Functional Genomics of Serotonin Receptor 2A... & CFS

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Latest from the CDC:

Functional Genomics of Serotonin Receptor 2A (HTR2A): Interaction of Polymorphism, Methylation, Expression and Disease Association

Virginia R. Falkenberg, Brian M. Gurbaxani, Elizabeth R. Unger and Mangalathu S. Rajeevan

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Abstract
Serotonergic neurotransmission plays a key role in the pathophysiology of neuropsychiatric illnesses. The functional significance of a promoter polymorphism, −1438G/A (rs6311), in one of the major genes of this system (serotonin receptor 2A, HTR2A) remains poorly understood in the context of epigenetic factors, transcription factors and endocrine influences. We used functional and structural equation modeling (SEM) approaches to assess the contributions of the polymorphism (rs6311), DNA methylation and clinical variables to HTR2A expression in chronic fatigue syndrome (CFS) subjects from a population-based study. HTR2A was up-regulated in CFS through allele-specific expression modulated by transcription factors at critical sites in its promoter: an E47 binding site at position −1,438, (created by the A-allele of rs6311 polymorphism), a glucocorticoid receptor (GR) binding site encompassing a CpG at position −1,420, and Sp1 binding at CpG methylation site −1,224. Methylation at −1,420 was strongly correlated with methylation at −1,439, a CpG site that is dependent upon the G-allele of rs6311 at position −1,438. SEM revealed a strong negative interaction between E47 and GR binding (in conjunction with cortisol level) on HTR2A expression. This study suggests that the promoter polymorphism (rs6311) can affect both transcription factor binding and promoter methylation, and this along with an individuals stress response can impact the rate of HTR2A transcription in a genotype and methylation-dependent manner. This study can serve as an example for deciphering the molecular determinants of transcriptional regulation of major genes of medical importance by integrating functional genomics and SEM approaches. Confirmation in an independent study population is required.


This study uses patients from the 2006 CDC Pharmacagenomics study, 1994 CDC criteria but with suspicions about how the CDC actually applied these criteria esp re low fatigue thresholds to qualify.

Basically, they didn't find much other than a weak association and given doubts over the sample, and the fact that they were looking at expression of the Serotonin Receptor gene in blood (PBMC), rather than the CNS (and gut?) where it is normally transcribed, this probably doesn't amount to much.

I was struck by this:
we applied structural equation modeling (SEM), a statistical approach that has been widely used in the psychosocial sciences

I'm sure that's what the field of Genomics has been missing until now: statistical approaches from the psychosocial sciences.
 

Dolphin

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This study uses patients from the 2006 CDC Pharmacagenomics study, 1994 CDC criteria but with suspicions about how the CDC actually applied these criteria esp re low fatigue thresholds to qualify.
"Subjects were classified according to the 1994 research case definition as evaluated by standardized questionnaires (Reeves et al. 2005)."
This is the empiric criteria. It boosted the prevalence the CDC got for the illness from 0.235% to 2.54%. It's the one Lenny Jason has researched and complained about. However, the Wichita cohort isn't as "bad" as the Georgia cohort as they were chosen from a group which contained a lot of people who had satisfied the 1994 definition at one stage. It's in between the two in its dilution.
 

Otis

Señor Mumbler
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I was struck by this:
we applied structural equation modeling (SEM), a statistical approach that has been widely used in the psychosocial sciences

I'm sure that's what the field of Genomics has been missing until now: statistical approaches from the psychosocial sciences.
Yes, definitely value-add. :eek: So glad (NOT) to see Dr. Unger picking up where Reeves left off.
 
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"Subjects were classified according to the 1994 research case definition as evaluated by standardized questionnaires (Reeves et al. 2005)."

This is the empiric criteria.
Well spotted - so that makes it an even bigger waste of time.
 

Jenny

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It is good news that medical researchers are using statistical analyses used in the social sciences. Social science is way ahead of medical research in research methodology and analysis.

Jenny
 
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I suppose its encouraging that this research from the CDC looks at possible biomedical causes (in this case genetic) of CFS, just a shame that their watered-dwon case definition and suspect methodology makes this particular study rather pointless.
 

Dolphin

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I suppose its encouraging that this research from the CDC looks at possible biomedical causes (in this case genetic) of CFS, just a shame that their watered-dwon case definition and suspect methodology makes this particular study rather pointless.
Yes, one of the problems of their watered-down definition is that it can put other people off looking at an area, or it can look like there are conflicting results (if one or more research teams look at the area). So even if they are doing what might be "interesting" biomedical research, it can still cause problems. :(
 

willamedico

Shalon Simmer
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It is good that medical researchers are using statistical analysis that definitely benefit them as in time consuming sense. There are also certain advantages and disadvantages.