurology, Mayo Clinic, 200 First St., Rochester, MN 55905, USA;
| | - Richard Bogan
- College of Medicine, Medical University of South Carolina, 171 Ashley Ave, Charleston, SC 29425, USA;
| | - Clete A. Kushida
- Department of Psychiatry and Behavioral Sciences, Stanford University, 3165 Porter Drive, Stanford, CA 94304, USA; (K.L.J.C.); (U.H.); (V.P.S.); (J.H.); (E.B.L.); (L.D.S.); (L.L.); (J.Z.); (C.A.K.)
| | - Yo-El S. Ju
- Department of Neurology, Washington University, St. Louis, MO 63110, USA;
- Hope Center for Neurological Disorders, Washington University, St. Louis, MO 63110, USA
- Center on Biological Rhythms and Sleep (COBRAS), Washington University, 1600 S. Brentwood Blvd, St. Louis, MO 63144, USA
| | - Nayia Petousi
- Experimental Medicine Division, Nuffield Department of Medicine, University of Oxford, Headley Way, Headington, Oxford OX3 9DU, UK;
- National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Headley Way, Headington, Oxford OX3 9DU, UK;
- Oxford Centre for Respiratory Medicine, Oxford University Hospitals NHS Foundation Trust, Headley Way, Headington, Oxford OX3 9DU, UK
| | - Chris D. Turnbull
- National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Headley Way, Headington, Oxford OX3 9DU, UK;
- Oxford Centre for Respiratory Medicine, Oxford University Hospitals NHS Foundation Trust, Headley Way, Headington, Oxford OX3 9DU, UK
| | - Emmanuel Mignot
- Department of Psychiatry and Behavioral Sciences, Stanford University, 3165 Porter Drive, Stanford, CA 94304, USA; (K.L.J.C.); (U.H.); (V.P.S.); (J.H.); (E.B.L.); (L.D.S.); (L.L.); (J.Z.); (C.A.K.)
| | | |
Collapse
|
12
|
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
Collapse
|
13
|
SARZYNSKI MARKA, RICE TREVAK, DESPRÉS JEANPIERRE, PÉRUSSE LOUIS, TREMBLAY ANGELO, STANFORTH PHILIPR, TCHERNOF ANDRÉ, BARBER JACOBL, FALCIANI FRANCESCO, CLISH CLARY, ROBBINS JEREMYM, GHOSH SUJOY, GERSZTEN ROBERTE, LEON ARTHURS, SKINNER JAMESS, RAO DC, BOUCHARD CLAUDE. The HERITAGE Family Study: A Review of the Effects of Exercise Training on Cardiometabolic Health, with Insights into Molecular Transducers. Med Sci Sports Exerc 2022; 54:S1-S43. [PMID: 35611651 PMCID: PMC9012529 DOI: 10.1249/mss.0000000000002859] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The aim of the HERITAGE Family Study was to investigate individual differences in response to a standardized endurance exercise program, the role of familial aggregation, and the genetics of response levels of cardiorespiratory fitness and cardiovascular disease and diabetes risk factors. Here we summarize the findings and their potential implications for cardiometabolic health and cardiorespiratory fitness. It begins with overviews of background and planning, recruitment, testing and exercise program protocol, quality control measures, and other relevant organizational issues. A summary of findings is then provided on cardiorespiratory fitness, exercise hemodynamics, insulin and glucose metabolism, lipid and lipoprotein profiles, adiposity and abdominal visceral fat, blood levels of steroids and other hormones, markers of oxidative stress, skeletal muscle morphology and metabolic indicators, and resting metabolic rate. These summaries document the extent of the individual differences in response to a standardized and fully monitored endurance exercise program and document the importance of familial aggregation and heritability level for exercise response traits. Findings from genomic markers, muscle gene expression studies, and proteomic and metabolomics explorations are reviewed, along with lessons learned from a bioinformatics-driven analysis pipeline. The new opportunities being pursued in integrative -omics and physiology have extended considerably the expected life of HERITAGE and are being discussed in relation to the original conceptual model of the study.
Collapse
Affiliation(s)
- MARK A. SARZYNSKI
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC
| | - TREVA K. RICE
- Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO
| | - JEAN-PIERRE DESPRÉS
- Department of Kinesiology, Faculty of Medicine, Laval University, Quebec, QC, CANADA
- Quebec Heart and Lung Institute Research Center, Laval University, Québec, QC, CANADA
| | - LOUIS PÉRUSSE
- Department of Kinesiology, Faculty of Medicine, Laval University, Quebec, QC, CANADA
- Institute of Nutrition and Functional Foods (INAF), Laval University, Quebec, QC, CANADA
| | - ANGELO TREMBLAY
- Department of Kinesiology, Faculty of Medicine, Laval University, Quebec, QC, CANADA
- Institute of Nutrition and Functional Foods (INAF), Laval University, Quebec, QC, CANADA
| | - PHILIP R. STANFORTH
- Department of Kinesiology and Health Education, University of Texas at Austin, Austin, TX
| | - ANDRÉ TCHERNOF
- Quebec Heart and Lung Institute Research Center, Laval University, Québec, QC, CANADA
- School of Nutrition, Laval University, Quebec, QC, CANADA
| | - JACOB L. BARBER
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC
| | - FRANCESCO FALCIANI
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UNITED KINGDOM
| | - CLARY CLISH
- Metabolomics Platform, Broad Institute and Harvard Medical School, Boston, MA
| | - JEREMY M. ROBBINS
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
- Cardiovascular Research Center, Beth Israel Deaconess Medical Center, Boston, MA
| | - SUJOY GHOSH
- Cardiovascular and Metabolic Disorders Program and Centre for Computational Biology, Duke-National University of Singapore Medical School, SINGAPORE
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA
| | - ROBERT E. GERSZTEN
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
- Cardiovascular Research Center, Beth Israel Deaconess Medical Center, Boston, MA
| | - ARTHUR S. LEON
- School of Kinesiology, University of Minnesota, Minneapolis, MN
| | | | - D. C. RAO
- Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO
| | - CLAUDE BOUCHARD
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA
| |
Collapse
|
14
|
Recent Developments in Clinical Plasma Proteomics—Applied to Cardiovascular Research. Biomedicines 2022; 10:biomedicines10010162. [PMID: 35052841 PMCID: PMC8773619 DOI: 10.3390/biomedicines10010162] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 01/05/2022] [Accepted: 01/12/2022] [Indexed: 01/27/2023] Open
Abstract
The human plasma proteome mirrors the physiological state of the cardiovascular system, a fact that has been used to analyze plasma biomarkers in routine analysis for the diagnosis and monitoring of cardiovascular diseases for decades. These biomarkers address, however, only a very limited subset of cardiovascular diseases, such as acute myocardial infarct or acute deep vein thrombosis, and clinical plasma biomarkers for the diagnosis and stratification cardiovascular diseases that are growing in incidence, such as heart failure and abdominal aortic aneurysm, do not exist and are urgently needed. The discovery of novel biomarkers in plasma has been hindered by the complexity of the human plasma proteome that again transforms into an extreme analytical complexity when it comes to the discovery of novel plasma biomarkers. This complexity is, however, addressed by recent achievements in technologies for analyzing the human plasma proteome, thereby facilitating the possibility for novel biomarker discoveries. The aims of this article is to provide an overview of the recent achievements in technologies for proteomic analysis of the human plasma proteome and their applications in cardiovascular medicine.
Collapse
|
15
|
Corey KE, Pitts R, Lai M, Loureiro J, Masia R, Osganian SA, Gustafson JL, Hutter MM, Gee DW, Meireles OR, Witkowski ER, Richards SM, Jacob J, Finkel N, Ngo D, Wang TJ, Gerszten RE, Ukomadu C, Jennings LL. ADAMTSL2 protein and a soluble biomarker signature identify at-risk non-alcoholic steatohepatitis and fibrosis in adults with NAFLD. J Hepatol 2022; 76:25-33. [PMID: 34600973 PMCID: PMC8688231 DOI: 10.1016/j.jhep.2021.09.026] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 09/14/2021] [Accepted: 09/18/2021] [Indexed: 01/03/2023]
Abstract
BACKGROUND & AIMS Identifying fibrosis in non-alcoholic fatty liver disease (NAFLD) is essential to predict liver-related outcomes and guide treatment decisions. A protein-based signature of fibrosis could serve as a valuable, non-invasive diagnostic tool. This study sought to identify circulating proteins associated with fibrosis in NAFLD. METHODS We used aptamer-based proteomics to measure 4,783 proteins in 2 cohorts (Cohort A and B). Targeted, quantitative assays coupling aptamer-based protein pull down and mass spectrometry (SPMS) validated the profiling results in a bariatric and NAFLD cohort (Cohort C and D, respectively). Generalized linear modeling-logistic regression assessed the ability of candidate proteins to classify fibrosis. RESULTS From the multiplex profiling, 16 proteins differed significantly by fibrosis in cohorts A (n = 62) and B (n = 98). Quantitative and robust SPMS assays were developed for 8 proteins and validated in Cohorts C (n = 71) and D (n = 84). The A disintegrin and metalloproteinase with thrombospondin motifs like 2 (ADAMTSL2) protein accurately distinguished non-alcoholic fatty liver (NAFL)/non-alcoholic steatohepatitis (NASH) with fibrosis stage 0-1 (F0-1) from at-risk NASH with fibrosis stage 2-4, with AUROCs of 0.83 and 0.86 in Cohorts C and D, respectively, and from NASH with significant fibrosis (F2-3), with AUROCs of 0.80 and 0.83 in Cohorts C and D, respectively. An 8-protein panel distinguished NAFL/NASH F0-1 from at-risk NASH (AUROCs 0.90 and 0.87 in Cohort C and D, respectively) and NASH F2-3 (AUROCs 0.89 and 0.83 in Cohorts C and D, respectively). The 8-protein panel and ADAMTSL2 protein had superior performance to the NAFLD fibrosis score and fibrosis-4 score. CONCLUSION The ADAMTSL2 protein and an 8-protein soluble biomarker panel are highly associated with at-risk NASH and significant fibrosis; they exhibited superior diagnostic performance compared to standard of care fibrosis scores. LAY SUMMARY Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of liver disease worldwide. Diagnosing NAFLD and identifying fibrosis (scarring of the liver) currently requires a liver biopsy. Our study identified novel proteins found in the blood which may identify fibrosis without the need for a liver biopsy.
Collapse
Affiliation(s)
- Kathleen E. Corey
- Division of Gastroenterology, Massachusetts General Hospital (MGH) and Harvard Medical School (HMS), Boston, MA, USA
| | - Rebecca Pitts
- Novartis Institutes for BioMedical Research, Cambridge, MA, USA
| | - Michelle Lai
- Division of Hepatology, Beth Israel Deaconess Hospital (BIDMC) and HMS, Boston, MA, USA
| | - Joseph Loureiro
- Novartis Institutes for BioMedical Research, Cambridge, MA, USA
| | - Ricard Masia
- Department of Pathology, MGH and HMS, Boston, MA, USA
| | - Stephanie A. Osganian
- Division of Gastroenterology, Massachusetts General Hospital (MGH) and Harvard Medical School (HMS), Boston, MA, USA
| | - Jenna L. Gustafson
- Division of Gastroenterology, Massachusetts General Hospital (MGH) and Harvard Medical School (HMS), Boston, MA, USA
| | | | | | | | | | | | - Jaison Jacob
- Novartis Institutes for BioMedical Research, Cambridge, MA, USA
| | - Nancy Finkel
- Novartis Institutes for BioMedical Research, Cambridge, MA, USA
| | - Debby Ngo
- Department of Pulmonary/Critical Care, Cardiovascular Institute, BIDMC and HMS, Boston, MA, USA
| | - Thomas J Wang
- Department of Cardiology, Vanderbilt University School of Medicine, Nashville, TN USA
| | - Robert E. Gerszten
- Division of Cardiovascular Medicine and Cardiovascular Institute, BIDMC and HMS, Boston, MA, USA
| | | | | |
Collapse
|
16
|
Hartl D, de Luca V, Kostikova A, Laramie J, Kennedy S, Ferrero E, Siegel R, Fink M, Ahmed S, Millholland J, Schuhmacher A, Hinder M, Piali L, Roth A. Translational precision medicine: an industry perspective. J Transl Med 2021; 19:245. [PMID: 34090480 PMCID: PMC8179706 DOI: 10.1186/s12967-021-02910-6] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 05/25/2021] [Indexed: 02/08/2023] Open
Abstract
In the era of precision medicine, digital technologies and artificial intelligence, drug discovery and development face unprecedented opportunities for product and business model innovation, fundamentally changing the traditional approach of how drugs are discovered, developed and marketed. Critical to this transformation is the adoption of new technologies in the drug development process, catalyzing the transition from serendipity-driven to data-driven medicine. This paradigm shift comes with a need for both translation and precision, leading to a modern Translational Precision Medicine approach to drug discovery and development. Key components of Translational Precision Medicine are multi-omics profiling, digital biomarkers, model-based data integration, artificial intelligence, biomarker-guided trial designs and patient-centric companion diagnostics. In this review, we summarize and critically discuss the potential and challenges of Translational Precision Medicine from a cross-industry perspective.
Collapse
Affiliation(s)
- Dominik Hartl
- Novartis Institutes for BioMedical Research, Basel, Switzerland.
- Department of Pediatrics I, University of Tübingen, Tübingen, Germany.
| | - Valeria de Luca
- Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Anna Kostikova
- Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Jason Laramie
- Novartis Institutes for BioMedical Research, Cambridge, MA, USA
| | - Scott Kennedy
- Novartis Institutes for BioMedical Research, Cambridge, MA, USA
| | - Enrico Ferrero
- Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Richard Siegel
- Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Martin Fink
- Novartis Institutes for BioMedical Research, Basel, Switzerland
| | | | | | | | - Markus Hinder
- Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Luca Piali
- Roche Innovation Center Basel, Basel, Switzerland
| | - Adrian Roth
- Roche Innovation Center Basel, Basel, Switzerland
| |
Collapse
|
17
|
Robbins JM, Peterson B, Schranner D, Tahir UA, Rienmüller T, Deng S, Keyes MJ, Katz DH, Beltran PMJ, Barber JL, Baumgartner C, Carr SA, Ghosh S, Shen C, Jennings LL, Ross R, Sarzynski MA, Bouchard C, Gerszten RE. Human plasma proteomic profiles indicative of cardiorespiratory fitness. Nat Metab 2021; 3:786-797. [PMID: 34045743 PMCID: PMC9216203 DOI: 10.1038/s42255-021-00400-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Accepted: 04/26/2021] [Indexed: 12/16/2022]
Abstract
Maximal oxygen uptake (VO2max) is a direct measure of human cardiorespiratory fitness and is associated with health. However, the molecular determinants of interindividual differences in baseline (intrinsic) VO2max, and of increases of VO2max in response to exercise training (ΔVO2max), are largely unknown. Here, we measure ~5,000 plasma proteins using an affinity-based platform in over 650 sedentary adults before and after a 20-week endurance-exercise intervention and identify 147 proteins and 102 proteins whose plasma levels are associated with baseline VO2max and ΔVO2max, respectively. Addition of a protein biomarker score derived from these proteins to a score based on clinical traits improves the prediction of an individual's ΔVO2max. We validate findings in a separate exercise cohort, further link 21 proteins to incident all-cause mortality in a community-based cohort and reproduce the specificity of ~75% of our key findings using antibody-based assays. Taken together, our data shed light on biological pathways relevant to cardiorespiratory fitness and highlight the potential additive value of protein biomarkers in identifying exercise responsiveness in humans.
Collapse
Affiliation(s)
- Jeremy M Robbins
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Bennet Peterson
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Daniela Schranner
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Exercise Biology Group, Faculty of Sports and Health Sciences, Technical University of Munich, Munich, Germany
| | - Usman A Tahir
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Theresa Rienmüller
- Institute of Health Care Engineering with Testing Center of Medical Devices, Graz University of Technology, Graz, Austria
| | - Shuliang Deng
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Michelle J Keyes
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
- National Heart, Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
| | - Daniel H Katz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | - Jacob L Barber
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
| | - Christian Baumgartner
- Institute of Health Care Engineering with Testing Center of Medical Devices, Graz University of Technology, Graz, Austria
| | - Steven A Carr
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sujoy Ghosh
- Cardiovascular & Metabolic Disorders Program and Center for Computational Biology, Duke-NUS Graduate Medical School, Singapore, Singapore
| | - Changyu Shen
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Lori L Jennings
- Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | - Robert Ross
- School of Kinesiology and Health Studies, Queen's University, Kingston, Ontario, Canada
| | - Mark A Sarzynski
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA
| | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| |
Collapse
|
18
|
Joshi A, Rienks M, Theofilatos K, Mayr M. Systems biology in cardiovascular disease: a multiomics approach. Nat Rev Cardiol 2021; 18:313-330. [PMID: 33340009 DOI: 10.1038/s41569-020-00477-1] [Citation(s) in RCA: 108] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/02/2020] [Indexed: 12/13/2022]
Abstract
Omics techniques generate large, multidimensional data that are amenable to analysis by new informatics approaches alongside conventional statistical methods. Systems theories, including network analysis and machine learning, are well placed for analysing these data but must be applied with an understanding of the relevant biological and computational theories. Through applying these techniques to omics data, systems biology addresses the problems posed by the complex organization of biological processes. In this Review, we describe the techniques and sources of omics data, outline network theory, and highlight exemplars of novel approaches that combine gene regulatory and co-expression networks, proteomics, metabolomics, lipidomics and phenomics with informatics techniques to provide new insights into cardiovascular disease. The use of systems approaches will become necessary to integrate data from more than one omic technique. Although understanding the interactions between different omics data requires increasingly complex concepts and methods, we argue that hypothesis-driven investigations and independent validation must still accompany these novel systems biology approaches to realize their full potential.
Collapse
Affiliation(s)
- Abhishek Joshi
- King's British Heart Foundation Centre, King's College London, London, UK
- Bart's Heart Centre, St. Bartholomew's Hospital, London, UK
| | - Marieke Rienks
- King's British Heart Foundation Centre, King's College London, London, UK
| | | | - Manuel Mayr
- King's British Heart Foundation Centre, King's College London, London, UK.
| |
Collapse
|
19
|
Huang J, Chen X, Fu X, Li Z, Huang Y, Liang C. Advances in Aptamer-Based Biomarker Discovery. Front Cell Dev Biol 2021; 9:659760. [PMID: 33796540 PMCID: PMC8007916 DOI: 10.3389/fcell.2021.659760] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 02/23/2021] [Indexed: 12/12/2022] Open
Abstract
The discovery and identification of biomarkers promote the rational and fast development of medical diagnosis and therapeutics. Clinically, the application of ideal biomarkers still is limited due to the suboptimal technology in biomarker discovery. Aptamers are single-stranded deoxyribonucleic acid or ribonucleic acid molecules and can selectively bind to varied targets with high affinity and specificity. Compared with antibody, aptamers have desirable advantages, such as flexible design, easy synthesis and convenient modification with different functional groups. Currently, different aptamer-based technologies have been developed to facilitate biomarker discovery, especially CELL-SELEX and SOMAScan technology. CELL-SELEX technology is mainly used to identify cell membrane surface biomarkers of various cells. SOMAScan technology is an unbiased biomarker detection method that can analyze numerous and even thousands of proteins in complex biological samples at the same time. It has now become a large-scale multi-protein biomarker discovery platform. In this review, we introduce the aptamer-based biomarker discovery technologies, and summarize and highlight the discovered emerging biomarkers recently in several diseases.
Collapse
Affiliation(s)
- Jie Huang
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
| | - Xinxin Chen
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
| | - Xuekun Fu
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
| | - Zheng Li
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
| | - Yuhong Huang
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
| | - Chao Liang
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
| |
Collapse
|
20
|
Ngo D, Benson MD, Long JZ, Chen ZZ, Wang R, Nath AK, Keyes MJ, Shen D, Sinha S, Kuhn E, Morningstar JE, Shi X, Peterson BD, Chan C, Katz DH, Tahir UA, Farrell LA, Melander O, Mosley JD, Carr SA, Vasan RS, Larson MG, Smith JG, Wang TJ, Yang Q, Gerszten RE. Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk. JCI Insight 2021; 6:144392. [PMID: 33591955 PMCID: PMC8021115 DOI: 10.1172/jci.insight.144392] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 01/28/2021] [Indexed: 01/14/2023] Open
Abstract
Recent advances in proteomic technologies have made high-throughput profiling of low-abundance proteins in large epidemiological cohorts increasingly feasible. We investigated whether aptamer-based proteomic profiling could identify biomarkers associated with future development of type 2 diabetes (T2DM) beyond known risk factors. We identified dozens of markers with highly significant associations with future T2DM across 2 large longitudinal cohorts (n = 2839) followed for up to 16 years. We leveraged proteomic, metabolomic, genetic, and clinical data from humans to nominate 1 specific candidate to test for potential causal relationships in model systems. Our studies identified functional effects of aminoacylase 1 (ACY1), a top protein association with future T2DM risk, on amino acid metabolism and insulin homeostasis in vitro and in vivo. Furthermore, a loss-of-function variant associated with circulating levels of the biomarker WAP, Kazal, immunoglobulin, Kunitz, and NTR domain-containing protein 2 (WFIKKN2) was, in turn, associated with fasting glucose, hemoglobin A1c, and HOMA-IR measurements in humans. In addition to identifying potentially novel disease markers and pathways in T2DM, we provide publicly available data to be leveraged for insights about gene function and disease pathogenesis in the context of human metabolism.
Collapse
Affiliation(s)
- Debby Ngo
- Cardiovascular Institute
- Division of Pulmonary, Critical Care and Sleep Medicine, and
| | - Mark D. Benson
- Cardiovascular Institute
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (BIDMC), Boston, Massachusetts, USA
| | - Jonathan Z. Long
- Department of Pathology, Stanford University, Stanford, California, USA
| | - Zsu-Zsu Chen
- Cardiovascular Institute
- Division of Endocrinology, Diabetes and Metabolism, BIDMC, Boston, Massachusetts, USA
| | - Ruiqi Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | | | | | | | | | - Eric Kuhn
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | | | | | | | | | - Daniel H. Katz
- Cardiovascular Institute
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (BIDMC), Boston, Massachusetts, USA
| | - Usman A. Tahir
- Cardiovascular Institute
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (BIDMC), Boston, Massachusetts, USA
| | | | - Olle Melander
- Department of Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden
| | - Jonathan D. Mosley
- Departments of Medicine and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Steven A. Carr
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Ramachandran S. Vasan
- Department of Medicine, Divisions of Preventive Medicine and Cardiology, Boston University School of Medicine, Boston, Massachusetts, USA
- The National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts, USA
| | - Martin G. Larson
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
- The National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts, USA
| | - J. Gustav Smith
- Department of Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden
- Wallenberg Center for Molecular Medicine and Diabetes Center, Lund University, Lund, Sweden
- Department of Cardiology and Wallenberg Laboratory, Gothenburg University and Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Thomas J. Wang
- Department of Medicine, University of Texas, Southwestern Medical Center, Dallas, Texas, USA
| | - Qiong Yang
- Division of Endocrinology, Diabetes and Metabolism, BIDMC, Boston, Massachusetts, USA
| | - Robert E. Gerszten
- Cardiovascular Institute
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center (BIDMC), Boston, Massachusetts, USA
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| |
Collapse
|
21
|
Abstract
Atherosclerotic cardiovascular disease (ASCVD) proceeds through a series of stages: initiation, progression (or regression), and complications. By integrating known biology regarding molecular signatures of each stage with recent advances in high-dimensional molecular data acquisition platforms (to assay the genome, epigenome, transcriptome, proteome, metabolome, and gut microbiome), snapshots of each phase of atherosclerotic cardiovascular disease development can be captured. In this review, we will summarize emerging approaches for assessment of atherosclerotic cardiovascular disease risk in humans using peripheral blood molecular signatures and molecular imaging approaches. We will then discuss the potential (and challenges) for these snapshots to be integrated into a personalized movie providing dynamic readouts of an individual's atherosclerotic cardiovascular disease risk status throughout the life course.
Collapse
Affiliation(s)
- Matthew Nayor
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Kemar J. Brown
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Ramachandran S. Vasan
- Sections of Preventive Medicine & Epidemiology, and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, MA; Department of Epidemiology, Boston University School of Public Health; Boston University Center for Computing and Data Sciences
| |
Collapse
|
22
|
Plasma protein expression profiles, cardiovascular disease, and religious struggles among South Asians in the MASALA study. Sci Rep 2021; 11:961. [PMID: 33441605 PMCID: PMC7806901 DOI: 10.1038/s41598-020-79429-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 12/07/2020] [Indexed: 11/12/2022] Open
Abstract
Blood protein concentrations are clinically useful, predictive biomarkers of cardiovascular disease (CVD). Despite a higher burden of CVD among U.S. South Asians, no CVD-related proteomics study has been conducted in this sub-population. The aim of this study is to investigate the associations between plasma protein levels and CVD incidence, and to assess the potential influence of religiosity/spirituality (R/S) on significant protein-CVD associations, in South Asians from the MASALA Study. We used a nested case–control design of 50 participants with incident CVD and 50 sex- and age-matched controls. Plasma samples were analyzed by SOMAscan for expression of 1305 proteins. Multivariable logistic regression models and model selection using Akaike Information Criteria were performed on the proteins and clinical covariates, with further effect modification analyses conducted to assess the influence of R/S measures on significant associations between proteins and incident CVD events. We identified 36 proteins that were significantly expressed differentially among CVD cases compared to matched controls. These proteins are involved in immune cell recruitment, atherosclerosis, endothelial cell differentiation, and vascularization. A final multivariable model found three proteins (Contactin-5 [CNTN5], Low affinity immunoglobulin gamma Fc region receptor II-a [FCGR2A], and Complement factor B [CFB]) associated with incident CVD after adjustment for diabetes (AUC = 0.82). Religious struggles that exacerbate the adverse impact of stressful life events, significantly modified the effect of Contactin-5 and Complement factor B on risk of CVD. Our research is this first assessment of the relationship between protein concentrations and risk of CVD in a South Asian sample. Further research is needed to understand patterns of proteomic profiles across diverse ethnic communities, and the influence of resources for resiliency on proteomic signatures and ultimately, risk of CVD.
Collapse
|
23
|
YANG JW, WANG CY, LUO L, GUO L, XIE JW. Applications and Prospects of Oligonucleotide Aptamers in Mass Spectrometry. CHINESE JOURNAL OF ANALYTICAL CHEMISTRY 2020. [DOI: 10.1016/s1872-2040(20)60056-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
|
24
|
Chan MY, Efthymios M, Tan SH, Pickering JW, Troughton R, Pemberton C, Ho HH, Prabath JF, Drum CL, Ling LH, Soo WM, Chai SC, Fong A, Oon YY, Loh JP, Lee CH, Foo RSY, Ackers-Johnson MA, Pilbrow A, Richards AM. Prioritizing Candidates of Post-Myocardial Infarction Heart Failure Using Plasma Proteomics and Single-Cell Transcriptomics. Circulation 2020; 142:1408-1421. [PMID: 32885678 PMCID: PMC7547904 DOI: 10.1161/circulationaha.119.045158] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Supplemental Digital Content is available in the text. Background: Heart failure (HF) is the most common long-term complication of acute myocardial infarction (MI). Understanding plasma proteins associated with post-MI HF and their gene expression may identify new candidates for biomarker and drug target discovery. Methods: We used aptamer-based affinity-capture plasma proteomics to measure 1305 plasma proteins at 1 month post-MI in a New Zealand cohort (CDCS [Coronary Disease Cohort Study]) including 181 patients post-MI who were subsequently hospitalized for HF in comparison with 250 patients post-MI who remained event free over a median follow-up of 4.9 years. We then correlated plasma proteins with left ventricular ejection fraction measured at 4 months post-MI and identified proteins potentially coregulated in post-MI HF using weighted gene co-expression network analysis. A Singapore cohort (IMMACULATE [Improving Outcomes in Myocardial Infarction through Reversal of Cardiac Remodelling]) of 223 patients post-MI, of which 33 patients were hospitalized for HF (median follow-up, 2.0 years), was used for further candidate enrichment of plasma proteins by using Fisher meta-analysis, resampling-based statistical testing, and machine learning. We then cross-referenced differentially expressed proteins with their differentially expressed genes from single-cell transcriptomes of nonmyocyte cardiac cells isolated from a murine MI model, and single-cell and single-nucleus transcriptomes of cardiac myocytes from murine HF models and human patients with HF. Results: In the CDCS cohort, 212 differentially expressed plasma proteins were significantly associated with subsequent HF events. Of these, 96 correlated with left ventricular ejection fraction measured at 4 months post-MI. Weighted gene co-expression network analysis prioritized 63 of the 212 proteins that demonstrated significantly higher correlations among patients who developed post-MI HF in comparison with event-free controls (data set 1). Cross-cohort meta-analysis of the IMMACULATE cohort identified 36 plasma proteins associated with post-MI HF (data set 2), whereas single-cell transcriptomes identified 15 gene-protein candidates (data set 3). The majority of prioritized proteins were of matricellular origin. The 6 most highly enriched proteins that were common to all 3 data sets included well-established biomarkers of post-MI HF: N-terminal B-type natriuretic peptide and troponin T, and newly emergent biomarkers, angiopoietin-2, thrombospondin-2, latent transforming growth factor-β binding protein-4, and follistatin-related protein-3, as well. Conclusions: Large-scale human plasma proteomics, cross-referenced to unbiased cardiac transcriptomics at single-cell resolution, prioritized protein candidates associated with post-MI HF for further mechanistic and clinical validation.
Collapse
Affiliation(s)
- Mark Y Chan
- Department of Medicine, Yong Loo-Lin School of Medicine, National University of Singapore (M.Y.C., M.E., S.H.T., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., M.A.A.-J., A.M.R.).,National University Heart Centre, National University Health System, Singapore (M.Y.C., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., A.M.R.)
| | - Motakis Efthymios
- Department of Medicine, Yong Loo-Lin School of Medicine, National University of Singapore (M.Y.C., M.E., S.H.T., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., M.A.A.-J., A.M.R.).,Genome Institute of Singapore, Agency for Science, Technology, and Research, Singapore (M.E., R.S.Y.F., M.A.A.-J.)
| | - Sock Hwee Tan
- Department of Medicine, Yong Loo-Lin School of Medicine, National University of Singapore (M.Y.C., M.E., S.H.T., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., M.A.A.-J., A.M.R.)
| | - John W Pickering
- Christchurch Heart Institute, Department of Medicine, University of Otago, New Zealand (J.W.P., R.T., C.P., A.P., A.M.R.)
| | - Richard Troughton
- Christchurch Heart Institute, Department of Medicine, University of Otago, New Zealand (J.W.P., R.T., C.P., A.P., A.M.R.)
| | - Christopher Pemberton
- Christchurch Heart Institute, Department of Medicine, University of Otago, New Zealand (J.W.P., R.T., C.P., A.P., A.M.R.)
| | - Hee-Hwa Ho
- Tan Tock Seng Hospital, Singapore (H.-H.H., J.-F.P.)
| | | | - Chester L Drum
- Department of Medicine, Yong Loo-Lin School of Medicine, National University of Singapore (M.Y.C., M.E., S.H.T., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., M.A.A.-J., A.M.R.).,National University Heart Centre, National University Health System, Singapore (M.Y.C., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., A.M.R.)
| | - Lieng Hsi Ling
- Department of Medicine, Yong Loo-Lin School of Medicine, National University of Singapore (M.Y.C., M.E., S.H.T., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., M.A.A.-J., A.M.R.).,National University Heart Centre, National University Health System, Singapore (M.Y.C., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., A.M.R.)
| | - Wern-Miin Soo
- Department of Medicine, Yong Loo-Lin School of Medicine, National University of Singapore (M.Y.C., M.E., S.H.T., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., M.A.A.-J., A.M.R.).,National University Heart Centre, National University Health System, Singapore (M.Y.C., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., A.M.R.)
| | | | - Alan Fong
- Sarawak Heart Institute, Kuching, Malaysia (A.F., Y.-Y.O.)
| | - Yen-Yee Oon
- Sarawak Heart Institute, Kuching, Malaysia (A.F., Y.-Y.O.)
| | - Joshua P Loh
- Department of Medicine, Yong Loo-Lin School of Medicine, National University of Singapore (M.Y.C., M.E., S.H.T., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., M.A.A.-J., A.M.R.).,National University Heart Centre, National University Health System, Singapore (M.Y.C., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., A.M.R.)
| | - Chi-Hang Lee
- Department of Medicine, Yong Loo-Lin School of Medicine, National University of Singapore (M.Y.C., M.E., S.H.T., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., M.A.A.-J., A.M.R.).,National University Heart Centre, National University Health System, Singapore (M.Y.C., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., A.M.R.)
| | - Roger S Y Foo
- Department of Medicine, Yong Loo-Lin School of Medicine, National University of Singapore (M.Y.C., M.E., S.H.T., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., M.A.A.-J., A.M.R.).,National University Heart Centre, National University Health System, Singapore (M.Y.C., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., A.M.R.).,Genome Institute of Singapore, Agency for Science, Technology, and Research, Singapore (M.E., R.S.Y.F., M.A.A.-J.)
| | - Matthew Andrew Ackers-Johnson
- Department of Medicine, Yong Loo-Lin School of Medicine, National University of Singapore (M.Y.C., M.E., S.H.T., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., M.A.A.-J., A.M.R.).,Genome Institute of Singapore, Agency for Science, Technology, and Research, Singapore (M.E., R.S.Y.F., M.A.A.-J.)
| | - Anna Pilbrow
- Christchurch Heart Institute, Department of Medicine, University of Otago, New Zealand (J.W.P., R.T., C.P., A.P., A.M.R.)
| | - A Mark Richards
- Department of Medicine, Yong Loo-Lin School of Medicine, National University of Singapore (M.Y.C., M.E., S.H.T., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., M.A.A.-J., A.M.R.).,National University Heart Centre, National University Health System, Singapore (M.Y.C., C.L.D., L.H.L., W.-M.S., J.P.L., C.-H.L., R.S.Y.F., A.M.R.).,Changi General Hospital, Singapore (S.-C.C.)
| |
Collapse
|
25
|
Highly multiplexed proteomic assessment of human bone marrow in acute myeloid leukemia. Blood Adv 2020; 4:367-379. [PMID: 31985806 DOI: 10.1182/bloodadvances.2019001124] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 12/16/2019] [Indexed: 02/07/2023] Open
Abstract
Acute myeloid leukemia (AML) is a genetically heterogeneous disease that is characterized by abnormal clonal proliferation of myeloid progenitor cells found predominantly within the bone marrow (BM) and blood. Recent studies suggest that genetic and phenotypic alterations in the BM microenvironment support leukemogenesis and allow leukemic cells to survive and evade chemotherapy-induced death. However, despite substantial evidence indicating the role of tumor-host interactions in AML pathogenesis, little is known about the complex microenvironment of the BM. To address this, we performed novel proteomic profiling of the noncellular compartment of the BM microenvironment in patients with AML (n = 10) and age- and sex-matched healthy control subjects (n = 10) using an aptamer-based, highly multiplexed, affinity proteomics platform (SOMAscan). We show that proteomic assessment of blood or RNA-sequencing of BM are suboptimal alternate screening strategies to determine the true proteomic composition of the extracellular soluble compartment of AML patient BM. Proteomic analysis revealed that 168 proteins significantly differed in abundance, with 91 upregulated and 77 downregulated in leukemic BM. A highly connected signaling network of cytokines and chemokines, including IL-8, was found to be the most prominent proteomic signature associated with AML in the BM microenvironment. We report the first description of significantly elevated levels of the myelosuppressive chemokine CCL23 (myeloid progenitor inhibitory factor-1) in both AML and myelodysplastic syndrome patients and perform functional experiments supportive of a role in the suppression of normal hematopoiesis. This unique paired RNA-sequencing and proteomics data set provides innovative mechanistic insights into AML and healthy aging and should serve as a useful public resource.
Collapse
|
26
|
Raffield LM, Dang H, Pratte KA, Jacobson S, Gillenwater L, Ampleford E, Barjaktarevic I, Basta P, Clish CB, Comellas AP, Cornell E, Curtis JL, Doerschuk C, Durda P, Emson C, Freeman C, Guo X, Hastie AT, Hawkins GA, Herrera J, Johnson WC, Labaki WW, Liu Y, Masters B, Miller M, Ortega VE, Papanicolaou G, Peters S, Taylor KD, Rich SS, Rotter JI, Auer P, Reiner AP, Tracy RP, Ngo D, Gerszten RE, O’Neal WK, Bowler RP. Comparison of Proteomic Assessment Methods in Multiple Cohort Studies. Proteomics 2020; 20:e1900278. [PMID: 32386347 PMCID: PMC7425176 DOI: 10.1002/pmic.201900278] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Revised: 04/30/2020] [Indexed: 11/09/2022]
Abstract
Novel proteomics platforms, such as the aptamer-based SOMAscan platform, can quantify large numbers of proteins efficiently and cost-effectively and are rapidly growing in popularity. However, comparisons to conventional immunoassays remain underexplored, leaving investigators unsure when cross-assay comparisons are appropriate. The correlation of results from immunoassays with relative protein quantification is explored by SOMAscan. For 63 proteins assessed in two chronic obstructive pulmonary disease (COPD) cohorts, subpopulations and intermediate outcome measures in COPD Study (SPIROMICS), and COPDGene, using myriad rules based medicine multiplex immunoassays and SOMAscan, Spearman correlation coefficients range from -0.13 to 0.97, with a median correlation coefficient of ≈0.5 and consistent results across cohorts. A similar range is observed for immunoassays in the population-based Multi-Ethnic Study of Atherosclerosis and for other assays in COPDGene and SPIROMICS. Comparisons of relative quantification from the antibody-based Olink platform and SOMAscan in a small cohort of myocardial infarction patients also show a wide correlation range. Finally, cis pQTL data, mass spectrometry aptamer confirmation, and other publicly available data are integrated to assess relationships with observed correlations. Correlation between proteomics assays shows a wide range and should be carefully considered when comparing and meta-analyzing proteomics data across assays and studies.
Collapse
Affiliation(s)
- Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Hong Dang
- Marsico Lung Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Katherine A. Pratte
- Division of Pulmonary Medicine, Department of Medicine, National Jewish Health (NJH), Denver, CO
| | - Sean Jacobson
- Division of Pulmonary Medicine, Department of Medicine, National Jewish Health (NJH), Denver, CO
| | - Lucas Gillenwater
- Division of Pulmonary Medicine, Department of Medicine, National Jewish Health (NJH), Denver, CO
| | - Elizabeth Ampleford
- Department of Internal Medicine, Section for Pulmonary, Critical Care, Allergy & Immunology, School of Medicine, Wake Forest University, Winston-Salem, NC
| | - Igor Barjaktarevic
- UCLA Division of Pulmonary and Critical Care, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA
| | - Patricia Basta
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Clary B. Clish
- Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA
| | | | - Elaine Cornell
- Department of Pathology & Laboratory Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT
| | - Jeffrey L. Curtis
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI
- VA Ann Arbor Healthcare System, Ann Arbor, MI
| | - Claire Doerschuk
- Marsico Lung Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Peter Durda
- Department of Pathology & Laboratory Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT
| | - Claire Emson
- Translational Science and Experimental Medicine, Research and Early Development, Respiratory & Immunology, BioPharmaceuticals R&D, AstraZenenca, Gaithersburg, MD
| | - Christine Freeman
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI
- VA Ann Arbor Healthcare System, Ann Arbor, MI
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Annette T. Hastie
- Department of Internal Medicine, Section for Pulmonary, Critical Care, Allergy & Immunology, School of Medicine, Wake Forest University, Winston-Salem, NC
| | - Gregory A. Hawkins
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC
| | | | - W. Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA
| | - Wassim W. Labaki
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI
| | - Yongmei Liu
- Department of Epidemiology & Prevention, Wake Forest School of Medicine, Winston-Salem, NC
| | | | | | - Victor E. Ortega
- Department of Internal Medicine, Section for Pulmonary, Critical Care, Allergy & Immunology, School of Medicine, Wake Forest University, Winston-Salem, NC
| | - George Papanicolaou
- Epidemiology Branch, Division of Cardiovascular Sciences, National Heart, Lung and Blood Institute, Bethesda, MD
| | - Stephen Peters
- Department of Internal Medicine, Section for Pulmonary, Critical Care, Allergy & Immunology, School of Medicine, Wake Forest University, Winston-Salem, NC
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Paul Auer
- Zilber School of Public Health, University of Wisconsin Milwaukee, Milwaukee, WI
| | - Alex P. Reiner
- Fred Hutchinson Cancer Research Center, Seattle, WA
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Russell P. Tracy
- Department of Pathology & Laboratory Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT
- Department of Biochemistry, Larner College of Medicine at the University of Vermont, Burlington, VT
| | - Debby Ngo
- Division of Pulmonary, Sleep and Critical Care Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Robert E. Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Wanda Kay O’Neal
- Marsico Lung Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Russell P. Bowler
- Division of Pulmonary Medicine, Department of Medicine, National Jewish Health (NJH), Denver, CO
| | | |
Collapse
|
27
|
Comprehensive analysis reveals a six-gene signature and associated drugs in mimic inguinal hernia model. Hernia 2020; 24:1211-1219. [DOI: 10.1007/s10029-020-02213-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 05/04/2020] [Indexed: 02/06/2023]
|
28
|
Nayor M, Short MI, Rasheed H, Lin H, Jonasson C, Yang Q, Hveem K, Felix JF, Morrison AC, Wild PS, Morley MP, Cappola TP, Benson MD, Ngo D, Sinha S, Keyes MJ, Shen D, Wang TJ, Larson MG, Brumpton BM, Gerszten RE, Omland T, Vasan RS. Aptamer-Based Proteomic Platform Identifies Novel Protein Predictors of Incident Heart Failure and Echocardiographic Traits. Circ Heart Fail 2020; 13:e006749. [PMID: 32408813 PMCID: PMC7236427 DOI: 10.1161/circheartfailure.119.006749] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND We used a large-scale, high-throughput DNA aptamer-based discovery proteomic platform to identify circulating biomarkers of cardiac remodeling and incident heart failure (HF) in community-dwelling individuals. METHODS We evaluated 1895 FHS (Framingham Heart Study) participants (age 55±10 years, 54% women) who underwent proteomic profiling and echocardiography. Plasma levels of 1305 proteins were related to echocardiographic traits and to incident HF using multivariable regression. Statistically significant protein-HF associations were replicated in the HUNT (Nord-Trøndelag Health) study (n=2497, age 63±10 years, 43% women), and results were meta-analyzed. Genetic variants associated with circulating protein levels (pQTLs) were related to echocardiographic traits in the EchoGen (n=30 201) and to incident HF in the CHARGE (n=20 926) consortia. RESULTS Seventeen proteins associated with echocardiographic traits in cross-sectional analyses (false discovery rate <0.10), and 8 of these proteins had pQTLs associated with echocardiographic traits in EchoGen (P<0.0007). In Cox models adjusted for clinical risk factors, 29 proteins demonstrated associations with incident HF in FHS (174 HF events, mean follow-up 19 [limits, 0.2-23.7] years). In meta-analyses of FHS and HUNT, 6 of these proteins were associated with incident HF (P<3.8×10-5; 3 with higher risk: NT-proBNP [N-terminal proB-type natriuretic peptide], TSP2 [thrombospondin-2], MBL [mannose-binding lectin]; and 3 with lower risk: ErbB1 [epidermal growth factor receptor], GDF-11/8 [growth differentiation factor-11/8], and RGMC [hemojuvelin]). For 5 of the 6 proteins, pQTLs were associated with echocardiographic traits (P<0.0006) in EchoGen, and for RGMC, a protein quantitative trait loci was associated with incident HF (P=0.001). CONCLUSIONS A large-scale proteomics approach identified new predictors of cardiac remodeling and incident HF. Future studies are warranted to elucidate how biological pathways represented by these proteins may mediate cardiac remodeling and HF risk and to assess if these proteins can improve HF risk prediction.
Collapse
Affiliation(s)
- Matthew Nayor
- Framingham Heart Study, Framingham, MA
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Meghan I. Short
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX
| | - Humaira Rasheed
- K.G. Jebsen Centre for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Norway
- MRC Integrative Epidemiology Unit, University of Bristol, UK
| | - Honghuang Lin
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA
| | - Christian Jonasson
- K.G. Jebsen Centre for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Norway
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Kristian Hveem
- K.G. Jebsen Centre for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Norway
| | - Janine F. Felix
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Alanna C. Morrison
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas
| | - Philipp S. Wild
- Preventive Cardiology and Preventive Medicine, Center for Cardiology, and Center for Thrombosis and Hemostasis, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- DZHK (German Center for Cardiovascular Research), partner site RhineMain, Mainz, Germany
| | - Michael P. Morley
- The Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, PA
| | - Thomas P. Cappola
- The Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, PA
- Division of Cardiovascular Medicine, Perelman School of Medicine, University of Pennsylvania, PA
| | - Mark D. Benson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | | | | | - Debby Ngo
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Sumita Sinha
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Michelle J. Keyes
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Dongxiao Shen
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Thomas J. Wang
- Division of Cardiovascular Medicine, Vanderbilt University, Nashville, TN
| | - Martin G. Larson
- Framingham Heart Study, Framingham, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Ben M. Brumpton
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX
- K.G. Jebsen Centre for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Norway
- Clinic of Thoracic and Occupational Medicine, St. Olavs Hospital, Trondheim University Hospital, Norway
| | - Robert E. Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Torbjørn Omland
- Department of Cardiology, Akershus University Hospital, Lørenskog, and Center for Heart Failure Research, Institute of Clinical Medicine, University of Oslo, Norway
| | - Ramachandran S. Vasan
- Framingham Heart Study, Framingham, MA
- Sections of Preventive Medicine & Epidemiology, and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, MA
| |
Collapse
|
29
|
Shubin AV, Kollar B, Dillon ST, Pomahac B, Libermann TA, Riella LV. Blood proteome profiling using aptamer-based technology for rejection biomarker discovery in transplantation. Sci Data 2019; 6:314. [PMID: 31819064 PMCID: PMC6901551 DOI: 10.1038/s41597-019-0324-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Accepted: 11/04/2019] [Indexed: 12/24/2022] Open
Abstract
Face transplantation is a promising solution for patients with devastating facial injuries who lack other satisfactory treatment options. At the same time, this type of transplantation is accompanied with high risks of acute transplant rejection. The limitations of traditional skin biopsy and the need to frequently monitor the condition of face transplant call for less invasive biomarkers to better diagnose and treat acute rejection. Discovery of peripheral serum proteins accurately reflecting the transplant status would represent a reasonable solution to meet this demand. However, to date, there is no clinical data available to address the feasibility of this approach. In this study, we used the next generation aptamer-based SOMAscan proteomics platform to profile 1305 proteins of peripheral blood serum in twenty-four samples taken from 6 patients during no-rejection, nonsevere rejection, and severe rejection episodes. Also, we provide a detailed description of biosample processing and all steps to generate and analyze the SOMAscan dataset with hope it will assist in performing biomarker discovery in other transplantation centers using this platform.
Collapse
Affiliation(s)
- Andrey V Shubin
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, 02138, USA
| | - Branislav Kollar
- Division of Plastic Surgery, Department of Surgery, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Simon T Dillon
- Beth Israel Deaconess Medical Center Genomics, Proteomics, Bioinformatics and Systems Biology Center, Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, 02215, USA
| | - Bohdan Pomahac
- Division of Plastic Surgery, Department of Surgery, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Towia A Libermann
- Beth Israel Deaconess Medical Center Genomics, Proteomics, Bioinformatics and Systems Biology Center, Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, 02215, USA.
| | - Leonardo V Riella
- Schuster Transplantation Research Center, Renal Division, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
| |
Collapse
|
30
|
McConnell EM, Cozma I, Morrison D, Li Y. Biosensors Made of Synthetic Functional Nucleic Acids Toward Better Human Health. Anal Chem 2019; 92:327-344. [PMID: 31656066 DOI: 10.1021/acs.analchem.9b04868] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Erin M McConnell
- Department of Biochemistry and Biomedical Sciences , McMaster University , Hamilton , Ontario , Canada , L8S 4K1
| | - Ioana Cozma
- Department of Biochemistry and Biomedical Sciences , McMaster University , Hamilton , Ontario , Canada , L8S 4K1.,Department of Surgery, Division of General Surgery , McMaster University , Hamilton , Ontario , Canada , L8S 4K1
| | - Devon Morrison
- Department of Biochemistry and Biomedical Sciences , McMaster University , Hamilton , Ontario , Canada , L8S 4K1
| | - Yingfu Li
- Department of Biochemistry and Biomedical Sciences , McMaster University , Hamilton , Ontario , Canada , L8S 4K1
| |
Collapse
|
31
|
McGilligan V, Watterson S, Rjoob K, Chemaly M, Bond R, Iftikhar A, Knoery C, Leslie SJ, McShane A, Bjourson A, Peace A. An exploratory analysis investigating blood protein biomarkers to augment ECG diagnosis of ACS. J Electrocardiol 2019; 57S:S92-S97. [PMID: 31519392 DOI: 10.1016/j.jelectrocard.2019.09.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 08/23/2019] [Accepted: 09/04/2019] [Indexed: 11/26/2022]
Abstract
BACKGROUND Acute Coronary Syndrome (ACS) is currently diagnosed using a 12‑lead Electrocardiogram (ECG). Our recent work however has shown that interpretation of the 12‑lead ECG is complex and that clinicians can be sub-optimal in their interpretation. Additionally, ECG does not always identify acute total occlusions in certain patients. PURPOSE The aim of the present study was to undertake an exploratory analysis to compare protein expression profiles of ACS patients that may in the future augment ECG diagnosis. METHODS Patients were recruited consecutively at the cardiac catheterization laboratory at Altnagelvin Hospital over a period of 6 months. A low risk control group was recruited by advertisement. Blood samples were analysed using the multiplex proximity extension assays by OLINK proteomics. Support vector machine (SVM) learning was used as a classifier to distinguish between patient groups on training data. The ST segment elevation level was extracted from each ECG for a subset of patients and combined with the protein markers. Quadratic SVM (QSVM) learning was then used as a classifier to distinguish STEMI from NSTEMI on training and test data. RESULTS Of the 344 participants recruited, 77 were initially diagnosed with NSTEMI, 7 with STEMI, and 81 were low risk controls. The other participants were those diagnosed with angina (stable and unstable) or non-cardiac patients. Of the 368 proteins analysed, 20 proteins together could significantly differentiate between patients with ACS and patients with stable angina (ROC-AUC = 0.96). Six proteins discriminated significantly between the stable angina and the low risk control groups (ROC-AUC = 1.0). Additionally, 16 proteins together perfectly discriminated between the STEMI and NSTEMI patients (ROC-AUC = 1). ECG comparisons with the protein biomarker data for a subset of patients (STEMI n = 6 and NSTEMI n = 6), demonstrated that 21 features (20 proteins + ST elevation) resulted in the highest classification accuracy 91.7% (ROC-AUC = 0.94). The 20 proteins without the ST elevation feature gave an accuracy of 80.6% (ROC-AUC 0.91), while the ST elevation feature without the protein biomarkers resulted in an accuracy of 69.3% (ROC-AUC = 0.81). CONCLUSIONS This preliminary study identifies panels of proteins that should be further explored in prospective studies as potential biomarkers that may augment ECG diagnosis and stratification of ACS. This work also highlights the importance for future studies to be designed to allow a comparison of blood biomarkers not only with ECG's but also with cardio angiograms.
Collapse
Affiliation(s)
- Victoria McGilligan
- Centre for Personalised Medicine, Ulster University, Londonderry BT47 6SB, Northern Ireland, UK; Northern Ireland Centre for Stratified Medicine, Ulster University, Londonderry BT47 6SB, Northern Ireland, UK.
| | - Steven Watterson
- Northern Ireland Centre for Stratified Medicine, Ulster University, Londonderry BT47 6SB, Northern Ireland, UK
| | - Khaled Rjoob
- Centre for Personalised Medicine, Ulster University, Londonderry BT47 6SB, Northern Ireland, UK; School of Computing, Ulster University, Jordanstown campus, Northern Ireland, UK
| | - Melody Chemaly
- Centre for Personalised Medicine, Ulster University, Londonderry BT47 6SB, Northern Ireland, UK; Northern Ireland Centre for Stratified Medicine, Ulster University, Londonderry BT47 6SB, Northern Ireland, UK
| | - Raymond Bond
- Centre for Personalised Medicine, Ulster University, Londonderry BT47 6SB, Northern Ireland, UK; School of Computing, Ulster University, Jordanstown campus, Northern Ireland, UK
| | - Aleeha Iftikhar
- Centre for Personalised Medicine, Ulster University, Londonderry BT47 6SB, Northern Ireland, UK; School of Computing, Ulster University, Jordanstown campus, Northern Ireland, UK
| | - Charles Knoery
- Cardiac Unit, Raigmore Hospital, NHS Highland, Inverness IV2 3UJ, UK; Division of Rural Health and Wellbeing, University of Highlands and Islands, Inverness IV2 3JH, UK
| | - Stephen J Leslie
- Cardiac Unit, Raigmore Hospital, NHS Highland, Inverness IV2 3UJ, UK; Division of Rural Health and Wellbeing, University of Highlands and Islands, Inverness IV2 3JH, UK
| | - Anne McShane
- Emergency Department, Letterkenny University Hospital, Donegal, Ireland
| | - Anthony Bjourson
- Centre for Personalised Medicine, Ulster University, Londonderry BT47 6SB, Northern Ireland, UK; Northern Ireland Centre for Stratified Medicine, Ulster University, Londonderry BT47 6SB, Northern Ireland, UK
| | - Aaron Peace
- Centre for Personalised Medicine, Ulster University, Londonderry BT47 6SB, Northern Ireland, UK; Northern Ireland Centre for Stratified Medicine, Ulster University, Londonderry BT47 6SB, Northern Ireland, UK; Cardiology Department, Western Health and Social Care Trust, Altnagelvin Hospital, Londonderry, Northern Ireland, UK
| |
Collapse
|
32
|
Lau E, Paik DT, Wu JC. Systems-Wide Approaches in Induced Pluripotent Stem Cell Models. ANNUAL REVIEW OF PATHOLOGY-MECHANISMS OF DISEASE 2018; 14:395-419. [PMID: 30379619 DOI: 10.1146/annurev-pathmechdis-012418-013046] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Human induced pluripotent stem cells (iPSCs) provide a renewable supply of patient-specific and tissue-specific cells for cellular and molecular studies of disease mechanisms. Combined with advances in various omics technologies, iPSC models can be used to profile the expression of genes, transcripts, proteins, and metabolites in relevant tissues. In the past 2 years, large panels of iPSC lines have been derived from hundreds of genetically heterogeneous individuals, further enabling genome-wide mapping to identify coexpression networks and elucidate gene regulatory networks. Here, we review recent developments in omics profiling of various molecular phenotypes and the emergence of human iPSCs as a systems biology model of human diseases.
Collapse
Affiliation(s)
- Edward Lau
- Stanford Cardiovascular Institute, and Department of Medicine, Division of Cardiology, Stanford University, Stanford, California 94305, USA;
| | - David T Paik
- Stanford Cardiovascular Institute, and Department of Medicine, Division of Cardiology, Stanford University, Stanford, California 94305, USA;
| | - Joseph C Wu
- Stanford Cardiovascular Institute, and Department of Medicine, Division of Cardiology, Stanford University, Stanford, California 94305, USA; .,Department of Radiology, Stanford University, Stanford, California 94305, USA
| |
Collapse
|
33
|
Increased levels of circulating MMP3 correlate with severe rejection in face transplantation. Sci Rep 2018; 8:14915. [PMID: 30297859 PMCID: PMC6175842 DOI: 10.1038/s41598-018-33272-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Accepted: 09/26/2018] [Indexed: 12/16/2022] Open
Abstract
Face transplantation is a viable treatment option for carefully selected patients with devastating injuries to the face. However, acute rejection episodes occur in more than 80% of recipients in the first postoperative year. Unfortunately, neither a correlation between histological grades of rejection and anti-rejection treatment nor systemic surrogate markers of rejection in face transplantation are established in clinical routine. Therefore, we utilized next generation aptamer-based SOMAscan proteomics platform for non-invasive rejection biomarker discovery. Longitudinal serum samples from face transplant recipients with long-term follow-up were included in this study. From the 1,310 proteins analyzed by SOMAscan, a 5-protein signature (MMP3, ACY1, IL1R2, SERPINA4, CPB2) was able to discriminate severe rejection from both no-rejection and nonsevere rejection samples. Technical validation on ELISA platform showed high correlation with the SOMAscan data for the MMP3 protein (rs = 0.99). Additionally, MMP3 levels were significantly increased during severe rejection as compared to no-rejection (p = 0.0009) and nonsevere rejection (p = 0.0173) episodes. Pathway analyses revealed significant activation of the metallopeptidase activity during severe face transplant rejection. This pilot study demonstrates the feasibility of SOMAscan to identify non-invasive candidate biomarkers of rejection in face transplantation. Further validation in a larger independent patient cohort is needed.
Collapse
|
34
|
Chen A, Chen Z, Xia Y, Lu D, Jia J, Hu K, Sun A, Zou Y, Qian J, Ge J. Proteomics Analysis of Myocardial Tissues in a Mouse Model of Coronary Microembolization. Front Physiol 2018; 9:1318. [PMID: 30283360 PMCID: PMC6157402 DOI: 10.3389/fphys.2018.01318] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Accepted: 08/31/2018] [Indexed: 01/30/2023] Open
Abstract
Coronary microembolization (CME) is an important clinical problem, and it is related to poor outcome. The specific molecular mechanisms of CME are not fully understood. In the present study, we established a mice model of CME. Isobaric tags for relative and absolute quantitation (iTRAQ) and liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) technologies identified 249 differentially expressed proteins in the myocardial tissues of CME mice as compared with sham-operated mice. Bioinformatics analysis demonstrated that these differentially expressed proteins were enriched in several energy metabolism or cytoskeleton organization related processes or pathways. Quantitative PCR and Western blotting validation experiments revealed that succinate dehydrogenase (SDHA and SDHB) were upregulated, Rho GDP dissociation inhibitor α (RhoGDIα) and Filamin-A (FLNA) were downregulated significantly in CME mice. These findings indicated that the alternations of the cytoskeleton and energy metabolism pathways play important roles in the pathogenesis of CME, future studies are warranted to verify if targeting these molecules might be useful to alleviate CME injury or not.
Collapse
Affiliation(s)
- Ao Chen
- Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhangwei Chen
- Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yan Xia
- Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Danbo Lu
- Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jianguo Jia
- Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Kai Hu
- Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Aijun Sun
- Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yunzeng Zou
- Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Juying Qian
- Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Junbo Ge
- Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, China
| |
Collapse
|