Biomedical subjects

Rui Zhao

Publications and source records attributed to Rui Zhao.

4 recordsLinked to original sources

PubMed2026

Proteogenomic analysis of pediatric and AYA high-grade glioma reveals age-dependent biology, female-male differences, and kinase targets.

High-grade gliomas (HGGs) in children and adolescents and young adults (AYA) exhibit distinct biology across the neurodevelopmental spectrum. To dissect tumor-intrinsic molecular characteristics independent of developmental variation, we perform comprehensive proteogenomic analyses of tumors from 112 HGG patients aged 0-40 years. Our multi-omics analysis identifies two AYA subgroups-adolescents (aged 15-26 years) and young adults (aged 26-40 years)-with distinct molecular profiles and survival outcomes. Tumor-normal comparisons and survival modeling highlight roles of oxidative phosphorylation and neuronal system biology in glioma progression. Causal network analysis and cell line studies provide a rationale for personalized therapies targeting candidate kinases, such as CDK8. Survival modeling, clustering, and immune-landscape analyses identify proteins, post-translational modifications, and immune signatures linked to outcomes and reveal clinically relevant differences between male and female patients.

adolescent and young adult glioma↗

PubMed2026

Metagenomic next-generation sequencing of cerebrospinal fluid reveals pathogen spectrum and mortality predictors among patients with advanced HIV-1 disease at a tertiary hospital in China.

BACKGROUND: Central nervous system (CNS) infections remain the major causes of morbidity and mortality among people living with HIV-1 (PLWH), particularly in resource-limited settings. However, the clinical characteristics and prognostic indicators of PLWH with suspected CNS infections are not well defined. In this study, we aim to characterize the spectrum of CNS pathogens, clinical characteristics, in-hospital mortality, and factors associated with death among people with advanced HIV-1 disease (AHD) in Guangxi, China. METHODS: Metagenomic next-generation sequencing (mNGS) was performed to analyze types of infection in cerebrospinal fluid (CSF) from 61 treatment-naive PLWH with suspected CNS infections. Clinical data, routine laboratory tests, and biochemical tests were collected and analyzed. RESULTS: Among the 61 CSF samples, primarily with AHD, a total of 206 pathogens were identified. Viral pathogens predominated, with Epstein-Barr virus being the most frequently identified, followed by cytomegalovirus. Compared with patients with single-pathogen infection, those with multiple infections (viral, bacterial, and fungal) exhibited significantly lower CD4 T cell counts, higher C-reactive protein levels, and markedly reduced lipid metabolism parameters. However, infection types were not significantly associated with in-hospital death. Multivariate logistic regression analysis identified plasma low density lipoprotein (LDL) and CSF lactate dehydrogenase (LDH) as independent predictors of in-hospital death. CONCLUSION: In PLWH with AHD and suspected CNS infections, multiple pathogens frequently coexist in the CSF. Plasma LDL and CSF LDH levels were independent predictors of death, indicating their potential value as early risk stratification in AHD.

Humans↗

PubMed2026

COVID-19 multi-omics reveal organ-specific responses and biomarkers.

OBJECTIVE: Post-COVID-19 syndrome is characterised by persistent immune dysfunction and multi-organ sequelae. This study aimed to characterise the systemic blood molecular landscape induced by SARS-CoV-2 infection and identify prognostic markers linked to skeletal muscle mass loss, a key driver of poor outcomes. METHODS: We enrolled 30 healthy controls and 307 COVID-19 patients, collecting 422 plasma samples for integrated proteomic and metabolomic profiling to investigate organ-specific molecular alterations in COVID-19. RESULTS: We comprehensively mapped the molecular landscape of COVID-19, encompassing immune, tissue-specific, and metabolic perturbations, and delineated their interactions. Focusing on organ-damage-related molecular patterns associated with disease progression and mortality, we found that skeletal muscle mass loss contributed to poor clinical outcomes of COVID-19 (p < 0.0001). Dysregulated arginine metabolism emerged as a key metabolic signature in fatal COVID-19 cases, with GLUL, GOT1, and citrulline showing significant correlation with skeletal muscle mass loss. Longitudinal analyses further revealed that reduced citrulline levels underlie the poor outcome of COVID-19 patients with muscle mass loss. These findings were robustly supported through multiple approaches: Mendelian randomization confirmed causal relationships between citrulline depletion, sarcopenia/fat-free mass loss, and COVID-19 mortality (p < 0.05), transcriptomic analyses of SARS-CoV-2-infected golden hamsters (GSE231910) provided additional support in enrichment of arginine biosynthesis (FDR < 0.05), and in vitro experiments further demonstrated that citrulline depletion promotes pro-inflammatory M1 macrophage polarisation — a key immunological feature of critical COVID-19. Leveraging these insights, we developed a skeletal muscle loss-specific prognostic prediction model for COVID-19 using GLUL, GOT1, and citrulline. This model effectively stratified patients into high- and low-risk groups (p = 0.035). CONCLUSION: Our study advances the understanding of COVID-19-induced organ pathophysiology and provides a foundation for developing targeted therapeutic strategies for post-COVID sequelae.

COVID-19↗

PubMed2025

Hematological diseases-related mucormycosis: A retrospective single center study.

BACKGROUND AND AIM: Mucormycosis is a life-threatening invasive fungal infection. This study aimed to analyze the clinical characteristics of patients with hematologic malignancies complicated with mucormycosis. METHODS: This retrospective study investigated the clinical characteristics, epidemiological features, treatment, and prognosis of 46 patients with hematological diseases and Mucor infection as indicated by mNGS from August 28, 2020 to September 11, 2023. Metagenomic next-generation sequencing (mNGS) refers to the application of high-throughput sequencing technology for the comprehensive analysis of nucleic acid content in patient samples, facilitating the detection and characterization of microbial DNA and/or RNA, and then comparing and analyzing the results with an information database to determine the types of pathogenic microorganisms present in the sample. RESULTS: The median age of admission for the included patients was 49 years (9-78). Multivariate analysis identified age over 60 years (p = 0.006 < 0.05), high-dose corticosteroids (p = 0.001 < 0.05), neutropenia lasting more than 10 days (p = 0.041 < 0.05), and two or more Mucor infections (p = 0.004 < 0.05) were independent risk factors for OS in patients with hematological diseases. Moreover, differences between groups were analyzed using the Fisher exact probability method, and no significant difference was observed in the efficacy of various types of antifungal therapies. CONCLUSION: Patients with hematologic malignancies benefit greatly from early diagnosis and treatment when suspected of Mucor infection. mNGS is an important supplementary method for early diagnosis of Mucor infection. Moderated use of corticosteroids, reducing the duration of neutropenia, and enhancing autologous immune function are important measures to reduce patient mortality rate.

Retrospective Studies↗