{'fraction_non_alphanumeric': 0.01305379746835443, 'fraction_numerical': 0.003955696202531646, 'mean_word_length': 5.986187845303867, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Large-scale informatic analysis to algorithmically identify blood biomarkers of neurological damage

Significance The discovery and development of precision blood biomarkers which can accurately detect damage to brain tissue could transform how we diagnose and treat neurological pathologies. In this study, we used mRNA expression data generated from thousands of tissue samples to algorithmically evaluate nearly every protein-coding gene in the human genome in terms of potential to produce blood biomarkers for neurological damage based on expression profiles both across the body and within the brain. This unprecedented analysis identifies a plethora of previously unexplored candidate blood biomarkers which could have clinical utility for noninvasive diagnosis and monitoring of various common neurological conditions, including traumatic brain injury, stroke, and multiple sclerosis. The identification of precision blood biomarkers which can accurately indicate damage to brain tissue could yield molecular diagnostics with the potential to improve how we detect and treat neurological pathologies. However, a majority of candidate blood biomarkers for neurological damage that are studied today are proteins which were arbitrarily proposed several decades before the advent of high-throughput omic techniques, and it is unclear whether they represent the best possible targets relative to the remainder of the human proteome. Here, we leveraged mRNA expression data generated from nearly 12,000 human specimens to algorithmically evaluate over 17,000 protein-coding genes in terms of their potential to produce blood biomarkers for neurological damage based on their expression profiles both across the body and within the brain. The circulating levels of proteins associated with the top-ranked genes were then measured in blood sampled from a diverse cohort of patients diagnosed with a variety of acute and chronic neurological disorders, including ischemic stroke, hemorrhagic stroke, traumatic brain injury, Alzheimer’s disease, and multiple sclerosis, and evaluated for their diagnostic performance. Our analysis identifies several previously unexplored candidate blood biomarkers of neurological damage with possible clinical utility, many of which whose presence in blood is likely linked to specific cell-level pathologic processes. Furthermore, our findings also suggest that many frequently cited previously proposed blood biomarkers exhibit expression profiles which could limit their diagnostic efficacy.