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May 20, 2011 no comments

Finding exogenous biomarkers of heart disease: humans are ecosystems too!

It is ten years this week since the Total Scientific team, together with our collaborators at Imperial College in London submitted the first large-scale clinical metabolomics study for publication in Nature Medicine.  We applied proton NMR spectroscopy to serum samples collected from patients with coronary heart disease (defined by angiography), as well as control subjects with normal coronary arteries.  The results were dramatic: we could completely separate the groups of subjects based on the coronary artery status using a non-invasive blood test.

Despite such encouraging findings, the implications of that ground-breaking study have yet to impact clinical medicine.  There are a number of reasons for that: in 2006, a replication study was published, again in Nature Medicine, with some misleading conclusions.  Although they saw broadly the same patterns that we have observed five years previously, they interpreted their reduced diagnostic power as a negative outcome – though in reality its source was most likely the inappropriate concatenation of samples from different studies, collected with different protocols.

But another limitation of our study has its origin in the techniques we applied.  NMR spectroscopy is an amazingly reproducible analytical technique, but it has poor sensitivity (so misses many low abundance biomarkers) and, perhaps more crucially, it can be difficult to determine the exact molecular species responsible for the differences between groups of subjects.

In our study, the majority of the diagnostic power arose from a peak with a chemical shift around 3.22 ppm, which we attributed to the trimethylamine group in choline.  Individuals with angiographically-defined heart disease have much lower levels of this signal compared with healthy subjects.  Although we speculated that the signal might arise due to phosphatidylcholine residues in HDL, the lack of certainty about the molecular identity of this powerful diagnostic marker (that was clearly replicated in the 2006 study) hampered further investigation.

Then, last month, Wang and colleagues published a fascinating follow-up study in Nature.  Using LC-MS based metabolomics they identified three metabolites of phosphatidylcholine as predictors of heart disease (choline, TMAO and betaine).  In a stroke, they replicated our earlier findings and provided additional clarity as to the molecular nature of the biomarkers.  It has taken a decade to move from the realisation that there was a powerful metabolic signature associated with heart disease to an unambiguous identification of the molecules that are responsible.

Are measurements of these metabolites useful in the clinical management of heart disease?  That remains an open question, but with the molecular identity of the biomarkers in hand it is a question that can be readily investigated without the need for complex and expensive analytical techniques such as NMR and LC-MS.

But Wang and his colleagues went one step further: they showed that these biomarkers were generated by the gut flora metabolizing dietary phosphatidylcholine.  So the signature we originally published in 2002 may not represent differences in host metabolism at all, but actually reflect key differences in the intestinal flora of subjects with heart disease.  All of which serves as a useful reminder that we humans are complex ecosystems, and our biochemistry reflects much more than just our own endogenous metabolic pathways.

Metabolomics is an incredibly powerful platform for the discovery of new biomarkers, as this decade-long quest has demonstrated.  And the pathways it reveals can lead in the most surprising of directions.

Dr. David Grainger
CBO, Total Scientific Ltd.


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