"a 256-peptide immunosignature with the ability to separate ME/CFS cases from controls"

The findings reported by Oliver Günther and colleagues [1] (open-access available here) really interested me. They interested me because they talked about the "hit and run" hypothesis being pertinent to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), where "a pathogen or other immunological insult experienced by a subject may be gone, but leaves behind physiological disequilibrium." They interested me because researchers turned to "an immunosignature assay (ISA) that employs a microarray of thousands of random-sequence peptides to interrogate antibodies in a broad and unbiased fashion" to try and pick out the biological effects of the 'hit and run' hypothesis in relation to ME/CFS. And they interested me because researchers reported that they were able to identify "a 256-peptide signature that separates ME/CFS samples from healthy controls, suggesting that the hit-and-run hypothesis of immune dysfunction merits further investigation." Lots of interesting things (honest!).

The Günther paper is open-access so doesn't really need too grand an explanation from me. The long-and-short of it was that following the adoption of a discovery and validation methodology (an increasingly favoured option in ME/CFS research circles), authors came up with a sort of 'biological fingerprint' "optimally separating ME/CFS cases and controls" based on the examination of serum samples. They also noted that in amongst their 256-peptide signature, one particular peptide - "LRVVWLSGVASG" - was also mentioned in another independent study with similar aims [2] perhaps therefore requiring further research focus. For those who might not be totally au fait with peptide designation, that string of letters is not meant to be pronounced, but rather each letter corresponds to an amino acid making up that particular peptide.

Whilst this is great work and indeed, represents some really quite detailed analysis, the authors caution that the science is not quite there yet when it comes to a 'biological test' for ME/CFS. So: "the heterogenous nature of ME/CFS clinical presentation and the variance natural present amongst control samples means that group labels in the Discovery and Validation Sets are not based on any gold standard." Diagnosis of ME/CFS still remains a point of real contention in various circles (see here) given the variety of diagnostic criteria available. Indeed, some commentators have suggested that the combination of 'ME/CFS' as a unified diagnostic label simply cannot ever exist (see here). The authors further note that: "Even the best research case definitions are often subjective and—in the absence of clear biomarkers—any group of ME/CFS cases likely comprise a heterogeneous set of pathologies."

I'm also minded to suggest that as per the lessons being learned in connection to autism biomarker research for example (see here), one needs to perhaps think about getting different research groups together who are looking at ME/CFS from different angles (see here). Y'know, sort of combining various different biomarker studies looking at various different biological 'angles' and sorta meta-analysing all the collected data to see if a larger, grander, range of variables might provide a more accurate biomarker picture of the condition(s)...

Still, the Günther study represents some good science and good value-for-research-money. It stresses how, by utilising the pretty sophisticated analytical equipment available these days, one can start creeping ever closer to some of the possible biochemistry that underpins ME/CFS (or at least some ME/CFS) and perhaps then also start some conversations centred on what can be done to alleviate symptoms and cure such a devastating illness.

----------

[1] Günther OP. et al. Immunosignature Analysis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). Mol Neurobiol. 2018 Oct 8.

[2] Singh S. et al. Humoral Immunity Profiling of Subjects with Myalgic Encephalomyelitis Using a Random Peptide Microarray Differentiates Cases from Controls with High Specificity and Sensitivity. Mol Neurobiol. 2018 Jan;55(1):633-641.

----------