Is obstructive sleep apnea a circadian rhythm disorder?

Obstructive sleep apnea is the most common sleep-related breathing disorder worldwide and remains underdiagnosed. Its multiple associated comorbidities contribute to a decreased quality of life and work performance as well as an increased risk of death. Standard treatment seems to have limited effects on cardiovascular and metabolic aspects of the disease, emphasising the need for early diagnosis and additional therapeutic approaches. Recent evidence suggests that the dysregulation of circadian rhythms, processes with endogenous rhythmicity that are adjusted to the environment through various cues, is involved in the pathogenesis of comorbidities. In patients with obstructive sleep apnea, altered circadian gene expression patterns have been demonstrated. Obstructive respiratory events may promote circadian dysregulation through the effects of sleep disturbance and intermittent hypoxia, with subsequent inflammation and disruption of neural and hormonal homeostasis. In this review, current knowledge on obstructive sleep apnea, circadian rhythm regulation, and circadian rhythm sleep disorders is summarised. Studies that connect obstructive sleep apnea to circadian rhythm abnormalities are critically evaluated. Furthermore, pathogenetic mechanisms that may underlie this association, most notably hypoxia signalling, are presented. A bidirectional relationship between obstructive sleep apnea and circadian rhythm dysregulation is proposed. Approaching obstructive sleep apnea as a circadian rhythm disorder may prove beneficial for the development of new, personalised diagnostic, therapeutic and prognostic tools. However, further studies are needed before the clinical approach to obstructive sleep apnea includes targeting the circadian system.

The role of bile acids in carcinogenesis.

Bile acids are soluble derivatives of cholesterol produced in the liver that subsequently undergo bacterial transformation yielding a diverse array of metabolites. The bulk of bile acid synthesis takes place in the liver yielding primary bile acids; however, other tissues have also the capacity to generate bile acids (e.g. ovaries). Hepatic bile acids are then transported to bile and are subsequently released into the intestines. In the large intestine, a fraction of primary bile acids is converted to secondary bile acids by gut bacteria. The majority of the intestinal bile acids undergo reuptake and return to the liver. A small fraction of secondary and primary bile acids remains in the circulation and exert receptor-mediated and pure chemical effects (e.g. acidic bile in oesophageal cancer) on cancer cells. In this review, we assess how changes to bile acid biosynthesis, bile acid flux and local bile acid concentration modulate the behavior of different cancers. Here, we present in-depth the involvement of bile acids in oesophageal, gastric, hepatocellular, pancreatic, colorectal, breast, prostate, ovarian cancer. Previous studies often used bile acids in supraphysiological concentration, sometimes in concentrations 1000 times higher than the highest reported tissue or serum concentrations likely eliciting unspecific effects, a practice that we advocate against in this review. Furthermore, we show that, although bile acids were classically considered as pro-carcinogenic agents (e.g. oesophageal cancer), the dogma that switch, as lower concentrations of bile acids that correspond to their serum or tissue reference concentration possess anticancer activity in a subset of cancers. Differences in the response of cancers to bile acids lie in the differential expression of bile acid receptors between cancers (e.g. FXR vs. TGR5). UDCA, a bile acid that is sold as a generic medication against cholestasis or biliary surge, and its conjugates were identified with almost purely anticancer features suggesting a possibility for drug repurposing. Taken together, bile acids were considered as tumor inducers or tumor promoter molecules; nevertheless, in certain cancers, like breast cancer, bile acids in their reference concentrations may act as tumor suppressors suggesting a Janus-faced nature of bile acids in carcinogenesis.

Bacterial DNA Recognition by SERS Active Plasma-Coupled Nanogold.

It is shown that surface-enhanced Raman spectroscopy (SERS) can identify bacteria based on their genomic DNA composition, acting as a "sample-distinguishing marker". Successful spectral differentiation of bacterial species was accomplished with nanogold aggregates synthesized through single-step plasma reduction of the ionic gold-containing vapored precursor. A high enhancement factor (EF = 107) in truncated coupled plasmonic particulates allowed SERS-probing at nanogram sample quantities. Simulations confirmed the occurrence of the strongest electric field confinement within nanometric gaps between gold dimers/chains from where the molecular fingerprints of bacterial DNA fragments gained photon scattering enhancement. The most prominent Raman modes linked to fundamental base-pair molecular vibrations were deconvoluted and used to proceed with nitrogenous base content estimation. The genomic composition (percentage of guanine-cytosine and adenine-thymine) was successfully validated by third-generation sequencing using nanopore technology, further proving that the SERS technique can be employed to swiftly specify bioentities by the discriminative principal-component statistical approach.

Detecting gene-gene interactions from GWAS using diffusion kernel principal components.

Genes and gene products do not function in isolation but as components of complex networks of macromolecules through physical or biochemical interactions. Dependencies of gene mutations on genetic background (i.e., epistasis) are believed to play a role in understanding molecular underpinnings of complex diseases such as inflammatory bowel disease (IBD). However, the process of identifying such interactions is complex due to for instance the curse of high dimensionality, dependencies in the data and non-linearity. Here, we propose a novel approach for robust and computationally efficient epistasis detection. We do so by first reducing dimensionality, per gene via diffusion kernel principal components (kpc). Subsequently, kpc gene summaries are used for downstream analysis including the construction of a gene-based epistasis network. We show that our approach is not only able to recover known IBD associated genes but also additional genes of interest linked to this difficult gastrointestinal disease.

Community effort endorsing multiscale modelling, multiscale data science and multiscale computing for systems medicine.

Systems medicine holds many promises, but has so far provided only a limited number of proofs of principle. To address this road block, possible barriers and challenges of translating systems medicine into clinical practice need to be identified and addressed. The members of the European Cooperation in Science and Technology (COST) Action CA15120 Open Multiscale Systems Medicine (OpenMultiMed) wish to engage the scientific community of systems medicine and multiscale modelling, data science and computing, to provide their feedback in a structured manner. This will result in follow-up white papers and open access resources to accelerate the clinical translation of systems medicine.

Pyridylethanol(phenylethyl)amines are non-azole, highly selective Candida albicans sterol 14α-demethylase inhibitors.

Sterol 14α-demethylase (CYP51) is the main drug target for the treatment of fungal infections. The worldwide increase in the incidence of opportunistic fungal infections and the emerging resistance to available azole-based antifungal drugs, raise the need to develop structurally distinct and selective fungal CYP51 inhibitors. In this work we have, for the first time, investigated the binding of pyridylethanol(phenylethyl)amines to any fungal CYP51. The comparison of the binding to Candida albicans and human CYP51 studied by spectroscopic and modeling methods revealed moieties decisive for selectivity and potency and resulted in the development of highly selective derivatives with significantly increased inhibitory potency. The structure-based insight into the selectivity requirements of this new chemical class of fungal CYP51 inhibitors, their unique binding properties and the low molecular weight of lead derivatives offer novel directions for the targeted development of antifungal clinical candidates.

Sex-dependent dynamics of metabolism in primary mouse hepatocytes.

The liver is one of the most sexually dimorphic organs. The hepatic metabolic pathways that are subject to sexual dimorphism include xenobiotic, amino acid and lipid metabolism. Non-alcoholic fatty liver disease and hepatocellular carcinoma are among diseases with sex-dependent prevalence, progression and outcome. Although male and female livers differ in their abilities to metabolize foreign compounds, including drugs, sex-dependent treatment and pharmacological dynamics are rarely applied in all relevant cases. Therefore, it is important to consider hepatic sexual dimorphism when developing new treatment strategies and to understand the underlying mechanisms in model systems. We isolated primary hepatocytes from male and female C57BL6/N mice and examined the sex-dependent transcriptome, proteome and extracellular metabolome parameters in the course of culturing them for 96 h. The sex-specific gene expression of the general xenobiotic pathway altered and the female-specific expression of Cyp2b13 and Cyp2b9 was significantly reduced during culture. Sex-dependent differences of several signaling pathways increased, including genes related to serotonin and melatonin degradation. Furthermore, the ratios of male and female gene expression were inversed for other pathways, such as amino acid degradation, beta-oxidation, androgen signaling and hepatic steatosis. Because the primary hepatocytes were cultivated without the influence of known regulators of sexual dimorphism, these results suggest currently unknown modulatory mechanisms of sexual dimorphism in vitro. The large sex-dependent differences in the regulation and dynamics of drug metabolism observed during cultivation can have an immense influence on the evaluation of pharmacodynamic processes when conducting initial preclinical trials to investigate potential new drugs.

Identification of Novel RNA Binding Proteins Influencing Circular RNA Expression in Hepatocellular Carcinoma.

Circular RNAs (circRNAs) are increasingly recognized as having a role in cancer development. Their expression is modified in numerous cancers, including hepatocellular carcinoma (HCC); however, little is known about the mechanisms of their regulation. The aim of this study was to identify regulators of circRNAome expression in HCC. Using publicly available datasets, we identified RNA binding proteins (RBPs) with enriched motifs around the splice sites of differentially expressed circRNAs in HCC. We confirmed the binding of some of the candidate RBPs using ChIP-seq and eCLIP datasets in the ENCODE database. Several of the identified RBPs were found to be differentially expressed in HCC and/or correlated with the overall survival of HCC patients. According to our bioinformatics analyses and published evidence, we propose that NONO, PCPB2, PCPB1, ESRP2, and HNRNPK are candidate regulators of circRNA expression in HCC. We confirmed that the knocking down the epithelial splicing regulatory protein 2 (ESRP2), known to be involved in the maintenance of the adult liver phenotype, significantly changed the expression of candidate circRNAs in a model HCC cell line. By understanding the systemic changes in transcriptome splicing, we can identify new proteins involved in the molecular pathways leading to HCC development and progression.

Common Transcriptional Program of Liver Fibrosis in Mouse Genetic Models and Humans.

Multifactorial metabolic diseases, such as non-alcoholic fatty liver disease, are a major burden to modern societies, and frequently present with no clearly defined molecular biomarkers. Herein we used system medicine approaches to decipher signatures of liver fibrosis in mouse models with malfunction in genes from unrelated biological pathways: cholesterol synthesis-Cyp51, notch signaling-Rbpj, nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling-Ikbkg, and unknown lysosomal pathway-Glmp. Enrichment analyses of Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome and TRANScription FACtor (TRANSFAC) databases complemented with genome-scale metabolic modeling revealed fibrotic signatures highly similar to liver pathologies in humans. The diverse genetic models of liver fibrosis exposed a common transcriptional program with activated estrogen receptor alpha (ERα) signaling, and a network of interactions between regulators of lipid metabolism and transcription factors from cancer pathways and the immune system. The novel hallmarks of fibrosis are downregulated lipid pathways, including fatty acid, bile acid, and steroid hormone metabolism. Moreover, distinct metabolic subtypes of liver fibrosis were proposed, supported by unique enrichment of transcription factors based on the type of insult, disease stage, or potentially, also sex. The discovered novel features of multifactorial liver fibrotic pathologies could aid also in improved stratification of other fibrosis related pathologies.

Novel insights into biological roles of inducible cAMP early repressor ICER.

ICER corresponds to a group of alternatively spliced Inducible cAMP Early Repressors with high similarity, but multiple roles, including in circadian rhythm, and are involved in attenuation of cAMP-dependent gene expression. We present experimental and in silico data revealing biological differences between the isoforms with exon gamma (ICER) or without it (ICERγ). Both isoforms are expressed in the liver and the adrenal glands and can derive from differential splicing. In adrenals the expression is circadian, with maximum at ZT12 and higher amplitude of Icerγ. In the liver, the expression of Icerγ is lower than Icer in the 24 h time frame. Icer mRNA has a delayed early response to forskolin. The longer ICER protein binds to three DNA grooves of the Per1 promoter, while ICERγ only to two, as deduced by molecular modelling. This is in line with gel shift competition assays showing stronger binding of ICER to Per1 promotor. Only Icerγ siRNA provoked an increase of Per1 expression. In conclusion, we show that ICER and ICERγ have distinct biochemical properties in tissue expression, DNA binding, and response to forskolin. Data are in favour of ICERγ as the physiologically important form in hepatic cells where weaker binding of repressor might be preferred in guiding the cAMP-dependent response.

Regulation of cytochrome P450 enzyme activity and expression by nitric oxide in the context of inflammatory disease.

Many hepatic cytochrome P450 enzymes and their associated drug metabolizing activities are down-regulated in disease states, and much of this has been associated with inflammatory cytokines and their signaling pathways. One such pathway is the induction of inducible nitric oxide synthase (NOS2) and generation of nitric oxide (NO) in many tissues and cells including the liver and hepatocytes. Experiments in the 1990s demonstrated that NO could bind to and inhibit P450 enzymes, and suggested that inhibition of NOS could attenuate, and NO generation could mimic, the down-regulation by inflammatory stimuli of not only P450 catalytic activities but also of mRNA expression and protein levels of certain P450 enzymes. This review will summarize and examine the evidence that NO functionally inhibits and down-regulates P450 enzymes in vivo and in vitro, with a particular focus on the mechanisms by which these effects are achieved.

Simplified LC-MS Method for Analysis of Sterols in Biological Samples.

We developed a simple and robust liquid chromatographic/mass spectrometric method (LC-MS) for the quantitative analysis of 10 sterols from the late part of cholesterol synthesis (zymosterol, dehydrolathosterol, 7-dehydrodesmosterol, desmosterol, zymostenol, lathosterol, FFMAS, TMAS, lanosterol, and dihydrolanosterol) from cultured human hepatocytes in a single chromatographic run using a pentafluorophenyl (PFP) stationary phase. The method also avails on a minimized sample preparation procedure in order to obtain a relatively high sample throughput. The method was validated on 10 sterol standards that were detected in a single chromatographic LC-MS run without derivatization. Our developed method can be used in research or clinical applications for disease-related detection of accumulated cholesterol intermediates. Disorders in the late part of cholesterol synthesis lead to severe malformation in human patients. The developed method enables a simple, sensitive, and fast quantification of sterols, without the need of extended knowledge of the LC-MS technique, and represents a new analytical tool in the rising field of cholesterolomics.

Tick-tock hedgehog-mutual crosstalk with liver circadian clock promotes liver steatosis.

BACKGROUND & AIMS: The mammalian circadian clock controls various aspects of liver metabolism and integrates nutritional signals. Recently, we described Hedgehog (Hh) signaling as a novel regulator of liver lipid metabolism. Herein, we investigated crosstalk between hepatic Hh signaling and circadian rhythm. METHODS: Diurnal rhythms of Hh signaling were investigated in liver and hepatocytes from mice with ablation of Smoothened (SAC-KO) and crossbreeds with PER2::LUC reporter mice. By using genome-wide screening, qPCR, immunostaining, ELISA and RNAi experiments in vitro we identified relevant transcriptional regulatory steps. Shotgun lipidomics and metabolic cages were used for analysis of metabolic alterations and behavior. RESULTS: Hh signaling showed diurnal oscillations in liver and hepatocytes in vitro. Correspondingly, the level of Indian Hh, oscillated in serum. Depletion of the clock gene Bmal1 in hepatocytes resulted in significant alterations in the expression of Hh genes. Conversely, SAC-KO mice showed altered expression of clock genes, confirmed by RNAi against Gli1 and Gli3. Genome-wide screening revealed that SAC-KO hepatocytes showed time-dependent alterations in various genes, particularly those associated with lipid metabolism. The clock/hedgehog module further plays a role in rhythmicity of steatosis, and in the response of the liver to a high-fat diet or to differently timed starvation. CONCLUSIONS: For the first time, Hh signaling in hepatocytes was found to be time-of-day dependent and to feed back on the circadian clock. Our findings suggest an integrative role of Hh signaling, mediated mainly by GLI factors, in maintaining homeostasis of hepatic lipid metabolism by balancing the circadian clock. LAY SUMMARY: The results of our investigation show for the first time that the Hh signaling in hepatocytes is time-of-day dependent, leading to differences not only in transcript levels but also in the amount of Hh ligands in peripheral blood. Conversely, Hh signaling is able to feed back to the circadian clock.

Large-scale computational models of liver metabolism: How far from the clinics?

Understanding the dynamics of human liver metabolism is fundamental for effective diagnosis and treatment of liver diseases. This knowledge can be obtained with systems biology/medicine approaches that account for the complexity of hepatic responses and their systemic consequences in other organs. Computational modeling can reveal hidden principles of the system by classification of individual components, analyzing their interactions and simulating the effects that are difficult to investigate experimentally. Herein, we review the state-of-the-art computational models that describe liver dynamics from metabolic, gene regulatory, and signal transduction perspectives. We focus especially on large-scale liver models described either by genome scale metabolic networks or an object-oriented approach. We also discuss the benefits and limitations of each modeling approach and their value for clinical applications in diagnosis, therapy, and prevention of liver diseases as well as precision medicine in hepatology. (Hepatology 2017;66:1323-1334).

Meta-Analysis and Experimental Validation Identified FREM2 and SPRY1 as New Glioblastoma Marker Candidates.

Glioblastoma (GB) is the most aggressive brain malignancy. Although some potential glioblastoma biomarkers have already been identified, there is a lack of cell membrane-bound biomarkers capable of distinguishing brain tissue from glioblastoma and/or glioblastoma stem cells (GSC), which are responsible for the rapid post-operative tumor reoccurrence. In order to find new GB/GSC marker candidates that would be cell surface proteins (CSP), we have performed meta-analysis of genome-scale mRNA expression data from three data repositories (GEO, ArrayExpress and GLIOMASdb). The search yielded ten appropriate datasets, and three (GSE4290/GDS1962, GSE23806/GDS3885, and GLIOMASdb) were used for selection of new GB/GSC marker candidates, while the other seven (GSE4412/GDS1975, GSE4412/GDS1976, E-GEOD-52009, E-GEOD-68848, E-GEOD-16011, E-GEOD-4536, and E-GEOD-74571) were used for bioinformatic validation. The selection identified four new CSP-encoding candidate genes—CD276, FREM2, SPRY1, and SLC47A1—and the bioinformatic validation confirmed these findings. A review of the literature revealed that CD276 is not a novel candidate, while SLC47A1 had lower validation test scores than the other new candidates and was therefore not considered for experimental validation. This validation revealed that the expression of FREM2—but not SPRY1—is higher in glioblastoma cell lines when compared to non-malignant astrocytes. In addition, FREM2 gene and protein expression levels are higher in GB stem-like cell lines than in conventional glioblastoma cell lines. FREM2 is thus proposed as a novel GB biomarker and a putative biomarker of glioblastoma stem cells. Both FREM2 and SPRY1 are expressed on the surface of the GB cells, while SPRY1 alone was found overexpressed in the cytosol of non-malignant astrocytes.

Computational Modelling of Liver Metabolism and its Applications in Research and the Clinics.

Computational models of liver metabolism are gaining an increasing importance within the research community. Moreover, their first clinical applications have been reported in recent years in the context of personalised and systems medicine. Herein, we survey selected experimental models together with the computational modelling approaches that are used to describe the metabolic processes of the liver in silico. We also review the recent developments in the large-scale hepatic computational models where we focus on object-oriented models as a part of our research. The object-oriented modelling approach is beneficial in efforts to describe the interactions between the tissues, such as how metabolism of the liver interacts with metabolism of other tissues via blood. Importantly, this modelling approach can account as well for transcriptional and post-translational regulation of metabolic reactions which is a difficult task to achieve. The current and potential clinical applications of large-scale hepatic models are also discussed. We conclude with the future perspectives within the systems and translational medicine research community.

Rosuvastatin and Atorvastatin Are Ligands of the Human Constitutive Androstane Receptor/Retinoid X Receptor α Complex.

Statins are well known lipid lowering agents that inhibit the enzyme 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA) reductase. They also activate drug metabolism but their exact receptor-mediated action has not been proven so far. We tested whether atorvastatin and rosuvastatin are direct ligands of human constitutive androstane receptor (CAR). We measured binding activities of atorvastatin and rosuvastatin to the human constitutive androstane receptor/retinoid X receptor α ligand-binding domain (CAR/RXRα-LBD) heterodimer with surface plasmon resonance (SPR). Additionally, three-dimensional models of CAR/RXRα-LBD were constructed by ligand-based and structure-based in silico modeling. Experiments and computational modeling show that atorvastatin and rosuvastatin bind to the human CAR/RXRα-LBD heterodimer, suggesting both can modulate the activity of CAR through direct interaction with the LBD of this receptor. We confirm that atorvastatin and rosuvastatin are direct ligands of CAR. The clinical consequences of CAR activation by statins are in their potential drug-drug interactions, and changes in glucose and energy metabolism.

Interaction of PER2 with the Constitutive Androstane Receptor Possibly Links Circadian Rhythms to Metabolism.

Period 2 (PER2) is an important factor in daily oscillations called circadian rhythms, which are emerging as one of the most important regulatory networks, responsible for homeostasis and transcriptional regulation of a number of genes. Our work shows that PER2 could act as a co-activator of the constitutive androstane receptor (CAR), a key nuclear receptor (NR) that regulates the metabolism of endobiotics and xenobiotics. Bioinformatic analysis shows that PER2 and CAR possess structural elements that could enable them to interact which was confirmed experimentally by CoIP experiment. Co-transfection of mouse hepatocarcinoma cells with plasmids overexpressing Per2 and Car increases expression of Bmal1, a potential CAR target gene, more than transfections with Car only. This is the first report indicating the interaction of PER2 and CAR.

Amyloid precursor protein α- and ß-cleaved ectodomains exert opposing control of cholesterol homeostasis via SREBP2.

Amyloid precursor protein (APP) is ubiquitously expressed. Studies in neuronal cells have implicated APP or its fragments as negative regulators of cholesterol metabolism. In the current study, APP acted, via its α-cleavage, as a positive regulator of sterol regulatory element-binding protein-2 (SREBP2) signaling in human astrocytic cells (U251MG), hepatic cells (HepG2), and primary fibroblasts, leading to an approximate 30% increase in SRE-dependent gene expression and, consequently, enhanced cholesterol biosynthesis and LDL receptor levels. This effect was mediated via the secretory ectodomain APPsα. The ß-cleaved ectodomain, in turn, repressed SRE-dependent gene expression by up to ∼ 30%. This resulted in decreased cholesterol synthesis and LDL receptor content, establishing a physiological feedback loop in cholesterol-loaded cells, where APP undergoes preferential ß-cleavage. Patients with familial Alzheimer's disease had decreased circulating lathosterol, reflecting hepatic cholesterol synthesis, and their fibroblasts had reduced LDL receptor content, which was alleviated by decreasing ß-cleavage. These results show that APP regulates cholesterol metabolism in cells relevant for whole-body cholesterol balance and reveal that APP α- and ß-cleavages produce opposing paracrine regulators of SREBP2 signaling.

SteatoNet: the first integrated human metabolic model with multi-layered regulation to investigate liver-associated pathologies.

Current state-of-the-art mathematical models to investigate complex biological processes, in particular liver-associated pathologies, have limited expansiveness, flexibility, representation of integrated regulation and rely on the availability of detailed kinetic data. We generated the SteatoNet, a multi-pathway, multi-tissue model and in silico platform to investigate hepatic metabolism and its associated deregulations. SteatoNet is based on object-oriented modelling, an approach most commonly applied in automotive and process industries, whereby individual objects correspond to functional entities. Objects were compiled to feature two novel hepatic modelling aspects: the interaction of hepatic metabolic pathways with extra-hepatic tissues and the inclusion of transcriptional and post-transcriptional regulation. SteatoNet identification at normalised steady state circumvents the need for constraining kinetic parameters. Validation and identification of flux disturbances that have been proven experimentally in liver patients and animal models highlights the ability of SteatoNet to effectively describe biological behaviour. SteatoNet identifies crucial pathway branches (transport of glucose, lipids and ketone bodies) where changes in flux distribution drive the healthy liver towards hepatic steatosis, the primary stage of non-alcoholic fatty liver disease. Cholesterol metabolism and its transcription regulators are highlighted as novel steatosis factors. SteatoNet thus serves as an intuitive in silico platform to identify systemic changes associated with complex hepatic metabolic disorders.