Identification of vital modules and genes associated with heart failure based on weighted gene coexpression network analysis

p200CUX1-regulated BMP8B inhibits the progression of acute myeloid leukemia via the MAPK signaling pathway

The full-length p200CUX1 protein encoded by the homology frame CUT-like protein (CUX1) plays an important role in tumors as a pro-oncogene or oncogene. However, its role and mechanism in acute myeloid leukemia remain unknown. p200CUX1 regulates several pathways, including the MAPK signaling pathway. Our data showed that p200CUX1 is lowly expressed in THP1 and U937 AML cell lines. Lentiviral overexpression of p200CUX1 reduced proliferation and promoted apoptosis and G0/G1 phase blockade, correlating with MAPK pathway suppression. Additionally, p200CUX1 regulated the expression of bone morphogenetic protein 8B (BMP8B), which is overexpressed in AML. Overexpression of p200CUX1 downregulated BMP8B expression and inhibited the MAPK pathway. Furthermore, BMP8B knockdown inhibited AML cell proliferation, enhanced apoptosis and the sensitivity of ATRA-induced cell differentiation, and blocked G0/G1 transition. Our findings demonstrate the pivotal function of the p200CUX1-BMP8B-MAPK axis in maintaining the viability of AML cells. Consequently, targeting p200CUX1 could represent a viable strategy in AML therapy.

Identification of diagnostic model in heart failure with myocardial fibrosis and conduction block by integrated gene co-expression network analysis

BACKGROUND

Despite the advancements in heart failure(HF) research, the early diagnosis of HF continues to be a challenging issue in clinical practice. This study aims to investigate the genes related to myocardial fibrosis and conduction block, with the goal of developing a diagnostic model for early treatment of HF in patients.

METHOD

The gene expression profiles of GSE57345, GSE16499, and GSE9128 were obtained from the Gene Expression Omnibus (GEO) database. After merging the expression profile data and adjusting for batch effects, differentially expressed genes (DEGs) associated with conduction block and myocardial fibrosis were identified. Gene Ontology (GO) resources, Kyoto Encyclopedia of Genes and Genomes (KEGG) resources, and gene set enrichment analysis (GSEA) were utilized for functional enrichment analysis. A protein-protein interaction network (PPI) was constructed using a string database. Potential key genes were selected based on the bioinformatics information mentioned above. SVM and LASSO were employed to identify hub genes and construct the module associated with HF. The mRNA levels of TAC mice and external datasets (GSE141910 and GSE59867) are utilized for validating the diagnostic model. Additionally, the study explores the relationship between the diagnostic model and immune cell infiltration.

RESULTS

A total of 395 genes exhibiting differential expression were identified. Functional enrichment analysis revealed that these specific genes primarily participate in biological processes and pathways associated with the constituents of the extracellular matrix (ECM), immune system processes, and inflammatory responses. We identified a diagnostic model consisting of 16 hub genes, and its predictive performance was validated using external data sets and a transverse aortic coarctation (TAC) mouse model. In addition, we observed significant differences in mRNA expression of 7 genes in the TAC mouse model. Interestingly, our study also unveiled a correlation between these model genes and immune cell infiltration.

CONCLUSIONS

We identified sixteen key genes associated with myocardial fibrosis and conduction block, as well as diagnostic models for heart failure. Our findings have significant implications for the intensive management of individuals with potential genetic variants associated with heart failure, especially in the context of advancing cell-targeted therapy for myocardial fibrosis.

Study of molecular patterns associated with ferroptosis in Parkinson's disease and its immune signature

Parkinson's disease is the second most common neurodegenerative disease in the world. We downloaded data on Parkinson's disease and Ferroptosis-related genes from the GEO and FerrDb databases. We used WCGAN and Random Forest algorithm to screen out five Parkinson's disease ferroptosis-related hub genes. Two genes were identified for the first time as possibly playing a role in Braak staging progression. Unsupervised clustering analysis based on hub genes yielded ferroptosis isoforms, and immune infiltration analysis indicated that these isoforms are associated with immune cells and may represent different immune patterns. FRHGs scores were obtained to quantify the level of ferroptosis modifications in each individual. In addition, differences in interleukin expression were found between the two ferroptosis subtypes. The biological functions involved in the hub gene are analyzed. The ceRNA regulatory network of hub genes was mapped. The disease classification diagnosis model and risk prediction model were also constructed by applying hub genes based on logistic regression. Multiple external datasets validated the hub gene and classification diagnostic model with some accuracy. This study explored hub genes associated with ferroptosis in Parkinson's disease and their molecular patterns and immune signatures to provide new ideas for finding new targets for intervention and predictive biomarkers.

Comprehensive analysis of geographic and breed-purpose influences on genetic diversity and inherited disease risk in the Doberman dog breed

BACKGROUND

Publicly available phenotype data and genotyping array data from two citizen science projects: "Doberman Health Surveys" and "The Doberman Diversity Project" were analyzed to explore relative homozygosity, diversity, and disorder risk according to geographical locale and breeding purpose in the Doberman.

RESULTS

From the phenotypic data cohort, life expectancy of a Doberman at birth is 9.1 years. The leading causes of death were heart disease (accounting for 28% of deaths) and cancers (collectively accounting for 14% of deaths). By genotyping, the world Doberman population exists as four major cohorts (European exhibition-bred, Americas exhibition-bred, European work, Americas pet/informal). Considering the entire Doberman population, four genomic regions longer than 500 Kb are fixed in 90% or more of 3,226 dogs included in this study. The four fixed regions reside on two autosomal chromosomes: CFA3:0.8-2.3 Mb (1.55 Mb); CFA3: 57.9-59.8 Mb (1.8 Mb); CFA31:0-1.2 Mb (1.2 Mb); and CFA31:4.80-6.47 Mb (1.67 Mb). Using public variant call files including variants for eight Doberman pinschers, we observed 30 potentially functional alternate variants that were evolutionarily diverged relative to the wider sequenced dog population within the four strongly homozygous chromosomal regions. Effective population size (Ne) is a statistical measure of breed diversity at the time of sampling that approximates the number of unique individuals. The major identified sub-populations of Dobermans demonstrated Ne in the range 70-236. The mean level of inbreeding in the Doberman breed is 40% as calculated by the number of array variants in runs of homozygosity divided by the assayed genome size (excluding the X chromosome). The lowest observed level of inbreeding in the Dobermans assayed was 15% in animals that were first generation mixes of European and USA bred Dobermans. Array variant analysis shows that inter-crossing between European and USA-bred Dobermans has capacity to re-introduce variation at many loci that are strongly homozygous.

CONCLUSIONS

We conclude that efforts to improve breed diversity first should focus on regions with the highest fixation levels, but managers must ensure that mutation loads are not worsened by increasing the frequencies of rarer haplotypes in the identified regions. The analysis of global data identified regions of strong fixation that might impact known disorder risks in the breed. Plausible gene candidates for future analysis of the genetic basis of cardiac disease and cancer were identified in the analysis.

Comparative cytotoxicity, endocrine-disrupting effects, oxidative stress of halophenolic disinfection byproducts and the underlying molecular mechanisms revealed by transcriptome analysis

Halophenolic disinfection byproducts (DBPs) are a class of emerging pollutants whose adverse effects on human cells and the underlying molecular mechanisms still need further exploration. In this study, we found that when halophenolic DBPs were substituted with the same halogen, the more substitution sites, the more cytotoxic, while when they were substituted at the same sites, the most toxic chemical was iodophenols, followed by bromophenols and chlorophenols. In addition, several of them exerted significant endocrine-disrupting effects at sublethal concentrations. 2,4,6-triiodophenol (TIP) and 2,4-dichlorophenol (2,4-DCP) showed the highest estradiol equivalent factor (EEF) of 4.41 × 10^-8 and flutamide equivalent factor (FEF) of 0.4, respectively. Furthermore, all of the halophenolic DBPs except for 2-chlorophenol (2-CP) and 2-bromophenol (2-BP) significantly increased the levels of reactive oxygen species (ROS) or 8-hydroxydeoxyguanosine (8-OHdG) in HepG2 cells. The lowest cytotoxicity and unchanged ROS and 8-OHdG levels after 2-CP exposure may result from the activation of the transporters of the adenosine triphosphate (ATP) binding cassette in cells. Transcriptome analysis revealed distinct grouping patterns of 2-CP, 2,6-dibromophenol (2,6-DBP), and TIP at the concentrations of EC₂₀, and the top differentially expressed genes (DEGs) were involved in the antioxidant-, immune-, and endocrine-associated systems. The weighted gene correlation network analysis well connected the phenotypes (EC₅₀, EEF, FEF, ROS, 8-OHdG, and ABC transporters) with the DEGs and revealed that the MAPK signaling pathway played a vital role in regulating the biological response after exposure to halophenolic DBPs. This study provides deep insights into the underlying mechanisms of the toxic effects induced by halophenolic DBPs.