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      Coregulation Analysis of Mechanistic Biomarkers in Autosomal Dominant Polycystic Kidney Disease

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          Abstract

          Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disorder leading to deterioration of kidney function and end stage kidney disease (ESKD). A number of molecular processes are dysregulated in ADPKD but the exact mechanism of disease progression is not fully understood. We measured protein biomarkers being linked to ADPKD-associated molecular processes via ELISA in urine and serum in a cohort of ADPKD patients as well as age, gender and eGFR matched CKD patients and healthy controls. ANOVA and t-tests were used to determine differences between cohorts. Spearman correlation coefficient analysis was performed to assess coregulation patterns of individual biomarkers and renal function. Urinary epidermal growth factor (EGF) and serum apelin (APLN) levels were significantly downregulated in ADPKD patients. Serum vascular endothelial growth factor alpha (VEGFA) and urinary angiotensinogen (AGT) were significantly upregulated in ADPKD patients as compared with healthy controls. Arginine vasopressin (AVP) was significantly upregulated in ADPKD patients as compared with CKD patients. Serum VEGFA and VIM concentrations were positively correlated and urinary EGF levels were negatively correlated with urinary AGT levels. Urinary EGF and AGT levels were furthermore significantly associated with estimated glomerular filtration rate (eGFR) in ADPKD patients. In summary, altered protein concentrations in body fluids of ADPKD patients were found for the mechanistic markers EGF, APLN, VEGFA, AGT, AVP, and VIM. In particular, the connection between EGF and AGT during progression of ADPKD warrants further investigation.

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          An automated method for finding molecular complexes in large protein interaction networks

          Background Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have already produced a wealth of data. As the size of the interaction set increases, databases and computational methods will be required to store, visualize and analyze the information in order to effectively aid in knowledge discovery. Results This paper describes a novel graph theoretic clustering algorithm, "Molecular Complex Detection" (MCODE), that detects densely connected regions in large protein-protein interaction networks that may represent molecular complexes. The method is based on vertex weighting by local neighborhood density and outward traversal from a locally dense seed protein to isolate the dense regions according to given parameters. The algorithm has the advantage over other graph clustering methods of having a directed mode that allows fine-tuning of clusters of interest without considering the rest of the network and allows examination of cluster interconnectivity, which is relevant for protein networks. Protein interaction and complex information from the yeast Saccharomyces cerevisiae was used for evaluation. Conclusion Dense regions of protein interaction networks can be found, based solely on connectivity data, many of which correspond to known protein complexes. The algorithm is not affected by a known high rate of false positives in data from high-throughput interaction techniques. The program is available from .
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            OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders

            Online Mendelian Inheritance in Man, OMIM®, is a comprehensive, authoritative and timely research resource of curated descriptions of human genes and phenotypes and the relationships between them. The new official website for OMIM, OMIM.org (http://omim.org), was launched in January 2011. OMIM is based on the published peer-reviewed biomedical literature and is used by overlapping and diverse communities of clinicians, molecular biologists and genome scientists, as well as by students and teachers of these disciplines. Genes and phenotypes are described in separate entries and are given unique, stable six-digit identifiers (MIM numbers). OMIM entries have a structured free-text format that provides the flexibility necessary to describe the complex and nuanced relationships between genes and genetic phenotypes in an efficient manner. OMIM also has a derivative table of genes and genetic phenotypes, the Morbid Map. OMIM.org has enhanced search capabilities such as genome coordinate searching and thesaurus-enhanced search term options. Phenotypic series have been created to facilitate viewing genetic heterogeneity of phenotypes. Clinical synopsis features are enhanced with UMLS, Human Phenotype Ontology and Elements of Morphology terms and image links. All OMIM data are available for FTP download and through an API. MIMmatch is a novel outreach feature to disseminate updates and encourage collaboration.
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              Tolvaptan in patients with autosomal dominant polycystic kidney disease.

              The course of autosomal dominant polycystic kidney disease (ADPKD) is often associated with pain, hypertension, and kidney failure. Preclinical studies indicated that vasopressin V(2)-receptor antagonists inhibit cyst growth and slow the decline of kidney function. In this phase 3, multicenter, double-blind, placebo-controlled, 3-year trial, we randomly assigned 1445 patients, 18 to 50 years of age, who had ADPKD with a total kidney volume of 750 ml or more and an estimated creatinine clearance of 60 ml per minute or more, in a 2:1 ratio to receive tolvaptan, a V(2)-receptor antagonist, at the highest of three twice-daily dose regimens that the patient found tolerable, or placebo. The primary outcome was the annual rate of change in the total kidney volume. Sequential secondary end points included a composite of time to clinical progression (defined as worsening kidney function, kidney pain, hypertension, and albuminuria) and rate of kidney-function decline. Over a 3-year period, the increase in total kidney volume in the tolvaptan group was 2.8% per year (95% confidence interval [CI], 2.5 to 3.1), versus 5.5% per year in the placebo group (95% CI, 5.1 to 6.0; P<0.001). The composite end point favored tolvaptan over placebo (44 vs. 50 events per 100 follow-up-years, P=0.01), with lower rates of worsening kidney function (2 vs. 5 events per 100 person-years of follow-up, P<0.001) and kidney pain (5 vs. 7 events per 100 person-years of follow-up, P=0.007). Tolvaptan was associated with a slower decline in kidney function (reciprocal of the serum creatinine level, -2.61 [mg per milliliter](-1) per year vs. -3.81 [mg per milliliter](-1) per year; P<0.001). There were fewer ADPKD-related adverse events in the tolvaptan group but more events related to aquaresis (excretion of electrolyte-free water) and hepatic adverse events unrelated to ADPKD, contributing to a higher discontinuation rate (23%, vs. 14% in the placebo group). Tolvaptan, as compared with placebo, slowed the increase in total kidney volume and the decline in kidney function over a 3-year period in patients with ADPKD but was associated with a higher discontinuation rate, owing to adverse events. (Funded by Otsuka Pharmaceuticals and Otsuka Pharmaceutical Development and Commercialization; TEMPO 3:4 ClinicalTrials.gov number, NCT00428948.).
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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                26 June 2021
                July 2021
                : 22
                : 13
                : 6885
                Affiliations
                [1 ]Department of Internal Medicine IV (Nephrology and Hypertension), Medical University Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria; Johannes.Leierer@ 123456i-med.ac.at (J.L.); Hoferdikt@ 123456gmail.com (B.H.); Susanne.Eder@ 123456i-med.ac.at (S.E.); Julia.Kerschbaum@ 123456i-med.ac.at (J.K.); Michael.Rudnicki@ 123456i-med.ac.at (M.R.); Gert.Mayer@ 123456i-med.ac.at (G.M.)
                [2 ]Medical Center Hentschelhof, 6020 Innsbruck, Austria; A.Dzien@ 123456medicalcenter-innsbruck.at
                Author notes
                Author information
                https://orcid.org/0000-0002-7884-9827
                https://orcid.org/0000-0003-2087-5691
                https://orcid.org/0000-0002-6896-2279
                Article
                ijms-22-06885
                10.3390/ijms22136885
                8269435
                34206927
                82ac98b0-45f7-44c4-b9c2-1164e057c61d
                © 2021 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 ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 12 April 2021
                : 22 June 2021
                Categories
                Article

                Molecular biology
                autosomal dominant polycystic kidney disease,mechanistic biomarkers,egfr signaling,angiogenesis

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