Exploring Shared Pathogenesis of Alzheimer's Disease and Type 2 Diabetes Mellitus via Co-expression Networks Analysis

RNA-Seq transcriptome profiling of Nile rat livers reveals novel insights on the anti-diabetic mechanisms of Water-Soluble Palm Fruit Extract

Water-Soluble Palm Fruit Extract (WSPFE) has been shown to confer anti-diabetic effects in the Nile rat (NR) (Arvicanthis niloticus). Liquid and powder WSPFE both deterred diabetes onset in NRs fed a high-carbohydrate (hiCHO) diet, but the liquid form provided better protection. In this study, NRs were fed either a hiCHO diet or the same diet added with liquid or powder WSPFE. Following feeding of the diets for 8 weeks, random blood glucose levels were measured to categorize NRs as either diabetes-resistant or diabetes-susceptible, based on a cut-off value of 75 mg/dL. Livers were then obtained for Illumina HiSeq 4000 paired end RNA-sequencing (RNA-Seq) and the data were mapped to the reference genome. Consistent with physiological and biochemical parameters, the gene expression data obtained indicated that WSPFE was associated with protection against diabetes. Among hepatic genes upregulated by WSPFE versus controls, were genes related to insulin-like growth factor binding protein, leptin receptor, and processes of hepatic metabolism maintenance, while those downregulated were related to antigen binding, immunoglobulin receptor, inflammation- and cancer-related processes. WSPFE supplementation thus helped inhibit diabetes progression in NRs by increasing insulin sensitivity and reducing both the inflammatory effects of a hiCHO diet and the related DNA-damage compensatory mechanisms contributing to liver disease progression. In addition, the genetic permissiveness of susceptible NRs to develop diabetes was potentially associated with dysregulated compensatory mechanisms involving insulin signaling and oxidative stress over time. Further studies on other NR organs associated with diabetes and its complications are warranted.

Uncovering the shared neuro-immune-related regulatory mechanisms between spinal cord injury and osteoarthritis

Adults with spinal cord injury (SCI), a destructive neurological injury, have a significantly higher incidence of osteoarthritis (OA), a highly prevalent chronic joint disorder. This study aimed to dissect the neuroimmune-related regulatory mechanisms of SCI and OA using bioinformatics analysis. Using microarray data from the Gene Expression Omnibus database, differentially expressed genes (DEGs) were screened between SCI and sham samples and between OA and control samples. Common DEGs were used to construct a protein-protein interaction (PPI) network. Weighted gene co-expression network analysis (WGCNA) was used to mine SCI- and OA-related modules. Shared miRNAs were identified, and target genes were predicted using the Human MicroRNA Disease Database (HMDD) database. A miRNA-gene-pathway regulatory network was constructed with overlapping genes, miRNAs, and significantly enriched pathways. Finally, the expression of the identified genes and miRNAs was verified using RT-qPCR. In both the SCI and OA groups, 185 common DEGs were identified, and three hub clusters were obtained from the PPI network. WGCNA revealed three SCI-related modules and two OA-related modules. There were 43 overlapping genes between the PPI network clusters and the WGCNA network modules. Seventeen miRNAs shared between patients with SCI and OA were identified. A regulatory network consisting of five genes, six miRNAs, and six signaling pathways was constructed. Upregulation of CD44, TGFBR1, CCR5, and IGF1, while lower levels of miR-125b-5p, miR-130a-3p, miR-16-5p, miR-204-5p, and miR-204-3p in both SCI and OA were successfully verified using RT-qPCR. Our study suggests that a miRNA-gene-pathway network is implicated in the neuroimmune-related regulatory mechanisms of SCI and OA. CD44, TGFBR1, CCR5, and IGF1, and their related miRNAs (miR-125b-5p, miR-130a-3p, miR-16-5p, miR-204-5p, and miR-204-3p) may serve as promising biomarkers and candidate therapeutic targets for SCI and OA.

Identification of key mRNAs and signaling pathways in obsessive compulsive disorder based on weighted gene co-expression network analysis and cytoHubba plugin

PURPOSE

Obsessive-compulsive disorder (OCD) is a complex psychiatric disorder. Genetic and broad environmental factors are common risk factors for OCD. The purpose of this study is to explore the molecular mechanism of OCD and to find new molecular targets for the diagnosis and management of OCD.

METHODS

All data were downloaded from public dataset. Key modules and candidate key mRNAs were identified based on weighted gene co-expression network analysis (WGCNA). The "limma" R package was used for differential expression analysis of mRNAs. Subsequently, functional enrichment analysis of differentially expressed mRNAs (DEmRNAs) was also carried out. In addition, a diagnostic model was constructed. Finally, the infiltration level of immune cells in OCD and its correlation with multicentric key DEmRNAs were analyzed.

RESULTS

Green and red modules were selected as the hub modules. A total of 447 mRNAs were considered candidate key mRNAs according to GS > 0.2 and MM > 0.3. A total of 26 DEmRNAs in the same direction were identified in the GSE60190 and GSE78104 datasets. A total of 26 DEmRNAs were intersected with candidate key mRNAs in WGCNA to obtain 10 intersection DEmRNAs (HSPB1, ITPK1, CBX7, PPP1R10, TAOK1, PISD, MKNK2, RWDD1, PPA1, and RELN). However, only four DEmRNAs (HSPB1, TAOK1, MKNK2, and PPA1) predicted related drugs. Subsequently, receiver operating characteristic analysis shows that the diagnostic model has high diagnostic value. Moreover, six multicentric key DEmRNAs (SNRPF, SNRNP70, PRPF8, NOP56, EPRS, and CCT2) were screened by UpSet package. Finally, six multicentric key DEmRNAs were found to be associated with immune cells.

CONCLUSION

The key molecules obtained in this study lay a foundation for further research on the molecular mechanism of OCD.

A review and analysis of key biomarkers in Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects over 50 million elderly individuals worldwide. Although the pathogenesis of AD is not fully understood, based on current research, researchers are able to identify potential biomarker genes and proteins that may serve as effective targets against AD. This article aims to present a comprehensive overview of recent advances in AD biomarker identification, with highlights on the use of various algorithms, the exploration of relevant biological processes, and the investigation of shared biomarkers with co-occurring diseases. Additionally, this article includes a statistical analysis of key genes reported in the research literature, and identifies the intersection with AD-related gene sets from databases such as AlzGen, GeneCard, and DisGeNet. For these gene sets, besides enrichment analysis, protein-protein interaction (PPI) networks utilized to identify central genes among the overlapping genes. Enrichment analysis, protein interaction network analysis, and tissue-specific connectedness analysis based on GTEx database performed on multiple groups of overlapping genes. Our work has laid the foundation for a better understanding of the molecular mechanisms of AD and more accurate identification of key AD markers.

Tauroursodeoxycholic acid: a bile acid that may be used for the prevention and treatment of Alzheimer's disease

Alzheimer's disease (AD) is a prevalent neurodegenerative disease that has become one of the main factors affecting human health. It has serious impacts on individuals, families, and society. With the development of population aging, the incidence of AD will further increase worldwide. Emerging evidence suggests that many physiological metabolic processes, such as lipid metabolism, are implicated in the pathogenesis of AD. Bile acids, as the main undertakers of lipid metabolism, play an important role in the occurrence and development of Alzheimer's disease. Tauroursodeoxycholic acid, an endogenous bile acid, has been proven to possess therapeutic effects in different neurodegenerative diseases, including Alzheimer's disease. This review tries to find the relationship between bile acid metabolism and AD, as well as explore the therapeutic potential of bile acid taurocursodeoxycholic acid for this disease. The potential mechanisms of taurocursodeoxycholic acid may include reducing the deposition of Amyloid-β protein, regulating apoptotic pathways, preventing tau hyperphosphorylation and aggregation, protecting neuronal synapses, exhibiting anti-inflammatory properties, and improving metabolic disorders. The objective of this study is to shed light on the use of tauroursodeoxycholic acid preparations in the prevention and treatment of AD, with the aim of identifying effective treatment targets and clarifying various treatment mechanisms involved in this disease.

The CEBPA-FGF21 regulatory network may participate in the T2DM-induced skeletal muscle atrophy by regulating the autophagy-lysosomal pathway

AIMS

Recent years have witnessed an increasing research interest in the roles of transcription factor (TF)-gene regulatory network in type 2 diabetes mellitus (T2DM). Thus, we sought to characterize the mechanistic insights based on the TF-gene regulatory network in skeletal muscle atrophy in T2DM.

METHODS

Differentially expressed TFs (DETFs) and mRNAs (DEmRNAs) were obtained in T2DM-related gene expression profiles (GSE12643, GSE55650, GSE166502, and GSE29221), followed by WGCNA, and GO and KEGG enrichment analyses. Next, the iRegulon plug-in unit of Cytoscape software was used to construct a TF-mRNA regulatory network. Besides, RT-qPCR and ChIP-seq were utilized to measure the expression of CEBPA and FGF21 in the skeletal muscle tissues or cells of T2DM rat models. At last, the effect of overexpression of FGF21 on the autophagy-lysosomal pathway was examined in skeletal muscle cells of T2DM rats.

RESULTS

Totally, 12 DETFs and 102 DEmRNAs were found in the skeletal muscle tissues of T2DM samples. The DEmRNAs were mainly enriched in the autophagy-lysosomal pathway. CEBPA affected the skeletal muscle atrophy in T2DM by regulating 5 target genes via the autophagy-lysosomal pathway. CEBPA could target FGF21. In addition, the expression of CEBPA was elevated, while the expression of FGF21 was diminished in the skeletal muscle tissues or cells of T2DM rats. The CEBPA-FGF21 regulatory network promoted skeletal muscle atrophy in T2DM by activating the autophagy-lysosomal pathway.

CONCLUSION

The CEBPA-FGF21 regulatory network may participate in the T2DM-induced skeletal muscle atrophy by regulating the autophagy-lysosomal pathway. Thus, our study provides interesting targets for prevention of skeletal muscle atrophy in T2DM.

Exploration of the potential common pathogenic mechanisms in COVID-19 and silicosis by using bioinformatics and system biology

Silicosis is an occupational lung disease that is common worldwide. In recent years, coronavirus disease 2019 (COVID-19) has provided daunting challenges to public healthcare systems globally. Although multiple studies have shown a close link between COVID-19 and other respiratory diseases, the inter-relational mechanisms between COVID-19 and silicosis remain unclear. This study aimed to explore the shared molecular mechanisms and drug targets of COVID-19 and silicosis. Gene expression profiling identified four modules that were most closely associated with both diseases. Furthermore, we performed functional analysis and constructed a protein-protein interaction network. Seven hub genes (budding uninhibited by benzimidazoles 1 [BUB1], protein regulator of cytokinesis 1 [PRC1], kinesin family member C1 [KIFC1], ribonucleotide reductase regulatory subunit M2 [RRM2], cyclin-dependent kinase inhibitor 3 [CDKN3], Cyclin B2 [CCNB2], and minichromosome maintenance complex component 6 [MCM6]) were involved in the interaction between COVID-19 and silicosis. We investigated how diverse microRNAs and transcription factors regulate these seven genes. Subsequently, the correlation between the hub genes and infiltrating immune cells was explored. Further in-depth analyses were performed based on single-cell transcriptomic data from COVID-19, and the expression of hub-shared genes was characterized and located in multiple cell clusters. Finally, molecular docking results reveal small molecular compounds that may improve COVID-19 and silicosis. The current study reveals the common pathogenesis of COVID-19 and silicosis, which may provide a novel reference for further research.

Identification of key biomarkers associated with immune cells infiltration for myocardial injury in dermatomyositis by integrated bioinformatics analysis

BACKGROUND

Dermatomyositis (DM) is an acquired autoimmune disease that can cause damage to various organs, including the heart muscle. However, the mechanisms underlying myocardial injury in DM are not yet fully understood.

METHODS

In this study, we utilized publicly available datasets from the Gene Expression Omnibus (GEO) database to identify hub-genes that are enriched in the immune system process in DM and myocarditis. Weighted gene co-expression network analysis (WGCNA), differentially expressed genes (DEGs) analysis, protein-protein interaction (PPI), and gene ontology (GO) analysis were employed to identify these hub-genes. We then used the CIBERSORT method to analyze immune cell infiltration in skeletal muscle specimens of DM and myocardium specimens of myocarditis respectively. Correlation analysis was performed to investigate the relationship between key genes and infiltrating immune cells. Finally, we predicted regulatory miRNAs of hub-genes through miRNet and validated their expression in online datasets and clinical samples.

RESULTS

Using integrated bioinformatics analysis, we identified 10 and 5 hub-genes that were enriched in the immune system process in the database of DM and myocarditis respectively. The subsequent intersections between hub-genes were IFIT3, OAS3, ISG15, and RSAD2. We found M2 macrophages increased in DM and myocarditis compared to the healthy control, associating with the expression of IFIT3, OAS3, ISG15, and RSAD2 in DM and myocarditis positively. Gene function enrichment analysis (GSEA) showed that IFIT3, OAS3, ISG15, and RSAD2 were mainly enriched in type I interferon (IFN) signaling pathway, cellular response to type I interferon, and response to type I interferon. Finally, we verified that the expression of miR-146a-5p was significantly higher in the DM with myocardial injury than those without myocardial injury (p = 0.0009).

CONCLUSION

Our findings suggest that IFIT3, OAS3, ISG15, and RSAD2 may play crucial roles in the underlying mechanism of myocardial injury in DM. Serum miR-146a-5p could be a potential biomarker for myocardial injury in DM.

A draft conceptual model of SLC6A1 neurodevelopmental disorder

Introduction

SLC6A1 Neurodevelopmental Disorder (SLC6A1-NDD), first described in 2015, is a rare syndrome caused by a mutation in the SLC6A1 gene which encodes for the GABA Transporter 1 (GAT-1) protein. Epilepsy is one of the most common symptoms in patients and is often the primary treatment target, though the severity of epilepsy is variable. The impact of seizures and other symptoms of SLC6A1-NDD on patients and caregivers is wide-ranging and has not been described in a formal disease concept study.

Methods

A literature search was performed using the simple search term, "SLC6A1." Papers published before 2015, and those which did not describe the human neurodevelopmental disorder were removed from analysis. Open-ended interviews on lived experiences were conducted with two patient advocate key opinion leaders. An analysis of de-identified conversations between families of people with SLC6A1-NDD on social media was performed to quantify topics of concern.

Results

Published literature described symptoms in all of the following domains: neurological, visual, motor, cognitive, communication, behavior, gastrointestinal, sleep, musculo-skeletal, and emotional in addition to epilepsy. Key opinion leaders noted two unpublished features: altered hand use in infants, and developmental regression with onset of epilepsy. Analysis of social media interactions confirmed that the core symptoms of epilepsy and autistic traits were prominent concerns, but also demonstrated that other symptoms have a large impact on family life.

Discussion

For rare diseases, analysis of published literature is important, but may not be as comprehensive as that which can be gleaned from spontaneous interactions between families and through qualitative interviews. This report reflects our current understanding of the lived experience of SLC6A1-NDD. The discrepancy between the domains of disease reported in the literature and those discussed in patient conversations suggests that a formal qualitative interview-based disease concept study of SLC6A1-NDD is warranted.

Exploring the common pathogenesis of Alzheimer's disease and type 2 diabetes mellitus via microarray data analysis

Background

Alzheimer's Disease (AD) and Type 2 Diabetes Mellitus (DM) have an increased incidence in modern society. Although more and more evidence has supported that DM is prone to AD, the interrelational mechanisms remain fully elucidated.

Purpose

The primary purpose of this study is to explore the shared pathophysiological mechanisms of AD and DM.

Methods

Download the expression matrix of AD and DM from the Gene Expression Omnibus (GEO) database with sequence numbers GSE97760 and GSE95849, respectively. The common differentially expressed genes (DEGs) were identified by limma package analysis. Then we analyzed the six kinds of module analysis: gene functional annotation, protein-protein interaction (PPI) network, potential drug screening, immune cell infiltration, hub genes identification and validation, and prediction of transcription factors (TFs).

Results

The subsequent analyses included 339 common DEGs, and the importance of immunity, hormone, cytokines, neurotransmitters, and insulin in these diseases was underscored by functional analysis. In addition, serotonergic synapse, ovarian steroidogenesis, estrogen signaling pathway, and regulation of lipolysis are closely related to both. DEGs were input into the CMap database to screen small molecule compounds with the potential to reverse AD and DM pathological functions. L-690488, exemestane, and BMS-345541 ranked top three among the screened small molecule compounds. Finally, 10 essential hub genes were identified using cytoHubba, including PTGS2, RAB10, LRRK2, SOS1, EEA1, NF1, RAB14, ADCY5, RAPGEF3, and PRKACG. For the characteristic Aβ and Tau pathology of AD, RAPGEF3 was associated significantly positively with AD and NF1 significantly negatively with AD. In addition, we also found ADCY5 and NF1 significant correlations with DM phenotypes. Other datasets verified that NF1, RAB14, ADCY5, and RAPGEF3 could be used as key markers of DM complicated with AD. Meanwhile, the immune cell infiltration score reflects the different cellular immune microenvironments of the two diseases.

Conclusion

The common pathogenesis of AD and DM was revealed in our research. These common pathways and hub genes directions for further exploration of the pathogenesis or treatment of these two diseases.

Application and prospect of quasi-targeted metabolomics in age-related hearing loss

Age-related hearing loss (ARHL) is a common sensory deficit in the elderly, which seriously affects physical and mental health. Therefore, understanding its underlying molecular mechanisms and taking interventions to treat ARHL are urgently needed. In our study, cochlea of 4-week-old C57BL/6 mice as the Youth group (n = 6) and 48-week-old cochlea as the Old group (n = 6) were subjected to quasi-targeted metabolomics analysis by Ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). In total, 208 differential metabolites were identified in 12 cochlea samples, which highlighted the following discriminant compounds: tryptophan, piperidine, methionine, L-arginine, histamine, serotonin, acetylcholine, and 4-aminobutyric acid. Differentially expressed metabolites were identified which were involved in KEGG pathways related to the digestion and absorption of oxidative stress associated amino acids, Synaptic vesicle cycle of serotonin, Pantothenate and CoA Biosynthesis. These findings are a first step toward elucidating the pathophysiological pathways involved in the etiology of ARHL and provide the possibility to further explore the mechanisms of ARHL using metabolomic analysis.

Identification of genetic molecular markers and immune infiltration characteristics of Alzheimer's disease through weighted gene co-expression network analysis

Background

Alzheimer's disease (AD) is a progressive neurodegenerative disease that leads to cognitive impairment and memory loss. Currently, the pathogenesis and underlying causative genes of AD remain unclear, and there exists no effective treatment for this disease. This study explored AD-related diagnostic and therapeutic biomarkers from the perspective of immune infiltration by analyzing public data from the NCBI Gene Expression Omnibus database.

Method

In this study, weighted gene co-expression network analysis (WGCNA) was conducted to identify modules and hub genes contributing to AD development. A protein–protein interaction network was constructed when the genes in the modules were enriched and examined by Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Furthermore, a gene network was established using topological WGCNA, from which five hub genes were selected. Logistic regression analysis and receiver operating characteristic curve analysis were performed to explore the clinical value of genes in AD diagnosis. The genes in the core module intersected with the hub genes, and four intersection genes (ATP2A2, ATP6V1D, CAP2, and SYNJ1) were selected. These four genes were enriched by gene set enrichment analysis (GSEA). Finally, an immune infiltration analysis was performed.

Results

The GO/KEGG analysis suggested that genes in the core module played a role in the differentiation and growth of neural cells and in the transmission of neurotransmitters. The GSEA of core genes showed that these four genes were mainly enriched in immune/infection pathways (e.g., cholera infection and Helicobacter pylori infection pathways) and other metabolic pathways. An investigation of immune infiltration characteristics revealed that activated mast cells, regulatory T cells, plasma cells, neutrophils, T follicular helper cells, CD8 T cells, resting memory CD4 T cells, and M1 macrophages were the core immune cells contributing to AD progression. qRT-PCR analysis showed that the ATP6V1D is upregulated in AD.

Conclusion

The results of enrichment and immuno-osmotic analyses indicated that immune pathways and immune cells played an important role in the occurrence and development of AD. The selected key genes were used as biomarkers related to the pathogenesis of AD to further explore the pathways and cells, which provided new perspectives on therapeutic targets in AD.

Exploration of Shared Gene Signatures and Molecular Mechanisms Between Periodontitis and Nonalcoholic Fatty Liver Disease

Background: Periodontitis is associated with periodontal tissue damage and teeth loss. Nonalcoholic fatty liver disease (NAFLD) has an intimate relationship with periodontitis. Nevertheless, interacted mechanisms between them have not been clear. This study was intended for the exploration of shared gene signatures and latent therapeutic targets in periodontitis and NAFLD.

Methods: Microarray datasets of periodontitis and NAFLD were obtained from the Gene Expression Omnibus (GEO) database. The weighted gene co-expression network analysis (WGCNA) was utilized for the acquisition of modules bound up with NAFLD and periodontitis. We used ClueGO to carry out biological analysis on shared genes to search their latent effects in NAFLD and periodontitis. Another cohort composed of differential gene analysis verified the results. The common microRNAs (miRNAs) in NAFLD and periodontitis were acquired in the light of the Human microRNA Disease Database (HMDD). According to miRTarbase, miRDB, and Targetscan databases, latent target genes of miRNAs were forecasted. Finally, the miRNAs–mRNAs network was designed.

Results: Significant modules with periodontitis and NAFLD were obtained via WGCNA. GO enrichment analysis with GlueGo indicated that damaged migration of dendritic cells (DCs) might be a common pathophysiologic feature of NAFLD and periodontitis. In addition, we revealed common genes in NAFLD and periodontitis, including IGK, IGLJ3, IGHM, MME, SELL, ENPP2, VCAN, LCP1, IGHD, FCGR2C, ALOX5AP, IGJ, MMP9, FABP4, IL32, HBB, FMO1, ALPK2, PLA2G7, MNDA, HLA-DRA, and SLC16A7. The results of differential analysis in another cohort were highly accordant with the findings of WGCNA. We established a comorbidity model to explain the underlying mechanism of NAFLD secondary to periodontitis. Finally, the analysis of miRNA pointed out that hsa-mir-125b-5p, hsa-mir-17-5p, and hsa-mir-21-5p might provide potential therapeutic targets.

Conclusion: Our study initially established a comorbidity model to explain the underlying mechanism of NAFLD secondary to periodontitis, found that damaged migration of DCs might be a common pathophysiological feature of NAFLD and periodontitis, and provided potential therapeutic targets.

Establishment and Verification of a Gene Signature for Diagnosing Type 2 Diabetics by WGCNA, LASSO Analysis, and In Vitro Experiments

Objective

The incidence and prevalence of type 2 diabetes are increasing with age. Nevertheless, there is lack of sensitive diagnostic tools and effective therapeutic regimens. We aimed to establish and verify a practical and valid diagnostic tool for this disease.

Methods

WGCNA was presented on the expression profiling of type 2 diabetic and normal islets in combined GSE25724 and GSE38642 datasets. By LASSO Cox regression analyses, a gene signature was constructed based on the genes in diabetes-related modules. ROC curves were plotted for assessing the diagnostic efficacy. Correlations between the genes and immune cell infiltration and pathways were analyzed. BST2 and BTBD1 expression was verified in glucotoxicity-induced and normal islet β cells. The influence of BST2 on β cell dysfunction was investigated under si-BST2 transfection.

Results

Totally, 14 coexpression modules were constructed, and red and cyan modules displayed the correlations to diabetes. The LASSO gene signature (BST2, BTBD1, IFIT1, IFIT3, and RTP4) was developed. The AUCs in the combined datasets and GSE20966 dataset were separately 0.914 and 0.910, confirming the excellent performance in diagnosing type 2 diabetes. Each gene in the model was distinctly correlated to immune cell infiltration and key signaling pathways (TGF-β and P53, etc.). The abnormal expression of BST2 and BTBD1 was confirmed in glucotoxicity-induced β cells. BST2 knockdown ameliorated β cell dysfunction and altered the activation of TGF-β and P53 pathways.

Conclusion

Our findings propose a gene signature with high efficacy to diagnose type 2 diabetes, which could assist and improve early diagnosis and therapy.

Circadian rhythms in neurodegenerative disorders

Endogenous biological clocks, orchestrated by the suprachiasmatic nucleus, time the circadian rhythms that synchronize physiological and behavioural functions in humans. The circadian system influences most physiological processes, including sleep, alertness and cognitive performance. Disruption of circadian homeostasis has deleterious effects on human health. Neurodegenerative disorders involve a wide range of symptoms, many of which exhibit diurnal variations in frequency and intensity. These disorders also disrupt circadian homeostasis, which in turn has negative effects on symptoms and quality of life. Emerging evidence points to a bidirectional relationship between circadian homeostasis and neurodegeneration, suggesting that circadian function might have an important role in the progression of neurodegenerative disorders. Therefore, the circadian system has become an attractive target for research and clinical care innovations. Studying circadian disruption in neurodegenerative disorders could expand our understanding of the pathophysiology of neurodegeneration and facilitate the development of novel, circadian-based interventions for these disabling disorders. In this Review, we discuss the alterations to the circadian system that occur in movement (Parkinson disease and Huntington disease) and cognitive (Alzheimer disease and frontotemporal dementia) neurodegenerative disorders and provide directions for future investigations in this field.

Key Common Genes in Obstructive Sleep Apnea and Lung Cancer are Associated with Prognosis of Lung Cancer Patients

Background

Obstructive sleep apnea (OSA) is associated with an increased risk of lung cancer. This study aimed to identify key common genes in OSA and lung cancer and explore their prognostic value in lung cancer.

Materials and Methods

Transcriptome data of OSA and lung cancer were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database, respectively. Genes associated with OSA and lung cancer were screened by weighted gene co-expression network analysis (WGCNA). Univariate and multivariate Cox regression algorithms were applied to identify key genes and construct the risk score model. Receiver operating characteristic (ROC) curves and a nomogram were performed to evaluate the prognostic value of the risk score. The screened key genes and their roles in prognosis were validated by GEO (GSE30219) analysis.

Results

A total of 104 common genes were screened in OSA and lung cancer by WGCNA. Modulator of apoptosis 1 (MOAP1), chromobox 7 (CBX7), platelet-derived growth factor subunit B (PDGFB), and mitogen-activated protein kinase 3 (MAP2K3) were identified as key genes by univariate and then multivariate Cox regression analyses. The risk score model was constructed on the basis of four gene signatures. ROC curves and the nomogram showed that the risk score had a high accuracy in predicting the survival of patients with lung cancer. In addition, the result of multivariate Cox regression analysis indicated that the risk score was an independent prognostic factor in lung cancer.

Conclusion

This study constructed a unique model for predicting the prognosis of lung cancer patients on the basis of four genes common to OSA and lung cancer. These genes may also serve as candidate genes to improve our knowledge about the underlying mechanism of OSA that leads to an increased risk of lung cancer at the genetic level.

Shared Molecular Mechanisms of Hypertrophic Cardiomyopathy and Its Clinical Presentations: Automated Molecular Mechanisms Extraction Approach

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiovascular disease with a prevalence of 1 in 500 people and varying clinical presentations. Although there is much research on HCM, underlying molecular mechanisms are poorly understood, and research on the molecular mechanisms of its specific clinical presentations is scarce. Our aim was to explore the molecular mechanisms shared by HCM and its clinical presentations through the automated extraction of molecular mechanisms. Molecular mechanisms were congregated by a query of the INDRA database, which aggregates knowledge from pathway databases and combines it with molecular mechanisms extracted from abstracts and open-access full articles by multiple machine-reading systems. The molecular mechanisms were extracted from 230,072 articles on HCM and 19 HCM clinical presentations, and their intersections were found. Shared molecular mechanisms of HCM and its clinical presentations were represented as networks; the most important elements in the intersections’ networks were found, centrality scores for each element of each network calculated, networks with reduced level of noise generated, and cooperatively working elements detected in each intersection network. The identified shared molecular mechanisms represent possible mechanisms underlying different HCM clinical presentations. Applied methodology produced results consistent with the information in the scientific literature.

Stratification of Type 2 Diabetes by Age of Diagnosis in the UK Biobank Reveals Subgroup-Specific Genetic Associations and Causal Risk Profiles

The pathogenesis of type 2 diabetes (T2D) might change with increasing age. Here, we used a stratification based on age of diagnosis to gain insight into the genetics and causal risk factors of T2D across different age-groups. We performed genome-wide association studies (GWAS) on T2D and T2D subgroups based on age of diagnosis (<50, 50-60, 60-70, and >70 years) (total of 24,986 cases). As control subjects, participants were at least 70 years of age at the end of follow-up without developing T2D (N =187,130). GWAS identified 208 independent lead single nucleotide polymorphism (SNPs) mapping to 69 loci associated with T2D (P < 1.0e-8). Among others, SNPs mapped to CDKN2B-AS1 and multiple independent SNPs mapped to TCF7L2 were more strongly associated with cases diagnosed after age 70 years than with cases diagnosed before age 50 years. Based on the different case groups, we performed two-sample Mendelian randomization. Most notably, we observed that of the investigated risk factors, the association between BMI and T2D attenuated with increasing age of diagnosis. Collectively, our results indicate that stratification of T2D based on age of diag-nosis reveals subgroup-specific genetics and causal determinants, supporting the hypothesis that the pathogenesis of T2D changes with increasing age.

Exploration of the Shared Gene Signatures and Molecular Mechanisms Between Systemic Lupus Erythematosus and Pulmonary Arterial Hypertension: Evidence From Transcriptome Data

Background

Systemic lupus erythematosus (SLE) is an autoimmune disease that can affect multiple systems. Pulmonary arterial hypertension (PAH) has a close linkage with SLE. However, the inter-relational mechanisms between them are still unclear. This article aimed to explore the shared gene signatures and potential molecular mechanisms in SLE and PAH.

Methods

The microarray data of SLE and PAH in the Gene Expression Omnibus (GEO) database were downloaded. The Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify the co-expression modules related to SLE and PAH. The shared genes existing in the SLE and PAH were performed an enrichment analysis by ClueGO software, and their unique genes were also performed with biological processes analyses using the DAVID website. The results were validated in another cohort by differential gene analysis. Moreover, the common microRNAs (miRNAs) in SLE and PAH were obtained from the Human microRNA Disease Database (HMDD) and the target genes of whom were predicted through the miRTarbase. Finally, we constructed the common miRNAs–mRNAs network with the overlapped genes in target and shared genes.

Results

Using WGCNA, four modules and one module were identified as the significant modules with SLE and PAH, respectively. A ClueGO enrichment analysis of shared genes reported that highly activated type I IFN response was a common feature in the pathophysiology of SLE and PAH. The results of differential analysis in another cohort were extremely similar to them. We also proposed a disease road model for the possible mechanism of PAH secondary to SLE according to the shared and unique gene signatures in SLE and PAH. The miRNA–mRNA network showed that hsa-miR-146a might regulate the shared IFN-induced genes, which might play an important role in PAH secondary to SLE.

Conclusion

Our work firstly revealed the high IFN response in SLE patients might be a crucial susceptible factor for PAH and identified novel gene candidates that could be used as biomarkers or potential therapeutic targets.

Interactive Association Between Intronic Polymorphism (rs10506151) of the LRRK2 Gene and Type 2 Diabetes on Neurodegenerative Diseases

Purpose

We investigated the interactive effect of rs10506151 polymorphism of the Leucine-rich repeat kinase 2 (LRRK2) gene and type 2 diabetes (T2D) on neurodegenerative disease (ND) risk.

Materials and Methods

Data of 17, 927 participants in the Taiwan Biobank (TWB) assessed between 2008 and 2015 were linked to healthcare records in the National Health Insurance Research Database (NHIRD). The odd ratios (ORs) and 95% confidence intervals (CIs) for NDs were determined using logistic regression analysis.

Results

There were 145 cases with NDs, and 28.28% (n = 41) of these individuals had T2D. Associations of neurodegenerative disorders with LRRK2 rs10506151 variant and T2D were not significant. The corresponding ORs (95% CI) for NDs were 1.06 (0.75–1.49) in CA/AA compared to CC individuals and 0.93 (0.63–1.39) in those with T2D compared to non-diabetic participants. However, we found evidence of a significant interaction between rs10506151 and T2D (p = 0.0073). After stratification by genotypes of rs10506151, the OR for NDs was 0.37 (CI, 0.17–0.82) in CA/AA individuals with T2D and 1.41 (0.88–2.27) in their CC counterparts. When CA/AA individuals with T2D represented the reference group, the OR (95% CI) was 1.74 (0.81–3.73) in CC individuals with no T2D, 2.47 (CI, 1.14–5.38) in CA/AA individuals with no T2D, and 2.34 (CI, 1.07–5.11) in CC individuals with T2D.

Conclusion

Our data indicated that the risk of NDs was significantly lower among diabetic individuals with combined CA/AA of the LRRK2 rs10506151 variant in Taiwan.

Identification of metabolism genes related to hepatocarcinogenesis and progression in type 2 diabetes mellitus via co-expression networks analysis

Background

Type 2 Diabetes Mellitus (T2DM) is an independent risk factor of hepatocellular carcinoma (HCC). However, the related genes and modules to hepatocarcinogenesis and progression in T2DM remain unclear.

Methods

The microarray data from Gene Expression Omnibus (GEO) were analyzed to screen differentially expressed genes (DEGs) of T2DM and HCC dataset. Then, weighted gene co-expression network analysis (WGCNA) was performed on these DEGs to detect the modules and genes, respectively. Common genes in modules with clinical interests of T2DM and HCC were obtained and annotated via GOSemSim package and Metascape. Genes related to late-stage HCC and high glycated haemoglobin (HbA1c) were also identified. These genes were validated by UALCAN analysis and univariate cox regression based on The Cancer Genome Atlas (TCGA). Finally, another two independent datasets were applied to confirm the results of our study.

Results

A total of 1288 and 1559 DEGs of T2DM and HCC were screened, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment revealed several shared pathways in two diseases, such as pathways in cancer and metabolism. A total of 37 common genes correlated with T2DM and HCC were then identified with WGCNA. Furthermore, 12 genes from modules associated with late-stage HCC and high HbA1c were regarded as hub genes. Among these genes, 8 genes associated with tumor invasion and metastasis were validated by UALCAN analysis. Moreover, downregulations of ACAT1, SLC2A2, PCK1 and ABAT were significantly associated with poorer prognosis in HCC patients with elevated HbA1c. Additionally, the expressions of PCK1 and ABAT were raised in HepG2 cells pre-treated with metformin and phenformin.

Conclusions

The present study confirmed several metabolic genes related to hyperglycemia and malignant tumor, which may provide not only new insights into the pathogenesis of hepatocarcinogenesis and progression in T2DM, but also novel therapeutic targets for T2DM patients with HCC in the future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-021-00177-x.

Identification of Hub Genes Related to Alzheimer's Disease and Major Depressive Disorder

BackgroundAlthough many studies reported a close relationship between depression and Alzheimer's disease (AD), the underlying pathophysiological mechanism remains unclear. The present study aimed to investigate the mechanism of AD and major depressive disorder (MDD). Method: The datasets were downloaded from the Gene Expression Omnibus. After screening differentially expressed genes (DEGs), gene ontology and pathway analysis were performed and protein-protein interaction, TF-target gene, and miRNA-target gene networks were established. Results: 171 DEGs of AD-related datasets and 79 DEGs shared by AD and MDD were detected. Functional analysis revealed that AD and MDD common genes were significantly enriched in circadian entrainment and long-term depression signaling pathways. Five hub genes were identified after construction of networks and validation of hub gene signatures. In conclusion, DYNC1H1, MAPRE3, TTBK2, ITGB1, and WASL may be potential targets for the diagnosis and treatment of AD and MDD.

The Other Side of Alzheimer's Disease: Influence of Metabolic Disorder Features for Novel Diagnostic Biomarkers

Nowadays, the amyloid cascade hypothesis is the dominant model to explain Alzheimer's disease (AD) pathogenesis. By this hypothesis, the inherited genetic form of AD is discriminated from the sporadic form of AD (SAD) that accounts for 85-90% of total patients. The cause of SAD is still unclear, but several studies have shed light on the involvement of environmental factors and multiple susceptibility genes, such as Apolipoprotein E and other genetic risk factors, which are key mediators in different metabolic pathways (e.g., glucose metabolism, lipid metabolism, energetic metabolism, and inflammation). Furthermore, growing clinical evidence in AD patients highlighted the presence of affected systemic organs and blood similarly to the brain. Collectively, these findings revise the canonical understating of AD pathogenesis and suggest that AD has metabolic disorder features. This review will focus on AD as a metabolic disorder and highlight the contribution of this novel understanding on the identification of new biomarkers for improving an early AD diagnosis.