"Parempaa aivovammapotilaiden diagnostiikkaa ja hoitoa verikokeen avulla?"
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Edellä mainittujen proteiinibiomarkkereiden (S100B, GFAP, UCH-L1) ohella on tutkittu pieniä verestä mitattavia aineenvaihduntatuotteita kuten rasvahappoja ja glukoosijohdoksia aivovammadiagnostiikassa. Toisin kuin usean proteiinin näiden aineenvaihduntabiomarkkereiden pääsy verenkiertoon ei vaadi veri-aivoesteen vauriota.
Aivovammamarkkereiden tutkimuksessa metabolomiikan menetelmiä on toistaiseksi käytetty vileä vähän.
Hiljattain kuuden aineenvaihduntatuotteen yhdistelmän osoitettiin olevan suomalais-brittiläisessä kahden keskuksen tutkimuksessa jopa GFAP_UCH-L1- testiä tarkempi tunnistamaan TT-kuvantamista tarvitsevat potilaat.
Dickens AM, Posti JP, Takala RSK et al. Serum metabolites with computed tomography findings after traumatic brain injury. J neurotrauma 2018
Löydänkin paljon lähteitä hakemalla ylläolevalla tekstillä. Tässä abstraktissa kerrotaan 8 eri biomarkkerin tutkimuksesta akuutissa aivovammassa tarkoituksena pystyä erottamaan aivovamman eri vaikeusasteissa (Glascow Coma Scale) TT- positiiviset ja TT negatiiviset aivovammat.
Tutkimuksessa käytetyt proteiinibiomarkerit ovat:
- beta-amyloidiiisoformi 1-40(Abeta40)
- beta-amyloidi-isoformi 1-42(Abeta42),
- gliaalinen fibrillaarinen asidinen proteiini GFAP,
- sydänrasvahappoa sitova proteiini H-FABP
- Interleukiini-10 (IL-10)
- kevyt neurofilamentti NF-L
- S100 kalsiumia sitova proteiini B (S100B)
- Tau proteiini
Paras kolmen panelikombinaatio kaikenasteisten aivovammojen ryhmissä oli GFAP +H-FABP + IL10 ja paras kolmen paneli lievien vammojen ryhmässä oli H-FABP + S100B + tau. Panelit koostuivat lähinnä eri biomarkkereista kuin niistä, jotka yksinään olivat parhaita erottamassa TT+ ja TT- potilaat.
https://www.liebertpub.com/doi/10.1089/neu.2018.6254
Abstract
The
aim of the study was to examine the ability of eight protein biomarkers
and their combinations in discriminating computed tomography
(CT)-negative and CT-positive patients with traumatic brain injury
(TBI), utilizing highly sensitive immunoassays in a well-characterized
cohort. Blood samples were obtained from 160 patients with acute TBI
within 24 h of admission. Levels of β-amyloid isoforms 1–40 (Aβ40) and
1–42 (Aβ42), glial fibrillary acidic protein (GFAP), heart fatty-acid
binding protein (H-FABP), interleukin 10 (IL-10), neurofilament light
(NF-L), S100 calcium-binding protein B (S100B), and tau were measured.
Patients were divided into CT-negative (n = 65) and CT-positive (n = 95), and analyses were conducted separately for TBIs of all severities (Glasgow Coma Scale [GCS] score 3–15) and
mild TBIs (mTBIs; GCS 13–15).
NF-L, GFAP, and tau were the best in discriminating CT-negative and CT-positive patients, both in patients with mTBI and with all severities.
In patients with all severities, area under the curve of the receiver operating characteristic (AUC) was 0.822, 0.817, and 0.781 for GFAP, NF-L, and tau, respectively.
In patients with mTBI, AUC was 0.720, 0.689, and 0.676, for GFAP, tau, and NF-L, respectively. The best panel of three biomarkers for discriminating CT-negative and CT-positive patients in the group of all severities was a combination of GFAP+H-FABP+IL-10, with a sensitivity of 100% and specificity of 38.5%.
In patients with mTBI, the best panel of three biomarkers was H-FABP+S100B+tau, with a sensitivity of 100% and specificity of 46.4%. Panels of biomarkers outperform individual biomarkers in separating CT-negative and CT-positive patients. Panels consisted mainly of different biomarkers than those that performed best as an individual biomarker.
Patients were divided into CT-negative (n = 65) and CT-positive (n = 95), and analyses were conducted separately for TBIs of all severities (Glasgow Coma Scale [GCS] score 3–15) and
mild TBIs (mTBIs; GCS 13–15).
NF-L, GFAP, and tau were the best in discriminating CT-negative and CT-positive patients, both in patients with mTBI and with all severities.
In patients with all severities, area under the curve of the receiver operating characteristic (AUC) was 0.822, 0.817, and 0.781 for GFAP, NF-L, and tau, respectively.
In patients with mTBI, AUC was 0.720, 0.689, and 0.676, for GFAP, tau, and NF-L, respectively. The best panel of three biomarkers for discriminating CT-negative and CT-positive patients in the group of all severities was a combination of GFAP+H-FABP+IL-10, with a sensitivity of 100% and specificity of 38.5%.
In patients with mTBI, the best panel of three biomarkers was H-FABP+S100B+tau, with a sensitivity of 100% and specificity of 46.4%. Panels of biomarkers outperform individual biomarkers in separating CT-negative and CT-positive patients. Panels consisted mainly of different biomarkers than those that performed best as an individual biomarker.
