Systems biology is one of science’s growth areas. Sequencing technologies and software tools developed on the back of the human genome project have reduced the cost of, and therefore increased access to, large and complex datasets (ending in -ome) of genome sequences (genomics), gene expression (transcriptomics) and proteins and metabolites (proteomics and metabolomics). Systems biological techniques integrate these datasets and provide insights into how phenotypes may emerge from interacting biological processes rather than isolated genes or proteins.
A recent editorial in the journal Nephrology Dialysis Transplantation examined this field in general and its relevance to nephrology. The authors mention that –omic datasets have been useful in modeling “self-organized highly interconnected networks”, and that such networks have implicated unexpected candidates in disease pathogenesis (see for example, this paper on cardiac hypertrophy).
The review goes on to suggest that using the tools of systems biology to finely phenotype individuals will usher in an era of truly personalized medicine. However, it is not clear to me that a definite sequel to this type of analysis will be the personalization of treatment or even that the concept of personalized medicine is particularly suited to our current view of what constitutes clinical evidence.
Diseases such as the ANCA-associated vasculitides (AAV) are now known to exhibit genomic variability. Randomised controlled trials (RCTs) in AAV (such as here and here) have been hampered by:
- Short follow-up times
- Inter-group heterogeneity which may have affected outcomes. These factors have contributed to ongoing debate about the applicability of the results of these trials (see correspondence here).
- Additionally a recent trial in membranous nephropathy, likely to represent another disease with distinct –omic subsets, was marked by slow recruitment.
All these points together suggest that it may be difficult to conduct meaningful clinical studies of distinct –omic subtypes in nephrological diseases. Currently, primacy is given to RCTs when evaluating the efficacy of new treatments; and in nephrology the community is finally beginning to produce the RCTs which have been absent historically.
If the focus is to switch away from RCTs with their large, well-matched study groups and towards splitting groups up by some -omic fingerprint I am able to envisage a time when one has to choose between giving more credence to the results of larger, “non-personalised” trials or smaller studies featuring –omic data but lacking the controlled element of RCTs. Would this represent progress?