Category: Genetics

A functional polymorphism in the disrupted-in schizophrenia 1 gene is associated with chronic fatigue syndrome

Abstract:

AIMS: Disrupted-in schizophrenia 1 (DISC1), identified in a pedigree with a familial psychosis with the chromosome translocation (1:11), is a putative susceptibility gene for psychoses such as schizophrenia and major depressive disorder (MDD). Patients with chronic fatigue syndrome (CFS) report having continuous severe fatigue and many overlapping symptoms with MDD; however, the mechanism and effective treatment of CFS are still unclear. We focused on the overlapping symptoms between CFS and MDD and performed an association study of the functional single-nucleotide polymorphism (SNP) in the DISC1 gene with CFS.

MAIN METHODS: Venous blood was drawn from CFS patients and controls and genomic DNA was extracted from the whole blood according to standard procedures. Ser704Cys DISC1 SNP was genotyped using the TaqMan 5′-exonuclease allelic discrimination assay.

KEY FINDINGS: We found that the Cys704 allele of Ser704Cys SNP was associated with an increased risk of CFS development compared with the Ser704 allele.

SIGNIFICANCE: DISC1 Ser704Cys might be a functional variant that affects one of the mechanisms implicated in the biology of CFS. Some patients with CFS showed a phenotype similar to that of patients with MDD, but further studies are needed to clarify the biological mechanism, because this study is of a rather preliminary nature. Despite the variety of patients with CFS, DISC1 Ser704Cys has an association with CFS, which may also suggest that DISC1 plays a central role in the induction of various psychiatric diseases.

Copyright 2010 Elsevier Inc. All rights reserved.

 

Source: Fukuda S, Hashimoto R, Ohi K, Yamaguti K, Nakatomi Y, Yasuda Y, Kamino K, Takeda M, Tajima S, Kuratsune H, Nishizawa Y, Watanabe Y. A functional polymorphism in the disrupted-in schizophrenia 1 gene is associated with chronic fatigue syndrome. Life Sci. 2010 May 8;86(19-20):722-5. doi: 10.1016/j.lfs.2010.03.007. Epub 2010 Mar 20. https://www.ncbi.nlm.nih.gov/pubmed/20227423

 

Microbial infections in eight genomic subtypes of chronic fatigue syndrome/myalgic encephalomyelitis

Abstract:

BACKGROUND: The authors have previously reported genomic subtypes of chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) based on expression of 88 human genes.

AIM: To attempt to reproduce these findings, determine the specificity of this signature to CFS/ME, and test for associations between CFS/ME subtype and infection.

METHODS: Expression levels of 88 human genes were determined in blood of 62 new patients with idiopathic CFS/ME (according to Fukuda criteria), six patients with Q-fever-associated CFS/ME from the Birmingham Q-fever outbreak (according to Fukuda criteria), 14 patients with endogenous depression (according to DSM-IV criteria) and 29 normal blood donors.

RESULTS: In patients with CFS/ME, differential expression was confirmed for all 88 genes. Q-CFS/ME had similar patterns of gene expression to idiopathic CFS/ME. Gene expression in patients with endogenous depression was similar to that in the normal controls, except for upregulation of five genes (APP, CREBBP, GNAS, PDCD2 and PDCD6). Clustering of combined gene data in CFS/ME patients for this and the authors’ previous study (117 CFS/ME patients) revealed genomic subtypes with distinct differences in SF36 scores, clinical phenotypes, severity and geographical distribution. Antibody testing for Epstein-Barr virus, enterovirus, Coxiella burnetii and parvovirus B19 revealed evidence of subtype-specific relationships for Epstein-Barr virus and enterovirus, the two most common infectious triggers of CFS/ME.

CONCLUSIONS: This study confirms the involvement of these genes in CFS/ME.

 

Source: Zhang L, Gough J, Christmas D, Mattey DL, Richards SC, Main J, Enlander D, Honeybourne D, Ayres JG, Nutt DJ, Kerr JR. Microbial infections in eight genomic subtypes of chronic fatigue syndrome/myalgic encephalomyelitis. J Clin Pathol. 2010 Feb;63(2):156-64. doi: 10.1136/jcp.2009.072561. Epub 2009 Dec 2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2921262/ (Full article)

 

Transcription profile analysis of vastus lateralis muscle from patients with chronic fatigue syndrome

Abstract:

Chronic fatigue syndrome (CFS) is a disabling condition characterized by unexplained chronic fatigue that impairs normal activities. Many body systems are affected and etiology has not yet been identified. In addition to immunological and psychological aspects, skeletal muscle symptoms are prominent in CFS patients.

In an effort to establish which pathways might be involved in the onset and development of muscle symptoms, we used global transcriptome analysis to identify genes that were differentially expressed in the vastus lateralis muscle of female and male CFS patients.

We found that the expression of genes that play key roles in mitochondrial function and oxidative balance, including superoxide dismutase 2, were altered, as were genes involved in energy production, muscular trophism and fiber phenotype determination. Importantly, the expression of a gene encoding a component of the nicotinic cholinergic receptor binding site was reduced, suggesting impaired neuromuscular transmission. We argue that these major biological processes could be involved in and/or responsible for the muscle symptoms of CFS.

Source: Pietrangelo T, Mancinelli R, Toniolo L, Montanari G, Vecchiet J, Fanò G, Fulle S. Transcription profile analysis of vastus lateralis muscle from patients with chronic fatigue syndrome. Int J Immunopathol Pharmacol. 2009 Jul-Sep;22(3):795-807. https://www.ncbi.nlm.nih.gov/pubmed/19822097

 

Molecular study of receptor for advanced glycation endproduct gene promoter and identification of specific HLA haplotypes possibly involved in chronic fatigue syndrome

Abstract:

The receptor for advanced glycation end product (RAGE) is thought to play an important role in inflammation. Chronic fatigue syndrome (CFS) is a long-lasting fatigue that compromises at least 50% of a subject’s daily activities without other known cause. Immune dysfunction has been implicated and an association with a peculiar genetic cytokine profile, predisposing to an immunomodulatory response of inflammatory nature, was found.

The aim of this study is to analyse RAGE polymorphisms and HLA-DRB1 alleles in seventy-five Italian CFS patients and 141 controls matched for age, sex and ethnicity. These two groups underwent genomic study for RAGE 374T/A and 429C/T promoter polymorphisms; moreover, 46 patients and 186 controls were typed for HLA-DRB1 at low resolution molecular level. Of these, 31 patients and 99 controls also underwent high resolution analysis to define the HLA-DRB1*11 and DRB1*13 alleles.

The haplotypes RAGE-374T, DRB1*04; RAGE-374T, DRB1*09; RAGE-374T, DRB1*11; RAGE-374A, DRB1*13; RAGE-429T, DRB1*04 and RAGE-429C, DRB1*11 were significantly more frequent in CFS patients, whereas RAGE-429C, DRB1*07 would seem protective. A significantly lower frequency of DRB1*1104 (5.4% vs 12.9% p=0.04, OR=0.39) and a significantly higher frequency of HLA-DRB1*1301 (13.0% vs 5.1% p=0.006, OR= 2.79) were found in CFS patients. A synergic effect was observed with RAGE polymorphism.

The OR values strengthened in the following cis combinations: RAGE-374A, HLA-DRB1*1104 (OR=0.27) and RAGE-374A, HLADRB1*1301 (OR=6.23). HLA haplotypes rather than single alleles of RAGE or of DRB1 genes seem to be involved in CFS, probably including a subregion of major interest.

 

Source: Carlo-Stella N, Bozzini S, De Silvestri A, Sbarsi I, Pizzochero C, Lorusso L, Martinetti M, Cuccia M. Molecular study of receptor for advanced glycation endproduct gene promoter and identification of specific HLA haplotypes possibly involved in chronic fatigue syndrome. Int J Immunopathol Pharmacol. 2009 Jul-Sep;22(3):745-54. https://www.ncbi.nlm.nih.gov/pubmed/19822091

 

A comparison of classification methods for predicting Chronic Fatigue Syndrome based on genetic data

Abstract:

BACKGROUND: In the studies of genomics, it is essential to select a small number of genes that are more significant than the others for the association studies of disease susceptibility. In this work, our goal was to compare computational tools with and without feature selection for predicting chronic fatigue syndrome (CFS) using genetic factors such as single nucleotide polymorphisms (SNPs).

METHODS: We employed the dataset that was original to the previous study by the CDC Chronic Fatigue Syndrome Research Group. To uncover relationships between CFS and SNPs, we applied three classification algorithms including naive Bayes, the support vector machine algorithm, and the C4.5 decision tree algorithm. Furthermore, we utilized feature selection methods to identify a subset of influential SNPs. One was the hybrid feature selection approach combining the chi-squared and information-gain methods. The other was the wrapper-based feature selection method.

RESULTS: The naive Bayes model with the wrapper-based approach performed maximally among predictive models to infer the disease susceptibility dealing with the complex relationship between CFS and SNPs.

CONCLUSION: We demonstrated that our approach is a promising method to assess the associations between CFS and SNPs.

 

Source: Huang LC, Hsu SY, Lin E. A comparison of classification methods for predicting Chronic Fatigue Syndrome based on genetic data. J Transl Med. 2009 Sep 22;7:81. doi: 10.1186/1479-5876-7-81. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2765429/ (Full article)

 

Autoantibodies, polymorphisms in the serotonin pathway, and human leukocyte antigen class II alleles in chronic fatigue syndrome: are they associated with age at onset and specific symptoms?

Abstract:

This study aimed to determine the influence of autoantibodies, polymorphisms in the serotonin pathway, and human leukocyte antigen (HLA) class II genes on age at chronic fatigue syndrome (CFS) onset and symptoms.

Eighty-one CFS patients were enrolled, and clinical data were recorded. Autoantibodies to different components of the central nervous system were tested. Polymorphisms in the promoter of the serotonin transporter gene (l/s) and a single nucleotide polymorphism in the serotonin receptor-2A gene (A/G) as well as HLA class II alleles were determined. Multivariate logistic-regression analyses were carried out.

The mean age at CFS onset +/- SD was 33.5 +/- 12.5 years. An age at CFS onset (ACFSO) during the third decade of life was associated with the serotonin receptor AA genotype and the HLA-DRB1*03 allele. An ACFSO during the fourth decade of life was associated with the HLA-DRB1*07 allele, whereas an ACFSO > or = 43 years was associated with having at least one copy of the serotonin G allele.

Concerning CFS symptoms, the serotonin AG genotype was protective against depressive symptoms. Although having at least one copy of the serotonin A allele and being female were associated with risk for arthralgia, the presence of antineuronal cell antibodies was protective against this. Episodes of unexplained fever were associated with the HLA-DRB1*11 allele. None of the genetic or serological features was associated with myalgia. None of the antibodies determined correlated with any ACFSO or other symptoms.

Our results reveal that in CFS, like other autoimmune diseases, different genetic features are related to age at CFS onset and symptoms.

 

Source: Ortega-Hernandez OD, Cuccia M, Bozzini S, Bassi N, Moscavitch S, Diaz-Gallo LM, Blank M, Agmon-Levin N, Shoenfeld Y. Autoantibodies, polymorphisms in the serotonin pathway, and human leukocyte antigen class II alleles in chronic fatigue syndrome: are they associated with age at onset and specific symptoms? Ann N Y Acad Sci. 2009 Sep;1173:589-99. doi: 10.1111/j.1749-6632.2009.04802.x. https://www.ncbi.nlm.nih.gov/pubmed/19758204

 

A gene signature for post-infectious chronic fatigue syndrome

Abstract:

BACKGROUND: At present, there are no clinically reliable disease markers for chronic fatigue syndrome. DNA chip microarray technology provides a method for examining the differential expression of mRNA from a large number of genes. Our hypothesis was that a gene expression signature, generated by microarray assays, could help identify genes which are dysregulated in patients with post-infectious CFS and so help identify biomarkers for the condition.

METHODS: Human genome-wide Affymetrix GeneChip arrays (39,000 transcripts derived from 33,000 gene sequences) were used to compare the levels of gene expression in the peripheral blood mononuclear cells of male patients with post-infectious chronic fatigue (n = 8) and male healthy control subjects (n = 7).

RESULTS: Patients and healthy subjects differed significantly in the level of expression of 366 genes. Analysis of the differentially expressed genes indicated functional implications in immune modulation, oxidative stress and apoptosis. Prototype biomarkers were identified on the basis of differential levels of gene expression and possible biological significance.

CONCLUSION: Differential expression of key genes identified in this study offer an insight into the possible mechanism of chronic fatigue following infection. The representative biomarkers identified in this research appear promising as potential biomarkers for diagnosis and treatment.

 

Source: Gow JW, Hagan S, Herzyk P, Cannon C, Behan PO, Chaudhuri A. A gene signature for post-infectious chronic fatigue syndrome. BMC Med Genomics. 2009 Jun 25;2:38. doi: 10.1186/1755-8794-2-38. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2716361/ (Full article)

 

An integrated approach to infer causal associations among gene expression, genotype variation, and disease

Abstract:

Gene expression data and genotype variation data are now capable of providing genome-wide patterns across many different clinical conditions. However, the separate analysis of these data has limitations in elucidating the complex network of gene interactions underlying complex traits, such as common human diseases. More information about the identity of key driver genes of common diseases comes from integrating these two heterogeneous types of data. We developed a two-step procedure to characterize complex diseases by integrating genotype variation data and gene expression data.

The first step elucidates the causal relationship among genetic variation, gene expression level, and disease. Based on the causal relationship determined at the first step, the second step identifies significant gene expression traits whose effects on disease status or whose responses to disease status are modified by the specific genotype variation. For the selected significant genes, a pathway enrichment analysis can be performed to identify the genetic mechanism of a complex disease. The proposed two-step procedure was shown to be an effective method for integrating three different levels of data, i.e., genotype variation, gene expression and disease status.

By applying the proposed procedure to a chronic fatigue syndrome (CFS) dataset, we identified a list of potential causal genes for CFS, and found an evidence for difference in genetic mechanisms of the etiology between CFS without ‘a major depressive disorder with melancholic features’ (CFS) and CFS with ‘a major depressive disorder with melancholic features’ (CFS-MDD/m). Especially, the SNPs within NR3C1 gene were shown to differently influence the susceptibility of developing CFS and CFS-MDD/m through integrative action with gene expression levels.

 

Source: Lee E, Cho S, Kim K, Park T. An integrated approach to infer causal associations among gene expression, genotype variation, and disease. Genomics. 2009 Oct;94(4):269-77. doi: 10.1016/j.ygeno.2009.06.002. Epub 2009 Jun 18. http://www.sciencedirect.com/science/article/pii/S0888754309001347 (Full article)

 

Gene expression in peripheral blood leukocytes in monozygotic twins discordant for chronic fatigue: no evidence of a biomarker

Abstract:

BACKGROUND: Chronic fatiguing illness remains a poorly understood syndrome of unknown pathogenesis. We attempted to identify biomarkers for chronic fatiguing illness using microarrays to query the transcriptome in peripheral blood leukocytes.

METHODS: Cases were 44 individuals who were clinically evaluated and found to meet standard international criteria for chronic fatigue syndrome or idiopathic chronic fatigue, and controls were their monozygotic co-twins who were clinically evaluated and never had even one month of impairing fatigue. Biological sampling conditions were standardized and RNA stabilizing media were used. These methodological features provide rigorous control for bias resulting from case-control mismatched ancestry and experimental error. Individual gene expression profiles were assessed using Affymetrix Human Genome U133 Plus 2.0 arrays.

FINDINGS: There were no significant differences in gene expression for any transcript.

CONCLUSIONS: Contrary to our expectations, we were unable to identify a biomarker for chronic fatiguing illness in the transcriptome of peripheral blood leukocytes suggesting that positive findings in prior studies may have resulted from experimental bias.

 

Source: Byrnes A, Jacks A, Dahlman-Wright K, Evengard B, Wright FA, Pedersen NL, Sullivan PF. Gene expression in peripheral blood leukocytes in monozygotic twins discordant for chronic fatigue: no evidence of a biomarker. PLoS One. 2009 Jun 5;4(6):e5805. doi: 10.1371/journal.pone.0005805. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2688030/ (Full article)

 

A Bayesian approach to gene-gene and gene-environment interactions in chronic fatigue syndrome

Abstract:

INTRODUCTION: In the study of genomics, it is essential to address gene-gene and gene-environment interactions for describing the complex traits that involves disease-related mechanisms. In this work, our goal is to detect gene-gene and gene-environment interactions resulting from the analysis of chronic fatigue syndrome patients’ genetic and demographic factors including SNPs, age, gender and BMI.

MATERIALS & METHODS: We employed the dataset that was original to the previous study by the Centers for Disease Control and Prevention Chronic Fatigue Syndrome Research Group. To investigate gene-gene and gene-environment interactions, we implemented a Bayesian based method for identifying significant interactions between factors. Here, we employed a two-stage Bayesian variable selection methodology based on Markov Chain Monte Carlo approaches.

RESULTS: By applying our Bayesian based approach, NR3C1 was found in the significant two-locus gene-gene effect model, as well as in the significant two-factor gene-environment effect model. Furthermore, a significant gene-environment interaction was identified between NR3C1 and gender. These results support the hypothesis that NR3C1 and gender may play a role in biological mechanisms associated with chronic fatigue syndrome.

CONCLUSION: We demonstrated that our Bayesian based approach is a promising method to assess the gene-gene and gene-environment interactions in chronic fatigue syndrome patients by using genetic factors, such as SNPs, and demographic factors such as age, gender and BMI.

 

Source: Lin E, Hsu SY. A Bayesian approach to gene-gene and gene-environment interactions in chronic fatigue syndrome. Pharmacogenomics. 2009 Jan;10(1):35-42. Doi: 10.2217/14622416.10.1.35. https://www.ncbi.nlm.nih.gov/pubmed/19102713