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Towards Allograft Longevity: Leveraging Omics Technologies to Improve Heart Transplant Outcomes

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Abstract

Purpose of Review

Heart transplantation (HT) remains the optimal therapy for patients living with end-stage heart disease. Despite recent improvements in peri-transplant management, the median survival after HT has remained relatively static, and complications of HT, including infection, rejection, and allograft dysfunction, continue to impact quality of life and long-term survival.

Recent Findings

Omics technologies are becoming increasingly accessible and can identify novel biomarkers for, and reveal the underlying biology of, several disease states. While some technologies, such as gene expression profiling (GEP) and donor-derived cell-free DNA (dd-cfDNA), are routinely used in the clinical care of HT recipients, a number of emerging platforms, including pharmacogenomics, proteomics, and metabolomics, hold great potential for identifying biomarkers to aid in the diagnosis and management of post-transplant complications. Omics-based assays can improve patient and allograft longevity by facilitating a personalized and precision approach to post-HT care.

Summary

The following article is a contemporary review of the current and future opportunities to leverage omics technologies, including genomics, transcriptomics, proteomics, and metabolomics in the field of HT.

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References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. 2022 Annual Report of the U.S. Organ Procurement and Transplantation Network and the Scientific Registry of Transplant Recipients: Transplant Data 1994–2021. Department of Health and Human Services HRaSA; 2022. https://srtr.transplant.hrsa.gov/annual_report/Default.aspx

  2. Khush KK, Potena L, Cherikh WS, Chambers DC, Harhay MO, Hayes D Jr, Hsich E, Sadavarte A, Singh TP, Zuckermann A, et al. The International Thoracic Organ Transplant Registry of the International Society for Heart and Lung Transplantation: 37th adult heart transplantation report-2020; focus on deceased donor characteristics. J Heart Lung Transplant. 2020;39:1003–15. https://doi.org/10.1016/j.healun.2020.07.010.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Truby LK, Takeda K, Topkara VK, Takayama H, Garan AR, Yuzefpolskaya M, Colombo P, Naka Y, Farr M. Risk of severe primary graft dysfunction in patients bridged to heart transplantation with continuous-flow left ventricular assist devices. J Heart Lung Transplant. 2018;37:1433–42. https://doi.org/10.1016/j.healun.2018.07.013.

    Article  PubMed  Google Scholar 

  4. Truby LK, Takeda K, Farr M, Beck J, Yuzefpolskaya M, Colombo PC, Topkara VK, Mancini D, Naka Y, Takayama H. Incidence and impact of on-cardiopulmonary bypass vasoplegia during heart transplantation. ASAIO J. 2018;64:43–51. https://doi.org/10.1097/MAT.0000000000000623.

    Article  PubMed  Google Scholar 

  5. Silverstein A. My Transplanted Heart and I Will Die Soon. In: New York Times. 2023. https://www.nytimes.com/2023/04/18/opinion/heart-transplant-donor.html

  6. •• McGarrah RW, Shah SH. Integrative omics: harnessing the proteome to maximize the potential of the genome. Circulation. 2018;137:1173–5. https://doi.org/10.1161/circulationaha.117.032807. Geneticvariationcanbeintegratedwithinotheromicsdata(e.g.,transcriptomics,proteomics) Once identified, genetic variants and biomarkers can be interrogated for the identification of the phenotype of interest.

    Article  PubMed  Google Scholar 

  7. Pham MX, Teuteberg JJ, Kfoury AG, Starling RC, Deng MC, Cappola TP, Kao A, Anderson AS, Cotts WG, Ewald GA, et al. Gene-expression profiling for rejection surveillance after cardiac transplantation. N Engl J Med. 2010;362:1890–900. https://doi.org/10.1056/NEJMoa0912965.

    Article  CAS  PubMed  Google Scholar 

  8. • Agbor-Enoh S, Shah P, Tunc I, Hsu S, Russell S, Feller E, Shah K, Rodrigo ME, Najjar SS, Kong H, et al. Cell-Free DNA to Detect Heart Allograft Acute Rejection. Circulation. 2021;143:1184–97. https://doi.org/10.1161/circulationaha.120.049098. Donor-derived cell-free DNA demonstrated excellent negative predictive value for acute allograft rejection.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Andargie TE, Tsuji N, Seifuddin F, Jang MK, Yuen PS, Kong H, Tunc I, Singh K, Charya A, Wilkins K, et al. Cell-free DNA maps COVID-19 tissue injury and risk of death and can cause tissue injury. JCI Insight. 2021;6. https://doi.org/10.1172/jci.insight.147610

  10. De Vlaminck I, Valantine HA, Snyder TM, Strehl C, Cohen G, Luikart H, Neff NF, Okamoto J, Bernstein D, Weisshaar D, et al. Circulating cell-free DNA enables noninvasive diagnosis of heart transplant rejection. Sci Transl Med. 2014;6:241ra277. https://doi.org/10.1126/scitranslmed.3007803.

    Article  CAS  Google Scholar 

  11. Jaiswal S, Natarajan P, Silver AJ, Gibson CJ, Bick AG, Shvartz E, McConkey M, Gupta N, Gabriel S, Ardissino D, et al. Clonal hematopoiesis and risk of atherosclerotic cardiovascular disease. N Engl J Med. 2017;377:111–21. https://doi.org/10.1056/NEJMoa1701719.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Scolari FL, Brahmbhatt DH, Abelson S, Medeiros JJF, Anker MS, Fung NL, Otsuki M, Calvillo-Arguelles O, Lawler PR, Ross HJ, et al. Clonal hematopoiesis confers an increased mortality risk in orthotopic heart transplant recipients. Am J Transplant. 2022;22:3078–86. https://doi.org/10.1111/ajt.17172.

    Article  CAS  PubMed  Google Scholar 

  13. Thervet E, Anglicheau D, Legendre C, Beaune P. Role of pharmacogenetics of immunosuppressive drugs in organ transplantation. Ther Drug Monit. 2008;30:143–50. https://doi.org/10.1097/FTD.0b013e31816babef.

    Article  CAS  PubMed  Google Scholar 

  14. Elens L, Bouamar R, Shuker N, Hesselink DA, van Gelder T, van Schaik RH. Clinical implementation of pharmacogenetics in kidney transplantation: calcineurin inhibitors in the starting blocks. Br J Clin Pharmacol. 2014;77:715–28. https://doi.org/10.1111/bcp.12253.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Kamdem LK, Streit F, Zanger UM, Brockmöller J, Oellerich M, Armstrong VW, Wojnowski L. Contribution of CYP3A5 to the in vitro hepatic clearance of tacrolimus. Clin Chem. 2005;51:1374–81. https://doi.org/10.1373/clinchem.2005.050047.

    Article  CAS  PubMed  Google Scholar 

  16. Haufroid V, Mourad M, Van Kerckhove V, Wawrzyniak J, De Meyer M, Eddour DC, Malaise J, Lison D, Squifflet JP, Wallemacq P. The effect of CYP3A5 and MDR1 (ABCB1) polymorphisms on cyclosporine and tacrolimus dose requirements and trough blood levels in stable renal transplant patients. Pharmacogenetics. 2004;14:147–54. https://doi.org/10.1097/00008571-200403000-00002.

    Article  CAS  PubMed  Google Scholar 

  17. Jacobson PA, Oetting WS, Brearley AM, Leduc R, Guan W, Schladt D, Matas AJ, Lamba V, Julian BA, Mannon RB, et al. Novel polymorphisms associated with tacrolimus trough concentrations: results from a multicenter kidney transplant consortium. Transplantation. 2011;91:300–8. https://doi.org/10.1097/TP.0b013e318200e991.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Kuehl P, Zhang J, Lin Y, Lamba J, Assem M, Schuetz J, Watkins PB, Daly A, Wrighton SA, Hall SD, et al. Sequence diversity in CYP3A promoters and characterization of the genetic basis of polymorphic CYP3A5 expression. Nat Genet. 2001;27:383–91. https://doi.org/10.1038/86882.

    Article  CAS  PubMed  Google Scholar 

  19. Kniepeiss D, Renner W, Trummer O, Wagner D, Wasler A, Khoschsorur GA, Truschnig-Wilders M, Tscheliessnigg KH. The role of CYP3A5 genotypes in dose requirements of tacrolimus and everolimus after heart transplantation. Clin Transplant. 2011;25:146–50. https://doi.org/10.1111/j.1399-0012.2009.01198.x.

    Article  CAS  PubMed  Google Scholar 

  20. Birdwell KA, Decker B, Barbarino JM, Peterson JF, Stein CM, Sadee W, Wang D, Vinks AA, He Y, Swen JJ, et al. Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines for CYP3A5 genotype and tacrolimus dosing. Clin Pharmacol Ther. 2015;98:19–24. https://doi.org/10.1002/cpt.113.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Lesche D, Sigurdardottir V, Setoud R, Oberhänsli M, Carrel T, Fiedler GM, Largiadèr CR, Mohacsi P, Sistonen J. CYP3A5*3 and POR*28 genetic variants influence the required dose of tacrolimus in heart transplant recipients. Ther Drug Monit. 2014;36:710–5. https://doi.org/10.1097/ftd.0000000000000080.

    Article  CAS  PubMed  Google Scholar 

  22. Zheng H, Webber S, Zeevi A, Schuetz E, Zhang J, Bowman P, Boyle G, Law Y, Miller S, Lamba J, et al. Tacrolimus dosing in pediatric heart transplant patients is related to CYP3A5 and MDR1 gene polymorphisms. Am J Transplant Off J Am Soc Transplant Am Soc Transplant Surg. 2003;3:477–83. https://doi.org/10.1034/j.1600-6143.2003.00077.x.

    Article  CAS  Google Scholar 

  23. • Oreschak K, Saba LM, Rafaels N, Ambardekar AV, Deininger KM, Page RL 2nd, Lindenfeld J, Aquilante CL. Association between variants in calcineurin inhibitor pharmacokinetic and pharmacodynamic genes and renal dysfunction in adult heart transplant recipients. Front Genet. 2021;12:658983. https://doi.org/10.3389/fgene.2021.658983. Genetic variation in TGFB1 and PLCB1 genes may be associated with post-transplant renal dysfunction in the setting of calcineurin inhibition.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Kobashigawa JA, Miller LW, Russell SD, Ewald GA, Zucker MJ, Goldberg LR, Eisen HJ, Salm K, Tolzman D, Gao J, et al. Tacrolimus with mycophenolate mofetil (MMF) or sirolimus vs. cyclosporine with MMF in cardiac transplant patients: 1-year report. Am J Trans : Off J Am Soc Trans Am Soc Trans Surg. 2006;6:1377–86. https://doi.org/10.1111/j.1600-6143.2006.01290.x.

    Article  CAS  Google Scholar 

  25. Ohmann EL, Burckart GJ, Brooks MM, Chen Y, Pravica V, Girnita DM, Zeevi A, Webber SA. Genetic polymorphisms influence mycophenolate mofetil-related adverse events in pediatric heart transplant patients. J Heart Lung Transplant. 2010;29:509–16. https://doi.org/10.1016/j.healun.2009.11.602.

    Article  PubMed  Google Scholar 

  26. Oreschak K, Saba LM, Rafaels N, Ambardekar AV, Deininger KM, Page IR, Lindenfeld J, Aquilante CL. Variants in mycophenolate and CMV antiviral drug pharmacokinetic and pharmacodynamic genes and leukopenia in heart transplant recipients. J Heart Lung Transplant. 2021;40:917–25. https://doi.org/10.1016/j.healun.2021.05.020.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Salvadori M, Tsalouchos A. Pharmacogenetics of immunosuppressant drugs: a new aspect for individualized therapy. World J Transplant. 2020;10:90–103. https://doi.org/10.5500/wjt.v10.i5.90.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Kirchner GI, Meier-Wiedenbach I, Manns MP. Clinical pharmacokinetics of everolimus. Clin Pharmacokinet. 2004;43:83–95. https://doi.org/10.2165/00003088-200443020-00002.

    Article  CAS  PubMed  Google Scholar 

  29. Mahalati K, Kahan BD. Clinical pharmacokinetics of sirolimus. Clin Pharmacokinet. 2001;40:573–85. https://doi.org/10.2165/00003088-200140080-00002.

    Article  CAS  PubMed  Google Scholar 

  30. Lesche D, Sigurdardottir V, Setoud R, Englberger L, Fiedler GM, Largiadèr CR, Mohacsi P, Sistonen J. Influence of CYP3A5 genetic variation on everolimus maintenance dosing after cardiac transplantation. Clin Transplant. 2015;29:1213–20. https://doi.org/10.1111/ctr.12653.

    Article  CAS  PubMed  Google Scholar 

  31. Lemaitre F, Bezian E, Goldwirt L, Fernandez C, Farinotti R, Varnous S, Urien S, Antignac M. Population pharmacokinetics of everolimus in cardiac recipients: comedications, ABCB1, and CYP3A5 polymorphisms. Ther Drug Monit. 2012;34:686–94. https://doi.org/10.1097/FTD.0b013e318273c899.

    Article  CAS  PubMed  Google Scholar 

  32. Picard N, Rouguieg-Malki K, Kamar N, Rostaing L, Marquet P. CYP3A5 genotype does not influence everolimus in vitro metabolism and clinical pharmacokinetics in renal transplant recipients. Transplantation. 2011;91:652–6. https://doi.org/10.1097/TP.0b013e31820ae4ac.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Pham MX, Teuteberg JJ, Kfoury AG, Starling RC, Deng MC, Cappola TP, Kao A, Anderson AS, Cotts WG, Ewald GA, et al. Gene-expression profiling for rejection surveillance after cardiac transplantation. N Engl J Med. 2010;362:1890–900. https://doi.org/10.1056/NEJMoa0912965.

    Article  CAS  PubMed  Google Scholar 

  34. Halloran PF, Potena L, Van Huyen JD, Bruneval P, Leone O, Kim DH, Jouven X, Reeve J, Loupy A. Building a tissue-based molecular diagnostic system in heart transplant rejection: the heart Molecular Microscope Diagnostic (MMDx) System. J Heart Lung Transplant. 2017;36:1192–200. https://doi.org/10.1016/j.healun.2017.05.029.

    Article  PubMed  Google Scholar 

  35. Loupy A, Duong Van Huyen JP, Hidalgo L, Reeve J, Racapé M, Aubert O, Venner JM, Falmuski K, Bories MC, Beuscart T, et al. Gene expression profiling for the identification and classification of antibody-mediated heart rejection. Circulation. 2017;135:917–35. https://doi.org/10.1161/CIRCULATIONAHA.116.022907.

    Article  CAS  PubMed  Google Scholar 

  36. • Mantell BS, Cordero H, See SB, Clerkin KJ, Vasilescu R, Marboe CC, Naka Y, Restaino S, Colombo PC, Addonizio LJ, et al. Transcriptomic heterogeneity of antibody mediated rejection after heart transplant with or without donor specific antibodies. J Heart Lung Transplant. 2021;40:1472–80. https://doi.org/10.1016/j.healun.2021.06.012. RNA sequencing of endomyocardial biopsies demonstrated heterogeneous subtypes of acute antibody mediated rejected, likely related to mechanism of allograft injury.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Kopecky BJ, Dun H, Amrute JM, Lin CY, Bredemeyer AL, Terada Y, Bayguinov PO, Koenig AL, Frye CC, Fitzpatrick JAJ, et al. Donor macrophages modulate rejection after heart transplantation. Circulation. 2022;146:623–38. https://doi.org/10.1161/circulationaha.121.057400.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Amancherla K, Qin J, Hulke M, Pfeiffer R, Lindenfeld J, Schlendorf K, Tucker N, Moslehi J. Single-nuclear RNA-sequencing identifies cell-specific transcriptional programs in cardiac allograft vasculopathy. J Heart Lung Transplant. 2022;41:S150. https://doi.org/10.1016/j.healun.2022.01.355.

    Article  Google Scholar 

  39. Li JSY, Raghubar AM, Matigian NA, Ng MSY, Rogers NM, Mallett AJ. The utility of spatial transcriptomics for solid organ transplantation. Transplantation. 9900. https://pubmed.ncbi.nlm.nih.gov/36584371

  40. Katz DH, Robbins JM, Deng S, Tahir UA, Bick AG, Pampana A, Yu Z, Ngo D, Benson MD, Chen ZZ, et al. Proteomic profiling platforms head to head: leveraging genetics and clinical traits to compare aptamer- and antibody-based methods. Sci Adv. 2022;8:eabm5164. https://doi.org/10.1126/sciadv.abm5164.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. • Truby LK, Kwee LC, Agarwal R, Grass E, DeVore AD, Patel CB, Chen D, Schroder JN, Bowles D, Milano CA, et al. Proteomic profiling identifies CLEC4C expression as a novel biomarker of primary graft dysfunction after heart transplantation. J Heart Lung Transplant. 2021;40:1589–98. https://doi.org/10.1016/j.healun.2021.07.024. ProteomicprofilingidentifiedbiomarkerCLEC4Casbeingassociatedwithprimarygraftdysfunction,suggestingaroleofantigenpresentingcells’interferon-based response in the pathogenesis of transient allograft dysfunction.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Wei D, Trenson S, Van Keer JM, Melgarejo J, Cutsforth E, Thijs L, He T, Latosinska A, Ciarka A, Vanassche T, et al. The novel proteomic signature for cardiac allograft vasculopathy. ESC Heart Fail. 2022;9:1216–27. https://doi.org/10.1002/ehf2.13796.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Almufleh A, Zhang L, Mielniczuk LM, Stadnick E, Davies RA, Du Q, Rayner K, Liu PP, Chih S. Biomarker discovery in cardiac allograft vasculopathy using targeted aptamer proteomics. Clin Transplant. 2020;34:e13765. https://doi.org/10.1111/ctr.13765.

    Article  CAS  PubMed  Google Scholar 

  44. Cheng S, Shah SH, Corwin EJ, Fiehn O, Fitzgerald RL, Gerszten RE, Illig T, Rhee EP, Srinivas PR, Wang TJ, et al. Potential impact and study considerations of metabolomics in cardiovascular health and disease: a scientific statement from the American Heart Association. Circ Cardiovasc Genet. 2017;10. https://doi.org/10.1161/HCG.0000000000000032

  45. Lin F, Ou Y, Huang CZ, Lin SZ, Ye YB. Metabolomics identifies metabolite biomarkers associated with acute rejection after heart transplantation in rats. Sci Rep. 2017;7:15422. https://doi.org/10.1038/s41598-017-15761-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Hautbergue T, Laverdure F, Van SD, Vallee A, Sanchis-Borja M, Decante B, Gaillard M, Junot C, Fenaille F, Mercier O, et al. Metabolomic profiling of cardiac allografts after controlled circulatory death J Heart Lung Transplanthttps://doi.org/10.1016/j.healun.2023.02.1492

  47. Truby LK, Bowles D, Casalinova S, Kwee LC, Ilkayeva O, Muehlbauer M, Huebner J, Holley C, DeVore AD, Patel C, et al. Metabolomic profiling during ex-vivo normothermic perfusion prior to heart transplantation defines patterns of substrate utilization and correlates with markers of allograft injury. J Heart Lung Transplant. 2023;42:S77. https://doi.org/10.1016/j.healun.2023.02.168.

    Article  Google Scholar 

  48. Record M, Subra C, Silvente-Poirot S, Poirot M. Exosomes as intercellular signalosomes and pharmacological effectors. Biochem Pharmacol. 2011;81:1171–82. https://doi.org/10.1016/j.bcp.2011.02.011.

    Article  CAS  PubMed  Google Scholar 

  49. Simpson RJ, Jensen SS, Lim JW. Proteomic profiling of exosomes: current perspectives. Proteomics. 2008;8:4083–99. https://doi.org/10.1002/pmic.200800109.

    Article  CAS  PubMed  Google Scholar 

  50. Benichou G, Prunevieille A. Graft-derived exosomes. When small vesicles play a big role in transplant rejection. Am J Transplant. 2018;18:1585–6. https://doi.org/10.1111/ajt.14720.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Mirzakhani M, Mohammadnia-Afrouzi M, Shahbazi M, Mirhosseini SA, Hosseini HM, Amani J. The exosome as a novel predictive/diagnostic biomarker of rejection in the field of transplantation. Clin Immunol. 2019;203:134–41. https://doi.org/10.1016/j.clim.2019.04.010.

    Article  CAS  PubMed  Google Scholar 

  52. Palmieri V, Mansueto G, Coscioni E, Maiello C, Benincasa G, Napoli C. Novel biomarkers useful in surveillance of graft rejection after heart transplantation. Transpl Immunol. 2021;67:101406. https://doi.org/10.1016/j.trim.2021.101406.

    Article  CAS  PubMed  Google Scholar 

  53. Peche H, Heslan M, Usal C, Amigorena S, Cuturi MC. Presentation of donor major histocompatibility complex antigens by bone marrow dendritic cell-derived exosomes modulates allograft rejection. Transplantation. 2003;76:1503–10. https://doi.org/10.1097/01.TP.0000092494.75313.38.

    Article  CAS  PubMed  Google Scholar 

  54. Peche H, Renaudin K, Beriou G, Merieau E, Amigorena S, Cuturi MC. Induction of tolerance by exosomes and short-term immunosuppression in a fully MHC-mismatched rat cardiac allograft model. Am J Transplant. 2006;6:1541–50. https://doi.org/10.1111/j.1600-6143.2006.01344.x.

    Article  CAS  PubMed  Google Scholar 

  55. Song J, Huang J, Chen X, Teng X, Song Z, Xing Y, Wang M, Chen K, Wang Z, Yang P, et al. Donor-derived exosomes induce specific regulatory T cells to suppress immune inflammation in the allograft heart. Sci Rep. 2016;7:20077. https://doi.org/10.1038/srep20077.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Liu Q, Rojas-Canales DM, Divito SJ, Shufesky WJ, Stolz DB, Erdos G, Sullivan ML, Gibson GA, Watkins SC, Larregina AT, et al. Donor dendritic cell-derived exosomes promote allograft-targeting immune response. J Clin Invest. 2016;126:2805–20. https://doi.org/10.1172/JCI84577.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Marino J, Babiker-Mohamed MH, Crosby-Bertorini P, Paster JT, LeGuern C, Germana S, Abdi R, Uehara M, Kim JI, Markmann JF, et al. Donor exosomes rather than passenger leukocytes initiate alloreactive T cell responses after transplantation. Sci Immunol. 2016;1:1. https://doi.org/10.1126/sciimmunol.aaf8759.

    Article  Google Scholar 

  58. Montecalvo A, Shufesky WJ, Stolz DB, Sullivan MG, Wang Z, Divito SJ, Papworth GD, Watkins SC, Robbins PD, Larregina AT, et al. Exosomes as a short-range mechanism to spread alloantigen between dendritic cells during T cell allorecognition. J Immunol. 2008;180:3081–90. https://doi.org/10.4049/jimmunol.180.5.3081.

    Article  CAS  PubMed  Google Scholar 

  59. Morelli AE, Bracamonte-Baran W, Burlingham WJ. Donor-derived exosomes: the trick behind the semidirect pathway of allorecognition. Curr Opin Organ Transplant. 2017;22:46–54. https://doi.org/10.1097/MOT.0000000000000372.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Habertheuer A, Korutla L, Rostami S, Reddy S, Lal P, Naji A, Vallabhajosyula P. Donor tissue-specific exosome profiling enables noninvasive monitoring of acute rejection in mouse allogeneic heart transplantation. J Thorac Cardiovasc Surg. 2018;155:2479–89. https://doi.org/10.1016/j.jtcvs.2017.12.125.

    Article  PubMed  Google Scholar 

  61. Vallabhajosyula P, Korutla L, Habertheuer A, Yu M, Rostami S, Yuan CX, Reddy S, Liu C, Korutla V, Koeberlein B, et al. Tissue-specific exosome biomarkers for noninvasively monitoring immunologic rejection of transplanted tissue. J Clin Invest. 2017;127:1375–91. https://doi.org/10.1172/JCI87993.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Kennel PJ, Saha A, Maldonado DA, Givens R, Brunjes DL, Castillero E, Zhang X, Ji R, Yahi A, George I, et al. Serum exosomal protein profiling for the non-invasive detection of cardiac allograft rejection. J Heart Lung Transplant. 2018;37:409–17. https://doi.org/10.1016/j.healun.2017.07.012.

    Article  PubMed  Google Scholar 

  63. Castellani C, Burrello J, Fedrigo M, Burrello A, Bolis S, Di Silvestre D, Tona F, Bottio T, Biemmi V, Toscano G, et al. Circulating extracellular vesicles as non-invasive biomarker of rejection in heart transplant. J Heart Lung Transplant. 2020;39:1136–48. https://doi.org/10.1016/j.healun.2020.06.011.

    Article  PubMed  Google Scholar 

  64. Sukma Dewi I, Celik S, Karlsson A, Hollander Z, Lam K, McManus JW, Tebbutt S, Ng R, Keown P, McMaster R, et al. Exosomal miR-142-3p is increased during cardiac allograft rejection and augments vascular permeability through down-regulation of endothelial RAB11FIP2 expression. Cardiovasc Res. 2017;113:440–52. https://doi.org/10.1093/cvr/cvw244.

    Article  CAS  PubMed  Google Scholar 

  65. Sharma M, Liu W, Perincheri S, Gunasekaran M, Mohanakumar T. Exosomes expressing the self-antigens myosin and vimentin play an important role in syngeneic cardiac transplant rejection induced by antibodies to cardiac myosin. Am J Transplant. 2018;18:1626–35. https://doi.org/10.1111/ajt.14650.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Sharma M, Ravichandran R, Bansal S, Bremner RM, Smith MA, Mohanakumar T. Tissue-associated self-antigens containing exosomes: role in allograft rejection. Hum Immunol. 2018;79:653–8. https://doi.org/10.1016/j.humimm.2018.06.005.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Giangreco NP, Lebreton G, Restaino S, Jane Farr M, Zorn E, Colombo PC, Patel J, Levine R, Truby L, Soni RK, et al. Plasma kallikrein predicts primary graft dysfunction after heart transplant. J Heart Lung Transplant. 2021;40:1199–211. https://doi.org/10.1016/j.healun.2021.07.001.

    Article  PubMed  PubMed Central  Google Scholar 

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Funding

LKT receives funding from the AHA (https://doi.org/10.58275/AHA.23CDA1050881.pc.gr.167969). KKK receives funding from the NIH (R01 CA22976605).

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LKT wrote the main manuscript text and prepared all tables and figures. DM, AS, and JA contributed sections of the manuscript. All other authors reviewed the manuscript.

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Truby, L.K., Maamari, D., Saha, A. et al. Towards Allograft Longevity: Leveraging Omics Technologies to Improve Heart Transplant Outcomes. Curr Heart Fail Rep 20, 493–503 (2023). https://doi.org/10.1007/s11897-023-00631-z

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  • DOI: https://doi.org/10.1007/s11897-023-00631-z

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