Biomedical subjects

Peng Yang

Publications and source records attributed to Peng Yang.

3 recordsLinked to original sources

PubMed2026

A geroprotective probiotic and its functional metabolite counteract inflammaging to extend healthspan.

The gut microbiome profoundly influences host aging, yet the specific microbes and mechanisms governing divergent aging trajectories remain elusive. In this study, we delineated enterotype-specific gut microbial remodeling during aging and developed a microbiome-based aging clock (MicroAge) to track biological aging trajectories. We identified Bifidobacterium pseudocatenulatum (B. pseudocatenulatum) as a candidate geroprotective species consistently depleted during aging across both sexes and multiple Chinese cohorts. In naturally aged mice, oral B. pseudocatenulatum monotherapy rescued intestinal homeostasis, mitigated multiorgan inflammaging, enhanced cognitive-motor performance and extended healthspan. Mechanistically, we characterized 5-aminovaleric acid betaine (5-AVAB) as a key B. pseudocatenulatum-derived metabolite whose levels decline physiologically in aging humans. 5-AVAB supplementation partially recapitulated a broad spectrum of the systemic benefits observed with B. pseudocatenulatum treatment, including improved cognitive and motor function and suppressed multiorgan inflammaging. Our findings identify the B. pseudocatenulatum-5-AVAB axis as a promising target for microbiome-based interventions to promote healthy aging.

Animals↗

PubMed2026

Landscape Genomics Reveals Divergent Adaptation Modes and Predicts Climate Vulnerability in Xinjiang Indigenous Sheep.

Climate change increasingly endangers precious indigenous sheep germplasm resources distributed across diverse Chinese landscapes, and systematically decoding their polygenic climate-adaptive genetic mechanisms is essential for targeted breed conservation and long-term sustainable pastoral production. Whole-genome resequencing data from 93 individuals covering six representative local sheep breeds were analyzed in this work. After filtering highly collinear climate variables, three mature landscape genomic approaches were jointly applied to identify environment-linked gene variants, while two predictive metrics across ten CMIP6 future climate scenarios quantified each breed's long-term adaptive risks. Six temperature- and water-related environmental factors jointly drove sheep population genetic differentiation, with temperature fluctuation indices showing markedly stronger explanatory power. Detected adaptive genes were significantly enriched in ion transport, energy metabolism and cellular stress response pathways. Future projections indicated western breeds (Bayinbuluke, Cele Black, Xiahe) face severe maladaptation risks under high-emission SSP370 scenarios by 2100, whereas central and eastern breeds possess much broader climate tolerance. This study systematically reveals the core genomic basis of ovine climate adaptation and quantifies distinct breed-specific climate vulnerability, providing solid reliable theoretical support for precision germplasm conservation and selective breeding of climate-resilient sheep varieties.

adaptive loci↗

PubMed2025

Learning directed acyclic graphs for ligands and receptors based on spatially resolved transcriptomic data of ovarian cancer.

To unravel the mechanism of immune activation and suppression within tumors, a critical step is to identify transcriptional signals governing cell-cell communication between tumor and immune/stromal cells in the tumor microenvironment. Central to this communication are interactions between secreted ligands and cell-surface receptors, creating a highly connected signaling network among cells. Recent advancements in in situ-omics profiling, particularly spatial transcriptomic (ST) technology, provide unique opportunities to directly characterize ligand-receptor signaling networks that power cell-cell communication. In this paper, we propose a novel statistical method, LRnetST, to characterize the ligand-receptor interaction networks between adjacent tumor and immune/stroma cells based on ST data. LRnetST utilizes a directed acyclic graph model with a novel approach to handle the zero-inflated distributions of ST data. It also leverages existing ligand-receptor regulation databases as prior information, and employs a bootstrap aggregation strategy to achieve robust network estimation. Application of LRnetST to ST data of high-grade serous ovarian tumor samples revealed both common and distinct ligand-receptor regulations across different tumors. Some of these interactions were validated through both a MERFISH dataset and a CosMx SMI dataset of independent ovarian tumor samples. These results cast light on biological processes relating to the communication between tumor and immune/stromal cells in ovarian tumors. An open-source R package of LRnetST is available on GitHub at https://github.com/jie108/LRnetST.

Humans↗