Differential Gene Expression after Emotional Freedom Techniques (EFT) Treatment: A Novel Pilot Protocol for Salivary mRNA Assessment

2016 ◽  
Vol 8 (1) ◽  
pp. 17-32
Marjorie Maharaj ◽  

You are here: Home › Differential Gene Expression after Emotional Freedom Techniques (EFT) Treatment: A Novel Pilot Protocol for Salivary mRNA Assessment doi 10.9769/EPJ.2016.8.1.MM Marjorie E. Maharaj, Department of Applied Psychology, Akamai University, Hilo, HI Abstract: Biopsychology is a rapidly expanding field of study since the completion of the Human Genome Project in 2003. There is little data measuring the effect of psychotherapeutic interventions on gene expression, due to the technical, logistical, and financial requirements of analysis. Being able to measure easily the effects of therapeutic experiences can validate the benefits of intervention. In order to test the feasibility of gene expression testing in a private practice setting, this study compared messenger ribonucleic acid (mRNA) and gene expression before and after psychotherapy and a control condition. With four non-clinical adult participants, it piloted a novel methodology using saliva stored at room temperature. A preliminary test of the interleukin- 8 (IL8) gene in both blood and saliva was performed in order to determine equivalency in the two biofluids; convergent validity was found. Following saliva test validation, a broad, genome-wide analysis was performed to detect differential gene expression in samples collected before and after treatment with Emotional Freedom Techniques (EFT), an evidence-based practice combining acupressure and cognitive exposure. The control treatment was non-therapeutic social interaction. To establish a baseline, participants received the control first, followed a week later by EFT. Analysis of samples was performed at three time points: immediately before treatment, immediately after, and 24 hours later. Differential expression between EFT and control was found in numerous genes implicated in overall health (p < 0.05). Further, the differentially expressed genes in this study were shown to be linked to immunity, pro or anti-inflammatory, as well as neuronal processes in the brain. Ten of the 72 differentially expressed genes are identified as promising targets for downstream research. The data show promise for the future use of salivary samples to determine the effects of therapy; this pilot protocol also illustrated the challenges and limitations of novel technologies employed in biopsychology. Keywords: epigenetics, DNA, mRNA, gene expression, protein synthesis, brain plasticity, neurogenesis, biopsychology

2007 ◽  
Vol 32 (1) ◽  
pp. 154-159 ◽  
Li Li ◽  
Amitabha Chaudhuri ◽  
John Chant ◽  
Zhijun Tang

We have devised a novel analysis approach, percentile analysis for differential gene expression (PADGE), for identifying genes differentially expressed between two groups of heterogeneous samples. PADGE was designed to compare expression profiles of sample subgroups at a series of percentile cutoffs and to examine the trend of relative expression between sample groups as expression level increases. Simulation studies showed that PADGE has more statistical power than t-statistics, cancer outlier profile analysis (COPA) (Tomlins SA, Rhodes DR, Perner S, Dhanasekaran SM, Mehra R, Sun XW, Varambally S, Cao X, Tchinda J, Kuefer R, Lee C, Montie JE, Shah RB, Pienta KJ, Rubin MA, Chinnaiyan AM. Science 310: 644–648, 2005), and kurtosis (Teschendorff AE, Naderi A, Barbosa-Morais NL, Caldas C. Bioinformatics 22: 2269–2275, 2006). Application of PADGE to microarray data sets in tumor tissues demonstrated its utility in prioritizing cancer genes encoding potential therapeutic targets or diagnostic markers. A web application was developed for researchers to analyze a large gene expression data set from heterogeneous biological samples and identify differentially expressed genes between subsets of sample classes using PADGE and other available approaches. Availability: http://www.cgl.ucsf.edu/Research/genentech/padge/ .

2019 ◽  
Vol 2 (1) ◽  
Jackson Townsend ◽  
Heather A. Hundley

Background and Hypothesis: RNA editing is one of several mechanisms regulating gene expression. One type of RNA editing, the deamination of adenosine to inosine, is carried out by ADAR enzymes. ADAR enzymes are essential for neural function and aberrant editing is implicated in various forms of neuropathology. C. elegans lacking the RNA editing enzyme, ADR-2, are viable allowing us to ascertain how loss of RNA editing affects neural gene expression. The effects of loss of adr-2 on neural gene expression will be analyzed in both the first larval (L1) and young adult stages. We hypothesize that the transcriptome will change depending on life stage and the presence of ADR-2. Methods: Three replicates of neural cells isolated from wild type and adr-2(-) L1 and young adult stage animals were obtained. Total RNA was extracted from each population and mRNA was isolated using an oligo-dT bead. The mRNA was fragmented, and reverse transcribed to generate a complentary DNA (cDNA) library. The cDNA was sequenced by a facility at Indiana University. Quality of the library was evaluated using FASTqc. DE-seq2 software evaluated the differential gene expression. Results: I examined differential gene expression in two life stages of the WT and adr-2 neural samples. After obtaining the differentially expressed genes, the portions of the transcriptome that require ADR-2 was determined. WT young adults showed increased (3715) and decreased (2504) expression of neural genes when compared to the L1 stage. Many differentially expressed genes required adr-2 (~40% of the upregulated and 78% of the downregulated genes.) In addition, some genes were uniquely altered (631 upregulated, 196 downregulated) in the absence of adr-2. Conclusion and Potential Impact: The life stage and presence of ADR-2 alter the neural transcriptome and this function changes throughout development. Future studies will determine whether these genes are altered due to the lack of RNA editing or binding by ADR-2.

2021 ◽  
Vol 14 (1) ◽  
pp. 38-45
O. Lykhenko ◽  

The purpose of the study was to provide the pipeline for processing of publicly available unprocessed data on gene expression via integration and differential gene expression analysis. Data collection from open gene expression databases, normalization and integration into a single expression matrix in accordance with metadata and determination of differentially expressed genes were fulfilled. To demonstrate all stages of data processing and integrative analysis, there were used the data from gene expression in the human placenta from the first and second trimesters of normal pregnancy. The source code for the integrative analysis was written in the R programming language and publicly available as a repository on GitHub. Four clusters of functionally enriched differentially expressed genes were identified for the human placenta in the interval between the first and second trimester of pregnancy. Immune processes, developmental processes, vasculogenesis and angiogenesis, signaling and the processes associated with zinc ions varied in the considered interval between the first and second trimester of placental development. The proposed sequence of actions for integrative analysis could be applied to any data obtained by microarray technology.

2018 ◽  
Adam McDermaid ◽  
Brandon Monier ◽  
Jing Zhao ◽  
Qin Ma

AbstractDifferential gene expression (DGE) is one of the most common applications of RNA-sequencing (RNA-seq) data. This process allows for the elucidation of differentially expressed genes (DEGs) across two or more conditions. Interpretation of the DGE results can be non-intuitive and time consuming due to the variety of formats based on the tool of choice and the numerous pieces of information provided in these results files. Here we present an R package, ViDGER (Visualization of Differential Gene Expression Results using R), which contains nine functions that generate information-rich visualizations for the interpretation of DGE results from three widely-used tools, Cuffdiff, DESeq2, and edgeR.

2020 ◽  
Arne Jacobs ◽  
Kathryn R. Elmer

AbstractUnderstanding the contribution of different molecular processes to the evolution and development of divergent phenotypes is crucial for identifying the molecular routes of rapid adaptation. Here, we used RNA-seq data to compare patterns of alternative splicing and differential gene expression in a case of parallel adaptive evolution, the replicated postglacial divergence of the salmonid fish Arctic charr (Salvelinus alpinus) into benthic and pelagic ecotypes across multiple independent lakes.We found that genes that were differentially spliced and differentially expressed between the benthic and pelagic ecotypes were mostly independent (<6% overlap) and were involved in different processes. Differentially spliced genes were primarily enriched for muscle development and functioning, while differentially expressed genes were mostly involved in energy metabolism, immunity and growth. Together, these likely explain different axes of divergence between ecotypes in swimming performance and activity. Furthermore, we found that alternative splicing and gene expression are mostly controlled by independent cis-regulatory quantitative trait loci (<3.4% overlap). Cis-regulatory regions were associated with the parallel divergence in splicing (16.5% of intron clusters) and expression (6.7 - 10.1% of differentially expressed genes), indicating shared regulatory variation across ecotype pairs. Contrary to theoretical expectation, we found that differentially spliced genes tended to be highly central in regulatory networks (‘hub genes’) and were annotated to significantly more gene ontology terms compared to non-differentially spliced genes, consistent with a higher level of connectivity and pleiotropy.Together, our results suggest that the concerted regulation of alternative splicing and differential gene expression through different regulatory regions leads to the divergence of complementary phenotypes important for local adaptation. This study provides novel insights into the importance of contrasting but putatively complementary molecular processes for rapid and parallel adaptive evolution.

2020 ◽  
Vol 6 (4) ◽  
pp. 205521732097851
IS Brorson ◽  
AM Eriksson ◽  
IS Leikfoss ◽  
V Vitelli ◽  
EG Celius ◽  

Background Genetic and clinical observations have indicated T cells are involved in MS pathology. There is little insight in how T cells are involved and whether or not these can be used as markers for MS. Objectives Analysis of the gene expression profiles of circulating CD8+ T cells of MS patients compared to healthy controls. Methods RNA from purified CD8+ T cells was sequenced and analyzed for differential gene expression. Pathway analyses of genes at several p-value cutoffs were performed to identify putative pathways involved. Results We identified 36 genes with significant differential gene expression in MS patients. Four genes reached at least 2-fold differences in expression. The majority of differentially expressed genes was higher expressed in MS patients. Genes associated to MS in GWAS showed enrichment amongst the differentially expressed genes. We did not identify enrichment of specific pathways amongst the differentially expressed genes in MS patients. Conclusions CD8+ T cells of MS patients show differential gene expression, with predominantly higher activity of genes in MS patients. We do not identify specific biological pathways in our study. More detailed analysis of CD8+ T cells and subtypes of these may increase understanding of how T cells are involved in MS.

2019 ◽  
Vol 51 (8) ◽  
pp. 323-332 ◽  
Alison M. Thomas ◽  
Claudia P. Cabrera ◽  
Malcolm Finlay ◽  
Kulvinder Lall ◽  
Muriel Nobles ◽  

Atrial fibrillation is a significant worldwide contributor to cardiovascular morbidity and mortality. Few studies have investigated the differences in gene expression between the left and right atrial appendages, leaving their characterization largely unexplored. In this study, differential gene expression was investigated in atrial fibrillation and sinus rhythm using left and right atrial appendages from the same patients. RNA sequencing was performed on the left and right atrial appendages from five sinus rhythm (SR) control patients and five permanent AF case patients. Differential gene expression in both the left and right atrial appendages was analyzed using the Bioconductor package edgeR. A selection of differentially expressed genes, with relevance to atrial fibrillation, were further validated using quantitative RT-PCR. The distribution of the samples assessed through principal component analysis showed distinct grouping between left and right atrial appendages and between SR controls and AF cases. Overall 157 differentially expressed genes were identified to be downregulated and 90 genes upregulated in AF. Pathway enrichment analysis indicated a greater involvement of left atrial genes in the Wnt signaling pathway whereas right atrial genes were involved in clathrin-coated vesicle and collagen formation. The differing expression of genes in both left and right atrial appendages indicate that there are different mechanisms for development, support and remodeling of AF within the left and right atria.

2019 ◽  
Navjot Singh ◽  
Heather C. Kim ◽  
Renjie Song ◽  
Jaskiran K. Dhinsa ◽  
Steven R. Torres ◽  

AbstractCandida albicans has been associated with a number of human diseases that pertain to the gastrointestinal (GI) tract. However, the details of how gut-associated lymphoid tissues (GALT) such as Peyer’s patches (PPs) in the small intestine play a role in immune surveillance and microbial differentiation, and what mechanisms PP use to protect the mucosal barrier in response to fungal organisms such as C. albicans, are still unclear. We particularly focus on PPs as they are the immune sensors and inductive sites of the gut that influence inflammation and tolerance. We have previously demonstrated that CD11c+ phagocytes located in the sub-epithelial dome (SED) within PPs sample C. albicans. To gain insight on how specific cells within PPs sense and respond to the sampling of fungi, we gavaged mice with C. albicans strains ATCC 18804 and SC5314 as well as Saccharomyces cerevisiae. We measured the differential gene expression of sorted CD45+ B220+ B-cells, CD3+ T-cells, and CD11c+ DCs within the first 24 hrs post-gavage using nanostring nCounter® technology. The results reveal that at 24 hrs, PP phagocytes were the cell type that displayed differential gene expression. These phagocytes were both able to sample C. albicans and able to discriminate between strains. In particular, strain ATCC 18804 upregulated fungal specific pro-inflammatory genes in CD11c+ phagocytes pertaining to innate and adaptive immune responses. Interestingly, PP CD11c+ phagocytes differentially expressed genes in response to C. albicans that were important in the protection of the mucosal barrier. These results highlight that the mucosal barrier not only responds to C. albicans, but also aids in the protection of the host.ImportanceThe specific gene expression changes within PPs that send the warning signals when encountering fungi, and how PPs can discriminate between innocuous S. cerevisiae or different strains of C. albicans during early stages of sampling, have not been elucidated. Here we show that within the first 24 hours of sampling, CD11c+ phagocytes were not only important in sampling, but they were the cell type that exhibited clear differential gene expression. These differentially expressed genes play important dual roles in inflammation, chemotaxis, and fungal specific recognition, as well as maintaining homeostasis and protection of the mucosal barrier. Using nanostring technology, we were also able to demonstrate that PPs can distinguish between different strains of C. albicans and can “set off the alarms” when necessary.

2002 ◽  
Vol 22 (3) ◽  
pp. 245-252 ◽  
Eric V. Shusta ◽  
Ruben J. Boado ◽  
Gary W. Mathern ◽  
William M. Pardridge

The microvasculature of the human brain plays an important role in the development and maintenance of the central nervous system and in the pathogenesis of brain diseases, and is the site of differential gene expression within the brain. However, human brain microvascular-specific genes may not be detected in whole-brain gene microarray because the volume of the brain microvascular endothelium is relatively small (0.1%) compared with the whole brain. Therefore, the differential gene expression within the human brain microvasculature was evaluated using suppression subtractive hybridization with RNA isolated from human brain microvessels. Gene identification was restricted to the first 71 clones that were differentially expressed at the brain microvasculature. Twenty of these were genes encoding proteins with known function that were involved in angiogenesis, neurogenesis, molecular transport, and maintenance of endothelial tight junctions or the cytoskeleton. Eighteen genes coding for proteins of an unknown function were identified, including five genes containing satellite DNA sequences. The results provide the initial outline of the genomics of the human brain microvasculature, and have implications for the identification of both targets for brain-specific drug transport and changes in microvascular gene expression in brain diseases.

2009 ◽  
Vol 2009 ◽  
pp. 1-7 ◽  
Qihua Tan ◽  
Mads Thomassen ◽  
Kirsten M. Jochumsen ◽  
Ole Mogensen ◽  
Kaare Christensen ◽  

Different from significant gene expression analysis which looks for genes that are differentially regulated, feature selection in the microarray-based prognostic gene expression analysis aims at finding a subset of marker genes that are not only differentially expressed but also informative for prediction. Unfortunately feature selection in literature of microarray study is predominated by the simple heuristic univariate gene filter paradigm that selects differentially expressed genes according to their statistical significances. We introduce a combinatory feature selection strategy that integrates differential gene expression analysis with the Gram-Schmidt process to identify prognostic genes that are both statistically significant and highly informative for predicting tumour survival outcomes. Empirical application to leukemia and ovarian cancer survival data through-within- and cross-study validations shows that the feature space can be largely reduced while achieving improved testing performances.

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