Beyond the Human Genome: What Is Multi-omics?

Technology Policy Science & Innovation

Beyond the Human Genome: What Is Multi-omics?

Posted on: 4th October 2021
By Multiple Authors
Martin Carkett
Policy Lead, Science & Innovation Unit
Tejaswini Mishra
Biomedical Research Scientist, Stanford University

This piece forms part of an expert explainer series in a collaboration between the Tony Blair Institute for Global Change (TBI) and the Stanford Healthcare Innovation Lab (SHIL). Together, TBI and SHIL have a shared vision to transform personal and global health in the 21st century. Combining leading policy and research capabilities, they are working to develop the technology and knowledge to improve lives around the world. 



Multi-omics is often described as a pivotal step on the road to delivering modern, personalised, precision medicine. Beyond genomics – the sequencing of our individual genomes to examine, among other things, our predispositions to disease – multi-omics seeks to also simultaneously, comprehensively and continuously measure a broader set of biomolecules including epigenetic markers, mRNAs, proteins and metabolites in our cells. By measuring and integrating this information over time, we can examine the molecular mechanisms of our health and disease in a more detailed and dynamic way, and derive novel, more targeted, therapeutic approaches. But what does this mean for the future of health care, and why should multi-omics be an important focus for researchers, clinicians and policymakers?

Genomics: The First Step in Precision Medicine 

The completion of the Human Genome Project in 2003 heralded a new era of genetic medicine. For the first time in the history of humanity, we could look into the very fabric of our being and read the blueprint of instructions present in every one of our cells –  our DNA.

DNA is essentially a biological unit of data storage. It consists of a length of base pairs, each of which represents one of just four values (A, T, C or G), not dissimilar to binary digit (bit) data storage used in modern computing. The Human Genome – the complete set of DNA which encodes our species – consists of around 3 billion base pairs, housed in the nuclei of each of our cells. 

While this sequence of base pairs is virtually identical in every human, there are subtle differences in each of our individual genomes that make us unique. Whole genome sequencing, pioneered by the Human Genome Project, enables us to read a person's individual genome and, amongst other things, identify deviations from the "normal" Human Genome, which are often associated with abnormalities and can help us predict the likelihood of certain diseases occurring.   

Over the past two decades, quantum leaps in DNA sequencing technologies have dramatically reduced the time and costs required to sequence an entire genome – now around just $1,000/genome – making it feasible that we can all have our genomes sequenced as part of routine health care in the near future. This will be the first major step towards the future of personalised medicine. 

Beyond Genomics 

DNA may be the "instructions", and there is clearly great value in understanding when these instructions aren’t quite right. However, that's not the whole story. What if the instructions are correct, but you are unable to access them? Or you can access them, but you are unable to read them or interpret them correctly? This is where multi-omics comes in.

Taking a step back, it’s important to appreciate how the information stored in DNA is accessed and used, to understand the utility of studying multi-omics. The Human Genome contains around 25,000 genes, each of which typically encodes for a single protein that performs a specific biological function in the cell. However, only a percentage of these genes are "expressed" (switched on) in a cell at a given time, to ensure that the cell functions as it should. 

When a gene is "switched on", the information it holds is "transcribed" into messenger RNA (mRNA), which acts as a vehicle to transport this information from the nucleus into the main body of the cell where it is then "translated" via cellular machinery into the intended protein. If the instructions are wrong (there is a mutation in the DNA), this usually permeates to some degree through to the protein, which may cause complete or partial loss of function, resulting in a biological defect. 

However, the extent of loss of function can be difficult to judge from the genome alone. Moreover, even if there is not a mutation in the DNA, the "level of expression" – to what extent a gene is switched on and therefore how much protein is ultimately produced (like a dimmer switch) – can often be just as important in determining health or disease.

Multi-omics allows us to explore these facets by simultaneously examining a more comprehensive set of biomolecules in a cell, integrating information from each step on the path from DNA to biological function. This includes studying the epigenome (which indicates which genes are more or less accessible and likely to be expressed), the transcriptome (revealing to what extent different variants of genes are expressed), the proteome (to what extent genes are being correctly translated from mRNA into proteins) and the metabolome (to what extent those proteins are functioning) in addition to the genome (whether genes are present and correctly coded).  

Multi-omics: The Next Step 

Multi-omics therefore offers the potential to see a much more detailed picture of what is occurring at a molecular level and enables us to better determine the mechanisms of disease and make more targeted medical interventions. From a fundamental research perspective, better understanding how regulatory networks and cell signalling pathways should normally operate and how they can become dysfunctional in disease, is critical to the discovery of new druggable targets.

Importantly, multi-omics also provides a dynamic view over time across different cell and tissue types, as opposed to the largely static snapshot that the genome alone provides. This is vitally important in developing our understanding of how environmental factors, such as diet, lifestyle and age, in combination with genetic factors, affect health and disease over time; it also allows a much more personalised view of our individual health. 

As with the Human Genome Project, researchers are already beginning to map out a reference "Human Multi-ome", which aims to describe the "normal" epigenetic conditions and levels of mRNA, proteins and metabolites in each of the 200 cell types in an adult human, in a longitudinal series over a lifetime. This is clearly a much more complex challenge than sequencing the genome alone, but one that will yield significantly more powerful datasets. 

Personal multi-omic profiling has already been achieved for a handful of individuals, but the technology to do this accurately and at scale is still in its infancy and there needs to be much greater depth and diversity before a reliable reference Human Multi-ome is achieved. In time, we will reach a stage where beyond a reference, we can each have our individual multi-omic data regularly measured so that we can determine personal baselines of key biomolecules and deviations from these, to provide early indications of where we might be diverging from our optimal health. 

This will be key in delivering preventative, personalised, precision medicine in the 21st century and achieving the public health and economic benefits that this can bring. Much of the technology already exists, but, as with genomics at the turn of the century, time and costs present major barriers to widespread clinical application. These will reduce over time, but, as also with genomics, this can be greatly accelerated with political will.

Given the potential prize, progressing multi-omic advancements at pace should be a greater focus for policymakers and, as we have previously argued, they can expedite this agenda by centralising and harmonising national and international research efforts, providing investment and by using the levers of power to incentivise the private sector. 

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