Maybe because brain cells are hard--and expensive--to scan in high detail? It's hard to measure how tightly astrocyte feet are clamped around a blood vessel, or how much quinolinic acid is being produced in a small clump of cells, and it probably doesn't take all that much variance to cause noticeable symptoms. I recently came across three studies using complex processing of EEG signals that seem to accurately identify PWME from controls. One study was from 1990 IIRC. So, here's a technique that might be a reliable clinical exam for ME, more or less duplicated twice ... and no one is funding development of it. The latest study was done by an undergrad, paid for by himself and the test subjects. I suppose a better answer to your question is: lack of funding.
There have been more than a few of each sort of brain imaging method and the results, at least in terms of specific regions have been inconsistent.
The expectation is that if something goes wrong then this will cause damage and this will show up on a scan.
Generally speaking, brain pathology will lead to some kind of specific neurological outcome, but ME/CFS doesn't fit the pattern as other such diseases (from MS to Alzheimers), particularly the progressive nature of the pathology in the brain.
My cytokine profile only showed a few cytokines slightly or mildly elevated, but maybe it doesn't take much. Maybe the glial cells are much more sensitive to those cytokines (tougher to test than measuring cytokine levels in serum). The positive feedback loop could be restricted to the brain, and extra cytokines from the body could add to that to make symptoms more severe. Viral infections seemed to create the same increase in symptoms for me that physical exertion did, and cytokines could explain that.
Cytokines are part of localised cell to cell communications. By the time they spill over into circulation, they are no longer useful and as such, in circulation they are degraded to levels where they are no longer going to have much effect. If a test reveals high levels of cytokines in blood serum, the problem isn't the activity of those cytokines in the serum, the problem is the cause of the high level of cytokine signalling in the periphery.
Cerebrospinal fluid cytokine studies of ME/CFS have been inconsistent. It is indeed possible that there could still be aberrant feedback loops in specific/localised parts of the brain or periphery, but the key conclusion of this is that cytokines are not the "something in the blood".
There have also been a variety of experiments (in healthy people) that show that no particular cytokine causes/maintains those symptoms we associate with viral infections. The converse is still possible, namely when damage associated with such symptoms occur, this can cause the release of cytokines.
Any hypothesis based on pathogenic exosomes has the same limitations - exosomes are a part of cell to cell communication. The spilling over into the blood itself is unlikely to be perpetuating the disease, so the key question is where are they coming from?
I'm not a biologist, and certainly not a specialist in the specific fields of brain/body communication, so I lack the specific knowledge to form a strong detailed hypothesis. The brain has very strong control over various body processes, so to me it seem reasonable that altering even a few brain cells could affect production of exosomes or whatever might be the 'something in the blood'.
Unless we can propose specific mechanisms, our beliefs/opinions don't really count for much.
(this last bit isn't aimed at anyone in particular)
A key point that many seem to miss (including discussions in peer-reviewed manuscripts) is the importance of scale - phenomena at a biochemical level is quite different from phenomena at a cellular level, which is different from phenomena at physiological scales. Plausible hypotheses need to respect this and appropriate perspective to describe how the phenomena on each scale is linked.
A classic example of this lack of respect of scale is how aspiring students (high school and even undergraduates) are taught this nonsense model of "lock and key" receptor-ligand binding.
While the emphasis is on the importance of shape and structure of the receptor matching the ligand, this tells us very little about biochemical signalling! The truth is there are always multiple types of locks (multiple receptors for the same ligand) and many keys (ligands).
Some receptors may bind to ligands that you expect to have different effects (such epeniphrine, acetylcholine, dopamine, serotonin), yet there are receptors that bind to these neurotransmitters that trigger similar cellular signalling cascades (Gi alpha subunit coupled receptors). Secondly, ligands that tightly bind to receptors aren't considered to be agonists, but instead antagonists since they are blocking the signal - the rate of competitive binding determines the rate of signalling!
It's better to think of a single binding event as a small voice in a vast crowd.
The cell too, based on it's response to it's microenvironment (which leads to it's development over time, with respect to it's DNA 'cookbook') determines how it wishes to respond to such signals based on which types of receptors and how many it expresses.
Thus the biochemical signalling of a cell could be imagined more like a vast orchestra, performing a complex composition, rather than a simple biochemical cascade.
But even then, this is just a single cell and tells us nothing about the other trillions of cells in the body. Even if one cell makes a series of persistent mistakes and manages to survive, this itself does not cause disease (even neoplasms are not a purely cellular phenomena). If the symptoms we are trying to predict requires that cells that are on opposite sides of the body are all somehow making the same mistakes, then it is clear we also require a physiological scale explanation. This is why many hypotheses for ME/CFS, such as the "it's the mitochondria" hypotheses fall flat, because at best, they are inherently incomplete.
Genetic causes are the exception (since this defect really is in every cell), but based on epidemiological research and genetic studies so far, this doesn't seem like a strong factor, however the DecodeME study will tell us for sure.
Hypotheses based on persistent latent viral infections, or pathogenic feedback loops induced by prolonged viral infection (in specific physiological regions where those feedback loops can be maintained) are plausible. But this still begs the question, what are the actual feedback loops, why do they persist for years, and how do they explain the symptom kinetics on a physiological level? (and any differences between patients)
On the other side, there are hypotheses that consider the physiological scales, but are lacking at other scales. These are mostly brain-based hypotheses, and include autonomic dysfunction, HPA-axis dysfunction, central sensitivity and so on. These hypotheses often off a simplified description of biochemical pathways in addition to hypothesised phenomena at a physiological scale. Yet they fail to explain the overall pattern of symptoms, and fail to explain what occurs at a cellular level (and the most replicated objective sign so far, the reduction in the gas exchange threshold on the 2 day CPET). Such hypotheses also don't explain why the hypothesised biomarkers are not found in the serum or CFS many patients (abnormal levels of neurotransmitters or hormones).
The remaining hypotheses tend be limited by the lack of ease by which we can experiment on humans. There have been many studies of red blood cells or peripheral blood mononuclear cells, but this testing assumes that these cells will have a pathogenic marker, despite the fact that there are a wide range of cellular microenviroments in the body that are quite different to that of blood circulation. Likewise, it can be difficult to take biopsies of various organs without disrupting the relationship between the cells and their microenvironment.
Lastly, I'd like to point out that the title of the thread is a false dilemma - accumulation of metabolites could be part of a signalling feedback problem.
