Category: Methodology

The chronic fatigue syndrome: a comparative pathway analysis

Abstract:

In this paper, we introduce a method to detect pathological pathways of a disease. We aim to identify biological processes rather than single genes affected by the chronic fatigue syndrome (CFS). So far, CFS has neither diagnostic clinical signals nor abnormalities that could be diagnosed by laboratory examinations. It is also unclear if the CFS represents one disease or can be subdivided in different categories. We use information from clinical trials, the gene ontology (GO) database as well as gene expression data to identify undirected dependency graphs (UDGs) representing biological processes according to the GO database. The structural comparison of UDGs of sick versus non-sick patients allows us to make predictions about the modification of pathways due to pathogenesis.

 

Source: Emmert-Streib F. The chronic fatigue syndrome: a comparative pathway analysis. J Comput Biol. 2007 Sep;14(7):961-72. https://www.ncbi.nlm.nih.gov/pubmed/17803373

 

Publication trends in chronic fatigue syndrome: comparisons with fibromyalgia and fatigue: 1995-2004

Abstract:

OBJECTIVE: In order to identify publishing patterns in chronic fatigue syndrome (CFS), we compared the annual number of peer review articles for CFS, fibromyalgia (FM), and non-CFS fatigue over a recent decade (1995-2004).

METHOD: Citations were drawn from Ovid/Medline, PsychInfo, and the Journal of Chronic Fatigue Syndrome for peer review articles focusing on CFS, FM, and fatigue for each year of the decade ending in 2004. Statistics included chi-square, tests for differences in proportions, and regression-based curve estimation.

RESULTS: The frequency of CFS peer review articles did not significantly change from the first half to the second half of the decade (1995-2004). By comparison, the output of both FM and fatigue articles significantly increased (P<.0001). A quadratic model (inverted U shape; P<.02) best fit the data for CFS annual publication frequency. By comparison, exponential models best fit the data for both FM (P<.0001) and fatigue (P<.0001) citations. The highest percentage of citations (15-16%) for both CFS and FM fell within the domains of diagnosis, physiopathology, and psychology. For fatigue, almost one third (31.4%) of the citations were focused on etiology, while psychology (11.5%) and physiopathology (10.4%) articles were the next most cited. Based on first-author affiliation, CFS articles were most likely to originate in the United States (37.7%), England (31.4%), and the Netherlands (4.9%).

CONCLUSION: The output of CFS peer review articles has not increased over the past decade, while the number of FM and fatigue articles has increased substantially.

 

Source: Friedberg F, Sohl S, Schmeizer B. Publication trends in chronic fatigue syndrome: comparisons with fibromyalgia and fatigue: 1995-2004. J Psychosom Res. 2007 Aug;63(2):143-6. https://www.ncbi.nlm.nih.gov/pubmed/17662750

 

Spectroscopic diagnosis of chronic fatigue syndrome by multivariate analysis of visible and near-infrared spectra

Abstract:

We have recently evaluated the possibility of visible and near-infrared (Vis-NIR) spectroscopy for diagnosis of chronic fatigue syndrome(CFS). Vis-NIR spectra in the 600-1,100 nm region for sera from CFS patients and healthy donors were subjected to principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA) to develop multivariate models to discriminate between CFS patients and healthy donors. The PCA and SIMCA model predicted successful prediction of the masked samples. Furthermore, taking advantage of Vis-NIR spectroscopy to enable noninvasive analysis, our preliminary results have shown that SIMCA model from Vis-NIR spectra of thumb has achieved 70-80% correct determinations. In this review, we will introduce the potential of the Vis-NIR spectroscopy for CFS diagnosis.

 

Source: Sakudo A, Kuratsune H, Hakariya Y, Kobayashi T, Ikuta K. Spectroscopic diagnosis of chronic fatigue syndrome by multivariate analysis of visible and near-infrared spectra. Nihon Rinsho. 2007 Jun;65(6):1051-6. [Article in Japanese] https://www.ncbi.nlm.nih.gov/pubmed/17561696

 

Evaluation of fatigue by using acceleration plethysmography

Abstract:

We evaluated the fatigue of patients with chronic fatigue syndrome by using acceleration plethysmography. The changes in the acceleration plethysmography were relatively dominant in the sympathetic nervous system from the viewpoint of the autonomic nervous system, and the fluctuation in the time-series data of the acceleration plethysmography was decreased from the viewpoint of chaos or complexity system. We found the relation between the level of fatigue and the changes in acceleration plethysmography. Therefore, the acceleration plethysmography might be useful for the evaluation of fatigue.

 

Source: Yamaguti K. Evaluation of fatigue by using acceleration plethysmography. Nihon Rinsho. 2007 Jun;65(6):1034-42. [Article in Japanese] https://www.ncbi.nlm.nih.gov/pubmed/17561694

 

Continuous measurement of BRSI in chronic fatigue syndrome

Abstract:

This paper discusses the development of a system to measure continuous cardiac baroreceptor measurement during a 45-minute 70-degree head-up tilt (HUT) of five groups of subjects suffering the following: chronic fatigue syndrome (CFS), CFS with fibromyalgia (CFS-FM), CFS with postural orthostatic tachycardia syndrome (CFS-POTS), controls with POTS (CON-POTS), and controls (CON). The duration of the test was 56-minutes, which included a five-minute supine baseline, a 45-minute HUT and a six-minute recovery period. The system was developed in LabView, and can provide a comparative time analyses of weighted BRSI averages. Baroreflex effectiveness index (BEI) was also investigated over the course of lags 0, 1 and 2 as well as an assessment of overall BEI performance between groups.

 

Source: Donnelly DL, Rockland RH, Reisman SS, Quigley KS. Continuous measurement of BRSI in chronic fatigue syndrome. Conf Proc IEEE Eng Med Biol Soc. 2004;2:906-8. https://www.ncbi.nlm.nih.gov/pubmed/17271825

 

Screening for psychological distress using internet administration of the Hospital Anxiety and Depression Scale (HADS) in individuals with chronic fatigue syndrome

Abstract:

OBJECTIVES: To investigate the factor structure and internal consistency of the Hospital Anxiety and Depression Scale (HADS) in individuals with Chronic Fatigue Syndrome (CFS) using an Internet administered version of the instrument.

DESIGN: Between subjects.

METHOD: Confirmatory factor analysis (CFA) and internal consistency analysis of the HADS was used to determine the psychometric characteristics of the instrument in individuals with CFS and a control group with data captured via an Internet data collection protocol.

RESULTS: CFA revealed that a 3-factor solution offered the most parsimonious account of the data. Internal consistency estimations of the anxiety and depression subscales were found to be acceptable for both groups. The CFS group was found to have significantly higher HADS-assessed anxiety and depression scores compared with controls, however, there was also evidence found that Internet administration of the instrument may inflate HADS subscale scores as an artifact of testing medium.

CONCLUSIONS: The HADS is suitable for use for screening individuals with CFS in terms of the factor structure of the instrument, however, clinicians should be aware that this instrument assesses 3 domains of affective disturbance rather than 2 as is interpreted within the current HADS anxiety and depression subscale scoring system. Researchers need also be aware that Internet administration of negative affective state measures such as the HADS is likely to inflate scores and need to ensure that comparisons between clinical groups are made with control group data gathered using the same collection methodology.

 

Source: McCue P, Buchanan T, Martin CR. Screening for psychological distress using internet administration of the Hospital Anxiety and Depression Scale (HADS) in individuals with chronic fatigue syndrome. Br J Clin Psychol. 2006 Nov;45(Pt 4):483-98. https://www.ncbi.nlm.nih.gov/pubmed/17076959

 

High-resolution magnetic resonance imaging sinc-interpolation-based subvoxel registration and semi-automated quantitative lateral ventricular morphology employing threshold computation and binary image creation in the study of fatty acid interventions in schizophrenia, depression, chronic fatigue syndrome and Huntington’s disease

Abstract:

Serial high-resolution structural magnetic resonance imaging scans of the brain can now be precisely aligned, with six degrees of freedom (three mutually orthogonal translational and three rotational degrees of freedom around three mutually orthogonal axes), using a rigid-body subvoxel registration technique. This is driven by the in-plane point spread function for images acquired in the Fourier domain with data obtained over a bounded region of k-space, namely the sinc interpolation function, where sinc z = (sin z)/z, with z being any complex number (including zero).

Computational subtraction of the three-dimensional Cartesian spatial representation matrices of serially acquired scan data allows for the determination of structural cerebral changes with great precision, since voxel signals from unchanged structures are almost completely cancelled. Thus changes readily show up against a background of noise. Furthermore, lateral ventricular changes can now be accurately quantified using a semi-automated method involving contour production, threshold computation, binary image creation and ventricular extraction.

These techniques have been applied to the investigation of the effects on cerebral structure of intervention with fatty acids, particularly the long-chain polyunsaturated n-3 fatty acid eicosapentaenoic acid (EPA), in disorders such as schizophrenia, treatment-resistant depression, chronic fatigue syndrome (myalgic encephalomyelitis or ME), and Huntington’s disease.

 

Source: Puri BK. High-resolution magnetic resonance imaging sinc-interpolation-based subvoxel registration and semi-automated quantitative lateral ventricular morphology employing threshold computation and binary image creation in the study of fatty acid interventions in schizophrenia, depression, chronic fatigue syndrome and Huntington’s disease. Int Rev Psychiatry. 2006 Apr;18(2):149-54. https://www.ncbi.nlm.nih.gov/pubmed/16777669

Clinical methodology and its implications for the study of therapeutic interventions for chronic fatigue syndrome: a commentary

Abstract:

Chronic fatigue syndrome (CFS) is a complex, multisymptom illness of unknown etiology. A variety of operational case definitions based on symptom report have been developed that share some common clinical features. Patients often come to clinical presentation after months or, more typically, years of symptomatic distress. Comorbid presentation with psychiatric illnesses has been noted.

Due to these fundamental issues, the impact of patient selection and the specification of the methods of outcome assessment loom large in therapeutic studies of CFS. While a substantial body of research has focused on increasing our understanding of the basic pathobiology of CFS, there have been comparatively fewer studies that have addressed the problems of patient characterization and outcome assessment. The role of clinical methodology in the study of the therapeutics of CFS is not trivial, and may confound our understanding of pragmatic recommendations for treatment.

 

Source: Demitrack MA. Clinical methodology and its implications for the study of therapeutic interventions for chronic fatigue syndrome: a commentary. Pharmacogenomics. 2006 Apr;7(3):521-8. https://www.ncbi.nlm.nih.gov/pubmed/16610962

 

Interpreter of maladies: redescription mining applied to biomedical data analysis

Abstract:

Comprehensive, systematic and integrated data-centric statistical approaches to disease modeling can provide powerful frameworks for understanding disease etiology. Here, one such computational framework based on redescription mining in both its incarnations, static and dynamic, is discussed.

The static framework provides bioinformatic tools applicable to multifaceted datasets, containing genetic, transcriptomic, proteomic, and clinical data for diseased patients and normal subjects. The dynamic redescription framework provides systems biology tools to model complex sets of regulatory, metabolic and signaling pathways in the initiation and progression of a disease.

As an example, the case of chronic fatigue syndrome (CFS) is considered, which has so far remained intractable and unpredictable in its etiology and nosology. The redescription mining approaches can be applied to the Centers for Disease Control and Prevention’s Wichita (KS, USA) dataset, integrating transcriptomic, epidemiological and clinical data, and can also be used to study how pathways in the hypothalamic-pituitary-adrenal axis affect CFS patients.

 

Source: Waltman P, Pearlman A, Mishra B. Interpreter of maladies: redescription mining applied to biomedical data analysis. Pharmacogenomics. 2006 Apr;7(3):503-9. https://www.ncbi.nlm.nih.gov/pubmed/16610960

 

Allostatic load is associated with symptoms in chronic fatigue syndrome patients

Abstract:

OBJECTIVES: To further explore the relationship between chronic fatigue syndrome (CFS) and allostatic load (AL), we conducted a computational analysis involving 43 patients with CFS and 60 nonfatigued, healthy controls (NF) enrolled in a population-based case-control study in Wichita (KS, USA). We used traditional biostatistical methods to measure the association of high AL to standardized measures of physical and mental functioning, disability, fatigue and general symptom severity. We also used nonlinear regression technology embedded in machine learning algorithms to learn equations predicting various CFS symptoms based on the individual components of the allostatic load index (ALI).

METHODS: An ALI was computed for all study participants using available laboratory and clinical data on metabolic, cardiovascular and hypothalamic-pituitary-adrenal (HPA) axis factors. Physical and mental functioning/impairment was measured using the Medical Outcomes Study 36-item Short Form Health Survey (SF-36); current fatigue was measured using the 20-item multidimensional fatigue inventory (MFI); frequency and intensity of symptoms was measured using the 19-item symptom inventory (SI). Genetic programming, a nonlinear regression technique, was used to learn an ensemble of different predictive equations rather just than a single one. Statistical analysis was based on the calculation of the percentage of equations in the ensemble that utilized each input variable, producing a measure of the ‘utility’ of the variable for the predictive problem at hand. Traditional biostatistics methods include the median and Wilcoxon tests for comparing the median levels of subscale scores obtained on the SF-36, the MFI and the SI summary score.

RESULTS: Among CFS patients, but not controls, a high level of AL was significantly associated with lower median values (indicating worse health) of bodily pain, physical functioning and general symptom frequency/intensity. Using genetic programming, the ALI was determined to be a better predictor of these three health measures than any subcombination of ALI components among cases, but not controls.

 

Source: Goertzel BN, Pennachin C, de Souza Coelho L, Maloney EM, Jones JF, Gurbaxani B. Allostatic load is associated with symptoms in chronic fatigue syndrome patients. Pharmacogenomics. 2006 Apr;7(3):485-94. https://www.ncbi.nlm.nih.gov/pubmed/16610958