Multi-omics. An emerging avenue of research for investigating the underlying architecture of human disease is the development of multi-omics approaches. Integration and analysis of large-scale data generated from genome sequencing alongside other -omics technologies including transcriptomics, proteomics, and metabolomics, enable a more comprehensive and nuanced insight into biological systems that underlie disease. However, in contrast to genomic data, the generation of multi-omics data remains expensive, time-consuming, and is typically limited in large-scale population studies. In a recent publication, Xu and collaborators developed a model predicting >17,000 multi-omic traits from genomic profiles across 50,000 people. Here is a brief review of their paper, with a focus on the relevance of developing multi-omics resources in 2023.
