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      Call for Papers: Digital Platforms and Artificial Intelligence in Dementia

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      Call for Papers: Epidemiology of CKD and its Complications

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      Combined Genetic Association and Differed Expression Analysis of UBE2L3 Uncovers a Genetic Regulatory Role of (Immuno)proteasome in IgA Nephropathy

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          Abstract

          Introduction

          IgA nephropathy (IgAN) is a leading cause of end-stage renal disease. The exact pathogenesis of IgAN is not well defined, but some genetic studies have led to a novel discovery that the (immuno)proteasome probably plays an important role in IgAN.

          Methods

          We firstly analyzed the association of variants in the UBE2L3 region with susceptibility to IgAN in 3,495 patients and 9,101 controls, and then analyzed the association between lead variant and clinical phenotypes in 1,803 patients with regular follow-up data. The blood mRNA levels of members of the ubiquitin-proteasome system including UBE2L3 were analyzed in peripheral blood mononuclear cells from 53 patients and 28 healthy controls. The associations between UBE2L3 and the expression levels of genes involved in Gd-IgA1 production were also explored.

          Results

          The rs131654 showed the most significant association signal in UBE2L3 region (OR: 1.10, 95% CI: 1.04–1.16, p = 2.29 × 10 −3), whose genotypes were also associated with the levels of Gd-IgA1 ( p = 0.04). The rs131654 was observed to exert cis-eQTL effects on UBE2L3 in various tissues and cell types, particularly in immune cell types in multiple databases. The UBE2L3, LUBAC, and proteasome subunits were highly expressed in patients compared with healthy controls. High expression levels of UBE2L3 were not only associated with higher proteinuria ( r = 0.34, p = 0.01) and lower eGFR ( r = −0.28, p = 0.04), but also positively correlated with the gene expression of LUBAC and other proteasome subunits. Additionally, mRNA expression levels of UBE2L3 were also positively correlated with IL-6 and RELA, but negatively correlated with the expression levels of the key enzyme in the process of glycosylation including C1GALT1 and C1GALT1C1.

          Conclusion

          In conclusion, by combined genetic association and differed expression analysis of UBE2L3, our data support a role of genetically conferred dysregulation of the (immuno)proteasome in regulating galactose-deficient IgA1 in the development of IgAN.

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          Most cited references32

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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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              METAL: fast and efficient meta-analysis of genomewide association scans

              Summary: METAL provides a computationally efficient tool for meta-analysis of genome-wide association scans, which is a commonly used approach for improving power complex traits gene mapping studies. METAL provides a rich scripting interface and implements efficient memory management to allow analyses of very large data sets and to support a variety of input file formats. Availability and implementation: METAL, including source code, documentation, examples, and executables, is available at http://www.sph.umich.edu/csg/abecasis/metal/ Contact: goncalo@umich.edu

                Author and article information

                Journal
                Kidney Dis (Basel)
                Kidney Dis (Basel)
                KDD
                KDD
                Kidney Diseases
                S. Karger AG (Basel, Switzerland )
                2296-9381
                2296-9357
                2 March 2024
                June 2024
                : 10
                : 3
                : 167-180
                Affiliations
                [a ]Renal Division, Peking University First Hospital, Beijing, China
                [b ]Kidney Genetics Center, Peking University Institute of Nephrology, Beijing, China
                [c ]Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
                [d ]Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education, Beijing, China
                [e ]Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
                [f ]State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
                Author notes
                Correspondence to: Xu-Jie Zhou, zhouxujie@ 123456bjmu.edu.cn

                Lin-lin Xu, Ting Gan, and Yang Li contributed equally to this work.

                Article
                537987
                10.1159/000537987
                11149991
                38835407
                0d2c0db5-9598-4d9f-a1c1-f6536af3f50b
                © 2024 The Author(s). Published by S. Karger AG, Basel

                This article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC) ( http://www.karger.com/Services/OpenAccessLicense). Usage and distribution for commercial purposes requires written permission.

                History
                : 12 October 2023
                : 20 February 2024
                : 2024
                Page count
                Figures: 5, Tables: 2, References: 27, Pages: 14
                Funding
                Support was provided by National Science Foundation of China (82000680, 82022010, 82131430172, 82370709, 8197061382070733, and 82070731); Beijing Natural Science Foundation (Z190023); Academy of Medical Sciences – Newton Advanced Fellowship (NAFR13\1033); King’s College London – Peking University Health Science Center Joint Institute for Medical Research (BMU2021KCL004); Fok Ying Tung Education Foundation (171030); Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (2019-I2M-5-046, 2020-JKCS-009); and National High Level Hospital Clinical Research Funding (Interdisciplinary Clinical Research Project of Peking University First Hospital, 2022CR41). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article

                iga nephropathy,immunoproteasome,ubiquitin-conjugating enzyme,ubiquitin-proteasome system

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