scholarly journals Integrated Analysis of Gene Expression and Genotype Variation Data for Chronic Fatigue Syndrome

10.5772/29422 ◽  
2012 ◽  
Author(s):  
Jungsoo Gim ◽  
Taesung Park
Keyword(s):  
Gene Expression ◽  
Chronic Fatigue Syndrome ◽  
Chronic Fatigue ◽  
Integrated Analysis ◽  
Fatigue Syndrome ◽  
Genotype Variation ◽  
Variation Data

scholarly journals Integrated Analysis of Gene Expression Differences in Twins Discordant for Disease and Binary Phenotypes

2017 ◽  
Author(s):  
Sivateja Tangirala ◽  
Chirag J Patel
Keyword(s):  
Gene Expression ◽  
Meta Analysis ◽  
Gene Expression Signature ◽  
Chronic Fatigue ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Fatigue Syndrome ◽  
Genes And Environment ◽  
Intermittent Allergic Rhinitis ◽  
Differential Gene

AbstractWhile both genes and environment contribute to phenotype, deciphering environmental contributions to phenotype is a challenge. Furthermore, elucidating how different phenotypes may share similar environmental etiologies also is challenging. One way to identify environmental influences is through a discordant monozygotic (MZ) twin study design. Here, we assessed differential gene expression in MZ discordant twin pairs (affected vs. non-affected) for seven phenotypes, including chronic fatigue syndrome, obesity, ulcerative colitis, major depressive disorder, intermittent allergic rhinitis, physical activity, and intelligence quotient, comparing the spectrum of genes differentially expressed across seven phenotypes individually. Second, we performed meta-analysis for each gene to identify commonalities and differences in gene expression signatures between the seven phenotypes. In our integrative analyses, we found that there may be a common gene expression signature (with small effect sizes) across the phenotypes; however, differences between phenotypes with respect to differentially expressed genes were more prominently featured. Therefore, defining common environmentally induced pathways in phenotypes remains elusive. We make our work accessible by providing a new database (DiscTwinExprDB: http://apps.chiragjpgroup.org/disctwinexprdb/) for investigators to study non-genotypic influence on gene expression.

Post-exertion malaise in chronic fatigue syndrome: symptoms and gene expression

2013 ◽  
Vol 1 (4) ◽  
pp. 190-209 ◽  
Author(s):  
Jacob D. Meyer ◽  
Alan R. Light ◽  
Sanjay K. Shukla ◽  
Derek Clevidence ◽  
Steven Yale ◽  
...  
Keyword(s):  
Gene Expression ◽  
Chronic Fatigue Syndrome ◽  
Chronic Fatigue ◽  
Fatigue Syndrome

scholarly journals Utility of the Blood for Gene Expression Profiling and Biomarker Discovery in Chronic Fatigue Syndrome

2002 ◽  
Vol 18 (4) ◽  
pp. 193-199 ◽  
Author(s):  
Suzanne D. Vernon ◽  
Elizabeth R. Unger ◽  
Irina M. Dimulescu ◽  
Mangalathu Rajeevan ◽  
William C. Reeves
Keyword(s):  
Gene Expression ◽  
Chronic Fatigue Syndrome ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Biomarker Discovery ◽  
Chronic Fatigue ◽  
Classification Algorithms ◽  
Control Analysis ◽  
Healthy Controls ◽  
Fatigue Syndrome

Chronic fatigue syndrome (CFS) is a debilitating illness lacking consistent anatomic lesions and eluding conventional laboratory diagnosis. Demonstration of the utility of the blood for gene expression profiling and biomarker discovery would have implications into the pathophysiology of CFS. The objective of this study was to determine if gene expression profiles of peripheral blood mononuclear cells (PMBCs) could distinguish between subjects with CFS and healthy controls. Total RNA from PBMCs of five CFS cases and seventeen controls was labeled and hybridized to 1764 genes on filter arrays. Gene intensity values were analyzed by various classification algorithms and nonparametric statistical methods. The classification algorithms grouped the majority of the CFS cases together, and distinguished them from the healthy controls. Eight genes were differentially expressed in both an age-matched case-control analysis and when comparing all CFS cases to all controls. Several of the diffrentially expressed genes are associated with immunologic functions (e.g., CMRF35 antigen, IL-8, HD protein) and implicate immune dysfunction in the pathophysiology of CFS. These results successfully demonstrate the utility of the blood for gene expression profiling to distinguish subjects with CFS from healthy controls and for identifying genes that could serve as CFS biomarkers.

scholarly journals Gene Expression Subtypes in Patients with Chronic Fatigue Syndrome/Myalgic Encephalomyelitis

2008 ◽  
Vol 197 (8) ◽  
pp. 1171-1184 ◽  
Author(s):  
Jonathan R. Kerr ◽  
Robert Petty ◽  
Beverley Burke ◽  
John Gough ◽  
David Fear ◽  
...  
Keyword(s):  
Gene Expression ◽  
Chronic Fatigue Syndrome ◽  
Chronic Fatigue ◽  
Myalgic Encephalomyelitis ◽  
Fatigue Syndrome
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