Weizhi Zhang | PubMed Health

PubMed2026

Identification of potential key genes involved in iron deficiency for sepsis: A retrospective cohort and transcriptomic study.

Iron overload has been associated with sepsis, but the role of iron deficiency and its molecular links remain unclear. We investigated the association between iron deficiency and sepsis and identified candidate genes potentially linking these conditions. MIMIC-IV data were used to assess the association between serum iron and sepsis status. Transcriptomic datasets from dietary iron-deficient mice (GSE10421), LPS-induced septic mice (GSE267388), and a human blood sepsis cohort (GSE137340) were sequentially analyzed to identify and externally evaluate candidate genes. IEU Open GWAS summary statistics were used for exploratory Mendelian randomization (MR). Exploratory drug prediction was performed using L1000FWD, followed by molecular docking analysis. Patients with sepsis had significantly lower serum iron levels, and restricted cubic spline analysis showed a nonlinear association between serum iron and the odds of sepsis. Cross-tissue transcriptomic analysis identified Sqle, Lss, and Rdh11 as candidate genes. In the human blood cohort, SQLE and RDH11 were significantly increased, whereas LSS was not significantly altered. Exploratory MR showed that genetically proxied SQLE expression was associated with higher odds of sepsis (odds ratio [OR] = 1.23, P = 1.67 × 10-3), whereas LSS expression was associated with lower odds (OR = 0.97, P = 8.90 × 10-4); RDH11 showed no significant association (OR = 1.01, P = .90). Drug prediction identified ML106 as the top-ranked candidate drug, and molecular docking predicted potential binding poses with SQLE and LSS. Serum iron showed a nonlinear association with sepsis status. SQLE, LSS, and RDH11 emerged as candidate genes, with concordant expression changes of SQLE and RDH11 observed in human blood. MR findings for SQLE and LSS were exploratory and require further validation. ML106 was identified through exploratory drug prediction and requires experimental validation before its therapeutic relevance can be established.

Sepsis↗

PubMed2026

Identification of a G-quadruplex-forming cell-free DNA fragment as a biomarker for the precise diagnosis of hepatocellular carcinoma.

Early detection of hepatocellular carcinoma (HCC) remains challenging, as the currently recommended surveillance strategy based on ultrasound combined with alpha-fetoprotein (AFP) is limited by suboptimal sensitivity and accessibility. Cell-free DNA (cfDNA) provides a minimally invasive avenue for cancer detection. However, most existing cfDNA-based approaches either perform unreliably in low-input samples or require analytically complex workflows. Here, we systematically profiled serum cfDNA from individuals with HCC and without HCC and identified a high-abundance tumor-associated single cfDNA fragment at the FAM230F genomic region. Integrative analysis of liver assay for transposase-accessible chromatin with sequencing (ATAC-seq) data revealed consistent tumor-specific chromatin accessibility at this locus, suggesting a tumor-derived origin. Structural characterization further demonstrated enrichment of G-quadruplex (G4) features within the target sequence, which may increase resistance to serum nuclease degradation and promote its preferential retention in circulation. Based on these properties, we established a qPCR-based detection workflow with clinical accessibility. In a validation cohort independent of the discovery cohort, a ΔC t cutoff of 2 was selected by maximizing the Youden index within the same cohort. The assay showed a sensitivity of 94.5% and a specificity of 90.5% for distinguishing HCC from non-HCC. Collectively, our study identifies FAM230F as a structurally stable tumor-associated cfDNA fragment and establishes a simple and scalable qPCR-based assay for HCC detection, providing a practical framework for translating cfDNA fragment analysis into clinical biomarkers.

Journal Article↗