Cerebral blood flow velocity not involved in POTS neurocognitive impairment

Increasing orthostatic stress impairs neurocognitive functioning in chronic fatigue syndrome with postural tachycardia syndrome.
Ocon AJ, Messer ZR, Medow MS, Stewart JM.

Abstract
CFS (chronic fatigue syndrome) is commonly co-morbid with POTS (postural tachycardia syndrome).

Individuals with CFS/POTS experience unrelenting fatigue, tachycardia during orthostatic stress and ill-defined neurocognitive impairment, often described as 'mental fog'.

We hypothesized that orthostatic stress causes neurocognitive impairment in CFS/POTS related to decreased CBFV (cerebral blood flow velocity).

A total of 16 CFS/POTS and 20 control subjects underwent graded tilt table testing (at 0, 15, 30, 45, 60 and 75°) with continuous cardiovascular, cerebrovascular, and respiratory monitoring and neurocognitive testing using an n-back task at each angle.

The n-back task tests working memory, concentration, attention and information processing.

The n-back task imposes increasing cognitive challenge with escalating (0-, 1-, 2-, 3- and 4-back) difficulty levels.

Subject dropout due to orthostatic presyncope at each angle was similar between groups.

There were no n-back accuracy or RT (reaction time) differences between groups while supine.

CFS/POTS subjects responded less correctly during the n-back task test and had greater nRT (normalized RT) at 45, 60 and 75°.

Furthermore, at 75° CFS/POTS subjects responded less correctly and had greater nRT than controls during the 2-, 3- and 4-back tests.

Changes in CBFV (cerebral blood flow velocity) were not different between the groups and were not associated with n-back task test scores.

Thus we conclude that increasing orthostatic stress combined with a cognitive challenge impairs the neurocognitive abilities of working memory, accuracy and information processing in CFS/POTS, but that this is not related to changes in CBFV.

Individuals with CFS/POTS should be aware that orthostatic stress may impair their neurocognitive abilities.

Alas, the sample size is a bit smallish…

(via ProHealth)

"Infectious mononucleosis-like syndrome probably attributable to Coxsackie A virus infection"

Infectious mononucleosis-like syndrome probably attributable to Coxsackie A virus infection

Burke A. Cunha, Nardeen Mickail, Andrew P. Petelin,

Infectious mononucleosis (IM) is a clinical syndrome most often attributable to Epstein-Barr virus (EBV).

Characteristic clinical features of EBV IM include bilateral upper lid edema, exudative or nonexudative pharyngitis, bilateral posterior cervical adenopathy, and splenomegaly ± maculopapular rash.

Laboratory features of EBV IM include atypical lymphocytes and elevated levels of serum transaminases. Leukopenia and thrombocytopenia are not uncommon.

The syndrome of IM may also be attributable to other infectious diseases, eg, cytomegalovirus (CMV), human herpes virus-6 (HHV-6), or Toxoplasma gondii.

Less commonly, viral hepatitis, leptospirosis, brucellosis, or parvovirus B19 may present as an IM-like infection. To the best of our knowledge, only 2 cases of IM-like infections attributable to Coxsackie B viruses (B3 and B4) have been reported.

We present the first reported case of an IM-like syndrome with sore throat, fatigue, atypical lymphocytes, and elevated levels of serum transaminases likely due to Coxsackie A in an immunocompetent adult.

Hat tip to Tom Kindlon / CO-CURE

(But one person? So they showed in one person that Coxsackie A can do this?)

23 new drug applications in the US in 2008

Consider two numbers: 800,000 and 21.

The first is the number of medical research papers that were published in 2008. The second is the number of new drugs that were approved by the Food and Drug Administration last year.
…
And before anyone jumps to pin the blame on the F.D.A., it’s important to note that it’s not just new drug approvals that have declined — new drug applications have, too. Last year the F.D.A. received just 23.

Here are the conditions treated for those 23 drugs:

•  Diabetes Mellitus Type II (about 25 million people in the US)
•  Breast Cancer (1.35 million people in the US)
•  Rheumatoid Arthritis, Juvenile Idiopathic Arthritis (about 1 million people in the US)
•  Prostate Cancer (965,000 people in the US)
•  Schizophrenia (430,000 people in the US)
•  Allergic Conjunctivitis (425,000 people in the US)
•  Osteoporosis (416,000 people in the US)
•  Gout (385,000 people in the US)
•  Multiple Sclerosis (384,000 people in the US)
•  Cervical Dystonia, Blepharospasm, Glabellar Lines (about 30,000 people in the US)
•  Dupuytren’s Contracture (21,100 people in the US have this)
•  Gaucher Disease (10,600 people in the US)
•  Reduction of Excess Abdominal Fat in HIV-Infected Patients with Lipodystrophy (5000 people in the US)
•  NAGS Deficiency Hyperammonemia (320 patients per year diagnosed)
•  Pompe disease (90 patients in the US have this)

•  Contraception
•  Prevention of Thromboembolism in Atrial Fibrillation
•  Varicose Vein
•  Pneumonia, Skin and Structure Infection
•  Postcoital Contraception

ME/CFS Study: EEG spectral coherence data distinguish chronic fatigue syndrome patients from healthy controls and depressed patients - A case control study

You have to hand it to Anthony Komaroff, he makes sure that his work is solid (even if that means moving the research ahead a bit slower...). Not only did he enroll 70 patients with ME/CFS (which already is a lot) and 24 patients with major depression, but furthermore he enrolled 148 (!) patients with "general fatigue" (not evaluated whether they meet CDC/Fukuda) and 390 (!) healthy controls.

EEG spectral coherence data distinguish chronic fatigue syndrome patients from healthy controls and depressed patients - A case control study
Abstract (provisional)

Frank Duffy, Gloria McAnulty, Michelle McCreary, George Cuchural and Anthony Komaroff

Background
Previous studies suggest central nervous system involvement in chronic fatigue syndrome (CFS), yet there are no established diagnostic criteria. CFS may be difficult to differentiate from clinical depression. The study's objective was to determine if spectral coherence, a computational derivative of spectral analysis of the electroencephalogram (EEG), could distinguish patients with CFS from healthy control subjects and not erroneously classify depressed patients as having CFS.

Methods
This is a study, conducted in an academic medical center electroencephalography laboratory, of 632 subjects: 390 healthy normal controls, 70 patients with carefully defined CFS, 24 with major depression, and 148 with general fatigue. Aside from fatigue, all patients were medically healthy by history and examination. EEGs were obtained and spectral coherences calculated after extensive artifact removal. Principal Components Analysis identified coherence factors and corresponding factor loading patterns. Discriminant analysis determined whether spectral coherence factors could reliably discriminate CFS patients from healthy control subjects without misclassifying depression as CFS.

Results
Analysis of EEG coherence data from a large sample (n=632) of patients and healthy controls identified 40 factors explaining 55.6% total variance. Factors showed highly significant group differentiation (p<.0004) identifying 89.5% of unmedicated female CFS patients and 92.4% of healthy female controls. Recursive jackknifing showed predictions were stable. A conservative 10-factor discriminant function model was subsequently applied, and also showed highly significant group discrimination (p<.001), accurately classifying 88.9% unmedicated males with CFS, and 82.4% unmedicated male healthy controls. No patient with depression was classified as having CFS. The model was less accurate (73.9%) in identifying CFS patients taking psychoactive medications. Factors involving the temporal lobes were of primary importance.

Conclusions
EEG spectral coherence analysis identified unmedicated patients with CFS and healthy control subjects without misclassifying depressed patients as CFS, providing evidence that CFS patients demonstrate brain physiology that is not observed in healthy normals or patients with major depression. Studies of new CFS patients and comparison groups are required to determine the possible clinical utility of this test. The results concur with other studies finding neurological abnormalities in CFS, and implicate temporal lobe involvement in CFS pathophysiology.

Over at ME/CFS forums, Forbin has made this observation:

For part of the study, they also recruited patients who complained of prolonged, unexplained fatigue (with other conditions ruled out) but who had never been worked up for CFS. About 45% of those people had results consistent with the CFS group. The paper suggests that this is broadly consistent with a previously published estimate that 35% of such a group might be expected to be classified with CFS. They speculate that “the less than 100% accuracy of our spectral coherence based classification function could reflect a deficiency in the CDC criteria for CFS...”

So it seems to me that at least a one third of "significantly fatigued patients (where no underlying diagnosis can be securely established)" (sfP) suffer from "genuine" ME/CFS – and up to two third of sfP might have something different (or might be patients with ME/CFS who are less symptomatic).

90% of patients with CDC-CFS (diagnosed by Komaroff?) have abnormal EEG. So in the right hands (and with a large enough cohort) the CDC criteria aren't so bad for research (up to 10% false positive and no false negatives), but might be better suited for clinical diagnoses than research.


From what I have read so far, I have a feeling the CCC might reject some patients with "genuine" ME/CFS (and not include false positives) and so might be better for research, especially when in the hands of less experienced researchers... It would be nice if they would do something like this: "xx% of our CFS-subjects qualified for both CDC and CCC. Hindsight analysis showed that CCC improved specificity to yy%, but decreased sensitivity to zz%. ..."

Alan Light 2011 Lecture: Gene Expression Biomarkers for Chronic Fatigue & Fibromyalgia Syndromes

As a follow-up to the last post, here is his 2011 lecture (about 1 hour) by Alan Light for OFFER Utah about his very excellent ME/CFS gene-expression study.

This is objective data that there is biological reason for the symptoms [in ME/CFS and Fibromyalgia].

You may want to switch to 1080p HD to best view the slides.
(Part 1 Part 2 Part 3 Part 4 Part 5)

My take-home messages:

1. 70% of ME/CFS patients have Fibromyalgia (FMS) symptoms. And Fibromyalgia gets worse after exercise, even if the definition for FMS does not specify for it. And a majority of FMS patients (but not all) have ME/CFS symptoms.

2. TRPV1 contributes to the body's temperature set point.

3. Alan Light found a sensory definition of fatigue (The nerves at the muscle tell the brain "You are tired") in ME/CFS that contributes to the desire to use the muscles less. It is related to "actual" muscle fatigue ("The muscle is about to fail"), but it is not the same.

4. In both ME/CFS and FMS there is a 40% subgroup, that has a Ad2A (vasoconstriction) decrease. That gene is responsible for preventing orthostatic intolerance (OI / POTS). 70% patients with this gene expression profile have orthostatic intolerance, and 20% without have POTS (it might depend when and how you measure POTS).

5. FMS without CFS patients look like controls after execercise, but have different baseline levels. P2X4, TRPV1 and IL10 are expressed higher at baseline.

6. Gene expression as biomarker for ME/CFS and Fibromyalgia? Specificity 94% (6% of false negatives) and sensitivity of 65% (35% of false positives), good but not excellent biomarker, could be improved. Might be clinically available within 2 to 3 years.

7. The orthostatic subgroup should be treated differently.

8. Pregabalin or Gabapentin decrease the level of pain and of mental fatigue - maybe.

9. The cause could be increase of sensitivity of fatigue and pain, or dysfunction of the sympathetic nervous system.
(My comment, this the only flaw of Alan Light's work I can think of. He is leaving out one possibility: Of course it could be that there is an actual increase of fatigue and pain due to a pathologically increased muscle exhaustion in ME/CFS and FMS patients. If the nerves are sensing something, it could actually be there – doh!)

10. This is objective data that there is biological reason for the symptoms.
(Translated to English: "The psychosomatic school can go and f*ck themselves.")

As an addendum:
Don't miss Christopher Snell's 2012 lecture, which ties in nicely!

Alan Light 2007 Lecture: The Physiology of Chronic Pain and Fatigue

OFFER Utah (warning, their website plays music...) has a lot of lectures regarding ME/CFS on their OFFER Utah Youtube Channel. They have some very good and interesting lectures (and some less so). If you haven't already, you should subscribe to their Youtube channel, add the feed to your RSS-Reader, etc. ...

One very interesting video is this 44 minutes lecture by Alan Light:

"The Physiology of Chronic Pain and Fatigue" Dr. Alan R. Light.

This presentation by Alan R Light was made during the 2007 OFFER Provider's Conference. This lecture shows basically where Alan Light came from and his studies that lead up to the ME/CFS post-exertional gene-expression study "the Lights" (he and his wife Kathleen Light) have done together with Lucinda Bateman.

I had these take home messages:

1. Acute pain and fatigue sensing are protective and evolutionary important to prevent depletion or injury of important systems. If an living being has an impairment in sensing of pain and fatigue, it will usually die quite quickly. So there are multiple pathways in a living being to measure this information.

2. There are many concepts of fatigue. For ME/CFS fatigue is not sleepiness, fatigue is not failure of the muscle, but a sensory event – one could move the muscle with enough willpower.

3. The sensing of muscle-pain and fatigue happens by nerve sensory-endings located between the muscle and the blood vessels. Several metabolites (Lactate, ATP, pH/protons) are measured together by receptors (e.g. P2X4, P2X5, ASIC3, TRPV1) working together.

4. Fatigue and pain share receptors, but are not the same.

5. The sympathetic nervous system can restrict blood vessels to muscles that are not fatigued and increase blood flow to muscles that are.

6. Mononuclear blood cells have these receptors too, as they need to go "where the action is", where damage is, where things are going wrong and they are circulating through the muscles that are used.

7. Enhanced muscle pain is caused by cytokines, and if the blood flow is not increased (if the sympathetic nervous system does not regulate it properly), the metabolites in the muscles build up, and with it fatigue and pain.

8. The NIH (and the medical profession at general) are not interested and it is very difficult to get funding for these studies. All his research depends on the support by the university of Utah. There is some old medical "knowlegde" ("these receptors don't function at physiological ranges" etc.) that needs to be challenged and updated. This research that should have been done 25 years ago and the NIH is dragging its feet.
(I find it ironic that it is Alan Light's research in ME/CFS that improves the understanding in biological and medical sciences of how pain and fatigue work – after all the damage that Strauss et. al. have done with their psychosomatic bullshit, after all the damage Wessely and Sharpe are still doing today)

Don't miss Alan Light's 2011 follow-up lecture!

And don't miss Christopher Snell's 2012 lecture, which ties in nicely!