Genetics research最新文献

Background: Cardiac conduction disorders (CCDs) represent a broad spectrum of severe cardiovascular conditions associated with syncope and sudden cardiac death. Therefore, identification of reliable biomarkers is necessary to significantly improve the diagnostic accuracy and therapeutic outcomes of CCDs. This study analyzed GWAS summary datasets using a genomic structural equation model (Genomic-SEM), fine mapping, linkage disequilibrium score regression (LDSC), and two-sample Mendelian randomization (TSMR) analyses to identify genetic loci and genes associated with CCDs.

Methods: GWAS summary datasets of European subjects were obtained from the GWAS Catalog and FinnGen databases. The GenomicSEM R package was used to construct a structural equation model to identify common latent factors influencing CCD progression. The Functional Mapping and Annotation of Genome-Wide Association Studies (FUMA) platform was used to annotate the lead SNPs and candidate genes. Fine-mapping tools, such as SuSiE and FINEMAP, and Phenome-Wide Association Study (PheWAS) analysis were used to identify causal SNPs associated with CCDs. Transcriptome-Wide Association Study (TWAS) and Functional Summary Statistics (FOCUS) analyses were performed to identify CCD susceptibility genes. LDSC and TSMR were performed to determine causal relationships between the candidate risk genes and specific CCDs.

Results: Newly explored CCD-associated leading SNPs (rs71208329 and rs112720315) were generated from genomic SEM and FUMA analyses. Fine-mapping and PheWAS analysis confirmed that rs112720315 was linked to nonischemic cardiomyopathy. TWAS, FUMA, and FOCUS analyses showed that five genes (CCDC141, SCN10A, SH3PXD2A, FKBP7, and ESR2) were associated with CCDs. The APOL1 gene is associated with the risk of CCDs in African ancestry. TSMR and LDSC analyses further demonstrated that these genes were significantly associated with CCDs and were potential prediction biomarkers for CCDs.

Conclusion: The novel genetic locus rs112720315 is significantly associated with the occurrence of CCDs. Biomarkers such as CCDC141, SCN10A, ESR2, FKBP7, and SH3PXD2A can predict a wide spectrum of CCDs. The APOL1 gene is a specific marker for CCDs in African ancestry.

Background: Osteoarthritis (OA) is a complex, progressive joint disease characterized by cartilage degradation and inflammation. Traditional bulk tissue analyses have limited our understanding of the cellular diversity within OA tissues.

Methods: This study employed scRNA-seq and integrated bioinformatic analyses to investigate the cellular composition and molecular pathways involved in OA. Publicly available datasets were analyzed to identify differentially expressed genes (DEGs) and enriched pathways. The genes, such as NR4A2, BMP1, and AVPR1A, were selected for further analysis. Molecular docking studies were conducted to explore the interaction with two identified compounds. Additionally, immune infiltration characteristics were analyzed using gene set variation analysis (GSVA) and correlation with key OA-associated genes.

Results: We analyzed cartilage samples from OA and normal individuals (GSE220243) and identified eight distinct chondrocyte subpopulations, with significant pathway enrichment in TNF, TGF-β, and PI3K-Akt signaling pathways. Further differential gene expression analysis of GSE114007 identified 2247 genes, including 26 key OA-associated drug targets, such as NR4A2, BMP1, and AVPR1A, which demonstrated strong diagnostic potential (AUC > 0.70) across multiple cohorts. Immune infiltration analysis revealed significant correlations between these key genes and immune cell subsets, highlighting their roles in the inflammatory microenvironment of OA. Additionally, molecular docking studies suggested that bexarotene has a favorable binding affinity for NR4A2, BMP1, and AVPR1A, making it a promising therapeutic candidate.

Conclusion: Our findings provide new insights into the molecular landscape of OA, offering valuable biomarkers and therapeutic targets for future OA interventions.

Objective: To elucidate different methylation landscapes between cartilage of femoral neck fracture and preserved and damaged cartilages in hip osteoarthritis (OA).

Methods: Genome-wide DNA methylation data were acquired from two data sets in GEO database (GSE63106 and GSE63695), which were based on Illumina HumanMethylation450 BeadChip arrays. A total of 63 hip samples were selected for further analysis, including 19 cartilages obtained from patients with femoral neck fracture, 14 preserved cartilages, and 30 damaged cartilages obtained from patients with OA. We identified the differential methylated positions (DMPs) and genes between different cartilage groups.

Results: There were 116,750 DMPs and 51,200 DMPs identified in preserved and damaged cartilages compared to cartilage in femoral neck fracture, respectively, while there were no signals found between preserved and damaged cartilages. Gene ontology analysis showed that most of differential methylated genes were enriched in extracellular matrix and structure organization, collagen-containing extracellular matrix, and KEGG enrichment highlighted PI3K-AKT and AMPK signaling pathways, which were known to be crucial for the progression of OA. Further construction of protein-protein interaction networks with differential methylated genes elucidated molecular basis of the disease. Three hypermethylated genes (NOTCH1, GREM1, and DYSF) and three hypomethylated genes (HDAC4, S100A10, and RUNX1) were selected to detect the relative expression in different cartilages, and their expression was correlated with the methylation status within the genes.

Conclusion: We demonstrated the differential methylated genes across the whole genome not only on preserved cartilage but also on damaged cartilage during OA. The molecular network highlighted the potential therapy targets which may be involved in the initiation or progression of the disease.

Purpose: The genetic spectrum and early clinical indicators of familial exudative vitreoretinopathy (FEVR) remain incompletely defined, and few studies have investigated the genetic variants and clinical phenotypes associated with eoHM-FEVR and anisometropia-FEVR patients. The purpose of this study was to screen the pathogenic variations in 11 FEVR families and analyze the refractive status and pathogenic genes in patients with irregular dominantly inherited FEVR.

Methods: The patients with clinical diagnoses of eoHM-FEVR or anisometropia-FEVR were evaluated from October 2019 to August 2022. Comprehensive ophthalmic tests were performed on participants to confirm the phenotype. The genotype was identified using whole-exon sequencing and further verified the results among other family members by Sanger sequencing. Normal protein structures were modeled with AlphaFold, whereas mutant variants were analyzed via PyMOL. Variant pathogenicity followed the American College of Medical Genetics and Genomics (ACMG) guidelines. The protein-protein interaction (PPI) network analysis with STRING and k-means clustering was applied for detecting the interaction of genes in the candidate genes, and the ClusPro Server was used for protein-protein docking.

Results: A total of 11 FEVR families were included in the study, and all the probands were found to have high myopia in both eyes or one eye before the age of 7 years. The pathogenic variants were identified in the genes TSPAN12, LRP5, and FZD4 known to be associated with FEVR in six probands. Among 13 eoHM-related genes, FZD4 and LRP2 encode proteins that can dock together as analyzed by ClusPro software.

Conclusion: This study observed dominant inheritance of an irregular pattern in FEVR families, with asymmetric FEVR presenting as severe anisometropia. The eye with higher myopia often had more advanced FEVR and pronounced fundus changes. PPI network analysis revealed important modules of gene interaction, and the FZD4-LRP2 complex protein was potentially related to high myopia development. For patients with high myopia or with obvious anisometropia in both eyes, more attention should be paid clinically to the comprehensive examination of the peripheral fundus and early genetic testing.

Background: Optic nerve injury, as a neurodegenerative disorder, leads to irreversible visual impairment. Although the underlying mechanisms linking physical activity to optic nerve injury remain unclear, this study aimed to establish a causal relationship between physical activity and optic nerve injury using a Mendelian randomization (MR) framework.

Methods: This MR study utilized genome-wide significant variants as instrumental variables (IVs) for assessing the relationship between physical activity and optic nerve injury, focusing on individuals of European descent. The approach was supported by comprehensive sensitivity analyses and augmented by bioinformatics tools including differential gene expression, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses.

Results: Our study demonstrated that after adjustment for MVPA, alcohol intake, BMI, blood glucose, blood lipids, and smoking, LST was positively associated with glaucoma risk (β = 0.016, 95% CI: 0.004 to 0.027, p = 0.014), indicating its role as an independent risk factor. Conversely, MVPA was negatively associated with glaucoma risk (β = -0.012, 95% CI: -0.022 to -0.002, p = 0.026), supporting a protective effect, while smoking also showed a significant association (β = -0.020, 95% CI: -0.039 to -0.002, p = 0.037). Sensitivity analyses confirmed the robustness of these findings, and bioinformatic analyses implicated cholesterol metabolism and fibrosis pathways in optic nerve injury.

Conclusion: These findings underscore the potential of lifestyle modifications, including increased physical activity and reduced sedentary behavior, as a cost-effective strategy to prevent and manage optic nerve injury.

Background: Cockayne syndrome (CS) is a rare, autosomal-recessive, multisystem disorder characterized by microcephaly, failure to thrive, photosensitivity, leukodystrophy, muscle contracture, and intellectual disability. It is caused by deleterious variant in the ERCC6 and ERCC8 genes, which are involved in the transcription-coupled nucleotide excision repair system. According to severity and age of onset, CS is categorized into four types: I, II, III, and cerebrooculofacioskeletal syndrome (COFS). However, some researchers consider COFS to be a distinct disease from CS, while others describe COFS as a severe form of CS.

Methods: Whole-exome sequencing (WES) and Sanger sequencing were used to identify potential pathogenic causative variant.

Results: WES data analysis revealed a nonsense variant (NM_000124: c.3862C>T, p.R1288X) in the ERCC6 gene, which was co-segregated using Sanger sequencing. Although this variant has been reported previously in association with both CS and COFS separately, this study's patient manifested intermediate symptoms.

Conclusion: This study's findings expand the clinical spectrum of the variant (NM_000124: c.3862C>T, p.R1288X) and provide more supporting evidence that CS and COFS are phenotypic spectrums rather than different clinical conditions in which genetic and epigenetic factors probably play a pivotal role in the severity of symptoms.

Objective: To develop a prognostic nomogram for Wilms' tumor (WT) integrating genetic and clinical factors to improve evaluation accuracy and clinical utility.

Methods: RNA sequencing (RNA-seq) data from 125 WT patients and single-cell RNA (scRNA-seq) data from 2437 samples were analyzed using bioinformatics tools for data processing, including normalization and scaling with SCTransform, and cell clustering with Seurat. Principal component analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP) were utilized for data visualization. Differential gene expression analysis identified pivotal genes for the Genetic Feature Prognostic Model for WT (GPM-WT). Univariate Cox regression analysis refined this model by incorporating clinical prognostic indicators. Survival analysis, Cox regression, and ROC curve assessments evaluated these models' prognostic capabilities. Immune cell infiltration and drug sensitivity were quantified, linking these to patient risk categories.

Results: Six prognostic lymphocyte genes (KLRC1, APOC2, GBP2, SLA, MLLT3, and SIGLEC5) were identified for GPM-WT. Clinical factors, age and sex, were integrated to refine the model. The Lymphocyte Gene and Clinical Features Prognostic Nomogram (LGCPN-WT) effectively distinguished high from low-risk groups, predicting 2-5-year survival rates with area under the curve (AUC) values of 0.771, 0.774, 0.751, and 0.785. Elevated immune cell infiltration and enhanced drug sensitivity characterized the high-risk group, exhibiting significant responsiveness to chemotherapy, targeted, and immunotherapy treatments (p < 0.05).

Conclusions: The study developed an integrated LGCPN-WT model, significantly enhancing survival prediction accuracy and clinical utility for WT, thus supporting personalized treatment approaches.

Autism spectrum disorders (ASDs) are a group of neurodevelopmental disorders with high heritability. Nevertheless, the involvement of genetic variants in ASDs is not fully understood. One gene of interest is TRIO, which encodes a large protein that aids in GDP-to-GTP exchange as a Ras homologous (Rho) guanine nucleotide exchange factor (GEF), facilitating cytoskeleton reorganization. Thus, it plays crucial roles in neuronal migration, neurite outgrowth, and synaptic transmission. De novo mutations in TRIO have been extensively reported in the pathogenesis of ASDs. However, no evidence currently supports the genetic association between common variants in TRIO and ASDs. To investigate the role of common genetic variations in autism risk, we analyzed 12 tagging single-nucleotide polymorphisms (SNPs) in the TRIO gene. These tagging SNPs captured an average of 75% of all common variations in TRIO with a minor allele frequency (MAF) > 5%. Using the family-based association study in 239 Chinese Han autism trios, we identified the significant association of three SNPs (rs32593, rs33005, and rs27479) with autism. To confirm the association, the sample size was expanded to 427 trios by recruiting 188 additional trios. Our findings across all 427 trios confirmed that A allele of rs32593, G allele of rs33005, and C allele of rs27479 showed a preferential transmission to the affected offspring (rs32593: A > G, Z = 2.600, p = 0.0093; rs33005: G > T, Z = 2.978, p = 0.0029; rs27479: C > A, Z = 3.214, p = 0.0013) after Bonferroni's correction (p < 0.0042). Haplotype analyses showed that one haplotype (A-G) constructed from rs32593 and rs33005 was significantly associated with autism (p = 0.0064; Global p = 0.022). These results suggested that the common variants in TRIO might be involved in the susceptibility to autism in the Chinese Han population.

Background: Previous studies on the causal relationship or shared genetic basis between major depression disorder (MDD) and gastrointestinal (GI) diseases covered either a limited range and not comprehensive enough.

Methods: We used linkage disequilibrium score regression (LDSC) to estimate the heritability for nine traits and the genetic correlation (r _g ) between MDD and eight GI diseases, respectively. We further conducted a two-sample Mendelian randomization (MR) analysis to identify the causal relationship between MDD and eight GI diseases. Finally, based on the result of MR, we performed stratified LDSC (S-LDSC) to estimate the partitioned heritability and significantly enriched tissues, transcriptome-wide association study (TWAS) to define shared genes, and colocalization analysis to define the pleiotropic single-nucleotide polymorphisms (SNPs) and genes.

Results: For the heritability, heritability of all nine traits was significant. For genetic correlation, six GI diseases showed significant correlations with MDD. For the result of MR, we revealed the causal relationship between MDD and acute appendicitis (OR = 1.09), irritable bowel syndrome (IBS) (OR = 1.14), and ulcer of esophagus (OR = 1.24). Additionally, we found no significant overlapping tissues after S-LDSC. Finally, we defined three shared genes: PRSS16, ZNF602P, and ZNF204P by TWAS and nine pleiotropic genes C4A, FLOT1, LINC00243, MICB, and PRSS16 by colocalization analysis between MDD and acute appendicitis.

Conclusions: Our findings provided the evidence of genetic association, causal relationship, and shared pleiotropic genes between MDD and GI diseases especially acute appendicitis, offering new insights into our understanding of their shared genetic basis.

This case study examines a preterm newborn with autosomal recessive ABCC8 gene-related diffuse congenital hyperinsulinism (CHI). The interdisciplinary management of the patient, including advanced genetic testing and long-read sequencing, finally led to the molecular diagnosis. These findings were relevant for the immediate decision on further treatment options highlighting the importance of differentiating between focal and diffuse CHI forms, and for providing the family with counseling on the recurrence risks and prenatal diagnostic options. In summary, this study illustrates the clinical and genetic intricacies of CHI, emphasizing the significance of comprehensive genetic analysis in diagnostics and tailored treatment. The case advocates for the integration of state-of-the-art genetic diagnostic technologies in combination with clinical interdisciplinary management to improve patient outcomes.