Exploratory Subgrouping in CFS:

Infectious, Inflammatory, and Other

 

Karina M. Corradi, Leonard A. Jason,* Susan R. Torres-Harding


* Corresponding author: Leonard Jason, Ph.D. DePaul University, Center for Community Research, 990 W. Fullerton Avenue, Chicago, IL 60614; Ljason@depaul.edu; Phone (773) 325 2018; Fax: (773) 325 4923

As published in the Journal of IiME 1 (1) 8-14 prior to the IiME International ME/CFS Conference 2007.



Abstract

 

The current study sought to subgroup individuals with chronic fatigue syndrome. Based on a battery of basic laboratory screening tests, subgroups of Infectious, Inflammatory and Other were formed. When compared to controls, all subgroups reported significantly greater physical disability. Additionally, the Other group reported greater physical disability when compared to the Inflammatory group. When considering mental disability, only the Inflammatory group reported greater levels of disability. The Inflammatory and Infectious groups had an increased rate of current psychiatric comorbidity, but only in the Inflammatory group had an increased rate of lifetime psychiatric diagnoses. Interestingly, individuals who identified themselves as members of minority groups were significantly more likely to present with an ongoing infectious process when compared to Caucasian participants.

Keywords: chronic fatigue syndrome, subgrouping, physical disability, mental disability, psychiatric comorbidity

 

Introduction

Chronic fatigue syndrome (CFS) affects an estimated 836,000 adults in the United States (Jason et al., 1999), and is 3 to 5 times more common in women than men. CFS can impact any number of bodily systems including neurological, immunological, hormonal, gastrointestinal, and musculoskeletal (Friedberg & Jason, 1998). CFS is a diagnosis of exclusion. There are currently no specific diagnostic tests for its identification. Researchers have reported various biological abnormalities when investigating CFS, including hormonal abnormalities (Cannon et al., 1998; Moorkens, Berwaerts, Wynants & Abs, 2000), immune activation (Miller, Cohen & Ritchey, 2002), neuroendocrine changes, (Farrar, Locke & Kantrowitz, 1995) and neurological abnormalities (Cook, Lange, DeLuca & Natelson, 2001) among others. However, studies involving basic blood work appear to show no typical pattern of abnormality among individuals with CFS (Johnson, DeLuca & Natelson, 1999).

It has been suggested that a number of unique subgroups exist within the overall cluster of individuals diagnosed with this disorder (Cukor, Tiersky & Natelson, 2000; Jason et al. 2001; Johnson, DeLuca & Natelson, 1999). In the paper specifying the current US case definition for CFS diagnosis (Fukuda et al., 1994), the working group that developed the criteria referred to the importance of subgrouping within cohorts of individuals diagnosed with CFS. This demonstrates that, even as the current definitional criteria were being presented, there was an awareness of the heterogeneity within the identified group. After the publication of these criteria in 1994, many attempts to subgroup have been undertaken, but to date, no one method has proven to be consistently superior in differentiating subgroups.

Psychiatric comorbidity has often been considered a differentiating variable in research studies aimed at subgrouping (Borish et al., 1998; Cukor, Tiersky and Natelson, 2000; DeLuca, Johnson, Ellis & Natelson, 1997a; Masuda, Munemoto, Yamanaka, Takei & Tei, 2002). However, when Tiersky, Matheis, DeLuca, Lange, and Natelson (2003) examined individuals with CFS with and without psychiatric co-morbidity, they found that physical functional capacity was not worse in individuals with CFS and a concurrent psychiatric illness. Morriss and associates (1999) also found that depression was not associated with the reporting of pain, FM, IBS, or medically unexplained symptoms in individuals with CFS. Similarly, Ciccone, Busichio, Vickroy, and Natelson (2003) did not find that psychiatric illness, alone or in combination with a comorbid personality disorder, was associated with physical impairment.

In contrast to the findings above, Borish, Schmaling, DiClementi, Streib, Negri, and Jones (1998) found evidence of low level inflammation, similar to that of allergies, in a subgroup of individuals with CFS. Borish et al. suggested that there might be two subgroups of individuals with CFS, those with immune activation (infectious or inflammatory) and those devoid of immune activation with other illness processes, including psychiatric disorders. Lutgendorf, Klimas, Antoni, Brickman, and Fletcher (1995) found that those patients with immune activation had the most severe cognitive deficits, while Natelson, Cohen, Brassloff and Lee (1993) found that those with ongoing inflammatory processes reported greater cognitive and mental disabilities. Buchwald, Wener, Pearlman, and Kith (1997) found individuals with CFS and chronic fatigue to have significant abnormalities in C-reactive protein (an indicator of acute inflammation) and neopterin (an indicator of immune system activation, malignant disease, and viral infections) when compared to controls. Buchwald et al. (1997) stated that groups of individuals with active low-level inflammatory, infectious processes could be identified and that this was evidence of an organic process in these patients with CFS. Cook, Lange, DeLuca, and Natelson (2001) found that individuals with an abnormal MRI and ongoing inflammatory processes had increased physical disability, suggesting an organic basis for some individuals with CFS. Conceivably, individuals without evidence of these infectious or inflammatory processes on basic laboratory screening tests might be more likely to contain individuals who had other neuroendocrine or neurologic illnesses that might not be readily identified using the minimum battery of laboratory of tests recommended by Fukuda and colleagues (1994) in order to diagnose CFS. However, those with infectious or inflammatory processes might be expected to be more physically impaired compared to those without these processes, based on research by Cook, Lange, DeLuca and Natelson (2001) and Lange, et al. (1999). There is also evidence that those individuals with CFS and with inflammatory processes report greater mental difficulties when compared to those individuals without them (Natelson, Cohen, Brassloff & Lee, 1993).

Clearly, individuals diagnosed with CFS are heterogeneous with varying illness course and disability patterns (Jason, Corradi, Torres-Harding, & Taylor, 2005). Similar to other disorders such as cancer, it is likely that a number of distinct types of CFS exist, and that grouping all individuals who meet diagnostic criteria together is prohibiting the identification of these distinct biological markers of the individual subgroups. When specific subgroups are identified, even basic blood work may reveal a typical pattern of abnormality on diagnostic tests (DeLuca, Johnson, Ellis & Natelson, 1997b; Hickie et al. 1995; Jason et al., 2001).

This exploratory study considered several possible subgroups that fall under the umbrella diagnosis of CFS. It was expected that clinically significant groups would be found on the basis of abnormal blood tests. The laboratory tests that formed the basis for subgrouping were part of the battery of laboratory screening tests recommended by Fukuda et al. (1994). These groups consisted of an ongoing infectious group, an ongoing Inflammatory group, and an “Other” group (having neither infectious or inflammatory processes). Using these subgroups, this study sought to explore the relationships between membership in a subgroup, reported disability (both mental and physical), and psychiatric co-morbidity. It was hypothesized that the individuals with CFS would evidence higher levels of physical and mental disability than those in a control group, and that those in the Infectious and Inflammatory subgroup would exhibit higher levels of physical and mental disability when compared to the Other group. It was also hypothesized that the Inflammatory group would report greater mental difficulties when compared to the Infectious and Other groups.

Method

Procedure

Procedures developed by Kish (1965) were used to select one adult from each household contacted. The person with the most recent birthday was asked to complete the interview. A stratified random sample of several neighborhoods in Chicago was used, and a random sample of adults was screened. In stage one, 28,673 telephone numbers were contacted, with 18,675 adults completing the initial interview (see Jason et al., 1999 for further details). Persons who completed the initial screening stage of the study with indications that they may have had CFS, as well as a group negative for CFS (control group), were invited to participate in the second and third stages of the research study. Stage two involved administration of a structured psychiatric interview, the SCID, conducted by telephone. Stage three involved a medical exam at Mercy Hospital, including a physical exam, laboratory tests, including a complete blood count (CBC), white blood cell differential, antinuclear antibodies (ANA), sedimentation rate (Sed rate), rheumatoid arthritis (RA factor), chest X-ray, a detailed medical interview, and a structured medical questionnaire. Participants were also asked at this time to release previous medical records to the research study. The authors received IRB approval for conducting the study. Individuals who participated in the medical examination were provided financial compensation.

When each participant completed the study, a team of four physicians and a psychiatrist made the final diagnosis of CFS, Idiopathic Chronic Fatigue, Fatigue explained by a medical condition, or no fatigue. These physicians were familiar with the CFS diagnostic criteria and were blind to the experimental status of the participant. Two physicians independently rated each case to determine whether the participant met the CFS case definition (Fukuda et al., 1994). If a disagreement occurred, a third physician rater was used to arrive at a diagnostic consensus.

Participants

The participants for this project consisted of individuals with CFS and a control group. For the purposes of this study, it was important that the control sample include only individuals who presented themselves as mentally and physically healthy, due to the fact that abnormal medical test results were a primary variable. A total of 19 of 47 individuals in the control group were excluded from this study (e.g., on-going medical, sleep or severe and untreated psychiatric problems). The final sample included 31 in the CFS group (1 CFS participant was excluded due to lack of data on a critical variable), and 28 healthy controls. The CFS group consisted of 23 females and 8 males. The control group had 18 males and 10 females. Further demographic breakdown indicated that the CFS group had 5 African American, 14 Caucasian, 9 Latino, and 3 individuals who identified themselves as “other”. The control group consisted of 4 African American, 20 Caucasian, 2 Latino, and 2 individuals who identified as “other”.

Individuals with CFS were then sub-grouped into three groups according to medical evidence of possible inflammatory processes (as evidenced by abnormal eosinophils count, antinuclear antibodies [ANA], abnormal rheumatoid arthritis factor [RA factor], and abnormal sedimentation rate in the presence of one of the prior mentioned inflammatory markers), medical evidence of possible current infection (as evidenced by abnormal results on lymphocytes count or sedimentation rate [Sed rate] without the presence of an inflammatory marker), and a group without evidence of either of these organic processes. Each of these medical markers is discussed in the measures section below. When subgrouped based on these criteria, 8 participants with CFS were categorized into the Other group, 8 in the Infectious group, and 15 in the Inflammatory group.

Measures

Measures used for this study included laboratory blood tests, a self-report of disability, and a structured clinical interview for the determination of psychiatric diagnosis. 1

Footnotes

1All measures did not total 59 as all participants did not complete every measure.

Laboratory Tests

Standard laboratory tests were conducted during phase three of the full-scale study. Results used in the current study include: White blood cell (WBC) differential (specifically lymphocytes and eosinophils), rheumatoid arthritis factor (RA factor), antinuclear antibodies (ANA) and sedimentation rate (Sed rate). These laboratory tests were chosen for inclusion into the study based upon the recommendations of Fukuda and colleagues (1994) for diagnosing CFS. These tests are all part of the recommended minimum battery of laboratory screening tests suggested by this group in order to exclude other physiological causes of fatigue or another disease process. All blood-work completed for this study was analyzed through the laboratories at Mercy Hospital in Chicago Illinois, or National Health Laboratories Incorporated-Chicago, in Elmhurst, IL.

Eosinophils and Lymphocytes

Eosinophils and lymphocytes are specific types of leukocytes. To obtain the values presented and considered in this study, automated white blood cell differentials were performed. Differential white blood count is part of the complete blood count (CBC) and is composed of five types of leukocytes (WBCs whose chief function is to protect the body against microorganisms causing disease). These five consist of eosinophils, lymphocytes, neutrophils, basophils, and monocytes. The differential WBC is expressed in cubic millimeters and percent of total number of WBCs.

When elevated, eosinophil counts can indicate the presence of allergic inflammation, some forms of cancer, and parasitic disease. Significantly higher rates of allergy and allergic type reactions have been reported in the CFS population (Borish, et al., 1998). Several studies have also reported significant elevations of the eosinophil counts of individuals with CFS (Conti, Magrini, Priori, Valesini & Bonini, 1996; Baraniuk, Clauw, Yuta, Gaumond, Upadhyayula, Fujita, et al. 1998; Priori, Conti, Luan, Aprino & Valesini, 1994). The normal range endorsed by Mercy Hospital Laboratories for eosinophil count is 100-300 mL. This variable was coded as normal or abnormal depending on the test results from Mercy Hospital Laboratory.

When elevated levels of lymphocytes are found, this can be an indication of viral infection, chronic infection, and Hodgkin’s disease, among others. Elevated lymphocytes have been reported in the CFS population (Patarca, 2001), and abnormal lymphocyte responses have also been noted (Krueger et al., 2001). However, elevated levels and abnormal responses have not been found in all studies (Brimacombe, Zhang, Lange & Natelson, 2002). The normal range endorsed by Mercy Hospital Laboratories for lymphocytes is 800-4400mL. This variable was coded as normal or abnormal depending on the test results from Mercy Hospital Laboratory.

Rheumatoid Arthritis Factor (RA Factor)

RA factor measures antibodies in the serum of individuals with rheumatoid arthritis. When this test is abnormal, it indicates an inflammatory process such as rheumatoid arthritis, autoimmune disease and occasionally, infectious diseases. The presence of rheumatoid arthritis factor has been reported in the CFS population (Kerr et al., 2001). This laboratory test was conducted by National Health Laboratories Incorporated-Chicago, in Elmhurst, IL. Serum samples were first run undiluted, and if a positive result was found, the sample was then run diluted at a 1:10 dilution. The reference value for a normal result is < 1:20 titer. Ranges of 1:20-1:80 are positive for rheumatoid and other conditions. Results falling above 1:80 are positive for rheumatoid arthritis. Any positive results on this test were coded as abnormal. As Rheumatoid Arthritis is an exclusionary disorder for CFS diagnosis, all participants were screened for Rheumatoid Arthritis during their medical exam and this disorder was ruled out.

Sedimentation Rate (Sed Rate)

Sed rate measures the sinking velocity of blood cells, or the degree of rapidity with which the red cells sink in a mass of drawn blood (Dirckx, 2001). Elevated Sed Rate can indicate bacterial infection, pelvic inflammatory disease, systemic lupus erythematosus, and red blood cell abnormalities (Kee, 2001). Abnormal sedimentation rates have been reported in CFS populations (Richards, Roberts, McGregor, Dunston & Butt, 2000).

Results on this test are reported in millimeters per hour, and normal ranges depend on sex and age. The Mercy laboratories normal range for males < 50 is 0-10.4 mm/hr, and for males > 50, 0-11.4 mm/hr. For females < 50 the normal range is 0-11.0 mm/hr and for females > 50, 0-20.0 mm/hr. This variable was coded as normal or abnormal depending on the test results from Mercy Hospital Laboratories.

Antinuclear Antibodies (ANA)

ANA tests for the presence of antinuclear antibodies in the blood. A normal result is negative. When positive, it is an indication of systemic lupus or other rheumatoid disorders, which are inflammatory diseases. Occasionally this test can be positive in the presence of specific types of infections. Elevated rates of ANA have been reported in the CFS population (Nesher, Margalit & Ashkenazi, 2001). Several reports of a specific type of ANA found in some individuals with CFS have been published (Itoh et al., 2000; Nishikai, et al., 2001).

Psychiatric Diagnosis

To measure current and lifetime psychiatric diagnosis, the Structured Clinical Interview for the DSM (SCID; First, Spitzer, Gibbon & Williams, 1995) was used. Previous studies have indicated that the SCID is a reliable measure of psychiatric diagnosis in the CFS population (Taylor & Jason, 1998). The SCID requires administration by master’s level clinicians. To create the categories used in this study, all diagnoses identified as anxiety disorders by the DSM (such as generalized anxiety disorder, phobias etc.) were grouped together into one Anxiety Diagnosis variable, all disorders identified as depressive disorders (such as major depressive disorder, seasonal affective disorder, bipolar disorder etc.) into one Depressive Disorder variable, and all other psychiatric diagnoses (such as substance abuse disorders, somatization etc.) were grouped into an Other Psychiatric Diagnosis variable.

Disability

To determine disability level, the SF-36 (Stewart, Hays & Ware, 1988) was completed by all participants. The SF-36 is a 36-item questionnaire that assesses individuals’ self-report on physical and emotional health currently, in the past four weeks, and compared to the same time last year. The SF-36 has eight subscales, and one reported health transition score. Two composite scores are available for the SF-36, the Physical Component Summary (PCS) and the Mental Component Summary (MCS). Internal consistency coefficients range from .89 -.94 for the PCS, and .84 -.91 for the MCS across age, gender, race, education, medical diagnosis, and disease severity. The current study used these summary scales to determine differences in physical health, and mental health (Ware, Kosinski & Keller, 1994

Results

Initial analyses were conducted to determine if any significant differences existed between the control and the entire CFS group on sociodemographic variables. There was only one significant difference, which occurred for gender. Therefore, gender was run as a covariate in all subsequent analyses.

Subgroup Differences for Physical and Mental Disability

To consider the relationship between subgroup membership and reported physical disability, an ANCOVA was run with subgroup as the independent variable, PCS as the dependent variable, and gender as a covariate. Analyses indicated that significant differences could be found between the subgroups on the PCS (p < .01). Least Significant Difference post hoc analyses indicated that all three CFS subgroups reported significantly higher levels of physical disability than the Control group (M = 56.1). The Other group reported significantly higher levels of physical disability when compared to the Inflammatory group (Ms = 29.2 vs 39.2, respectively), but it was not significantly different from the Infectious (M = 34.7) group.

Next, an ANCOVA was conducted with a subgroup as the independent variable, MCS (a measure of mental disability) as the dependent variable, and gender as the covariate. Analyses indicated that significant differences did exist between the subgroups for the MCS variable (p < .01). Following the significant omnibus test, post hoc analyses indicated that the Inflammatory group had significantly greater mental disability compared to the control group (Ms = 36.5 vs 50.8, respectively), but was not significantly different from the Other (M = 43.6) or Infectious (M = 39.7) groups.

 

Relationships between Subgroups and Psychiatric Diagnoses

To attempt to understand the relationships that might exist between subgroups and psychiatric diagnoses, logistic regressions were conducted considering subgroups as the independent variables (e.g., Other, Infectious, Inflammatory, and Control) and one psychiatric diagnosis per logistic regression (with the following dependent variables in separate analyses: current depression, current anxiety, and current other psychiatric diagnosis). No significant differences were found among the subgroups and the presence of depression, anxiety disorder, or other psychiatric diagnosis.

Because prior studies have indicated that the CFS groups have significantly higher rates of current and lifetime psychiatric comorbidity, the analyses above were performed on current and any lifetime psychiatric diagnoses. Two logistic regressions used current psychiatric diagnosis and lifetime psychiatric diagnosis as dependent variables. The odds that an individual in the Infectious group also had a current psychiatric diagnosis were 6.13 times higher when compared to individuals in the control group. The odds that individuals in the Inflammatory group had a current psychiatric diagnosis were 12.65 times higher when compared to control group members.

The second logistic regression considered lifetime psychiatric diagnosis of any kind between membership in one of the subgroups, and membership in the control group. Analyses indicated that the odds that individuals in the Inflammatory group had a psychiatric diagnosis at some time in their lives were 18.66 times higher when compared to individuals in the control group.

 

Ethnic Differences

Prior to subgrouping, no significant differences existed between the control and CFS groups on ethnicity. However, when examining the three subgroups separately with the control group, chi square analysis indicated that significant differences did exist between the four groups [χ2 (3, N = 59) = 10.00, p = .019]. The Infectious group (91% minority, 9% Caucasian) were significantly more likely to be of minority status than the Other (32% minority, 67% Caucasian) and control (37% minority, 63% Caucasian) groups, but they were not significantly different from the Inflammatory (56% minority, 44% Caucasian) group.

 

Discussion

While it was hypothesized that the Infectious and Inflammatory groups would be significantly more physically impaired compared to the Other group, we found that the Other group reported significantly greater physical impairment compared to the Inflammatory group. In the present study, the Other group might have reported greater physical impairment because of other on-going physiological processes. For example, supplemental analyses indicated that the Other group was significantly more likely than the Infectious group to present with symptoms of orthostatic intolerance, specifically, dizziness immediately following standing, and dizziness when turning the head. The Other group might have contained individuals with ongoing illness processes that were not identifiable by the laboratory tests available for this study. Orthostatic intolerance is best diagnosed using tilt-table testing, which was beyond the scope of the current study.

The Inflammatory group was significantly different only from the control group. This result is consistent with past findings of greater mental disability in the Inflammatory group when compared to the control group, and is consistent with past research indicating individuals with ongoing inflammatory processes are more likely to report greater mental difficulties (Natelson, Cohen, Brassloff & Lee, 1993).

When measuring participants’ psychological status, the Other group was the only chronic fatigue subgroup that did not have significantly elevated psychiatric diagnoses. No significant relationships emerged between membership in the Infectious, Inflammatory, and Other groups, and current diagnosis of depression, anxiety, and any other psychiatric diagnosis. However, when examining simply the presence or absence of any current or lifetime psychiatric disorder, the Inflammatory group was more likely to have a current or lifetime psychiatric diagnosis when compared to controls. Also, individuals in the Infectious group were found to be more likely to have a current psychiatric diagnosis when compared to controls.

It is possible that the presence of a chronic illness may put enough psychological strain on an individual that this strain contributes to or caused psychiatric diagnosis, or that the same processes that increase an individual’s likelihood of having a mental disability when inflammatory processes are present, may increase the likelihood of a psychiatric diagnosis. It is also possible that the psychiatric symptoms are completely unrelated to the CFS diagnosis (Abbey, 1996). The relationship between psychiatric diagnosis and CFS diagnosis is one that is far from being understood and therefore is much in need of further study.

Finally, the Infectious group had a greater number of minorities compared to other subgroups and the control group. It is well documented that minority and low SES populations are less likely to have access to health care (Richman, Flaherty & Rospenda, 1994). Language barriers, past experiences with the healthcare system, and different medical and religious beliefs may all contribute to minority participants being less likely to utilize health care, even if they have the access (Borrayo & Jenkins, 2003; Johnson et al., 1995). It is also possible that minorities who are immigrants are more likely to travel to their country of origin and be exposed to different infectious agents in their travels. In addition to this, minority participants may be more likely to be employed in hazardous or environmentally stressful occupations with exposure to infectious agents. It is possible then that minorities in the present study had poorer health care utilization, and therefore were less likely to have had infectious processes treated.

The current exploratory investigation had several limitations. First, the medical tests used as the basis of subgrouping in this study were not exclusive indicators of infection or inflammation. Further, the distinction between infection or inflammation is often one that cannot clearly be made, as these two processes frequently occur together. While inflammation generally accompanies infection, there are distinct instances when inflammation occurs in the absence of known infection, such as allergic inflammation, or sub-clinical level rheumatoid arthritis. Future studies should seek to determine if clear differentiation can be made, with more accurate tests, between infection and inflammation. Second, the limited sample size for African American, Latino, Asian, and other minority groups necessitated the grouping of all minority participants into one larger minority group. It is difficult to be certain if the relationships found (i.e. that of minority participants being more likely to present with on-going infectious processes) are more likely in individuals who have minority status in general, or if differences in findings are due to a specific minority group. The current study had small sample sizes, and this could contribute to instability of results, limited generalizability and lack of statistical power. Logistic regressions with small sample sizes can over-fit models and generate high odds ratios. Future research should consider larger sample sizes of each minority group to explore within-group and between-group differences.

It is notable that these findings emerged when forming subgroups utilizing only a basic battery of laboratory screening tests. These laboratory tests were conducted primarily for the purpose of screening out other major illnesses that might explain a person’s chronic fatigue, as recommended by Fukuda and colleagues (1994). Many people with CFS exhibit only minimal or subtle abnormalities on these tests, and these abnormalities often are inconclusive or may not be acknowledged by the primary care physician because they do not lead to a diagnosis of another, more recognized disease process. Further, the more commonly reported physiological abnormalities reported in people with CFS, such as the presence of RNase L (Suhadolnik et al., 1997), adrenal insufficiency with subsequent low cortisol levels (Addington, 2000), the presence of orthostatic intolerance (Schondorf, Benoit, Wein, & Phaneuf, 1999), and immunological abnormalities (Patarca-Montero, Mark, Fletcher, & Klimas, 2000), can only be assessed using highly specialized, expensive, or experimental tests to which people with CFS and their physicians typically have little access. This study demonstrates that subgrouping is possible using laboratory tests that are readily available and can easily be ordered by primary care physicians.

The identification of clinically significant subgroups is the logical next step in furthering CFS research. There might be multiple pathways leading to the cause and maintenance of the neurobiologic disregulations and other symptoms experienced by individuals with CFS. Depending upon the individual and subtype, these may include unique biological, genetic, neurological, psychological, and socioenvironmental contributions. Previous research examining people with CFS as a homogenous group may have missed real differences that might exist among subgroups of people diagnosed with this illness. Subgrouping might be the key to understanding how CFS begins, how it is maintained, how medical and psychological variables influence its course, and in the best case, how it can be prevented, treated, and cured (Jason et al., 2005).

Acknowledgements

 

Request for reprints should be addressed to Leonard Jason, Center for Community Research, DePaul University, 990 W. Fullerton Avenue, Chicago, IL 60614.

Financial support for this study was provided by NIAID (Grant Number A136295).

References

Abbey, S. E., (1996). Psychiatric diagnostic overlap in chronic fatigue syndrome. In M. A. Demitrack & & S. E. Abbey Eds.), Chronic Fatigue Syndrome An Integrative Approach to Evaluation and Treatment (pp.49-71). New York: The Guilford Press.

Addington, J.S. (2000). Chronic fatigue syndrome: A dysfunction of the hypothalamic-pituitary-adrenal axis. Journal of Chronic Fatigue Syndrome, 7 (2), 63-73.

Baraniuk, J.N., Clauw, D., Yuta, A., Ali, M., Gaumond, E., Upadhyayula, N., Fujita, K., Shimizu, T.,(1998). Nasal secretion analysis in allergic rhinitis, cystic fibrosis, and nonallergic fibromyalgia/chronic fatigue syndrome subjects. American Journal of Rhinology, 12, 435-440. 

Borish, L., Schmaling, K., DiClementi, J., Streib, J., Negri, J., & Jones, J.F. (1998) Chronic fatigue syndrome: Identification of distinct subgroups on the basis of allergy and psychologic variables. Journal of Allergy and Clinical Immunology, 102(2), 222-230.

Borrayo, W. A. & Jenkins, S. R. (2003). Feeling frugal: Socioeconomic status, acculturation, and cultural health beliefs among women of Mexican descent. Cultural Diversity and Ethnic Minority Psychology, 9, 197-206.

Brimacombe, M., Zhang, Q., Lange, G. & Natelson, B. H. (2002). Immunological variables mediate cognitive dysfunction in gulf war veterans but not civilians with chronic fatigue syndrome. Neuroimmunomodulation, 10 (2), 93-100.

Buchwald, D., Wener, M.H., Pearlman, T. & Kith, P. (1997). Markers of inflammation and immune activation in chronic fatigue and chronic fatigue syndrome. The Journal of Rheumatology, 24, 372-376.

Cannon, J. G., Angel, J. B., Abad, L. W., O’Grady, J., Lundgren, N., Fagioli, L. & Kamaroff, A. L. (1998). Hormonal influences on stress-induced neutrophil mobilization in health and chronic fatigue syndrome. Journal of Clinical Immunology, 18(4), 291-298.

Ciccone, D.S., Busichio, K., Vickroy, M., & Natelson, B.H. (2003). Psychiatric morbidity in the chronic fatigue syndrome. Are patients with personality disorder more physically  impaired? Journal of Psychosomatic Research, 54, 445-452.

Conti, F., Magrini, L., Priori, R., Valesini, G. & Bonini, S. (1996). Eosinophil cationic protein serum levels and allergy in chronic fatigue syndrome. Allergy, 51 (2), 124-127.

Cook, D. B., Lange, G., DeLuca, J. & Natelson, B. H. (2001). Relationship of brain mri abnormalities and physical functional status in chronic fatigue syndrome. International Journal of Neuroscience, 107, 1-6.

Cukor, D., Tiersky, L & Natelson, B.H. (2000). Psychiatric comorbidity and somatic distress in sudden and gradual onset chronic fatigue syndrome. Journal of the Chronic Fatigue Syndrome, 7(4), 33-44.

DeLuca, J., Johnson, S. K., Ellis, S. P. & Natelson, B. H., (1997a). Cognitive functioning is impaired in patients with chronic fatigue syndrome devoid of psychiatric disease. Journal of Neurology, Neurosurgery and Psychiatry, 62(2), 151-155.

DeLuca, J., Johnson, S. K., Ellis, S. P. & Natelson, B. H. (1997b). Sudden vs. gradual onset of chronic fatigue syndrome differentiates individuals on cognitive and psychiatric measures. Journal of Psychiatric Research 31(1), 83-90.

Dirckx, J. H. (Ed.). (2001). Stedman’s concise medical dictionary for the health professions. Baltimore: Lippincott Williams & Wilkins.

Farrar, D. J., Locke, S. E., & Kantrowitz, F. G. (1995). Chronic fatigue syndrome 1: Etiology and pathogenesis. Behavioral Medicine, 21, 5-16.

First, M. B., Spitzer, R. L., Gibbon, M. & Williams, J. B. W. (1995). Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I/P Version 2.0). Washington D.C,: American Psychiatric Press.

Friedberg, F., & Jason, L. A. (1998) Understanding chronic fatigue syndrome: An empirical guide to assessment and treatment. Washington, DC: American Psychological Association.

Fukuda, K, Straus, S. E., Hickie, I., Sharpe, M. C., Dobbins, J. G., Kamaroff, A. & the International Chronic Fatigue Syndrome Study Group (1994). The chronic fatigue syndrome: A comprehensive approach to its definition and study. Annals of Internal Medicine, 121(12), 953-959.

Hickie, I., Lloyd, A., Hadzi-Pavlovic, D. & Parker, G. (1995). Can the chronic fatigue syndrome be defined by distinct clinical features? Psychological Medicine 25(5), 925-935.

Hickie, I., Lloyd, A., Wakefield, D. & Parker, G. (1990). The psychiatric status of patients with the chronic fatigue syndrome. British Journal of Psychiatry, 156, 534-540.

Itoh, Y., Igarashi, R., Tatsuma, N., Imai, T., Yoshida, J., Tsuchiya, M., Murakami, M. & Fukunaga, Y. (2000). Immunogenetic background of patients with autoimmune fatigue syndrome. Autoimmunity, 32 (3), 193-197.

Jason, L.A., Corradi, K.M., Torres-Harding, S., & Taylor, R. (2005). Chronic fatigue syndrome: The need for subtypes. Neuropsychology Review, 15, 29-58.

Jason, L.A., Richman, J.A., Rademaker, A.W., Jordan, K.M., Plioplys, A.V., Taylor, R. R., McCready, W., Huang, C. F. & Plioplys, S. (1999). A community-based study of chronic fatigue syndrome. Archieves of Internal Medicine, 159, 2129-2137.

Jason, L. A., Taylor, R. R., Kennedy, C. L., Torres-Harding, S., Song, S., Johnson, D. & Chimata, R. (2001). Subtypes of chronic fatigue syndrome: review of findings. Journal of the Chronic Fatigue Syndrome, 8(3-4), 1-21.

Johnson, K. W., Anderson, N. B., Bastida, W., Kramer, B. J., Williams, D. & Wong, M. (1995). Panel II: Macrosocial and environmental influences on minority health. Health Psychology, 14, 601-612.

Johnson, S. K., DeLuca, J. & Natelson, B.H. (1999). Chronic fatigue syndrome: Reviewing the research findings. Annals of Behavioral Medicine, 21(3), 258-271.

Kee, J.L. (2001). Handbook of Laboratory and Diagnostic Tests. Upper Saddle River, NJ: Prentice Hall.

Kerr, J. R., Barah, F., Mattey, D. L., Laing, I., Hopkins, S. J., Hutchinson, I. V. & Tyrrell, D. A. (2001). Circulating tumour necrosis factor-alpha and interferon-gamma are detectable during acute and convalescent parvovirus B19 infection and are associated with prolonged and chronic fatigue. The Journal of General Virology, 82 (12) 3011-3019.

Kish, L. (1965). Survey Sampling. N.Y.: Wiley.

Krueger, G. R., Koch, B., Hoffmann, A., Tojo, J., Brandt, M. E., Wang, G. & Buja, L. M. (2001). Dynamics of chronic active herpesvirus-g infection in patients with chronic fatigue syndrome: Data acquisition for computer modeling. In Vivo, 15 (6), 461-465.

Lange, G., DeLuca, J., Maldjian, J. A., Lee, H., Tiersky, L. A. & Natelson, B. H. (1999). Brain MRI abnormalities exist in a subset of patients with chronic fatigue syndrome. Journal of the Neurological Sciences, 171 (1), 3-7.

Lutgendorf, S., Klimas, N.G., Antoni, M., Brickman, A. & Fletcher, M.A. (1995). Relationships of cognitive difficulties to immune measures, depression and illness burden in chronic fatigue syndrome. Journal of Chronic Fatigue Syndrome, 1(2), 23-41.

Masuda, A., Mumemoto, T., Yamanake, T., Takei, M. & Tei, C. (2002). Psychosocial characteristics and immunological functions in patients with postinfectious chronic fatigue syndrome and noninfectious chronic fatigue syndrome. Journal of Behavioral Medicine, 25(5), 477-485.

Miller, G. E., Cohen, S., Ritchey, A. K. (2002). Chronic psychological stress and the regulation of proinflammatory cytokines: A glucocorticoid-resistance model. Health Psychology, 21(6), 531-541.

Moorkens, G., Berwaerts, J., Wynants, H. & Abs, R. (2000). Characterization of pituitary function with emphasis on GH secretion in the chronic fatigue syndrome. Clinical Endocrinology, 53, 99-106.

Morriss, R. K., Ahmed, M., Wearden, A. J., Mullis, R., Strickland, P., Appleby, L., Campbell, I. T. & Pearson, D. (1999). The role of depression in pain, psychophysiological syndromes and medically unexplained symptoms associated with chronic fatigue syndrome. Journal of Affective Disorders 55, 143-148.

Natelson, B.H., Cohen, J. M., Brassloff, I. & Lee, H.J. (1993). A controlled study of brain magnetic resonance imaging in patients with the chronic fatigue syndrome. Journal of the Neurological Sciences, 120 (2), 213-217.

Nesher, G, Margalit, R. & Ashkenazi, Y. J. (2001). Anti-nuclear envelope antibodies: Clinical associations. Seminars in Arthritis and Rheumatism, 30 (5), 313-320.

Nishikai, M., Tomomatsu, S., Hankins, R. W., Takagi, S., Miyachi, K., Kosaka, S. & Akiya, K. (2001). Autoantibodies to a 68/48 kDa protein in chronic fatigue syndrome and primary fibromyalgia: A possible marker for hypersomnia and cognitive disorders. Rheumatology 40 (7), 806-810.

Patarca, R. (2001). Cytokines and chronic fatigue syndrome. Annals of the New York Academy of Sciences, 933, 185-200.

Patarca-Montero, R., Mark, T., Fletcher, M.A., & Klimas, N.G. (2000). Immunology of chronic fatigue syndrome. Journal of Chronic Fatigue Syndrome, 6(3/4), 69-107.

Priori, R., Conti, R., Luan, F. L., Arpino, C. & Valesini, G. (1994). Chronic fatigue: A peculiar evolution of eosinophilia myalgia syndrome following treatment with L-tryptophan in four Italian adolescents. European Journal of Pediatrics, 153 (3), 344-346.

Richards, R. S., Roberts, T. K., McGregor, N. R., Dunstan, R. H. & Butt, H. L. (2000). Blood parameters indicative of oxidative stress are associated with symptom expression in chronic fatigue syndrome. Redox Report: Communications in Free Radical Research, 5 (1), 35-41.

Richman, J. A., Flaherty, J. A. & Rospenda, K. M. (1994). Chronic fatigue syndrome: Have flawed assumptions been derived from treatment-based studies?. American Journal of Public Health, 84 (2), 282-284.

Schondorf, R., Benoit, J., Wein, T., & Phaneuf, D. (1999). Orthostatic intolerance in the chronic fatigue syndrome. Journal of the Autonomic Nervous System, 75(2-3), 192-201.

Suhadolnik, R.J., Peterson, D.L., O'Brien, K., Cheney, P.R., Herst, C.V., Reichenbach, N.L. et al. (1997). Biochemical evidence for a novel low molecular weight 2-5A-dependent RNase L in chronic fatigue syndrome. Journal of Interferon & Cytokine Research, 17(7), 377-85.

Stewart A., Hays, R.D. & Ware, J. (1988). The MOS Short-Form General Health Survey. Medical Care 26, 724-735.

Taylor, R. R. & Jason, L. A. (1998). Comparing the DIS with the SCID: Chronic Fatigue Syndrome and Psychiatric Comorbidity. Psychology and Health, 13, 1087-1104.

Tiersky, L.A., Matheis, R.J., Deluca, J., Lange, G. & Natelson, B.H. (2003). Functional status, neuropsychological functioning, and mood in chronic fatigue syndrome. The Journal of Nervous and Mental Disease 191, 324-331.

Ware, J.E., Kosinski, M. & Keller, S.D. (1994). SF-36 Physical and Mental Health Summary Scales: A User’s Manual. Boston, MA: Health Assessment Lab.