An integrative analysis of consortium-based multi-omics QTL and genome-wide association study data uncovers new biomarkers for lung cancer DOI Open Access
Yanru Wang, Angela Yee‐Moon Wang, Ning Xie

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 16, 2024

Abstract The role of molecular traits (e.g., gene expression and protein abundance) in the occurrence, development, prognosis lung cancer has been extensively studied. However, biomarkers other layers connections among various that influence risk remain largely underexplored. We conducted first comprehensive assessment associations between (i.e., DNA methylation, expression, metabolite) through epigenome-wide association study (EWAS), transcriptome-wide (TWAS), proteome-wide (PWAS) metabolome-wide (MWAS), then we synthesized all omics to reveal potential regulatory mechanisms across layers. Our analysis identified 61 CpG sites, 62 genes, 6 proteins, 5 metabolites, yielding 123 novel biomarkers. These highlighted 90 relevant genes for cancer, 83 them were established our study. Multi-omics integrative revealed 12 these overlapped layers, suggesting cross-omics interactions. Moreover, 106 cross-layer pathways, indicating cell proliferation, differentiation, immunity, protein-catalyzed metabolite reaction interact risk. Further subgroup analyses biomarker distributions differ patient subgroups. To share signals different with community, released a free online platform, LungCancer-xWAS, which can be accessed at http://bigdata.njmu.edu.cn/LungCancer-xWAS/ . findings underscore importance xWAS integrating types quantitative trait loci (xQTL) data genome-wide (GWAS) deepen understanding pathophysiology, may provide valuable insights into therapeutic targets disease.

Language: Английский

An integrative analysis of consortium-based multi-omics QTL and genome-wide association study data uncovers new biomarkers for lung cancer DOI Open Access
Yanru Wang, Angela Yee‐Moon Wang, Ning Xie

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 16, 2024

Abstract The role of molecular traits (e.g., gene expression and protein abundance) in the occurrence, development, prognosis lung cancer has been extensively studied. However, biomarkers other layers connections among various that influence risk remain largely underexplored. We conducted first comprehensive assessment associations between (i.e., DNA methylation, expression, metabolite) through epigenome-wide association study (EWAS), transcriptome-wide (TWAS), proteome-wide (PWAS) metabolome-wide (MWAS), then we synthesized all omics to reveal potential regulatory mechanisms across layers. Our analysis identified 61 CpG sites, 62 genes, 6 proteins, 5 metabolites, yielding 123 novel biomarkers. These highlighted 90 relevant genes for cancer, 83 them were established our study. Multi-omics integrative revealed 12 these overlapped layers, suggesting cross-omics interactions. Moreover, 106 cross-layer pathways, indicating cell proliferation, differentiation, immunity, protein-catalyzed metabolite reaction interact risk. Further subgroup analyses biomarker distributions differ patient subgroups. To share signals different with community, released a free online platform, LungCancer-xWAS, which can be accessed at http://bigdata.njmu.edu.cn/LungCancer-xWAS/ . findings underscore importance xWAS integrating types quantitative trait loci (xQTL) data genome-wide (GWAS) deepen understanding pathophysiology, may provide valuable insights into therapeutic targets disease.

Language: Английский

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