scholarly journals The SARS-CoV-2 receptor angiotensin-converting enzyme 2 (ACE2) in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: analysis of high-throughput genetic, epigenetic, and gene expression studies

2021 ◽  
Author(s):  
João Malato ◽  
Franziska Sotzny ◽  
Sandra Bauer ◽  
Helma Freitag ◽  
André Fonseca ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Association Studies ◽  
Chronic Fatigue ◽  
Case Control ◽  
Healthy Controls ◽  
Converting Enzyme ◽  
Fatigue Syndrome ◽  
Expression Studies ◽  
Gene Expression Studies

Patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) show specific epigenetic and gene expression signatures of the disease. However, it is unknown whether these signatures in ME/CFS include abnormal levels of the human angiotensin-converting enzyme ACE and ACE2, the latter being the main receptor described for host-cell invasion by SARS-CoV-2. To investigate that, we first reviewed published case-control genome-wide association studies based on single nucleotide polymorphism data, case-control epigenome-wide association studies based on DNA methylation data, and case-control gene expression studies based on microarray data. From these published studies, we did not find any evidence for a difference between patients with ME/CFS and healthy controls in terms of genetic variation, DNA methylation, and gene expression levels of ACE and ACE2. In line with this evidence, the analysis of a new data set on the ACE/ACE2 gene expression in peripheral blood mononuclear cells did not find any differences between a female cohort of 37 patients and 34 age-matched healthy controls. Future studies should be conducted to extend this investigation to other potential receptors used by SARS-CoV-2. These studies will help researchers and clinicians to better assess the health risk imposed by this virus when infecting patients with this debilitating disease.

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 Designing the database for microarray experiments metadata

2017 ◽  
Author(s):  
Oleksandr Lykhenko ◽  
Alina Frolova ◽  
Maria Obolenska
Keyword(s):  
Gene Expression ◽  
Case Control ◽  
Control Groups ◽  
Multiple Hypothesis ◽  
Expression Studies ◽  
Gene Expression Studies ◽  
Microarray Datasets ◽  
New Hypothesis ◽  
Similar Gene ◽  
Additional Sample

AbstractAdvancements in both computer science and biotechnology opened way to unprecedented amount and variety of gene expression studies raw data in the open access. It is sometimes worth to rearrange and unite data from several similar gene expression studies into new case-control groups to test new hypothesis using available data. Unfortunately, most popular gene expression databases such as GEO and ArrayExpress were not designed to allow such cross-study procedures. In order to locate comparable samples in different studies numerous steps are required including gathering additional sample metadata and its standardization. Specialized databases are developed by investigators in their own fields of interest to reuse the processed data and create different case-control groups and test multiple hypothesis.Here we present detailed description of the specialized database creation along with its use case which is 32 gene expression cDNA microarray datasets on human placenta under conditions of pre-eclampsia containing expression data on more than 1000 biological samples. Samples contain sufficient metadata for them to be merged into relevant cross-experiment case-control groups for further integrative analysis.

scholarly journals JEPEGMIX2: improved gene-level joint analysis of eQTLs in cosmopolitan cohorts

2017 ◽  
Author(s):  
Chris Chatzinakos ◽  
Donghyung Lee ◽  
Bradley T Webb ◽  
Vladimir I Vladimirov ◽  
Kenneth S Kendler ◽  
...  
Keyword(s):  
Gene Expression ◽  
Association Studies ◽  
Supplementary Information ◽  
Joint Analysis ◽  
Genome Wide Association Studies ◽  
Expression Studies ◽  
Genome Wide ◽  
Gene Level ◽  
Supplementary Material ◽  
Gene Expression Studies

AbstractMotivationTo increase detection power, researchers use gene level analysis methods to aggregate weak marker signals. Due to gene expression controlling biological processes, researchers proposed aggregating signals for expression Quantitative Trait Loci (eQTL). Most gene-level eQTL methods make statistical inferences based on i) summary statistics from genome-wide association studies (GWAS) and ii) linkage disequilibrium (LD) patterns from a relevant reference panel. While most such tools assume homogeneous cohorts, our Gene-level Joint Analysis of functional SNPs in Cosmopolitan Cohorts (JEPEGMIX) method accommodates cosmopolitan cohorts by using heterogeneous panels. However, JEPGMIX relies on brain eQTLs from older gene expression studies and does not adjust for background enrichment in GWAS signals.ResultsWe propose JEPEGMIX2, an extension of JEPEGMIX. When compared to JPEGMIX, it uses i) cis-eQTL SNPs from the latest expression studies and ii) brains specific (sub)tissues and tissues other than brain. JEPEGMIX2 also i) avoids accumulating averagely enriched polygenic information by adjusting for background enrichment and ii), to avoid an increase in false positive rates for studies with numerous highly enriched (above the background) genes, it outputs gene q-values based on Holm adjustment of [email protected] informationSupplementary material is available at Bioinformatics online.

scholarly journals No differential gene expression for CD4+ T cells of MS patients and healthy controls

2019 ◽  
Vol 5 (2) ◽  
pp. 205521731985690 ◽  
Author(s):  
Ina S Brorson ◽  
Anna Eriksson ◽  
Ingvild S Leikfoss ◽  
Elisabeth G Celius ◽  
Pål Berg-Hansen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Sclerosis ◽  
T Cells ◽  
Differential Gene Expression ◽  
Genetic Variants ◽  
Healthy Controls ◽  
Expression Studies ◽  
Differential Gene ◽  
Gene Expression Studies ◽  
Multiple Sclerosis Patients

Background Multiple sclerosis-associated genetic variants indicate that the adaptive immune system plays an important role in the risk of developing multiple sclerosis. It is currently not well understood how these multiple sclerosis-associated genetic variants contribute to multiple sclerosis risk. CD4+ T cells are suggested to be involved in multiple sclerosis disease processes. Objective We aim to identify CD4+ T cell differential gene expression between multiple sclerosis patients and healthy controls in order to understand better the role of these cells in multiple sclerosis. Methods We applied RNA sequencing on CD4+ T cells from multiple sclerosis patients and healthy controls. Results We did not identify significantly differentially expressed genes in CD4+ T cells from multiple sclerosis patients. Furthermore, pathway analyses did not identify enrichment for specific pathways in multiple sclerosis. When we investigated genes near multiple sclerosis-associated genetic variants, we did not observe significant enrichment of differentially expressed genes. Conclusion We conclude that CD4+ T cells from multiple sclerosis patients do not show significant differential gene expression. Therefore, gene expression studies of all circulating CD4+ T cells may not result in viable biomarkers. Gene expression studies of more specific subsets of CD4+ T cells remain justified to understand better which CD4+ T cell subsets contribute to multiple sclerosis pathology.

Processing of Laser-Evoked Potentials in Patients with Chronic Whiplash-Associated Disorders, Chronic Fatigue Syndrome, and Healthy Controls: A Case–Control Study

Pain Medicine ◽  
2020 ◽  
Vol 21 (10) ◽  
pp. 2553-2563 ◽  
Author(s):  
Lisa Goudman ◽  
Liesbeth Daenen ◽  
Andre Mouraux ◽  
Jo Nijs ◽  
Patrick Cras ◽  
...  
Keyword(s):  
Chronic Fatigue Syndrome ◽  
Case Control Study ◽  
Chronic Fatigue ◽  
Case Control ◽  
Healthy Controls ◽  
Laser Evoked Potentials ◽  
Fatigue Syndrome ◽  
Whiplash Associated Disorders ◽  
Chronic Whiplash ◽  
Control Study

Abstract Objective Laser-evoked potentials (LEPs) are among the reliable neurophysiological tools to investigate patients with neuropathic pain, as they can provide an objective account of the functional status of thermo-nociceptive pathways. The goal of this study was to explore the functioning of the nociceptive afferent pathways by examining LEPs in patients with chronic whiplash-associated disorders (cWAD), patients with chronic fatigue syndrome (CFS), and healthy controls (HCs). Design Case–control study. Setting A single medical center in Belgium. Subjects The LEPs of 21 patients with cWAD, 19 patients with CFS, and 18 HCs were analyzed in this study. Methods All participants received brief nociceptive CO2 laser stimuli applied to the dorsum of the left hand and left foot while brain activity was recorded with a 32-channel electroencephalogram (EEG). LEP signals and transient power modulations were compared between patient groups and HCs. Results No between-group differences were found for stimulus intensity, which was supraliminal for Aδ fibers. The amplitudes and latencies of LEP wave components N1, N2, and P2 in patients with cWAD and CFS were statistically similar to those of HCs. There were no significant differences between the time–frequency maps of EEG oscillation amplitude between HCs and both patient populations. Conclusions EEG responses of heat-sensitive Aδ fibers in patients with cWAD and CFS revealed no significant differences from the responses of HCs. These findings thus do not support a state of generalized central nervous system hyperexcitability in those patients.

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