SEARCH · Search PubMed

Results for “Copy number variation”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6Linked to original sources

PubMed2025

Unraveling cellular dynamic changes in tumor evolution induced by long-term low dose-rate radiation.

BACKGROUND: In recent years, there has been a steady increase in professionals engaged in radioactive work. The biological impacts of long-term exposure to low dose-rate radiation remain elusive, as there is a dearth of systematic research in this field. METHODS: BEAS-2B cells were used to establish a cell model with continuous passaging after radiation exposure, which was subsequently subjected to in vivo tumorigenesis assays and in vitro malignant phenotype experiments. By scRNA-seq, we conducted copy number variation analysis, cell trajectory analysis, and cell communication analysis. Furthermore, we used FACS, molecular docking, multiplex immunohistochemistry, qRT-PCR, and co-immunoprecipitation to validate and further explore the molecular mechanisms driving tumor evolution. RESULTS: Long-term low dose-rate exposure is associated with a higher degree of malignancy, as evidenced by the induction of more CNV and EMT events, as well as the delayed activation of DNA repair pathways, which trigger increased genomic instability. The long-term low dose-rate specific ligand-receptor pair, ANGPTL4-SDC4, enhances cell malignancy by promoting angiogenesis in newly formed lung tumor cells. CONCLUSIONS: This study not only provides the first evidence and mechanistic explanation that long-term low dose-rate radiation leads to increased cellular malignancy but also offers valuable theoretical insights into the dynamic processes of early tumor evolution in lung cancer within the realm of tumor biology.

Humans↗

PubMed2026

Identification of novel HUWE1 variants in Turner-type X-linked intellectual disability.

OBJECTIVE: To characterize the clinical phenotypes and identify the genetic etiology in four unrelated families affected by Turner-type X-linked intellectual disability (XLID). METHODS: Peripheral blood samples were collected from four probands and their parents. Genomic DNA was extracted, and a comprehensive genetic analysis was performed using trio-based Whole Exome Sequencing (WES) combined with low-pass Copy Number Variation sequencing (CNV-seq). Candidate variants were subsequently validated via Sanger sequencing. RESULTS: Genetic analysis identified distinct variants in the HUWE1 across the four families. Specifically, four distinct HUWE1 variants were identified across the families: a hemizygous c.10034 > T (p.Lys3345Met) in Family 1; a heterozygous c.9209G > A (p.Arg3070His) in Family 2; a heterozygous c.12688T > C (p.Phe4230Leu) in Family 3; and a hemizygous c.9070G > A (p.Ala3024Thr) in Family 4. In accordance with ACMG guidelines, the novel variants in Families 1, 3, and 4 were classified as "Likely Pathogenic" (PS2 + PM2_Supporting + PP2 + PP3). In contrast, the previously reported variant in Family 2 was categorized as "Pathogenic" based on the criteria PS2 + PM2_Supporting + PM5 + PP2 + PP3_Moderate. All probands were clinically diagnosed with Turner-type XLID. CONCLUSIONS: This study expands the pathogenic variant spectrum of HUWE1 and provides novel molecular evidence for the clinical diagnosis of Turner-type XLID. These findings are of significant value for genetic counseling, carrier screening, and prenatal diagnosis for the affected families.

Humans↗

PubMed2020

Genomic Analysis of Circulating Tumor Cells at the Single-Cell Level.

Circulating tumor cells (CTCs) have a great potential for noninvasive diagnosis and real-time monitoring of cancer. A comprehensive evaluation of four whole genome amplification (WGA)/next-generation sequencing workflows for genomic analysis of single CTCs, including PCR-based (GenomePlex and Ampli1), multiple displacement amplification (Repli-g), and hybrid PCR- and multiple displacement amplification-based [multiple annealing and loop-based amplification cycling (MALBAC)] is reported herein. To demonstrate clinical utilities, copy number variations (CNVs) in single CTCs isolated from four patients with squamous non-small-cell lung cancer were profiled. Results indicate that MALBAC and Repli-g WGA have significantly broader genomic coverage compared with GenomePlex and Ampli1. Furthermore, MALBAC coupled with low-pass whole genome sequencing has better coverage breadth, uniformity, and reproducibility and is superior to Repli-g for genome-wide CNV profiling and detecting focal oncogenic amplifications. For mutation analysis, none of the WGA methods were found to achieve sufficient sensitivity and specificity by whole exome sequencing. Finally, profiling of single CTCs from patients with non-small-cell lung cancer revealed potentially clinically relevant CNVs. In conclusion, MALBAC WGA coupled with low-pass whole genome sequencing is a robust workflow for genome-wide CNV profiling at single-cell level and has great potential to be applied in clinical investigations. Nevertheless, data suggest that none of the evaluated single-cell sequencing workflows can reach sufficient sensitivity or specificity for mutation detection required for clinical applications.

Carcinoma, Non-Small-Cell Lung↗

PubMed2024

Whole exome sequencing analysis of 167 men with primary infertility.

BACKGROUND: Spermatogenic failure is one of the leading causes of male infertility and its genetic etiology has not yet been fully understood. METHODS: The study screened a cohort of patients (n = 167) with primary male infertility in contrast to 210 normally fertile men using whole exome sequencing (WES). The expression analysis of the candidate genes based on public single cell sequencing data was performed using the R language Seurat package. RESULTS: No pathogenic copy number variations (CNVs) related to male infertility were identified using the the GATK-gCNV tool. Accordingly, variants of 17 known causative (five X-linked and twelve autosomal) genes, including ACTRT1, ADAD2, AR, BCORL1, CFAP47, CFAP54, DNAH17, DNAH6, DNAH7, DNAH8, DNAH9, FSIP2, MSH4, SLC9C1, TDRD9, TTC21A, and WNK3, were identified in 23 patients. Variants of 12 candidate (seven X-linked and five autosomal) genes were identified, among which CHTF18, DDB1, DNAH12, FANCB, GALNT3, OPHN1, SCML2, UPF3A, and ZMYM3 had altered fertility and semen characteristics in previously described knockout mouse models, whereas MAGEC1,RBMXL3, and ZNF185 were recurrently detected in patients with male factor infertility. The human testis single cell-sequencing database reveals that CHTF18, DDB1 and MAGEC1 are preferentially expressed in spermatogonial stem cells. DNAH12 and GALNT3 are found primarily in spermatocytes and early spermatids. UPF3A is present at a high level throughout spermatogenesis except in elongating spermatids. The testicular expression profiles of these candidate genes underlie their potential roles in spermatogenesis and the pathogenesis of male infertility. CONCLUSION: WES is an effective tool in the genetic diagnosis of primary male infertility. Our findings provide useful information on precise treatment, genetic counseling, and birth defect prevention for male factor infertility.

Humans↗

PubMed2025

Anticancer drug response prediction integrating multi-omics pathway-based difference features and multiple deep learning techniques.

Individualized prediction of cancer drug sensitivity is of vital importance in precision medicine. While numerous predictive methodologies for cancer drug response have been proposed, the precise prediction of an individual patient's response to drug and a thorough understanding of differences in drug responses among individuals continue to pose significant challenges. This study introduced a deep learning model PASO, which integrated transformer encoder, multi-scale convolutional networks and attention mechanisms to predict the sensitivity of cell lines to anticancer drugs, based on the omics data of cell lines and the SMILES representations of drug molecules. First, we use statistical methods to compute the differences in gene expression, gene mutation, and gene copy number variations between within and outside biological pathways, and utilized these pathway difference values as cell line features, combined with the drugs' SMILES chemical structure information as inputs to the model. Then the model integrates various deep learning technologies multi-scale convolutional networks and transformer encoder to extract the properties of drug molecules from different perspectives, while an attention network is devoted to learning complex interactions between the omics features of cell lines and the aforementioned properties of drug molecules. Finally, a multilayer perceptron (MLP) outputs the final predictions of drug response. Our model exhibits higher accuracy in predicting the sensitivity to anticancer drugs comparing with other methods proposed recently. It is found that PARP inhibitors, and Topoisomerase I inhibitors were particularly sensitive to SCLC when analyzing the drug response predictions for lung cancer cell lines. Additionally, the model is capable of highlighting biological pathways related to cancer and accurately capturing critical parts of the drug's chemical structure. We also validated the model's clinical utility using clinical data from The Cancer Genome Atlas. In summary, the PASO model suggests potential as a robust support in individualized cancer treatment. Our methods are implemented in Python and are freely available from GitHub (https://github.com/queryang/PASO).

Deep Learning↗

PubMed2026

Urinary Small Extracellular Vesicle DNA as a Biomarker for the Non-Invasive Diagnosis of Bladder Cancer.

Existing diagnostic technologies for bladder cancer (BC) suffer from low sensitivity, low specificity, or a lack of validation. Therefore, validated, non-invasive diagnostic biomarkers with high sensitivity and specificity for early detection of BC are needed to complement and improve upon the limitations of existing diagnostic methods. We used low-pass whole genome sequencing (LP-WGS) technology to detect copy number variations (CNVs) in small extracellular vesicle (sEV) DNA isolated from urine samples of patients. Based on these results, we constructed and validated a diagnostic model to differentiate between benign and malignant bladder lesions. We conducted a receiver operating characteristic analysis and calculated the area under the curve (AUC) to evaluate the performance of the diagnostic model. The urine sEV-DNA LP-WGS data revealed CNV differences between benign and malignant samples. The diagnostic model achieved an AUC of 0.953, a sensitivity of 86.7%, and a specificity of 100% in the training cohort and an AUC of 0.985, a sensitivity of 90%, and a specificity of 100% in the validation cohort. Even at the lowest coverage depth of 0.01X, the performance of the diagnostic model remained relatively robust. Notably, the performance of this diagnostic model surpassed that of the biomarker neuron-specific enolase (sensitivity: 85.7% vs. 64.3%; specificity: 100% vs. 87.5%) and urinary cytology (sensitivity: 100% vs. 66.7%; specificity: 100% vs. 94.1%). Our study demonstrates that urine sEV-DNA exhibits high discriminatory power in distinguishing between benign and malignant bladder lesions, making it a promising tool for auxiliary diagnosis of BC.

Humans↗

PubMed2026

A cfDNA fragmentomics classifier for noninvasive differentiation of benign and malignant renal masses.

Noninvasive differentiation of malignant and benign renal masses remains a major clinical challenge, particularly for radiologically indeterminate lesions. Here, we developed and validated a plasma cell-free DNA (cfDNA) fragmentomics-based machine learning classifier for renal mass characterization. The model was trained on 331 participants (171 cancer, 160 benign) and independently validated on 144 participants (73 cancer, 71 benign). Three cfDNA fragmentation features, including copy number variation (CNV), fragmentation-based methylation (FRAGMA), and nucleosome footprint (NF), derived from low-pass whole-genome sequencing, were integrated into an ensemble framework. The model achieved strong discriminative performance, with area under the curve (AUC) values of 0.956 in the training cohort and 0.946 in the validation cohort, outperforming individual feature-based models. At a predefined operating threshold corresponding to 90% sensitivity, specificity reached 0.90 and 0.87, respectively. Notably, most cancer samples exhibited low tumor fraction (TF < 3%), yet the model maintained robust performance in low-TF samples (AUCs: 0.952 and 0.941, respectively). Performance remained consistent across tumor stage, grade, and histological subtypes. The classifier also demonstrated potential clinical utility in diagnostically challenging settings, including lipid-poor angiomyolipoma and oncocytoma, with 12 of 13 oncocytoma samples correctly classified in an independent cohort. In addition, the model correctly identified 85.3% of benign masses > 4 cm, for which surgical intervention is more commonly considered, and 84.6% of malignant tumors ≤ 4 cm, for which management can be challenging. Collectively, these findings support cfDNA fragmentomics as a promising noninvasive liquid biopsy approach for renal mass evaluation and clinical decision-making.

Humans↗

PubMed2025

The MTORC1 signaling pathway related gene POLR3G serves as a potential prognostic biomarker in Hepatocellular Carcinoma.

This study aims to investigate the prognostic significance and potential biological functions of the MTORC1 signaling pathway-associated gene POLR3G in Hepatocellular carcinoma (HCC). A prognostic risk model for HCC was developed by integrating HCC-related datasets and associated clinical data obtained from The Cancer Genome Atlas (TCGA) database. The GSVA website was employed to analyze the model genes across pan-cancer datasets, focusing on copy number variations (CNV), single nucleotide variations (SNV), methylation differences, drug sensitivity and immune cell infiltration profiles. Subsequently, we examined the expression levels and prognostic significance of POLR3G in HCC. Utilizing Spearman correlation analysis, we identified genes associated with POLR3G. Furthermore, Gene Set Enrichment Analysis (GSEA) was employed to elucidate the potential signaling pathways in which POLR3G may be involved. The relationship between POLR3G expression and immune cell abundance in HCC samples was assessed using the ssGSEA algorithm. Finally, the impact of POLR3G on HCC cell proliferation was validated through CCK-8 and EDU cell proliferation assays. Through univariate Cox regression analysis and LASSO regression analysis, we established a prognostic risk model for HCC comprising 13 genes. The analysis revealed that individuals categorized in the low-risk group had a markedly improved overall survival probability relative to those in the high-risk group. POLR3G exhibited a markedly elevated expression in HCC tissues when compared to adjacent normal tissues. The expression of POLR3G was correlated with tumor grade, and elevated POLR3G expression was associated with poor prognosis in HCC patients. Furthermore, the expression level of POLR3G was found to be correlated with the level of immune cell infiltration. Knockdown of POLR3G significantly inhibited the proliferative capacity of hepatocellular carcinoma cells. The findings suggest that POLR3G may serve as a potential biomarker influencing the prognosis of hepatocellular carcinoma patients by modulating the tumor immune microenvironment.

Humans↗

PubMed2025

Comprehensive chromosomal abnormality detection: integrating CNV-Seq with traditional karyotyping in prenatal diagnostics.

BACKGROUND: This study aimed to evaluate the efficacy of copy number variation sequencing (CNV-Seq) in detecting chromosomal abnormalities in prenatal diagnosis, comparing its performance with traditional karyotype analysis. METHODS: A retrospective analysis was conducted on 1001 prenatal samples collected between April 2021 and December 2023. Samples were analyzed using both CNV-Seq and karyotype analysis. The detection rates of chromosomal abnormalities were compared between the two methods across various prenatal diagnostic indications. Clinical follow-up was performed to assess pregnancy outcomes. RESULTS: CNV-Seq detected chromosomal abnormalities in 89 of 1,001 cases (8.9%), compared to 50 cases (5.0%) identified by traditional karyotyping. CNV-Seq not only detected all abnormalities identified by karyotyping, including common aneuploidies such as trisomy 21 and sex chromosome abnormalities, but also uncovered 53 additional pathogenic submicroscopic CNVs associated with 33 known syndromes. The detection rates of CNV-Seq were significantly higher in high-risk groups, such as those identified by non-invasive prenatal testing (HR-NIPT) and maternal serum screening (HR-MSS), demonstrating superior sensitivity and accuracy in prenatal diagnostics. CONCLUSION: CNV-Seq demonstrated superior sensitivity in detecting chromosomal abnormalities, particularly submicroscopic alterations, compared to traditional karyotyping. The study highlights the potential of CNV-Seq as a valuable tool in prenatal diagnostics, offering improved detection of genetic abnormalities and guiding clinical decision-making. However, a combined approach using both CNV-Seq and karyotype analysis is recommended for comprehensive prenatal genetic screening.

Humans↗

PubMed2025

Identification of maternal Gγ(Aγδβ)0 thalassemia through retrospective reanalysis of prenatal cfDNA sequencing data.

OBJECTIVE: Non-invasive prenatal screening (NIPS) is widely used to detect chromosomal abnormalities such as trisomies 21, 13, and 18 and is also effective in screening for copy number variations (CNVs). However, the routine application of NIPS to detect smaller CNVs within the HBB gene, specifically Gγ(Aγδβ)0 thalassemia, has yet to be well documented. This study aims to evaluate the efficacy of cfDNA-based maternal carrier screening in routine screening for Gγ(Aγδβ)0 thalassemia. METHODS: We performed a retrospective analysis of 107,300 pregnant women who underwent NIPS at Longgang Maternal and Child Healthcare Hospital in Shenzhen from December 2017 to May 2022. Using an improved algorithm, we reanalyzed NIPS data to identify maternal Gγ(Aγδβ)0 thalassemia. Positive cases were confirmed by multiplex ligation-dependent probe amplification (MLPA) using peripheral blood leukocytes. RESULTS: Among the 107,300 NIPS analyses, 38 maternal deletion CNVs within the HBB gene were identified using the improved algorithm, with a prevalence of 0.035% (38/107,300). MLPA confirmed that all detected deletions were consistent with Gγ(Aγδβ)0 thalassemia. The positive predictive value (PPV) for detecting Gγ(Aγδβ)0 thalassemia by cfDNA-based maternal carrier screening was 100%. Among the 38 Gγ(Aγδβ)0 cases, 9 were also associated with α-thalassemia deletions, including 4 cases with -SEA/αα, 4 with -α3.7/αα, and 1 with -α4.2/αα. No cases of homozygosity or compound HBB gene variants were observed. CONCLUSIONS: Gγ(Aγδβ)0 thalassemia is not uncommon in China, and repurposed NIPS methodology for maternal genomic analysis in detecting HBB gene deletions is a reliable method for identifying maternal carriers of this disease.

Humans↗

PubMed2025

Genetic insight into lung neuroendocrine tumors: Notch and Wnt signaling pathways as potential targets.

BACKGROUND: The molecular landscape of lung neuroendocrine neoplasms is still poorly characterized, making it difficult to develop a molecular classification and personalized therapeutic approaches. Significant clinical heterogeneity of these malignancies has been highlighted among poorly differentiated histotypes and within the subgroup of well-differentiated neuroendocrine tumors (NET). Currently, the main prognostic factors of lung NET include stage, histotype, grade, peripheral location, and demographic parameters. To gain deeper insights into the genomic underpinnings of lung NETs, we conducted a pilot investigation to uncover potential genetic mutations and copy number variations (CNVs) implicated in their pathogenesis. METHODS: Formalin-fixed, paraffin-embedded intraoperative tumor biopsies and matched peripheral blood mononuclear cell samples were collected from six consecutive patients with lung NETs. The whole exome sequencing (WES) was performed to profile germline and somatic mutations, identify novel genetic alterations, and detect CNVs. Clinical and pathological data were systematically documented at diagnosis and during follow-up. RESULTS: The WES analysis identified a subset of mutations shared between germline and somatic; some were of particular clinical interest as they were associated with tumor proliferation and potential therapeutic targets such as the genes KDM5C, ATR, COL7A1, NOTCH4, PTPRS, SMO, SPEN, SPTA1, TAF1. These mutations were predominantly linked to chromatin remodeling and were involved in critical oncogenic pathways such as Notch and Wnt signaling. CONCLUSIONS: This pilot study highlights the potential role of NGS analysis on solid biopsy in the assessment of the mutational profile of lung NET. A comparison of germline and somatic mutations is critical to identifying putative tumor driver mutations. In perspective, the enrichment of a subpopulation of cancer cells in the blood, with one or more specific mutations, is information of enormous clinical relevance, either for prognosis or therapeutic decisions. Translational studies on large prospective series are required to establish the role of liquid biopsy in lung NET.

Humans↗

PubMed2025

Mapping Cerebellar Morphology in 15q11.2 CNV Carriers Using Normative Modeling.

Copy number variations (CNVs) at the 15q11.2 locus of the human genome have been associated with altered brain structure and increased risk for neurodevelopmental and neuropsychiatric disorders. The cerebellum is increasingly seen as a crucial brain region for neurodevelopmental conditions, yet the effects of 15q11.2 CNVs on cerebellar morphology remain largely unclear. Importantly, 15q11.2 CNVs shows reduced or incomplete penetrance (meaning that not all CNV carriers are affected) and variable expressivity (meaning that symptoms may differ between individuals with the same genetic alteration). Thus, there is a need to not only assess group differences, but also to quantify anatomical variability at the individual level. Here, we address these issues using normative models of brain anatomy trained on large datasets (n > 52k, age range: 3-85) to assess both group and individual-level deviations in cerebellar anatomy in carriers of 15q11.2 deletions (n = 120, mean [SD] age= 64.95 [7.58]) and duplications (n = 149, mean [SD] age=64.31 [7.21]), compared to non-carriers (n = 19,028, mean [SD] age=64.31 [7.58]). Group-level case-control analyses revealed significantly smaller total and regional cerebellar volumes in both deletion and duplication carriers, though with small effect sizes. Individual-level deviation analyses, capturing pronounced alterations in specific individuals, revealed a heterogeneous pattern among carriers. Overall, our findings suggest that CNVs at the 15q11.2 locus exert modest and highly individualized effects on cerebellar morphology.

15q11.2↗

PubMed2025

Novel genetic determinants contribute to hearing loss in a central European cohort with enlarged vestibular aqueduct.

BACKGROUND: The enlarged vestibular aqueduct (EVA) is the most commonly detected inner ear malformation. Biallelic pathogenic variants in the SLC26A4 gene, coding for the anion exchanger pendrin, are frequently involved in determining Pendred syndrome and nonsyndromic autosomal recessive hearing loss DFNB4 in EVA patients. In Caucasian cohorts, the genetic determinants of EVA remain unknown in approximately 50% of cases. We have recruited a cohort of 32 Austrian patients with hearing loss and EVA to define the prevalence and type of pathogenic sequence alterations in SLC26A4 and discover novel EVA-associated genes. METHODS: Sanger sequencing, single nucleotide polymorphism (SNP) assays, copy number variation (CNV) testing, and Exome Sequencing (ES) were employed for gene analysis. Cell-based functional and molecular assays were used to discriminate between gene variants with and without impact on protein function. RESULTS: SLC26A4 biallelic variants were detected in 5/32 patients (16%) and monoallelic variants in 5/32 patients (16%). The pathogenicity of the uncharacterized SLC26A4 protein variants was assigned or excluded based on their ion transport function and cellular abundance. The monoallelic or biallelic Caucasian EVA haplotype was detected in 7/32 (22%) patients, but its pathogenicity could not be confirmed. X-linked pathogenic variants in POU3F4 (2/32, 6%) and biallelic pathogenic variants in GJB2 (2/32, 6%) were also found. No CNV of SLC26A4 and STRC genes was detected. ES of eleven undiagnosed patients with bilateral EVA detected rare sequence variants in six EVA-unrelated genes (monoallelic variants in SCD5, REST, EDNRB, TJP2, TMC1, and two variants in CDH23) in five patients (5/11, 45%). Cell-based assays showed that the TJP2 variant leads to a mislocalized protein product forming dimers with the wild-type, supporting autosomal dominant pathogenicity. The genetic causes of hearing loss and EVA remained unidentified in (14/32) 44% of patients. CONCLUSIONS: The present investigation confirms the role of SLC26A4 in determining hearing loss with EVA, identifies novel genes in this pathophysiological context, highlights the importance of functional testing to exclude or assign pathogenicity of a given gene variant, proposes a possible diagnostic workflow, suggests a novel pathomechanism of disease for TJP2, and highlights voids of knowledge that deserve further investigation.

Humans↗

PubMed2026

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↗

PubMed2026

Methylome Profiling of Cartilage Tumors: A Promising New Diagnostic Tool?

DNA methylation and copy number variation (CNV) profiling has emerged as a promising tool for the classification of bone and soft tissue tumors. We evaluated its utility in cartilage tumors, where distinguishing low-grade from high-grade conventional central chondrosarcomas (CSs) and atypical cartilaginous tumors (ACTs) from enchondromas (ECs) is a frequent diagnostic challenge, particularly on biopsy material. We analyzed 214 chondrogenic tumors, including ECs, ACTs, conventional CSs, dedifferentiated chondrosarcomas (DDCSs), and clear cell CSs, and determined their IDH1/2 mutation status. Unsupervised dimensionality reduction of genome-wide DNA methylation patterns revealed 4 clusters among IDH-mutant (MUT) tumors (IDH-MUT-1: mostly ECs and ACTs and some high-grade CSs; IDH-MUT-2: predominantly high-grade CSs; IDH-MUT-3: largely DDCSs; and IDH-MUT-SB: distinct skull base group with a markedly different methylation pattern) and 2 clusters among IDH-wild-type (WT) tumors (IDH-WT-1 and IDH-WT-2: both primarily high-grade CSs, with IDH-WT-2 showing higher tumor grade and more extensive CNVs). Clear cell CSs formed a separate cluster. The amount of CNVs, including loss of CDKN2A, increased with tumor grade, reflecting increased genomic instability during chondrosarcoma progression. Supervised classifiers trained separately, both on methylation and CNV data, and distinguished low-grade and high-grade cartilaginous tumors with area under the curve values of 0.87 to 0.97 and 85% to 90% accuracy. Furthermore, we tested whether DDCSs can be distinguished from metastatic carcinomas and other high-grade sarcomas of the bone. Across 246 reference samples, a supervised classifier achieved 97.2% accuracy (area under the curve, 99.8%) and correctly identified 30 of 32 DDCSs (93.8%). These results indicate that DNA methylation and CNV data analysis provide a valuable tool for distinguishing most low- and high-grade CSs, with additional utility also in differentiating DDCS from morphologic mimics.

cartilaginous tumors↗

PubMed2026

Age-associated epigenomic heterogeneity in papillary tumors of the pineal region: a multicenter YoungNOA investigation.

BACKGROUND: Papillary tumors of the pineal region (PTPR) are rare CNS neoplasms with adult and pediatric presentations, but whether age defines distinct molecular biology is unclear. METHODS: We assembled a multicenter retrospective cohort of 86 histologically confirmed PTPR with genome-wide DNA methylation data, comprising 62 adult and 24 pediatric tumors. Molecular subgroup, array platform, sex, and tumor purity were incorporated into multivariable models. Analyses included DNA methylation class assignment, differential methylation, copy-number variation (CNV), epigenetic mitotic-clock scores, methylation-based tumor microenvironment deconvolution, and descriptive survival evaluation. RESULTS: Adult and pediatric tumors mapped within the established PTPR-A and PTPR-B methylation framework rather than forming age-defined methylation classes. Pediatric tumors were enriched for PTPR-B (22 of 24 tumors [91.7%]) compared with adult tumors (39 of 62 [62.9%]). After adjustment for methylation-based subgroup as well as technical and biological covariates, 2,923 CpG probes were associated with age at a false discovery rate (FDR) threshold below 0.05, and 530 also met the prespecified effect-size threshold. Global methylation summaries were similar between age groups. CNV patterns were dominated by molecular subgroup; adjusted genomic CNV load was not independently associated with pediatric age. In contrast, epiTOC2 intrinsic rate score and the methylation signature represented by the first principal component (PC1) showed age-associated effects independent of molecular subgroup. Methylation-based deconvolution suggested a limited microenvironmental signal, with neutrophil fraction showing the most consistent adjusted association. CONCLUSIONS: Adult and pediatric PTPR share the established PTPR-A/PTPR-B framework. Pediatric tumors, particularly within PTPR-B, showed age-associated DNA methylation differences and higher epigenetic mitotic-clock (epiTOC2) scores in this retrospective cohort. These tissue-level associations do not establish clinical risk or treatment implications and require prospective clinical annotation and orthogonal validation.

Humans↗

PubMed2026

Exploring precision risk in pediatric vesicoureteral reflux: Innate immune gene variations and reflux outcomes in the RIVUR cohort.

INTRODUCTION: Children with vesicoureteral reflux (VUR) are at increased risk for morbidity from recurrent urinary tract infections (UTIs), yet the factors influencing spontaneous VUR resolution remain poorly defined. This study evaluates whether genetic variations in key urinary innate immune effectors (DEFA1A3, DMBT1, and RNASE7) influences VUR resolution and interacts with prophylaxis to alter clinical response. METHODS: We conducted a secondary analysis of 303 RIVUR participants with available DEFA1A3 and DMBT1 copy number variation (CNV) data and RNASE7 rs1263872 genotype. Primary outcomes were (1) VUR improvement (decrease in grade) and (2) VUR resolution at study exit. Multivariable logistic regression models included genotype, treatment, and their interactions, adjusting for age, sex, baseline grade (high vs low), laterality, bowel/bladder dysfunction, and any UTI. Internal validation used 2000-sample bootstrap with bias-corrected and accelerated confidence intervals and influence diagnostics. RESULTS: Clinical covariates did not significantly predict VUR improvement. Children with DEFA1A3 CNV >5 had higher odds of improvement (OR 2.36, 95% CI 1.12-4.96, p = 0.023), an effect that remained significant in bootstrap analyses. High-grade VUR was associated with lower odds of resolution (OR 0.34, 95% CI 0.12-0.94, p = 0.038). A significant interaction was observed between prophylaxis and high DMBT1 copy number for VUR resolution (interaction OR 2.99, 95% CI 1.11-8.04, p = 0.031); no interaction was seen for improvement. RNASE7 rs1263872 was not associated with either outcome. CONCLUSION: Innate immune gene variation may contribute to heterogeneity in VUR outcomes. High DEFA1A3 copy number was associated with reflux improvement and a DMBT1-prophylaxis interaction was associated with reflux resolution. The results of this study is hypothesis-generating and prompt further evaluation to assess whether a subset of children may experience structural benefit from prophylaxis or have a more favorable natural history based on their innate immune genotype.

Humans↗

PubMed1995

Selective DNA amplification regulates transcript levels in plant mitochondria.

Most plant mitochondrial genomes exist as subgenomic-size fragments apparently due to recombination between repetitive sequences. This leads to the possibility that independently replicating subgenomic domains could result in mitochondrial gene copy number variation. We show, through Southern-blot analysis of both restricted and intact mtDNA, that there are gene-specific copy number differences in the monocot Zea mays. Comparison of two different maize genotypes, B37(N) and B37(T), a cytoplasmic male-sterile strain, reveal fewer gene copy number differences for B37(T) than for B37(N). In contrast to maize, significant gene copy number differences are not detected in the dicot Brassica hirta. We also demonstrate that mitochondrial transcriptional rates in both species are apparently dependent on gene copy number since relative rates determined by run-on analysis are proportional to relative gene copy numbers. Thus a direct relationship exists between plant mitochondrial gene copy number and transcriptional rate.

Blotting, Southern↗