Gene co-expression network analysis identifies the hub genes associated with immune functions for nocturnal hemodialysis in patients with end-stage renal disease

Multivariate canonical correlation analysis identifies additional genetic variants for chronic kidney disease

Chronic kidney diseases (CKD) have genetic associations with kidney function. Univariate genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with estimated glomerular filtration rate (eGFR) and blood urea nitrogen (BUN), two complementary kidney function markers. However, it is unknown whether additional SNPs for kidney function can be identified by multivariate statistical analysis. To address this, we applied canonical correlation analysis (CCA), a multivariate method, to two individual-level CKD genotype datasets, and metaCCA to two published GWAS summary statistics datasets. We identified SNPs previously associated with kidney function by published univariate GWASs with high replication rates, validating the metaCCA method. We then extended discovery and identified previously unreported lead SNPs for both kidney function markers, jointly. These showed expression quantitative trait loci (eQTL) colocalisation with genes having significant differential expression between CKD and healthy individuals. Several of these identified lead missense SNPs were predicted to have a functional impact, including in SLC14A2. We also identified previously unreported lead SNPs that showed significant correlation with both kidney function markers, jointly, in the European ancestry CKDGen, National Unified Renal Translational Research Enterprise (NURTuRE)-CKD and Salford Kidney Study (SKS) datasets. Of these, rs3094060 colocalised with FLOT1 gene expression and was significantly more common in CKD cases in both NURTURE-CKD and SKS, than in the general population. Overall, by using multivariate analysis by CCA, we identified additional SNPs and genes for both kidney function and CKD, that can be prioritised for further CKD analyses.

C/EBPα aggravates renal fibrosis in CKD through the NOX4-ROS-apoptosis pathway in tubular epithelial cells

BACKGROUND

Chronic kidney disease (CKD) is a prevalent renal disorder with various risk factors. Emerging evidence indicates that the transcriptional factor CCAAT/enhancer binding protein alpha (C/EBPα) may be associated with renal fibrosis. However, the precise role of C/EBPα in CKD progression remains unexplored.

METHODS

We investigated the involvement of C/EBPα in CKD using two distinct mouse models induced by folic acid (FA) and unilateral ureteral obstruction (UUO). Additionally, we used RNA sequencing and KEGG analysis to identify potential downstream pathways governed by C/EBPα.

FINDINGS

Cebpa knockout significantly shielded mice from renal fibrosis and reduced reactive oxygen species (ROS) levels in both the FA and UUO models. Primary tubular epithelial cells (PTECs) lacking Cebpa exhibited reduced apoptosis and ROS accumulation following treatment with TGF-β. RNA sequencing analysis suggested that apoptosis is among the primary pathways regulated by C/EBPα, and identified NADPH oxidoreductase 4 (NOX4) as a key protein upregulated upon C/EBPα induction (ICCB280). Treatment with l-Theanine, a potential NOX4 inhibitor, mitigated renal fibrosis and inflammation in both the FA and UUO mouse models.

INTERPRETATION

Our study unveils a role for C/EBPα in suppressing renal fibrosis, mitigating ROS accumulation, and reducing cell apoptosis. Furthermore, we investigate whether these protective effects are mediated by C/EBPα's regulation of NOX4 expression. These findings present a promising therapeutic target for modulating ROS and apoptosis in renal tubular cells, potentially offering an approach to treating CKD and other fibrotic diseases.

Integrative systems biology framework discovers common gene regulatory signatures in multiple mechanistically distinct inflammatory skin diseases

More than 20% of the population across the world is affected by non-communicable inflammatory skin diseases including psoriasis, atopic dermatitis, hidradenitis suppurativa, rosacea, etc. Many of these chronic diseases are painful and debilitating with limited effective therapeutic interventions. However, recent advances in psoriasis treatment have improved the effectiveness and provide better management of the disease. This study aims to identify common regulatory pathways and master regulators that regulate molecular pathogenesis. We designed an integrative systems biology framework to identify the significant regulators across several inflammatory skin diseases. With conventional transcriptome analysis, we identified 55 shared genes, which are enriched in several immune-associated pathways in eight inflammatory skin diseases. Next, we exploited the gene co-expression-, and protein-protein interaction-based networks to identify shared genes and protein components in different diseases with relevant functional implications. Additionally, the network analytics unravels 55 high-value proteins as significant regulators in molecular pathogenesis. We believe that these significant regulators should be explored with critical experimental approaches to identify the putative drug targets for more effective treatments. As an example, we identified IKZF1 as a shared significant master regulator in three inflammatory skin diseases, which can serve as a putative drug target with known disease-derived molecules for developing efficacious combinatorial treatments for hidradenitis suppurativa, atopic dermatitis, and rosacea. The proposed framework is very modular, which can indicate a significant path of molecular mechanism-based drug development from complex transcriptomics data and other multi-omics data.

The roles of FLOT1 in human diseases (Review)

FLOT1, a scaffold protein of lipid rafts, is involved in several biological processes, including lipid raft protein‑-dependent or clathrin‑independent endocytosis, and the formation of hippocampal synapses, amongst others. Increasing evidence has shown that FLOT1 can function as both a cancer promoter and cancer suppressor dependent on the type of cancer. FLOT1 can affect the occurrence and development of several types of cancer by affecting epithelial‑mesenchymal transition, proliferation of cancer cells, and relevant signaling pathways, and is regulated by long intergenic non‑coding RNAs or microRNAs. In the nervous system, overexpression or abnormally low expression of FLOT1 may lead to the occurrence of neurological diseases, such as Alzheimer's disease, Parkinson's disease, major depressive disorder and other diseases. Additionally, it is also associated with dilated cardiomyopathy, pathogenic microbial infection, diabetes‑related diseases, and gynecological diseases, amongst other diseases. In the present review, the structure and localization of FLOT1, as well as the physiological processes it is involved in are reviewed, and then the upstream and downstream regulation of FLOT1 in human disease, particularly in different types of cancer and neurological diseases are discussed, with a focus on potentially targeting FLOT1 for the clinical treatment of several diseases.

Gene coexpression network analysis reveals perirenal adipose tissue as an important target of prenatal malnutrition in sheep

We have previously demonstrated that pre- and early postnatal malnutrition in sheep induced depot- and sex-specific changes in adipose morphological features, metabolic outcomes, and transcriptome in adulthood, with perirenal (PER) as the major target followed by subcutaneous (SUB) adipose tissue. We aimed to identify coexpressed and hub genes in SUB and PER to identify the underlying molecular mechanisms contributing to the early nutritional programming of adipose-related phenotypic outcomes. Transcriptomes of SUB and PER of male and female adult sheep with different pre- and early postnatal nutrition histories were used to construct networks of coexpressed genes likely to be functionally associated with pre- and early postnatal nutrition histories and phenotypic traits using weighted gene coexpression network analysis. The modules from PER showed enrichment of cell cycle regulation, gene expression, transmembrane transport, and metabolic processes associated with both sexes' prenatal nutrition. In SUB (only males), a module of enriched adenosine diphosphate metabolism and development correlated with prenatal nutrition. Sex-specific module enrichments were found in PER, such as chromatin modification in the male network but histone modification and mitochondria- and oxidative phosphorylation-related functions in the female network. These sex-specific modules correlated with prenatal nutrition and adipocyte size distribution patterns. Our results point to PER as a primary target of prenatal malnutrition compared to SUB, which played only a minor role. The prenatal programming of gene expression and cell cycle, potentially through epigenetic modifications, might be underlying mechanisms responsible for observed changes in PER expandability and adipocyte-size distribution patterns in adulthood in both sexes.

The characteristics of extrachromosomal circular DNA in patients with end-stage renal disease

BACKGROUND

End-stage renal disease (ESRD) is the final stage of chronic kidney disease (CKD). In addition to the structurally intact chromosome genomic DNA, there is a double-stranded circular DNA called extrachromosomal circular DNA (eccDNA), which is thought to be involved in the epigenetic regulation of human disease. However, the features of eccDNA in ESRD patients are barely known. In this study, we identified eccDNA from ESRD patients and healthy people, as well as revealed the characteristics of eccDNA in patients with ESRD.

METHODS

Using the high-throughput Circle-Sequencing technique, we examined the eccDNA in peripheral blood mononuclear cells (PBMCs) from healthy people (NC) (n = 12) and ESRD patients (n = 16). We analyzed the length distribution, genome elements, and motifs feature of eccDNA in ESRD patients. Then, after identifying the specific eccDNA in ESRD patients, we explored the potential functions of the target genes of the specific eccDNA. Finally, we investigated the probable hub eccDNA using algorithms.

RESULTS

In total, 14,431 and 11,324 eccDNAs were found in the ESRD and NC groups, respectively, with sizes ranging from 0.01 kb to 60 kb at most. Additionally, the ESRD group had a greater distribution of eccDNA on chromosomes 4, 11, 13, and 20. In two groups, we also discovered several motifs of specific eccDNAs. Furthermore, we identified 13,715 specific eccDNAs in the ESRD group and 10,585 specific eccDNAs in the NC group, both of which were largely annotated as mRNA catalog. Pathway studies using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) showed that the specific eccDNA in ESRD was markedly enriched in cell junction and communication pathways. Furthermore, we identified potentially 20 hub eccDNA-targeting genes from all ESRD-specific eccDNA-targeting genes. Also, we found that 39 eccDNA-targeting genes were associated with ESRD, and some of these eccDNAs may be related to the pathogenesis of ESRD.

CONCLUSIONS

Our findings revealed the characteristics of eccDNA in ESRD patients and discovered potentially hub and ESRD-relevant eccDNA-targeting genes, suggesting a novel probable mechanism of ESRD.

A single-cell map for the transcriptomic signatures of peripheral blood mononuclear cells in end-stage renal disease

BACKGROUND

Immune aberrations in end-stage renal disease (ESRD) are characterized by systemic inflammation and immune deficiency. The mechanistic understanding of this phenomenon remains limited.

METHODS

We generated 12 981 and 9578 single-cell transcriptomes of peripheral blood mononuclear cells (PBMCs) that were pooled from 10 healthy volunteers and 10 patients with ESRD by single-cell RNA sequencing. Unsupervised clustering and annotation analyses were performed to cluster and identify cell types. The analysis of hallmark pathway and regulon activity was performed in the main cell types.

RESULTS

We identified 14 leukocytic clusters that corresponded to six known PBMC types. The comparison of cells from ESRD patients and healthy individuals revealed multiple changes in biological processes. We noticed an ESRD-related increase in inflammation response, complement cascade and cellular metabolism, as well as a strong decrease in activity related to cell cycle progression in relevant cell types in ESRD. Furthermore, a list of cell type-specific candidate transcription factors (TFs) driving the ESRD-associated transcriptome changes was identified.

CONCLUSIONS

We generated a distinctive, high-resolution map of ESRD-derived PBMCs. These results revealed cell type-specific ESRD-associated pathways and TFs. Notably, the pooled sample analysis limits the generalization of our results. The generation of larger single-cell datasets will complement the current map and drive advances in therapies that manipulate immune cell function in ESRD.

Elucidation of Novel cis-Regulatory Elements and Promoter Structures Involved in Iron Excess Response Mechanisms in Rice Using a Bioinformatics Approach

Iron (Fe) excess is a major constraint on crop production in flooded acidic soils, particularly in rice cultivation. Under Fe excess, plants activate a complex mechanism and network regulating Fe exclusion by roots and isolation in various tissues. In rice, the transcription factors and cis-regulatory elements (CREs) that regulate Fe excess response mechanisms remain largely elusive. We previously reported comprehensive microarray analyses of several rice tissues in response to various levels of Fe excess stress. In this study, we further explored novel CREs and promoter structures in rice using bioinformatics approaches with this microarray data. We first performed network analyses to predict Fe excess-related CREs through the categorization of the gene expression patterns of Fe excess-responsive transcriptional regulons, and found four major expression clusters: Fe storage type, Fe chelator type, Fe uptake type, and WRKY and other co-expression type. Next, we explored CREs within these four clusters of gene expression types using a machine-learning method called microarray-associated motif analyzer (MAMA), which we previously established. Through a comprehensive bioinformatics approach, we identified a total of 560 CRE candidates extracted by MAMA analyses and 42 important conserved sequences of CREs directly related to the Fe excess response in various rice tissues. We explored several novel cis-elements as candidate Fe excess CREs including GCWGCWGC, CGACACGC, and Myb binding-like motifs. Based on the presence or absence of candidate CREs using MAMA and known PLACE CREs, we found that the Boruta-XGBoost model explained expression patterns with high accuracy of about 83%. Enriched sequences of both novel MAMA CREs and known PLACE CREs led to high accuracy expression patterns. We also found new roles of known CREs in the Fe excess response, including the DCEp2 motif, IDEF1-, Zinc Finger-, WRKY-, Myb-, AP2/ERF-, MADS- box-, bZIP and bHLH- binding sequence-containing motifs among Fe excess-responsive genes. In addition, we built a molecular model and promoter structures regulating Fe excess-responsive genes based on new finding CREs. Together, our findings about Fe excess-related CREs and conserved sequences will provide a comprehensive resource for discovery of genes and transcription factors involved in Fe excess-responsive pathways, clarification of the Fe excess response mechanism in rice, and future application of the promoter sequences to produce genotypes tolerant of Fe excess.

Transcriptional circuitry atlas of genetic diverse unstimulated murine and human macrophages define disparity in population-wide innate immunity

Macrophages are ubiquitous custodians of tissues, which play decisive role in maintaining cellular homeostasis through regulatory immune responses. Within tissues, macrophage exhibit extremely heterogeneous population with varying functions orchestrated through regulatory response, which can be further exacerbated in diverse genetic backgrounds. Gene regulatory networks (GRNs) offer comprehensive understanding of cellular regulatory behavior by unfolding the transcription factors (TFs) and regulated target genes. RNA-Seq coupled with ATAC-Seq has revolutionized the regulome landscape influenced by gene expression modeling. Here, we employ an integrative multi-omics systems biology-based analysis and generated GRNs derived from the unstimulated bone marrow-derived macrophages of five inbred genetically defined murine strains, which are reported to be linked with most of the population-wide human genetic variants. Our probabilistic modeling of a basal hemostasis pan regulatory repertoire in diverse macrophages discovered 96 TFs targeting 6279 genes representing 468,291 interactions across five inbred murine strains. Subsequently, we identify core and distinctive GRN sub-networks in unstimulated macrophages to describe the system-wide conservation and dissimilarities, respectively across five murine strains. Our study concludes that discrepancies in unstimulated macrophage-specific regulatory networks not only drives the basal functional plasticity within genetic backgrounds, additionally aid in understanding the complexity of racial disparity among the human population during stress.

Construction and Validation of Predictive Model to Identify Critical Genes Associated with Advanced Kidney Disease

Background

Chronic kidney disease (CKD) is characterized by progressive renal function loss, which may finally lead to end-stage renal disease (ESRD). The study is aimed at identifying crucial genes related to CKD progressive and constructing a disease prediction model to investigate risk factors.

Methods

GSE97709 and GSE37171 datasets were downloaded from the GEO database including peripheral blood samples from subjects with CKD, ESRD, and healthy controls. Differential expressed genes (DEGs) were identified and functional enrichment analysis. Machine learning algorithm-based prediction model was constructed to identify crucial functional feature genes related to ESRD.

Results

A total of 76 DEGs were screened from CDK vs. normal samples while 10,114 DEGs were identified from ESRD vs. CDK samples. For numerous genes related to ESRD, several GO biological terms and 141 signaling pathways were identified including markedly upregulated olfactory transduction and downregulated platelet activation pathway. The DEGs were clustering in three modules according to WGCNA access, namely, ME1, ME2, and ME3. By construction of the XGBoost model and dataset validation, we screened cohorts of genes associated with progressive CKD, such as FZD10, FOXD4, and FAM215A. FZD10 represented the highest score (F score = 21) in predictive model.

Conclusion

Our results demonstrated that FZD10, FOXD4, PPP3R1, and UCP2 might be critical genes in CKD progression.

Development of a Bioinformatics Framework for Identification and Validation of Genomic Biomarkers and Key Immunopathology Processes and Controllers in Infectious and Non-infectious Severe Inflammatory Response Syndrome

Sepsis is defined as dysregulated host response caused by systemic infection, leading to organ failure. It is a life-threatening condition, often requiring admission to an intensive care unit (ICU). The causative agents and processes involved are multifactorial but are characterized by an overarching inflammatory response, sharing elements in common with severe inflammatory response syndrome (SIRS) of non-infectious origin. Sepsis presents with a range of pathophysiological and genetic features which make clinical differentiation from SIRS very challenging. This may reflect a poor understanding of the key gene inter-activities and/or pathway associations underlying these disease processes. Improved understanding is critical for early differential recognition of sepsis and SIRS and to improve patient management and clinical outcomes. Judicious selection of gene biomarkers suitable for development of diagnostic tests/testing could make differentiation of sepsis and SIRS feasible. Here we describe a methodologic framework for the identification and validation of biomarkers in SIRS, sepsis and septic shock patients, using a 2-tier gene screening, artificial neural network (ANN) data mining technique, using previously published gene expression datasets. Eight key hub markers have been identified which may delineate distinct, core disease processes and which show potential for informing underlying immunological and pathological processes and thus patient stratification and treatment. These do not show sufficient fold change differences between the different disease states to be useful as primary diagnostic biomarkers, but are instrumental in identifying candidate pathways and other associated biomarkers for further exploration.

Traumatic brain injury induces long-lasting changes in immune and regenerative signaling

There are no existing treatments for the long-term degenerative effects of traumatic brain injury (TBI). This is due, in part, to our limited understanding of chronic TBI and uncertainty about which proposed mechanisms for long-term neurodegeneration are amenable to treatment with existing or novel drugs. Here, we used microarray and pathway analyses to interrogate TBI-induced gene expression in the rat hippocampus and cortex at several acute, subchronic and chronic intervals (24 hours, 2 weeks, 1, 2, 3, 6 and 12 months) after parasagittal fluid percussion injury. We used Ingenuity pathway analysis (IPA) and Gene Ontology enrichment analysis to identify significantly expressed genes and prominent cell signaling pathways that are dysregulated weeks to months after TBI and potentially amenable to therapeutic modulation. We noted long-term, coordinated changes in expression of genes belonging to canonical pathways associated with the innate immune response (i.e., NF-κB signaling, NFAT signaling, Complement System, Acute Phase Response, Toll-like receptor signaling, and Neuroinflammatory signaling). Bioinformatic analysis suggested that dysregulation of these immune mediators—many are key hub genes—would compromise multiple cell signaling pathways essential for homeostatic brain function, particularly those involved in cell survival and neuroplasticity. Importantly, the temporal profile of beneficial and maladaptive immunoregulatory genes in the weeks to months after the initial TBI suggests wider therapeutic windows than previously indicated.