The characteristic endogenous circadian rhythm of plasma glucocorticoid concentrations is made up from an underlying ultradian pulsatile secretory pattern. Recent evidence has indicated that this... Show moreThe characteristic endogenous circadian rhythm of plasma glucocorticoid concentrations is made up from an underlying ultradian pulsatile secretory pattern. Recent evidence has indicated that this ultradian cortisol pul-satility is crucial for normal emotional response in man. In this study, we investigate the anatomical tran-scriptional and cell type signature of brain regions sensitive to a loss of ultradian rhythmicity in the context of emotional processing. We combine human cell type and transcriptomic atlas data of high spatial resolution with functional magnetic resonance imaging (fMRI) data. We show that the loss of cortisol ultradian rhythm alters emotional processing response in cortical brain areas that are characterized by transcriptional and cellular profiles of GABAergic function. We find that two previously identified key components of rapid non-genomic GC signaling - the ANXA1 gene and retrograde endocannabinoid signaling - show most significant differential expression (q = 3.99e- 10) and enrichment (fold enrichment = 5.56, q = 9.09e-4). Our results further indicate that specific cell types, including a specific NPY-expressing GABAergic neuronal cell type, and specific G protein signaling cascades underly the cerebral effects of a loss of ultradian cortisol rhythm. Our results provide a biological mechanistic underpinning of our fMRI findings, indicating specific cell types and cascades as a target for manipulation in future experimental studies. Show less
Introduction: The leptin signaling pathway plays an important role as a key regulator of glucose homeostasis, metabolism control and systemic inflammatory responses. However, the metabolic effects... Show moreIntroduction: The leptin signaling pathway plays an important role as a key regulator of glucose homeostasis, metabolism control and systemic inflammatory responses. However, the metabolic effects of leptin on infectious diseases, for example tuberculosis (TB), are still little known. Objectives: In this study, we aim to investigate the role of leptin on metabolism in the absence and presence of mycobacterial infection in zebrafish larvae and mice. Methods: Metabolites in entire zebrafish larvae and the blood of mice were studied using high-resolution magic-angle-spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy and mass spectrometry, respectively. For transcriptome studies of zebrafish larvae, deep RNA sequencing was used. Results: The results show that leptin mutation leads to a similar metabolic syndrome as caused by mycobacterial infection in the two species, characterized by the decrease of 11 amine metabolites. In both species, this metabolic syndrome was not aggravated further when the leptin mutant was infected by mycobacteria. Therefore, we conclude that leptin and mycobacterial infection are both impacting metabolism non-synergistically. In addition, we studied the transcriptomes of lepb(ibl54) mutant zebrafish larvae and wild type (WT) siblings after mycobacterial infection. These studies showed that mycobacteria induced a very distinct transcriptome signature in the lepb(ibl54) mutant zebrafish compared to WT sibling control larvae. Furthermore, lepb(ibl55) Tg (pck1:luc1) zebrafish line was constructed and confirmed this difference in transcriptional responses. Conclusions: Leptin mutation and TB lead non-synergistically to a similar metabolic syndrome. Moreover, different transcriptomic responses in the lepb(ibl54) mutant and TB can lead to the similar metabolic end states. Show less
Population-scale expression profiling studies can provide valuable insights into biological and disease-underlying mechanisms. The availability of phenotypic traits is essential for studying... Show morePopulation-scale expression profiling studies can provide valuable insights into biological and disease-underlying mechanisms. The availability of phenotypic traits is essential for studying clinical effects. Therefore, missing, incomplete, or inaccurate phenotypic information can make analyses challenging and prevent RNA-seq or other omics data to be reused. A possible solution are predictors that infer clinical or behavioral phenotypic traits from molecular data. While such predictors have been developed based on different omics data types and are being applied in various studies, metabolomics-based surrogates are less commonly used than predictors based on DNA methylation profiles.In this study, we inferred 17 traits, including diabetes status and exposure to lipid medication, using previously trained metabolomic predictors. We evaluated whether these metabolomic surrogates can be used as an alternative to reported information for studying the respective phenotypes using expression profiling data of four population cohorts. For the majority of the 17 traits, the metabolomic surrogates performed similarly to the reported phenotypes in terms of effect sizes, number of significant associations, replication rates, and significantly enriched pathways.The application of metabolomics-derived surrogate outcomes opens new possibilities for reuse of multi-omics data sets. In studies where availability of clinical metadata is limited, missing or incomplete information can be complemented by these surrogates, thereby increasing the size of available data sets. Additionally, the availability of such surrogates could be used to correct for potential biological confounding. In the future, it would be interesting to further investigate the use of molecular predictors across different omics types and cohorts. Show less
Eenige, R. van; Panhuis, W.I.H.; Schoenke, M.; Jouffe, C.; Devilee, T.H.; Siebeler, R.; ... ; Kooijman, S. 2022
Objective: Brown adipose tissue (BAT) burns fatty acids (FAs) to produce heat, and shows diurnal oscillation in glucose and triglyceride (TG)derived FA-uptake, peaking around wakening. Here we... Show moreObjective: Brown adipose tissue (BAT) burns fatty acids (FAs) to produce heat, and shows diurnal oscillation in glucose and triglyceride (TG)derived FA-uptake, peaking around wakening. Here we aimed to gain insight in the diurnal regulation of metabolic BAT activity. Methods: RNA-sequencing, chromatin immunoprecipitation (ChIP)-sequencing, and lipidomics analyses were performed on BAT samples of wild type C57BL/6J mice collected at 3-hour intervals throughout the day. Knockout and overexpression models were used to study causal relationships in diurnal lipid handling by BAT. Results: We identified pronounced enrichment of oscillating genes involved in extracellular lipolysis in BAT, accompanied by oscillations of FA and monoacylglycerol content. This coincided with peak lipoprotein lipase (Lpl) expression, and was predicted to be driven by peroxisome proliferator-activated receptor gamma (PPARg) activity. ChIP-sequencing for PPARg confirmed oscillation in binding of PPARg to Lpl. Of the known LPL-modulators, angiopoietin-like 4 (Angptl4) showed the largest diurnal amplitude opposite to Lpl, and both Angptl4 knockout and overexpression attenuated oscillations of LPL activity and TG-derived FA-uptake by BAT. Conclusions: Our findings highlight involvement of PPARg and a crucial role of ANGPTL4 in mediating the diurnal oscillation of TG-derived FAuptake by BAT, and imply that time of day is essential when targeting LPL activity in BAT to improve metabolic health. (c) 2022 The Author(s). Published by Elsevier GmbH. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Show less
Background Leptin plays a critical role in the regulation of metabolic homeostasis. However, the molecular mechanism and cross talks between leptin and metabolic pathways leading to metabolic... Show moreBackground Leptin plays a critical role in the regulation of metabolic homeostasis. However, the molecular mechanism and cross talks between leptin and metabolic pathways leading to metabolic homeostasis across different species are not clear. This study aims to explore the effects of leptin in mice and zebrafish larvae by integration of metabolomics and transcriptomics. Different metabolomic approaches including mass spectrometry, nuclear magnetic resonance (NMR) and high-resolution magic-angle-spinning NMR spectrometry were used to investigate the metabolic changes caused by leptin deficiency in mutant ob/ob adult mice and lepb(-/-) zebrafish larvae. For transcriptome studies, deep RNA sequencing was used. Results Thirteen metabolites were identified as common biomarkers discriminating ob/ob mice and lepb(-/-) zebrafish larvae from their respective wild type controls: alanine, citrulline, ethanolamine, glutamine, glycine, histidine, isoleucine, leucine, methionine, phenylalanine, putrescine, serine and threonine. Moreover, we also observed that glucose and lipid levels were increased in lepb(-/-) zebrafish larvae compared to the lepb(+/+) group. Deep sequencing showed that many genes involved in proteolysis and arachidonic acid metabolism were dysregulated in ob/ob mice heads and lepb mutant zebrafish larvae compared to their wild type controls, respectively. Conclusions Leptin deficiency leads to highly similar metabolic alterations in metabolites in both mice and zebrafish larvae. These metabolic changes show similar features as observed during progression of tuberculosis in human patients, mice and zebrafish larvae. In addition, by studying the transcriptome, we found similar changes in gene regulation related to proteolysis and arachidonic acid metabolism in these two different in vivo models. Show less
Tio-Coma, M.; Kielbasa, S.M.; Eeden, S.J.F. van den; Mei, H.L.; Roy, J.C.; Wallinga, J.; ... ; Geluk, A. 2021
Background: Leprosy, a chronic infectious disease caused by Mycobacterium leprae, is often late-or misdiag-nosed leading to irreversible disabilities. Blood transcriptomic biomarkers that... Show moreBackground: Leprosy, a chronic infectious disease caused by Mycobacterium leprae, is often late-or misdiag-nosed leading to irreversible disabilities. Blood transcriptomic biomarkers that prospectively predict those who progress to leprosy (progressors) would allow early diagnosis, better treatment outcomes and facilitate interventions aimed at stopping bacterial transmission. To identify potential risk signatures of leprosy, we collected whole blood of household contacts (HC, n=5,352) of leprosy patients, including individuals who were diagnosed with leprosy 4-61 months after sample collection.Methods: We investigated differential gene expression (DGE) by RNA-Seq between progressors before pres-ence of symptoms (n=40) and HC (n=40), as well as longitudinal DGE within each progressor. A prospective leprosy signature was identified using a machine learning approach (Random Forest) and validated using reverse transcription quantitative PCR (RT-qPCR). Findings: Although no significant intra-individual longitudinal variation within leprosy progressors was iden-tified, 1,613 genes were differentially expressed in progressors before diagnosis compared to HC. We identi-fied a 13-gene prospective risk signature with an Area Under the Curve (AUC) of 95.2%. Validation of this RNA-Seq signature in an additional set of progressors (n=43) and HC (n=43) by RT-qPCR, resulted ina final 4 -gene signature, designated RISK4LEP (MT-ND2, REX1BD, TPGS1, UBC) (AUC=86.4%).Interpretation: This study identifies for the first time a prospective transcriptional risk signature in blood pre-dicting development of leprosy 4 to 61 months before clinical diagnosis. Assessment of this signature in con-tacts of leprosy patients can function as an adjunct diagnostic tool to target implementation of interventions to restrain leprosy development. (C) 2021 The Author(s). Published by Elsevier B.V. Show less
Background The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be... Show moreBackground The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D. Methods Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts. Results We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling. Conclusions Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D. Show less
Differentiation of mammalian pluripotent cells involves large-scale changes in transcription and, among the molecules that orchestrate these changes, chromatin remodellers are essential to initiate... Show moreDifferentiation of mammalian pluripotent cells involves large-scale changes in transcription and, among the molecules that orchestrate these changes, chromatin remodellers are essential to initiate, establish and maintain a new gene regulatory network. The Nucleosome Remodelling and Deacetylation (NuRD) complex is a highly conserved chromatin remodeller which fine-tunes gene expression in embryonic stem cells. While the function of NuRD in mouse pluripotent cells has been well defined, no study yet has defined NuRD function in human pluripotent cells. Here we find that while NuRD activity is required for lineage commitment from primed pluripotency in both human and mouse cells, the nature of this requirement is surprisingly different. While mouse embryonic stem cells (mESC) and epiblast stem cells (mEpiSC) require NuRD to maintain an appropriate differentiation trajectory as judged by gene expression profiling, human induced pluripotent stem cells (hiPSC) lacking NuRD fail to even initiate these trajectories. Further, while NuRD activity is dispensable for self-renewal of mESCs and mEpiSCs, hiPSCs require NuRD to maintain a stable self-renewing state. These studies reveal that failure to properly fine-tune gene expression and/or to reduce transcriptional noise through the action of a highly conserved chromatin remodeller can have different consequences in human and mouse pluripotent stem cells. Show less
Mills, J.D.; Vliet, E.A. van; Chen, B.J.; Janitz, M.; Anink, J.J.; Baayen, J.C.; ... ; Devinsky, O. 2020
Our understanding of mesial temporal lobe epilepsy (MTLE), one of the most common form of drug-resistant epilepsy in humans, is derived mainly from clinical, imaging, and physiological data from... Show moreOur understanding of mesial temporal lobe epilepsy (MTLE), one of the most common form of drug-resistant epilepsy in humans, is derived mainly from clinical, imaging, and physiological data from humans and animal models. High-throughput gene expression studies of human MTLE have the potential to uncover molecular changes underlying disease pathogenesis along with novel therapeutic targets. Using RNA- and small RNA-sequencing in parrallel, we explored differentially expressed genes in the hippocampus and cortex of MTLE patients who had undergone surgical resection and non-epileptic controls. We identified differentially expressed genes in the hippocampus of MTLE patients and differentially expressed small RNAs across both the cortex and hippocampus. We found significant enrichment for astrocytic and microglial genes among up-regulated genes, and down regulation of neuron specific genes in the hippocampus of MTLE patients. The transcriptome profile of the small RNAs reflected disease state more robustly than mRNAs, even across brain regions which show very little pathology. While mRNAs segregated predominately by brain region for MTLE and controls, small RNAs segregated by disease state. In particular, our data suggest that specific miRNAs (e.g., let-7b-3p and let-7c-3p) may be key regulators of multiple pathways related to MTLE pathology. Further, we report a strong association of other small RNA species with MTLE pathology. As such we have uncovered novel elements that may contribute to the establishment and progression of MTLE pathogenesis and that could be leveraged as therapeutic targets. Show less
Aims/hypothesisAnimal studies have indicated that disturbed diurnal rhythms of clock gene expression in adipose tissue can induce obesity and type 2 diabetes. The importance of the circadian timing... Show moreAims/hypothesisAnimal studies have indicated that disturbed diurnal rhythms of clock gene expression in adipose tissue can induce obesity and type 2 diabetes. The importance of the circadian timing system for energy metabolism is well established, but little is known about the diurnal regulation of (clock) gene expression in obese individuals with type 2 diabetes. In this study we aimed to identify key disturbances in the diurnal rhythms of the white adipose tissue transcriptome in obese individuals with type 2 diabetes.MethodsIn a case-control design, we included six obese individuals with type 2 diabetes and six healthy, lean control individuals. All participants were provided with three identical meals per day for 3days at zeitgeber time (ZT, with ZT 0:00 representing the time of lights on) 0:30, 6:00 and 11:30. Four sequential subcutaneous abdominal adipose tissue samples were obtained, on day 2 at ZT 15:30, and on day 3 at ZT 0:15, ZT 5:45 and ZT 11:15. Gene expression was measured using RNA sequencing.ResultsThe core clock genes showed reduced amplitude oscillations in the individuals with type 2 diabetes compared with the healthy control individuals. Moreover, in individuals with type 2 diabetes, only 1.8% (303 genes) of 16,818 expressed genes showed significant diurnal rhythmicity, compared with 8.4% (1421 genes) in healthy control individuals. Enrichment analysis revealed a loss of rhythm in individuals with type 2 diabetes of canonical metabolic pathways involved in the regulation of lipolysis. Enrichment analysis of genes with an altered mesor in individuals with type 2 diabetes showed decreased activity of the translation initiating pathway EIF2 signaling'. Individuals with type 2 diabetes showed a reduced diurnal rhythm in postprandial glucose concentrations.Conclusions/interpretationDiurnal clock and metabolic gene expression rhythms are decreased in subcutaneous adipose tissue of obese individuals with type 2 diabetes compared with lean control participants. Future investigation is needed to explore potential treatment targets as identified by our study, including clock enhancement and induction of EIF2 signalling.Data availabilityThe raw sequencing data and supplementary files for rhythmic expression analysis and Ingenuity Pathway Analysis have been deposited in NCBI Gene Expression Omnibus (GEO series accession number GSE104674). Show less
