@Jonathan Edwards
First, I should say that I appreciate having doctors and researchers present on these forums. I also agree with you that we need a fair dose of scientific skepticism. I'm skeptical of my own theories as well as yours and just about everything else out there. What is obvious is that we do not really understand ME - so skepticism about any proposed theory is mandatory. I am using the tools I have at my disposal to try to understand. That doesn't include a well funded lab - so unfortunately I cannot test at each step, as I'd like to do. The reason we have so many different ideas going in so many different directions in the field of ME research is that we do not have the funding to do high-powered, well designed studies to test hypotheses, and discard those that fail. XMRV is an exception - a testable hypothesis that failed, AND was sufficiently well funded so that now all but a few have abandoned it. I do think there can be a tendency to build a house of cards if you make a reasonable, plausible jump, but then lack the funding to prove or disprove it, and then build on that, over and over. These are problems that can only be addressed by funding and the research community taking ME more seriously. I'm not in a position to make that happen right now - you may be to some degree, although it is a Herculean task and there are very few if any individuals who can drastically alter perception of ME, but you can probably do a lot more than I to help.
Immunology is complicated - and we don't understand it all yet. One of my immunology professors used to like to say, "Most of the most brilliant minds in medicine that I have known went into immunology, where they were never heard from again." It's not a discipline that lends itself to very simple models.
I think we're going to have to disagree on the T-helper subsets for now. I find the evidence in peer reviewed journals and immunology texts very persuasive. It should, however, be thought of as a model. e.g. Not every patient with multiple myeloma has the same molecular pathology (is it a translocation, point mutation, hyperdiploidy, etc.), but it does converge on a common pathway. Still, we lump them together, and it allows us to treat them. Most hematologists use the same induction therapy on all patients who are pursuing an aggressive course of treatment, which is probably a proteosome inhibitor, an imid, maybe an aklylating agent, and dex - because they generally work, regardless of the exact molecular pathology. Right now, we classify cancers largely by tissue of origin - and it is a helpful model - but eventually, we will analyze the specific mutations, and that will be a better model. A better model that creates more subtypes can tailor therapy more effectively, but it's impractical to subdivide the model to the point where every human being is his/her own category. We must strike a balance. Medicine is all about categorization - the model is used as long as it predicts results accurately. When it doesn't you go deeper, until you're working at a molecular level. Since none of us can really claim knowledge of every amino acid residue of every protein in every human being, how they all interact, etc., we cannot go that deep all the time. The complexity is too great. We must always develop models to describe phenomena and predict results. The Th17 model predicts the efficacy of IL-17 and IL-23 mabs - which seems to work. That doesn't mean that it completely describes everything. We do know that in humans there are master transcriptional regulators of different CD4 immune profiles, and we can demonstrate their binding to DNA and promoting transcription of the cytokines we consider to be part of different subsets of cells. e.g. T-bet for Th1, GATA-3 for Th2, RORC for Th17 and FoxP3 for Treg. I wouldn't claim this explains everything, only that it is a useful model for understanding what is happening. There is also a great deal of plasticity in the model - cells may switch from one profile to another (Treg's are subclassified as induced or natural Tregs). However, there is evidence for a certain degree of discreteness - stimulation of naive CD4 Th cells with both Th1 and Th2 polarizing cytokines, over a wide range of quantities of each, yields a Th2 cell that produces Th2 cytokines. The switch appears to be binary, and GATA-3 appears to directly bind to DNA and prevent transcription of T-bet.
M. leprae modifies the host's immune response for survival (not uncommon in general among pathogens). Being intracellular, a humoral response won't be very effective. However, why do some people develop one form and others another? We also know that genetics plays a major role - so it's generally the same pathogen reacting to different immune systems that yields different results. The pathogen has the same bag of tricks in each person - the clinical phenotype of the individual is not just determined by variation / strain in the pathogen. We know, for example, that polymorphisms in the TNF-alpha promoter (-308) can have very large effects on the likelihood of development of lepromatous or tuberculoid leprosy. If you prefer, you can think of this at the cytokine level. Either model will work in many cases.
In reference to seronegative spondyloarthritides, by MHC molecules I presume you are referring to HLA-B27 and related molecules - which clearly play a major role. Let's take B27 since it's the prototypical example, say 2705 - a high susceptibility variant common in Europeans. We know that it is present in the vast majority of AS cases (90% or so, I think). However, the converse is not true - the vast majority of B27 carriers do not develop AS or related diseases. We have found other genes that are involved, although we cannot explain all of the genetic risk. One of those polymorphisms is a receptor for IL23 - and we know that IL-23 does make CD4 cells make IL-17 - which, if you block, improves symptoms. Also, if you block the IL23, it improves symptoms. The effects in psoriasis - also autoinflammatory - have been dramatic with sekukinumab - far surpassing TNF blockers. In this case, Th17 models do predict responses. Furthermore, they predict that if one responds to one (of 17/23), there is a good chance one will respond to the other. Interactions between cytokines need to be understood, and to understand that we have to understand how each cytokine changes the cytokine production of other cells, and which cytokines tend to be produced together by a given cell.
Back to RA for a bit - you say nothing was ever found to be wrong with T-cells. I'm not exactly sure what that means - what was looked at, etc. You suggest that B-cell feedback is relevant, which would be consistent with the success of rituximab in treatment of RA. However, abatacept prevents T-cell activation, and is also effective in RA. TNf-alpha blockers work - but TNF-alpha is expressed by many immune cells. The way I think of it is that each individual is an array of polymorphisms that create a different balance in each person. One person may be resistant to a type of disease while another is susceptible. Environment plays a role, as does pure, quantum mechanical randomness. By targeting any number of cytokines, we can alter that balance - and right now, the results are often still unpredictable. I do not believe that any disease is purely a disease of CD4 T-cells (rheum disease - I suppose HIV is mostly a CD4 disease, although glial cells are affected too). I do believe that in rheumatic disease, T-cells play a role. You can target that role to modify the function of the whole system, or you can target other cells (say, B-cells, in RA). It doesn't necessarily matter. If I have four guys holding up a heavy piece of furniture at the 4 corners, if I knock out the legs of any of the 4, the furniture will fall. We all have Il-17 and Th17 cells that make it, but we don't all have rheumatic disease. Some people, especially with diseases like AS, have only the mildest forms and it is never diagnosed - others face a rapid progression to extreme disability despite aggressive therapy. While a given cell's polarization may be, for a time, binary, the mixture of cells and cytokines is constantly changing. It may be that Il-17 levels are normal in some people with AS - but reducing them can still help.
There are multiple ways to categorize macrophages. I can classify my books by color, by number of pages, by author's last name, or by height. They are all valid ways to classify books. I would say there are a number of ways to categorize macrophages. With flow cytometry, we now love to count cells based on clusters of differentiation. You can now run panels for lymphocyte subsets and such - they run them in ME sometimes, although I'm not sure of their clinical usefulness. So looking at CD16 expression is interesting, and probably tells us about the transcriptional regulators that are active in that cell, and thus the cytokines and other proteins it is producing and secreting. It's one interesting, and probably useful, way of categorizing macrophages - but I don't think it's the only one. Has that model worked in ME? If not, then either a) there is nothing to find in ME re: macrophages or b) there is something to find, but another model is necessary. I don't know much about your personal research in RA, but it may be specifically relevant to RA.
Your comments on gout are interesting. It supports the idea that cytokines are made by a wide array of cells acting cooperatively. Most if not all cytokines are produced by more than one cell type - although relative importance may vary.
Are you implying a lack of respect for immunology as a discipline? As all of us, you come to the table with a preconceived set of ideas, largely shaped by your training and experience. True of me as well of course. I think we all need to challenge ourselves to go beyond that. When one scientist claims something, the other is always justified in requesting proof (or evidence at least). Skepticism to a degree is healthy, but too much skepticism can be a problem. As a rheumatologist, you think in terms of certain disease paradigms. You've developed a model - one that works - for treating your patients. You probably also have realized that your current understanding of disease has not worked to date in effectively treating ME patients. That you've come here shows a willingness to try to understand the disease better by listening to patients and trying to formulate new hypotheses. I would argue, however, that we may need to break out of the normal mold a bit to explain this disease. If it were a minor variation on a common theme of well understood illnesses, I think we'd have figured it out. Some degree of out of the box thinking is beneficial, tempered of course by scientific skepticism - and ultimately driven by a desire to find the truth. Over the years I have entertained a number of theories about ME. Some were discarded due to contradictory evidence. Others remain plausible but unproven. The simple fact is that we do need to think outside the box, because thinking in the box has not yielded any good answers - and by now, it should have. All that advice applies equally to me - I need to remain skeptical, but also open minded, and listen to new points of view, and I need to be willing to abandon preconceived notions when evidence does not support them.