Functional Module Analysis Research Articles

Exploring the impact of telemedicine in chronic patients from diverse socioeconomic contexts: systematic review of qualitative studies

BackgroundTelemedicine has a positive impact on improving health literacy and disease management ability of chronic disease patients and reducing the medical burden. However, telemedicine still has many problems in chronic disease management. We should actively solve the problems and maximize the functions of telemedicine.ObjectiveTo explore the application and improvement of telemedicine in chronic disease self-management to provide important insights from functional module analysis for stakeholders, healthcare professionals, and policymakers to promote the development of telemedicine in chronic disease management.DesignWe conducted a systematic review and qualitative synthesis of five English databases including PubMed, Embase, Web of Science, Cochrane Database of Systematic Reviews, and Scopus, as well as three Chinese databases: China National Knowledge Infrastructure (CNKI), WanFang and VIP database. Databases were searched from inception until November 12, 2024.MethodsThis review is reported in accordance with guidelines for Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ). Two reviewers independently performed study selection, data extraction, and quality assessment using the Joanna Briggs Institute's key assessment tools for qualitative research. Thematic analysis was used for data synthesis.ResultsA total of 35 studies were included, and the contents were refined and summarized into 8 new subthemes. Then, four themes were synthesized: Reminder and supervisor, Access to knowledge, Transition in medical treatment mode, and Emotional support platform.ConclusionBy improving information quality, developing diverse functions, and constructing multidisciplinary coordination mechanisms to meet the needs of patients with chronic diseases, improve the medical service system, maximize the function of telemedicine, and enhance the stickiness of patients to use telemedicine.

An efficient test case selection framework for multitenant SaaS applications using RTS4MTS

The augmentation of multitenant Software as a Service (SaaS) has significantly contributed to the success of cloud computing. To stay competitive, multitenant SaaS applications are frequently updated, necessitating regression tests. Regression testing ensures modifications do not alter existing functionalities or introduce new bugs. Rerunning all test cases is resource intensive. To minimize efforts, it's crucial to select a relevant subset of test cases. Thus, a novel framework, Regression Test Selection for Multitenant SaaS (RTS4MTS), is proposed for selective regression testing in multitenant SaaS applications. This framework uses the Functional Coverage Module (FCM) and Dependency Analysis Module (DAM) to select relevant test cases. It classifies existing test cases into two groups: those affected by modifications (need to test) and those unaffected (no need to test). Applying RTS4MTS to the multitenant SaaS MtBookTrip application demonstrated that the framework reduces the test suite size by 68% and lowers test execution time by 70%, thereby saving resources and testing costs.

Characteristics of Microbial Diversity and Metabolic Versatility in Dynamic Mid-Okinawa Trough Subsurface Sediments

Large-scale and multi-sample datasets have revealed that microbial diversity and geographic distribution patterns are distinct across various habitats, particularly between hydrothermal vent and cold seep ecosystems. To date, our understanding of the effects of spatial and geochemical gradients on marine microbial communities remains limited. Here, we report the microbial diversity and metabolic versatility of a remote seafloor sediment ecosystem at different sites (GC-2, -4, -5, -6, -8) in the Mid-Okinawa Trough (Mid-OT) using high-throughput metagenomic sequencing technology. Desulfobacteraceae (3.1%) were detected in a high abundance at GC-2 with intense methane concentrations (353 μL/L), which showed a clear correlation with cold seeping. Whereas Candidatus Brocadiaceae (1.7%), Rhodobacteraceae (0.9%), and Rhodospirillaceae (0.7%), which are commonly involved in denitrification and sulfur oxidation, were enriched at GC-8. Concurrently investigating the potential of deep-sea microbial metabolism, we gained insights into the adaptive capabilities and metabolic mechanisms of microorganisms within seafloor environments. Utilizing the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, the analysis of functional modules revealed a significant enrichment (71–74%) of genes associated with metabolic pathways. These results expand our knowledge of the relationship between microbial biodiversity and metabolic versatility in deep-sea extreme environments.

Evaluation on LED lighting driving power supply for urban rail vehicles based on adaptive PID algorithm

LED (Light Emitting Diode) lighting has the characteristics of efficiency, environmental protection, energy conservation, and so on. It is more and more widely used in the lighting system of urban rail vehicles. The research on the LED lighting system of rail vehicles has important practical significance. As the core of the LED lighting system of rail vehicles, the LED control system of urban rail vehicles is the key to ensure the stable operation of the entire LED lighting system. The lighting environment of urban rail vehicles needs LED lighting system with good power stability, long life of drive chip, high feedback accuracy, fast processing speed, intelligent algorithm efficiency and other characteristics to ensure continuous operation, and also should have strong anti-interference ability and excellent static performance. However, conventional lighting systems not only have low life, but also have poor stability. Therefore, this paper studied the uniqueness and functional module analysis of LED driving power supply by analyzing the causes and disadvantages of LED lighting, and finally optimized the design of LED lighting control system by using the adaptive PID (Proportional Integral Differential) algorithm. Through comparison, the brightness acquisition quality of LED lighting control system was 21.2 % higher than that of traditional lighting control system, and the lighting control effect was 18 % higher than that of traditional lighting control system. In short, the selection of LED lighting driving power affects the lighting effect of rail vehicles.

CCL20 and CD8A as potential diagnostic biomarkers for HBV-induced liver fibrosis in chronic hepatitis B

BackgroundThe main cause of the liver fibrosis (LF) remains hepatitis B virus (HBV) infection, especially in China. Histologically, liver fibrosis still occurs progressively in chronic hepatitis B (CHB) patients, even if HBV-DNA is negative or undetectable. The diagnosis of LF is beneficial to control the development of it, also it may promote the reversal of LF. Although liver biopsy is the gold standard of diagnosis in LF at present, it isa traumatic diagnosis. There are no diagnostic biomarkers as yet for the condition. It is badly in need of biomarkers clinically, which is simple to test, minimally invasive, highly specific, and sensitive. Early detection of HBV-LF development is crucial in the prevention, treatment, and prognosis prediction of HBV-LF. Cytokines are closely associated with both immune regulation and inflammation in the progression of hepatitis B virus associated-liver fibrosis (HBV-LF). In this bioinformatic study, we not only analyzed the relationship between HBV-LF and immune infiltration, but also identified key genes to uncover new therapeutic targets. ObjectivesTo find potential biomarkers for liver fibrosis in the development of chronic hepatic B patients. Materials and methodsWe obtained two sets of data including CHB/healthy control and CHB/HBV-LF from the Integrated Gene Expression (GEO) database to select for differential expression analysis. Protein-protein interaction (PPI) network was also generated, while key genes and important gene modules involved in the occurrence and development of HBV-LF were identified. These key genes were analyzed by functional enrichment analysis, module analysis, and survival analysis. Furthermore, the relationship between these two diseases and immune infiltration was explored. ResultsAmong the identified genes, 150 were individually associated with CHB and healthy control in the differential gene expression (DGE) analysis. While 14 with CHB and HBV-LF. It was also analyzed in the Robust rank aggregation (RRA) analysis, 34 differential genes were further identified by Cytohubba. Among 34 differential genes, two core genes were determined: CCL20 and CD8A. CCL20 was able to predict CHB positivity (area under the receiver operating characteristic curve [AUC-ROC] = 0.883, 95% confidence interval [CI] 0.786–0.963), while HBV-LF positivity ([AUC-ROC] = 0.687, 95% confidence interval [CI] 0.592–0.779). And CD8A was able to predict CHB positivity ([AUC-ROC] = 0.960, 95% confidence interval [CI] 0.915–0.992), while HBV-LF positivity ([AUC-ROC] = 0.773, 95% confidence interval [CI] 0.680–0.856). Relationship between CCL20 gene expression and LF grades was P < 0.05, as well as CD8A. ConclusionCCL20 and CD8A were found to be potential biomarkers and therapeutic targets for HBV-LF. It is instructive for research on the progression of LF in HBV patients, suppression of chronic inflammation, and development of molecularly targeted-therapy for HBV-LF.

Integrated transcriptome sequencing and weighted gene co-expression network analysis reveals key genes of papillary thyroid carcinomas

ObjectivePapillary thyroid carcinoma (PTC) accounts for the majority of thyroid cancers and has a high recurrence rate. We aimed to screen key genes involved in PTC to provide novel insights into the mechanisms of PTC. MethodsSeven microarray datasets of PTC were downloaded from gene expression omnibus database. Differentially expressed genes (DEGs) between PTC and normal samples were screened in the merged dataset. Then, protein-protein interaction (PPIs) functional modules analysis and weighted gene co-expression network analysis (WGCNA) were utilized to identify PTC-associated key genes. The identified key genes were then characterized from various aspects, including gene set enrichment analysis (GSEA) and the associations with immune infiltration, methylation levels and prognosis. ResultsA large numbers of DEGs were identified, and these DEGs are involved in several cancer pathways. Nine key genes (including down-regulated genes GNA14, AVPR1A, and WFS1, and up-regulated genes LAMB3, PLAU, MET, MFGE8, PRSS23, and SERPINA1) were identified. Patients in the AVPR1A and GNA14 high expression groups had better disease-free survival (DFS) than those in the low expression group. Key genes were mainly involved in P53 pathway, estrogen response, apoptosis, glycolysis, NOTCH signaling, epithelial mesenchymal transition, WNT_beta catenin signaling, and inflammatory response. The expression of key genes was associated with immune cell infiltration and corresponding methylation levels. The verification results of key gene proteins and mRNA expression levels using external validation datasets were consistent with our expectations, implying the involvements of key genes in PTC. ConclusionThe key genes may serve as potential therapeutic targets for PTC. This study provides novel insights into the mechanisms underlying PTC development.

Identification of crucial genes of pediatric inflammatory bowel disease in remission by protein-protein interaction network and module analyses.

Although the main treatments of inflammatory bowel disease (IBD) aim at the induction and maintenance of clinical remission, several studies have demonstrated inflammation still present in clinical remission. The goal of this study was to analyze the gene expression profiles between the pediatric IBD and control samples, aiming to further investigate the underlying therapeutic target in remission. Gene expression profiles data of GSE33943 were downloaded from Gene Expression Omnibus, which included 45 pediatric IBD samples and 13 control samples. The differentially expressed genes (DEGs) between IBD and control samples were identified by LIMMA package in R and the function of DEGs were predicted by Gene Ontology and KEGG pathway enrichment analyses using GeneAnswer package. Furthermore, a protein-protein interaction (PPI) network was constructed through the STRING database and functional module was obtained using ClusterONE. A total of 224 DEGs were screened between IBD and control samples. These DEGs (e.g. up-regulated FAS and down-regulated CCL5) were mainly enriched in cytokine‒cytokine receptor interaction and chemokine signaling pathway. In addition, some hub genes (e.g. up-regulated PSMA2 and PSMA6) were obtained through PPI network and functional module. These two genes were involved in Proteasome alpha-subunit and conserved site by functional module analysis. The immune and Proteasome mechanisms are still active during remission and FAS, PMSF6 and PMSF2 may be underlying targets for therapy of this disease.

Analysis of the Genetic Relationship between Atherosclerosis and Non-Alcoholic Fatty Liver Disease through Biological Interaction Networks.

Non-alcoholic fatty liver disease (NAFLD) seems to have some molecular links with atherosclerosis (ATH); however, the molecular pathways which connect both pathologies remain unexplored to date. The identification of common factors is of great interest to explore some therapeutic strategies to improve the outcomes for those affected patients. Differentially expressed genes (DEGs) for NAFLD and ATH were extracted from the GSE89632 and GSE100927 datasets, and common up- and downregulated DEGs were identified. Subsequently, a protein-protein interaction (PPI) network based on the common DEGs was performed. Functional modules were identified, and the hub genes were extracted. Then, a Gene Ontology (GO) and pathway analysis of common DEGs was performed. DEGs analysis in NAFLD and ATH showed 21 genes that were regulated similarly in both pathologies. The common DEGs with high centrality scores were ADAMTS1 and CEBPA which appeared to be down- and up-regulated in both disorders, respectively. For the analysis of functional modules, two modules were identified. The first one was oriented to post-translational protein modification, where ADAMTS1 and ADAMTS4 were identified, and the second one mainly related to the immune response, where CSF3 was identified. These factors could be key proteins with an important role in the NAFLD/ATH axis.

Integrated DNA Methylation/RNA Profiling in Middle Temporal Gyrus of Alzheimer’s Disease

Alzheimer’s disease is a neurodegenerative disorder clinically defined by gradual cognitive impairment and alteration in executive function. We conducted an epigenome-wide association study (EWAS) of a clinically and neuropathologically characterized cohort of 296 brains, including Alzheimer’s disease (AD) and non-demented controls (ND), exploring the relationship with the RNA expression from matched donors. We detected 5246 CpGs and 832 regions differentially methylated, finding overlap with previous EWAS but also new associations. CpGs previously identified in ANK1, MYOC, and RHBDF2 were differentially methylated, and one of our top hits (GPR56) was not previously detected. ANK1 was differentially methylated at the region level, along with APOE and RHBDF2. Only a small number of genes showed a correlation between DNA methylation and RNA expression statistically significant. Multiblock partial least-squares discriminant analysis showed several CpG sites and RNAs discriminating AD and ND (AUC = 0.908) and strongly correlated with each other. Furthermore, the CpG site cg25038311 was negatively correlated with the expression of 22 genes. Finally, with the functional epigenetic module analysis, we identified a protein–protein network characterized by inverse RNA/DNA methylation correlation and enriched for “Regulation of insulin-like growth factor transport”, with IGF1 as the hub gene. Our results confirm and extend the previous EWAS, providing new information about a brain region not previously explored in AD DNA methylation studies. The relationship between DNA methylation and gene expression is not significant for most of the genes in our sample, consistently with the complexities in the gene expression regulation.Graphical

Data-driven precision medicine through the analysis of biological functional modules

Data-driven methods are expected to enable a next generation of personalized, preventative medicine. Zhang and colleagues1 demonstrate how biological functional modules (BFMs) derived from the analysis of multimodal data can provide detailed quantitative health assessments and inform medical interventions.

Identification of an Epigenetic Signature for Coronary Heart Disease in Postmenopausal Women's PBMC DNA.

Menopause is accompanied with an increased risk of cardiovascular disease. DNA methylation may have a significant impact on postmenopausal women's development of coronary heart disease. DNA methylation alterations in peripheral blood mononuclear cells (PBMCs) from women with coronary heart disease and healthy controls were detected using the Illumina Infinium MethylationEPIC BeadChip platform in this work. We employed Sangerbox technology and the GO and KEGG databases to further study the pathogenesis of coronary heart disease in postmenopausal women. After that, we used functional epigenetic module analysis and Cytoscape to remove the hub genes from the protein–protein interaction networks. Five genes (FOXA2, PTRD, CREB1, CTNAP2, and FBN2) were the hub genes. Lipid accumulation, endothelial cell failure, inflammatory responses, monocyte recruitment and aggregation, and other critical biological processes were all influenced by these genes. Finally, we employed methylation-specific PCR to demonstrate that FOXA2 was methylated at a high level in postmenopausal women with coronary heart disease. To better understand coronary heart disease in postmenopausal women's molecular mechanisms, our study examine the major factors contributing to the state of DNA methylation modification, which will help discover novel diagnostic tools and treatment options.

Target RNA expression omics approach to reveal the liver detoxification effect induced by Chinese medicine prescription Niu Huang Jie Du against realgar overexposure to mice

Ethnopharmacological relevanceNiu Huang Jie Du prescription (NHJD) is a traditional Chinese medicine (TCM) widely used in patients suffering from excessive inner fire toxin (Huo Du Nei Sheng) syndrome, such as sore throat, gingival swelling, and pain, mouth and tongue sores, etc. This formula contains realgar (As4S4) which is one of the 28 toxic medicinal materials promulgated by the Chinese Ministry of Health. Many studies reported its toxicity on the liver and kidney, and the detoxification effect of NHJD. However, its detoxification mechanism is still unclear. Aim of the studyTo clarify the detoxification mechanism of NHJD to realgar, this study evaluated the detoxification effect of NHJD on realgar exposure in mice, and analyzed differences in mRNA expression profiles in liver tissues and associated functional predictions. Material and methodsICR mice were administered with NHJD, realgar, and CMC-Na as blank control for 12 weeks, respectively. Liver injury was evaluated by histopathologic examination and liver mRNA gene were sequenced by Illumina. Differentially expressed gene, functionally enrichment and protein association network analysis were conducted. Results43 genes were screened out, among which 15 genes in the realgar group were decreased, but the extent of the decline has been restored in the NHJD group. The remaining 28 genes have exactly the opposite trends. Functional module analysis revealed that those detoxification function-related genes were primarily for positive regulation of glutathione metabolism, P450 on the metabolism of exogenous compounds, oxidative stress and immune-related, etc. ConclusionsThe results indicated that realgar mainly causes liver damage by changing the common enzymes of drug metabolism, especially the expression of genes related to CYPs, GSTs family, oxidative stress, and complement immunity, while the TCM prescription NHJD has a regulatory effect on the abnormal expression of corresponding genes. Our results will provide some clues for the detoxification mechanism of arsenic-containing TCM prescriptions.

A Pyroptosis-Related Signature Predicts Overall Survival and Immunotherapy Responses in Lung Adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is a highly malignant cancer with a bleak prognosis. Pyroptosis is crucial in LUAD. The present study investigated the prognostic value of a pyroptosis-related signature in LUAD. Methods: LUAD’s genomic data were downloaded from TCGA and GEO databases. K-means clustering was used to classify the data based on pyroptosis-related genes (PRGs). The features of tumor microenvironment were compared between the two subtypes. Differentially expressed genes (DEGs) were identified between the two subtypes, and functional enrichment and module analysis were carried out. LASSO Cox regression was used to build a prognostic model. Its prognostic value was assessed. Results: In LUAD, genetic and transcriptional changes in PRGs were found. A total of 30 PRGs were found to be differentially expressed in LUAD tissues. Based on PRGs, LUAD patients were divided into two subgroups. Subtype 1 has a higher overall survival rate than subtype 2. The tumor microenvironment characteristics of the two subtypes differed significantly. Compared to subtype 1, subtype 2 had strong immunological infiltration. Between the two groups, 719 DEGs were discovered. WGCNA used these DEGs to build a co-expression network. The network modules were analyzed. A prognostic model based on seven genes was developed, including FOSL1, KRT6A, GPR133, TMPRSS2, PRDM16, SFTPB, and SFTA3. The developed model was linked to overall survival and response to immunotherapy in patients with LUAD. Conclusion: In LUAD, a pyroptosis-related signature was developed to predict overall survival and treatment responses to immunotherapy.

Reconstruction and Exploratory Analysis of mTORC1 Signaling Pathway and Its Applications to Various Diseases Using Network-Based Approach.

Mammalian target of rapamycin (mTOR) is a serine-threonine kinase member of the cellular phosphatidylinositol 3-kinase (PI3K) pathway, which is involved in multiple biological functions by transcriptional and translational control. mTOR is a downstream mediator in the PI3K/Akt signaling pathway and plays a critical role in cell survival. In cancer, this pathway can be activated by membrane receptors, including the HER (or ErbB) family of growth factor receptors, the insulin-like growth factor receptor, and the estrogen receptor. In the present work, we congregated an electronic network of mTORC1 built on an assembly of data using natural language processing, consisting of 470 edges (activations/interactions and/or inhibitions) and 206 nodes representing genes/proteins, using the Cytoscape 3.6.0 editor and its plugins for analysis. The experimental design included the extraction of gene expression data related to five distinct types of cancers, namely, pancreatic ductal adenocarcinoma, hepatic cirrhosis, cervical cancer, glioblastoma, and anaplastic thyroid cancer from Gene Expression Omnibus (NCBI GEO) followed by pre-processing and normalization of the data using R & Bioconductor. ExprEssence plugin was used for network condensation to identify differentially expressed genes across the gene expression samples. Gene Ontology (GO) analysis was performed to find out the over-represented GO terms in the network. In addition, pathway enrichment and functional module analysis of the protein-protein interaction (PPI) network were also conducted. Our results indicated NOTCH1, NOTCH3, FLCN, SOD1, SOD2, NF1, and TLR4 as upregulated proteins in different cancer types highlighting their role in cancer progression. The MCODE analysis identified gene clusters for each cancer type with MYC, PCNA, PARP1, IDH1, FGF10, PTEN, and CCND1 as hub genes with high connectivity. MYC for cervical cancer, IDH1 for hepatic cirrhosis, MGMT for glioblastoma and CCND1 for anaplastic thyroid cancer were identified as genes with prognostic importance using survival analysis.

Uncovering the Pathogenesis of Orofacial Clefts Using Bioinformatics Analysis.

Many genes have been found to be associated with the occurrence of the orofacial clefts (OFC). The links between these pathogenic genes are rarely studied. In this study, bioinformatics analysis were performed in order to find associations between OFC- related genes and provide new ideas for etiology study of OFCs. Orofacial clefts-related genes were searched and identified from the Online Mendelian Inheritance of Man (OMIM.org). These genes were then analyzed by bioinformatics methods, including protein-protein interaction network, functional enrichment analysis, module analysis, and hub genes analysis. After searching the database of OMIM.org and removing duplicate results, 279 genes were finally obtained. These genes were involved to 369 pathways in biological process, 56 in cell component, 64 in molecular function, and 45 in the Kyoto Encyclopedia of Genes and Genomes. Most identified genes were significantly enriched in embryonic appendage morphogenesis (29.17%), embryonic limb morphogenesis (6.06%), and limb development (4.33%) for biological process ( Fig. 5A ); ciliary tip (42.86%), MKS complex (28.57%), ciliary basal body (14.29%), and ciliary membrane (14.29%) for cell component. The top 10 hub genes were identified, including SHH, GLI2, PTCH1, SMAD4, FGFR1, BMP4, SOX9, SOX2, RUNX2 , and CDH1. Bioinformatics methods were used to analyze OFC- related genes in this study, including hub gene identifying and analysis, protein - protein interaction network construction, and functional enrichment analysis. Several potential mechanisms related to occurrence of OFCs were also discussed. These results may be helpful for further studies of the etiology of OFC.

Construction of a Support Vector Machine-Based Classifier for Pulmonary Arterial Hypertension Patients.

Pulmonary arterial hypertension (PAH) is a disease leading to right heart failure and death due to increased pulmonary arterial tension and vascular resistance. So far, PAH has not been fully understood, and current treatments are much limited. Gene expression profiles of healthy people and PAH patients in GSE33463 dataset were analyzed in this study. Then 110 differentially expressed genes (DEGs) were obtained. Afterward, the PPI network based on DEGs was constructed, followed by the analysis of functional modules, whose results showed that the genes in the major function modules significantly enriched in immune-related functions. Moreover, four optimal feature genes were screened from the DEGs by support vector machine–recursive feature elimination (SVM-RFE) algorithm (EPB42, IFIT2, FOSB, and SNF1LK). The receiver operating characteristic curve showed that the SVM classifier based on optimal feature genes could effectively distinguish healthy people from PAH patients. Last, the expression of optimal feature genes was analyzed in the GSE33463 dataset and clinical samples. It was found that EPB42 and IFIT2 were highly expressed in PAH patients, while FOSB and SNF1LK were lowly expressed. In conclusion, the four optimal feature genes screened here are potential biomarkers for PAH and are expected to be used in early diagnosis for PAH.

Condition-Specific Molecular Network Analysis Revealed That Flagellar Proteins Are Involved in Electron Transfer Processes of Shewanella piezotolerans WP3.

Because of the ability to metabolize a large number of electron acceptors such as nitrate, nitrite, fumarate, and metal oxides, Shewanella species have attracted much attention in recent years. Generally, the use of these electron acceptors is mainly achieved through electron transfer proteins and their interactions which will dynamically change across different environmental conditions in cells. Therefore, functional analysis of condition-specific molecular networks can reveal biological information on electron transfer processes. By integrating expression data and molecular networks, we constructed condition-specific molecular networks for Shewanella piezotolerans WP3. We then identified condition-specific key genes and studied their potential functions with an emphasis on their roles in electron transfer processes. Functional module analysis showed that different flagellar assembly modules appeared under these conditions and suggested that flagellar proteins are important for these conditions. We also identified the electron transfer modules underlying these various environmental conditions. The present results could help with screening electron transfer genes and understanding electron transfer processes under various environmental conditions for the Shewanella species.

Genome-wide DNA methylation profiling and gut flora analysis in intestinal polyps patients.

The intestinal polyp is the precancerous lesion of colorectal cancer. DNA methylation and intestinal microbiota may play an important role in the development of intestinal polyp. In this study, we included 10 patients with intestinal polyps who received the colonoscopy examination. We applied the Illumina Human Methylation 850K array to investigate the epigenome-wide DNA methylation patterns. Then, we filtered out the hub genes in the protein-protein interaction networks using functional epigenetic modules analysis. We also analyzed the colonizing bacteria on the surface of polyps compared with those in normal colonic mucosal epithelium with 16S ribosomal DNA sequencing. We identified 323 hypermethylated sites and 7992 hypomethylated sites between intestinal polyps and normal samples. Five hub genes, including CREB1, LPA, SVIL and KRT18, were identified in five modules. Hypomethylation of CREB1 is a candidate marker of colorectal adenoma. Gut microbiota analysis showed that Butyricicoccus was significantly decreased in the intestinal polyp groups. In conclusion, we identified DNA methylation disparities in intestinal polyps compared with normal tissue, of which methylation of CREB1 may hold clinical significance in colorectal cancer progress. Colonizing bacteria in the colonic epithelium might be related to the formation of intestinal polyps.

IRIS-FGM: an integrative single-cell RNA-Seq interpretation system for functional gene module analysis.

Single-cell RNA-Seq (scRNA-Seq) data is useful in discovering cell heterogeneity and signature genes in specific cell populations in cancer and other complex diseases. Specifically, the investigation of condition-specific functional gene modules (FGM) can help to understand interactive gene networks and complex biological processes in different cell clusters. QUBIC2 is recognized as one of the most efficient and effective biclustering tools for condition-specific FGM identification from scRNA-Seq data. However, its limited availability to a C implementation restricted its application to only a few downstream analysis functionalities. We developed an R package named IRIS-FGM (Integrative scRNA-Seq Interpretation System for Functional Gene Module analysis) to support the investigation of FGMs and cell clustering using scRNA-Seq data. Empowered by QUBIC2, IRIS-FGM can effectively identify condition-specific FGMs, predict cell types/clusters, uncover differentially expressed genes and perform pathway enrichment analysis. It is noteworthy that IRIS-FGM can also take Seurat objects as input, facilitating easy integration with the existing analysis pipeline. IRIS-FGM is implemented in the R environment (as of version 3.6) with the source code freely available at https://github.com/BMEngineeR/IRISFGM. Supplementary data are available at Bioinformatics online.

Epigenomic Profiles of African-American Transthyretin Val122Ile Carriers Reveals Putatively Dysregulated Amyloid Mechanisms.

The Val122Ile mutation in Transthyretin (TTR) gene causes a rare, difficult to diagnose hereditary form of cardiac amyloidosis. This mutation is most common in the United States and mainly present in people of African descent. The carriers have an increased risk of congestive heart failure, peripheral edema, and several other noncardiac phenotypes such as carpal tunnel syndrome, and arthroplasty which are top reasons for ambulatory/outpatient surgeries (OSs) in the country. We conducted first-ever epigenome-wide association study using the Illumina's EPIC array, in Val122Ile carriers of African descent for heart disease and multiple OSs-an early disease indicator. Differential methylation across genome wide cytosine-phosphate guanine (CpG) sites was tested between carriers with and without heart disease and OS. Significant CpG sites were investigated for cis-mQTLs loci, followed by gene ontology and protein-protein interaction network. We also investigated the significant CpG sites in a secondary cohort of carriers for replication. Five differentially methylated sites (P≤2.1×10-8) in genes-FAM129B, SKI, WDR27, GLS, and an intergenic site near RP11-550A5.2, and one differentially methylated region containing KCNA6 and GALNT3 (P=1.1×10-12) were associated with heart disease. For OS, we observe 4 sites-2 sites in UBE2E3 and SEC14L5, and other 2 in intergenic regions (P≤1.8×10-7) and 3 regions overlapping SH3D21, EVA1B, LTB4R2, and CIDEB (P≤3.9×10-7). Functional protein-interaction module analysis identified ABCA1 (P=0.001) for heart disease. Six cis-mQTLs were associated with one of the significant CpG sites (FAM129B; P=4.1×10-24). We replicated 2 CpG sites (cg18546846 and cg06641417; P<0.05) in an external cohort of biopsy-confirmed cases of TTR (transthyretin) amyloidosis. The genes identified are involved in transport and clearance of amyloid deposits (GLS, ABCA1, FAM129B); cardiac fibrosis (SKI); and muscle tissue regulation (SKI, FAM129B). These findings highlight the link between a complex amyloid circuit and diverse symptoms of Val122Ile.