Genetic/Proteomics session

Suzanne Vernon, Human Genomics Team Leader at the CDC, defines genomics as the study of function and interactions of genetic material in the genome, including interactions with environmental factors. Genetics on the other hand is the study of a single gene. She then described several gene profiling techniques such as microarrays, gene chips, and RT-PCR. Such advanced techniques are used by the CDC and other to unravel the CFS puzzle.

One of the most helpful techniques recognizes fine variations in the gene, known as Single Nucleotide Polymorphisms or SNPs (pronounced "snips"). For example, a health gene sequence of nucleotides may look like this to a geneticist:   TGCCGAT...

An abnormal gene may look like:   TTCCGAT...

That one small change is referred to as a SNP and can be used: (1) to understand who is predisposed to CFS/ME, (2) as a marker for the illness, or possibly (3) as a clue to a treatment.

Certain polymorphisms are associated with specific groups. For example, Vernon and her group have been able to identify normal healthy patients, persons with general fatigue, and PWCs just on the basis of specific polymorphism patterns. PWCs have then been subclassified into several distinct, genetically defined groups.

CFS/ME is difficult to study, however, because it does not appear to be controlled by a single gene, and the genes change over time (i.e. they are "epigenetic").

Proteomics is the study of intracellular proteins, particularly their structures and functions. While the genome is a rather constant entity, the proteome differs from cell to cell and is constantly changing through its interactions with the genome and the environment.

Genetic Profiles in Severe Forms of FM and CFS was presented by Estibaliz Olano. She and her colleagues at Progenika Biopharma (Barcelona) hypothesized that persons with CFS and FM could be differentiated genetically. From a pool of 2000 subjects they assessed 186 women with FM and 217 women with CFS/ME. These subjects were stratified by special questionnaires into "severe" or "mild-to-moderate" cases. SNP profiling was able to discriminate the severe cases from less severe cases of CFS/ME. These SNPs were related to 6 major genetic areas that fit the clinical understanding of CFS/ME:

• COMT,THP,DOPA,5HT (these genes control neurotransmitters),
• POMC (produces adrenocorticotropin, melanotropes, and melanocyte-stimulating hormone),
• Glucocorticoid and corticotrophin receptors,
• Interleukins (cytokine production),
• NOS (nitrous oxide production),
• TNF (more cytokine production).

Also 15 SNPs were identified that separated PWCs from persons with FM with 53% sensitivity and 95% specificity.

Comment: This work by a commercial lab in Spain is consistent with findings from the CDC (see below) and other genomic studies. Such corroboration makes it more likely that genomics can help us understand CFS/ME/FM, and perhaps will provide a marker for these illnesses.

M.S.Rajeevan reported results from one of the CDC genomic studies. This concluded that SNPs link CFS/ME to HPA axis dysregulation, immune dysfunction, and high levels of allostatic load (that is, chronic stress). 137 subjects were selected from the CDC's Wichita Hospital Study, and these individuals were able to be differentiated into 5 unique classes. Five genomic markers for glucocorticoid receptors were more common in PWCs than in persons with chronic fatigue alone and those who were not fatigued; there were 3 serotonin receptor markers that were associated with CFS as opposed to chronic fatigue or non-fatigued individuals.

James Baraniuk (Georgetown University, Washington DC) studied the proteomics of CFS/ME. He defined a proteome as "a set of proteins in one cell, compartment or person." His hypothesis was that Central Nervous System dysfunction was common in CFS, FM, and Gulf War Syndrome, so abnormal proteins would probably appear in cerebrospinal fluid (CSF). He studied the CSF of 52 subjects, most of whom met international criteria for CFS/ME.

In his first experiment, 10 proteins were identified as shared between CFS/ME and GWS, but totally absent from healthy individuals. The second experiment demonstrated that keratins (which are rare) and orosomucoids were seen in PWCs, but not in controls. Ten proteins found in the first cohort of PWCs matched the protein abnormalities in the second cohort. Baraniuk estimated that the chance of this occurrence was about one in one million!

Baraniuk found proteomic evidence for: protease-anti-protease imbalance, structural injury, oxidant injury, vascular deregulation, leptomeningeal activation, and structural repair. In conclusion, the common "CFS-related proteome" in cerebrospinal fluid suggests shared pathophysiology in CFS, FM, and GWS. This proteome is NOT found in healthy control samples.

Lastly, Frederick Albright (University of Utah) used geneology to provide evidence of a heritable contribution in CFS/ME. The Mormon geneology database includes 2.2-million Utah Mormon pioneers and their descendants over 10 generations, and health records have been linked to the geneology since 1994. Thus it is possible to follow the inheritance of CFS over at least 16 years. Albright identified 551 descendents with CFS (65% female, 35% male).

He first hypothesized that if CFS is heritable, it should occur at higher frequency in close relatives of CFS cases. In fact, the risk of a first degree relative contracting CFS was 7.68X, while the risk for a second degree relative was 2.54X. This suggests that CFS is indeed heritable.

The second hypothesis was that if CFS is familial, CFS cases should be more closely related than controls. Using sophisticated analysis, he demonstrated that case-relatedness was 4.13 units and control relatedness was 2.81, which was statistically significant. Thus CFS/ME appears to be familial as well as heritable.

New Methods

One of the most fascinating and practical papers was given by Akikazu Sakudo of Osaka University, where he works with H. Karutsune,Y. Watanabe, and others. Sakudo described using visible and nearinfrared spectroscopy (which is typically used to examine fruit for ripeness and quality) to discriminate PWCs from normal healthy controls. Both serum scan and a simple scan of the thumb were obtained and then analyzed using "principal component analysis" (PCA) and "soft independent modeling of class analogy" (SIMCA) statistical techniques. The result was a clear separation of normal healthy persons from persons defined by international (Fukuda or CDC) criteria to have CFS/ME.

Comment: This is like Star Trek! Using a simple handheld gun-like apparatus, Japanese researchers scanned a test tube of serum or simply scanned the patient's thumb, and immediately the Vis-NIR Spectroscope could predict whether or not the patient had CFS/ME. This technique takes less than one second to perform, and requires no skill on the part of the examiner! Although the spectroscope identified 100% of healthy individuals and 42 of 45 PWCs (93%), it is not known yet if the technique can separate PWCs from persons with other illnesses like MS, rheumatoid arthritis, and depression. If successful, this relatively inexpensive (US $3000-8000) and harmless device could provide rapid definitive diagnosis and finally silence the skeptics. [Thank goodness Vir-NIS spectroscopy can't treat, or I might be put out of a job by a machine!]