首页|Second Affiliated Hospital of Harbin Medical University Reports Findings in Bioi nformatics (Screening mitochondria-related biomarkers in skin and plasma of atop ic dermatitis patients by bioinformatics analysis and machine learning)
Second Affiliated Hospital of Harbin Medical University Reports Findings in Bioi nformatics (Screening mitochondria-related biomarkers in skin and plasma of atop ic dermatitis patients by bioinformatics analysis and machine learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Biotechnology - Bioinf ormatics is the subject of a report. According to news reporting from Heilongjia ng, People’s Republic of China, by NewsRx journalists, research stated, “There i s a significant imbalance of mitochondrial activity and oxidative stress (OS) st atus in patients with atopic dermatitis (AD). This study aims to screen skin and peripheral mitochondria-related biomarkers, providing insights into the underly ing mechanisms of mitochondrial dysfunction in AD.” The news correspondents obtained a quote from the research from the Second Affil iated Hospital of Harbin Medical University, “Public data were obtained from Mit oCarta 3.0 and GEO database. We screened mitochondria-related differentially exp ressed genes (MitoDEGs) using R language and then performed GO and KEGG pathway analysis on MitoDEGs. PPI and machine learning algorithms were also used to sele ct hub MitoDEGs. Meanwhile, the expression of hub MitoDEGs in clinical samples w ere verified. Using ROC curve analysis, the diagnostic performance of risk model constructed from these hub MitoDEGs was evaluated in the training and validatio n sets. Further computer-aided algorithm analyses included gene set enrichment a nalysis (GSEA), immune infiltration and mitochondrial metabolism, centered on th ese hub MitoDEGs. We also used real-time PCR and Spearman method to evaluate the relationship between plasma circulating cell-free mitochondrial DNA (ccf-mtDNA) levels and disease severity in AD patients. MitoDEGs in AD were significantly e nriched in pathways involved in mitochondrial respiration, mitochondrial metabol ism, and mitochondrial membrane transport. Four hub genes (BAX, IDH3A, MRPS6, an d GPT2) were selected to take part in the creation of a novel mitochondrial-base d risk model for AD prediction. The risk score demonstrated excellent diagnostic performance in both the training cohort (AUC = 1.000) and the validation cohort (AUC = 0.810). Four hub MitoDEGs were also clearly associated with the innate i mmune cells’ infiltration and the molecular modifications of mitochondrial hyper metabolism in AD. We further discovered that AD patients had considerably greate r plasma ccf-mtDNA levels than controls (U = 92.0, p<0.001 ). Besides, there was a significant relationship between the up-regulation of pl asma mtDNA and the severity of AD symptoms. The study highlights BAX, IDH3A, MRP S6 and GPT2 as crucial MitoDEGs and demonstrates their efficiency in identifying AD. Moderate to severe AD is associated with increased markers of mitochondrial damage and cellular stress (ccf=mtDNA).”
HeilongjiangPeople’s Republic of ChinaAsiaAtopic DermatitisBioinformaticsBiomarkersBiotechnologyCellular S tructuresCyborgsCytoplasmCytoplasmic StructuresDermatitisDermatologyDiagnostics and ScreeningEmerging TechnologiesHealth and MedicineInformati on TechnologyIntracellular SpaceMachine LearningMitochondriaOrganellesSkin Diseases and ConditionsSkin and Connective Tissue Diseases and ConditionsSubcellular Fractions
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