Circulating biomarker levels for diagnosis and risk-stratification of traumatic brain injury
Inventors
EDMONDS, Donna J. • VAN METER, Timothy E. • Mirshahi, Nazanin
Assignees
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Publication Number
US-12265091-B2
Publication Date
2025-04-01
Expiration Date
Abstract
Methods, compositions and kits useful in the diagnosis, prognosis and/or assessment of brain injuries and risk for brain injuries, such as hemorrhage, are based upon detection of certain biomarkers.
Core Innovation
The invention relates to a biomarker-based method for measuring biomarker proteins in a biological sample from a human patient that has or is suspected of having a brain injury. The method measures Neurogranin (NRGN) and Synuclein Beta (SNCB), compares them to reference levels, and detects a changed level of NRGN and a changed level of SNCB relative to reference levels.
In particular, the method uses detection of an increased level of NRGN together with a decreased level of SNCB to indicate a brain-injury related condition and to support subsequent clinical decision-making. The disclosure includes risk stratification concepts for brain injury, including categorization into high, medium, or low risk based on biomarker comparisons versus reference levels, and classifier algorithms when risk categorization or decision support is applied.
The disclosure further includes additional biomarker proteins such as GFAP, NSE, MT3, BDNF, ICAM5, Tau, P-tau, and Map2, and is described as being implemented using immunoassays and/or mass spectrometry. The system is also described as fitting within kit formats such as microarray chip or biochip formats.
Claims Coverage
One independent claim is directed to a method that measures NRGN and SNCB levels, compares them to reference levels, and administers brain-injury treatment based on an increased NRGN and decreased SNCB pattern. Dependent claims further refine reference-level definitions, optional timing windows, optional additional biomarkers, and classifier-based risk stratification using classifier algorithms.
Measuring NRGN and SNCB levels in a patient sample
Measuring levels of biomarker proteins Neurogranin (NRGN) and Synuclein Beta (SNCB) in a biological sample from a human patient that has or is suspected of having a brain injury.
Detecting changed NRGN and changed SNCB relative to reference levels
Detecting a changed level of NRGN and a changed level of SNCB relative to reference levels.
Administering brain-injury treatment based on NRGN/SNCB pattern
Administering treatment for a brain injury when an increased level of NRGN and a decreased level of SNCB is detected.
Classifying brain injury risk with a classifier algorithm
Comparing the increased level of NRGN and the decreased level of SNCB relative to reference levels and using at least one classifier algorithm to classify a patient as high, medium, or low risk of brain injury.
Selecting a classifier algorithm from specified model types
Selecting the at least one classifier algorithm from the group comprising decision tree classifier, logistic regression classifier, nearest neighbor classifier, neural network classifier, Gaussian mixture model (GMM) classifier, Support Vector Machine (SVM) classifier, nearest centroid classifier, linear regression classifier, linear discriminant analysis (LDA) classifier, quadratic discriminant analysis (QDA) classifier, random forest classifier, extreme gradient boosting (XG Boost) classifier, and linear mixed effects model classifier.
Defining reference levels as baseline levels measured before injury
Defining the reference levels as baseline levels of NRGN and SNCB, measured before a brain injury.
Measuring additional biomarker proteins relative to reference levels
Measuring levels of MT3, Tau, P-tau, or Map2 and detecting changes in those levels relative to their respective reference levels.
Using post-injury sampling time windows
Obtaining the biological sample from a human subject at least one, three, or six months after injury or suspected injury.
Overall, the claim set centers on measuring NRGN and SNCB, detecting increased NRGN together with decreased SNCB relative to reference levels, and administering brain-injury treatment when that pattern is present. Dependent claims refine the reference level definition, optionally restrict sample timing, optionally expand to additional biomarkers, and optionally use specified classifier algorithms to stratify brain injury risk as high, medium, or low.
Stated Advantages
Supports diagnosing and making treatment decisions for a brain injury based on a biomarker pattern of increased NRGN and decreased SNCB relative to reference levels.
Enables brain-injury risk stratification into high, medium, or low risk using classifier algorithms based on biomarker comparisons versus reference levels.
Provides diagnostic and risk-assessment performance concepts including ROC/AUC, sensitivity, and specificity.
Documented Applications
Traumatic brain injury (TBI) diagnosis and brain-injury hemorrhage risk stratification using biomarker measurements and reference-level comparisons.
Prognosis of recovery and related outcomes over follow-up time points using biomarker panels.
Return-to-work/return-to-play guidance based on the biomarker-based risk assessment and prognosis concepts.
Assessment related to depression using PHQ9 and other outcome concepts such as Glasgow Outcome Scale Extended (GOS-E) and ICD10 post-concussive syndrome (ICD10-PCS).
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