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Background: Minimal change disease (MCD) has a high recurrence rate, but currently, no biomarker can predict its recurrence. To this end, this study aimed at identifying potential serum cytokines as valuable biomarkers for predicting the risk of MCD recurrence. Materials and methods: Raybiotech 440 cytokine antibody microarray was used to detect the serum samples of eight relapsed, eight non-relapsed MCD patients after glucocorticoid treatment, and eight healthy controls. The differentially expressed cytokines were confirmed by enzyme-linked immunosorbent assay (ELISA) with serum samples from 29 non-relapsed and 35 relapsed MCD patients. The study used the receiver operating characteristic (ROC) curve analysis to investigate the sensitivity and specificity of a serum biomarker for predicting the MCD relapse. Results: Serum IL-12p40 levels increased significantly in the relapsed group. The Area Under the ROC Curve (AUC) of IL-12p40 was 0.727 (95%CI: 0.597-0.856; P < 0.01). The RNA-sequencing analysis and qPCR assay performed on the IL-12 treated mouse podocytes and the control group showed increased expression of podocyte damage genes, such as connective tissue growth factor (CTGF), matrix metallopeptidase 9 (MMP9), secreted phosphoprotein 1 (SPP1), and cyclooxygenase-2 (COX-2) in the former group. Conclusion: IL-12p40 may serve as a new biomarker for predicting the risk of MCD recurrence after glucocorticoid treatment, and it may be involved in the pathogenesis and recurrence of MCD.
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BACKGROUND: Metabolomics is useful in elucidating the progression of diabetes; however, the follow-up changes in metabolomics among health, diabetes mellitus, and diabetic kidney disease (DKD) have not been reported. This study was aimed to reveal metabolomic signatures in diabetes development and progression. METHODS: In this cross-sectional study, we compared healthy (n = 30), type 2 diabetes mellitus (T2DM) (n = 30), and DKD (n = 30) subjects with the goal of identifying gradual altering metabolites. Then, a prospective study was performed in T2DM patients to evaluate these altered metabolites in the onset of DKD. Logistic regression was conducted to predict rapid eGFR decline in T2DM subjects using altered metabolites. The prospective association of metabolites with the risk of developing DKD was examined using logistic regression and restricted cubic spline regression models. RESULTS: In this cross-sectional study, impaired amino acid metabolism was the main metabolic signature in the onset and development of diabetes, which was characterized by increased N-acetylaspartic acid, L-valine, isoleucine, asparagine, betaine, and L-methionine levels in both the T2DM and DKD groups. These candidate metabolites could distinguish the DKD group from the T2DM group. In the follow-up study, higher baseline levels of L-valine and isoleucine were significantly associated with an increased risk of rapid eGFR decline in T2DM patients. Of these, L-valine and isoleucine were independent risk factors for the development of DKD. Notably, nonlinear associations were also observed for higher baseline levels of L-valine and isoleucine, with an increased risk of DKD among patients with T2DM. CONCLUSION: Amino acid metabolism was disturbed in diabetes, and N-acetylaspartic acid, L-valine, isoleucine, asparagine, betaine, and L-methionine could be biomarkers for the onset and progression of diabetes. Furthermore, high levels of L-valine and isoleucine may be risk factors for DKD development.
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Diabetes Mellitus Tipo 2 , Nefropatias Diabéticas , Asparagina , Betaína , Estudos Transversais , Diabetes Mellitus Tipo 2/complicações , Diabetes Mellitus Tipo 2/metabolismo , Nefropatias Diabéticas/metabolismo , Progressão da Doença , Seguimentos , Humanos , Isoleucina , Metionina , Estudos Prospectivos , ValinaRESUMO
Demethylase Tet2 plays a vital role in the immune response. Acute kidney injury (AKI) initiation and maintenance phases are marked by inflammatory responses and leukocyte recruitment in endothelial and tubular cell injury processes. However, the role of Tet2 in AKI is poorly defined. Our study determined the degree of renal tissue damage associated with Tet2 gene expression levels in a cisplatin-induced AKI mice model. Tet2-knockout (KO) mice with cisplatin treatment experienced severe tubular necrosis and dilatation, inflammation, and AKI markers' expression levels than the wild-type mice. In addition, the administration of Tet2 plasmid protected Tet2-KO mice from cisplatin-induced nephrotoxicity, but not Tet2-catalytic-dead mutant. Tet2 KO was associated with a change in metabolic pathways like retinol, arachidonic acid, linolenic acid metabolism, and PPAR signaling pathway in the cisplatin-induced mice model. Tet2 expression is also downregulated in other AKI mice models and clinical samples. Thus, our results indicate that Tet2 has a renal protective effect during AKI by regulating metabolic and inflammatory responses through the PPAR signaling pathway.
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[Figure: see text].
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Proteínas ADAM/metabolismo , Injúria Renal Aguda/metabolismo , Rim/metabolismo , Ativação de Macrófagos/fisiologia , MicroRNAs/metabolismo , Proteínas ADAM/genética , Injúria Renal Aguda/genética , Injúria Renal Aguda/patologia , Animais , Linhagem Celular , Quimiocina CCL2/genética , Quimiocina CCL2/metabolismo , Modelos Animais de Doenças , Fibrose/genética , Fibrose/metabolismo , Fibrose/patologia , Humanos , Rim/patologia , Masculino , Camundongos , MicroRNAs/genética , RatosRESUMO
BACKGROUND AND AIMS: Susceptibility genes and the underlying mechanisms for the majority of risk loci identified by genome-wide association studies (GWAS) for colorectal cancer (CRC) risk remain largely unknown. We conducted a transcriptome-wide association study (TWAS) to identify putative susceptibility genes. METHODS: Gene-expression prediction models were built using transcriptome and genetic data from the 284 normal transverse colon tissues of European descendants from the Genotype-Tissue Expression (GTEx), and model performance was evaluated using data from The Cancer Genome Atlas (n = 355). We applied the gene-expression prediction models and GWAS data to evaluate associations of genetically predicted gene-expression with CRC risk in 58,131 CRC cases and 67,347 controls of European ancestry. Dual-luciferase reporter assays and knockdown experiments in CRC cells and tumor xenografts were conducted. RESULTS: We identified 25 genes associated with CRC risk at a Bonferroni-corrected threshold of P < 9.1 × 10-6, including genes in 4 novel loci, PYGL (14q22.1), RPL28 (19q13.42), CAPN12 (19q13.2), MYH7B (20q11.22), and MAP1L3CA (20q11.22). In 9 known GWAS-identified loci, we uncovered 9 genes that have not been reported previously, whereas 4 genes remained statistically significant after adjusting for the lead risk variant of the locus. Through colocalization analysis in GWAS loci, we additionally identified 12 putative susceptibility genes that were supported by TWAS analysis at P < .01. We showed that risk allele of the lead risk variant rs1741640 affected the promoter activity of CABLES2. Knockdown experiments confirmed that CABLES2 plays a vital role in colorectal carcinogenesis. CONCLUSIONS: Our study reveals new putative susceptibility genes and provides new insight into the biological mechanisms underlying CRC development.
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Biomarcadores Tumorais/genética , Neoplasias Colorretais/genética , Predisposição Genética para Doença , Modelos Genéticos , Alelos , Carcinogênese/genética , Estudos de Casos e Controles , Estudos de Coortes , Neoplasias Colorretais/epidemiologia , Técnicas de Silenciamento de Genes , Estudo de Associação Genômica Ampla , Humanos , Polimorfismo de Nucleotídeo Único , Regiões Promotoras Genéticas/genética , RNA-Seq , Fatores de Risco , Ensaios Antitumorais Modelo de XenoenxertoRESUMO
BACKGROUND: Pathogenic variants in susceptibility genes lead to increased breast cancer risk. METHODS: To identify coding variants associated with breast cancer risk, we conducted whole-exome sequencing in genomic DNA samples from 831 breast cancer cases and 839 controls of Chinese women. We also genotyped samples, including 4,580 breast cancer cases and 6,695 controls, using whole exome-chip arrays. We further performed a replication study using a Multi-Ethnic Global Array in samples from 1,793 breast cases and 2,059 controls. A single marker analysis was performed using the Fisher exact test. RESULTS: We identified a missense variant (rs139379666, P2974L; AF = 0.09% for breast cancer cases, but none for controls) in the ATM gene for breast cancer risk using combing data from 7,204 breast cancer cases and 9,593 controls (P = 1.7 × 10-5). To investigate the functionality of the variant, we first silenced ATM and then transfected the overexpression vectors of ATM containing the risk alleles (TT) or reference alleles (CC) of the variant in U2OS and breast cancer SK-BR3 cells, respectively. Our results showed that compared with the reference allele, the risk allele significantly disrupts the activity of homologous recombination-mediated double-strand breaks repair efficiency. Our results further showed that the risk allele may play a defected regulation role in the activity of the ATM structure. CONCLUSIONS: Our findings identified a novel mutation that disrupts ATM function, conferring to breast cancer risk. IMPACT: Functional investigation of genetic association findings is necessary to discover a pathogenic variant for breast cancer risk.
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Proteínas Mutadas de Ataxia Telangiectasia/genética , Neoplasias da Mama/epidemiologia , Neoplasias da Mama/genética , Mutação de Sentido Incorreto , Reparo de DNA por Recombinação , Proteínas Mutadas de Ataxia Telangiectasia/metabolismo , Estudos de Casos e Controles , China/epidemiologia , Estudos de Coortes , Feminino , Genótipo , Humanos , Fatores de Risco , Células Tumorais Cultivadas , Sequenciamento do Exoma/métodosRESUMO
Genome-wide association studies (GWASs) have identified more than 150 common genetic loci for breast cancer risk. However, the target genes and underlying mechanisms remain largely unknown. We conducted a cis-expression quantitative trait loci (cis-eQTL) analysis using normal or tumor breast transcriptome data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), The Cancer Genome Atlas (TCGA), and the Genotype-Tissue Expression (GTEx) project. We identified a total of 101 genes for 51 lead variants after combing the results of a meta-analysis of METABRIC and TCGA, and the results from GTEx at a Benjamini-Hochberg (BH)-adjusted p < 0.05. Using luciferase reporter assays in both estrogen-receptor positive (ER+) and negative (ER-) cell lines, we showed that alternative alleles of potential functional single-nucleotide polymorphisms (SNPs), rs11552449 (DCLRE1B), rs7257932 (SSBP4), rs3747479 (MRPS30), rs2236007 (PAX9), and rs73134739 (ATG10), could significantly change promoter activities of their target genes compared to reference alleles. Furthermore, we performed in vitro assays in breast cancer cell lines, and our results indicated that DCLRE1B, MRPS30, and ATG10 played a vital role in breast tumorigenesis via certain disruption of cell behaviors. Our findings revealed potential target genes for associations of genetic susceptibility risk loci and provided underlying mechanisms for a better understanding of the pathogenesis of breast cancer.