65 research outputs found
Salivary Diagnostics
Salivary diagnostics plays an important role in the early detection and prevention of many oral and systemic diseases in a fast and noninvasive way. Saliva collection is an easy, repeatable and inexpensive diagnostic source that can be used for both diagnosis and real-time monitoring of various human diseases. In the near future, many developed and validated salivary biomarkers have the potential to reach the clinical practice. Five diagnostic “omics” constituents of saliva include proteomics, transcriptomics, metabolomics, microbiomics and microRNAs. Based on them, the newly emerging technologies of salivary diagnostics are developed that include RNA-sequencing, point-of-care technologies and liquid biopsy. They have potential to enable screening, early detection, prognosis and monitoring of various human diseases. The recent developments broadened the salivary diagnostic approach from the oral cavity to the whole physiological system, thus toward personalized individual medicine applications
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Therapy of autoimmune inflammation in sporadic amyotrophic lateral sclerosis: Dimethyl fumarate and H‐151 downregulate inflammatory cytokines in the cGAS‐STING pathway
In sporadic amyotrophic lateral sclerosis (sALS), IL-17A- and granzyme-positive cytotoxic T lymphocytes (CTL), IL-17A-positive mast cells, and inflammatory macrophages invade the brain and spinal cord. In some patients, the disease starts following a trauma or a severe infection. We examined cytokines and cytokine regulators over the disease course and found that, since the early stages, peripheral blood mononuclear cells (PBMC) exhibit increased expression of inflammatory cytokines IL-12A, IFN-γ, and TNF-α, as well as granzymes and the transcription factors STAT3 and STAT4. In later stages, PBMCs upregulated the autoimmunity-associated cytokines IL-23A and IL-17B, and the chemokines CXCL9 and CXCL10, which attract CTL and monocytes into the central nervous system. The inflammation is fueled by the downregulation of IL-10, TGFβ, and the inhibitory T-cell co-receptors CTLA4, LAG3, and PD-1, and, in vitro, by stimulation with the ligand PD-L1. We investigated in two sALS patients the regulation of the macrophage transcriptome by dimethyl fumarate (DMF), a drug approved against multiple sclerosis and psoriasis, and the cyclic GMP-AMP synthase/stimulator of interferon genes (cGAS/STING) pathway inhibitor H-151. Both DMF and H-151 downregulated the expression of granzymes and the pro-inflammatory cytokines IL-1β, IL-6, IL-15, IL-23A, and IFN-γ, and induced a pro-resolution macrophage phenotype. The eicosanoid epoxyeicosatrienoic acids (EET) from arachidonic acid was anti-inflammatory in synergy with DMF. H-151 and DMF are thus candidate drugs targeting the inflammation and autoimmunity in sALS via modulation of the NFκB and cGAS/STING pathways
Open Problems in Extracellular RNA Data Analysis: Insights From an ERCC Online Workshop.
We now know RNA can survive the harsh environment of biofluids when encapsulated in vesicles or by associating with lipoproteins or RNA binding proteins. These extracellular RNA (exRNA) play a role in intercellular signaling, serve as biomarkers of disease, and form the basis of new strategies for disease treatment. The Extracellular RNA Communication Consortium (ERCC) hosted a two-day online workshop (April 19-20, 2021) on the unique challenges of exRNA data analysis. The goal was to foster an open dialog about best practices and discuss open problems in the field, focusing initially on small exRNA sequencing data. Video recordings of workshop presentations and discussions are available (https://exRNA.org/exRNAdata2021-videos/). There were three target audiences: experimentalists who generate exRNA sequencing data, computational and data scientists who work with those groups to analyze their data, and experimental and data scientists new to the field. Here we summarize issues explored during the workshop, including progress on an effort to develop an exRNA data analysis challenge to engage the community in solving some of these open problems
Genetic architecture of heart mitochondrial proteome influencing cardiac hypertrophy.
Mitochondria play an important role in both normal heart function and disease etiology. We report analysis of common genetic variations contributing to mitochondrial and heart functions using an integrative proteomics approach in a panel of inbred mouse strains called the Hybrid Mouse Diversity Panel (HMDP). We performed a whole heart proteome study in the HMDP (72 strains, n=2-3 mice) and retrieved 848 mitochondrial proteins (quantified in ≥50 strains). High- resolution association mapping on their relative abundance levels revealed three trans-acting genetic loci on chromosomes (chr) 7, 13 and 17 that regulate distinct classes of mitochondrial proteins as well as cardiac hypertrophy. DAVID enrichment analyses of genes regulated by each of the loci revealed that the chr13 locus was highly enriched for complex-I proteins (24 proteins, P=2.2E-61), the chr17 locus for mitochondrial ribonucleoprotein complex (17 proteins, P=3.1E-25) and the chr7 locus for ubiquinone biosynthesis (3 proteins, P=6.9E-05). Follow-up high resolution regional mapping identified NDUFS4, LRPPRC and COQ7 as the candidate genes for chr13, chr17 and chr7 loci, respectively, and both experimental and statistical analyses supported their causal roles. Furthermore, a large cohort of Diversity Outbred mice was used to corroborate Lrpprc gene as a driver of mitochondrial DNA (mtDNA)-encoded gene regulation, and to show that the chr17 locus is specific to heart. Variations in all three loci were associated with heart mass in at least one of two independent heart stress models, namely, isoproterenol-induced heart failure and diet-induced obesity. These findings suggest that common variations in certain mitochondrial proteins can act in trans to influence tissue-specific mitochondrial functions and contribute to heart hypertrophy, eluci- dating mechanisms that may underlie genetic susceptibility to heart failure in human populations
Performance of Salivary Extracellular RNA Biomarker Panels for Gastric Cancer Differs between Distinct Populations.
Gastric cancer (GC) has the fifth highest incidence among cancers and is the fourth leading cause of cancer-related death GC has predominantly a higher number of cases in certain ethnic groups such as the Korean population. GC found at an early stage is more treatable and has a higher survival rate as compared with GC found at a late stage. However, a diagnosis of GC is often delayed due to the lack of early symptoms and available screening programs in United States. Extracellular RNA (exRNA) is an emerging paradigm; exRNAs have the potential to serve as biomarkers in panels aimed at early detection of cancer. We previously reported the successful use of a panel of salivary exRNA for detecting GC in a high-prevalence Korean cohort, and that genetic changes reflected cancer-associated salivary exRNA changes. The current study is a case-control study of salivary exRNA biomarkers for detecting GC in an ethnically distinct U.S. cohort. A model constructed for the U.S. cohort combined demographic characteristics and salivary miRNA and mRNA biomarkers for GC and yielded an area under the receiver operating characteristic (ROC) curve (AUC) of 0.78. However, the constituents of this model differed from that constructed for the Korean cohort, thus, emphasizing the importance of population-specific biomarker development and validation
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Salivary biomarkers in cancer detection
Cancer is the second most common cause of death in the USA. Its symptoms are often not specific and absent, until the tumors have already metastasized. Therefore, there is an urgent demand for developing rapid, highly accurate and noninvasive tools for cancer screening, early detection, diagnostics, staging and prognostics. Saliva as a multi-constituent oral fluid comprises secretions from the major and minor salivary glands, extensively supplied by blood. Molecules such as DNAs, RNAs, proteins, metabolites, and microbiota, present in blood, could be also found in saliva. Recently, salivary diagnostics has drawn significant attention for the detection of specific biomarkers, since the sample collection and processing are simple, cost-effective, and precise and do not cause patient discomfort. Here, we review recent salivary candidate biomarkers for systemic cancers by dividing them according to their origin into: genomic, transcriptomic, proteomic, metabolomic and microbial types
Integrative analysis reveals multiple modes of LXR transcriptional regulation in liver.
The nuclear receptors liver X receptor (LXR) α and β play crucial roles in hepatic metabolism. Many genes induced in response to pharmacologic LXR agonism have been defined; however, the transcriptional consequences of loss of LXR binding to its genomic targets are less well characterized. Here, we addressed how deletion of both LXRα and LXRβ from mouse liver (LXR double knockout [DKO]) affects the transcriptional regulatory landscape by integrating changes in LXR binding, chromatin accessibility, and gene expression. Many genes involved in fatty acid metabolism showed reduced expression and chromatin accessibility at their intergenic and intronic regions in LXRDKO livers. Genes that were up-regulated with LXR deletion had increased chromatin accessibility at their promoter regions and were enriched for functions not linked to lipid metabolism. Loss of LXR binding in liver reduced the activity of a broad set of hepatic transcription factors, inferred through changes in motif accessibility. By contrast, accessibility at promoter nuclear factor Y (NF-Y) motifs was increased in the absence of LXR. Unexpectedly, we also defined a small set of LXR targets for direct ligand-dependent repression. These genes have LXR-binding sites but showed increased expression in LXRDKO liver and reduced expression in response to the LXR agonist. In summary, the binding of LXRs to the hepatic genome has broad effects on the transcriptional landscape that extend beyond its canonical function as an activator of lipid metabolic genes
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