In silico analysis of human renin gene-gene interactions and neighborhood topologically associated domains suggests breakdown of insulators contribute to ageing-associated diseases

Rapid identification of early renal damage in asymptomatic hyperuricemia patients based on urine Raman spectroscopy and bioinformatics analysis

Objective: The issue of when to start treatment in patients with hyperuricemia (HUA) without gout and chronic kidney disease (CKD) is both important and controversial. In this study, Raman spectroscopy (RS) was used to analyze urine samples, and key genes expressed differentially CKD were identified using bioinformatics. The biological functions and regulatory pathways of these key genes were preliminarily analyzed, and the relationship between them as well as the heterogeneity of the urine components of HUA was evaluated. This study provides new ideas for the rapid evaluation of renal function in patients with HUA and CKD, while providing an important reference for the new treatment strategy of HUA disease. Methods: A physically examined population in 2021 was recruited as the research subjects. There were 10 cases with normal blood uric acid level and 31 cases with asymptomatic HUA diagnosis. The general clinical data were collected and the urine samples were analyzed by Raman spectroscopy. An identification model was also established by using the multidimensional multivariate method of orthogonal partial least squares discriminant analysis (OPLS-DA) model for statistical analysis of the data, key genes associated with CKD were identified using the Gene Expression Omnibus (GEO) database, and key biological pathways associated with renal function damage in CKD patients with HUA were analyzed. Results: The Raman spectra showed significant differences in the levels of uric acid (640 cm^-1), urea, creatinine (1,608, 1,706 cm^-1), proteins/amino acids (642, 828, 1,556, 1,585, 1,587, 1,596, 1,603, 1,615 cm^-1), and ketone body (1,643 cm^-1) (p < 0.05). The top 10 differentially expressed genes (DEGs) associated with CKD (ALB, MYC, IL10, FOS, TOP2A, PLG, REN, FGA, CCNA2, and BUB1) were identified. Compared with the differential peak positions analyzed by the OPLS-DA model, it was found that the peak positions of glutathione, tryptophan and tyrosine may be important markers for the diagnosis and progression of CKD. Conclusion: The progression of CKD was related to the expression of the ALB, MYC, IL10, PLG, REN, and FGA genes. Patients with HUA may have abnormalities in glutathione, tryptophan, tyrosine, and energy metabolism. The application of Raman spectroscopy to analyze urine samples and interpret the heterogeneity of the internal environment of asymptomatic HUA patients can be combined with the OPLS-DA model to mine the massive clinical and biochemical examination information on HUA patients. The results can also provide a reference for identifying the right time for intervention for uric acid as well as assist the early detection of changes in the internal environment of the body. Finally, this approach provides a useful technical supplement for exploring a low-cost, rapid evaluation and improving the timeliness of screening. Precise intervention of abnormal signal levels of internal environment and energy metabolism may be a potential way to delay renal injury in patients with HUA.

Integration of Imaging Genomics Data for the Study of Alzheimer's Disease Using Joint-Connectivity-Based Sparse Nonnegative Matrix Factorization

Imaging genetics reveals the connection between microscopic genetics and macroscopic imaging, enabling the identification of disease biomarkers. In this work, we make full use of prior knowledge that has significant reference value for investigating the correlation between the brain and genetics to explore more biologically substantial biomarkers. In this paper, we propose joint-connectivity-based sparse nonnegative matrix factorization (JCB-SNMF). The algorithm simultaneously projects structural magnetic resonance imaging (sMRI), single-nucleotide polymorphism sites (SNPs), and gene expression data onto a common feature space, where heterogeneous variables with large coefficients in the same projection direction form a common module. In addition, the connectivity information for each region of the brain and genetic data are added as prior knowledge to identify regions of interest (ROIs), SNPs, and gene-related risks related to Alzheimer's disease (AD) patients. GraphNet regularization increases the anti-noise performance of the algorithm and the biological interpretability of the results. The simulation results show that compared with other NMF-based algorithms (JNMF, JSNMNMF), JCB-SNMF has better anti-noise performance and can identify and predict biomarkers closely related to AD from significant modules. By constructing a protein-protein interaction (PPI) network, we identified SF3B1, RPS20, and RBM14 as potential biomarkers of AD. We also found some significant SNP-ROI and gene-ROI pairs. Among them, two SNPs rs4472239 and rs11918049 and three genes KLHL8, ZC3H11A, and OSGEPL1 may have effects on the gray matter volume of multiple brain regions. This model provides a new way to further integrate multimodal impact genetic data to identify complex disease association patterns.

Prognostic and immunological value of ATP6AP1 in breast cancer: implications for SARS-CoV-2

Abnormal ATPase H+ Transporting Accessory Protein 1 (ATP6AP1) expression may promote carcinogenesis. We investigated the association of ATP6AP1 with breast cancer (BC) and COVID-19. The Oncomine, Gene Expression Profiling Interactive Analysis, Human Protein Atlas and Kaplan-Meier plotter databases were used to evaluate the expression and prognostic value of ATP6AP1 in BC. ATP6AP1 was upregulated in BC tissues, and higher ATP6AP1 expression was associated with poorer outcomes. Data from the Tumor Immune Estimation Resource, Tumor-Immune System Interaction Database and Kaplan-Meier plotter indicated that ATP6AP1 expression correlated with immune infiltration, and that its prognostic effects in BC depended on tumor-infiltrating immune cell subtype levels. Multiple databases were used to evaluate the association of ATP6AP1 with clinicopathological factors, assess the mutation and methylation of ATP6AP1, and analyze gene co-expression and enrichment. The ATP6AP1 promoter was hypomethylated in BC tissues and differentially methylated between different disease stages and subtypes. Data from the Gene Expression Omnibus indicated that ATP6AP1 levels in certain cell types were reduced after SARS-CoV-2 infections. Ultimately, higher ATP6AP1 expression was associated with a poorer prognosis and with higher or lower infiltration of particular immune cells in BC. BC patients may be particularly susceptible to SARS-CoV-2 infections, which may alter their prognoses.

Association of growth hormone receptor gene variant with longevity in men is due to amelioration of increased mortality risk from hypertension

The single nucleotide polymorphism (SNP) rs4130113 of the growth hormone receptor gene (GHR) is associated with longevity. Here we explored whether longevity-associated genotypes protect against mortality in all individuals, or only in individuals with aging-related diseases. Rs4130113 genotypes were tested for association with mortality in 3,557 elderly American men of Japanese ancestry. At baseline (1991–1993), 1,000 had diabetes, 730 had coronary heart disease (CHD), 1,901 had hypertension, 485 had cancer, and 919 lacked these diseases. The men were followed from baseline until Dec 31, 2019 or death (mean 10.8 ± 6.5 SD years, range 0.01–28.8 years; 99.0% deceased by that date). In a heterozygote disadvantage model, longevity-associated genotypes were associated with significantly lower mortality risk in individuals having hypertension (covariate-adjusted hazard ratio [HR] 0.83 [95% CI: 0.76–0.93, p = 4.3 x10^–4]. But in individuals with diabetes, CHD, and cancer there was no genotypic difference in lifespan. As expected, normotensive men outlived men with hypertension (p = 0.036). There was no effect, however, of genotypic difference on lifespan in normotensive men (p = 0.11). We found that SNP rs4130113 potentially influenced the binding of transcription factors E2A, MYF, NRSF, TAL1, and TCF12 so as to alter GHR expression. We propose that in individuals with hypertension, longevity-associated genetic variation in GHR enhances cell resilience mechanisms to help protect against cellular stress caused by hypertension. As a result, hypertension-affected men who possess the longevity-associated genetic variant of GHR live as long as normotensive men.

Vitamin D decreases silencer methylation to downregulate renin gene expression

Renin, encoded by REN, is an essential enzyme in the renin-angiotensin aldosterone system (RAAS) which is responsible for the maintenance of blood pressure homeostasis. Transcriptional regulation of REN has been linked to enhancer-promoter crosstalk, cAMP response element-binding protein (CREB), the active metabolite of vitamin D, 1,25-dihydroxyvitamin D₃ (1,25(OH)₂D₃), and a less well-characterized intronic silencer element. We hypothesized that in addition to these, differential DNA methylation is linked to REN expression and influenced by 1,25(OH)₂D₃. REN expressing cells (HEK293) were used to elucidate the effect of 1,25(OH)₂D₃ on REN methylation and expression as quantified by methylation-sensitive qPCR and RT-qPCR, respectively. In vitro 1,25(OH)₂D₃ supplementation (10 nM) induced significant hypomethylation of the REN silencer (P < 0.050), which was linked to a significant reduction in REN expression (P < 0.010) but had no effect on enhancer methylation. In addition, 1,25(OH)₂D₃ increased VDR (P < 0.05), as well as TET1 (P < 0.05) expression, suggesting an association between 1,25(OH)₂D₃ and DNA methylation. Thus, it appears that the silencer element, which is controlled by DNA methylation and influenced by 1,25(OH)₂D₃, plays an essential role in regulating REN expression.

Ctcf is required for renin expression and maintenance of the structural integrity of the kidney

Renin cells are crucial for the regulation of blood pressure and fluid electrolyte homeostasis. We have recently shown that renin cells possess unique chromatin features at regulatory regions throughout the genome that may determine the identity and memory of the renin phenotype. The 3-D structure of chromatin may be equally important in the determination of cell identity and fate. CCCTC-binding factor (Ctcf) is a highly conserved chromatin organizer that may regulate the renin phenotype by controlling chromatin structure. We found that Ctcf binds at several conserved DNA sites surrounding and within the renin locus, suggesting that Ctcf may regulate the transcriptional activity of renin cells. In fact, deletion of Ctcf in cells of the renin lineage led to decreased endowment of renin-expressing cells accompanied by decreased circulating renin, hypotension, and severe morphological abnormalities of the kidney, including defects in arteriolar branching, and ultimately renal failure. We conclude that control of chromatin architecture by Ctcf is necessary for the appropriate expression of renin, control of renin cell number and structural integrity of the kidney.