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      Transcriptional Profiling of Normal, Stenotic, and Regurgitant Human Aortic Valves

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          Abstract

          The genetic mechanisms underlying aortic stenosis (AS) and aortic insufficiency (AI) disease progression remain unclear. We hypothesized that normal aortic valves and those with AS or AI all exhibit unique transcriptional profiles. Normal control (NC) aortic valves were collected from non-matched donor hearts that were otherwise acceptable for transplantation ( n = 5). Valves with AS or AI ( n = 5, each) were collected from patients undergoing surgical aortic valve replacement. High-throughput sequencing of total RNA revealed 6438 differentially expressed genes (DEGs) for AS vs. NC, 4994 DEGs for AI vs. NC, and 2771 DEGs for AS vs. AI. Among 21 DEGs of interest, APCDD1L, CDH6, COL10A1, HBB, IBSP, KRT14, PLEKHS1, PRSS35, and TDO2 were upregulated in both AS and AI compared to NC, whereas ALDH1L1, EPHB1, GPX3, HIF3A, and KCNT1 were downregulated in both AS and AI ( p < 0.05). COL11A1, H19, HIF1A, KCNJ6, PRND, and SPP1 were upregulated only in AS, and NPY was downregulated only in AS ( p < 0.05). The functional network for AS clustered around ion regulation, immune regulation, and lipid homeostasis, and that for AI clustered around ERK1/2 regulation. Overall, we report transcriptional profiling data for normal human aortic valves from non-matched donor hearts that were acceptable for transplantation and demonstrated that valves with AS and AI possess unique genetic signatures. These data create a roadmap for the development of novel therapeutics to treat AS and AI.

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          Novel modulator for endothelial adhesion molecules: adipocyte-derived plasma protein adiponectin.

          Among the many adipocyte-derived endocrine factors, we recently found an adipocyte-specific secretory protein, adiponectin, which was decreased in obesity. Although obesity is associated with increased cardiovascular mortality and morbidity, the molecular basis for the link between obesity and vascular disease has not been fully clarified. The present study investigated whether adiponectin could modulate endothelial function and relate to coronary disease. For the in vitro study, human aortic endothelial cells (HAECs) were preincubated for 18 hours with the indicated amount of adiponectin, then exposed to tumor necrosis factor-alpha (TNF-alpha) (10 U/mL) or vehicle for the times indicated. The adhesion of human monocytic cell line THP-1 cells to HAECs was determined by adhesion assay. The surface expression of vascular cell adhesion molecule-1 (VCAM-1), endothelial-leukocyte adhesion molecule-1 (E-selectin), and intracellular adhesion molecule-1 (ICAM-1) was measured by cell ELISA. Physiological concentrations of adiponectin dose-dependently inhibited TNF-alpha-induced THP-1 adhesion and expression of VCAM-1, E-selectin, and ICAM-1 on HAECs. For the in vivo study, the concentrations of adiponectin in human plasma were determined by a sandwich ELISA system that we recently developed. Plasma adiponectin concentrations were significantly lower in patients with coronary artery disease than those in age- and body mass index-adjusted control subjects. These observations suggest that adiponectin modulates endothelial inflammatory response and that the measurement of plasma adiponectin levels may be helpful in assessment of CAD risk.
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            Aortic Stenosis

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              Why, When and How to Adjust Your P Values?

              Currently, numerous papers are published reporting analysis of biological data at different omics levels by making statistical inferences. Of note, many studies, as those published in this Journal, report association of gene(s) at the genomic and transcriptomic levels by undertaking appropriate statistical tests. For instance, genotype, allele or haplotype frequencies at the genomic level or normalized expression levels at the transcriptomic level are compared between the case and control groups using the Chi-square/Fisher’s exact test or independent (i.e. two-sampled) t-test respectively, with this culminating into a single numeric, namely the P value (or the degree of the false positive rate), which is used to make or break the outcome of the association test. This approach has flaws but nevertheless remains a standard and convenient approach in association studies. However, what becomes a critical issue is that the same cut-off is used when ‘multiple’ tests are undertaken on the same case-control (or any pairwise) comparison. Here, in brevity, we present what the P value represents, and why and when it should be adjusted. We also show, with worked examples, how to adjust P values for multiple testing in the R environment for statistical computing (http://www.R-project.org).
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                Author and article information

                Journal
                Genes (Basel)
                Genes (Basel)
                genes
                Genes
                MDPI
                2073-4425
                14 July 2020
                July 2020
                : 11
                : 7
                : 789
                Affiliations
                [1 ]Department of Cardiothoracic Surgery, Stanford University, Stanford, CA 94305, USA; christina.greene@ 123456cardio.chboston.org (C.L.G.); kevinjaatinen@ 123456gmail.com (K.J.J.); hanjay@ 123456stanford.edu (H.W.); tkoyano3@ 123456stanford.edu (T.K.K.); msbilbao@ 123456stanfordhealthcare.org (M.S.B.)
                [2 ]Stanford Cardiovascular Institute, Stanford University, Stanford, CA 94305, USA
                [3 ]Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
                Author notes
                [* ]Correspondence: joswoo@ 123456stanford.edu ; Tel.: +1-650-725-3828
                Author information
                https://orcid.org/0000-0002-2367-5591
                Article
                genes-11-00789
                10.3390/genes11070789
                7397246
                32674273
                4d6ff379-40e0-4ee4-bc2d-cd0e282a62b3
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 30 May 2020
                : 08 July 2020
                Categories
                Article

                aortic stenosis,aortic insufficiency,transcriptional profiling,rna sequencing

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