Transcriptome profiling of white adipose tissue in a mouse model for 15q duplication syndrome

Integrative analysis of multi-omics data to detect the underlying molecular mechanisms for obesity in vivo in humans

BACKGROUND

Obesity is a complex, multifactorial condition in which genetic play an important role. Most of the systematic studies currently focuses on individual omics aspect and provide insightful yet limited knowledge about the comprehensive and complex crosstalk between various omics levels.

SUBJECTS AND METHODS

Therefore, we performed a most comprehensive trans-omics study with various omics data from 104 subjects, to identify interactions/networks and particularly causal regulatory relationships within and especially those between omic molecules with the purpose to discover molecular genetic mechanisms underlying obesity etiology in vivo in humans.

RESULTS

By applying differentially analysis, we identified 8 differentially expressed hub genes (DEHGs), 14 differentially methylated regions (DMRs) and 12 differentially accumulated metabolites (DAMs) for obesity individually. By integrating those multi-omics biomarkers using Mendelian Randomization (MR) and network MR analyses, we identified 18 causal pathways with mediation effect. For the 20 biomarkers involved in those 18 pairs, 17 biomarkers were implicated in the pathophysiology of obesity or related diseases.

CONCLUSIONS

The integration of trans-omics and MR analyses may provide us a holistic understanding of the underlying functional mechanisms, molecular regulatory information flow and the interactive molecular systems among different omic molecules for obesity risk and other complex diseases/traits.

Loss of apoptosis repressor with caspase recruitment domain (ARC) worsens high fat diet-induced hyperglycemia in mice

Apoptosis repressor with caspase recruitment domain (ARC) is an endogenous inhibitor of cell death signaling that is expressed in insulin-producing β cells. ARC has been shown to reduce β-cell death in response to diabetogenic stimuli in vitro, but its role in maintaining glucose homeostasis in vivo has not been fully established. Here we examined whether loss of ARC in FVB background mice exacerbates high fat diet (HFD)-induced hyperglycemia in vivo over 24 weeks. Prior to commencing 24-week HFD, ARC-/- mice had lower body weight than wild type (WT) mice. This body weight difference was maintained until the end of the study and was associated with decreased epididymal and inguinal adipose tissue mass in ARC-/- mice. Non-fasting plasma glucose was not different between ARC-/- and WT mice prior to HFD feeding, and ARC-/- mice displayed a greater increase in plasma glucose over the first 4 weeks of HFD. Plasma glucose remained elevated in ARC-/- mice after 16 weeks of HFD feeding, at which time it had returned to baseline in WT mice. Following 24 weeks of HFD, non-fasting plasma glucose in ARC-/- mice returned to baseline and was not different from WT mice. At this final time point, no differences were observed between genotypes in plasma glucose or insulin under fasted conditions or following intravenous glucose administration. However, HFD-fed ARC-/- mice exhibited significantly decreased β-cell area compared to WT mice. Thus, ARC deficiency delays, but does not prevent, metabolic adaptation to HFD feeding in mice, worsening transient HFD-induced hyperglycemia.

UBE3A regulates the transcription of IRF, an antiviral immunity

UBE3A is a gene responsible for the pathogenesis of Angelman syndrome (AS), a neurodevelopmental disorder characterized by symptoms such as intellectual disability, delayed development and severe speech impairment. UBE3A encodes an E3 ubiquitin ligase, for which several targets have been identified, including synaptic molecules. Although proteolysis mainly occurs in the cytoplasm, UBE3A is localized to the cytoplasm and the nucleus. In fact, UBE3A is also known as a transcriptional regulator of the family of nuclear receptors. However, the function of UBE3A in the nucleus remains unclear. Therefore, we examined the involvement of UBE3A in transcription in the nuclei of neurons. Genome-wide transcriptome analysis revealed an enrichment of genes downstream of interferon regulatory factor (IRF) in a UBE3A-deficient AS mouse model. In vitro biochemical analyses further demonstrated that UBE3A interacted with IRF and, more importantly, that UBE3A enhanced IRF-dependent transcription. These results suggest a function for UBE3A as a transcriptional regulator of the immune system in the brain. These findings also provide informative molecular insights into the function of UBE3A in the brain and in AS pathogenesis.

Dysregulation of Alternative Poly-adenylation as a Potential Player in Autism Spectrum Disorder

We present here the hypothesis that alternative poly-adenylation (APA) is dysregulated in the brains of individuals affected by Autism Spectrum Disorder (ASD), due to disruptions in the calcium signaling networks. APA, the process of selecting different poly-adenylation sites on the same gene, yielding transcripts with different-length 3′ untranslated regions (UTRs), has been documented in different tissues, stages of development and pathologic conditions. Differential use of poly-adenylation sites has been shown to regulate the function, stability, localization and translation efficiency of target RNAs. However, the role of APA remains rather unexplored in neurodevelopmental conditions. In the human brain, where transcripts have the longest 3′ UTRs and are thus likely to be under more complex post-transcriptional regulation, erratic APA could be particularly detrimental. In the context of ASD, a condition that affects individuals in markedly different ways and whose symptoms exhibit a spectrum of severity, APA dysregulation could be amplified or dampened depending on the individual and the extent of the effect on specific genes would likely vary with genetic and environmental factors. If this hypothesis is correct, dysregulated APA events might be responsible for certain aspects of the phenotypes associated with ASD. Evidence supporting our hypothesis is derived from standard RNA-seq transcriptomic data but we suggest that future experiments should focus on techniques that probe the actual poly-adenylation site (3′ sequencing). To address issues arising from the use of post-mortem tissue and low numbers of heterogeneous samples affected by confounding factors (such as the age, gender and health of the individuals), carefully controlled in vitro systems will be required to model the effect of calcium signaling dysregulation in the ASD brain.

ARN: analysis and prediction by adipogenic professional database

Adipogenesis is the process of cell differentiation by which mesenchymal stem cells become adipocytes. Extensive research is ongoing to identify genes, their protein products, and microRNAs that correlate with fat cell development. The existing databases have focused on certain types of regulatory factors and interactions. However, there is no relationship between the results of the experimental studies on adipogenesis and these databases because of the lack of an information center. This information fragmentation hampers the identification of key regulatory genes and pathways. Thus, it is necessary to provide an information center that is quickly and easily accessible to researchers in this field. We selected and integrated data from eight external databases based on the results of text-mining, and constructed a publicly available database and web interface (URL: http://210.27.80.93/arn/ ), which contained 30873 records related to adipogenic differentiation. Then, we designed an online analysis tool to analyze the experimental data or form a scientific hypothesis about adipogenesis through Swanson's literature-based discovery process. Furthermore, we calculated the "Impact Factor" ("IF") value that reflects the importance of each node by counting the numbers of relation records, expression records, and prediction records for each node. This platform can support ongoing adipogenesis research and contribute to the discovery of key regulatory genes and pathways.