Exploring the molecular mechanism of comorbidity of autism spectrum disorder and inflammatory bowel disease by combining multiple data sets

The shared circulating diagnostic biomarkers and molecular mechanisms of systemic lupus erythematosus and inflammatory bowel disease

Background

Systemic lupus erythematosus (SLE) is a multi-organ chronic autoimmune disease. Inflammatory bowel disease (IBD) is a common chronic inflammatory disease of the gastrointestinal tract. Previous studies have shown that SLE and IBD share common pathogenic pathways and genetic susceptibility, but the specific pathogenic mechanisms remain unclear.

Methods

The datasets of SLE and IBD were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified using the Limma package. Weighted gene coexpression network analysis (WGCNA) was used to determine co-expression modules related to SLE and IBD. Pathway enrichment was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis for co-driver genes. Using the Least AbsoluteShrinkage and Selection Operator (Lasso) regressionand Support Vector Machine-Recursive Feature Elimination (SVM-RFE), common diagnostic markers for both diseases were further evaluated. Then, we utilizedthe CIBERSORT method to assess the abundance of immune cell infiltration. Finally,we used the single-cell analysis to obtain the location of common diagnostic markers.

Results

71 common driver genes were identified in the SLE and IBD cohorts based on the DEGs and module genes. KEGG and GO enrichment results showed that these genes were closely associated with positive regulation of programmed cell death and inflammatory responses. By using LASSO regression and SVM, five hub genes (KLRF1, GZMK, KLRB1, CD40LG, and IL-7R) were ultimately determined as common diagnostic markers for SLE and IBD. ROC curve analysis also showed good diagnostic performance. The outcomes of immune cell infiltration demonstrated that SLE and IBD shared almost identical immune infiltration patterns. Furthermore, the majority of the hub genes were commonly expressed in NK cells by single-cell analysis.

Conclusion

This study demonstrates that SLE and IBD share common diagnostic markers and pathogenic pathways. In addition, SLE and IBD show similar immune cellinfiltration microenvironments which provides newperspectives for future treatment.

Dietary intake and gastrointestinal symptoms are altered in children with Autism Spectrum Disorder: the relative contribution of autism-linked traits

BACKGROUND

Dietary and gastrointestinal (GI) problems have been frequently reported in autism spectrum disorder (ASD). However, the relative contributions of autism-linked traits to dietary and GI problems in children with ASD are poorly understood. This study firstly compared the dietary intake and GI symptoms between children with ASD and typically developing children (TDC), and then quantified the relative contributions of autism-linked traits to dietary intake, and relative contributions of autism-linked traits and dietary intake to GI symptoms within the ASD group.

METHODS

A sample of 121 children with ASD and 121 age-matched TDC were eligible for this study. The dietary intake indicators included food groups intakes, food variety, and diet quality. The autism-linked traits included ASD symptom severity, restricted repetitive behaviors (RRBs), sensory profiles, mealtime behaviors, and their subtypes. Linear mixed-effects models and mixed-effects logistic regression models were used to estimate the relative contributions.

RESULTS

Children with ASD had poorer diets with fewer vegetables/fruits, less variety of food, a higher degree of inadequate/unbalanced dietary intake, and more severe constipation/total GI symptoms than age-matched TDC. Within the ASD group, compulsive behavior (a subtype of RRBs) and taste/smell sensitivity were the only traits associated with lower vegetables and fruit consumption, respectively. Self-injurious behavior (a subtype of RRBs) was the only contributing trait to less variety of food. Limited variety (a subtype of mealtime behavior problems) and ASD symptom severity were the primary and secondary contributors to inadequate dietary intake, respectively. ASD symptom severity and limited variety were the primary and secondary contributors to unbalanced dietary intake, respectively. Notably, unbalanced dietary intake was a significant independent factor associated with constipation/total GI symptoms, and autism-linked traits manifested no contributions.

CONCLUSIONS

ASD symptom severity and unbalanced diets were the most important contributors to unbalanced dietary intake and GI symptoms, respectively. Our findings highlight that ASD symptom severity and unbalanced diets could provide the largest benefits for the dietary and GI problems of ASD if they were targeted for early detection and optimal treatment.

Identification of cuproptosis-related molecular classification and characteristic genes in ulcerative colitis

Ulcerative colitis (UC) is a refractory inflammatory disease with imbalances in intestinal mucosal homeostasis. Cuproptosis serves as newly identified programmed cell death (PCD) form involved in UC. In the study, UC-related datasets were extracted from the Gene Expression Omnibus (GEO) database. A comparison of UC patients and healthy controls identified 11 differentially expressed cuproptosis-related genes (DE-CRGs), where FDX1, LIAS, and DLAT were differentially expressed in UC groups from the mouse models and clinical samples, with their expression correlating with disease severity. By comprehending weighted gene co-expression network analysis (WGCNA) and differential expression analysis, the key genes common to the module genes relevant to different cuproptosis-related clusters and differentially expressed genes (DEGs) both in different clusters and patients with and without UC were identified using several bioinformatic analysis. Furthermore, the mRNA levels of four characteristic genes with diagnostic potential demonstrated significant decrease in both mouse models and clinical UC samples. Our discoveries offer a theoretical foundation for cuproptosis effect in UC.

Identification of the Shared Gene Signatures of HCK, NOG, RNF125 and Biological Mechanism in Pediatric Acute Lymphoblastic Leukaemia and Pediatric Sepsis

The shared mechanisms between pediatric acute lymphoblastic leukaemia (ALL) and pediatric sepsis are currently unclear. This study was aimed to explore the shared key genes of pediatric ALL and pediatric sepsis. The datasets involved were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between disease and control samples in GSE13904 and GSE79533 were intersected. The least absolute shrinkage and selection operator (LASSO) and the boruta analyses were performed in GSE13904 and GSE79533 separately based on shared DEGs, and shared key genes were obtained by taking the intersection of sepsis-related key genes and ALL-related key genes. Three shared key genes (HCK, NOG, RNF125) were obtained, that have a good diagnostic value for both sepsis and ALL. The correlation between shared key genes and differentially expressed immune cells was higher in GSE13904 and conversely, the correlation of which was lower in GSE79533. Suggesting that the sharing key genes had a different impact on the immune environment in pediatric ALL and pediatric sepsis. We make the case that this study provides a new perspective to study the relationship between pediatric ALL and pediatric sepsis.

Analysis of complement system and its related factors in Alzheimer's disease

Alzheimer's disease (AD) is a primary cause of dementia. The complement system is closely related to AD pathology and may be a potential target for the prevention and treatment of AD. In our study, we conducted a bioinformatics analysis to analyze the role of the complement system and its related factors in AD using Gene Expression Omnibus (GEO) data. We also conducted a functional analysis. Our study verified that 23 genes were closely related to differentially expressed complement system genes in diseases after intersecting the disease-related complement system module genes and differentially expressed genes. The STRING database was used to predict the interactions between the modular gene proteins of the differential complement system. A total of 21 gene proteins and 44 interaction pairs showed close interactions. We screened key genes and created a diagnostic model. The predictive effect of the model was constructed using GSE5281 and our study indicated that the predictive effect of the model was good. Our study also showed enriched negative regulation of Notch signaling, cytokine secretion involved in the immune response pathway, and cytokine secretion involved in immune response hormone-mediated apoptotic signaling pathway. We hope that our study provides a promising target to prevent and delay the onset, diagnosis, and treatment of AD.