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Background Mental stress-induced neurotransmitters can affect the immune system in various ways. Therefore, a better understanding of the role of neurotransmitters in the tumour immune microenvironment is expected to promote the development of novel anti-tumour therapies. Methods In this study, we analysed the plasma levels of neurotransmitters in anti-programmed cell death protein 1 (PD-1) monoclonal antibody (mAb)-resistance patients and sensitive patients, to identify significantly different neurotransmitters. Subsequently, animal experiments and experiments in vitro were used to reveal the specific mechanism of norepinephrine’s (NE) effect on immunotherapy. Results The plasma NE levels were higher in anti-PD-1 mAb-resistance patients, which may be the main cause of anti-PD-1 mAb resistance. Then, from the perspective of the immunosuppressive microenvironment to explore the specific mechanism of NE-induced anti-PD-1 mAb resistance, we found that NE can affect the secretion of C-X-C Motif Chemokine Ligand 9 (CXCL9) and adenosine (ADO) in tumour cells, thereby inhibiting chemotaxis and function of CD8+ T cells. Notably, the WNT7A/β-catenin signalling pathway plays a crucial role in this progression. Conclusion NE can affect the secretion of CXCL9 and ADO in tumour cells, thereby inhibiting chemotaxis and the function of CD8+ T cells and inducing anti-PD-1 mAb resistance in lung adenocarcinoma (LUAD).

Nonlinear model predictive control (NMPC) has become a preferred option particularly for controlling a strongly nonlinear system due to an increase in the availability of powerful cheap computing resources in recent years. However, there are still some hurdles to widely apply the NMPC algorithm for fast nonlinear dynamic systems. One of the primary challenges is how to quickly solve a set of nonlinear differential model equations and a nonlinear dynamic optimization problem in real time. A large portion of the computational problems arises from gradient vector and Hessian matrix derivations and evaluations. In this paper, the problem has been handled using an advanced symbolic computation tool called SymPy. With the symbolic computation, the complex gradient vector, Hessian matrix, and nonlinear dynamic optimization problem are derived analytically and evaluated with machine accuracy. As the rising need for a higher safety level, autonomous marine surface vehicles have been vastly used for various applications in recent years. It is known that model-free methods such as proportional-integral-derivative and nonlinear sliding mode controls are not sufficient to provide a robust control for a highly nonlinear surface vehicles. In this paper, the developed NMPC algorithm has been adopted to solve the two-dimensional trajectory tracking problem for an autonomous marine surface vehicle.

Background. Ferroptosis, a form of cell death driven by iron-dependent lipid peroxidation, may be a potential treatment for many cancers, including cervical cancer (CC). However, the regulation of long noncoding RNAs (lncRNAs) in the process of ferroptosis and whether ferroptosis inducers could increase the cytotoxicity of conventional chemotherapy drugs remain to be further elucidated. Methods. We analyzed the variation of 55 differentially ferroptosis-related genes (FRGs) and the influence of mutations in CC patients. The patients with CC were classified into two ferroptosis clusters by the non-negative matrix factorization (NMF) algorithm. The principal components analysis (PCA) was used to measure the ferroptosis score (FerroScore) in patients with CC. Besides, FerroScore was used to predict the sensitivity of chemotherapy and responses to immunotherapy in patients with CC. Finally, experiments were performed to verify the regulatory effect of AC026790.1 on erastin-induced ferroptosis, as well as the effect of erastin in combination with cisplatin on the toxicity of CC cells (SiHa, HeLa). Result. There were significant differences in the overall survival and immune cell infiltration between the two ferroptosis clusters. Patients with low FerroScore were more sensitive to chemotherapy drugs such as cisplatin and docetaxel. The low-FerroScore group had higher CD8+ T cell infiltration and immune checkpoint expression, demonstrating that patients with lower FerroScores were more sensitive to immunotherapy, which was consistent with the result of the submap method. In vitro, overexpression of AC026790.1 could promote erastin-induced ferroptosis, and the combination of erastin and cisplatin could increase the toxicity of CC cells. Conclusion. FerroScore has a potential prognostic value for CC that may provide a reference for chemotherapy and immunotherapy. LncRNA AC026790.1 can influence ferroptosis, and the combination of ferroptosis inducers and chemotherapy drugs can provide a new perspective on cancer treatment.

Background. Head and neck squamous cell carcinoma (HNSCC) is a frequently lethal malignancy, and the mortality is considerably high. The tumor microenvironment (TME) has been identified as a critical participation in cancer development, treatment, and prognosis. However, competing endogenous RNA (ceRNA) networks grouping with immune/stromal scores of HNSCC patients need to be further illustrated. Therefore, our study aimed to provide clues for searching promising prognostic markers of TME in HNSCC. Materials and Methods. ESTIMATE algorithm was used to calculate immune scores and stromal scores of the enrolled HNSCC patients. Differentially expressed genes (DEGs), lncRNAs (DELs), and miRNAs (DEMs) were identified by comparing the expression difference between high and low immune/stromal scores. Then, a ceRNA network and protein-protein interaction (PPI) network were constructed for selecting hub regulators. In addition, survival analysis was performed to access the association between immune scores, stromal scores, and differentially expressed RNAs in the ceRNA network and the overall survival (OS) of HNSCC patients. Then, the GSE65858 datasets from Gene Expression Omnibus (GEO) database was used for verification. At last, the difference between the clinical characteristics and immune cell infiltration in different expression groups of IL10RA, PRF1, and IL2RA was analyzed. Results. Survival analysis showed a better OS in the high immune score group, and then we constructed a ceRNA network composed of 97 DEGs, 79 DELs and 22 DEMs. Within the ceRNA network, FOXP3, IL10RA, STAT5A, PRF1, IL2RA, miR-148a-3p, miR-3065-3p, and lncRNAs, including CXCR2P1, HNRNPA1P21, CTA-384D8.36, and IGHV1OR15-2, were closely correlated with the OS of HNSCC patients. Especially, using the data from GSE65858, we successfully verified that IL10RA, PRF1, and IL2RA were not only significantly upregulated in patients high immune scores, but also their high expressions were associated with longer survival time. In addition, stratified analysis showed that PRF1 and IL2RA might be involved in the mechanism of tumor progress. Conclusion. In conclusion, we constructed a ceRNA network related to the TME of HNSCC, which provides candidates for therapeutic intervention and prognosis evaluation.

Background. Breast cancer (BC) is a highly heterogeneous disease with high morbidity and mortality. Its subtypes may have distinctly different biological behaviors, clinical outcomes, and therapeutic responses. The metabolic status of BC tissue is closely related to its progress. Therefore, we comprehensively characterized the function of metabolic genes in BC and identified new biomarkers to predict BC patients’ prognoses. Methods. Metabolic genes were identified by intersecting genes obtained from two published pieces of literature. The function of metabolic genes in BC was determined by extracting differentially expressed genes (DEGs), performing functional enrichment analyses, analyzing the infiltrating proportion of immune cells, and conducting metabolic subgroup analyses. A risk score model was constructed to assess the prognoses of BC patients by performing the univariate Cox regression, LASSO algorithm, multivariate Cox regression, Kaplan-Meier survival analyses, and ROC curve analyses in the training set. The prognostic model was then validated on the testing dataset, external dataset, the whole TCGA-BC database, and our clinical specimens. Finally, a nomogram was constructed for clinical prognostic prediction based on the risk score model and other clinicopathological parameters. Results. 955 metabolic genes were obtained. Among these, 157 metabolic DEGs were identified between BC and normal tissues for subsequent GO and KEGG pathway enrichment analyses. 5 metabolic genes were negatively correlated with CD8+ T cells, while 49 genes were positively correlated with CD8+ T cells. Furthermore, 5 metabolic subgroups with varying proportions of PAM50 subtypes, TNM classification, and immune cell infiltration were obtained. Finally, a risk score model was constructed to predict the prognoses of BC patients, and a nomogram incorporating the risk score model was established for clinical application. Conclusion. In this study, we elucidated tumor heterogeneity from metabolite profiling of BC. The roles of metabolic genes in the occurrence of BC were comprehensively characterized, clarifying the relationship between the tumor microenvironment (TME) and metabolic genes. Meanwhile, a concise prediction model was also constructed based on metabolic genes, providing a convenient and precise method for the individualized diagnosis and treatment of BC patients.

Although recent clinical investigations emphasize the roles of myriad diversities of RNAs in stromal and immune components in the tumor microenvironment, especially in colon adenocarcinoma, however, analyses of “competing endogenous RNAs (ceRNA)” network in association with stromal and immune scores have yet to be determined. This study was conducted to explore the regulatory mechanisms of a stromal-immune score-based ceRNA network in colon adenocarcinoma. Stromal and immune scores of colon adenocarcinoma tumor samples were calculated by using the ESTIMATE algorithm. Differential expression analysis between samples with high/low stromal and immune scores was performed, followed by functional annotation for the overlapping DEmRNAs. The ceRNA network was constructed by differential expression analysis, prediction of RNA-RNA interaction, and correlation with clinicopathological parameters of the patients, which were further verified by external datasets and experiments. Colon adenocarcinoma patients having higher immune scores exhibited prolonged overall survival. RNA dataset analyses from TCGA revealed aberrant expressions of a total of 2052 mRNAs, 108 lncRNAs, and 70 miRNAs between high and low stromal/immune groups. Functional annotation mapped the differentially overexpressed mRNAs for immune-associated GO terms. To construct the ceRNA network, a total of 48 lncRNAs, 40 miRNAs, and 199 mRNAs were sorted out. A dysregulated ceRNA network consisting of 6 lncRNAs, 11 miRNAs, and 39 mRNAs was constructed by comparing RNA expressions between cancer as well as adjacent normal tissues. The ceRNA regulatory axis “MIAT/miR-532-3p/STC1” was regarded as a potential hit by the comprehensive analysis. The RT-qPCR assay showed upregulation of MIAT and STC1 while downregulation of hsa-miR-532-3p expression in cancer. Thus, our study highlights the potential role of a stromal-immune score-based ceRNA network in the colon adenocarcinoma microenvironment. The ceRNA axis MIAT/miR-532-3p/STC1 could serve as a promising therapeutic target for colon adenocarcinoma.

ATPase family AAA domain-containing protein 2 (ATAD2) is highly expressed in a variety of cancer types, and acts as a co-activator of androgen and estrogen receptors, as well as MYC and E2F transcription factors, to promote tumor cell proliferation. However, the regulation of ATAD2 and its related mechanisms are still elusive. Here, we show that ATAD2 protein was stabilized during DNA damage response in colorectal cancer (CRC) cells. TRIM25, an oncogenic ubiquitin E3 ligase, can interact with ATAD2 and stabilize ATAD2 upon genotoxic insult. We further demonstrated that ATAD2 played a tumor promoting role in CRC and acted as a transcriptional co-activator of E2Fs to promote the expression of TRIM25. Thus, our results revealed an unknown ATAD2-E2Fs-TRIM25 positive feedback loop that drove CRC progression.

Background: Cervical cancer (CC) is the most common reproductive neoplasm in women, especially in developing countries. Ferroptosis, a novel type of cell death, and lncRNAs play critical roles in the prognosis of CC patients and antitumor immunity. Methods: A ferroptosis-related lncRNA signature (FRLS) was constructed by LASSO Cox regression analysis. Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis, multivariate analysis, and nomogram were used to evaluate and predict the FRLS. Based on the FRLS, immune-related genes, the tumor microenvironment (TME), immune checkpoints, and immunotherapy were investigated. Results: The FRLS was composed of ten lncRNAs and was markedly associated with the overall survival (OS) of CC patients. Gene set enrichment analysis (GSEA) demonstrated that the FRLS was largely associated with immune-related pathways. Weighted gene co-expression network analysis (WGCNA) was performed to analyze immune-related genes and to identify the optimal modules and genes. TLR4 was eventually identified, and its expression was verified in the Gene Expression Omnibus (GEO) database. Then, quantitative real-time PCR (qRT-PCR) was used to validate the results in CC and paracancerous tissues. Besides, our results showed that CD8+ T cells were significantly correlated between the low- and high-risk groups, and it could modulate ferroptosis during tumor immunotherapy. The expression of immune checkpoints was substantially different between the two groups. Additionally, tumor immune dysfunction and exclusion (TIDE) was applied to predict the sensitivity of immune checkpoint inhibitor (ICI) treatment. Conclusion: The FRLS established was significantly associated with prognosis; moreover, the FRLS is a prospective therapeutic target, and combined with immunotherapy, can be used in the treatment of CC patients.

We downloaded gene expression data, clinical data, and somatic mutation data of cervical squamous cell carcinoma (CSCC) patients from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Predictive lncRNAs were screened using univariate analysis and least absolute shrinkage and selection operator (LASSO) regression, and risk scores were calculated for each patient according to the expression levels of lncRNAs and regression coefficients to establish a risk model that could be a novel signature. We assessed the correlation between immune infiltration status, chemotherapeutics sensitivity, immune checkpoint proteins (ICP), and the signature. Therefore, we selected 11 immune-related lncRNAs (WWC2,AS2, STXBP5.AS1, ERICH6.AS1, USP30.AS1, LINC02073, RBAKDN, IL21R.AS1, LINC02078, DLEU1, LINC00426, BOLA3.AS1) to construct the risk model. Patients who were in the high-risk group had a shorter survival time than those in the low-risk group (p 0.001). Risk scores in the signature were negatively correlated with macrophage M1, macrophage M2, and T cell CD8 + ; what's more, T cell CD8 + was higher in the low-risk group. The expression levels of ICP such as PD-L1, PD-1, CTLA-4, TIGIT, LAG-3, and TIM-3 were substantially higher in the low-risk group. For chemotherapeutic agents, high-risk scores were associated with higher half-inhibitory concentrations (IC50) of cisplatin. These findings suggested that the risk model can be a novel signature for predicting CSCC patients' prognosis, and it also can be used to formulate clinical treatment plans for CSCC patients.

Multiple myeloma (MM) is an extremely complex plasma cell malignancy that is genetically heterogeneous. A recent Genome-wide association study (GWAS) indicated that variation at 2q22 (rs61070260) influences MM risk. This association has not been validated to date in a Chinese Han population. In this study, we evaluated the association between rs61070260 in LRP1B and MM risk in a Chinese Han population involving 739 MM patients and 592 healthy controls. Our results indicated that rs61070260 in LRP1B was significantly associated with MM susceptibility (P=3.937×10-37). Furthermore, the linkage disequilibrium (LD) analysis of rs61070260 revealed an LD block encompassing exons 26, 27 and 28 of the LRP1B gene, and a subsequent sequencing analysis identified three SNPs (rs762074421, rs756168629, rs113600691) in exons 26 and 28 of LRP1B. For the SNP rs756168629 in exon 26, a missense mutation which results in a transition from arginine to histidine at position 1661 of the LRP1B protein, has not been found in Chinese populations according to the Chinese Millionome Database and Genome Aggregation Database (EAS), and this mutation was predicted to be deleterious or damaging by SIFT and PolyPhen. These findings firmly establish the role of LRP1B in contributing to MM susceptibility. In addition, the identification of a rare coding mutation (p.R1661H) in LRP1B detected in MM individuals was suggested to be harmful to the encoded protein, which was characterized as a candidate tumour suppressor; thus, LRP1B is likely to be a disease-associated gene that is implicated in the development and progression of MM.

Background: Idiopathic membranous nephropathy (IMN) is an autoimmune disease and the leading cause of adult nephritic syndrome. HLA-DQA1 had been identified to be associated with IMN in Europeans and the result was replicated in Chinese Han population. In this study, six single nucleotide polymorphisms (SNPs) in the promoter of HLA-DQA1 and other two SNPs with IgA nephropathy were included for the association analysis. Methods: The SNPs were genotyped in 509 patients and 601 controls by the MassArray iPLEX. The quantification of anti-phospholipase A2 receptor (PLA2R) antibodies in sera of IMN patients was performed by anti-PLA2R ELISA (IgG) kit. Results: After analysis, four SNPs were significantly associated with IMN, with rs2187668 and rs28383345 as the top two signals (P = 8.42×10-5 and 2.48×10-5, respectively). Even under dominant model, the two SNPs were still significantly associated with IMN (P = 3.50×10-3 for rs28383345 and P = 6.55×10-5 for rs2187668). After conditional study with rs2187668, rs28383345 was the only variant significantly correlated with IMN after Bonferroni correction (P = 0.016). The minor alleles of the two SNPs were also mutually exclusive in our cohort. This indicated that the two SNPs were independently associated with IMN in Chinese Han population. Levels of anti-PLA2R autoantibodies were correlated with the genotypes of the two SNPs, but not significantly (P>0.05). Conclusions: Our results revealed that a novel independent variant in the promoter of HLA-DQA1 was associated with IMN in Chinese Han population. The locus possessed regulatory role according to the data of RegulomeDB. The exact role of the SNPs on the expression of HLA-DQA1 needs further investigation. Key words: Autoimmune Disease; HLA-DQA1; Idiopathic Membranous Nephropathy; Promoter; Chinese

The role of the X-ray repair cross-complementing gene 1(XRCC1) Arg399Gln and Arg194Trp polymorphisms has been involved in the investigations of susceptibility to multiple autoimmune diseases, but the results were inconsistent. Here, we have performed a meta-analysis to clarify the relationship between them. All appropriate case-control studies were searched in the PubMed, EMBASE and Chinese National Knowledge Infrastructure (CNKI) database. A meta-analysis was conducted on the association between the XRCC1 two polymorphisms (Arg399Gln, Arg194Trp) and risk of autoimmune diseases. Pooled odds ratios (OR) with 95% confidence intervals (CI) were conducted to assess the association. Fourteen relevant studies with a total of 2886 cases and 3257 controls were analyzed in our research. Analysis for the XRCC1 Arg399Gln polymorphism under recessive model (OR 1.53, 95% CI 1.07-2.18, P = 0.019), dominant model (OR 1.36, 95% CI 1.04-1.77, P = 0.026) and homozygous model (OR 1.67, 95% CI 1.07-2.62, P = 0.024) indicated an association in the overall population, as well as in Caucasian populations under the recessive model (OR 1.73, 95% CI 1.03-2.91, P = 0.039) and Asian populations under dominant model (OR 1.31, 95% CI 1.02-1.70, P = 0.037). Stratification by disease indicated significant association between XRCC1 Arg399Gln and rheumatoid arthritis (RA) in all genetic models (P

Background Cervical squamous cell carcinoma (CESC) is one of the most common malignancies associated with mortality in females. Its onset and prognosis are primarily concerned with persistent infection with high-risk types of human papillomavirus (HPV). However, the molecular mechanisms of HPV-positive CESC remain unclear. Methods In this study, we conducted a high-throughput sequencing to identify differentially expressed miRNAs (DEMs). Besides, three series were selected from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). Then the miRNA-TF-gene regulatory network was constructed using bioinformatic methods. Genes in the network were performed functional enrichment analysis and protein-protein interaction (PPI) network analysis. Ultimately, the expression levels of six key miRNAs, TFs, and mRNAs were validated by 20 HPV-positive CESC tissues and 15 normal cervical samples. Results A total of 52 DEMs and 300 DEGs differed between the HPV-positive CESC and normal cervical samples. Then the miRNA-TF-gene regulatory network was constructed consisting of 22 miRNAs, 6 TFs, and 76 corresponding genes, among which miR-149-5p, miRNA-1248 and E2F4 acted as key regulators. PPI network analysis showed that ten genes including TOP2A, AURKA, CHEK1, KIF11, MCM4, MKI67, DTL, FOXM1, SMC4, and FBXO5 were recognized as hub genes with the highest connectivity degrees. Besides, five key molecules miRNA-149-5p, E2F4, KIF11, DTL, and SMC4 were suggested to play crucial roles in the development of HPV-positive CESC. Conclusion These results present a unique insight into the pathological mechanisms of HPV-positive CESC and possibly provides potential therapeutic targets.

Background Lung adenocarcinoma (LUAD), largely remains a primary cause of cancer-related death worldwide. The molecular mechanisms in LUAD metastasis have not been completely uncovered. Methods In this study, we identified differentially expressed genes (DEGs), miRNAs (DEMs) and lncRNAs (DELs) underlying metastasis of LUAD from The Cancer Genome Atlas database. Intersection mRNAs were used to perform gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and co-expression network analysis. In addition, survival analyses of intersection mRNAs were conducted. Finally, intersection mRNAs, miRNAs and lncRNAs were subjected to construct miRNA-mRNA-lncRNA network. Results A total of 1015 DEGs, 54 DEMs and 22 DELs were identified in LUAD metastasis and non-metastasis samples. GO and KEGG pathway analysis had proven that the functions of intersection mRNAs were closely related with many important processes in cancer pathogenesis. Among the co-expression interactions network, 22 genes in the co-expression network were over the degree 20. These genes imply that they have connections with many other gene nodes. In addition, 14 target genes (ARHGAP11A, ASPM, HELLS, PRC1, TMPO, ARHGAP30, CD52, IL16, IRF8, P2RY13, PRKCB, PTPRC, SASH3 and TRAF3IP3) were found to be associated with survival in patients with LUAD significantly (log-rank P

The association between polymorphisms in the nucleoside diphosphate kinase 1 (NME1) gene and overall risk of cancer remains to be elucidated. Here, we performed a meta-analysis of the association between rs16949649, rs2302254, and rs34214448 polymorphisms in the NME1 gene and cancer risk. PubMed, Web of Science, and CNKI databases (as of June 6, 2017) were searched. Eight studies, encompassing 1644 cases and 2038 controls, were selected. The results revealed no significant relationship between NME1 polymorphisms and overall cancer susceptibility. Interestingly, the rs16949649 polymorphism was associated with increased susceptibility to gynecological cancer (heterozygous model: odds ratio [OR] = 1.74, 95% confidence interval [CI] = 1.06-2.86, P = 0.029). The rs2302254 polymorphism was linked to decreased susceptibility to gastric cancer in the other groups (recessive model: OR = 0.53, 95% CI = 0.28-0.98, P = 0.045). The rs34214448 polymorphism correlated significantly with increased susceptibility to non-small cell lung cancer according to all genetic models (P 0.05) and was linked to decreased risk in cervical cancer (recessive model: OR = 0.51, 95% CI = 0.27-0.94, P = 0.031). Thus, our meta-analysis found rs16949649 associated with increased susceptibility to gynecological cancer and rs2302254 was linked to reduced gastric cancer risk; additional, larger studies are required to confirm these findings.

The coexistence of immunoglobulin A nephropathy (IgAN) and idiopathic membranous nephropathy (IMN) in a few cases suggested that there could be existed a similar mechanism in pathogenesis of these two types of primary glomerulonephritis. In order to verify this hypothesis, a total of 23 reported IgAN-associated SNPs were genotyped in a cohort of 485 IMN patients and 569 healthy controls with Chinese Han origin. After Cochran-Armitage test for trend analysis, seven IgAN-associated SNPs located in the major histocompatibility complex (MHC) region were found to be significantly associated with the susceptibility of IMN, with rs9275596 as the top one (p = 1.97E-43, OR = 3.977). It was worth mentioning that the minor alleles of the SNPs conferred completely opposite effects on the pathogenesis of IMN and IgAN, suggesting quite different roles played by these SNPs for these two kinds of primary glomerulonephritis. Conditional logistic regression analysis displayed that SNPs protective from IMN (odds ratio

BACKGROUND: The incidence of dilated cardiomyopathy (DCM) has increased in recent years, and many studies have sought to further improve the general understanding of this condition. Previous studies have demonstrated that some single nucleotide polymorphisms (SNPs) associated with systemic lupus erythematosus also affect susceptibility to DCM, suggesting that immune‐related diseases may share similar genetic susceptibility. Recent large‐scale and genome‐wide association studies have identified NCR3,NOTCH4,CYP1A2,ITGA1,OPRM1,ST8SIA2, and LINC00704 as genetic risk factors associated with cardiac manifestations of neonatal lupus. Here, we aimed to determine whether these SNPs conferred susceptibility to DCM in the Chinese Han population. METHODS: We investigated the relationship between these polymorphisms and DCM risk in 273 patients with DCM and 548 healthy controls. Genotyping was performed using MassArray iPLEX system. RESULTS: Logistic regression analysis indicated that the T allele of rs3134942 in NOTCH4 gene increased the risk of DCM by 61% compared with the G allele (P (a) = 6.57 × 10(−3)). The SNP rs3134942 was also significantly associated with increased DCM risk in the additive (P (a) = 6.57 × 10(−3)) and dominant models (P (a) = 1.01 × 10(−2)). Additionally, rs2472299 in CYP1A2 gene showed suggestive association with reduced risk of DCM in the dominant model (P (a) = 4.24 × 10(−2)) and was correlated with smoking status in patients with DCM (P (a) = 1.56 × 10(−2)). CONCLUSIONS: Our findings suggested that rs3134942 in NOTCH4 may be involved in DCM risk. Further, studies in larger and ethnically diverse populations are required to confirm the results reported in this study.