About the Research

What is Chronic Fatigue Syndrome (CFS)?

 

Chronic fatigue syndrome (CFS) is a complex disorder characterized by intense fatigue (exhaustion, lack of energy) that is not improved by bed rest and that is worsened by physical or mental exertion. It is often accompanied by muscle and joint pain and weakness, sleep disorder, sore throat, severe headaches, sensory sensitivities, digestive, respiratory and cardiac problems, and cognitive impairments.  People with CFS often function at a substantially lower level than before they became ill.  Many are completely bedridden, unable to live productive lives or even engage in any social relationships, requiring a wheelchair even for short distances, care-givers for necessities such as meals and laundry, and home visits by doctors. Even talking or listening to conversation becomes too tiring. After multiple attempts at getting medical help, patients retreat to their homes and suffer for years out of view of society. This very debilitating disease affects as much as 1 percent of the world’s population, an estimated 1 to 3 million cases in the U.S. alone. In spite of the extreme pathology, the medical community has largely ignored this disease. Its cause is unknown.  There is no molecular diagnostic test, so it’s difficult to diagnose the myriad, nonspecific symptoms of the disease and these symptoms are often misinterpreted by physicians.  There is no treatment. Due to this lack of information and misunderstanding, CFS is not always recognized as a legitimate disease, and research is consequently seriously underfunded.  It is the last of the world’s prevalent diseases to have so little understanding.

 

What is the CFSRC?

 

The Chronic Fatigue Syndrome Research Center at Stanford has been created within the Stanford Genome Technology Center, which has pioneered an interdisciplinary approach to developing innovative technologies and analytic tools to address previously unsolvable biological problems. The CFSRC will focus this expertise on discovering a diagnosis, causes and cure for Chronic Fatigue Syndrome.

 

A Paradigm Shift for Research

 

Since there is so little funding for CFS, past research has largely focused on proposing a seemingly reasonable hypothesis for a possible cause, suggesting a potential treatment, and then testing that treatment on a few patients, often with no costly control groups. Due to the lack of significant basic research knowledge to guide them, scientists and doctors have been forced to use a “trial and error” approach when creating these hypotheses.   In the past, our knowledge has also been limited by the available technology. Now, however, as a result of the Human Genome Project, there are numerous new technologies for collecting and analyzing massive amounts of data. These new technologies need to be applied to CFS in a systematic manner. The Stanford Genome Technology Center has developed many of these technologies, not only for genetic information but also for immunology and infectious disease. We are known for our extensive collaborations with researchers throughout the world. We are therefore uniquely positioned to launch a comprehensive, interdisciplinary investigation in pursuit of diagnosis, causes and cure for CFS.

 

CFSRC Research Strategy

 

The proposed research will begin with a focus on collecting llarge amounts of molecular information, creating a molecular diagnostic test and using this information to work toward a treatment and then a cure. We will propose reasonable hypotheses but instead of specifically testing each hypothesis we will collect a massive amount of information on CFS patients, other-disease and non-disease “control” patients that will not only test the hypothesis but also allow enormous opportunity to discover new facts about CFS that will generate more focused hypotheses. These discoveries could rule out other hypotheses without further experimentation and might allow new ideas about the causes of CFS. For example, it is reasonable to propose that CFS is caused by a mitochondrial germ line mutation. To test this hypothesis, we will not only sequence the mitochondrial DNA, we will also sequence the entire genome of CFS patients. This will include the 1600 nuclear encoded mitochondrial genes, the more than 20,000 other genes, and the even more numerous control regions that regulate the genes. This sequencing creates the opportunity to discover DNA sequences that might be altered in CFS patients. This in turn could aid in generating a diagnostic test and open new possibilities for treatment and a cure.

 

In addition, the following analyses will be conducted:

 

  • quantitating gene expression from all the cell types in the blood

  • identifying and quantitating proteins that are found in the immune cells and blood serum

  • quantitating all the small molecules (about 2000) in the blood and urine

  • a similar analysis on spinal fluid

  • search for infectious agents in the blood, bone marrow, spinal fluid and saliva by massive sequencing

  • identifying the DNA sequence of all of the components of the immune system, including the HLA sequence, the sequence of all the antibody molecules, and other immune cell-types

  • identification of intestinal flora by massive DNA sequencing

  • analyze the small molecules in the body to ascertain which are human and which are from gut microbes.

  • look for molecular evidence of autoimmunity by analyzing immune complexes and screening produced antibodies against Human proteins.

 

With our extensive computational, statistical and analytic resources, we are able to extract significant patterns and information from enormous, complex data sets.

 

Collection of Molecular Data

 

We will use state of the art technology for all of the analyses to collect the highest quality data at the lowest cost. Our approaches will be of such quality and completeness that other researchers will not have to repeat our experimentation until newer technology is developed in the future. We do not believe in the “quick and dirty” approach that is seen in some research projects in which researchers use technology and procedures that generate low quality data with many inaccuracies. In contrast, quality, precision and reproducibility of data are our highest priority. For example, a number of researchers have monitored gene expression from blood leukocytes for CFS and other diseases using DNA microarray technology. Some researchers have used “home-brewed” arrays that contained only a fraction of the genes in the genome. The FDA has determined that these home-brewed arrays contained many mistakes (on average 25% wrong sequences). Due to this high level of inaccuracy, if one wants to know which genes are affected in CFS and by how much, the experiments using that technology would have to be repeated. This wastes valuable resources. We deplore the idea of some scientists who think, "I’d rather be first than be right.” In contrast, we are committed to being careful and accurate. We use technology that has 0% wrong sequences. We use the latest DNA microarray, which we co-developed, that examines every known exon in the human genome. We will also use RNAseq technology on a few patients (it’s more expensive and extremely slow) to make certain we did not miss anything. If we do not have access to state of the art technology for a particular assay we will seek a collaborator at Stanford, or at another institution, be it academic or industrtial.



Collaboration

 

We are currently collaborating with Andreas Kogelnik, MD, using patients from the Open Medicine Institute and with Jose Montoya, MD, using patients from Stanford. These collaborations and our ability to analyze massive amounts of data simultaneously enables us to use data that has been collected on one set of patients and control subjects at one location with the same set of investigators. This eliminates the large amount of variance inherent in past research, in which each different analysis (or assay) was completed on different patients, at different locations, with different investigators. An example of the benefits of this approach is that a diagnostic test might be developed from measurements from more than one data set collected simultaneously, which would not be possible if the data were collected from different sources at different times. Other similar collaborations are in process.

 

New Strategies for Diagnosis

 

At present, the criteria for diagnosing CFS are not very specific, and they are similar to a number of related diseases.Thus, patients diagnosed with CFS might have different diseases, but be lumped together due to this lack of specificity. The possibility of CFS patient heterogeneity could explain in part why it has been so difficult for the medical community to understand and treat this disease. If the CFS patient population turns out to be a manifestation of multiple different causes, then the molecular data that are collected from that population will be mixed, which in turn will prevent the development of a specific diagnostic test. We need some metric to stratify the CFS population into homogeneous groups. At the CFS Research Center, we would like to tackle this problem. One approach is to use patients that have clearly responded or clearly failed to respond to various drug treatments. If a patient responds to a particular drug treatment, they are probably more similar in cause and more likely to belong to a homogeneous group. The non-responders to the particular drug could be in a different homogeneous group or they could still be heterogeneous. This approach has the advantage that, if a diagnostic set of molecular markers can be found for responders to a particular drug, then it also provides a determination as to which drug has the best chance of working. Because some of the treatments are long and/or somewhat debilitating, this determination could be very beneficial to patients, who would not be unecessarily exposed to treatments to which they are unlikely to respond.  We first will generate responder and non-responder CFS patient groups for the drug Rituxan. A second set of patients will also be generated for analysis: those that improve, stay the same or get worse with Valcyte. Sample collection and archiving has already commenced and will await drug outcome before analysis.  If this type of CFS patient stratification indicates the CFS population is in fact heterogeneous, then we must focus on the cause, diagnosis, treatment and cure for each homogeneous group. We will explore many other ways of differentiating CFS patients into homogeneous groups to look for unique biomarkers.

 

Search for Genetic Cause

 

We will first look for a genetic cause or contributor to CFS and/or a genetic cause of differential drug response. This will involve whole genome DNA sequencing from patient and control groups.  We will analyze for chromosomal rearrangements, deletions, additions, inversions, base differences and an unusual arrangement of common alleles.  Because we would expect a large number of differences between any two individuals it will be difficult to associate any observation with a cause or a component of a diagnostic test without a large sample set.  The DNA sequence for the HLA region has a good chance to give clues to a cause or a useful diagnostic marker because it is a major control site for immune regulation.  Our lab has developed the special procedures that this complex HLA region requires to get accurate sequences. We will also sequence the mRNA and catalogue all alternative splices.  We will conduct the sequencing from isolated cells from patient and controls while at rest and after limited exercise.  A unique alternative splice could give hints to the origins of and a diagnostic marker for CFS. It is also possible and even likely that some of the DNA sequences become methylated, which can inactivate some genes and could account for the persistence of the disease.  We will compare methylation patterns between patients and controls.

 

Search for Microbial Cause

 

We will look for unusual and unknown microbes including viruses, bacteria, fungi and parasites.  We will use PCR for known organisms and DNA sequencing to discover unknown organisms.  We will examine the blood, saliva, spinal fluid, bone marrow, lymph fluid, urine, stool samples, and internal body sites such as tonsils and lymph nodes.We will search for unusual small molecules or an unusual concentration of normal small metabolites.

 

Multidisciplinary Collaboration: Best hope for Breakthrough

 

This approach and collaboration will include scientists and doctors who are experts in a wide range of body systems, including neurological, gastro-intestinal, immunological, musculo-skeletal, cardio-vascular, lymphatic, endocrinological, respiratory, sleep, and a diversity of disciplines, including genetics, biology, biochemistry, immunology, infectious disease, statistics, computer science, and engineering, Such a comprehensive, interdisciplinary effort holds great promise for significant breakthroughs in our understanding and treatment of CFS.

More in this category: « About CFS Ronald W. Davis »
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