Transcriptomic Profiles of Sepsis in the Human Brain.
Ontology highlight
ABSTRACT:
SUBMITTER: Bustamante AC
PROVIDER: S-EPMC7124721 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The purpose of this study is to examine the transcriptomic profiles (RNAseq) of post-mortem brain tissue samples from patients who have died of sepsis compared to non-sepsis controls using two analytic approaches. Tissue samples originated from the Adult Changes in Thought study (ACT) brain bank. In order to determine cause of death, hospital charts for 89 ACT subjects who died while hospitalized were reviewed using a structured instrument for diagnosis of sepsis. RNA was extracted from 24 post-mortem parietal cortex tissue samples. RNA sequencing was performed on the 24 samples using Illumina's Hi-Seq platform. Raw data was exported, pre-processed, and analyzed by two methods, differential expression and weighted gene co-expression network analysis (WGCNA). 176 genes were differentially expressed with fold change of > 1.5 and adjusted p < 0.5. The top differentially expressed genes were immune-related. WGCNA reveled 6 modules were significantly correlated with sepsis. Significant nodules were enriched in terms associated with innate immunity, cytokines, DAMPs, synaptic function, ion channel function, neuronal growth, and T-cell signalling among others. These data suggest sepsis is associated with specific transcriptional responses in the human brain. These results provide support for previously identified targets as well as provide evidence to suggest investigation into new targets for mechanistic exploration of sepsis-associated brain injury.
2019-11-26 | GSE135838 | GEO
Project description:Transcriptomic Profiles of Sepsis in the Human Brain
| PRJNA560245 | ENA
Project description:Historically, murine models of inflammation in biomedical research have been shown to minimally correlate with genomic expression patterns from blood leukocytes in humans. In 2019, our laboratory reported an improved surgical sepsis model of cecal ligation and puncture (CLP) that provides additional daily chronic stress (DCS), as well as adhering to the Minimum Quality Threshold in Pre-Clinical Sepsis Studies (MQTiPSS) guidelines. This model phenotypically recapitulates the persistent inflammation, immunosuppression, and catabolism syndrome observed in adult human surgical sepsis survivors. Whether these phenotypic similarities between septic humans and mice are replicated at the circulating blood leukocyte transcriptome has not been demonstrated. Our analysis, in contrast with previous findings, demonstrated that genome-wide expression in our new murine model more closely approximated human surgical sepsis patients, particularly in the more chronic phases of sepsis. Importantly, our new model of murine surgical sepsis with chronic stress did not reflect well gene expression patterns from humans with community-acquired sepsis. Our work indicates that improved preclinical murine sepsis modeling can better replicate both the phenotypic and transcriptomic responses to surgical sepsis, but cannot be extrapolated to other sepsis etiologies. Importantly, these improved models can be a useful adjunct to human-focused and artificial intelligence-based forms of research in order to improve septic patients' morbidity and mortality.
| S-EPMC7855423 | biostudies-literature
Project description:Transcriptomic studies hold great potential towards understanding the human aging process. Previous transcriptomic studies have identified many genes with age-associated expression levels; however, small samples sizes and mixed cell types often make these results difficult to interpret.Using transcriptomic profiles in CD14+ monocytes from 1,264 participants of the Multi-Ethnic Study of Atherosclerosis (aged 55-94 years), we identified 2,704 genes differentially expressed with chronological age (false discovery rate, FDR???0.001). We further identified six networks of co-expressed genes that included prominent genes from three pathways: protein synthesis (particularly mitochondrial ribosomal genes), oxidative phosphorylation, and autophagy, with expression patterns suggesting these pathways decline with age. Expression of several chromatin remodeler and transcriptional modifier genes strongly correlated with expression of oxidative phosphorylation and ribosomal protein synthesis genes. 17% of genes with age-associated expression harbored CpG sites whose degree of methylation significantly mediated the relationship between age and gene expression (p?<?0.05). Lastly, 15 genes with age-associated expression were also associated (FDR???0.01) with pulse pressure independent of chronological age. Comparing transcriptomic profiles of CD14+ monocytes to CD4+ T cells from a subset (n?=?423) of the population, we identified 30 age-associated (FDR?<?0.01) genes in common, while larger sets of differentially expressed genes were unique to either T cells (188 genes) or monocytes (383 genes). At the pathway level, a decline in ribosomal protein synthesis machinery gene expression with age was detectable in both cell types.An overall decline in expression of ribosomal protein synthesis genes with age was detected in CD14+ monocytes and CD4+ T cells, demonstrating that some patterns of aging are likely shared between different cell types. Our findings also support cell-specific effects of age on gene expression, illustrating the importance of using purified cell samples for future transcriptomic studies. Longitudinal work is required to establish the relationship between identified age-associated genes/pathways and aging-related diseases.
| S-EPMC4417516 | biostudies-literature
Project description:BACKGROUND:The application of advanced sequencing technologies and improved mass-spectrometry platforms revealed significant changes in gene expression and lipids in Alzheimer's disease (AD) brain. The results so far have prompted further research using "multi-omics" approaches. These approaches become particularly relevant, considering the inheritance of APOE?4 allele as a major genetic risk factor of AD, disease protective effect of APOE?2 allele, and a major role of APOE in brain lipid metabolism. METHODS:Postmortem brain samples from inferior parietal lobule genotyped as APOE?2/c (APOE?2/carriers), APOE?3/3, and APOE?4/c (APOE?4/carriers), age- and gender-matched, were used to reveal APOE allele-associated changes in transcriptomes and lipidomes. Differential gene expression and co-expression network analyses were applied to identify up- and downregulated Gene Ontology (GO) terms and pathways for correlation to lipidomics data. RESULTS:Significantly affected GO terms and pathways were determined based on the comparisons of APOE?2/c datasets to those of APOE?3/3 and APOE?4/c brain samples. The analysis of lists of genes in highly correlated network modules and of those differentially expressed demonstrated significant enrichment in GO terms associated with genes involved in intracellular proteasomal and lysosomal degradation of proteins, protein aggregates and organelles, ER stress, and response to unfolded protein, as well as mitochondrial function, electron transport, and ATP synthesis. Small nucleolar RNA coding units important for posttranscriptional modification of mRNA and therefore translation and protein synthesis were upregulated in APOE?2/c brain samples compared to both APOE?3/3 and APOE?4/c. The analysis of lipidomics datasets revealed significant changes in ten major lipid classes (exclusively a decrease in APOE?4/c samples), most notably non-bilayer-forming phosphatidylethanolamine and phosphatidic acid, as well as mitochondrial membrane-forming lipids. CONCLUSIONS:The results of this study, despite the advanced stage of AD, point to the significant differences in postmortem brain transcriptomes and lipidomes, suggesting APOE allele associated differences in pathogenic mechanisms. Correlations within and between lipidomes and transcriptomes indicate coordinated effects of changes in the proteasomal system and autophagy-canonical and selective, facilitating intracellular degradation, protein entry into ER, response to ER stress, nucleolar modifications of mRNA, and likely myelination in APOE?2/c brains. Additional research and a better knowledge of the molecular mechanisms of proteostasis in the early stages of AD are required to develop more effective diagnostic approaches and eventually efficient therapeutic strategies.
| S-EPMC6937981 | biostudies-literature
Project description:Transcriptional effects in circulating leukocytes from mice challenged to peritoneal contamination and infection (PCI) compared to sham (vehicle control). We gratefully acknowledge the BMBF grant for the Center for Sepsis Control and Care (CSCC) for this study
2017-09-01 | GSE36608 | GEO
Project description:BackgroundThe acquisition of reliable tissue-specific RNA sequencing data from human skin biopsy represents a major advance in research. However, the complexity of the process of isolation of specific layers from fresh-frozen human specimen by laser capture microdissection, the abundant presence of skin nucleases and RNA instability remain relevant methodological challenges. We developed and optimized a protocol to extract RNA from layers of human skin biopsies and to provide satisfactory quality and amount of mRNA sequencing data.ResultsThe protocol includes steps of collection, embedding, freezing, histological coloration and relative optimization to preserve RNA extracted from specific components of fresh-frozen human skin biopsy of 14 subjects. Optimization of the protocol includes a preservation step in RNALater® Solution, the control of specimen temperature, the use of RNase Inhibitors and the time reduction of the staining procedure. The quality of extracted RNA was measured using the percentage of fragments longer than 200 nucleotides (DV200), a more suitable measurement for successful library preparation than the RNA Integrity Number (RIN). RNA was then enriched using the TruSeq® RNA Access Library Prep Kit (Illumina®) and sequenced on HiSeq® 2500 platform (Illumina®). Quality control on RNA sequencing data was adequate to get reliable data for downstream analysis.ConclusionsThe described implemented and optimized protocol can be used for generating transcriptomics data on skin tissues, and it is potentially applicable to other tissues. It can be extended to multicenter studies, due to the introduction of an initial step of preservation of the specimen that allowed the shipment of biological samples.
| S-EPMC6009967 | biostudies-literature
Project description:The brain vasculature maintains brain homeostasis by tightly regulating ionic, molecular, and cellular transport between the blood and the brain parenchyma. These blood-brain barrier (BBB) properties are impediments to brain drug delivery, and brain vascular dysfunction accompanies many neurological disorders. The molecular constituents of brain microvascular endothelial cells (BMECs) and pericytes, which share a basement membrane and comprise the microvessel structure, remain incompletely characterized, particularly in humans. To improve the molecular database of these cell types, we performed RNA sequencing on brain microvessel preparations isolated from snap-frozen human and mouse tissues by laser capture microdissection (LCM). The resulting transcriptome datasets from LCM microvessels were enriched in known brain endothelial and pericyte markers, and global comparison identified previously unknown microvessel-enriched genes. We used these datasets to identify mouse-human species differences in microvessel-associated gene expression that may have relevance to BBB regulation and drug delivery. Further, by comparison of human LCM microvessel data with existing human BMEC transcriptomic datasets, we identified novel putative markers of human brain pericytes. Together, these data improve the molecular definition of BMECs and brain pericytes, and are a resource for rational development of new brain-penetrant therapeutics and for advancing understanding of brain vascular function and dysfunction.
| S-EPMC7378255 | biostudies-literature
Project description:The aim of this study was to explore the anti-psoriatic effect and potential mechanism of Angelica polysaccharide (APS) on an in vitro HaCaT cell model. MTS assay was performed to determine whether APS has the ability to inhibit the proliferation of HaCaT cells. RNA-sequencing (RNA-seq) was performed to investigate the underlying mechanism of APS. Quantitative real-time PCR (qRT-PCR) was used to verify the accuracy of RNA-seq data. Our MTS assay results demonstrated that APS time- and concentration-dependently inhibits the proliferation of HaCaT cells. The anti-proliferation property of APS suggests that APS may have anti-psoriatic effect. In the RNA-seq part, comparison between the CK group (i.e., Control group) and ASP groups revealed dramatic differences [468 differentially expressed genes (DEGs) for CK group vs. ASP50 group; 563 DEGs for CK group vs. ASP100 group; 532 DEGs for CK group vs. ASP200 group]. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrich analysis performed on all DEGs failed to find any significant enriched GO terms or KEGG pathways to explain the anti-proliferative effect of APS. All DEGs were then classified into 20 expression profiles by trend analysis. Interestingly, cell proliferation-related GO terms were mostly dispersed in the profile 2 and 17. DEGs enriched in these terms were then analyzed. After literature retrieval, DEGs such as SERPINE1, SMAD6, CTGF, and TGF-β were suspected to closely relevant to the anti-proliferation effect of APS. qRT-PCR results showed similar expression trend with RNA-seq data for 8 out of 10 genes, indicating our sequence data are reliable.
| S-EPMC6646613 | biostudies-literature
Project description:BackgroundAnalysis of gene expression data using genome-wide microarrays is a technique often used in genomic studies to find coexpression patterns and locate groups of co-transcribed genes. However, most studies done at global "omic" scale are not focused on human samples and when they correspond to human very often include heterogeneous datasets, mixing normal with disease-altered samples. Moreover, the technical noise present in genome-wide expression microarrays is another well reported problem that many times is not addressed with robust statistical methods, and the estimation of errors in the data is not provided.Methodology/principal findingsHuman genome-wide expression data from a controlled set of normal-healthy tissues is used to build a confident human gene coexpression network avoiding both pathological and technical noise. To achieve this we describe a new method that combines several statistical and computational strategies: robust normalization and expression signal calculation; correlation coefficients obtained by parametric and non-parametric methods; random cross-validations; and estimation of the statistical accuracy and coverage of the data. All these methods provide a series of coexpression datasets where the level of error is measured and can be tuned. To define the errors, the rates of true positives are calculated by assignment to biological pathways. The results provide a confident human gene coexpression network that includes 3327 gene-nodes and 15841 coexpression-links and a comparative analysis shows good improvement over previously published datasets. Further functional analysis of a subset core network, validated by two independent methods, shows coherent biological modules that share common transcription factors. The network reveals a map of coexpression clusters organized in well defined functional constellations. Two major regions in this network correspond to genes involved in nuclear and mitochondrial metabolism and investigations on their functional assignment indicate that more than 60% are house-keeping and essential genes. The network displays new non-described gene associations and it allows the placement in a functional context of some unknown non-assigned genes based on their interactions with known gene families.Conclusions/significanceThe identification of stable and reliable human gene to gene coexpression networks is essential to unravel the interactions and functional correlations between human genes at an omic scale. This work contributes to this aim, and we are making available for the scientific community the validated human gene coexpression networks obtained, to allow further analyses on the network or on some specific gene associations. The data are available free online at http://bioinfow.dep.usal.es/coexpression/.
| S-EPMC2597745 | biostudies-literature