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A pathogenic COL7A1 variant highlights semi-dominant inheritance in dystrophic epidermolysis bullosa.

Dystrophic epidermolysis bullosa is a rare subtype of inherited epidermolysis bullosa, caused by variants in the collagen type VII alpha 1 chain (COL7A1) gene (MIM120120). Both autosomal dominant and recessive inheritance has been reported with variable phenotype. We investigated a Pakistani family with dystrophic epidermolysis bullosa via exome sequencing and identified a pathogenic nonsense variant in COL7A1 NM_000094 c.1573 C > T:p.(Arg525*). The inheritance pattern observed was consistent with a semi-dominant model, where heterozygous parents exhibited a mild phenotype, and homozygous children were more severely affected. For dystrophic epidermolysis bullosa, loss-of-function variants are typically associated with the autosomal recessive form, while missense variants are linked to the autosomal dominant form. A review of the literature suggests a semi-dominance pattern for some missense variants, particularly glycine substitutions, but this concept had not been formally recognized. This study highlights the importance of considering semi-dominant inheritance models for dystrophic epidermolysis bullosa and other Mendelian diseases with an autosomal recessive mode of inheritance, as it can significantly impact diagnosis and genetic counseling.

Humans

TCGA-based identification of prognostic biomarkers and candidate traditional Chinese medicine compounds in papillary thyroid carcinoma: An observational study.

This study aimed to identify prognostic genes associated with papillary thyroid carcinoma (PTC) and explore candidate traditional Chinese medicine (TCM) compounds using integrated bioinformatics and molecular docking. In this observational study, PTC gene expression profiles and clinical data were obtained from The Cancer Genome Atlas. Differentially expressed genes were screened using differential-expression sequencing (DESeq2), followed by protein-protein interaction network analysis to identify hub genes. Their expression, diagnostic value, immune relevance, prognostic significance, protein-level validation, and single-cell distribution were assessed using gene expression profiling interactive analysis, receiver operating characteristic analysis, immune infiltration analysis, Kaplan-Meier survival analysis, the human protein atlas, and single-cell RNA-sequencing data. Candidate TCM compounds were predicted using symptom mapping (SymMap) and the TCM Systems Pharmacology Database and Analysis Platform, and molecular docking was performed to evaluate potential ligand-target interactions. Five hub genes, colony-stimulating factor 2, apolipoprotein E, fibronectin 1 (FN1), collagen type I alpha 1 chain (COL1A1), and intercellular adhesion molecule 1, were identified and found to be significantly upregulated in PTC tissues, with diagnostic value in receiver operating characteristic analysis. Immune infiltration analysis showed associations with macrophages, dendritic cells, and T helper 1 cells, whereas single-cell analysis demonstrated heterogeneous expression across immune and stromal cell populations, including fibroblasts. Higher FN1 and COL1A1 expression was associated with poorer outcomes. Immunohistochemistry supported the expression patterns, while single-cell analysis provided exploratory cell-type-level context for the cellular distribution of selected genes. Ginseng and Smilax glabra were predicted as common candidate TCMs, and docking suggested favorable binding between their active compounds and selected hub targets. Colony-stimulating factor 2, apolipoprotein E, FN1, COL1A1, and intercellular adhesion molecule 1 may be biologically relevant hub genes in PTC, while FN1 and COL1A1 may have prognostic value. Predicted TCM compounds provide preliminary computational evidence for possible compound-target interactions, requiring experimental and clinical validation.

Female

Plasma Proteomic Profiles Predict Individual Future Osteoarthritis Risk.

OBJECTIVE: Osteoarthritis (OA) is a widespread degenerative joint disease that causes a considerable socioeconomic burden. Despite progress in genetic and environmental insights, early diagnosis is still limited by the lack of evident symptoms during the initial phases and accurate biomarkers. This study aims to identify plasma proteins associated with future risk of OA and develop a predictive model. METHODS: We conducted a large-scale proteomic analysis of 45,307 participants from the UK Biobank, excluding those with baseline OA. Plasma samples were assayed using the Olink Explore Proximity Extension Assay targeting 1,463 unique proteins. Clinical variables and OA outcomes were extracted and linked to electronic health records. A predictive model was constructed using the LightGBM machine learning method, and SHapley Additive exPlanations (SHAP) were applied to evaluate the importance of variables. RESULTS: We identified a panel of proteins significantly associated with the risk of developing OA. Notably, after adjusting for multiple confounders, collagen type IX alpha 1 chain (COL9A1) and cartilage acidic protein 1 (CRTAC1) were the most significant predictors of incident OA, with hazard ratios of 1.54 (95% confidence interval [CI] 1.48-1.61) and 1.65 (95% CI 1.54-1.78), respectively. SHAP analysis allowed a profound interpretation of the contribution of each protein and clinical variable to the model, revealing the multifactorial nature of OA risk prediction. The temporal trajectories of plasma proteins indicated that the levels of COL9A1 and CRTAC1 began to deviate from normal for more than a decade before OA onset, suggesting their potential use in early detection strategies. The predictive model, developed using the LightGBM algorithm, integrated proteins with clinical covariates and demonstrated an area under the curve (AUC) of 0.729 for 5-year OA prediction, 0.721 for 10-year prediction, and 0.723 for all incident OA. The predictive accuracy of the model was further enhanced for hip and knee OA, achieving AUCs of 0.820 and 0.803 for 5-year predictions. CONCLUSION: Our study identified the role of plasma proteomics in predicting future OA risk, which could contribute to preemptive measures. The innovative model, which integrates proteomic biomarkers with clinical data, offers a potential tool for risk assessment, potentially optimizing OA management strategies and enhancing prevention efforts.

Humans

Spatial Proteomics of the Normal Breast Collagen Stroma: Links to Density and Body Mass Index.

Collagen breast stroma can become a breast cancer risk factor, yet proteomic regulation of normal breast stroma remains poorly defined. This study evaluates the spatial regulation of the collagen proteome from normal breast tissue. Normal breast tissue sections from the Susan G. Komen tissue bank were used (n = 40), with data including genetic ancestry (n = 20 African ancestry; n = 20 European ancestry), body-mass-index (BMI), age, and mammogram density by the Breast Imaging Reporting and Data System (BI-RADS). 10-plex cell marker staining showed CD44 and COL1A1 markers modulated with BMI. Collagen fiber widths by second harmonic generation microscopy contrasted in BMI categories by genetic ancestry. Targeted extracellular matrix proteomics mass spectrometry imaging showed the collagen alpha-1(I) chain proteome was spatially heterogeneous across the normal breast microenvironment with site-specific post-translational modification of proline hydroxylation. Signatures computationally extracted from stroma-rich regions reported that 47 collagen peptides distinguished BI-RADS categories (area under the receiver operating curve >0.7; p-value >0.05). Multivariate modeling of collagen peptides, fiber metrics, and clinical features supported a strong positive association with BMI as a determinant of collagen alterations in the normal breast. This study provides a foundation for larger studies investigating the clinical value of spatial collagen proteome alterations in human breast.

Humans

A Fibroblast-Based Adenoviral Reporter System Driven by the Mouse Collagen Type I Alpha 1 Promoter for Antifibrotic Drug Screening.

Cardiac fibrosis, characterized by aberrant fibroblast activation and excessive extracellular matrix deposition, lacks target-specific therapies, largely due to the absence of longitudinal, scalable, and non-destructive in vitro screening platforms. Traditional end-point assays and resource-intensive stem cell models inherently preclude real-time monitoring of fibrotic progression. To overcome these limitations, this protocol describes the generation, optimization, and validation of a mouse collagen type I alpha 1 (Col1a1) promoter-driven adenoviral mCherry fluorescent reporter system (Ad-mCol1a1p-mCherry) in NIH/3T3 fibroblasts. The critical steps for recombinant adenovirus packaging, transduction optimization (multiplicity of infection) to minimize cytotoxicity, and the establishment of a robust transforming growth factor beta (TGF-β)-induced fibrosis model are detailed. By circumventing the need for cell fixation, this system enables direct and longitudinal monitoring of collagen transcription in live cells. The model's specificity and reliability are pharmacologically validated using the TGF‑β type I receptor (ALK5) inhibitor SB431542, with fluorescent readouts correlating with endogenous fibrotic markers quantified via reverse transcription quantitative polymerase chain reaction and enzyme-linked immunosorbent assay. Ultimately, this cost-effective platform provides an accessible tool for the high-throughput screening of novel antifibrotic agents, thereby accelerating translational cardiovascular research.

Animals

Dynamic transcriptomic landscape from bulk RNA-seq reveals critical mmu-miR-181a-5p/hif1a and mmu-miR-101a-3p/col1a1 modules for deep second-degree burn wound healing.

Burn injuries constitute a significant global health challenge, with deep partial-thickness burns (deep second-degree) posing particular clinical concerns due to prolonged healing and high scarring risks stemming from reticular dermis damage. Current therapeutic strategies remain largely empirical, reflecting limited understanding of stage-specific regulatory mechanisms. This study systematically investigated the molecular basis of deep partial-thickness burn repair by establishing murine models and performing RNA-seq analysis across healing phases (0, 3, 7, 14 days post-burn, dpb). Integrated bioinformatics revealed pivotal ceRNA and PPI networks, identifying hif1a (hypoxia-responsive immunomodulator) and col1a1 (ECM remodeling hub) as nodal regulators. Mechanistically, mmu-miR-101a-3p and mmu-miR-181a-5p were validated as post-transcriptional repressors of col1a1 and hif1a, respectively. Our work pioneers the discovery of the mmu-miR-181a-5p/hif1a and mmu-miR-101a-3p/col1a1 axes as master regulators of burn repair, offering novel therapeutic targets. The multi-omics dataset and molecular networks established herein provide a foundational resource for wound healing research.

MicroRNAs

Newly identified single-nucleotide polymorphism associated with the transition from nonalcoholic fatty liver disease to liver fibrosis: results from a nested case-control study in the UK biobank.

BACKGROUND: Genetic factors may have a significant influence on the likelihood of liver fibrosis in individuals with nonalcoholic fatty liver disease (NAFLD). The present study was conducted to explore how single-nucleotide polymorphism (SNP) impacts the development of fibrosis in those suffering from NAFLD. MATERIALS AND METHODS: Utilizing the UK Biobank dataset, we conducted a nested case-control analysis among NAFLD participants, defining the case group as those with liver fibrosis and cirrhosis during follow-up. For our in vitro investigations, we employed the LX-2 human hepatic stellate cell line. Our procedures included cultivating these cells, employing SAMM50-rs2073080 plasmid techniques to enhance the expression of recently discovered SNPs, and conducting biochemical assays. To quantify gene expression, we used real-time PCR with fluorescence detection. RESULTS: The study analyzed data from 5467 participants (1094 cases and 4373 controls). Genome-wide association analysis identified nine significant loci, including the novel rs2073080 variant, strongly associated with NAFLD-associated hepatic fibrosis. In vitro TGF-β modeling revealed significant upregulation of α-SMA and COL1A1, confirming model effectiveness. Oxidative stress markers like elevated malondialdehyde (MDA) and reduced catalase (CAT) and superoxide dismutase (SOD) levels indicated liver damage in the TGF-β group. SAMM50-rs2073080 was upregulated in the NAFLD-associated fibrosis model. In vitro experiments on LX-2 cells showed that SAMM50-rs2073080 overexpression led to increased fibrosis, as indicated by higher cellular MDA levels and lower CAT and SOD levels, compared to the vector group. CONCLUSION: Our research highlights a significant association of SAMM50-rs2073080 with the progression of NAFLD to hepatic fibrosis, and the in vitro experiments further corroborated these findings.

Humans

A Novel Splice Variant in the COL1A1 Gene Leads to Exon 46 Skipping and Osteogenesis Imperfecta.

BACKGROUND: Osteogenesis imperfecta (OI) is a clinical and genetic disorder characterised by bone fragility, growth deficiency and skeletal deformity. Ninety per cent of OI cases are attributable to autosomal dominant variants in the COL1A1 and COL1A2 genes. METHODS: Candidate variants were identified and verified through trio whole-exome sequencing (trio-WES), copy number variation sequencing (CNV-seq) and Sanger sequencing. Minigene splicing assays were performed in HeLa and HEK293T cells with pcDNA3.1 and pcMINI-C vectors to investigate the function of the candidate variants. A systematic review of COL1A1 splicing variants and the corresponding genotype-phenotype spectrum was performed. RESULTS: Trio-WES revealed a novel heterozygous variant in the C-terminal region of the COL1A1 gene: NM_000088.4:c.3423+5G>A. Sanger sequencing confirmed the variant in both the proband (II-2) and her foetus (III-1) who were clinically suspected of having OI. The c.3423+5G>A variant causes complete skipping of Exon 46, as demonstrated by a minigene splicing assay. We retrieved 419 COL1A1 splicing variants from PubMed, excluded 15 without phenotypic data and 2 linked to Ehlers-Danlos syndrome and stratified the remaining 402 variants into three types on the basis of splice site location: (1) Variants at canonical splicing sites (77.8%, 313/402) mostly cause mild phenotypes, whereas a minority may be severe. (2) Intron variants in other locations, such as splice region variants (17.9%, 72/402), usually cause mild clinical phenotypes, and deep intronic splice variants (0.4%, 2/402) that may result in severe phenotypes. (3) Other variants (3.7%, 15/402), such as exon variants or fragment loss, are extremely rare. We also preliminarily discuss the mechanisms underlying phenotypic variability and the characteristics of C-terminal variants. CONCLUSIONS: This intron variant in COL1A1 was classified as likely pathogenic and was confirmed to disrupt COL1A1 expression. The summary analysis results also revealed a correlation among splicing variants, C-terminal region variants and disease, suggesting that variant location provides a useful framework for prognosis prediction.

Female

COL4A1 and COL4A2-related disorders: Clinical features, diagnostic guidelines, and management.

PURPOSE: Collagen type 4 alpha 1 (COL4A1) and alpha 2 (COL4A2) chains, encoded by COL4A1 and COL4A2, are essential for basement membrane integrity, contributing to structural stability and cell regulation. Pathogenic variants in these genes cause a spectrum of autosomal dominant and, more rarely, autosomal recessive disorders, which are collectively known as COL4A1/A2-related disorders. These multisystem disorders can include neurologic, ophthalmologic, renal, and other organ system pathology and vary widely in symptoms, complicating diagnosis and management. METHODS: Using a modified eDelphi method, we obtained consensus from international experts across medical subspecialties on the evaluation and management of COL4A1/A2-related disorders, with consensus set at ≥70% agreement. RESULTS: Consensus was achieved on recommendations for evaluating and managing these conditions. CONCLUSION: Genetic testing and counseling are advised for individuals showing symptoms of COL4A1/A2-related disorders and for at-risk relatives. Given the complexity and rarity of these disorders, management requires a multidisciplinary approach informed by current understanding of disease mechanisms. Recommended care includes neurological and ophthalmological imaging and monitoring of cardiovascular and renal function. Ongoing research is critical to uncover genotype-phenotype links and potential modifiers, with clinical research participation encouraged to advance knowledge and treatments.

Humans