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Elevated inflammation and decreased platelet activity is associated with poor outcomes after traumatic brain injury
Journal of Clinical Neuroscience xxx (xxxx) xxx
Contents lists available at ScienceDirect
Journal of Clinical Neuroscience journal homepage: www.elsevier.com/locate/jocn
Clinical study
Elevated inflammation and decreased platelet activity is associated with poor outcomes after traumatic brain injury Cole T. Lewis, Jude P.J. Savarraj, Mary F. McGuire, Georgene W. Hergenroeder, H. Alex Choi, Ryan S. Kitagawa ⇑ Department of Neurosurgery, University of Texas McGovern Medical School, Houston, TX, United States
a r t i c l e
i n f o
Article history: Received 5 April 2019 Accepted 4 September 2019 Available online xxxx Keywords: Traumatic brain injury Functional outcome Inflammation Cytokine levels Early brain injury Neuroinflammation Cytokine analysis
a b s t r a c t The inflammatory processes following traumatic brain injury (TBI) have not been fully characterized. We hypothesize that differences in systemic cytokine/chemokine (CC) levels are associated with TBI clinical outcomes. To test this hypothesis, we examined systemic levels of CCs and their relationship with patient outcomes. Plasma from acute TBI subjects was collected at 24–48 h, and the CC levels were measured using a multiplex 41-plex-kit. Clinical outcomes were assessed using the modified Rankin scale (mRS) with good outcomes defined as mRS 3 and poor outcome as mRS 4. The differences in CC concentrations between groups were then compared using the Mann-Whitney U test. Seventy-six acute TBI subjects were included in this study. In the mRS 4 group, interleukin-6 (IL-6) and interleukin-10 (IL-10) were elevated, indicating early activation of immune reaction and modulation. Simultaneously, PDGFAA and RANTES were lower in the mRS 4 group. Poor outcomes after TBI were associated with elevated levels of IL-6 and IL-10 and lower levels of PDGFAA and RANTES within 24–48 h after injury. Published by Elsevier Ltd.
1. Introduction Traumatic brain injury (TBI) kills 153 people a day in the United States and almost 3 million people suffered TBI in 2013 [1]. Patients who survive the initial injury may endure long-lasting effects including cognitive deficits, depression, personality changes and functional disability. However, the processes leading to these secondary injuries are unclear. We hypothesize that TBI is associated with an increase in systemic inflammatory response characterized by elevation cytokines and chemokines across patient outcomes. Identification of cytokine/chemokines (CC) early after TBI could result in improved stratification of patient severity and can lead to the development of therapies that can potentially improve outcomes. Specific cytokines have been associated with the inflammatory response after acute brain injury [2–5] and TBI. For example, tumor necrosis factor-a (TNF-a) and interleukin-6 (IL-6) have been identified as being pro-inflammatory, while transforming growth factor-b (TGF-b) is considered anti-inflammatory [6]. However, inflammation may either help or hinder healing depending on the timing, duration, and levels of pro- and anti-inflammatory cytokines after TBI [7]. To gain more insight into CC interactions ⇑ Corresponding author at: Department of Neurosurgery, University of Texas McGovern Medical School, 6400 Fannin St, Houston, TX 77030, United States. E-mail address: [email protected] (R.S. Kitagawa).
after TBI, we conducted a pilot study to identify CC’s and their relationship with patients’ outcomes.
2. Subjects, materials, and methods 2.1. Study population and patient criteria This is a retrospective cohort study of 76 patients with TBI admitted to the neuroscience intensive care unit at the Memorial Herman Hospital-Texas Medical Center from July 2013 to March 2015. Inclusion criteria were age >18 years and diagnosis of a TBI. Patients with any conditions that could affect baseline inflammation, including history of malignancy, autoimmune diseases and current pregnancy, were excluded. Demographic and clinical information was collected prospectively. Functional outcomes at discharge were assessed by the modified Rankin scale (mRS) [8–10]. Good clinical outcomes were defined as mRS 3 and poor clinical outcomes were an mRS 4.
2.2. Standard protocol approvals, registrations, and patient consents The study was conducted with approval of the Institutional Review Board (IRB Protocol Number HSC-MS-14-0319). Written informed consent was obtained from the patient or surrogate.
https://doi.org/10.1016/j.jocn.2019.09.004 0967-5868/Published by Elsevier Ltd.
Please cite this article as: C. T. Lewis, J. P. J. Savarraj, M. F. McGuire et al., Elevated inflammation and decreased platelet activity is associated with poor outcomes after traumatic brain injury, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.09.004
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C.T. Lewis et al. / Journal of Clinical Neuroscience xxx (xxxx) xxx
2.3. Samples Blood samples were collected at 24–48 h after injury in K2EDTA vacutainer tubes and centrifuged within an hour of draw (1460 g for 10 min at 4 °C), generating plasma. Plasma was centrifuged a second time (1460 g for 10 min at 4 °C) in order to generate platelet poor plasma. Platelet poor supernatant was collected and stored at 80 °C until ready for use.
epidermal growth factor (EGF), fibroblast growth factor-2 (FGF2), colony stimulating factors (CSF2 and CSF3), macrophage-derived chemokine (MDC), tumor necrosis factors (TNFa and TNFb), the vascular endothelial growth factors (VEGFA), IL12p40, IL12p70, the soluble CD40-ligand (sCD40L), IL-1b, IP-10, type II interferon family (IFNG), interferon-alpha-2 (IFNA2), the FMS-like tyrosine kinase 3 ligand (FLT3L) and transforming growth factor alpha (TGFa). All cytokine values were expressed in picograms per milliliter (pg/ml).
2.4. Cytokine assay 2.5. Statistics Cytokine concentrations in the plasma samples were determined using a MAGPIX magnetic bead based ELISA 41-plex assay [Millipore]) and a magnetic bead plate reader (Luminex MagPix [Luminex, Austin, TX]) according to manufacturer’s instructions. The following cytokines were tested: the CC chemokines (CCL2, CCL5, CCL7, CCL11 and CCL22), the CX chemokines (CX3CL1 and CXCL1), the macrophage inflammatory proteins (MIP1A and MIP1B), the interleukin-1 superfamily (IL-1A, IL1R1, IL-4, IL-5 and IL-6), the IL-17 family (IL-17a), interleukin-2 (IL-2), interleukin-3 (IL-3), interleukin-7 (IL-7), interleukin-8 (IL-8), interleukin-9 (IL9), interleukin-10 (IL-10), interleukin-13 (IL-13), interluekin-15 (IL-15), the platelet derived factors (PDGFAA and PDGF-AB/BB),
Descriptive statistics were calculated for demographic, clinical variables and cytokine levels (in good and poor outcome groups). As appropriate, the Mann-Whitney U (2 sample) test, Pearson’s Chi [11], Fisher’s exact test, or T test (Welch approximation) were used to test for differences in cytokine levels across different groups. A multivariate logistic regression model was used to test whether the cytokines were independently associated with outcomes. Statistical analyses were performed using software packages in R (v3.1.3) and STATA (v14.2).
3. Results Table 1 Demographics. Demographics
N = 76
Age (mean, SD) Gender (female), n, % CAD, n, % HTN, n, % DM, n, % Polytrauma, n, % CT-IVH, n, % Hospital LOS (median, IQR) GCS 8, n, %
47.8, 21 16, 21% 9, 11% 24, 31 14, 18 20, 26 15, 19 15.15 (7.9–24) 7 (6–12)
CAD – cardiac death; HTN – Hypertension; DM – Diabetes mellitus; CT-IVH – Computed Tomography Intraventricular hemorrhage; LOS – length of stay; SD – Standard deviation; IQR – Interquartile range; GCS – Glasgow coma scale.
Seventy-six patients were included in the study (see Table 1). There were no significant differences between good and poor outcomes for age, gender, presence of coronary artery disease, hypertension, diabetes mellitus, or polytrauma; intraventricular hemorrhage on computed tomography, hospital length of stay and admission Glasgow Coma Scale (GCS) 8 did differentiate the groups. Eight of the 41 cytokines measured also differentiated the groups: Eotaxin (CCL11), GRO (CXCL1), IL-6, IL-10, MCP3 (CCL7), PDGFAA, RANTES (CCL5), and TNFbeta (TNFB). See Table 2. Poor outcomes after TBI were associated with elevated levels of IL6 and IL-10 and lower levels of RANTES and PDGFAA at 24–48 h after injury. (See Fig. 1; additional details in Table S1). In a multivariate logistic regression model, IL6, IL10 and RANTES were found to be independent predictors of poor outcomes after adjusting for age and clinical severity at admission. PGDFAA was not a statistically significant (p 0.1) predictor of poor outcome after adjusting for age and clinical severity (GCS). See Table 2.
Table 2 Descriptive statistics, and significant cytokines at 24–48 h after injury based on discharge outcomes (mRS). Demographics
mrs 3 (n = 33)
mRS 4 (n = 43)
p-value
Age (mean, SD) Gender (female), n, % CAD, n, % HTN, n, % DM, n, % Polytrauma, n, % CT-IVH, n, % Hospital LOS (median, IQR) GCS 8, n, % Cytokines (median, IQR) EOTAXIN|CCL11 GRO|CXCL1 IL6 IL10 RANTES PDGFAA MCP3|CCL7
48 ± 23 9 (28) 3 (9) 10 (31) 6 (19) 6 (19) 3 (9) 10 (6–17) 13 (41)
47 ± 21 7 (18) 5 (14) 11 (30) 8 (22) 12 (30) 12 (30) 20 (10–27) 27 (68)
NS NS NS NS NS NS <0.05 <0.05 <0.05
155 (98–273) 285 (197–396) 133 (79–244) 33 (23–47) 5914 (3272–8501) 928 (461–1202) 101 (22–339)
91 (65–166) 184 (119–321) 190 (126–661) 49 (33–70) 2454 (1688–5737) 543 (264–873) 29 (18–66)
<0.01 <0.05 <0.05* <0.05* <0.05* <0.05y <0.05
CAD – cardiac death; HTN – Hypertension; DM – Diabetes mellitus; CT-IVH – Computed Tomography Intraventricular hemorrhage; LOS – length of stay; SD – Standard deviation; IQR – Interquartile range; GCS – Glasgow coma scale. * denotes significance (p < 0.05) after controlling for age and GCS score at admission in a multivariate logistic regression model. y denotes near significance (p 0.1) after controlling for age and GCS score at admission in a multivariate logistic regression model.
Please cite this article as: C. T. Lewis, J. P. J. Savarraj, M. F. McGuire et al., Elevated inflammation and decreased platelet activity is associated with poor outcomes after traumatic brain injury, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.09.004
C.T. Lewis et al. / Journal of Clinical Neuroscience xxx (xxxx) xxx
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Fig. 1. Poor outcomes after TBI were associated with elevated levels of IL-6 and IL-10 and lower levels of RANTES and PDGFAA at 24–48 h after injury.
4. Discussion Our study found that by 24–48 h patients who subsequently demonstrated poor outcome (mRS 4) had an associated increased expression of pro-inflammatory cytokine IL-6 and antiinflammatory cytokine IL-10. Platelet-derived molecules such as RANTES and PDGFAA were downregulated. The interleukin cytokines IL-6 and IL-10 have been well characterized as biomarkers of TBI [12] and early elevation of these cytokines has been associated with poor outcomes [13]. IL-6 is an interleukin that acts primarily as a pro-inflammatory cytokine and is secreted by T cells and macrophages to stimulate the immune response. In the CNS increased glial and neuronal IL6 production to promote neuronal survival has also been suggested to be a source of elevated IL-6 plasma levels after brain injury [14,15]. Although generally considered a pro-inflammatory cytokine, IL-6 may better be characterized as a modulator as it also has anti-inflammatory properties [16]. IL-10 is an antiinflammatory cytokine that inhibits synthesis of proinflammatory cytokines such as IFN-c, IL-2, IL-3, TNFa and GMCSF. It is secreted by monocytes and lymphocytes and has pleiotropic effects including immune regulation and inflammation. IL-10
has also been found to be an independent biomarker of mortality after severe traumatic brain injury [17]. The simultaneous elevation of pro- and anti-inflammatory cytokines in patients with poor outcomes after TBI implies a pathological response that may contribute to a poor outcome or be a marker for the severity of the disease. PDGFAA is the primary platelet-derived growth factor (PDGF) dimer found in human platelets and in acute human wound fluid [18]. This factor plays an essential role in the regulation of embryonic development, cell proliferation, migration, division, survival and chemotaxis. Synthesis of PDGF occurs due to external stimuli such as thrombin, low oxygen tension, or other cytokines and growth factors [19]. In studies of subarachnoid hemorrhage, markers of acute platelet activation, such as C-reactive protein and PDGF, have been significantly elevated in patients with poor outcomes [5,20]. However, in this TBI study, PDGFAA levels were lower in TBI patients with poor outcomes. RANTES (CCL5) is a chemoattractant for blood monocytes, memory T-helper cells and eosinophils. It also causes the release of histamine from basophils and activates eosinophils. One study found that only severe TBI patients had elevated plasma RANTES at admission; however, RANTES levels at Day 1 and Day 7 were not statistically predictive
Please cite this article as: C. T. Lewis, J. P. J. Savarraj, M. F. McGuire et al., Elevated inflammation and decreased platelet activity is associated with poor outcomes after traumatic brain injury, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.09.004
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of mortality [21]. Here, by 24–48 h after injury RANTES levels were reduced in TBI patients with poor outcomes.
4.1. Inflammatory response Our results are consistent with other studies of inflammatory response in trauma, including those with data-driven models. Significant differences in cerebrospinal fluid levels of IL-4, IL-5, IL-6, IL-8, IL-13 and TNFa were observed between TBI survivors vs. non-survivors over 5 days. This dynamic inflammatory response was further analyzed by principal component analysis (PCA) and dynamic Bayesian network (DyBN) inference and the results suggested that select molecules switched pro and anti-inflammatory roles over time. A mechanistic model of TBI based on the changes over time of key inflammatory response molecules (including TNFa, IL-6, and IL-10) showed that the dynamic time course of inflammatory mediators separated survivors from non-survivors [22]. Another study identified six candidate predictors of multiple organ failure after trauma: IP-10, MIP-1beta, IL-10, IL-6, IL-1Ra, and eotaxin [23]. Using cerebral microdialysis and paired arterial and jugular bulb plasma sampling of severe TBI patients, temporal peaks were reported on day one for PDGFAA and RANTES in addition to TNF-alpha, IL-7, IL-8, MIP-1alpha, sCD40L, GRO, IL1B, MIP1beta; and on day two for IL-6 and IL1ra, G-CSF, and CXCL10 (IP10) [24]. In an eight day model of aneurysmal subarachnoid hemorrhage (aSAH), PDGFAA, PDGF-AB/BB, sCD40L, and TNF-alpha were found to increase over time while CSF-3, IL-13, and FLT3L decreased over time [5].
4.2. Platelet dysfunction Platelet-derived molecules such as RANTES and PDGFAA were lower in TBI patients with poor outcomes. This reduction suggests that platelets, a crucial mediator of hemostasis, lost some ability to secrete molecules that (1) stabilize the thrombus after TBI-induced coagulopathy and (2) modulate immune/inflammatory response [25,26]. It has been found that platelet dysfunction, rather than platelet count [27], is associated with a strong negative prognostic factor in TBI [28]. However, it is difficult to assess platelet dysfunction based on standard laboratory tests [29,30], and decreased levels of RANTES and PDGFAA may be reasonable surrogates for assessing platelet dysfunction.
4.3. Limitations Our study is a single center observational study and bound by inherent biases of the specific population and treatment protocols. However, samples were collected early after injury and therefore mostly reflect the injury pathology. In order to determine the pathophysiologic significance of these findings, further studies and potentially interventional trials are needed. These findings may also be used as quantitative surrogate markers of disease severity and progression in the future.
5. Conclusion Several inflammatory response molecules were elevated after TBI while platelet-derived molecules were decreased 24–48 h after TBI. Inflammatory response mediators IL-6 and IL-10 were elevated while PDGFAA and RANTES were decreased, suggesting platelet dysfunction. The putative mechanisms involved in pathways that drive patient outcomes and their roles as potential targets for pharmacological treatment require further investigation.
Author contributions CL, JS, HC, and RK were involved in the conception and design of the study. CL, JS, GH and MM assisted in the acquisition and analysis of data. CL, JS, and MM contributed substantially in drafting the manuscript and figures. Acknowledgments Funding: Support from CCTS KL2 Scholars program, UTHealth McGovern Medical School. Disclosures None to declare. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.jocn.2019.09.004. References [1] 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;66:1–16. https://doi.org/10.15585/mmwr. ss6609a1. [2] Savarraj J, Parsha K, Hergenroeder G, Ahn S, Chang TR, Kim DH, et al. Early brain injury associated with systemic inflammation after subarachnoid hemorrhage. Neurocrit Care 2018;28:203–31. https://doi.org/10.1007/ s12028-017-0471-y. [3] Savarraj JP, McGuire MF, Parsha K, Hergenroeder G, Bajgur S, Ahn S, et al. Disruption of thrombo-inflammatory response and activation of a distinct cytokine cluster after subarachnoid hemorrhage. Cytokine 2018;111:334–41. https://doi.org/10.1016/j.cyto.2018.09.003. [4] Rowland B, Savarraj JPJ, Karri J, Zhang X, Cardenas J, Choi HA, et al. Acute inflammation in traumatic brain injury and polytrauma patients using network analysis. Shock 2019. https://doi.org/10.1097/ SHK.0000000000001349. [5] Savarraj JPJ, Parsha K, Hergenroeder GW, Zhu L, Bajgur SS, Ahn S, et al. Systematic model of peripheral inflammation after subarachnoid hemorrhage. Neurology 2017;88:1535–45. https://doi.org/10.1212/ WNL.0000000000003842. [6] Lenzlinger PM, Morganti-Kossmann MC, Laurer HL, McIntosh TK. The duality of the inflammatory response to traumatic brain injury. Mol Neurobiol 2001;24:169–81. https://doi.org/10.1385/MN:24:1-3:169. [7] Ziebell JM, Morganti-Kossmann MC. Involvement of pro- and antiinflammatory cytokines and chemokines in the pathophysiology of traumatic brain injury. Neurotherapeutics 2010;7:22–30. https://doi.org/10.1016/j. nurt.2009.10.016. [8] Rankin J. Cerebral vascular accidents in patients over the age of 60 II. Prognosis. Scott Med J 1957;2:200–15. https://doi.org/10.1177/003693305700200504. [9] Bonita R, Beaglehole R. Recovery of motor function after stroke. Stroke 1988;19:1497–500. https://doi.org/10.1161/01.str.19.12.1497. [10] van Swieten JC, Koudstaal PJ, Visser MC, Schouten HJ, van Gijn J. Interobserver agreement for the assessment of handicap in stroke patients. Stroke 1988;19:604–7. https://doi.org/10.1161/01.str.19.5.604. [11] Mann HB, Whitney DR. On a test of whether one of two random variables is stochastically larger than the other. Ann Math Stat 1947;18:50–60. [12] Hergenroeder GW, Moore AN, McCoy JP, Samsel L, Ward NH, Clifton GL, et al. Serum IL-6: a candidate biomarker for intracranial pressure elevation following isolated traumatic brain injury. J Neuroinflammation 2010;7:19. https://doi.org/10.1186/1742-2094-7-19. [13] Ferreira LCB, Regner A, Miotto KDL, de Moura S, Ikuta N, Vargas AE, et al. Increased levels of interleukin-6, -8 and -10 are associated with fatal outcome following severe traumatic brain injury. Brain Inj 2014;28:1311–6. https://doi. org/10.3109/02699052.2014.916818. [14] Ringheim GE, Burgher KL, Heroux JA. Interleukin-6 mRNA expression by cortical neurons in culture: evidence for neuronal sources of interleukin-6 production in the brain. J Neuroimmunol 1995;63:113–23. [15] John GR, Lee SC, Song X, Rivieccio M, Brosnan CF. IL-1-regulated responses in astrocytes: relevance to injury and recovery. Glia 2005;49:161–76. https://doi. org/10.1002/glia.20109. [16] Scheller J, Chalaris A, Schmidt-Arras D, Rose-John S. The pro- and antiinflammatory properties of the cytokine interleukin-6. Biochim Biophys Acta 2011;1813:878–88. https://doi.org/10.1016/j.bbamcr.2011.01.034. [17] Schneider Soares FM, Menezes de Souza N, Libório Schwarzbold M, Paim Diaz A, Costa Nunes J, Hohl A, et al. Interleukin-10 is an independent biomarker of
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Please cite this article as: C. T. Lewis, J. P. J. Savarraj, M. F. McGuire et al., Elevated inflammation and decreased platelet activity is associated with poor outcomes after traumatic brain injury, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.09.004
Contents lists available at ScienceDirect
Journal of Clinical Neuroscience journal homepage: www.elsevier.com/locate/jocn
Clinical study
Elevated inflammation and decreased platelet activity is associated with poor outcomes after traumatic brain injury Cole T. Lewis, Jude P.J. Savarraj, Mary F. McGuire, Georgene W. Hergenroeder, H. Alex Choi, Ryan S. Kitagawa ⇑ Department of Neurosurgery, University of Texas McGovern Medical School, Houston, TX, United States
a r t i c l e
i n f o
Article history: Received 5 April 2019 Accepted 4 September 2019 Available online xxxx Keywords: Traumatic brain injury Functional outcome Inflammation Cytokine levels Early brain injury Neuroinflammation Cytokine analysis
a b s t r a c t The inflammatory processes following traumatic brain injury (TBI) have not been fully characterized. We hypothesize that differences in systemic cytokine/chemokine (CC) levels are associated with TBI clinical outcomes. To test this hypothesis, we examined systemic levels of CCs and their relationship with patient outcomes. Plasma from acute TBI subjects was collected at 24–48 h, and the CC levels were measured using a multiplex 41-plex-kit. Clinical outcomes were assessed using the modified Rankin scale (mRS) with good outcomes defined as mRS 3 and poor outcome as mRS 4. The differences in CC concentrations between groups were then compared using the Mann-Whitney U test. Seventy-six acute TBI subjects were included in this study. In the mRS 4 group, interleukin-6 (IL-6) and interleukin-10 (IL-10) were elevated, indicating early activation of immune reaction and modulation. Simultaneously, PDGFAA and RANTES were lower in the mRS 4 group. Poor outcomes after TBI were associated with elevated levels of IL-6 and IL-10 and lower levels of PDGFAA and RANTES within 24–48 h after injury. Published by Elsevier Ltd.
1. Introduction Traumatic brain injury (TBI) kills 153 people a day in the United States and almost 3 million people suffered TBI in 2013 [1]. Patients who survive the initial injury may endure long-lasting effects including cognitive deficits, depression, personality changes and functional disability. However, the processes leading to these secondary injuries are unclear. We hypothesize that TBI is associated with an increase in systemic inflammatory response characterized by elevation cytokines and chemokines across patient outcomes. Identification of cytokine/chemokines (CC) early after TBI could result in improved stratification of patient severity and can lead to the development of therapies that can potentially improve outcomes. Specific cytokines have been associated with the inflammatory response after acute brain injury [2–5] and TBI. For example, tumor necrosis factor-a (TNF-a) and interleukin-6 (IL-6) have been identified as being pro-inflammatory, while transforming growth factor-b (TGF-b) is considered anti-inflammatory [6]. However, inflammation may either help or hinder healing depending on the timing, duration, and levels of pro- and anti-inflammatory cytokines after TBI [7]. To gain more insight into CC interactions ⇑ Corresponding author at: Department of Neurosurgery, University of Texas McGovern Medical School, 6400 Fannin St, Houston, TX 77030, United States. E-mail address: [email protected] (R.S. Kitagawa).
after TBI, we conducted a pilot study to identify CC’s and their relationship with patients’ outcomes.
2. Subjects, materials, and methods 2.1. Study population and patient criteria This is a retrospective cohort study of 76 patients with TBI admitted to the neuroscience intensive care unit at the Memorial Herman Hospital-Texas Medical Center from July 2013 to March 2015. Inclusion criteria were age >18 years and diagnosis of a TBI. Patients with any conditions that could affect baseline inflammation, including history of malignancy, autoimmune diseases and current pregnancy, were excluded. Demographic and clinical information was collected prospectively. Functional outcomes at discharge were assessed by the modified Rankin scale (mRS) [8–10]. Good clinical outcomes were defined as mRS 3 and poor clinical outcomes were an mRS 4.
2.2. Standard protocol approvals, registrations, and patient consents The study was conducted with approval of the Institutional Review Board (IRB Protocol Number HSC-MS-14-0319). Written informed consent was obtained from the patient or surrogate.
https://doi.org/10.1016/j.jocn.2019.09.004 0967-5868/Published by Elsevier Ltd.
Please cite this article as: C. T. Lewis, J. P. J. Savarraj, M. F. McGuire et al., Elevated inflammation and decreased platelet activity is associated with poor outcomes after traumatic brain injury, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.09.004
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C.T. Lewis et al. / Journal of Clinical Neuroscience xxx (xxxx) xxx
2.3. Samples Blood samples were collected at 24–48 h after injury in K2EDTA vacutainer tubes and centrifuged within an hour of draw (1460 g for 10 min at 4 °C), generating plasma. Plasma was centrifuged a second time (1460 g for 10 min at 4 °C) in order to generate platelet poor plasma. Platelet poor supernatant was collected and stored at 80 °C until ready for use.
epidermal growth factor (EGF), fibroblast growth factor-2 (FGF2), colony stimulating factors (CSF2 and CSF3), macrophage-derived chemokine (MDC), tumor necrosis factors (TNFa and TNFb), the vascular endothelial growth factors (VEGFA), IL12p40, IL12p70, the soluble CD40-ligand (sCD40L), IL-1b, IP-10, type II interferon family (IFNG), interferon-alpha-2 (IFNA2), the FMS-like tyrosine kinase 3 ligand (FLT3L) and transforming growth factor alpha (TGFa). All cytokine values were expressed in picograms per milliliter (pg/ml).
2.4. Cytokine assay 2.5. Statistics Cytokine concentrations in the plasma samples were determined using a MAGPIX magnetic bead based ELISA 41-plex assay [Millipore]) and a magnetic bead plate reader (Luminex MagPix [Luminex, Austin, TX]) according to manufacturer’s instructions. The following cytokines were tested: the CC chemokines (CCL2, CCL5, CCL7, CCL11 and CCL22), the CX chemokines (CX3CL1 and CXCL1), the macrophage inflammatory proteins (MIP1A and MIP1B), the interleukin-1 superfamily (IL-1A, IL1R1, IL-4, IL-5 and IL-6), the IL-17 family (IL-17a), interleukin-2 (IL-2), interleukin-3 (IL-3), interleukin-7 (IL-7), interleukin-8 (IL-8), interleukin-9 (IL9), interleukin-10 (IL-10), interleukin-13 (IL-13), interluekin-15 (IL-15), the platelet derived factors (PDGFAA and PDGF-AB/BB),
Descriptive statistics were calculated for demographic, clinical variables and cytokine levels (in good and poor outcome groups). As appropriate, the Mann-Whitney U (2 sample) test, Pearson’s Chi [11], Fisher’s exact test, or T test (Welch approximation) were used to test for differences in cytokine levels across different groups. A multivariate logistic regression model was used to test whether the cytokines were independently associated with outcomes. Statistical analyses were performed using software packages in R (v3.1.3) and STATA (v14.2).
3. Results Table 1 Demographics. Demographics
N = 76
Age (mean, SD) Gender (female), n, % CAD, n, % HTN, n, % DM, n, % Polytrauma, n, % CT-IVH, n, % Hospital LOS (median, IQR) GCS 8, n, %
47.8, 21 16, 21% 9, 11% 24, 31 14, 18 20, 26 15, 19 15.15 (7.9–24) 7 (6–12)
CAD – cardiac death; HTN – Hypertension; DM – Diabetes mellitus; CT-IVH – Computed Tomography Intraventricular hemorrhage; LOS – length of stay; SD – Standard deviation; IQR – Interquartile range; GCS – Glasgow coma scale.
Seventy-six patients were included in the study (see Table 1). There were no significant differences between good and poor outcomes for age, gender, presence of coronary artery disease, hypertension, diabetes mellitus, or polytrauma; intraventricular hemorrhage on computed tomography, hospital length of stay and admission Glasgow Coma Scale (GCS) 8 did differentiate the groups. Eight of the 41 cytokines measured also differentiated the groups: Eotaxin (CCL11), GRO (CXCL1), IL-6, IL-10, MCP3 (CCL7), PDGFAA, RANTES (CCL5), and TNFbeta (TNFB). See Table 2. Poor outcomes after TBI were associated with elevated levels of IL6 and IL-10 and lower levels of RANTES and PDGFAA at 24–48 h after injury. (See Fig. 1; additional details in Table S1). In a multivariate logistic regression model, IL6, IL10 and RANTES were found to be independent predictors of poor outcomes after adjusting for age and clinical severity at admission. PGDFAA was not a statistically significant (p 0.1) predictor of poor outcome after adjusting for age and clinical severity (GCS). See Table 2.
Table 2 Descriptive statistics, and significant cytokines at 24–48 h after injury based on discharge outcomes (mRS). Demographics
mrs 3 (n = 33)
mRS 4 (n = 43)
p-value
Age (mean, SD) Gender (female), n, % CAD, n, % HTN, n, % DM, n, % Polytrauma, n, % CT-IVH, n, % Hospital LOS (median, IQR) GCS 8, n, % Cytokines (median, IQR) EOTAXIN|CCL11 GRO|CXCL1 IL6 IL10 RANTES PDGFAA MCP3|CCL7
48 ± 23 9 (28) 3 (9) 10 (31) 6 (19) 6 (19) 3 (9) 10 (6–17) 13 (41)
47 ± 21 7 (18) 5 (14) 11 (30) 8 (22) 12 (30) 12 (30) 20 (10–27) 27 (68)
NS NS NS NS NS NS <0.05 <0.05 <0.05
155 (98–273) 285 (197–396) 133 (79–244) 33 (23–47) 5914 (3272–8501) 928 (461–1202) 101 (22–339)
91 (65–166) 184 (119–321) 190 (126–661) 49 (33–70) 2454 (1688–5737) 543 (264–873) 29 (18–66)
<0.01 <0.05 <0.05* <0.05* <0.05* <0.05y <0.05
CAD – cardiac death; HTN – Hypertension; DM – Diabetes mellitus; CT-IVH – Computed Tomography Intraventricular hemorrhage; LOS – length of stay; SD – Standard deviation; IQR – Interquartile range; GCS – Glasgow coma scale. * denotes significance (p < 0.05) after controlling for age and GCS score at admission in a multivariate logistic regression model. y denotes near significance (p 0.1) after controlling for age and GCS score at admission in a multivariate logistic regression model.
Please cite this article as: C. T. Lewis, J. P. J. Savarraj, M. F. McGuire et al., Elevated inflammation and decreased platelet activity is associated with poor outcomes after traumatic brain injury, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.09.004
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Fig. 1. Poor outcomes after TBI were associated with elevated levels of IL-6 and IL-10 and lower levels of RANTES and PDGFAA at 24–48 h after injury.
4. Discussion Our study found that by 24–48 h patients who subsequently demonstrated poor outcome (mRS 4) had an associated increased expression of pro-inflammatory cytokine IL-6 and antiinflammatory cytokine IL-10. Platelet-derived molecules such as RANTES and PDGFAA were downregulated. The interleukin cytokines IL-6 and IL-10 have been well characterized as biomarkers of TBI [12] and early elevation of these cytokines has been associated with poor outcomes [13]. IL-6 is an interleukin that acts primarily as a pro-inflammatory cytokine and is secreted by T cells and macrophages to stimulate the immune response. In the CNS increased glial and neuronal IL6 production to promote neuronal survival has also been suggested to be a source of elevated IL-6 plasma levels after brain injury [14,15]. Although generally considered a pro-inflammatory cytokine, IL-6 may better be characterized as a modulator as it also has anti-inflammatory properties [16]. IL-10 is an antiinflammatory cytokine that inhibits synthesis of proinflammatory cytokines such as IFN-c, IL-2, IL-3, TNFa and GMCSF. It is secreted by monocytes and lymphocytes and has pleiotropic effects including immune regulation and inflammation. IL-10
has also been found to be an independent biomarker of mortality after severe traumatic brain injury [17]. The simultaneous elevation of pro- and anti-inflammatory cytokines in patients with poor outcomes after TBI implies a pathological response that may contribute to a poor outcome or be a marker for the severity of the disease. PDGFAA is the primary platelet-derived growth factor (PDGF) dimer found in human platelets and in acute human wound fluid [18]. This factor plays an essential role in the regulation of embryonic development, cell proliferation, migration, division, survival and chemotaxis. Synthesis of PDGF occurs due to external stimuli such as thrombin, low oxygen tension, or other cytokines and growth factors [19]. In studies of subarachnoid hemorrhage, markers of acute platelet activation, such as C-reactive protein and PDGF, have been significantly elevated in patients with poor outcomes [5,20]. However, in this TBI study, PDGFAA levels were lower in TBI patients with poor outcomes. RANTES (CCL5) is a chemoattractant for blood monocytes, memory T-helper cells and eosinophils. It also causes the release of histamine from basophils and activates eosinophils. One study found that only severe TBI patients had elevated plasma RANTES at admission; however, RANTES levels at Day 1 and Day 7 were not statistically predictive
Please cite this article as: C. T. Lewis, J. P. J. Savarraj, M. F. McGuire et al., Elevated inflammation and decreased platelet activity is associated with poor outcomes after traumatic brain injury, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.09.004
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of mortality [21]. Here, by 24–48 h after injury RANTES levels were reduced in TBI patients with poor outcomes.
4.1. Inflammatory response Our results are consistent with other studies of inflammatory response in trauma, including those with data-driven models. Significant differences in cerebrospinal fluid levels of IL-4, IL-5, IL-6, IL-8, IL-13 and TNFa were observed between TBI survivors vs. non-survivors over 5 days. This dynamic inflammatory response was further analyzed by principal component analysis (PCA) and dynamic Bayesian network (DyBN) inference and the results suggested that select molecules switched pro and anti-inflammatory roles over time. A mechanistic model of TBI based on the changes over time of key inflammatory response molecules (including TNFa, IL-6, and IL-10) showed that the dynamic time course of inflammatory mediators separated survivors from non-survivors [22]. Another study identified six candidate predictors of multiple organ failure after trauma: IP-10, MIP-1beta, IL-10, IL-6, IL-1Ra, and eotaxin [23]. Using cerebral microdialysis and paired arterial and jugular bulb plasma sampling of severe TBI patients, temporal peaks were reported on day one for PDGFAA and RANTES in addition to TNF-alpha, IL-7, IL-8, MIP-1alpha, sCD40L, GRO, IL1B, MIP1beta; and on day two for IL-6 and IL1ra, G-CSF, and CXCL10 (IP10) [24]. In an eight day model of aneurysmal subarachnoid hemorrhage (aSAH), PDGFAA, PDGF-AB/BB, sCD40L, and TNF-alpha were found to increase over time while CSF-3, IL-13, and FLT3L decreased over time [5].
4.2. Platelet dysfunction Platelet-derived molecules such as RANTES and PDGFAA were lower in TBI patients with poor outcomes. This reduction suggests that platelets, a crucial mediator of hemostasis, lost some ability to secrete molecules that (1) stabilize the thrombus after TBI-induced coagulopathy and (2) modulate immune/inflammatory response [25,26]. It has been found that platelet dysfunction, rather than platelet count [27], is associated with a strong negative prognostic factor in TBI [28]. However, it is difficult to assess platelet dysfunction based on standard laboratory tests [29,30], and decreased levels of RANTES and PDGFAA may be reasonable surrogates for assessing platelet dysfunction.
4.3. Limitations Our study is a single center observational study and bound by inherent biases of the specific population and treatment protocols. However, samples were collected early after injury and therefore mostly reflect the injury pathology. In order to determine the pathophysiologic significance of these findings, further studies and potentially interventional trials are needed. These findings may also be used as quantitative surrogate markers of disease severity and progression in the future.
5. Conclusion Several inflammatory response molecules were elevated after TBI while platelet-derived molecules were decreased 24–48 h after TBI. Inflammatory response mediators IL-6 and IL-10 were elevated while PDGFAA and RANTES were decreased, suggesting platelet dysfunction. The putative mechanisms involved in pathways that drive patient outcomes and their roles as potential targets for pharmacological treatment require further investigation.
Author contributions CL, JS, HC, and RK were involved in the conception and design of the study. CL, JS, GH and MM assisted in the acquisition and analysis of data. CL, JS, and MM contributed substantially in drafting the manuscript and figures. Acknowledgments Funding: Support from CCTS KL2 Scholars program, UTHealth McGovern Medical School. Disclosures None to declare. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.jocn.2019.09.004. References [1] 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;66:1–16. https://doi.org/10.15585/mmwr. ss6609a1. [2] Savarraj J, Parsha K, Hergenroeder G, Ahn S, Chang TR, Kim DH, et al. Early brain injury associated with systemic inflammation after subarachnoid hemorrhage. Neurocrit Care 2018;28:203–31. https://doi.org/10.1007/ s12028-017-0471-y. [3] Savarraj JP, McGuire MF, Parsha K, Hergenroeder G, Bajgur S, Ahn S, et al. Disruption of thrombo-inflammatory response and activation of a distinct cytokine cluster after subarachnoid hemorrhage. Cytokine 2018;111:334–41. https://doi.org/10.1016/j.cyto.2018.09.003. [4] Rowland B, Savarraj JPJ, Karri J, Zhang X, Cardenas J, Choi HA, et al. Acute inflammation in traumatic brain injury and polytrauma patients using network analysis. Shock 2019. https://doi.org/10.1097/ SHK.0000000000001349. [5] Savarraj JPJ, Parsha K, Hergenroeder GW, Zhu L, Bajgur SS, Ahn S, et al. Systematic model of peripheral inflammation after subarachnoid hemorrhage. Neurology 2017;88:1535–45. https://doi.org/10.1212/ WNL.0000000000003842. [6] Lenzlinger PM, Morganti-Kossmann MC, Laurer HL, McIntosh TK. The duality of the inflammatory response to traumatic brain injury. Mol Neurobiol 2001;24:169–81. https://doi.org/10.1385/MN:24:1-3:169. [7] Ziebell JM, Morganti-Kossmann MC. Involvement of pro- and antiinflammatory cytokines and chemokines in the pathophysiology of traumatic brain injury. Neurotherapeutics 2010;7:22–30. https://doi.org/10.1016/j. nurt.2009.10.016. [8] Rankin J. Cerebral vascular accidents in patients over the age of 60 II. Prognosis. Scott Med J 1957;2:200–15. https://doi.org/10.1177/003693305700200504. [9] Bonita R, Beaglehole R. Recovery of motor function after stroke. Stroke 1988;19:1497–500. https://doi.org/10.1161/01.str.19.12.1497. [10] van Swieten JC, Koudstaal PJ, Visser MC, Schouten HJ, van Gijn J. Interobserver agreement for the assessment of handicap in stroke patients. Stroke 1988;19:604–7. https://doi.org/10.1161/01.str.19.5.604. [11] Mann HB, Whitney DR. On a test of whether one of two random variables is stochastically larger than the other. Ann Math Stat 1947;18:50–60. [12] Hergenroeder GW, Moore AN, McCoy JP, Samsel L, Ward NH, Clifton GL, et al. Serum IL-6: a candidate biomarker for intracranial pressure elevation following isolated traumatic brain injury. J Neuroinflammation 2010;7:19. https://doi.org/10.1186/1742-2094-7-19. [13] Ferreira LCB, Regner A, Miotto KDL, de Moura S, Ikuta N, Vargas AE, et al. Increased levels of interleukin-6, -8 and -10 are associated with fatal outcome following severe traumatic brain injury. Brain Inj 2014;28:1311–6. https://doi. org/10.3109/02699052.2014.916818. [14] Ringheim GE, Burgher KL, Heroux JA. Interleukin-6 mRNA expression by cortical neurons in culture: evidence for neuronal sources of interleukin-6 production in the brain. J Neuroimmunol 1995;63:113–23. [15] John GR, Lee SC, Song X, Rivieccio M, Brosnan CF. IL-1-regulated responses in astrocytes: relevance to injury and recovery. Glia 2005;49:161–76. https://doi. org/10.1002/glia.20109. [16] Scheller J, Chalaris A, Schmidt-Arras D, Rose-John S. The pro- and antiinflammatory properties of the cytokine interleukin-6. Biochim Biophys Acta 2011;1813:878–88. https://doi.org/10.1016/j.bbamcr.2011.01.034. [17] Schneider Soares FM, Menezes de Souza N, Libório Schwarzbold M, Paim Diaz A, Costa Nunes J, Hohl A, et al. Interleukin-10 is an independent biomarker of
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