Human Genomics最新文献

Background: Chronic obstructive pulmonary disease (COPD) is a complex disorder driven by both genetic susceptibility and environmental exposures. Endocrine-disrupting chemicals (EDCs) are widespread environmental contaminants that interfere with hormonal and immune pathways, yet their molecular links to COPD remain insufficiently defined.

Methods: We integrated exposomic and genomic data to systematically evaluate EDC-related molecular mechanisms in COPD. Chemical-gene interactions were curated from the TEDX and CTD to identify EDC-associated genes. Two-sample Mendelian randomization (MR) was performed to assess genetically supported associations between gene expression and COPD risk. Bayesian colocalization analysis was applied to determine whether shared genetic variants underlie both gene expression and COPD susceptibility. Network analyses were conducted to map EDC-gene interactions and protein-protein interaction (PPI) landscapes.

Results: Among 4207 EDC-associated genes with available cis-eQTLs, MR identified 30 genes significantly associated with COPD after FDR correction. Colocalization analysis prioritized 18 genes with strong or moderate evidence of a shared genetic signal, including TCF19, MAP1LC3B, and IRF1. Network analyses revealed extensive interactions between these genes and multiple EDCs, such as bisphenol A, triclosan, and formaldehyde. Functional connectivity highlighted pathways related to immune regulation, autophagy, and epigenetic control.

Conclusion: This integrative translational exposomics framework identifies genetically supported links between EDC-related genes and COPD risk. The findings provide mechanistic insights into how environmental endocrine disruptors may contribute to COPD pathogenesis and offer prioritized molecular targets for future experimental validation and environmental health interventions.

Background: Extrachromosomal DNA (ecDNA) is an emerging hallmark of cancer that promotes tumor evolution and heterogeneity. However, the molecular characteristics and clinical significance of ecDNA in hepatocellular carcinoma (HCC) remain incompletely understood.

Methods: The clinical outcomes, genomics, transcriptomics, proteomics, tumor microenvironment, and drug target landscapes of ecDNA-negative and ecDNA-positive HCC in the Cancer Genome Atlas (TCGA) were compared. Next, the least absolute shrinkage and selection operator (LASSO) and random survival forest (RSF) algorithms were used to screen the ecDNA gene signature. A nomogram was constructed and evaluated based on the risk score and clinicopathological features. Finally, the role of DNASE1L3 was validated through in vitro experiments.

Results: EcDNA-positive tumors showed increased vascular invasion, higher AFP levels, and more TP53 mutations. These tumors displayed unique activation of proliferation pathways, decreased stromal infiltration, and heightened immune activation. Our validated six-gene signature (RNF186, BMP6, AOC1, FBLL1, MYBL2, and DNASE1L3) demonstrated strong prognostic value when combined with tumor stage in the nomogram. Notably, DNASE1L3 was downregulated in HCC, showed endothelial cell-specific expression, and suppressed the proliferation and migration of Hep3B2.1-7 cells.

Conclusion: Our study characterizes the molecular and clinical distinctions between ecDNA-negative and ecDNA-positive HCC and establishes a clinically applicable gene signature for patient prognosis. These findings advance our understanding of ecDNA-driven tumor heterogeneity and provide potential strategies for personalized HCC management.

Background: Fetal microcephaly (FMIC) is a neurodevelopmental disorder with heterogeneous etiologies and uncertain prenatal prognosis. Discrepancies between prenatal and postnatal head circumference (HC) measurements may confound ultrasound-based diagnosis, underscoring the need for genetic stratification to improve risk assessment.

Methods: This prospective cohort study analyzed data from 301 fetuses with suspected FMIC collected between 2014 and 2022. Trio-prenatal exome sequencing (pES) was performed in 301 fetuses with suspected FMIC and normal results on karyotyping and chromosomal microarray analysis. Diagnostic yield, molecular spectrum, and pathway enrichment were analyzed. Clinical follow-up was conducted to correlate genetic findings with postnatal neurodevelopmental outcomes.

Results: Molecular diagnoses were achieved in 41 cases (13.6%). Diagnostic yield was significantly higher in complex FMIC compared with isolated FMIC (15.9% vs. 10.1%, p < 0.01), and peaked in cases with family history (26.7%). Our findings expand the prenatal phenotypic spectrum for six genes (TUBB2A, DUOX2, EBP, FAM111A, FGFR3, PEX1), indicating that microcephaly can be a primary presenting feature in the fetus for conditions where it was previously considered a secondary or postnatal finding. Pathogenic variants were enriched in neurogenesis and extracellular matrix-related pathways, implicating dysregulated cell cycle progression and synaptogenesis. Importantly, HC standard deviation (HC-SD) correlated with diagnostic yield and, as demonstrated by multivariable analysis, served as an independent predictor of postnatal prognosis (aOR: 2.1 per 1-SD decrease; 95% CI: 1.5-3.0), whereas fetal growth restriction appeared nonspecific.

Conclusions: This prospective cohort study provides the largest prenatal genomic and prognostic analysis of FMIC to date, revealing potential genotype-phenotype associations, pathogenic pathways, and prognostic markers. These findings enhance understanding of FMIC mechanisms and provide essential evidence for prenatal genetic counseling and individualized risk assessment.

Background: Inherited retinal diseases (IRDs) are highly diverse and rare genetic disorders causing mild to complete vision loss across different age groups, with a notably higher disease burden in India. Although genetic testing has improved diagnostic accuracy, India's distinct genetic landscape, shaped by diverse racial backgrounds, admixtures, endogamy, and consanguinity, presents unique challenges. Additionally, phenotype overlaps, non-canonical presentations, genetic heterogeneity, and insufficient literature evidence contribute to clinically and genetically unsolved cases. Since genetic variant reporting commonly relies on information from non-Indian population databases, it is important to build comprehensive knowledge from published Indian data for its unbiased representation in relevant clinical resources. This review aims to assess the current state of Indian IRD research and its lacunae, as this understanding is essential to gauge the readiness of research institutions and tertiary centres for maximizing accessibility to genetic testing and potential treatment options.

Methods: We screened 764 PubMed-sourced Indian IRD articles until October 2023 and analysed 21,158 IRD cases from 287 publications reporting clinical and/or genetic data, and further found that 80 publications (n = 628 cases) reported genetic variants (v = 686 variants). Relevant literature was analysed to assess demographic distribution, genetic trends and the research landscape in India.

Results and clinical significance: Our analyses draw a comprehensive sketch of publication-derived demographics and genetic insights into major IRDs reported in India. They emphasize the urgent need for comprehensive and timely clinical and genetic reporting, since Indian IRD research remains fragmented. This calls for integrated nationwide efforts in systematic reporting through an extensive national IRD case registry for improving diagnostic accuracy, enhancing patient recruitment for clinical trials, and expanding access to emerging therapeutics.