Key result
A computational text-mining approach identified 2,785 genes associated with stroke risk and proposed a 9-gene prognostic panel as a potential diagnostic marker for stroke subtypes.
Why the study?
To investigate prospective key genes and pathways associated with the pathogenesis and prognosis of stroke types and their subtypes to discover predictive genetic markers.
A computational text-mining approach identified a 9-gene signature that may serve as a potential diagnostic and prognostic marker for stroke and its subtypes.
Requires prospective validation before any clinical use; leaves open the 9-gene panel's role in stroke risk stratification.
To investigate prospective key genes and pathways associated with the pathogenesis and prognosis of stroke types along with subtypes. Human genes using genome assembly build 38 patch release 13 with known gene symbols through NCBI gene database ( https://www.ncbi.nlm.nih.gov/gene ) were fetched. PubMed advanced queries were constructed using stroke-related keywords and associations were calculated using Normalized pointwise mutual information (nPMI) between each gene symbol and queries. Genes related with stroke risk within their types and subtypes were investigated in order to discover genetic markers to predict individuals who are at the risk of developing stroke with their subtypes. A total of 2,785 (9.4%) genes were found to be linked to the risk of stroke. Based on stroke types, 1,287 (46.2%) and 376 (13.5%) genes were found to be related with IS and HS respectively. Further stratification of IS based on TOAST classification, 86 (6.6%) genes were confined to Large artery atherosclerosis; 131 (10.1%) and 130 (10%) genes were related with the risk of small vessel disease and Cardioembolism subtypes of IS. Besides, a prognostic panel of 9 genes signature consisting of CYP4A11, ALOX5P, NOTCH, NINJ2, FGB, MTHFR, PDE4D, HDAC9, and ZHFX3 can be treated as a diagnostic marker to predict individuals who are at the risk of developing stroke with their subtypes.
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Das et al. (2021) studied Stroke and its subtypes (n=28,281). Normalized pointwise mutual information (nPMI) text mining was evaluated on Identification of stroke-associated genes. A computational text-mining approach identified 2,785 genes associated with stroke risk and proposed a 9-gene prognostic panel as a potential diagnostic marker for stroke subtypes.
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