Multi-omics Strategy Toward Identifying and Managing Hereditary and Metabolic Liver Diseases

A wide range of etiologies can cause liver diseases and pose threats to human health, causing a heavy burden to the economy. Hepatologists are facing challenges identifying unexplained liver diseases especially hereditary and metabolic liver diseases. Omics technologies such as metabonomics, genomics, and epigenomics are developing rapidly and play an important role in precision medicine. Meanwhile, more understanding of the characteristics of rare liver diseases and advanced diagnostic algorithms are needed to help physicians manage such diseases better.

It's essential to explore the correlations between gene alterations and clinical phenotypes. Gene mutation spectrum in different regions are also to be clarified. Omics technologies not only contribute to the diagnosis of certain liver diseases but may also uncover their pathogenesis. Artificial intelligence combining clinical data and advanced omics technologies is crucial to constructing a big database, thus facilitating the management of these liver diseases.

This Research Topic welcomes original research, reviews, and meta-analysis, on the following themes but is not limited to them:

• Application of omics technologies in the diagnosis of liver disease
• Learning model for clinical diagnosis and risk assessment of liver diseases based on big database
• Research on potential pathogenesis and therapeutic targets by applying omics technologies
• Application of omics technologies in accurate diagnosis of non-hereditary and metabolic liver diseases
• Studies related to clinical and pathological aspects of hereditary and metabolic liver diseases

Keywords: omics technology, artificial intelligence, precision medicine, liver disease, genomic alteration

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.