{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T18:58:37Z","timestamp":1793905117292,"version":"4.8.0"},"reference-count":35,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T00:00:00Z","timestamp":1785283200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Mol. Biosci."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Hypertensive cerebral hemorrhage (HCH) accounts for the majority of spontaneous intracerebral hemorrhage (ICH) cases. Cognitive impairment (CI) is a major contributor to long-term disability following ICH, yet the molecular mechanisms underlying CI in hypertensive ICH remain poorly understood. Therefore, identifying biomarkers capable of effectively diagnosing or predicting CI in HCH is particularly critical for managing patients with hypertensive cerebral hemorrhage with cognitive impairment (HCHwCI).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In this research, clinical samples underwent transcriptome sequencing analysis. Identification of biomarkers associated with CI in HCH was achieved through differential expression analysis, protein-protein interaction (PPI) network construction, and expression level evaluation. Subsequently, to investigate the molecular mechanisms of the biomarkers in HCHwCI, comprehensive analyses were performed, including gene set enrichment analysis (GSEA), molecular regulatory network construction, drug prediction, and molecular docking. Finally, the expression of biomarkers was detected by reverse transcription-quantitative polymerase chain reaction (RT-qPCR).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Using 247 differentially expressed CI-related genes (CRGs), we identified CXCL8 and FCGR3B as significantly upregulated biomarkers in HCH patients with CI, a finding subsequently validated by RT-qPCR. CXCL8 and FCGR3B were also found to be significantly enriched in oxidative phosphorylation and other related pathways. The molecular regulation study found that 67 microRNAs (miRNAs) were predicted to regulate CXCL8, and 58 miRNAs were predicted to regulate FCGR3B. Among them, hsa-miR-3168 and hsa-miR-567 jointly regulated both CXCL8 and FCGR3B. In addition, there were 29 transcription factors (TFs) were predicted to target CXCL8, and there were 2 TFs were predicted to target FCGR3B, such as the pairs of CXCL8-STAT6 and FCGR3B-YY1. Moreover, through drug prediction, there were 542 drugs targeting CXCL8 and FCGR3B (such as methotrexate and hydrogen peroxide). Among them, the | Total Score | of FCGR3B and clozapine is 6.3 kcal\/mol, and the | Total Score | of CXCL8 and 6401-97-4 is 5.1 kcal\/mol, both indicating good binding activity\n                      <jats:italic>in silico<\/jats:italic>\n                      , serving as a proof-of-concept for the computational docking approach.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>In this study, two potential biomarkers, CXCL8 and FCGR3B, were preliminarily identified through transcriptome sequencing combined with biological validation methods to provide novel insights into future therapeutic strategies and research directions for HCHwCI.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmolb.2026.1877108","type":"journal-article","created":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T04:49:34Z","timestamp":1785300574000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Transcriptome sequencing and validation of potential biomarkers associated with cognitive impairment after hypertensive intracerebral hemorrhage"],"prefix":"10.3389","volume":"13","author":[{"given":"Yao","family":"Tang","sequence":"first","affiliation":[{"name":"Department of General Ward, Affiliated Hospital of Guizhou Medical University","place":["Guiyang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Boyin","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of General Ward, Affiliated Hospital of Guizhou Medical University","place":["Guiyang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xingmei","family":"Luo","sequence":"additional","affiliation":[{"name":"Physical Examination Center, Affiliated Hospital of Guizhou Medical University","place":["Guiyang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,29]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"22","DOI":"10.17691\/stm2022.14.3.03","article-title":"Messenger RNA of FCGR3A and FCGR3B genes as monitoring markers of clear cell renal adenocarcinoma (a pilot study)","volume":"14","author":"Alyasova","year":"2022","journal-title":"Sovrem. 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