Systemsbiology is one of science’s growth areas. Sequencing technologies and softwaretools developed on the back of the human genome project have reduced the costof, and therefore increased access to, large and complex datasets (ending in -ome) ofgenome sequences (genomics), gene expression (transcriptomics) and proteins andmetabolites (proteomics and metabolomics). Systems biological techniques integratethese datasets and provide insights into how phenotypes may emerge from interactingbiological 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-organizedhighly interconnected networks”, and that such networks have implicatedunexpected candidates in disease pathogenesis (see for example, this paper on cardiac hypertrophy).
The review goeson to suggest that using the tools of systems biologyto finely phenotype individuals will usher in an era of truly personalized medicine. However, it isnot clear to me that a definite sequel to this type of analysis will be the personalizationof treatment or even that the concept of personalized medicine is particularlysuited to our current view of what constitutes clinical evidence.
Diseases such as the ANCA-associatedvasculitides (AAV) are now known to exhibit genomic variability. Randomised controlled trials (RCTs) in AAV (such as here and here) have beenhampered by:
- Short follow-up times
- Inter-group heterogeneity which mayhave affected outcomes. These factors have contributed to ongoing debateabout the applicability of the results of these trials (see correspondence here).
- Additionally a recent trial in membranous nephropathy, likely to representanother 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 ofdistinct –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 hasto 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?
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