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Multi-Omics SMR and Experimental supportive analyses Decipher Causal Drivers Hepatocellular Carcinoma

ABSTRACT: Hepatocellular carcinoma (HCC) is a highly prevalent and fatal digestive system malignancy, challenging to treat due to its latent onset and non-specific symptoms in advanced stages. Somatic mutations play a crucial role in hepatocarcinogenesis, with nearly half of HCC patients carrying oncogenic driver mutations such as TP53, CTNNB1, or TERT. In parallel, germline susceptibility variants identified by genome-wide association studies (GWAS) — including loci near TERT, MBOAT7, TM6SF2, and PNPLA3 — reveal inherited predisposition that shapes the molecular landscape for HCC development. Despite recent therapeutic advancements, long-term survival remains suboptimal, necessitating a deeper understanding of its pathogenesis and the identification of precise molecular targets. Traditional genomic studies, such as genome-wide association studies (GWAS), have successfully identified associated variants; however, due to their statistical design, they do not provide direct causal inference, functional supportive analyses, or comprehensive insight into multi-level molecular regulation and tumor microenvironment heterogeneity, serving instead as a critical starting point for subsequent functional and integrative analyses.

ORGANISM(S): Homo sapiens

PROVIDER: GSE317443 | GEO | 2026/01/28

REPOSITORIES: GEO

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Project description:Background: The identification of causal variants responsible for disease associations from genome-wide association studies (GWAS) facilitates functional understanding of the disease mechanisms implicated by GWAS. One of the earliest GWAS associations to COPD spans an intragenic region within FAM13A, but the causal variants at this loci have not yet been identified. Massively parallel reporter assays (MPRA) can be used to prioritize functional regulatory variants in a high-throughput manner. Methods: We used an integrated approach using fine-mapping in over 10,000 subjects from COPD GWAS studies, two MPRA experiments, traditional reporter assays, chromatin conformation capture, and CRISPR-based gene editing to characterize COPD-associated regulatory variants in FAM13A in human bronchial epithelial cell lines. Results: Conditional genetic association and fine mapping analyses identified two independent COPD association signals in FAM13A. MPRA identified 45 common functional regulatory variants, and six COPD-associated putative functional variants were prioritized for further functional investigation. Three variants demonstrated significant activity in traditional reporter assays, and one variant, rs2013701, was selected for further testing in the endogenous genomic context based on a direction of effect consistent with postulated mechanisms of FAM13A-mediated COPD susceptibility. CRISPR-based genome editing for this variant confirmed allele-specific effects on FAM13A expression and altered rates of cellular proliferation, providing multiple levels of functional characterization for this COPD-associated variant. Conclusions: Comprehensive screening for regulatory variants near FAM13A identified the presence of extensive functional regulatory variation within a 250kb window of FAM13A in HBECs. Focused functional evaluation of the COPD-associated functional variants in LD with the two independent association signals in this region prioritized the common variant rs2013701, for which multiple parallel lines of functional evidence confirm allelic effects on FAM13A regulation.

Project description:Genome-wide association studies (GWAS) have successfully identified 145 genomic regions that contribute to schizophrenia risk, but linkage disequilibrium (LD) makes it challenging to discern causal variants. Computational finemapping prioritized thousands of credible variants, ~98% of which lie within poorly characterized non-coding regions. To functionally validate their regulatory effects, we performed a massively parallel reporter assay (MPRA) on 5,173 finemapped schizophrenia GWAS variants in primary human neural progenitors (HNPs). We identified 440 variants with allelic regulatory effects (MPRA-positive variants), with 72% of GWAS loci containing at least one MPRA-positive variant. Transcription factor binding had modest predictive power for predicting the allelic activity of MPRA-positive variants, while GWAS association, finemap posterior probability, enhancer overlap, and evolutionary conservation failed to predict MPRA-positive variants. Furthermore, 64% of MPRA-positive variants did not exhibit eQTL signature, suggesting that MPRA could identify yet unexplored variants with regulatory potentials. MPRA-positive variants differed from eQTLs, as they were more frequently located in distal neuronal enhancers. Therefore, we leveraged neuronal 3D chromatin architecture to identify 273 genes that physically interact with MPRA-positive variants. These genes annotated by chromatin interactome displayed higher mutational constraints and regulatory complexity than genes annotated by eQTLs, recapitulating a recent finding that eQTL- and GWAS-detected variants map to genes with different properties. Finally, we propose a model in which allelic activity of multiple variants within a GWAS locus can be aggregated to predict gene expression by taking chromatin contact frequency and accessibility into account. In conclusion, we demonstrate that MPRA can effectively identify functional regulatory variants and delineate previously unknown regulatory principles of schizophrenia.

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Multi-Omics SMR and Experimental supportive analyses Decipher Causal Drivers Hepatocellular Carcinoma

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