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      Genetics of osteopontin in patients with chronic kidney disease: The German Chronic Kidney Disease study

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          Abstract

          Osteopontin (OPN), encoded by SPP1, is a phosphorylated glycoprotein predominantly synthesized in kidney tissue. Increased OPN mRNA and protein expression correlates with proteinuria, reduced creatinine clearance, and kidney fibrosis in animal models of kidney disease. But its genetic underpinnings are incompletely understood. We therefore conducted a genome-wide association study (GWAS) of OPN in a European chronic kidney disease (CKD) population. Using data from participants of the German Chronic Kidney Disease (GCKD) study (N = 4,897), a GWAS (minor allele frequency [MAF]≥1%) and aggregated variant testing (AVT, MAF<1%) of ELISA-quantified serum OPN, adjusted for age, sex, estimated glomerular filtration rate (eGFR), and urinary albumin-to-creatinine ratio (UACR) was conducted. In the project, GCKD participants had a mean age of 60 years (SD 12), median eGFR of 46 mL/min/1.73m 2 (p25: 37, p75: 57) and median UACR of 50 mg/g (p25: 9, p75: 383). GWAS revealed 3 loci (p<5.0E-08), two of which replicated in the population-based Young Finns Study (YFS) cohort (p<1.67E-03): rs10011284, upstream of SPP1 encoding the OPN protein and related to OPN production, and rs4253311, mapping into KLKB1 encoding prekallikrein (PK), which is processed to kallikrein (KAL) implicated through the kinin-kallikrein system (KKS) in blood pressure control, inflammation, blood coagulation, cancer, and cardiovascular disease. The SPP1 gene was also identified by AVT (p = 2.5E-8), comprising 7 splice-site and missense variants. Among others, downstream analyses revealed colocalization of the OPN association signal at SPP1 with expression in pancreas tissue, and at KLKB1 with various plasma proteins in trans, and with phenotypes (bone disorder, deep venous thrombosis) in human tissue. In summary, this GWAS of OPN levels revealed two replicated associations. The KLKB1 locus connects the function of OPN with PK, suggestive of possible further post-translation processing of OPN. Further studies are needed to elucidate the complex role of OPN within human (patho)physiology.

          Author summary

          Osteopontin (OPN) is involved in many (patho)physiological processes of the human body. Among others, it is known to be associated with adverse kidney outcomes. Since its genetic underpinnings are incompletely understood, we conducted a genome-wide association study of OPN in a European chronic kidney disease (CKD) population (N = 4,897). Of the three detected signals, two could be replicated within a population-based study of Finns. One locus is located upstream of SPP1 which encodes the OPN protein and is related to OPN production. This gene was also disclosed by an analysis of rare variants, all presumably effecting the gene product. Another locus maps into KLKB1 encoding prekallikrein (PK) that after processing to kallikrein (KAL) is implicated in blood pressure control and inflammation among others. Overall, our results highlight the multi-functional role of OPN and its possible pathological role in CKD. Further studies are needed to elucidate the complex role of OPN in humans.

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            PLINK: a tool set for whole-genome association and population-based linkage analyses.

            Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
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              A new equation to estimate glomerular filtration rate.

              Equations to estimate glomerular filtration rate (GFR) are routinely used to assess kidney function. Current equations have limited precision and systematically underestimate measured GFR at higher values. To develop a new estimating equation for GFR: the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Cross-sectional analysis with separate pooled data sets for equation development and validation and a representative sample of the U.S. population for prevalence estimates. Research studies and clinical populations ("studies") with measured GFR and NHANES (National Health and Nutrition Examination Survey), 1999 to 2006. 8254 participants in 10 studies (equation development data set) and 3896 participants in 16 studies (validation data set). Prevalence estimates were based on 16,032 participants in NHANES. GFR, measured as the clearance of exogenous filtration markers (iothalamate in the development data set; iothalamate and other markers in the validation data set), and linear regression to estimate the logarithm of measured GFR from standardized creatinine levels, sex, race, and age. In the validation data set, the CKD-EPI equation performed better than the Modification of Diet in Renal Disease Study equation, especially at higher GFR (P < 0.001 for all subsequent comparisons), with less bias (median difference between measured and estimated GFR, 2.5 vs. 5.5 mL/min per 1.73 m(2)), improved precision (interquartile range [IQR] of the differences, 16.6 vs. 18.3 mL/min per 1.73 m(2)), and greater accuracy (percentage of estimated GFR within 30% of measured GFR, 84.1% vs. 80.6%). In NHANES, the median estimated GFR was 94.5 mL/min per 1.73 m(2) (IQR, 79.7 to 108.1) vs. 85.0 (IQR, 72.9 to 98.5) mL/min per 1.73 m(2), and the prevalence of chronic kidney disease was 11.5% (95% CI, 10.6% to 12.4%) versus 13.1% (CI, 12.1% to 14.0%). The sample contained a limited number of elderly people and racial and ethnic minorities with measured GFR. The CKD-EPI creatinine equation is more accurate than the Modification of Diet in Renal Disease Study equation and could replace it for routine clinical use. National Institute of Diabetes and Digestive and Kidney Diseases.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: MethodologyRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: MethodologyRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: Funding acquisitionRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: Funding acquisitionRole: InvestigationRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: Funding acquisitionRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                PLoS Genetics
                Public Library of Science (San Francisco, CA USA )
                1553-7390
                1553-7404
                6 April 2022
                April 2022
                : 18
                : 4
                : e1010139
                Affiliations
                [1 ] Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, Germany
                [2 ] Faculty of Biology, University of Freiburg, Freiburg, Germany
                [3 ] Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Freiburg, Germany
                [4 ] Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
                [5 ] Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
                [6 ] Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
                [7 ] Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
                [8 ] Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
                [9 ] Centre for Population Health Research, University of Turku and Turku University Hospital, Turku Finland
                [10 ] Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
                [11 ] Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
                [12 ] Department of Nephrology and Medical Intensive Care, Charité, University-Medicine, Berlin, Germany
                [13 ] Department of Medicine IV, Nephrology and Primary Care, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, Germany
                Newcastle University, UNITED KINGDOM
                Author notes

                The authors have declared that no competing interests exist.

                ¶ a list of investigators participating in the GCKD Study can be found in S1 Information

                Author information
                https://orcid.org/0000-0003-2651-8791
                https://orcid.org/0000-0001-7057-7663
                https://orcid.org/0000-0001-9649-281X
                https://orcid.org/0000-0002-5605-5196
                https://orcid.org/0000-0002-6678-7964
                https://orcid.org/0000-0003-3823-0920
                https://orcid.org/0000-0003-2263-447X
                https://orcid.org/0000-0002-7541-5310
                Article
                PGENETICS-D-21-01377
                10.1371/journal.pgen.1010139
                9015153
                35385482
                583bce71-8f7f-4edb-b7cb-8081706e7ab7
                © 2022 Cheng et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 13 October 2021
                : 9 March 2022
                Page count
                Figures: 3, Tables: 3, Pages: 23
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung;
                Award ID: 01ZX1912B
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: 431984000 SFB 1453
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung;
                Award ID: 01ER0804
                Funded by: the KfH Foundation for Preventive Medicine
                Funded by: funder-id http://dx.doi.org/10.13039/501100009109, Pharmaceuticals Bayer;
                Funded by: Academy of Finland
                Award ID: 322098, 286284, 134309 (Eye), 126925, 121584, 124282, 129378 (Salve), 117787 (Gendi), and 41071 (Skidi)
                Funded by: Social Insurence Institution of Finland
                Funded by: Competitive State Research Financing of the Expert Responsibility area of Kuopio, Tampere and Turku University Hospitals
                Award ID: X51001
                Funded by: Juho Vainio Foundation
                Funded by: funder-id http://dx.doi.org/10.13039/501100008484, Paavo Nurmen Säätiö;
                Funded by: Finnish Foundation for Cardiovascular Research
                Funded by: Finnish Cultural Foundation
                Funded by: The Sigrid Juselius Foundation
                Funded by: Tampere Tuberculosis Foundation
                Funded by: funder-id http://dx.doi.org/10.13039/501100004756, Emil Aaltosen Säätiö;
                Funded by: funder-id http://dx.doi.org/10.13039/100010114, Yrjö Jahnssonin Säätiö;
                Funded by: funder-id http://dx.doi.org/10.13039/501100004325, Signe ja Ane Gyllenbergin Säätiö;
                Funded by: Diabetes Research Foundation of Finnish Diabetes Association
                Funded by: funder-id http://dx.doi.org/10.13039/501100007601, Horizon 2020;
                Award ID: No 848146 (To Aition) and No 755320 (TAXINOMISIS)
                Funded by: European Research Council
                Award ID: No 742927 (MULTIEPIGEN project)
                Funded by: Tampere University Hospital Supporting Foundation
                Funded by: Finnish Society of Clinical Chemistry
                The work of UTS was supported within the e:Med ( https://www.sys-med.de/en/) junior consortium CKDNapp ( https://ckdn.app/), which is funded by grants from the German Ministry of Education and Research (BMBF, grant number 01ZX1912B; https://www.gesundheitsforschung-bmbf.de/de/ckdnapp-entwicklung-der-chronic-kidney-disease-nephrologists-app-10066.php). The work of PS was partially funded by German Research Foundation (DFG) Project-ID 431984000 - SFB 1453. The GCKD study was funded by grants from the BMBF (grant number 01ER0804) and the KfH Foundation for Preventive Medicine ( https://www.kfh-stiftung-praeventivmedizin.de/content/stiftung) and corporate sponsors. Genotyping and measurements of osteopontin were supported by Bayer Pharma AG ( https://www.bayer.com/en/). The Young Finns Study has been financially supported by the Academy of Finland ( https://www.aka.fi/en/): grants 322098, 286284, 134309 (Eye), 126925, 121584, 124282, 129378 (Salve), 117787 (Gendi), and 41071 (Skidi); the Social Insurance Institution of Finland ( https://www.kela.fi/web/en/); Competitive State Research Financing of the Expert Responsibility area of Kuopio, Tampere and Turku University Hospitals (grant X51001; https://www.vsshp.fi/en/tutkijoille/rahoitus/Pages/default.aspx); Juho Vainio Foundation ( https://juhovainionsaatio.fi/en/juho-vainio-foundation/); Paavo Nurmi Foundation ( https://www.paavonurmensaatio.fi/saatio_e3.htm); Finnish Foundation for Cardiovascular Research ( https://www.sydantutkimussaatio.fi/en/foundation); Finnish Cultural Foundation ( https://skr.fi/en); The Sigrid Juselius Foundation ( https://www.sigridjuselius.fi/en/); Tampere Tuberculosis Foundation ( http://www.tuberkuloosisaatio.fi/); Emil Aaltonen Foundation ( https://emilaaltonen.fi/apurahat/in-english/); Yrjö Jahnsson Foundation ( https://www.yjs.fi/en/); Signe and Ane Gyllenberg Foundation ( https://gyllenbergs.fi/en/); Diabetes Research Foundation of Finnish Diabetes Association ( https://www.diabetes.fi/en/finnish_diabetes_association/association/the_diabetes_research_foundation). This project has received funding from the European Union’s Horizon 2020 research and innovation programme ( https://ec.europa.eu/programmes/horizon2020/en/home) under grant agreements No 848146 (To Aition) and No 755320 (TAXINOMISIS). This project has received funding from the European Research Council (ERC; https://erc.europa.eu/) advanced grants under grant agreement No 742927 (MULTIEPIGEN project); Tampere University Hospital Supporting Foundation ( https://www.tays.fi/en-US/Research_and_development) and Finnish Society of Clinical Chemistry ( https://www.ifcc.org/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We acknowledge support by the Open Access Publication Fund of the University of Freiburg.
                Categories
                Research Article
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Genome-Wide Association Studies
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Genome-Wide Association Studies
                Biology and Life Sciences
                Genetics
                Human Genetics
                Genome-Wide Association Studies
                Biology and Life Sciences
                Genetics
                Single Nucleotide Polymorphisms
                Medicine and Health Sciences
                Nephrology
                Renal Diseases
                Chronic Kidney Disease
                Biology and Life Sciences
                Anatomy
                Renal System
                Kidneys
                Medicine and Health Sciences
                Anatomy
                Renal System
                Kidneys
                Biology and Life Sciences
                Genetics
                Genetic Loci
                Medicine and Health Sciences
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                Cardiovascular Diseases
                Medicine and Health Sciences
                Cardiology
                Cardiovascular Medicine
                Cardiovascular Diseases
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                Biochemistry
                Proteins
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                Custom metadata
                vor-update-to-uncorrected-proof
                2022-04-18
                Public posting of individual level participant data is not covered by the informed patient consent form. As stated in the patient consent form and approved by the Ethics Committees, a dataset containing pseudonyms can be obtained by collaborating scientists upon approval of a scientific project proposal by the steering committee of the GCKD study: ( http://gckd.org). Complete summary statistics used in this project from the GCKD study can be obtained here: https://nxc-1453.imbi.uni-freiburg.de/s/gGrGW5xZRNPEHNc.

                Genetics
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