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Endotypes and the Path to Precision in Moderate and Severe Traumatic Brain Injury

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Abstract

Heterogeneity is recognized as a major barrier in efforts to improve the care and outcomes of patients with traumatic brain injury (TBI). Even within the narrower stratum of moderate and severe TBI, current management approaches do not capture the complexity of this condition characterized by manifold clinical, anatomical, and pathophysiologic features. One approach to heterogeneity may be to resolve undifferentiated TBI populations into endotypes, subclasses that are distinguished by shared biological characteristics. The endotype paradigm has been explored in a range of medical domains, including psychiatry, oncology, immunology, and pulmonology. In intensive care, endotypes are being investigated for syndromes such as sepsis and acute respiratory distress syndrome. This review provides an overview of the endotype paradigm as well as some of its methods and use cases. A conceptual framework is proposed for endotype research in moderate and severe TBI, together with a scientific road map for endotype discovery and validation in this population.

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References

  1. Khellaf A, Khan DZ, Helmy A. Recent advances in traumatic brain injury. J Neurol. 2019;266(11):2878–89. https://doi.org/10.1007/s00415-019-09541-4.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Dewan MC, Rattani A, Gupta S, et al. Estimating the global incidence of traumatic brain injury. J Neurosurg. 2018;130(4):1080–97. https://doi.org/10.3171/2017.10.JNS17352.

    Article  Google Scholar 

  3. Taylor CA, Bell JM, Breiding MJ, Xu L. Traumatic brain injury-related emergency department visits, hospitalizations, and deaths—United States, 2007 and 2013. MMWR Surveill Summ. 2017;66(9):1–16.

    Article  Google Scholar 

  4. Wright DW, Yeatts SD, Silbergleit R, et al. Very early administration of progesterone for acute traumatic brain injury. N Engl J Med. 2014;371(26):2457–66. https://doi.org/10.1056/NEJMoa1404304.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Skolnick BE, Maas AI, Narayan RK, et al. A clinical trial of progesterone for severe traumatic brain injury. N Engl J Med. 2014;371(26):2467–76. https://doi.org/10.1056/NEJMoa1411090.

    Article  CAS  PubMed  Google Scholar 

  6. Hutchinson PJ, Kolias AG, Timofeev IS, et al. Trial of decompressive craniectomy for traumatic intracranial hypertension. N Engl J Med. 2016;375(12):1119–30. https://doi.org/10.1056/NEJMoa1605215.

    Article  PubMed  Google Scholar 

  7. Andrews PJD, Sinclair HL, Rodriguez A, et al. Hypothermia for intracranial hypertension after traumatic brain injury. N Engl J Med. 2015;373(25):2403–12. https://doi.org/10.1056/NEJMoa1507581.

    Article  CAS  PubMed  Google Scholar 

  8. Zafar SN, Khan AA, Ghauri AA, Shamim MS. Phenytoin versus leviteracetam for seizure prophylaxis after brain injury—a meta analysis. BMC Neurol. 2012;12:30. https://doi.org/10.1186/1471-2377-12-30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Cooper DJ, Nichol AD, Bailey M, et al. Effect of early sustained prophylactic hypothermia on neurologic outcomes among patients with severe traumatic brain injury: the POLAR Randomized Clinical Trial. JAMA. 2018;320(21):2211–20. https://doi.org/10.1001/jama.2018.17075.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Cooper DJ, Rosenfeld JV, Murray L, et al. Decompressive craniectomy in diffuse traumatic brain injury. N Engl J Med. 2011;364(16):1493–502. https://doi.org/10.1056/NEJMoa1102077.

    Article  CAS  PubMed  Google Scholar 

  11. Chesnut RM, Temkin N, Carney N, et al. A trial of intracranial-pressure monitoring in traumatic brain injury. N Engl J Med. 2012;367(26):2471–81. https://doi.org/10.1056/NEJMoa1207363.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Luo P, Li X, Wu X, et al. Preso regulates NMDA receptor-mediated excitotoxicity via modulating nitric oxide and calcium responses after traumatic brain injury. Cell Death Dis. 2019;10(7):1–14. https://doi.org/10.1038/s41419-019-1731-x.

    Article  CAS  Google Scholar 

  13. Werner C, Engelhard K. Pathophysiology of traumatic brain injury. Br J Anaesth. 2007;99(1):4–9. https://doi.org/10.1093/bja/aem131.

    Article  CAS  PubMed  Google Scholar 

  14. Menon DK, Schwab K, Wright DW, Maas AI. Position statement: definition of traumatic brain injury. Arch Phys Med Rehabil. 2010;91(11):1637–40. https://doi.org/10.1016/j.apmr.2010.05.017.

    Article  PubMed  Google Scholar 

  15. Varadhan R, Segal JB, Boyd CM, Wu AW, Weiss CO. A framework for the analysis of heterogeneity of treatment effect in patient-centered outcomes research. J Clin Epidemiol. 2013;66(8):818–25. https://doi.org/10.1016/j.jclinepi.2013.02.009.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Teasdale G, Jennett B. Assessment of coma and impaired consciousness. A practical scale. Lancet. 1974;2(7872):81–4. https://doi.org/10.1016/s0140-6736(74)91639-0.

    Article  CAS  PubMed  Google Scholar 

  17. Steyerberg EW, Mushkudiani N, Perel P, et al. Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics. PLoS Med. 2008;5(8):e165. https://doi.org/10.1371/journal.pmed.0050165.

    Article  PubMed  PubMed Central  Google Scholar 

  18. MRC CRASH Trial Collaborators, Perel P, Arango M, et al. Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients. BMJ. 2008;336(7641):425–429. https://doi.org/10.1136/bmj.39461.643438.25

  19. Carney N, Totten AM, O’Reilly C, et al. Guidelines for the management of severe traumatic brain injury, Fourth Edition. Neurosurgery. 2017;80(1):6–15. https://doi.org/10.1227/NEU.0000000000001432.

    Article  PubMed  Google Scholar 

  20. Brennan PM, Murray GD, Teasdale GM. Simplifying the use of prognostic information in traumatic brain injury. Part 1: the GCS-Pupils score: an extended index of clinical severity. J Neurosurg. 2018;128(6):1612–20. https://doi.org/10.3171/2017.12.JNS172780.

    Article  PubMed  Google Scholar 

  21. Silverberg ND, Iaccarino MA, Panenka WJ, et al. Management of concussion and mild traumatic brain injury: a synthesis of practice guidelines. Arch Phys Med Rehabil. 2020;101(2):382–93. https://doi.org/10.1016/j.apmr.2019.10.179.

    Article  PubMed  Google Scholar 

  22. Reddy K, Sinha P, O’Kane CM, Gordon AC, Calfee CS, McAuley DF. Subphenotypes in critical care: translation into clinical practice. Lancet Respir Med. 2020;8(6):631–43. https://doi.org/10.1016/S2213-2600(20)30124-7.

    Article  PubMed  Google Scholar 

  23. Kuruvilla ME, Lee FEH, Lee GB. Understanding asthma phenotypes, endotypes, and mechanisms of disease. Clinic Rev Allerg Immunol. 2019;56(2):219–33. https://doi.org/10.1007/s12016-018-8712-1.

    Article  Google Scholar 

  24. Gottesman II, Gould TD. The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry. 2003;160(4):636–45. https://doi.org/10.1176/appi.ajp.160.4.636.

    Article  PubMed  Google Scholar 

  25. Agache I, Akdis CA. Endotypes of allergic diseases and asthma: an important step in building blocks for the future of precision medicine. Allergol Int. 2016;65(3):243–52. https://doi.org/10.1016/j.alit.2016.04.011.

    Article  CAS  PubMed  Google Scholar 

  26. Steyerberg EW, Wiegers E, Sewalt C, et al. Case-mix, care pathways, and outcomes in patients with traumatic brain injury in CENTER-TBI: a European prospective, multicentre, longitudinal, cohort study. Lancet Neurol. 2019;18(10):923–34. https://doi.org/10.1016/S1474-4422(19)30232-7.

    Article  PubMed  Google Scholar 

  27. Wenzel SE, Schwartz LB, Langmack EL, et al. Evidence that severe asthma can be divided pathologically into two inflammatory subtypes with distinct physiologic and clinical characteristics. Am J Respir Crit Care Med. 1999;160(3):1001–8. https://doi.org/10.1164/ajrccm.160.3.9812110.

    Article  CAS  PubMed  Google Scholar 

  28. Svenningsen S, Nair P. Asthma endotypes and an overview of targeted therapy for asthma. Front Med (Lausanne). 2017;4:158. https://doi.org/10.3389/fmed.2017.00158.

    Article  Google Scholar 

  29. Santus P, Saad M, Damiani G, Patella V, Radovanovic D. Current and future targeted therapies for severe asthma: managing treatment with biologics based on phenotypes and biomarkers. Pharmacol Res. 2019;146:104296. https://doi.org/10.1016/j.phrs.2019.104296.

    Article  CAS  PubMed  Google Scholar 

  30. Ortega HG, Liu MC, Pavord ID, et al. Mepolizumab treatment in patients with severe eosinophilic asthma. N Engl J Med. 2014;371(13):1198–207. https://doi.org/10.1056/NEJMoa1403290.

    Article  CAS  PubMed  Google Scholar 

  31. Genkel VV, Shaposhnik II. Conceptualization of heterogeneity of chronic diseases and atherosclerosis as a pathway to precision medicine: endophenotype, endotype, and residual cardiovascular risk. Int J Chronic Dis. 2020;2020:5950813. https://doi.org/10.1155/2020/5950813.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Battaglia M, Ahmed S, Anderson MS, et al. Introducing the endotype concept to address the challenge of disease heterogeneity in type 1 diabetes. Diabetes Care. 2020;43(1):5–12. https://doi.org/10.2337/dc19-0880.

    Article  PubMed  Google Scholar 

  33. Tromp J, Ouwerkerk W, Demissei BG, et al. Novel endotypes in heart failure: effects on guideline-directed medical therapy. Eur Heart J. 2018;39(48):4269–76. https://doi.org/10.1093/eurheartj/ehy712.

    Article  CAS  PubMed  Google Scholar 

  34. Collins FS, Varmus H. A new initiative on precision medicine. N Engl J Med. 2015;372(9):793–5. https://doi.org/10.1056/NEJMp1500523.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. DiNardo AR, Nishiguchi T, Grimm SL, et al. Tuberculosis endotypes to guide stratified host-directed therapy. Med. 2021;2(3):217–32. https://doi.org/10.1016/j.medj.2020.11.003.

    Article  CAS  PubMed  Google Scholar 

  36. Shah PP, Franke JL, Medikonda R, et al. Mutation status and postresection survival of patients with non-small cell lung cancer brain metastasis: implications of biomarker-driven therapy. J Neurosurg. Published online June 4, 2021:1–11. https://doi.org/10.3171/2020.10.JNS201787

  37. Sinha P, Delucchi KL, McAuley DF, O’Kane CM, Matthay MA, Calfee CS. Development and validation of parsimonious algorithms to classify ARDS phenotypes: secondary analyses of randomised controlled trials. Lancet Respir Med. 2020;8(3):247–57. https://doi.org/10.1016/S2213-2600(19)30369-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Famous KR, Delucchi K, Ware LB, et al. Acute respiratory distress syndrome subphenotypes respond differently to randomized fluid management strategy. Am J Respir Crit Care Med. 2017;195(3):331–8. https://doi.org/10.1164/rccm.201603-0645OC.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Calfee CS, Delucchi K, Parsons PE, et al. Subphenotypes in acute respiratory distress syndrome: latent class analysis of data from two randomised controlled trials. Lancet Respir Med. 2014;2(8):611–20. https://doi.org/10.1016/S2213-2600(14)70097-9.

    Article  PubMed  PubMed Central  Google Scholar 

  40. McAuley DF, Laffey JG, O’Kane CM, et al. Simvastatin in the acute respiratory distress syndrome. N Engl J Med. 2014;371(18):1695–703. https://doi.org/10.1056/NEJMoa1403285.

    Article  CAS  PubMed  Google Scholar 

  41. Calfee CS, Delucchi KL, Sinha P, et al. Acute respiratory distress syndrome subphenotypes and differential response to simvastatin: secondary analysis of a randomised controlled trial. Lancet Respir Med. 2018;6(9):691–8. https://doi.org/10.1016/S2213-2600(18)30177-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Seymour CW, Gomez H, Chang CCH, et al. Precision medicine for all? Challenges and opportunities for a precision medicine approach to critical illness. Crit Care. 2017;21:257. https://doi.org/10.1186/s13054-017-1836-5.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Prescott HC, Calfee CS, Thompson BT, Angus DC, Liu VX. Toward smarter lumping and smarter splitting: rethinking strategies for sepsis and acute respiratory distress syndrome clinical trial design. Am J Respir Crit Care Med. 2016;194(2):147–55. https://doi.org/10.1164/rccm.201512-2544CP.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Leligdowicz A, Matthay MA. Heterogeneity in sepsis: new biological evidence with clinical applications. Crit Care. 2019;23:80. https://doi.org/10.1186/s13054-019-2372-2.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Singer M, Deutschman CS, Seymour CW, et al. The third international consensus definitions for sepsis and septic shock (sepsis-3). JAMA. 2016;315(8):801–10. https://doi.org/10.1001/jama.2016.0287.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. DeMerle KM, Angus DC, Baillie JK, et al. Sepsis subclasses: a framework for development and interpretation. Crit Care Med. 2021;49(5):748–59. https://doi.org/10.1097/CCM.0000000000004842.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Davenport EE, Burnham KL, Radhakrishnan J, et al. Genomic landscape of the individual host response and outcomes in sepsis: a prospective cohort study. Lancet Respir Med. 2016;4(4):259–71. https://doi.org/10.1016/S2213-2600(16)00046-1.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Antcliffe DB, Burnham KL, Al-Beidh F, et al. Transcriptomic signatures in sepsis and a differential response to steroids. From the VANISH randomized trial. Am J Respir Crit Care Med. 2019;199(8):980–6. https://doi.org/10.1164/rccm.201807-1419OC.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Antcliffe DB, Gordon AC. Why understanding sepsis endotypes is important for steroid trials in septic shock. Crit Care Med. 2019;47(12):1782–4. https://doi.org/10.1097/CCM.0000000000003833.

    Article  PubMed  Google Scholar 

  50. Sweeney TE, Azad TD, Donato M, et al. Unsupervised analysis of transcriptomics in bacterial sepsis across multiple datasets reveals three robust clusters. Crit Care Med. 2018;46(6):915–25. https://doi.org/10.1097/CCM.0000000000003084.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Girard TD, Thompson JL, Pandharipande PP, et al. Clinical phenotypes of delirium during critical illness and severity of subsequent long-term cognitive impairment: a prospective cohort study. Lancet Respir Med. 2018;6(3):213–22. https://doi.org/10.1016/S2213-2600(18)30062-6.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Sinha P, Delucchi KL, Chen Y, et al. Latent class analysis-derived subphenotypes are generalisable to observational cohorts of acute respiratory distress syndrome: a prospective study. Thorax. Published online July 12, 2021:thoraxjnl-2021–217158. https://doi.org/10.1136/thoraxjnl-2021-217158

  53. Sinha P, Calfee CS, Delucchi KL. Practitioner’s guide to latent class analysis: methodological considerations and common pitfalls. Crit Care Med. 2021;49(1):e63–79. https://doi.org/10.1097/CCM.0000000000004710.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Kondziella D, Menon DK, Helbok R, et al. A precision medicine framework for classifying patients with disorders of consciousness: advanced classification of consciousness endotypes (ACCESS). Neurocrit Care. 2021;35(Suppl 1):27–36. https://doi.org/10.1007/s12028-021-01246-9.

    Article  PubMed  Google Scholar 

  55. Sandsmark DK, Bashir A, Wellington CL, Diaz-Arrastia R. Cerebral microvascular injury: a potentially treatable endophenotype of traumatic brain injury-induced neurodegeneration. Neuron. 2019;103(3):367–79. https://doi.org/10.1016/j.neuron.2019.06.002.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Dhar R, Falcone GJ, Chen Y, et al. Deep learning for automated measurement of hemorrhage and perihematomal edema in supratentorial intracerebral hemorrhage. Stroke. 2020;51(2):648–51. https://doi.org/10.1161/STROKEAHA.119.027657.

    Article  PubMed  Google Scholar 

  57. Nielson JL, Cooper SR, Yue JK, et al. Uncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysis. PLoS ONE. 2017;12(3):e0169490. https://doi.org/10.1371/journal.pone.0169490.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Huibregtse ME, Bazarian JJ, Shultz SR, Kawata K. The biological significance and clinical utility of emerging blood biomarkers for traumatic brain injury. Neurosci Biobehav Rev. 2021;130:433–47. https://doi.org/10.1016/j.neubiorev.2021.08.029.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Jahns FP, Miroz JP, Messerer M, et al. Quantitative pupillometry for the monitoring of intracranial hypertension in patients with severe traumatic brain injury. Crit Care. 2019;23(1):155. https://doi.org/10.1186/s13054-019-2436-3.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Haveman ME, Van Putten MJAM, Hom HW, Eertman-Meyer CJ, Beishuizen A, Tjepkema-Cloostermans MC. Predicting outcome in patients with moderate to severe traumatic brain injury using electroencephalography. Crit Care. 2019;23(1):401. https://doi.org/10.1186/s13054-019-2656-6.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Lee H, Mizrahi MA, Hartings JA, et al. Continuous electroencephalography after moderate to severe traumatic brain injury. Crit Care Med. 2019;47(4):574–82. https://doi.org/10.1097/CCM.0000000000003639.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Jha RM, Elmer J, Zusman BE, et al. Intracranial pressure trajectories: a novel approach to informing severe traumatic brain injury Phenotypes. Crit Care Med. 2018;46(11):1792–802. https://doi.org/10.1097/CCM.0000000000003361.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Pollard TJ, Johnson AEW, Raffa JD, Celi LA, Mark RG, Badawi O. The eICU collaborative research database, a freely available multi-center database for critical care research. Sci Data. 2018;5:180178. https://doi.org/10.1038/sdata.2018.178.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Johnson AEW, Pollard TJ, Shen L, et al. MIMIC-III, a freely accessible critical care database. Sci Data. 2016;3:160035. https://doi.org/10.1038/sdata.2016.35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Yue JK, Vassar MJ, Lingsma HF, et al. Transforming research and clinical knowledge in traumatic brain injury pilot: multicenter implementation of the common data elements for traumatic brain injury. J Neurotrauma. 2013;30(22):1831–44. https://doi.org/10.1089/neu.2013.2970.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Maas AIR, Menon DK, Steyerberg EW, et al. Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI): a prospective longitudinal observational study. Neurosurgery. 2015;76(1):67–80. https://doi.org/10.1227/NEU.0000000000000575.

    Article  PubMed  Google Scholar 

  67. Bowman K, Matney C, Berwick DM. Improving Traumatic Brain Injury Care and Research: A Report From the National Academies of Sciences, Engineering, and Medicine. JAMA. 2022;327(5):419–20. https://doi.org/10.1001/jama.2022.0089.

    Article  PubMed  Google Scholar 

  68. Bhatraju PK, Zelnick LR, Herting J, et al. Identification of acute kidney injury subphenotypes with differing molecular signatures and responses to vasopressin therapy. Am J Respir Crit Care Med. 2019;199(7):863–72. https://doi.org/10.1164/rccm.201807-1346OC.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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TDA created the article outline, performed the literature review, and wrote the manuscript. PPS participated in the literature review and drafting of the manuscript. HBK reviewed and edited the manuscript. RDS conceptualized the article and reviewed and edited the manuscript. The final manuscript was approved by all authors.

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Azad, T.D., Shah, P.P., Kim, H.B. et al. Endotypes and the Path to Precision in Moderate and Severe Traumatic Brain Injury. Neurocrit Care 37 (Suppl 2), 259–266 (2022). https://doi.org/10.1007/s12028-022-01475-6

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