| Literature DB >> 29922126 |
Chanan Meydan1, Uriya Bekenstein2, Hermona Soreq2.
Abstract
Sepsis and metabolic syndrome (MetS) are both inflammation-related entities with high impact for human health and the consequences of concussions. Both represent imbalanced parasympathetic/cholinergic response to insulting triggers and variably uncontrolled inflammation that indicates shared upstream regulators, including short microRNAs (miRs) and long non-coding RNAs (lncRNAs). These may cross talk across multiple systems, leading to complex molecular and clinical outcomes. Notably, biomedical and RNA-sequencing based analyses both highlight new links between the acquired and inherited pathogenic, cardiac and inflammatory traits of sepsis/MetS. Those include the HOTAIR and MIAT lncRNAs and their targets, such as miR-122, -150, -155, -182, -197, -375, -608 and HLA-DRA. Implicating non-coding RNA regulators in sepsis and MetS may delineate novel high-value biomarkers and targets for intervention.Entities:
Keywords: SNPs; metabolic syndrome; miRs; ncRNAs; sepsis
Year: 2018 PMID: 29922126 PMCID: PMC5996041 DOI: 10.3389/fnmol.2018.00189
Source DB: PubMed Journal: Front Mol Neurosci ISSN: 1662-5099 Impact factor: 5.639
Figure 1Sepsis and metabolic syndrome (MetS) share ncRNA controllers and inflammation characteristics. (A) Scheme of the impact over mortality rate for both sepsis and MetS. Sepsis involves rapid dynamics with mortality rate peaking in the scale of days, whereas entailed mortality from MetS related complications develops over many years. (B) Sepsis and MetS are both subject to ncRNA regulation, and share common microRNA (miR) and ncRNA regulators. (C) Long non-coding RNAs (LncRNAs; left pane, denoted as black line) exert diverse functions including chromatin modification, ribonucleoprotein complex formation or “sponge” activities, whereas miRs (right hand side, pink lines) primarily suppress their targets via post-transcriptional interaction with short sequence motifs on their target mRNAs, and lead to physiological changes (e.g., cholinergic changes, as a result of acetylcholinesterase (AChE) reduction).
Non-coding RNA molecules associated with both sepsis and metabolic syndrome (MetS).
| Non-coding RNA | Mets/Sepsis | Role | Reference | |
|---|---|---|---|---|
| miR-122 | MetS | Modulation of hepatocyte-associated proteins (ACC2, SCD1, ACLY, AMP-K) and lipid metabolism | Esau et al. ( | |
| Sepsis | Decreased in sepsis vs. healthy controls and non-septic SIRS, correlates with sepsis mortality | Caserta et al. ( | ||
| Increased in chronic liver infection with hepatitis C virus and involved in its pathogenesis | Janssen et al. ( | |||
| Marker for abnormal coagulation in sepsis | Janssen et al. ( | |||
| miR-150 | MetS | Upregulated in adipose and hepatic tissues, and in insulin resistance | Karolina et al. ( | |
| Sepsis | Downregulated in sepsis vs. non-septic SIRS and healthy controls, correlates with SOFA score, predictive of mortality | Vasilescu et al. ( | ||
| Correlates with proinflammatory cytokines (TNFα, IL-10, IL-18) | Vasilescu et al. ( | |||
| miR-182 | MetS | Implicated in insulin regulation and diabetes-associated muscle atrophy | Poy et al. ( | |
| Sepsis | Upregulated in sepsis in GWAS | Vasilescu et al. ( | ||
| miR-197 | MetS | Upregulated in adipose tissue | Karolina et al. ( | |
| Sepsis | Upregulated in lung infections | Tang et al. ( | ||
| Decreased in chronic hepatitis B and enterovirus infections | Tang et al. ( | |||
| miR-375 | MetS | Suppresses insulin secretion | Zampetaki and Mayr ( | |
| Sepsis | Upregulated in hepatitis B virus infections | Li et al. ( | ||
| miR-155 | MetS | Involved in the pathogenesis of atherosclerosis and diabetes | Nazari-Jahantigh et al. ( | |
| Sepsis | Involved in bacterial infections and hepatitis C-associated liver disease | Correia et al. ( | ||
| miR-608 | MetS | Involved in cholinergic signaling with implication for hypertension | Hanin et al. ( | |
| Sepsis | SNP is a prognostic marker for reduced risk of sepsis after major trauma | Zhang et al. ( | ||
| Interaction with IL-6 | Hanin et al. ( | |||
| HOTAIR | MetS | Implicated in adipocyte differentiation | Wu et al. ( | |
| Sepsis | Promotes TNFα production in cardiomyocites in sepsis, through NF-kB pathway | Wu et al. ( | ||
| Lethe | MetS | Leads to inflammatory effects in high-glucose environment | Zgheib et al. ( | |
| Sepsis | Regulates NF-kB and induced by IL-1β and TNFα | Rapicavoli et al. ( | ||
| NEAT1 | MetS | Regulates PPARg2 splicing during adipogenesis | Chen ( | |
| Mediates miR-140-induced adipogenesis | Gernapudi et al. ( | |||
| Sepsis | Induced by herpesvirus infections in a STAT3-dependant manner | Wang et al. ( | ||
| Upregulated in Hantavirus infections, downregulation | Ma et al. ( | |||
| DMRT2 | MetS | Suppressed in adipose tissue of obese humans (RNA sequencing) | Liu et al. ( | |
| Sepsis | Induced | Liu et al. ( | ||
| TP53I13 | MetS | Suppressed in adipose tissue of obese humans (RNA sequencing) | Liu et al. ( | |
| Sepsis | Induced | Liu et al. ( | ||
| Cox2 | Sepsis | Induced by Toll-like receptor activation | Carpenter et al. ( | |
| PACER | Sepsis | Involved in assembly of NF-kB | Krawczyk and Emerson ( | |
| Lnc-DC | Sepsis | Regulates dendritic cell differentiation | Wang et al. ( | |
| THRIL | Sepsis | Upregulates TNFα | Li et al. ( | |
| TNFAIP3 | Sepsis | Regulated by TNFα, coregulator of NF-kB | Vereecke et al. ( | |
Shown are lncRNAs and miRs reported to affect MetS and sepsis before and after concussions, including their predicted mechanism of action and associated molecular machinery (See Supplementary Material for additional citations).
Molecular elements associated with the long non-coding RNA (lncRNA) HOTAIR in sepsis and MetS.
| Protein symbol | Human protein | Sepsis dataset of CAPSOD study, GSE63042 | |||||
|---|---|---|---|---|---|---|---|
| Protein name | Atlas, v16.1 | ||||||
| Tissue-wide average expression (TPM) | Adipose tissue expression (TPM) | Sepsis (mortality) vs. non-infectious SIRS, | Septic shock vs. non-infectious SIRS, | Severe sepsis vs. non-infectious SIRS, | Uncomplicated sepsis vs. non-infectious SIRS, | All sepsis vs. non-infectious SIRS, | |
| 26.0 | 35.8 | 0.12 | 0.24 | 0.15 | 0.33 | 0.10 | |
| Salvador homolog 1 | |||||||
| 44.2 | 101.0 | 0.09 | 0.61 | 0.51 | 0.15 | 0.67 | |
| Kruppel-like factor 4 | |||||||
| 6.8 | 1.8 | 0.89 | 0.80 | 0.63 | 0.29 | 0.75 | |
| Enhancer of zeste homolog 2 | |||||||
| Suppressor of zeste 12 homolog | 19.4 | 13.9 | 0.40 | 0.89 | 0.94 | 0.74 | 0.78 |
| Conserved helix-loop-helix ubiquitous kinase | 12.6 | 15.0 | 0.49 | 0.50 | 0.25 | 0.98 | 0.66 |
| Inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase beta | 8.9 | 7.4 | 0.56 | 0.22 | 0.09 | 0.17 | |
| 20.6 | 55.8 | 0.15 | 0.15 | 0.21 | 0.16 | ||
| Notch homolog 3 | |||||||
| 36.4 | 33.2 | 0.91 | 0.21 | 0.23 | 0.13 | 0.21 | |
| ELAV-like 1 (Hu antigen R) | |||||||
| 35.4 | 13.7 | 0.26 | 0.75 | 0.72 | 0.55 | 0.39 | |
| Lysine Demethylase 3A | |||||||
| 4.0 | 9.8 | * | * | * | * | * | |
| Snail homolog 1 | |||||||
| 0.3 | 0.3 | 0.81 | 0.55 | 0.68 | 0.22 | 0.60 | |
| Tumor necrosis factor | |||||||
| Insulin-like growth factor 2 (somatomedin A) | 147.6 | 102.0 | * | * | * | * | * |
| 4.6 | 0.6 | * | * | * | * | * | |
| Protocadherin 10 | |||||||
| 9.2 | 0.3 | * | * | * | * | * | |
| Forkhead box A1 | |||||||
| 6.0 | 2.4 | 0.58 | 0.92 | 0.50 | 0.48 | 0.60 | |
| Forkhead box M1 | |||||||
| Catenin (cadherin-associated protein), beta 1, 88 kDa | 154.3 | 156.3 | 0.44 | 0.14 | |||
| 12.2 | 10.0 | 0.44 | 0.14 | ||||
| SET domain containing 2 | |||||||
| 3.2 | 0.3 | * | * | * | * | * | |
| Astrotactin 1 | |||||||
| 0.2 | 0.0 | 0.51 | 0.39 | 0.15 | 0.52 | 0.94 | |
| Ptotocadherin alpha-1 | |||||||
| Mucin 5AC, oligomeric mucus/gel-forming | 10.2 | 0.0 | * | * | * | * | * |
| 8.0 | 18.3 | * | * | * | * | * | |
| Neurotrimin | |||||||
| 28.8 | 16.1 | 0.22 | |||||
| Protein tyrosine kinase 2 beta | |||||||
| 955.0 | 2578.1 | 0.18 | 0.07 | ||||
| Vimentin | |||||||
*Unavailable data. Shown are the 23 known mediators associated with HOTAIR; their expression in adipose tissue relative to tissue-average, according to RNA sequencing of tissues from healthy human subjects (The Human Protein Atlas 16.1); and T-test values of their differential blood cells and liver expression levels in various sepsis conditions vs. non-septic SIRS (CAPSOD study, see text), in a descending order (mortality > shock > severe > uncomplicated). Significantly changed expression levels in the CAPSOD database are bolded (P value < 0.1).
Figure 2The lncRNA MIAT targets multi-chromosome originated sepsis and MetS-related miRs. MIAT and miR-150 crosstalk exerts inflammatory impact in sepsis and MetS. Shown are selected inflammation-related targets of miR-150 which associate with the clinical characteristics of sepsis (red) or MetS (blue).
Figure 3Asymmetric impacts of single nucleotide polymorphisms (SNPs) interrupting miR-608/AChE interaction highlight the relevance for concussions. SNPs in the miR-608 and AChE genes may both interrupt the miR-608/AChE interaction, but the multi-target impact of miR-608 affects the risk of sepsis (red) whereas the AChE SNP relates to MetS (blue). Specifically, the miR-608 SNP (left) may modulate both HLA-DRA and inflammation by interrupting its cholinergic blockade. The AChE SNP (right) may likewise interfere with the cholinergic blockade of NFkB-mediated inflammation, while modulating anxiety, cortisol and blood pressure in MetS patients, which should be highly relevant for the consequences of concussions.