PubMed HealthSearch

Biomedical subjects

Jian Yang

Publications and source records attributed to Jian Yang.

8 recordsLinked to original sources

Genetic evidence and cross-species functional characterization implicate CNN2 in age-related macular degeneration susceptibility.

Age-related macular degeneration (AMD) is a leading cause of irreversible visual impairment in the aging population globally. Although genome-wide association studies (GWAS) have identified many AMD susceptibility loci, the genes and mechanisms underlying many of these associations remain unresolved. Here, we integrated expression quantitative trait locus (eQTL) data with AMD GWAS to prioritize nine putative genes. Through in vivo screening in zebrafish, we demonstrated that the downregulation of cnn2 and sarm1 expression led to ocular structural abnormalities and visual functional impairment. Subsequent mouse model studies confirmed that Cnn2 deficiency affected photoreceptor structure and function, impaired contrast sensitivity, and caused abnormalities in cone cell immunostaining. Given that CNN2 is predominantly expressed in endothelial cells, we propose that endothelial dysfunction may cascade to impair photoreceptor function. Collectively, through in silico prioritization and cross-species functional characterization, we identify CNN2 as a candidate susceptibility gene in AMD pathogenesis, providing vital underlying mechanistic insights.

Animals

Beyond Photometric Consistency: Addressing Loss Insensitivity to Depth Noise in Endoscopic Estimation via Error Calibration.

Self-supervised monocular depth estimation in endoscopy is fundamentally constrained by the ill-posed nature of photometric supervision. In this work, we identify a critical yet overlooked cause of this ambiguity: the inherent insensitivity of photometric loss to depth noise. To overcome this intrinsic limitation, we propose Depth Error Calibration Learning (DECL), a two-stage framework that suppresses prediction variance and mitigates residual errors in self-supervised depth estimation. In Stage I (Variance Reduction), a cyclic depth generation strategy produces multiple depth hypotheses for the input image. The per-pixel empirical variance is quantified and integrated into a dedicated variance loss term, which penalizes inconsistent predictions and encourages the network to generate more stable and reliable depth estimates. In Stage II (Bias Calibration), an image-conditioned diffusion model refines the Stage-I depth prior and mitigates structured residuals through iterative denoising, thereby improving geometric accuracy and global consistency. Extensive experiments on three public endoscopic datasets demonstrate that DECL achieves consistent improvements over representative self-supervised monocular depth estimation methods under the evaluated protocols. Moreover, ablation studies on two representative backbones indicate that DECL is not restricted to a single network implementation, while broader validation on additional backbone families remains necessary. The source code is publicly available at https://github.com/DavidLuBit/EndoDenoising.

Journal Article

TWIST2-dependent transcriptional activation of TPI1 mediates TGF-β1-driven fibroblast activation in pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial lung disease characterized by aberrant profibrotic signaling and excessive extracellular matrix deposition, accompanied by fibroblast-to-myofibroblast transition. Despite extensive investigation, the molecular mechanisms underlying IPF pathogenesis remain incompletely understood. Here, we investigated the role of triosephosphate isomerase 1 (TPI1) in IPF progression and its regulation by transforming growth factor-β (TGF-β) signaling. Loss-of-function analyses identified TPI1 as a downstream effector of TGF-β1, as its knockdown markedly suppressed fibrotic marker expression, fibroblast proliferation, and migration. Mechanistically, TWIST2 was shown to function as a direct transcriptional regulator of TPI1, binding to its promoter and promoting transcriptional activation. Rescue experiments further confirmed that the TWIST2-TPI1 axis is central to the progression of pulmonary fibrosis. Notably, knockdown of either TPI1 or TWIST2 effectively attenuated TGF-β1-induced fibrotic phenotypes. Collectively, these findings define the TGF-β1/TWIST2/TPI1 signaling axis as an important regulator of pathogenic fibroblast behavior and pro-fibrotic responses through transcriptional control of TPI1, highlighting its potential as a therapeutic target for IPF.

Twist-Related Protein 1

S100P as a Shared Biomarker in Inflammatory Bowel Disease, Colorectal Cancer, and Pancreatic Adenocarcinoma: An Integrated Transcriptomic Analysis.

Inflammatory bowel disease (IBD) is associated with an increased risk of colorectal cancer (CRC) and pancreatic adenocarcinoma (PAAD), yet the molecular features shared among these diseases remain incompletely understood. This study aimed to identify common genes and biological pathways associated with IBD, CRC, and PAAD through integrated transcriptomic analysis and experimental validation. Gene expression datasets for IBD, CRC, and PAAD were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. Weighted gene co-expression network analysis and differential expression analysis were performed to identify disease-associated and shared genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (analyses were used to explore enriched biological functions and pathways. Immune cell infiltration was evaluated using Cell-type Identification by Estimating Relative Subsets of RNA Transcripts. Receiver operating characteristic analysis was performed to assess the diagnostic performance of common genes. Single-cell RNA sequencing analysis was conducted to examine the cellular distribution of S100P. In addition, the effects of S100P downregulation were evaluated in lipopolysaccharide (LPS)-stimulated colonic epithelial cells. A total of 162 disease-associated genes and four common genes were identified. Functional enrichment analyses indicated significant enrichment of immune- and inflammation-related pathways, including the interleukin-17 signaling pathway. Immune infiltration analysis revealed similar trends in several immune cell populations across IBD, CRC, and PAAD. Single-cell analysis showed elevated S100P expression in epithelial cells from all three diseases. Downregulation of S100P restored the proliferative capacity of LPS-stimulated colonic epithelial cells and reduced inflammatory cytokine expression. Integrated transcriptomic analysis identified S100P as a biomarker associated with IBD, CRC, and PAAD and highlighted shared immune-related features across these diseases.

Humans

Microbial decomposer diversity and metabolic function during the decomposition of brine shrimp carcasses in a saline lake.

BACKGROUND: Decomposition of brine shrimp carcasses has a crucial role in carbon cycling of saline lakes, yet the microbial dynamics remain poorly understood. RESULTS: Here we integrated metagenomics, metatranscriptomics, culturomics, metabolomics, and microcosm experiments to investigate microbial community succession and function during brine shrimp (Artemia sp.) carcass decomposition in Barkol Lake, a hypersaline lake in China. A total of 149 metagenome-assembled genomes (MAGs) and 77 pure culture genomes were recovered across 33 phyla, with 72.12% genomes representing species-level novel lineages. Our results reveal diverse bacterial and archaeal taxa, including novel lineages from CG03, T1Sed10-126 and rare archaeal taxa (Asgardarchaeota, Thermoplasmatota, Nanoarchaeota, and Halobacteriota), involved in degradation of biomacromolecules-proteins, carbohydrates, lipids, and nucleic acids-via extracellular hydrolysis, nutrient transport, and intracellular catabolism. These taxa exhibit substrate preferences, rapidly responding to the breakdown of polysaccharides and proteins, followed by lipids and nucleic acids. Hydrolyzed oligomers are further oxidized by various microbes through fermentation, sulfate reduction, and methanogenesis via metabolic handoffs. Additionally, viral auxiliary metabolic genes (AMGs) further enhance microbial host functions, contributing to key ecological processes such as carbon cycling and stress response. A temporally structured microbial decomposer network (MDN) was observed, driving mineralization cascades from fermentation to sulfate reduction and methanogenesis. CONCLUSIONS: This study reveals microbial metabolic handoffs and virus-mediated modulation as critical mechanisms for organic matter turnover, expanding the known diversity and function of decomposers in saline ecosystems. Our findings offer new insights into biogeochemical processes in saline lakes and highlight a synergistic microbial decomposer network involving bacteria, archaea, and viruses that collectively drive nutrient cycling during brine shrimp carcass decomposition. Video Abstract.

Animals

CCRR: a user-friendly platform for analyzing complex chromosomal rearrangements in tumors.

SUMMARY: Complex chromosomal rearrangements in tumors involve intricate genomic alterations that significantly affect gene function and contribute to cancer development. Identifying these events is crucial for cancer research but is often challenging due to the complexity and limitations of existing tools. We developed the Complex Chromosomal Rearrangements Resolver (CCRR), a comprehensive, reproducible, and user-friendly platform for analyzing complex rearrangements in tumors. CCRR integrates multiple SV and CNV detection tools within a Docker container environment, simplifying installation and configuration. It can be easily deployed, automating the execution and merging of results, providing high-confidence consensus SV and CNV calls, allowing researchers to efficiently analyze complex chromosomal rearrangements in tumors without extensive bioinformatics expertise. CCRR also includes a web server for one-click analysis and customized visualization. AVAILABILITY AND IMPLEMENTATION: The CCRR platform is freely available at https://www.ccrr.life. Source code and executables can be accessed at https://github.com/laslk/CCRR. An archived version is available at Zenodo: https://doi.org/10.5281/zenodo.15386513.

Software

wgatools: an ultrafast toolkit for manipulating whole-genome alignments.

SUMMARY: With the rapid development of long-read sequencing technologies, the era of individual complete genomes is approaching. We have developed wgatools, a cross-platform, ultrafast toolkit that supports a range of whole-genome alignment formats, offering practical tools for conversion, processing, evaluation, and visualization of alignments, thereby facilitating population-level genome analysis and advancing functional and evolutionary genomics. AVAILABILITY AND IMPLEMENTATION: wgatools supports diverse formats and can process, filter, and statistically evaluate alignments, perform alignment-based variant calling, and visualize alignments both locally and genome-wide. Built with Rust for efficiency and safe memory usage, it ensures fast performance and can handle large datasets consisting of hundreds of genomes. wgatools is published as free software under the MIT open-source license, and its source code is freely available at https://github.com/wjwei-handsome/wgatools and https://zenodo.org/records/14882797.

Software

Association analysis of mitochondrial DNA heteroplasmic variants: Methods and application.

We rigorously assessed a comprehensive association testing framework for heteroplasmy, employing both simulated and real-world data. This framework employed a variant allele fraction (VAF) threshold and harnessed multiple gene-based tests for robust identification and association testing of heteroplasmy. Our simulation studies demonstrated that gene-based tests maintained an appropriate type I error rate at &#x3b1;&#x202f;=&#x202f;0.001. Notably, when 5&#x202f;% or more heteroplasmic variants within a target region were linked to an outcome, burden-extension tests (including the adaptive burden test, variable threshold burden test, and z-score weighting burden test) outperformed the sequence kernel association test (SKAT) and the original burden test. Applying this framework, we conducted association analyses on whole-blood derived heteroplasmy in 17,507 individuals of African and European ancestries (31&#x202f;% of African Ancestry, mean age of 62, with 58&#x202f;% women) with whole genome sequencing data. We performed both cohort- and ancestry-specific association analyses, followed by meta-analysis on both pooled samples and within each ancestry group. Our results suggest that mtDNA-encoded genes/regions are likely to exhibit varying rates in somatic aging, with the notably strong associations observed between heteroplasmy in the RNR1 and RNR2 genes (p&#x202f;<&#x202f;0.001) and advance aging by the Original Burden test. In contrast, SKAT identified significant associations (p&#x202f;<&#x202f;0.001) between diabetes and the aggregated effects of heteroplasmy in several protein-coding genes. Further research is warranted to validate these findings. In summary, our proposed statistical framework represents a valuable tool for facilitating association testing of heteroplasmy with disease traits in large human populations.

Humans