Literature DB >> 33469656

Machine Learning-Driven Metabolomic Evaluation of Cerebrospinal Fluid: Insights Into Poor Outcomes After Aneurysmal Subarachnoid Hemorrhage.

Matthew Koch1, Animesh Acharjee2, Zsuzsanna Ament3, Riana Schleicher3, Matthew Bevers4, Christopher Stapleton1, Aman Patel1, W Taylor Kimberly3.   

Abstract

BACKGROUND: Aneurysmal subarachnoid hemorrhage (aSAH) is associated with a high mortality and poor neurologic outcomes. The biologic underpinnings of the morbidity and mortality associated with aSAH remain poorly understood.
OBJECTIVE: To ascertain potential insights into pathological mechanisms of injury after aSAH using an approach of metabolomics coupled with machine learning methods.
METHODS: Using cerebrospinal fluid (CSF) samples from 81 aSAH enrolled in a retrospective cohort biorepository, samples collected during the peak of delayed cerebral ischemia were analyzed using liquid chromatography-tandem mass spectrometry. A total of 138 metabolites were measured and quantified in each sample. Data were analyzed using elastic net (EN) machine learning and orthogonal partial least squares-discriminant analysis (OPLS-DA) to identify the leading CSF metabolites associated with poor outcome, as determined by the modified Rankin Scale (mRS) at discharge and at 90 d. Repeated measures analysis determined the effect size for each metabolite on poor outcome.
RESULTS: EN machine learning and OPLS-DA analysis identified 8 and 10 metabolites, respectively, that predicted poor mRS (mRS 3-6) at discharge and at 90 d. Of these candidates, symmetric dimethylarginine (SDMA), dimethylguanidine valeric acid (DMGV), and ornithine were consistent markers, with an association with poor mRS at discharge (P = .0005, .002, and .0001, respectively) and at 90 d (P = .0036, .0001, and .004, respectively). SDMA also demonstrated a significantly elevated CSF concentration compared with nonaneurysmal subarachnoid hemorrhage controls (P = .0087).
CONCLUSION: SDMA, DMGV, and ornithine are vasoactive molecules linked to the nitric oxide pathway that predicts poor outcome after severe aSAH. Further study of dimethylarginine metabolites in brain injury after aSAH is warranted. © Congress of Neurological Surgeons 2021.

Entities:  

Keywords:  Aneurysm; Biomarker; Cerebrospinal fluid; Machine learning; Metabolites; Metabolomics; Subarachnoid hemorrhage

Mesh:

Substances:

Year:  2021        PMID: 33469656      PMCID: PMC8046589          DOI: 10.1093/neuros/nyaa557

Source DB:  PubMed          Journal:  Neurosurgery        ISSN: 0148-396X            Impact factor:   4.654


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