Weighted gene co-expression network analysis to explain the relationship between plasma total carotenoids and lipid profile

A discriminant analysis of plasma metabolomics for the assessment of metabolic responsiveness to red raspberry consumption

Background

Many studies show that the intake of raspberries is beneficial to immune-metabolic health, but the responses of individuals are heterogeneous and not fully understood.

Methods

In a two-arm parallel-group, randomized, controlled trial, immune-metabolic outcomes and plasma metabolite levels were analyzed before and after an 8-week red raspberry consumption. Based on partial least squares discriminant analysis (PLS-DA) on plasma xenobiotic levels, adherence to the intervention was first evaluated. A second PLS-DA followed by hierarchical clustering was used to classify individuals into response subgroups. Clinical immune and metabolic outcomes, including insulin resistance (HOMA-IR) and sensitivity (Matsuda, QUICKI) indices, during the intervention were assessed and compared between response subgroups.

Results

Two subgroups of participants, type 1 responders (n = 17) and type 2 responders (n = 5), were identified based on plasma metabolite levels measured during the intervention. Type 1 responders showed neutral to negative effects on immune-metabolic clinical parameters after raspberry consumption, and type 2 responders showed positive effects on the same parameters. Changes in waist circumference, waist-to-hip ratio, fasting plasma apolipoprotein B, C-reactive protein and insulin levels as well as Matsuda, HOMA-IR and QUICKI were significantly different between the two response subgroups. A deleterious effect of two carotenoid metabolites was also observed in type 1 responders but these variables were significantly associated with beneficial changes in the QUICKI index and in fasting insulin levels in type 2 responders. Increased 3-ureidopropionate levels were associated with a decrease in the Matsuda index in type 2 responders, suggesting that this metabolite is associated with a decrease in insulin sensitivity for those subjects, whereas the opposite was observed for type 1 responders.

Conclusion

The beneficial effects associated with red raspberry consumption are subject to inter-individual variability. Metabolomics-based clustering appears to be an effective way to assess adherence to a nutritional intervention and to classify individuals according to their immune-metabolic responsiveness to the intervention. This approach may be replicated in future studies to provide a better understanding of how interindividual variability impacts the effects of nutritional interventions on immune-metabolic health.

Hub microRNAs and genes in the development of atrial fibrillation identified by weighted gene co-expression network analysis

Co-expression network may contribute to better understanding molecular interaction patterns underlying cellular processes. To explore microRNAs (miRNAs) expression patterns correlated with AF, we performed weighted gene co-expression network analysis (WGCNA) based on the dataset GSE28954. Thereafter, we predicted target genes using experimentally verified databases (ENOCRI, miRTarBase, and Tarbase), and overlapped genes with differentially expressed genes (DEGs) from GSE79768 were identified as key genes. Integrated analysis of association between hub miRNAs and key genes was conducted to screen hub genes. In general, we identified 3 differentially expressed miRNAs (DEMs) and 320 DEGs, predominantly enriched in inflammation-related functional items. Two significant modules (red and blue) and hub miRNAs (hsa-miR-146b-5p and hsa-miR-378a-5p), which highly correlated with AF-related phenotype, were detected by WGCNA. By overlapping the DEGs and predicted target genes, 38 genes were screened out. Finally, 9 genes (i.e. ATP13A3, BMP2, CXCL1, GABPA, LIF, MAP3K8, NPY1R, S100A12, SLC16A2) located at the core region in the miRNA-gene interaction network were identified as hub genes. In conclusion, our study identified 2 hub miRNAs and 9 hub genes, which may improve the understanding of molecular mechanisms and help to reveal potential therapeutic targets against AF.

Systems-level network modeling deciphers the master regulators of phenotypic plasticity and heterogeneity in melanoma

Phenotypic (i.e. non-genetic) heterogeneity in melanoma drives dedifferentiation, recalcitrance to targeted therapy and immunotherapy, and consequent tumor relapse and metastasis. Various markers or regulators associated with distinct phenotypes in melanoma have been identified, but, how does a network of interactions among these regulators give rise to multiple "attractor" states and phenotypic switching remains elusive. Here, we inferred a network of transcription factors (TFs) that act as master regulators for gene signatures of diverse cell-states in melanoma. Dynamical simulations of this network predicted how this network can settle into different "attractors" (TF expression patterns), suggesting that TF network dynamics drives the emergence of phenotypic heterogeneity. These simulations can recapitulate major phenotypes observed in melanoma and explain de-differentiation trajectory observed upon BRAF inhibition. Our systems-level modeling framework offers a platform to understand trajectories of phenotypic transitions in the landscape of a regulatory TF network and identify novel therapeutic strategies targeting melanoma plasticity.

Using systems biology approaches to identify signalling pathways activated during chronic wound initiation

Chronic wounds are a significant health problem worldwide. However, nothing is known about how chronic wounds initiate and develop. Here we use a chronic wound model in diabetic mice and a Systems Biology Approach using nanoString nCounter technology and weighted gene correlation network analysis (WGCNA), with tissues collected at 6, 12, 24 and 48 h post-wounding, to identify metabolic signalling pathways involved in initiation of chronicity. Normalized counts obtained from the nanoString nCounter Mouse Metabolic Panel were used for the WGCNA, which groups genes into co-expression modules to visualize the correlation network. Genes with significant module membership and gene trait significance (p < 0.05) were used to identify signalling pathways that are important for the development of chronicity. The pathway analysis using the Reactome database showed stabilization of PTEN, which down-regulates PI3K/AKT1, which in turn down-regulates Nrf2, as shown by ELISA, thus disabling antioxidant production, resulting in high oxidative stress levels. We find that pathways involved in inflammation, including those that generate pro-inflammatory lipids derived from arachidonic acid metabolism, IFNγ and catecholamines, occur. Moreover, HIF3α is over-expressed, potentially blocking Hif1α and preventing activation of growth factors and cytokines that promote granulation tissue formation. We also find that FGF1 is under-expressed, while thrombospondin-1 is over-expressed, resulting in decreased angiogenesis, a process that is critical for healing. Finally, enzymes involved in glycolysis are down-regulated, resulting in decreased production of pyruvate, a molecule critical for ATP production, leading to extensive cell death and wound paralysis. These findings offer new avenues of study that may lead to the development of novel treatments of CW to be administered right after debridement.

Target identification of hepatic fibrosis using Pien Tze Huang based on mRNA and lncRNA

Hepatic fibrosis is a spontaneous wound-healing response triggered by chronic liver injury. Pien Tze Huang (PZH), a traditional Chinese herbal medicine, has been widely used to treat various hepatic diseases in Asia. We used a CCl4-induced mouse model to establish a PZH group of hepatic fibrosis mice treated with PZH and a control group of hepatic fibrosis mice without any treatment. We performed RNA-seq and mass spectrometry sequencing to investigate the mechanism of the PZH response in hepatic fibrosis and identified multiple differentially expressed transcripts (DETs) and proteins (DEPs) that may be drug targets of PZH. Liver functional indices, including serum albumin (ALB), alanine aminotransferase (ALT) and aspartate aminotransferase (AST), were significantly decreased in the PZH treatment group (P < 0.05) in the eighth week. Hematoxylin-eosin (HE), Masson and Sirius red staining demonstrated that PZH significantly inhibited infiltration of inflammatory cells and collagen deposition. A total of 928 transcripts and 138 proteins were differentially expressed in PZH-treated mice compared to the control group. Gene Ontology (GO) enrichment analysis suggested that PZH may alleviate liver injury and fibrosis by enhancing the immune process. Taken together, our results revealed that multiple DETs and DEPs may serve as drug targets of PZH in hepatic fibrosis patient in future clinical practice.

Antioxidant Effect of Wheat Germ Extracts and Their Antilipidemic Effect in Palmitic Acid-Induced Steatosis in HepG2 and 3T3-L1 Cells

Wheat germ (WG) is a by-product of wheat milling and comprises many bioactive compounds. This study aimed to compare the antioxidant and antilipidemic effects of different WG extracts (WGEs) by analyzing candidate bioactive compounds such as carotenoids, tocopherols, γ-oryzanol, and biogenic amines by reversed-phase high-performance liquid chromatography. Antioxidant activity was determined using the ABTS, DPPH, and FRAP assays. The antilipidemic effect was evaluated in palmitic acid-induced steatosis in HepG2 hepatocytes and 3T3-L1 adipocytes. Cellular lipid accumulation was assessed by Oil Red O staining and a cellular triglyceride content assay. All analyzed WGEs showed significant antioxidant potential, although some bioactive compounds, such as carotenoids, tocopherols, and γ-oryzanol, were the highest in the ethanol extract. Correlation analysis revealed the antioxidant potential of all identified biogenic amines except for spermidine. Ethanol and n-hexane extracts significantly inhibited cellular lipid accumulation in cell models. These results suggest that WGEs exhibit promising antioxidant potential, with a variety of bioactive compounds. Collectively, the findings of this study suggest that bioactive compounds in WGEs attenuate plasma lipid and oxidation levels. In conclusion, WG can be used as a natural antioxidant and nutraceutical using appropriate solvents and extraction methods.

Integrative Network Analysis of Multi-Omics Data in the Link between Plasma Carotenoid Concentrations and Lipid Profile

INTRODUCTION

Carotenoids, which are a reliable biomarker of fruit and vegetable consumption, are positively associated with the lipid profile. Circulating carotenoid concentrations may interact with several omics profiles including genome, transcriptome, and epigenome. Few studies have used multi-omics approaches, and they rarely include environmental factors, such as diet.

OBJECTIVE

The objective of this observational study was to examine the potential role of multi-omics data in the interconnection between diet, represented by total carotenoids, and lipid profile using weighted gene correlation network analysis (WGCNA).

METHODS

Blood leukocyte DNA methylation levels of 472,245 CpG sites and whole blood gene expression levels of 18,160 transcripts were tested for associations with total carotenoid concentrations using regressions in 48 healthy subjects. WGCNA was used to identify co-omics modules and hub genes related to the lipid profile.

RESULTS

Among genes associated with total carotenoid concentrations, a total of 236 genes were identified at both DNA methylation and gene expression levels. Using WGCNA, six modules, consisting of groups of highly correlated genes represented by colors, were identified and linked to the lipid profile. Probes clustered in the turquoise and green modules correlated with plasma lipid concentrations. A total of 28 hub genes were identified.

CONCLUSIONS

Genome-wide DNA methylation and gene expression levels were both associated with plasma total carotenoid concentrations. Several hub genes, mostly involved in lipid metabolism and inflammatory response with several genetic variants associated with plasma lipid concentrations, came out of the integrative analysis. This provides a comprehensive understanding of the interactive molecular system between carotenoids, omics, and plasma lipid profile.

Network Analysis of the Potential Role of DNA Methylation in the Relationship between Plasma Carotenoids and Lipid Profile

Variability in plasma carotenoids may be attributable to several factors including genetic variants and lipid profile. Until now, the impact of DNA methylation on this variability has not been widely studied. Weighted gene correlation network analysis (WGCNA) is a systems biology method used for finding gene clusters (modules) with highly correlated methylation levels and for relating them to phenotypic traits. The objective of the present study was to examine the role of DNA methylation in the relationship between plasma total carotenoid concentrations and lipid profile using WGCNA in 48 healthy subjects. Genome-wide DNA methylation levels of 20,687 out of 472,245 CpG sites in blood leukocytes were associated with total carotenoid concentrations. Using WGCNA, nine co-methylation modules were identified. A total of 2734 hub genes (17 unique top hub genes) were potentially related to lipid profile. This study provides evidence for the potential implications of gene co-methylation in the relationship between plasma carotenoids and lipid profile. Further studies and validation of the hub genes are needed.