Admission Levels of Interleukin 10 and Amyloid β 1–40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury

Jussi P. Posti; Riikka S.K. Takala; Rahul Raj; Teemu M. Luoto; Leire Azurmendi; Linnéa Lagerstedt; Mehrbod Mohammadian; Iftakher Hossain; Jessica Gill; Janek Frantzén; Mark van Gils; Peter J. Hutchinson; Ari J. Katila; Pia Koivikko; Henna Riikka Maanpää; David K. Menon; Virginia F. Newcombe; Jussi Tallus; Kaj Blennow; Olli Tenovuo; Henrik Zetterberg; Jean Charles Sanchez

doi:10.3389/fneur.2020.549527

Admission Levels of Interleukin 10 and Amyloid β 1–40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury

Jussi P. Posti, Riikka S.K. Takala, Rahul Raj, Teemu M. Luoto, Leire Azurmendi, Linnéa Lagerstedt, Mehrbod Mohammadian, Iftakher Hossain, Jessica Gill, Janek Frantzén, Mark van Gils, Peter J. Hutchinson, Ari J. Katila, Pia Koivikko, Henna Riikka Maanpää, David K. Menon, Virginia F. Newcombe, Jussi Tallus, Kaj Blennow, Olli TenovuoHenrik Zetterberg, Jean Charles Sanchez

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Abstract

Background: Blood biomarkers may enhance outcome prediction performance of head computed tomography scores in traumatic brain injury (TBI). Objective: To investigate whether admission levels of eight different protein biomarkers can improve the outcome prediction performance of the Helsinki computed tomography score (HCTS) without clinical covariates in TBI. Materials and methods: Eighty-two patients with computed tomography positive TBIs were included in this study. Plasma levels of β-amyloid isoforms 1–40 (Aβ40) and 1–42 (Aβ42), glial fibrillary acidic protein, heart fatty acid-binding protein, interleukin 10 (IL-10), neurofilament light, S100 calcium-binding protein B, and total tau were measured within 24 h from admission. The patients were divided into favorable (Glasgow Outcome Scale—Extended 5–8, n = 49) and unfavorable (Glasgow Outcome Scale—Extended 1–4, n = 33) groups. The outcome was assessed 6–12 months after injury. An optimal predictive panel was investigated with the sensitivity set at 90–100%. Results: The HCTS alone yielded a sensitivity of 97.0% (95% CI: 90.9–100) and specificity of 22.4% (95% CI: 10.2–32.7) and partial area under the curve of the receiver operating characteristic of 2.5% (95% CI: 1.1–4.7), in discriminating patients with favorable and unfavorable outcomes. The threshold to detect a patient with unfavorable outcome was an HCTS > 1. The three best individually performing biomarkers in outcome prediction were Aβ40, Aβ42, and neurofilament light. The optimal panel included IL-10, Aβ40, and the HCTS reaching a partial area under the curve of the receiver operating characteristic of 3.4% (95% CI: 1.7–6.2) with a sensitivity of 90.9% (95% CI: 81.8–100) and specificity of 59.2% (95% CI: 40.8–69.4). Conclusion: Admission plasma levels of IL-10 and Aβ40 significantly improve the prognostication ability of the HCTS after TBI.

Original language	English
Article number	549527
Journal	Frontiers in Neurology
Volume	11
DOIs	https://doi.org/10.3389/fneur.2020.549527
Publication status	Published - 30 Oct 2020
Publication type	A1 Journal article-refereed

Funding

Funding. This work was partially funded by the European Commission under the 7th Framework Programme (FP7-270259-TBIcare), Academy of Finland?Grant # 17379, Government's Special Financial Transfer tied to academic research in Health Sciences (Finland) (JP), the Maire Taponen foundation (JP), the Integra EANS Research Grant (IH), the Finnish Medical Foundation (IH), University of Turku Graduate School funding (MM), the Royal College of Surgeons (PH), NIHR Research Professorship and the NIHR Cambridge BRC (PH), NIHR Research UK (through a Senior Investigator Award and the Cambridge Biomedical Research Centre) (DM), Academy of Medical Sciences/The Health Foundation Clinician Scientist Fellowship (VN), Swedish Research Council (#2017-00915) (KB), the Alzheimer Drug Discovery Foundation (ADDF) (KB), USA (#RDAPB-201809-2016615) (KB), the Swedish Alzheimer Foundation (#AF-742881) (KB), Hj?rnfonden, Sweden (#FO2017-0243) (KB), the Swedish state under the agreement between the Swedish government and the County Councils (KB), the ALF-Agreement (#ALFGBG-715986) (KB), and European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236) (KB), and Wallenberg Academy Fellowship and grants from the Swedish and European Research Councils (HZ).

Keywords

beta amyloid 1–40
biomarkers
Helsinki CT score
interleukin 10 (IL10)
outcome prediction
panel analysis
traumatic brain injury

Publication forum classification

Publication forum level 1

ASJC Scopus subject areas

Neurology
Clinical Neurology

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Cite this

Posti, J. P., Takala, R. S. K., Raj, R., Luoto, T. M., Azurmendi, L., Lagerstedt, L., Mohammadian, M., Hossain, I., Gill, J., Frantzén, J., van Gils, M., Hutchinson, P. J., Katila, A. J., Koivikko, P., Maanpää, H. R., Menon, D. K., Newcombe, V. F., Tallus, J., Blennow, K., ... Sanchez, J. C. (2020). Admission Levels of Interleukin 10 and Amyloid β 1–40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury. Frontiers in Neurology, 11, Article 549527. https://doi.org/10.3389/fneur.2020.549527

@article{ae561c8b3c9f41ee83b1a3a26c8baf9b,

title = "Admission Levels of Interleukin 10 and Amyloid β 1–40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury",

abstract = "Background: Blood biomarkers may enhance outcome prediction performance of head computed tomography scores in traumatic brain injury (TBI). Objective: To investigate whether admission levels of eight different protein biomarkers can improve the outcome prediction performance of the Helsinki computed tomography score (HCTS) without clinical covariates in TBI. Materials and methods: Eighty-two patients with computed tomography positive TBIs were included in this study. Plasma levels of β-amyloid isoforms 1–40 (Aβ40) and 1–42 (Aβ42), glial fibrillary acidic protein, heart fatty acid-binding protein, interleukin 10 (IL-10), neurofilament light, S100 calcium-binding protein B, and total tau were measured within 24 h from admission. The patients were divided into favorable (Glasgow Outcome Scale—Extended 5–8, n = 49) and unfavorable (Glasgow Outcome Scale—Extended 1–4, n = 33) groups. The outcome was assessed 6–12 months after injury. An optimal predictive panel was investigated with the sensitivity set at 90–100%. Results: The HCTS alone yielded a sensitivity of 97.0% (95% CI: 90.9–100) and specificity of 22.4% (95% CI: 10.2–32.7) and partial area under the curve of the receiver operating characteristic of 2.5% (95% CI: 1.1–4.7), in discriminating patients with favorable and unfavorable outcomes. The threshold to detect a patient with unfavorable outcome was an HCTS > 1. The three best individually performing biomarkers in outcome prediction were Aβ40, Aβ42, and neurofilament light. The optimal panel included IL-10, Aβ40, and the HCTS reaching a partial area under the curve of the receiver operating characteristic of 3.4% (95% CI: 1.7–6.2) with a sensitivity of 90.9% (95% CI: 81.8–100) and specificity of 59.2% (95% CI: 40.8–69.4). Conclusion: Admission plasma levels of IL-10 and Aβ40 significantly improve the prognostication ability of the HCTS after TBI.",

keywords = "beta amyloid 1–40, biomarkers, Helsinki CT score, interleukin 10 (IL10), outcome prediction, panel analysis, traumatic brain injury",

author = "Posti, {Jussi P.} and Takala, {Riikka S.K.} and Rahul Raj and Luoto, {Teemu M.} and Leire Azurmendi and Linn{\'e}a Lagerstedt and Mehrbod Mohammadian and Iftakher Hossain and Jessica Gill and Janek Frantz{\'e}n and {van Gils}, Mark and Hutchinson, {Peter J.} and Katila, {Ari J.} and Pia Koivikko and Maanp{\"a}{\"a}, {Henna Riikka} and Menon, {David K.} and Newcombe, {Virginia F.} and Jussi Tallus and Kaj Blennow and Olli Tenovuo and Henrik Zetterberg and Sanchez, {Jean Charles}",

note = "Funding Information: Funding. This work was partially funded by the European Commission under the 7th Framework Programme (FP7-270259-TBIcare), Academy of Finland?Grant # 17379, Government's Special Financial Transfer tied to academic research in Health Sciences (Finland) (JP), the Maire Taponen foundation (JP), the Integra EANS Research Grant (IH), the Finnish Medical Foundation (IH), University of Turku Graduate School funding (MM), the Royal College of Surgeons (PH), NIHR Research Professorship and the NIHR Cambridge BRC (PH), NIHR Research UK (through a Senior Investigator Award and the Cambridge Biomedical Research Centre) (DM), Academy of Medical Sciences/The Health Foundation Clinician Scientist Fellowship (VN), Swedish Research Council (#2017-00915) (KB), the Alzheimer Drug Discovery Foundation (ADDF) (KB), USA (#RDAPB-201809-2016615) (KB), the Swedish Alzheimer Foundation (#AF-742881) (KB), Hj?rnfonden, Sweden (#FO2017-0243) (KB), the Swedish state under the agreement between the Swedish government and the County Councils (KB), the ALF-Agreement (#ALFGBG-715986) (KB), and European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236) (KB), and Wallenberg Academy Fellowship and grants from the Swedish and European Research Councils (HZ). Publisher Copyright: {\textcopyright} Copyright {\textcopyright} 2020 Posti, Takala, Raj, Luoto, Azurmendi, Lagerstedt, Mohammadian, Hossain, Gill, Frantz{\'e}n, van Gils, Hutchinson, Katila, Koivikko, Maanp{\"a}{\"a}, Menon, Newcombe, Tallus, Blennow, Tenovuo, Zetterberg and Sanchez. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",

year = "2020",

month = oct,

day = "30",

doi = "10.3389/fneur.2020.549527",

language = "English",

volume = "11",

}

Posti, JP, Takala, RSK, Raj, R, Luoto, TM, Azurmendi, L, Lagerstedt, L, Mohammadian, M, Hossain, I, Gill, J, Frantzén, J, van Gils, M, Hutchinson, PJ, Katila, AJ, Koivikko, P, Maanpää, HR, Menon, DK, Newcombe, VF, Tallus, J, Blennow, K, Tenovuo, O, Zetterberg, H & Sanchez, JC 2020, 'Admission Levels of Interleukin 10 and Amyloid β 1–40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury', Frontiers in Neurology, vol. 11, 549527. https://doi.org/10.3389/fneur.2020.549527

TY - JOUR

T1 - Admission Levels of Interleukin 10 and Amyloid β 1–40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury

AU - Posti, Jussi P.

AU - Takala, Riikka S.K.

AU - Raj, Rahul

AU - Luoto, Teemu M.

AU - Azurmendi, Leire

AU - Lagerstedt, Linnéa

AU - Mohammadian, Mehrbod

AU - Hossain, Iftakher

AU - Gill, Jessica

AU - Frantzén, Janek

AU - van Gils, Mark

AU - Hutchinson, Peter J.

AU - Katila, Ari J.

AU - Koivikko, Pia

AU - Maanpää, Henna Riikka

AU - Menon, David K.

AU - Newcombe, Virginia F.

AU - Tallus, Jussi

AU - Blennow, Kaj

AU - Tenovuo, Olli

AU - Zetterberg, Henrik

AU - Sanchez, Jean Charles

N1 - Funding Information: Funding. This work was partially funded by the European Commission under the 7th Framework Programme (FP7-270259-TBIcare), Academy of Finland?Grant # 17379, Government's Special Financial Transfer tied to academic research in Health Sciences (Finland) (JP), the Maire Taponen foundation (JP), the Integra EANS Research Grant (IH), the Finnish Medical Foundation (IH), University of Turku Graduate School funding (MM), the Royal College of Surgeons (PH), NIHR Research Professorship and the NIHR Cambridge BRC (PH), NIHR Research UK (through a Senior Investigator Award and the Cambridge Biomedical Research Centre) (DM), Academy of Medical Sciences/The Health Foundation Clinician Scientist Fellowship (VN), Swedish Research Council (#2017-00915) (KB), the Alzheimer Drug Discovery Foundation (ADDF) (KB), USA (#RDAPB-201809-2016615) (KB), the Swedish Alzheimer Foundation (#AF-742881) (KB), Hj?rnfonden, Sweden (#FO2017-0243) (KB), the Swedish state under the agreement between the Swedish government and the County Councils (KB), the ALF-Agreement (#ALFGBG-715986) (KB), and European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236) (KB), and Wallenberg Academy Fellowship and grants from the Swedish and European Research Councils (HZ). Publisher Copyright: © Copyright © 2020 Posti, Takala, Raj, Luoto, Azurmendi, Lagerstedt, Mohammadian, Hossain, Gill, Frantzén, van Gils, Hutchinson, Katila, Koivikko, Maanpää, Menon, Newcombe, Tallus, Blennow, Tenovuo, Zetterberg and Sanchez. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/10/30

Y1 - 2020/10/30

N2 - Background: Blood biomarkers may enhance outcome prediction performance of head computed tomography scores in traumatic brain injury (TBI). Objective: To investigate whether admission levels of eight different protein biomarkers can improve the outcome prediction performance of the Helsinki computed tomography score (HCTS) without clinical covariates in TBI. Materials and methods: Eighty-two patients with computed tomography positive TBIs were included in this study. Plasma levels of β-amyloid isoforms 1–40 (Aβ40) and 1–42 (Aβ42), glial fibrillary acidic protein, heart fatty acid-binding protein, interleukin 10 (IL-10), neurofilament light, S100 calcium-binding protein B, and total tau were measured within 24 h from admission. The patients were divided into favorable (Glasgow Outcome Scale—Extended 5–8, n = 49) and unfavorable (Glasgow Outcome Scale—Extended 1–4, n = 33) groups. The outcome was assessed 6–12 months after injury. An optimal predictive panel was investigated with the sensitivity set at 90–100%. Results: The HCTS alone yielded a sensitivity of 97.0% (95% CI: 90.9–100) and specificity of 22.4% (95% CI: 10.2–32.7) and partial area under the curve of the receiver operating characteristic of 2.5% (95% CI: 1.1–4.7), in discriminating patients with favorable and unfavorable outcomes. The threshold to detect a patient with unfavorable outcome was an HCTS > 1. The three best individually performing biomarkers in outcome prediction were Aβ40, Aβ42, and neurofilament light. The optimal panel included IL-10, Aβ40, and the HCTS reaching a partial area under the curve of the receiver operating characteristic of 3.4% (95% CI: 1.7–6.2) with a sensitivity of 90.9% (95% CI: 81.8–100) and specificity of 59.2% (95% CI: 40.8–69.4). Conclusion: Admission plasma levels of IL-10 and Aβ40 significantly improve the prognostication ability of the HCTS after TBI.

AB - Background: Blood biomarkers may enhance outcome prediction performance of head computed tomography scores in traumatic brain injury (TBI). Objective: To investigate whether admission levels of eight different protein biomarkers can improve the outcome prediction performance of the Helsinki computed tomography score (HCTS) without clinical covariates in TBI. Materials and methods: Eighty-two patients with computed tomography positive TBIs were included in this study. Plasma levels of β-amyloid isoforms 1–40 (Aβ40) and 1–42 (Aβ42), glial fibrillary acidic protein, heart fatty acid-binding protein, interleukin 10 (IL-10), neurofilament light, S100 calcium-binding protein B, and total tau were measured within 24 h from admission. The patients were divided into favorable (Glasgow Outcome Scale—Extended 5–8, n = 49) and unfavorable (Glasgow Outcome Scale—Extended 1–4, n = 33) groups. The outcome was assessed 6–12 months after injury. An optimal predictive panel was investigated with the sensitivity set at 90–100%. Results: The HCTS alone yielded a sensitivity of 97.0% (95% CI: 90.9–100) and specificity of 22.4% (95% CI: 10.2–32.7) and partial area under the curve of the receiver operating characteristic of 2.5% (95% CI: 1.1–4.7), in discriminating patients with favorable and unfavorable outcomes. The threshold to detect a patient with unfavorable outcome was an HCTS > 1. The three best individually performing biomarkers in outcome prediction were Aβ40, Aβ42, and neurofilament light. The optimal panel included IL-10, Aβ40, and the HCTS reaching a partial area under the curve of the receiver operating characteristic of 3.4% (95% CI: 1.7–6.2) with a sensitivity of 90.9% (95% CI: 81.8–100) and specificity of 59.2% (95% CI: 40.8–69.4). Conclusion: Admission plasma levels of IL-10 and Aβ40 significantly improve the prognostication ability of the HCTS after TBI.

KW - beta amyloid 1–40

KW - biomarkers

KW - Helsinki CT score

KW - interleukin 10 (IL10)

KW - outcome prediction

KW - panel analysis

KW - traumatic brain injury

U2 - 10.3389/fneur.2020.549527

DO - 10.3389/fneur.2020.549527

M3 - Article

AN - SCOPUS:85096068667

SN - 1664-2295

VL - 11

JO - Frontiers in Neurology

JF - Frontiers in Neurology

M1 - 549527

ER -

Admission Levels of Interleukin 10 and Amyloid β 1–40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury

Abstract

Funding

Keywords

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