Identification of key genes and their association with immune infiltration in adipose tissue of obese patients: a bioinformatic analysis

Genetic Commonalities Between Metabolic Syndrome and Rheumatic Diseases Through Disease Interactome Modules

This study aims to elucidate the potential genetic commonalities between metabolic syndrome (MetS) and rheumatic diseases through a disease interactome network, according to publicly available large-scale genome-wide association studies (GWAS). The analysis included linkage disequilibrium score regression analysis, cross trait meta-analysis and colocalisation analysis to identify common genetic overlap. Using modular partitioning, the network-based association between the two disease proteins in the protein-protein interaction set was divided and quantified. Clinical samples from public databases were used to confirm the mapped genes. Mendelian randomisation analyses were conducted using genetic instrumental variables for causal inference. MetS and rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), Sjogren's syndrome (SS) and their primary module networks shared topological overlap and genetic correlation. Functional analysis highlighted the significance of these shared targets in processes such as a diverse array of metabolic pathways involving glucose, lipids, energy, protein transport, inflammatory response, autophagy and cytokine regulation, elucidating the pathways through which MetS intersects with rheumatic diseases. Causal associations were determined between MetS phenotypes and rheumatic diseases. The persistence of MetS effects on rheumatic diseases remained evident even after adjusting for alcohol consumption and smoking. We have highlighted specific genetic associations between MetS and rheumatic diseases. Several genes (e.g., PRRC2A, PSMB8, BAG6, GPSM3, PBX2, etc.) have been identified with molecular commonalities in MetS and RA, AS, SLE and SS, which may serve as potential targets for shared treatments.

Maternal immune cell gene expression associates with maternal gut microbiome, milk composition and infant gut microbiome

BACKGROUND

Pre-pregnancy overweight and obesity promote deleterious health impacts on both mothers during pregnancy and the offspring. Significant changes in the maternal peripheral blood mononuclear cells (PBMCs) gene expression due to obesity are well-known. However, the impact of pre-pregnancy overweight on immune cell gene expression during pregnancy and its association with maternal and infant outcomes is not well explored.

METHODS

Blood samples were collected from healthy normal weight (NW, pre-pregnancy BMI 18.5-24.9) or overweight (OW, pre-pregnancy BMI 25-29.9) 2nd parity pregnant women at 12, 24 and 36 weeks of pregnancy. PBMCs were isolated from the blood and subjected to mRNA sequencing. Maternal and infant microbiota were analyzed by 16S rRNA gene sequencing. Integrative multi-omics data analysis was performed to evaluate the association of gene expression with maternal diet, gut microbiota, milk composition, and infant gut microbiota.

RESULTS

Gene expression analysis revealed that 453 genes were differentially expressed in the OW women compared to NW women at 12 weeks of pregnancy, out of which 354 were upregulated and 99 were downregulated. Several up-regulated genes in the OW group were enriched in inflammatory, chemokine-mediated signaling and regulation of interleukin-8 production-related pathways. At 36 weeks of pregnancy healthy eating index score was positively associated with several genes that include, DTD1, ELOC, GALNT8, ITGA6-AS1, KRT17P2, NPW, POT1-AS1 and RPL26. In addition, at 36 weeks of pregnancy, genes involved in adipocyte functions, such as NG2 and SMTNL1, were negatively correlated to human milk 2'FL and total fucosylated oligosaccharides content collected at 1 month postnatally. Furthermore, infant Akkermansia was positively associated with maternal PBMC anti-inflammatory genes that include CPS1 and RAB7B, at 12 and 36 weeks of pregnancy.

CONCLUSIONS

These findings suggest that prepregnancy overweight impacts the immune cell gene expression profile, particularly at 12 weeks of pregnancy. Furthermore, deciphering the complex association of PBMC's gene expression levels with maternal gut microbiome and milk composition and infant gut microbiome may aid in developing strategies to mitigate obesity-mediated effects.

The causal associations of inflammatory cytokines with obesity and systemic lupus erythematosus: A Mendelian randomization study

OBJECTIVE

Previous studies have partly discussed the roles of inflammatory cytokines in obesity and systemic lupus erythematosus (SLE), but the causal relationship among inflammatory cytokines, obesity, and SLE is unclear. It is challenging to comprehensively evaluate the causal relationship between these variables. This study aimed to investigate the role of cytokines as intermediates between obesity and SLE.

METHODS

The inverse-variance weighted method (IVW) of mendelian randomization (MR) is mainly used to explore the causal relationship between exposure and outcome by using the genetic variation of the open large genome-wide association studies (GWAS), namely single-nucleotide polymorphisms (SNPs) related to obesity (more than 600 000 participants), inflammatory cytokines (8293 healthy participants) and SLE (7219 cases). Methods such as weighted median, MR-Egger are used to evaluate the reliability of causality. Reverse analysis is performed for each MR analysis to avoid reverse causality. Cochran's Q statistic and funnel chart are used to detect heterogeneity, MR-Egger intercept test and leave-one-out sensitivity analyses evaluated pleiotropy.

RESULTS

Obesity was associated with 25 cytokines, and 3 cytokines were associated with SLE, including CTACK (OR = 1.19, 95% CI: 1.06, 1.33, p = .002), IL-18 (OR = 1.13, 95% CI: 1.01, 1.26, p = .027), SCGFb (OR = 0.89, 95% CI: 0.79, 0.99, p = .044). In the opposite direction, SLE was associated with 18 cytokines, and 2 cytokines were associated with obesity, including IP-10 (βIVW = -.03, 95% CI: -0.05, -0.01, p = .002), MIP-1B (βIVW = -.03, 95% CI: -0.05, -0.01, p = .004).

CONCLUSION

Our MR study suggested that CTACK, IL-18 and SCGFb may play an intermediary role in obesity to SLE, while IP-10 and MIP-1B may play an intermediary role in SLE to obesity.

Adipose-specific overexpression of human AGPAT2 in mice causes increased adiposity and mild hepatic dysfunction

AGPAT2, a critical enzyme involved in the biosynthesis of phospholipids and triacylglycerol (TAG), is highly expressed in adipose tissue (AT). Whether overexpression of AGPAT2 in AT will result in increased TAG synthesis (obesity) and its metabolic complications remains unknown. We overexpressed human AGPAT2 specifically in AT using the adiponectin promoter and report increased mass of subcutaneous, gonadal, and brown AT in wild-type mice. Unexpectedly, overexpression of hAGPAT2 did not change the pattern of phospholipid or TAG concentration of the AT depots. Although there is an increase in liver weight, plasma aspartate aminotransferase, and plasma insulin at various time points of the study, it did not result in significant liver dysfunction. Despite increased adiposity in the Tg-AT-hAGPAT2;mAgpat2+/+ mice, there was no significant increase in TAG concentration of AT. Therefore, this study suggests a role of AGPAT2 in the generation of AT, but not for adipocyte TAG synthesis.

Pharmacoinformatic screening of phytoconstituent and evaluation of its anti-PDAC effect using in vitro studies

With no prominent treatment for pancreatic ductal adenocarcinoma (PDAC) in conventional chemotherapy, recent studies have focused on uniting conventional and traditional medicines including plant phytoconstituents. Herein, we used pharmacoinformatic studies to identify potent phytoconstituent as ligand having inhibition activities against canonical anticancer targets, and evaluated its effect on PDAC cell lines. SwissTargetPrediction and SuperPred tools were utilized to segregate protein targets of ligand in humans, following which FunRich was applied to garner its targets in PDAC. STRING analysis predicted protein-protein interactions and dynamic simulation studies confirmed stability of ligand-protein complex. For in vitro cytotoxic potential, ligand treatment at different concentrations was given to PDAC cell lines both alone and combined with gemcitabine, followed by evaluation of effects on migration. Differential gene expression was checked using PCR for evaluating mechanism of cytotoxicity. Results showed pentagalloylglucose (PGG) with highest docking and MMGBSA scores for Cyclooxygenase 2 (Cox2) inhibition site. SwissTargetPrediction and SuperPred analysis detected 40 targets of PGG in PDAC. Simulation data showed stability of protein-ligand complex. In in vitro experiments Mia-PaCa-2 was more sensitive to PGG than Panc-1. PGG successfully inhibited migration both alone and in combination with gemcitabine. Additionally, PGG treatment induced apoptosis in both the cell lines; but showed antagonism when combined with gemcitabine. In conclusion, our report demonstrates PGG has good binding with Cox2 and showed anti-PDAC activity by inhibiting migration and inducing apoptosis, thus it can be used as a therapy option. But further studies are required to confirm its behaviour as a combination therapy drug.Communicated by Ramaswamy H. Sarma.

Regulated adipose tissue-specific expression of human AGPAT2 in lipodystrophic Agpat2-null mice results in regeneration of adipose tissue

Genetic loss of Agpat2 in humans and mice results in congenital generalized lipodystrophy with near-total loss of adipose tissue and predisposition to develop insulin resistance, diabetes mellitus, hepatic steatosis, and hypertriglyceridemia. The mechanism by which Agpat2 deficiency results in loss of adipose tissue remains unknown. We studied this by re-expressing human AGPAT2 (hAGPAT2) in Agpat2-null mice, regulated by doxycycline. In both sexes of Agpat2-null mice, adipose-tissue-specific re-expression of hAGPAT2 resulted in partial regeneration of both white and brown adipose tissue (but only 30%-50% compared with wild-type mice), which had molecular signatures of adipocytes, including leptin secretion. Furthermore, the stromal vascular fraction cells of regenerated adipose depots differentiated ex vivo only with doxycycline, suggesting the essential role of Agpat2 in adipocyte differentiation. Turning off expression of hAGPAT2 in vivo resulted in total loss of regenerated adipose tissue, clear evidence that Agpat2 is essential for adipocyte differentiation in vivo.

A narrative review: CXC chemokines influence immune surveillance in obesity and obesity-related diseases: Type 2 diabetes and nonalcoholic fatty liver disease

Adipose tissue develops lipids, aberrant adipokines, chemokines, and pro-inflammatory cytokines as a consequence of the low-grade systemic inflammation that characterizes obesity. This low-grade systemic inflammation can lead to insulin resistance (IR) and metabolic complications, such as type 2 diabetes (T2D) and nonalcoholic fatty liver disease (NAFLD). Although the CXC chemokines consists of numerous regulators of inflammation, cellular function, and cellular migration, it is still unknown that how CXC chemokines and chemokine receptors contribute to the development of metabolic diseases (such as T2D and NAFLD) during obesity. In light of recent research, the objective of this review is to provide an update on the linkage between the CXC chemokine, obesity, and obesity-related metabolic diseases (T2D and NAFLD). We explore the differential migratory and immunomodulatory potential of CXC chemokines and their mechanisms of action to better understand their role in clinical and laboratory contexts. Besides that, because CXC chemokine profiling is strongly linked to leukocyte recruitment, macrophage recruitment, and immunomodulatory potential, we hypothesize that it could be used to predict the therapeutic potential for obesity and obesity-related diseases (T2D and NAFLD).

Identification of Comorbidities, Genomic Associations, and Molecular Mechanisms for COVID-19 Using Bioinformatics Approaches

Several studies have been done to identify comorbidities of COVID-19. In this work, we developed an analytical bioinformatics framework to reveal COVID-19 comorbidities, their genomic associations, and molecular mechanisms accomplishing transcriptomic analyses of the RNA-seq datasets provided by the Gene Expression Omnibus (GEO) database, where normal and infected tissues were evaluated. Using the framework, we identified 27 COVID-19 correlated diseases out of 7,092 collected diseases. Analyzing clinical and epidemiological research, we noticed that our identified 27 diseases are associated with COVID-19, where hypertension, diabetes, obesity, and lung cancer are observed several times in COVID-19 patients. Therefore, we selected the above four diseases and performed assorted analyses to demonstrate the association between COVID-19 and hypertension, diabetes, obesity, and lung cancer as comorbidities. We investigated genomic associations with the cross-comparative analysis and Jaccard's similarity index, identifying shared differentially expressed genes (DEGs) and linking DEGs of COVID-19 and the comorbidities, in which we identified hypertension as the most associated illness. We also revealed molecular mechanisms by identifying statistically significant ten pathways and ten ontologies. Moreover, to understand cellular physiology, we did protein-protein interaction (PPI) analyses among the comorbidities and COVID-19. We also used the degree centrality method and identified ten biomarker hub proteins (IL1B, CXCL8, FN1, MMP9, CXCL10, IL1A, IRF7, VWF, CXCL9, and ISG15) that associate COVID-19 with the comorbidities. Finally, we validated our findings by searching the published literature. Thus, our analytical approach elicited interconnections between COVID-19 and the aforementioned comorbidities in terms of remarkable DEGs, pathways, ontologies, PPI, and biomarker hub proteins.