Personalized medicine and ‘everything-omics’

Individualized medicine

The case for ‘personalized medicine’ is promulgated more and more, but one difficulty is that what the term means is often unclear. To some it means no more than a personal appraisal by your local medical practitioner but to others it means the sequencing of your genome in whole or part (e.g. Buford & Pahor, 2012). But there is much more to this on both the personal side and the medicine side.

Eric Topol (Director of the Scripps Translational Science Institute) recently summarised the growing cascade of ‘omics’ (Topol, 2014). Currently, massive data collection on an individual can include one’s genome, transcriptome, proteome, metabolome, microbiome, epigenome, and even one’s exposome (or environmental exposure). Many of these ‘omic’ measures differ between tissues, organs, and disease states and change with time. This adds some dimensions to what I could call the ‘panorome’ that is you. Topol lumps these ‘omic’ measures together as the science of ‘panoromics’ – the panorama of ‘omic’ measures that signify individuality (even for so-called identical twins). The depth and accuracy of such collected data is improving rapidly.

Whole-genome sequencing is the first of the ‘omics’ to really insert itself into clinical medicine. However, note that whole-genome sequencing is not quite that, as about 3% of the genome is not accessible for sequencing. But, there is no doubt that cheap whole-genome sequencing is here to stay and its place in medicine will evolve rapidly. However, it remains to be seen if the hoopla surrounding the drafting in 2003 of the genome in the Human Genome Project will become reality – the premise that we would soon know the details of heritable factors that underlie cancer, vascular disease and mental illness was legitimate optimism.Chromosomes

The use of genome sequencing will increase as more individuals with known diseases and backgrounds have their genome sequenced. This will be enhanced when many family members are also sequenced so that the impact of rare variants of diseases can be assessed. Topol proposes that the other ‘omic’ domains will also prove useful particularly when, in future, data from them can be combined for an individual. Their potential is already clear. Two examples. First, the microbiome is derived initially from the mother at birth. Part of it is the DNA of commensal bacterial flora in the gut which can control handling of drugs including some used to treat cancer and cardiac failure. It is clear that an individual’s microbiome can influence many aspects of physiology. The epigenome is the map of methylation to histone modifications in the DNA as well as alterations in chromatin structure. The science of epigenetics and the epigenome has already established a place in physiology and pathophysiology. It provides a mechanism by which endogenous and exogenous factors (such as maternal stress and temperature respectively) can effect change in the next generation and beyond. The importance of epigenetics in cancer biology is established but increasingly its role in diabetes, arthritis and hypertension is being revealed.

What Topol predicts is a medical landscape in which ‘individualized medicine’ (his preferred term) becomes the norm based on ‘panoromics’. My cautionary tale is that there is much to be learned before the hype becomes reality. We need to know more about the origins of the actual phenotype of an individual. Until then the idea that a common genetic variant will cause a common disease in that person is flawed. This is because the era of equating a gene with a phenotype is over. So, much remains to be determined. Then, when realistic benefits are demonstrated for individualized ‘omic’ medicine, there is the task of transmission of new information into society with the attendant implementation issues of cost and equity. Already we know how to influence key disease risk factors (e.g. hypertension as a cause of stroke; physical inactivity as a cause of osteoporosis) but we are well behind at implementing change, even in first-world populations.



Topol EJ (2014). Individualized medicine from prewomb to tomb. Cell 157: 241-253.



Buford TW & Pahor M. (2012). Making preventive medicine more personalized: implications for exercise-related research. Prev Med 55: 34-36.

Bird A (2007). Perceptions of epigenetics. Nature 447: 396-398.

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