Systems view of adipogenesis via novel omics-driven and tissue-specific activity scoring of network functional modules

Predicting mechanisms of action at genetic loci associated with discordant effects on type 2 diabetes and abdominal fat accumulation

Obesity is a major risk factor for cardiovascular disease, stroke, and type 2 diabetes (T2D). Excessive accumulation of fat in the abdomen further increases T2D risk. Abdominal obesity is measured by calculating the ratio of waist-to-hip circumference adjusted for the body-mass index (WHRadjBMI), a trait with a significant genetic inheritance. Genetic loci associated with WHRadjBMI identified in genome-wide association studies are predicted to act through adipose tissues, but many of the exact molecular mechanisms underlying fat distribution and its consequences for T2D risk are poorly understood. Further, mechanisms that uncouple the genetic inheritance of abdominal obesity from T2D risk have not yet been described. Here we utilize multi-omic data to predict mechanisms of action at loci associated with discordant effects on abdominal obesity and T2D risk. We find six genetic signals in five loci associated with protection from T2D but also with increased abdominal obesity. We predict the tissues of action at these discordant loci and the likely effector Genes (eGenes) at three discordant loci, from which we predict significant involvement of adipose biology. We then evaluate the relationship between adipose gene expression of eGenes with adipogenesis, obesity, and diabetic physiological phenotypes. By integrating these analyses with prior literature, we propose models that resolve the discordant associations at two of the five loci. While experimental validation is required to validate predictions, these hypotheses provide potential mechanisms underlying T2D risk stratification within abdominal obesity.

Stages of preadipocyte differentiation: biomarkers and pathways for extracellular structural remodeling

BACKGROUND

This study utilized bioinformatics to analyze the underlying biological mechanisms involved in adipogenic differentiation, synthesis of the extracellular matrix (ECM), and angiogenesis during preadipocyte differentiation in human Simpson-Golabi-Behmel syndrome at different time points and identify targets that can potentially improve fat graft survival.

RESULTS

We analyzed two expression profiles from the Gene Expression Omnibus and identified differentially expressed genes (DEGs) at six different time points after the initiation of preadipocyte differentiation. Related pathways were identified using Gene Ontology/Kyoto Encyclopedia of Genes and Genomes analyses and Gene Set Enrichment Analysis (GSEA). We further constructed a protein-protein interaction (PPI) network and its central genes. The results showed that upregulated DEGs were involved in cell differentiation, lipid metabolism, and other cellular activities, while downregulated DEGs were associated with angiogenesis and development, ECM tissue synthesis, and intercellular and intertissue adhesion. GSEA provided a more comprehensive basis, including participation in and positive regulation of key pathways of cell metabolic differentiation, such as the "peroxisome proliferator-activated receptor signaling pathway" and the "adenylate-activated protein kinase signaling pathway," a key pathway that negatively regulates pro-angiogenic development, ECM synthesis, and adhesion.

CONCLUSIONS

We identified the top 20 hub genes in the PPI network, including genes involved in cell differentiation, ECM synthesis, and angiogenesis development, providing potential targets to improve the long-term survival rate of fat grafts. Additionally, we identified drugs that may interact with these targets to potentially improve fat graft survival.

Transcriptome-wide association study identifies multiple genes associated with childhood body mass index

BACKGROUND

Childhood obesity is one of the most common and costly nutritional problems with high heritability. The genetic mechanism of childhood obesity remains unclear. Here, we conducted a transcriptome-wide association study (TWAS) to identify novel genes for childhood obesity.

METHODS

By integrating the GWAS summary of childhood body mass index (BMI), we conducted TWAS analyses with pre-computed gene expression weights in 39 obesity priority tissues. The GWAS summary statistics of childhood BMI were derived from the early growth genetics consortium with 35,668 children from 20 studies.

RESULTS

We identified 15 candidate genes for childhood BMI after Bonferroni corrections. The most significant gene, ADCY3, was identified in 13 tissues, including adipose, brain, and blood. Interestingly, eight genes were only identified in the specific tissue, such as FAIM2 in the brain (P = 2.04 × 10^-7) and fat mass and obesity-associated gene (FTO) in the muscle (P = 1.93 × 10^-8). Compared with the TWAS results of adult BMI, we found that one gene TUBA1B with predominant influence only on childhood BMI in the muscle (P = 1.12 × 10^-7). We evaluated the candidate genes by querying public databases and identified 12 genes functionally related to obesity phenotypes, including nine differentially expressed genes during the differentiation of human preadipocyte cells. The remaining genes (FAM150B, KNOP1, and LMBR1L) were regarded as novel candidate genes for childhood BMI.

CONCLUSIONS

Our study identified multiple candidate genes for childhood BMI, providing novel clues for understanding the genetic mechanism of childhood obesity.

History and Future Perspectives on the Discipline of Quantitative Systems Pharmacology Modeling and Its Applications

Mathematical biology and pharmacology models have a long and rich history in the fields of medicine and physiology, impacting our understanding of disease mechanisms and the development of novel therapeutics. With an increased focus on the pharmacology application of system models and the advances in data science spanning mechanistic and empirical approaches, there is a significant opportunity and promise to leverage these advancements to enhance the development and application of the systems pharmacology field. In this paper, we will review milestones in the evolution of mathematical biology and pharmacology models, highlight some of the gaps and challenges in developing and applying systems pharmacology models, and provide a vision for an integrated strategy that leverages advances in adjacent fields to overcome these challenges.

DNA methylation during human adipogenesis and the impact of fructose

BACKGROUND

Increased adipogenesis and altered adipocyte function contribute to the development of obesity and associated comorbidities. Fructose modified adipocyte metabolism compared to glucose, but the regulatory mechanisms and consequences for obesity are unknown. Genome-wide methylation and global transcriptomics in SGBS pre-adipocytes exposed to 0, 2.5, 5, and 10 mM fructose, added to a 5-mM glucose-containing medium, were analyzed at 0, 24, 48, 96, 192, and 384 h following the induction of adipogenesis.

RESULTS

Time-dependent changes in DNA methylation compared to baseline (0 h) occurred during the final maturation of adipocytes, between 192 and 384 h. Larger percentages (0.1% at 192 h, 3.2% at 384 h) of differentially methylated regions (DMRs) were found in adipocytes differentiated in the glucose-containing control media compared to adipocytes differentiated in fructose-supplemented media (0.0006% for 10 mM, 0.001% for 5 mM, and 0.005% for 2.5 mM at 384 h). A total of 1437 DMRs were identified in 5237 differentially expressed genes at 384 h post-induction in glucose-containing (5 mM) control media. The majority of them inversely correlated with the gene expression, but 666 regions were positively correlated to the gene expression.

CONCLUSIONS

Our studies demonstrate that DNA methylation regulates or marks the transformation of morphologically differentiating adipocytes (seen at 192 h), to the more mature and metabolically robust adipocytes (as seen at 384 h) in a genome-wide manner. Lower (2.5 mM) concentrations of fructose have the most robust effects on methylation compared to higher concentrations (5 and 10 mM), suggesting that fructose may be playing a signaling/regulatory role at lower concentrations of fructose and as a substrate at higher concentrations.

Regulatory Crosstalk of Doxorubicin, Estradiol and TNFα Combined Treatment in Breast Cancer-derived Cell Lines

We present a new model of ESR1 network regulation based on analysis of Doxorubicin, Estradiol, and TNFα combination treatment in MCF-7. We used Doxorubicin as a therapeutic agent, TNFα as marker and mediator of an inflammatory microenvironment and 17β-Estradiol (E2) as an agonist of Estrogen Receptors, known predisposing factor for hormone-driven breast cancer, whose pharmacological inhibition reduces the risk of breast cancer recurrence. Based on the results of transcriptomics analysis, we found 71 differentially expressed genes that are specific for the combination treatment with Doxorubicin + Estradiol + TNFα in comparison with single or double treatments. The responsiveness to the triple treatment was examined for seven genes by qPCR, of which six were validated, and then extended to four additional cell lines differing for p53 and/or ER status. The results of differential regulation enrichment analysis highlight the role of the ESR1 network that included 36 of 71 specific differentially expressed genes. We propose that the combined activation of p53 and NF-kB transcription factors significantly influences ligand-dependent, ER-driven transcriptional responses, also of the ESR1 gene itself. These results provide a model of coordinated interaction of TFs to explain the Doxorubicin, E2 and TNFα induced repression mechanisms.

The Power of LC-MS Based Multiomics: Exploring Adipogenic Differentiation of Human Mesenchymal Stem/Stromal Cells

The molecular study of fat cell development in the human body is essential for our understanding of obesity and related diseases. Mesenchymal stem/stromal cells (MSC) are the ideal source to study fat formation as they are the progenitors of adipocytes. In this work, we used human MSCs, received from surgery waste, and differentiated them into fat adipocytes. The combination of several layers of information coming from lipidomics, metabolomics and proteomics enabled network analysis of the biochemical pathways in adipogenesis. Simultaneous analysis of metabolites, lipids, and proteins in cell culture is challenging due to the compound’s chemical difference, so most studies involve separate analysis with unimolecular strategies. In this study, we employed a multimolecular approach using a two–phase extraction to monitor the crosstalk between lipid metabolism and protein-based signaling in a single sample (~10⁵ cells). We developed an innovative analytical workflow including standardization with in-house produced ¹³C isotopically labeled compounds, hyphenated high-end mass spectrometry (high-resolution Orbitrap MS), and chromatography (HILIC, RP) for simultaneous untargeted screening and targeted quantification. Metabolite and lipid concentrations ranged over three to four orders of magnitude and were detected down to the low fmol (absolute on column) level. Biological validation and data interpretation of the multiomics workflow was performed based on proteomics network reconstruction, metabolic modelling (MetaboAnalyst 4.0), and pathway analysis (OmicsNet). Comparing MSCs and adipocytes, we observed significant regulation of different metabolites and lipids such as triglycerides, gangliosides, and carnitine with 113 fully reprogrammed pathways. The observed changes are in accordance with literature findings dealing with adipogenic differentiation of MSC. These results are a proof of principle for the power of multimolecular extraction combined with orthogonal LC-MS assays and network construction. Considering the analytical and biological validation performed in this study, we conclude that the proposed multiomics workflow is ideally suited for comprehensive follow-up studies on adipogenesis and is fit for purpose for different applications with a high potential to understand the complex pathophysiology of diseases.

Systematic exploration of cell morphological phenotypes associated with a transcriptomic query

Cell morphological phenotypes, including shape, size, intensity, and texture of cellular compartments have been shown to change in response to perturbation with small molecule compounds. Image-based cell profiling or cell morphological profiling has been used to associate changes of cell morphological features with alterations in cellular function and to infer molecular mechanisms of action. Recently, the Library of Integrated Network-based Cellular Signatures (LINCS) Project has measured gene expression and performed image-based cell profiling on cell lines treated with 9515 unique compounds. These data provide an opportunity to study the interdependence between transcription and cell morphology. Previous methods to investigate cell phenotypes have focused on targeting candidate genes as components of known pathways, RNAi morphological profiling, and cataloging morphological defects; however, these methods do not provide an explicit model to link transcriptomic changes with corresponding alterations in morphology. To address this, we propose a cell morphology enrichment analysis to assess the association between transcriptomic alterations and changes in cell morphology. Additionally, for a new transcriptomic query, our approach can be used to predict associated changes in cellular morphology. We demonstrate the utility of our method by applying it to cell morphological changes in a human bone osteosarcoma cell line.

Exploring the cellular network of metabolic flexibility in the adipose tissue

Background

Metabolic flexibility is the ability of cells to change substrates for energy production based on the nutrient availability and energy requirement. It has been shown that metabolic flexibility is impaired in obesity and chronic diseases such as type 2 diabetes mellitus, cardiovascular diseases, and metabolic syndrome, although, whether it is a cause or an effect of these conditions remains to be elucidated.

Main body

In this paper, we have reviewed the literature on metabolic flexibility and curated pathways and processes resulting in a network resource to investigate the interplay between these processes in the subcutaneous adipose tissue. The adipose tissue has been shown to be responsible, not only for energy storage but also for maintaining energy homeostasis through oxidation of glucose and fatty acids. We highlight the role of pyruvate dehydrogenase complex–pyruvate dehydrogenase kinase (PDC-PDK) interaction as a regulatory switch which is primarily responsible for changing substrates in energy metabolism from glucose to fatty acids and back. Baseline gene expression of the subcutaneous adipose tissue, along with a publicly available obesity data set, are visualised on the cellular network of metabolic flexibility to highlight the genes that are expressed and which are differentially affected in obesity.

Conclusion

We have constructed an abstracted network covering glucose and fatty acid oxidation, as well as the PDC-PDK regulatory switch. In addition, we have shown how the network can be used for data visualisation and as a resource for follow-up studies.

Electronic supplementary material

The online version of this article (10.1186/s12263-018-0609-3) contains supplementary material, which is available to authorized users.

Co-Expression Network Analysis of AMPK and Autophagy Gene Products during Adipocyte Differentiation

Autophagy is involved in the development and differentiation of many cell types. It is essential for the pre-adipocytes to respond to the differentiation stimuli and may contribute to reorganizing the intracellulum to adapt the morphological and metabolic demands. Although AMPK, an energy sensor, has been associated with autophagy in several cellular processes, how it connects to autophagy during the adipocyte differentiation remains to be investigated. Here, we studied the interaction between AMPK and autophagy gene products at the mRNA level during adipocyte differentiation using public-access datasets. We used the weighted-gene co-expression analysis to detect and validate multiple interconnected modules of co-expressed genes in a dataset of MDI-induced 3T3-L1 pre-adipocytes. These modules were found to be highly correlated with the differentiation course of the adipocytes. Several novel interactions between AMPK and autophagy gene products were identified. Together, it is possible that AMPK-autophagy interaction is temporally and locally modulated in response to the differentiation stimuli.

Combined use of protein biomarkers and network analysis unveils deregulated regulatory circuits in Duchenne muscular dystrophy

Although the genetic basis of Duchenne muscular dystrophy has been known for almost thirty years, the cellular and molecular mechanisms characterizing the disease are not completely understood and an efficacious treatment remains to be developed. In this study we analyzed proteomics data obtained with the SomaLogic technology from blood serum of a cohort of patients and matched healthy subjects. We developed a workflow based on biomarker identification and network-based pathway analysis that allowed us to describe different deregulated pathways. In addition to muscle-related functions, we identified other biological processes such as apoptosis, signaling in the immune system and neurotrophin signaling as significantly modulated in patients compared with controls. Moreover, our network-based analysis identified the involvement of FoxO transcription factors as putative regulators of different pathways. On the whole, this study provided a global view of the molecular processes involved in Duchenne muscular dystrophy that are decipherable from serum proteome.

Emerging perspectives on branched-chain amino acid metabolism during adipocyte differentiation

PURPOSE OF REVIEW

Adipogenesis has been extensively studied in the context of carbohydrate and lipid metabolism. However, little information exists on the role of amino acid metabolism during adipocyte differentiation. Here, we review how branched-chain amino acid (BCAA) metabolism is modified during adipogenesis and, due to the limited information in the area, address questions that remain to be answered with further research.

RECENT FINDINGS

BCAAs are rapidly consumed during adipocyte differentiation and are indispensable for this process. Furthermore, we describe how BCAA catabolic enzymes and the metabolic fate of BCAAs are modified during adipogenesis.

SUMMARY

Obesity is a chronic disease characterized by increased adipose tissue due to either an increase in the size (hypertrophy) and/or number of adipocytes (hyperplasia). Hyperplasia is determined by the rate of adipogenesis. Therefore, understanding the mechanism that modulates adipogenesis in the context of amino acid metabolism will help to establish pharmacological and dietary interventions involving the type and amount of dietary protein for the treatment of obesity and its associated comorbidities.Video abstract http://links.lww.com/COCN/A11.

Dysregulated pathways for off-pump coronary artery bypass grafting

Background

The objective of this paper was to identify dysregulated myocardial pathways with off-pump coronary artery bypass grafting (OPCABG) based on pathway interaction network (PIN).

Methodology

To achieve this goal, firstly, gene expression profiles, protein-protein interactions (PPIs) and pathway data were collected. Secondly, we constructed a PIN by integrating these data and Pearson correlation coefficient (PCC) algorithm. Next, for every pathway in the PIN, its activity was counted dependent on the principal component analysis (PCA) method to select the seed pathway. Ultimately, a minimum pathway set (MPS) was extracted from the PIN on the basis of the seed pathway and the area under the receiver operating characteristics curve (AUROC) index, and pathways in the MPS were denoted as dysregulated pathways.

Results

The PIN had 1,189 nodes and 22,756 interactions, of which mitochondrial translation termination was the seed pathway. Starting with mitochondrial translation termination, a MPS (AUROC = 0.983) with 7 nodes and 26 edges was obtained. The 7 pathways were regarded as dysregulated myocardial pathways with OPCABG.

Conclusion

The findings might provide potential biomarkers to diagnose early, serve as the evidence to perform the OPCABG and predict inflammatory response and myocardial reperfusion injury after OPCABG in the future.

Graphical Modeling Meets Systems Pharmacology

A main source of failures in systems projects (including systems pharmacology) is poor communication level and different expectations among the stakeholders. A common and not ambiguous language that is naturally comprehensible by all the involved players is a boost to success. We present bStyle, a modeling tool that adopts a graphical language close enough to cartoons to be a common media to exchange ideas and data and that it is at the same time formal enough to enable modeling, analysis, and dynamic simulations of a system. Data analysis and simulation integrated in the same application are fundamental to understand the mechanisms of actions of drugs: a core aspect of systems pharmacology.