+100%-

“Our Raman spectroscopic approach has great potential as a diagnostic technique for diseases like ME/CFS” the authors

A blood test for ME/CFS is like the holy grail. This research team thinks they may be onto something.

A blood test for ME/CFS is like the holy grail. This research team thinks they may be onto something.

A blood test – it’s like the holy grail for chronic fatigue syndrome (ME/CFS). Not only would it legitimize the disease, and make it easier to diagnose the disease, but it should also give us clues as to what’s causing it and perhaps even provide the long-sought biomarker drugs companies could use to assess the effectiveness of their drugs.

Of course, the question persists whether finding a single biomarker is even possible in such an apparently heterogeneous disease. If one was found, though, one would think given the disease’s apparent heterogeneity, it would be getting at its core elements.

Factors have been proposed before, but none has yet stuck. The “Developing a Blood Cell-Based Diagnostic Test for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Peripheral Blood Mononuclear Cell” study employed a different testing regimen (using Raman spectroscopy) and artificial intelligence (AI) to analyze the results. The authors believe that an AI-led approach is going to crack ME/CFS and similar diseases. (A blog on the potential role AI could play in ME/CFS is coming up.)

The mostly Oxford-led study also included researchers from the London School of Tropical Medicine, Poland, and the US. Led by long-time mitochondrial researcher Karl Morten of Oxford and Raman specialist Jiabao Xu, it was funded by the ME Association, with help from the Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences (!).

Raman Spectroscopy Takes Center Stage

The single cell Raman spectroscopy (SCRS) uses a laser to get a fingerprint of all biomolecules in a cell. Its ability to chart all the major building blocks – proteins, amino acids, lipids and phospholipids, and carbohydrates – makes it possible to assess the metabolic and physiological status of each cell.

The study – a follow-up to an earlier pilot study – combined “single-cell Raman” with artificial intelligence (machine learning) to come up with some intriguing findings. The pilot study (5 patients and 5 healthy controls) was able to differentiate the patients from controls astoundingly well (98%) and fingered high phenylalanine levels as a possible differentiating factor. That finding suggested that ME/CFS patients’ cells were – as other studies have concluded – turning to the less capable amino acids for fuel instead of relying on better substrates such as glucose and fatty acids.

Encouraged by the positive results, the investigators expanded their study to almost 100 individuals, including 61 ME/CFS patients, 16 healthy controls, and in an indication that they were pretty serious about the biomarker stuff – 21 multiple sclerosis patients. (Biomarkers must be tested against other diseases as well as healthy controls). They used the Raman approach to assess immune cells called peripheral blood mononuclear cells (PBMCs).

Results

The rates of mitochondrial respiration using thawed-out frozen cells were similar in all groups. (While other studies have found problems with the little energy centers of our cells, this measure of them has failed in two out of three studies and the authors discarded it as a possible biomarker.)

A supervised linear discriminant analysis (LDA) of the Raman spectroscopy findings, however, clearly differentiated the ME/CFS, MS, and healthy controls from each other. We’re used to seeing considerable overlaps between ME/CFS and controls, but in this case the groups were very well differentiated (D and E) – suggesting these researchers were really onto something. They were even able to capture differences between mild, moderate, and severe ME/CFS patients (group F).

Nice separations!

Check out the separation between the healthy controls (green), ME/CFS (red), and MS patients (green) in Figures D and E, and the healthy controls (green), mild (tan), and moderate/severe ME/CFS patients (red) in Figure B (!).

Adding to the pluses, the researchers found little indication of any possible confounding factors (sex, body mass index (BMI), age, disease duration, types, and total counts of medications and supplements, as well as the freezing duration and processing time for each sample). The fact that gender – which has complicated other results – did not in this case was encouraging.

A universal increase in tryptophan and tyrosine in cellular PBMCs was found in both ME/CFS and MS. With the nice separations, it was a little surprising to see some muddy findings. The phenylalanine picture, for instance, got more complicated with moderate and severe patients showing reduced levels and mild ME/CFS (and MS patients) showing increased levels. Similarly, elevated unsaturated fatty acid levels also left mild ME/CFS patients looking more like MS patients than moderate to severe ME/CFS patients, who had reduced unsaturated fatty acid levels. Why such a physiological break between mild and moderate and severe patients might be present is not clear.

Reduced glycogen levels in the mild and severe ME cohort (but not the moderate cohort?), as well as in the MS group, presented another complication as well. Glucose quantification – the amount of glucose present – on the other hand, was decreased in all ME subgroups – plus, the MS cohort had the lowest glucose levels.

All in all, the authors reported that the findings agreed with the altered utilization of amino acids (tryptophan, tyrosine, and phenylalanine) in patients with ME/CFS. Interestingly, the same general process of amino acid dysregulation was found in the MS group.

Note the similarities seen between ME/CFS and MS thus far. Increased tryptophan, tyrosine, reduced glycogen levels and glucose quantification were common to both diseases (in some subsets). Plus, the elevated unsaturated fatty acid levels and reduced phenylalanine levels were similar to mild ME/CFS.

A Focus on Tryptophan

The tryptophan-kynurenine pathway has been an object of discussion for some years but has been showing up more, recently. Just how versatile this pathway is can be seen in the two opposing hypotheses that have popped up about it.

Could the Kynurenine Pathway Be Causing ME/CFS, FM and Long COVID?

THE GIST

  • A blood test – it’s like the holy grail for chronic fatigue syndrome (ME/CFS). Not only would it legitimize the disease, and make it easier to diagnose the disease, but it should also give us clues as to what’s causing it.
  • This team of Oxford, London School of Tropical Medicine, Polish, and U.S. researchers, used a technique called Raman spectroscopy which has the ability to chart all the major building blocks – proteins, amino acids, lipids, and phospholipids, and carbohydrates – in a cell, making it possible to assess the metabolic and physiological status of each cell.
  • Encouraged by the positive results of an earlier pilot study, the investigators expanded their study to include almost 100 individuals, including 61 ME/CFS patients, 16 healthy controls, and, in an indication that they were pretty serious about finding a biomarker – 21 multiple sclerosis patients.
  • The artificial intelligence-driven Raman spectroscopy findings were able  to- to a remarkable degree – differentiate the ME/CFS, MS, and healthy controls from each other. We’re used to seeing considerable overlaps between ME/CFS and controls, but not in this case (see image in blog).  The Raman Spectra analysis was able to differentiate ME/CFS, MS, and healthy controls with remarkable accuracy (91% specificity; 93% sensitivity for ME/CFS).
  • Lauding the ease of the test, the small amount of blood it requires, its ability to be done on “fixed material”, and the fact that it can be frozen without deterioration the authors stated:
  • an “objective, sensitive, and straightforward diagnostic tool can therefore resolve the controversy concerning the nature of ME/CFS and…has the potential to make drastic impacts on patients’ quality of life….(When used in combination) “with sophisticated machine learning algorithms, our Raman spectroscopic approach has great potential as a diagnostic technique for diseases like ME/CFS”.
  • A universal increase in tryptophan and tyrosine and reduced glucose levels were found in the mild moderate and severe ME/CFS patients.
  • There were some oddities, though. Moderate and severe patients showed reduced phenylalanine levels while mild ME/CFS (and MS patients) showed increased levels. Similarly, elevated unsaturated fatty acid levels were found in mild ME/CFS patients while moderate to severe patients had reduced levels.  Reduced glycogen levels were found in the mild and severe ME cohort (but not the moderate cohort (?).
  • Increased tryptophan, tyrosine, reduced glycogen levels, and glucose quantification were found in both ME/CFS and MS patients (in some subsets). Plus, the elevated unsaturated fatty acid levels and reduced phenylalanine levels were similar to mild ME/CFS.
  • The increased tryptophan levels found in both the ME/CFS and MS groups jive with Robert Phair’s metabolic trap hypothesis for ME/CFS, which proposes that genetic mutations in an enzyme are inhibiting the metabolism of tryptophan to kynurenine and could result in high serotonin levels. The authors asserted that it “is crucial to acknowledge the potential dysfunctional effects of tryptophan and serotonin in the context of ME/CFS“.
  • The findings also suggested – once again – that ME/CFS patients’ cells are turning to “dirty fuel” – amino acids – for energy instead of using the cleaner burning glucose and fatty acids. Evidence of altered fatty acid and lipid metabolism – two hot research topics right now in ME/CFS – were also found.
  • The authors looked beyond ME/CFS, stating that in chronic, complex, unexplained conditions like it, including fibromyalgia, chronic Lyme disease, and long COVID, they believe that complex data and machine learning approaches such as those used in this study are going to lead the way.

 

The increased tryptophan levels found in both the ME/CFS and MS groups jives with Robert Phair’s metabolic trap hypothesis for ME/CFS, which proposes that genetic mutations in an enzyme are inhibiting the metabolism of tryptophan to kynurenine.  (The authors noted, though, that because many of the cells they measured did not use the enzyme in question, further study is needed.)

The authors proposed that the high tryptophan levels in the immune cells they measured could, by sequestering abnormal amounts of tryptophan in them, result in reduced brain tryptophan levels – a situation known to cause central or brain-induced fatigue. Or, as both Phair and Cortene propose, high levels of tryptophan in the blood could produce the symptoms of ME/CFS by producing high levels of serotonin in the brain.

Regardless of the specific mechanisms involved, the authors asserted that it “is crucial to acknowledge the potential dysfunctional effects of tryptophan and serotonin in the context of ME/CFS“.

The authors reported their results also fit with broad-spectrum metabolite analyses which found reduced levels of serum amino acids and disturbances in pyruvate dehydrogenase, sphingolipid, and phospholipid metabolism. The cells of both ME/CFS and MS patients appeared to be having trouble utilizing glucose – a preferred fuel source – and were turning to amino acids instead.

The low glycogen levels found were reminiscent of what’s seen after continuous exercise – which clearly wasn’t happening in ME/CFS. Instead, the authors believe they may reflect the increased use of amino acid stores to power their cells. Evidence of altered fatty acid and lipid metabolism – two hot research topics right now in ME/CFS – were also found.

Budding Diagnostic Tool?

While some similarities were found between ME/CFS and MS, the AI-driven Raman Spectra analysis was able to differentiate ME/CFS, MS, and healthy controls with remarkable accuracy (91% specificity; 93% sensitivity for ME/CFS).

The authors, clearly encouraged by the results, lauded the ease of the test, the small amount of blood it requires, its ability to be done on “fixed material”, and the fact that it can be frozen without deterioration. All in all, it appears to present an easy diagnostic – with the proviso that Raman microscopes – not apparently in great supply – need to be used. They stated:

an “objective, sensitive, and straightforward diagnostic tool can therefore resolve the controversy concerning the nature of ME/CFS and…has the potential to make drastic impacts on patients’ quality of life….(When used in combination) “with sophisticated machine learning algorithms, our Raman spectroscopic approach has great potential as a diagnostic technique for diseases like ME/CFS”.

They looked beyond ME/CFS, stating that in chronic, complex, unexplained conditions like it, including fibromyalgia, chronic Lyme disease, and long COVID, they believe that complex data and machine learning approaches are going to lead the way. As diagnostic algorithms get more precise, treatments will be identified and developed for the subtly differing disease states found in ME/CFS and other diseases.

In fact, they expect that as the biological footprints of these diseases become increasingly uncovered, subtle tests will be able to pick up their signs before major symptoms have shown themselves. Predictive analytics that employ machine learning algorithms are already being used to ferret out disease states before they become evident.

Conclusion

Using a new technique called Raman spectroscopy, in combination with machine learning, this British-Polish and US research group were able to distinguish ME/CFS from healthy controls and multiple sclerosis with an unusually high degree of accuracy.

Could a new technique produce a blood test for ME/CFS? Time will tell.

Could a new technique produce a blood test for ME/CFS? Time will tell.

The reduced glucose levels and increased tryptophan and tyrosine levels across the mild, moderate, and severe ME/CFS groups made sense, given what we know, and put a spotlight on energy metabolism, tryptophan, and serotonin. With regard to those last two, the authors went so far as to assert that it’s “crucial to acknowledge the potential dysfunctional effects of tryptophan and serotonin” in ME/CFS.

The findings also suggested – once again – that ME/CFS patients’ cells are turning to “dirty fuel” – amino acids – for energy instead of using the cleaner burning glucose and fatty acids.

Some of the findings were curious. The phenylalanine and unsaturated fatty acids findings were complicated with mild patients showing opposite results from moderate and severe patients. With low glycogen levels in the mild and severe ME/CFS patients – but not in the moderate patients (?). Perhaps not so surprising for a fatiguing disease, multiple sclerosis showed some clear similarities (and differences) to ME/CFS.

In the end, in its broad scope, the study validated problems with energy metabolism, demonstrated amino acid abnormalities, and highlighted tryptophan issues,

Could a long wished-for, (prayed for), biomarker for ME/CFS be next? Time will tell. The authors were certainly excited, stating, “Our Raman spectroscopic approach has great potential as a diagnostic technique for diseases like ME/CFS”. A biomarker would require larger studies that include more disease groups that are similar to ME/CFS, such as fibromyalgia.

Larger, more comprehensive studies that incorporate the Raman spectroscope with metabolomics and proteomics and use more disease controls appear to either be underway or are planned for. We shall see!

However, this turns out it’s good to see ME/CFS researchers and their funders turning to the new technologies to solve ME/CFS. It comes as no surprise that the massive capabilities of artificial intelligence may be particularly helpful for complex diseases like ME/CFS. More on that later.

For more from Professor Morten on the mitochondria and ME/CFS check out his presentation below.

Like this Blog? Please Support Health Rising and Keep the Information Flowing

GIVE A ONE-TIME DONATION


GIVE MONTHLY



HEALTH RISING IS NOT A 501 (c) 3 NON-PROFIT

GET FREE ME/CFS AND FIBROMYALGIA INFO

Like the blog you're reading? Don't miss another one.

Get the most in-depth information available on the latest ME/CFS and FM treatment and research findings by registering for Health Rising's free  ME/CFS and Fibromyalgia blog here.


Stay on Top of the News!

Subscribe To Health Rising’s Free Information on Chronic Fatigue Syndrome (ME/CFS), Fibromyalgia (FM), Long COVID and Related Diseases.

Thank you for signing up!

Pin It on Pinterest

Share This