Biomedical subjects

Rui Sun

Publications and source records attributed to Rui Sun.

4 recordsLinked to original sources

PubMed2026

The impact for causal associations between common diseases and inflammatory bowel disease: a disease-wide bidirectional Mendelian randomization study.

OBJECTIVES: Observational studies on associations between various diseases and inflammatory bowel disease (IBD) are often limited by confounding and reverse causation. We aimed to assess potential causal relationships between a wide range of diseases and IBD, including Crohn's disease (CD) and ulcerative colitis (UC). METHODS: We performed a comprehensive bidirectional Mendelian randomization (MR) analysis of 104 common diseases and IBD traits using the generalized summary-data-based MR (GSMR) approach. Genome-wide association study (GWAS) summary statistics for diseases were obtained from the MRC Integrative Epidemiology Unit, and IBD data from the International IBD Genetics Consortium. Summary-data-based MR (SMR) integrating GWAS and expression quantitative trait locus data was applied to identify pleiotropic genes associated with IBD. RESULTS: MR analyses identified 38, 34, and 52 exposures significantly associated with IBD, UC, and CD, respectively. Childhood- and adult-onset asthma showed distinct causal effects on UC and CD. Reverse MR indicated associations between IBD traits and 15 diseases, including multiple sclerosis. SMR identified RGS14 and CARD9 as pleiotropic genes linked to IBD, suggesting shared genetic mechanisms with asthma and multiple sclerosis. CONCLUSIONS: These findings provide evidence for causal links and shared immune-related genetic mechanisms underlying IBD, highlighting potential targets for future research.

Humans↗

PubMed2026

AI proteomics: from protein identification to virtual cells.

Artificial intelligence (AI) is transforming scientific research, including proteomics. In this Perspective, we highlight key mass spectrometry (MS)-based proteomics areas where AI is driving innovation, ranging from protein identification to building AI virtual cells. These include improving peptide and protein identification and quantification; characterizing protein-protein interactions and protein complexes; advancing spatial and perturbation proteomics; integrating multi-omics data; and, ultimately, enabling AI virtual cells. Finally, we call for global collaboration among data producers, data consumers and other stakeholders to establish an AI-friendly ecosystem for MS-based proteomics, laying the foundation for transformative advancements in proteomics driven by AI.

Proteomics↗

PubMed2026

Decoding glioblastoma evolution and heterogeneity through mechanistic modeling: implications for clinical translation.

Glioblastoma (GBM) is one of the most aggressive and lethal primary brain tumors in adults, characterized by dynamic clonal evolution and extensive genomic, cellular, spatial, and microenvironmental heterogeneity. Multi-omics studies have revealed that GBM follows complex evolutionary trajectories involving genetic, epigenetic, transcriptional, and immune-microenvironmental remodeling as tumors grow, adapt to the brain microenvironment, and acquire therapeutic resistance. Increasing evidence suggests that GBM may originate from aberrant neural stem or progenitor cells, including those residing in the subventricular zone, and that glioblastoma stem cells (GSCs) contribute to tumor propagation, heterogeneity, and recurrence. A key conceptual challenge is to reconcile hierarchical cancer stem cell models, in which GSCs are viewed as relatively stable tumor-propagating subpopulations, with dynamic state plasticity models, in which stem-like properties can be reversibly acquired or lost during transitions among proneural-like, mesenchymal-like, invasive, and therapy-tolerant states. Recent advances in single-cell profiling, spatial transcriptomics, lineage tracing, organoid culture, 3D bioprinting, genetically engineered models, and artificial intelligence (AI)-assisted computational modeling have substantially improved the ability to study these processes. However, no currently available model fully recapitulates human GBM heterogeneity, recurrence, treatment history, and tumor-microenvironment interactions. Therefore, model selection should be guided by clearly defined mechanistic questions rather than by reliance on any single platform. This review summarizes current advances in in vitro, ex vivo, in vivo, and computational models for studying GBM evolution and heterogeneity, and discusses how integrated model pipelines may improve preclinical drug testing, treatment-response prediction, and precision neuro-oncology.

Humans↗

PubMed2026

Allelic variation in UVR8 modulates thermotolerance-yield tradeoffs in plants.

Industrial activities have driven stratospheric ozone depletion, increasing surface UV-B radiation while exacerbating global warming. These changes limit crop productivity, alter species distributions, and disrupt plant metabolic processes, but the mechanisms linking energy signaling to heat-stress responses remain unclear. Here, we identify the photoreceptor UV RESISTANCE LOCUS 8b (OsUVR8b) as a substrate of SNF1-related protein kinase 1 (SnRK1) in rice and reveal a natural variation at its SnRK1-mediated phosphorylation site (Ser177) that is correlated with adaptation to tropical climates. The thermotolerant OsUVR8bAla177 accessions show geographic enrichment in low-latitude regions with elevated temperatures. Functional validation through prime editing demonstrated that a Ser177-to-Ala177 substitution enhances heat tolerance, whereas the reverse edit compromises it. Mechanistically, OsUVR8bSer177 exhibits reduced stability and an impaired capacity for scavenging reactive oxygen species under heat stress. The regulatory function of the OsUVR8b Ser177 phosphorylation site, a molecular switch that governs UVR8 stability and thermotolerance, can be functionally re-established across rice, Arabidopsis, tobacco, and soybean, indicating its preservation during domestication. Notably, OsUVR8bSer177 maintains higher fertility and yield under non-stress conditions, indicating a tradeoff between heat adaptation and productivity. Our findings thus establish this switch as a key regulator of the yield-resilience balance and a promising target for breeding of climate-resilient crops.

Thermotolerance↗