In a recent number of Nature Reviews, Human Protein Atlas researchers Mathias Uhlén and Adil Mardinoglu discuss a study by E.G. Williams and co workers in Science where five complementary -omics datasets across various environmental states (including genomics, transcriptomics, proteomics, metabolomics and phenomics) using the liver as a platform for multiomics analysis are integrated.

Uhlén and Mardinoglu stress that it is vital to integrate functional characterization and precise quantification of multiple layers of information, such as the abundance of gene products, mRNA, proteins and metabolites, as well as their molecular interactions with the environmental factors (such as diet).

In the Science-study the researchers demonstrate that the multiomics approach is a powerful tool for understanding the dynamics of biological functions in the liver.

They introduced a pipeline to identify the genetic relationships and metabolic phenotypes in 386 individuals from 80 diverse cohorts of the BXD mouse genetic reference population. The BXD family is one of the largest and best-characterized mouse genetic reference populations to study the complex interactions between genes and environment.

Uhlén and Mardinoglu show that the work of Williams et al. represents a useful contribution towards our increased understanding of the liver as a whole and, particularly, in terms of metabolic function in addressing fundamental biological questions in 80 diverse cohorts of the BXD mouse genetic reference population. This comprehensive dataset can also be used in selecting the most appropriate laboratory mouse strain for a particular experiment or control, which is an important consideration when studying human liver-related disorders.

Uhlén and Mardinoglu conclude that this systems biology approach can be applied directly in humans, or it can be done in models of human disease with the findings translated and interpreted in relation to human disease. This approach might also open up new opportunities for integrating health-care delivery with -omics technologies for the improvement of clinical practice and public health, and a new possibility for a precision medicine approach that combines a patient?s multilayers of -omics data with other risk factors, including age, family history, gut microbiota and sedentary lifestyle.

However, complete understanding of the functioning of complex individual human biology in health and disease, and how the observed phenotypic differences are related to genetic variance, requires the engagement of an unprecedented collaborative and interdisciplinary approach from scientists and clinicians.

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