Post-infectious myalgic encephalomyelitis/chronic fatigue syndrome (PI-ME/CFS) is a disabling disorder, yet the clinical phenotype is poorly defined, the pathophysiology is unknown, and no disease-modifying treatments are available. We used rigorous criteria to recruit PI-ME/CFS participants with matched controls to conduct deep phenotyping. Among the many physical and cognitive complaints, one defining feature of PI-ME/CFS was an alteration of effort preference, rather than physical or central fatigue, due to dysfunction of integrative brain regions potentially associated with central catechol pathway dysregulation, with consequences on autonomic functioning and physical conditioning. Immune profiling suggested chronic antigenic stimulation with increase in naïve and decrease in switched memory B-cells. Alterations in gene expression profiles of peripheral blood mononuclear cells and metabolic pathways were consistent with cellular phenotypic studies and demonstrated differences according to sex. Together these clinical abnormalities and biomarker differences provide unique insight into the underlying pathophysiology of PI-ME/CFS, which may guide future intervention.
There is much speculation on which hypervariable region provides the highest bacterial specificity in 16S rRNA sequencing. The optimum solution to prevent bias and to obtain a comprehensive view of complex bacterial communities would be to sequence the entire 16S rRNA gene; however, this is not possible with second generation standard library design and short-read next-generation sequencing technology. This paper examines a new process using seven hypervariable or V regions of the 16S rRNA (six amplicons: V2, V3, V4, V6-7, V8, and V9) processed simultaneously on the Ion Torrent Personal Genome Machine (Life Technologies, Grand Island, NY). Four mock samples were amplified using the 16S Ion Metagenomics Kit™ (Life Technologies) and their sequencing data is subjected to a novel analytical pipeline. Results are presented at family and genus level. The Kullback-Leibler divergence (DKL), a measure of the departure of the computed from the nominal bacterial distribution in the mock samples, was used to infer which region performed best at the family and genus levels. Three different hypervariable regions, V2, V4, and V6-7, produced the lowest divergence compared to the known mock sample. The V9 region gave the highest (worst) average DKL while the V4 gave the lowest (best) average DKL. In addition to having a high DKL, the V9 region in both the forward and reverse directions performed the worst finding only 17% and 53% of the known family level and 12% and 47% of the genus level bacteria, while results from the forward and reverse V4 region identified all 17 family level bacteria. The results of our analysis have shown that our sequencing methods using 6 hypervariable regions of the 16S rRNA and subsequent analysis is valid. This method also allowed for the assessment of how well each of the variable regions might perform simultaneously. Our findings will provide the basis for future work intended to assess microbial abundance at different time points throughout a clinical protocol.
Transcriptomic studies in clinical research are essential tools for deciphering the functional elements of the genome and unraveling underlying disease mechanisms. Various technologies have been developed to deduce and quantify the transcriptome including hybridization and sequencing-based approaches. Recently, high density exon microarrays have been successfully employed for detecting differentially expressed genes and alternative splicing events for biomarker discovery and disease diagnostics. The field of transcriptomics is currently being revolutionized by high throughput DNA sequencing methodologies to map, characterize, and quantify the transcriptome. In an effort to understand the merits and limitations of each of these tools, we undertook a study of the transcriptome in sickle cell disease, a monogenic disease comparing the Affymetrix Human Exon 1.0 ST microarray (Exon array) and Illumina’s deep sequencing technology (RNA-seq) on whole blood clinical specimens. Analysis indicated a strong concordance (R = 0.64) between Exon array and RNA-seq data at both gene level and exon level transcript expression. The magnitude of differential expression was found to be generally higher in RNA-seq than in the Exon microarrays. We also demonstrate for the first time the ability of RNA-seq technology to discover novel transcript variants and differential expression in previously unannotated genomic regions in sickle cell disease. In addition to detecting expression level changes, RNA-seq technology was also able to identify sequence variation in the expressed transcripts. Our findings suggest that microarrays remain useful and accurate for transcriptomic analysis of clinical samples with low input requirements, while RNA-seq technology complements and extends microarray measurements for novel discoveries.
Many patients with alcohol use disorder (AUD) consume alcohol chronically and in large amounts that alter intestinal microbiota, damage the gastrointestinal tract, and thereby injure other organs via malabsorption and intestinal inflammation. We hypothesized that alcohol consumption and subsequent abstinence would change the gut microbiome in adults admitted to a treatment program. Stool and oral specimens, diet data, gastrointestinal assessment scores, anxiety, depression measures and drinking amounts were collected longitudinally for up to 4 weeks in 22 newly abstinent inpatients with AUD who were dichotomized as less heavy drinkers (LHD, <10 drinks/d) and very heavy drinkers (VHD, 10 or more drinks/d). Next-generation 16 S rRNA gene sequencing was performed to measure the gut and oral microbiome at up to ten time points/subject and LHD and VHD were compared for change in principal components, Shannon diversity index and specific genera. The first three principal components explained 46.7% of the variance in gut microbiome diversity across time and all study subjects, indicating the change in gut microbiome following abstinence. The first time point was an outlier in three-dimensional principal component space versus all other time points. The gut microbiota in LHD and VHD were significantly dissimilar in change from day 1 to day 5 (p = .03) and from day 1 to week 3 (p = .02). The VHD drinking group displayed greater change from baseline. The Shannon diversity index of the gut microbiome changed significantly during abstinence in five participants. In both groups, the Shannon diversity was lower in the oral microbiome than gut. Ten total genera were shared between oral and stool in the AUD participants. These data were compared with healthy controls from the Human Microbiome Project to investigate the concept of a core microbiome. Rapid changes in gut microbiome following abstinence from alcohol suggest resilience of the gut microbiome in AUD and reflects the benefits of refraining from the highest levels of alcohol and potential benefits of abstinence.
Background: CD146 is a well described homotypic adhesion molecule found on endothelial cells and a limited number of other cell types. In cells from the peripheral circulation, CD146 has also been reported to be on activated lymphocytesin vitroandin vivo. The function associated with CD146 expression on lymphoid cells is unknown and very little information is available concerning the nature of CD146+ lymphocytes. In the current study, lymphocytes from healthy donors were characterized based upon the presence or absence of CD146 expression.Results: CD146 was expressed on a low percentage of circulating T lymphocytes, B lymphocytes, and NK cells in healthy individuals. CD146 expression can be induced and upregulatedin vitroon both B cells and T cells, but does not correlate with the expression of other markers of T cell activation. CD146 positive T cells do not represent clonal expansions as determined with the use of anti Vβ reagents. Data suggest that CD146 positive cells have enhanced adherence to endothelial monolayers in vitro. Gene profiling and immunophenotyping studies between CD146+ and CD146- T cells revealed several striking genotypic distinctions such as the upregulation of IL-8 and phenotypic differences including the paucity of CCR7 and CD45RA among CD146 positive T cells, consistent with effector memory function. A number of genes involved in cell adhesion, signal transduction, and cell communication are dramatically upregulated in CD146+ T cells compared to CD146- T cells.Conclusion: CD146 appears to identify small, unique populations of T as well as B lymphocytes in the circulation. The T cells have immunophenotypic characteristics of effector memory lymphocytes. The characteristics of these CD146+ lymphocytes in the circulation, together with the known functions in cell adhesion of CD146 on endothelial cells, suggests that these lymphocytes may represent a small subpopulation of cells primed to adhere to the endothelium and possibly extravasate to sites of inflammation.
Background: High levels of sleep disturbances reported among individuals with alcohol use disorder (AUD) can stimulate inflammatory gene expression, and in turn, may alter pro-inflammatory cytokines levels. We aimed to investigate associations between pro-inflammatory cytokine markers with subjective measures of sleep quality, psychological variables and alcohol consumption among individuals with AUD.Methods: This exploratory study is comprised of individuals with AUD (n = 50) and healthy volunteers (n = 14). Spearman correlation was used to investigate correlations between plasma cytokine levels and clinical variables of interest (liver and inflammatory markers, sleep quality, patient reported anxiety/depression scores, and presence of mood and/or anxiety disorders (DSM IV/5); and history of alcohol use variables.Results: The AUD group was significantly older, with poorer sleep quality, higher anxiety/depression scores, and higher average drinks per day as compared to controls. Within the AUD group, IL-8 and MCP-1 had positive significant correlations with sleep, anxiety, depression and drinking variables. Specifically, higher levels of MCP-1 were associated with poorer sleep (p = 0.004), higher scores of anxiety (p = 0.006) and depression (p < 0.001), and higher number of drinking days (p = 0.002), average drinks per day (p < 0.001), heavy drinking days (p < 0.001) and total number of drinks (p < 0.001). The multiple linear regression model for MCP-1 showed that after controlling for sleep status and heavy drinking days, older participants (p = 0.003) with more drinks per day (p = 0.016), and higher alkaline phosphatase level (p = 0.001) had higher MCP-1 level.Conclusion: This exploratory analysis revealed associations with cytokines MCP-1 and IL-8 and drinking consumption, sleep quality, and anxiety and depression in the AUD group. Furthermore, inflammatory and liver markers were highly correlated with certain pro-inflammatory cytokines in the AUD group suggesting a possible relationship between chronic alcohol use and inflammation. These associations may contribute to prolonged inflammatory responses and potentially higher risk of co-morbid chronic diseases.