ljimbo423
Senior Member
- Messages
- 4,705
- Location
- United States, New Hampshire
I did a search and couldn't find this posted. Very interesting view of cytokines in ME/CFS! Michael B. VanElzakker* seems to be the lead Author.
Neuroinflammation and Cytokines in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS): A Critical Review of Research Methods
Michael B. VanElzakker*, Sydney A. Brumfield and Paula S. Lara Mejia
https://www.frontiersin.org/articles/10.3389/fneur.2018.01033/full
Neuroinflammation and Cytokines in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS): A Critical Review of Research Methods
Michael B. VanElzakker*, Sydney A. Brumfield and Paula S. Lara Mejia
- Division of Neurotherapeutics, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
The Same Exact Lab, Personnel, and Protocol Will Likely Get Different Results From the Same Manufacturer's Kit
Assuming that there actually is a predictable, consistent peripheral “cytokine profile” in a complex illness such as ME/CFS, one potential solution to some of the above-described issues is if a single lab were to use the exact same techniques, equipment, and procedures across multiple studies, or if different labs standardized these procedures.
However, empirical evidence shows that this is not the case. An experienced immunology lab, led by a PI with decades of experience and over 100 publications, conducted a within- and between-lab comparison study. Breen et al. (188) compared the ability of four multiplex kits to detect 13 cytokines in human plasma and serum.
The four kits were tested on the same sample across six different laboratories and across multiple lots of the same kit. Their results showed a large amount of variance both within the same lab and across multiple labs. While all 13 cytokines were detected by at least one kit, none of the kits were able to detect all 13 cytokines.
Additionally, their results alarmingly indicate that each cytokine within each multiplex kit had at least one significant lab and/or lot effect. In other words, measuring the same sample twice with the same kit in the same laboratory following the same strict protocol yielded significant differences in absolute cytokine values (Figure 2).
Cytokines Can Be Highly Influenced by Individual Behavior
A final note of warning against overinterpreting studies of peripheral cytokines is that study participants can contribute noise in myriad ways. Factors that can significantly affect circulating cytokine levels within an individual include: time of day (192–194), status of alcohol, nicotine, or other drug use (195–201), quality and amount of sleep (202), acute and chronic stress (203), acute and chronic fitness habits specific to type of exercise (204–206), sex (207, 208), phase of menstrual cycle (209, 210), age (211), chronic dietary patterns (212), and acute differences immediately following a meal (213, 214).
Thus, even eating a spicy burrito with extra guacamole the day of sample collection will result in a different cytokine profile than eating Indian food or a slice of chocolate cake. A research participant adding sour cream to the mashed potatoes they had for lunch will alter their cytokine profile.
Capsaicin, the main source of heat in hot peppers, alters levels of IL-6, IL-10, TNFα, NOx, and MDA (215), and the natural sugars in avocado alter gene expression of IL-1α, IL-6, and IL-8 (216, 217). The bacteria used in dairy (i.e., the sour cream on the mashed potatoes) increase IL-1β, TNFα, and IFNγ (218, 219).
Cumin, a spice commonly used in Indian cuisine, reduces expression of inflammatory cytokines CXL-1 and−2, TNFα, IL-1β, IL-6, and IL-18 (220, 221). Chocolate increases IL-10 and IL-1β (222). Clearly, cytokines can be affected by a huge number of variables unrelated to disease.
This type of variance, driven by individual behaviors, could be reasonably well explained in a single study using a within-subjects design. However, it can prevent comparability across studies that use different designs. For example, a study that collects blood samples during fasting cannot be compared to studies of non-fasting individuals undergoing exercise challenge. This type of variability in study design is widespread in the ME/CFS cytokine literature (see Table A1).
Conclusion
The above review focused on neuroinflammation and the methods used to measure it. We argued for the importance of anchoring methodological details in known biological mechanisms and existing research literature.
The ME/CFS research field has been stuck in a somewhat defensive posture, with a focus on demonstrating “this is a real condition” by showing significant biological differences between patients and controls. We believe this has led to a situation in which too much is made of the specifics reported by descriptive studies (such as the average “cytokine profile” present in cases vs. controls at the moment of assay) and not enough emphasis has been placed on potential mechanisms driving symptoms. The field is ready to move past proving “this is a real condition” and to start elucidating the specific relationship of ME/CFS symptoms to neuroinflammation.
Moving past a defensive posture and toward understanding pathophysiology requires careful focus on research methods. In designing a study, a goal of ME/CFS researchers should be to determine if a significant result can actually inform disease mechanisms, or if it is simply a reportable difference between patients and controls.
For example, a PET study of TSPO binding may find differences between patients and controls when using a cerebellum reference, and this holds some value for the “this is a real condition” argument. But because of the difficulty in interpretation, such a study is less valuable for discerning actual pathophysiology.
In consideration of neuroinflammation-related mechanisms and research methods, the following recommendations emerge:
• The relationship of ME/CFS to neuroinflammation is a fundamental question that needs to be directly addressed from multiple research angles.
• The existing neuroinflammation basic science literature should serve as a guide for choosing ROIs in ME/CFS brain scan studies.
• ME/CFS causes changes to patients' lives that could accidentally be explaining some study results (i.e., sedentary lifestyle or diet can affect cytokines). This makes careful selection of control groups particularly important.
• Cytokines seem attractive because they are easy to collect and measure, but are a very noisy variable and the specific findings of any given study should not be overinterpreted.
• Some methodological details are so fundamental (e.g., brainstem registration, or selection of a “baseline” reference brain region or metabolite, or choosing between blood serum and cerebrospinal fluid) that they can be completely responsible for a study's results or lack thereof.
https://www.frontiersin.org/articles/10.3389/fneur.2018.01033/full