0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      SGLT2 inhibition, high-density lipoprotein, and kidney function: a mendelian randomization study

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Sodium-glucose cotransporter 2 (SGLT2) inhibition is recognized for its evident renoprotective benefits in diabetic renal disease. Recent data suggest that SGLT2 inhibition also slows down kidney disease progression and reduces the risk of acute kidney injury, regardless of whether the patient has diabetes or not, but the mechanism behind these observed effects remains elusive. The objective of this study is to utilize a mendelian randomization (MR) methodology to comprehensively examine the influence of metabolites in circulation regarding the impact of SGLT2 inhibition on kidney function.

          Methods

          We used a MR study to obtain associations between genetic proxies for SGLT2 inhibition and kidney function. We retrieved the most recent and comprehensive summary statistics from genome-wide association studies (GWAS) that have been previously published and involved kidney function parameters such as estimated glomerular filtration rate (eGFR), urine albumin-to-creatinine ratio (UACR), and albuminuria. Additionally, we included blood metabolite data from 249 biomarkers in the UK Biobank for a more comprehensive analysis. We performed MR analyses to explore the causal relationships between SGLT2 inhibition and kidney function and two-step MR to discover potential mediating metabolites.

          Results

          The study found that a decrease in HbA1c levels by one standard deviation, which is genetically expected to result in SGLT2 inhibition, was linked to a decreased likelihood of developing type 2 diabetes mellitus (T2DM) (odds ratio [OR] = 0.55 [95% CI 0.35, 0.85], P = 0.007). Meanwhile, SGLT2 inhibition also protects eGFR (β = 0.05 [95% CI 0.03, 0.08], P = 2.45 × 10 − 5) and decreased UACR (-0.18 [95% CI -0.33, -0.02], P = 0.025) and albuminuria (-1.07 [95% CI -1.58, -0.57], P = 3.60 × 10 − 5). Furthermore, the study found that of the 249 metabolites present in the blood, only one metabolite, specifically the concentration of small high-density lipoprotein (HDL) particles, was significantly correlated with both SGLT2 inhibition and kidney function. This metabolite was found to play a crucial role in mediating the improvement of renal function through the use of SGLT2 inhibition (β = 0.01 [95% CI 0.005, 0.018], P = 0.001), with a mediated proportion of 13.33% (95% CI [5.71%, 26.67%], P = 0.020).

          Conclusions

          The findings of this investigation provide evidence in favor of a genetically anticipated biological linkage between the inhibition of SGLT2, the presence of circulating metabolites, and renal function. The findings demonstrate that the protective effect of SGLT2 inhibition on renal function is mostly mediated by HDL particle concentrations in circulating metabolites. These results offer significant theoretical support for both the preservation of renal function and a better comprehension of the mechanisms underlying SGLT2 inhibition.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12944-024-02072-6.

          Related collections

          Most cited references33

          • Record: found
          • Abstract: found
          • Article: not found

          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.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The GTEx Consortium atlas of genetic regulatory effects across human tissues

            (2020)
            The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the version 8 data, examining 15,201 RNA-sequencing samples from 49 tissues of 838 postmortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue specificity of genetic effects and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Mendelian randomization: using genes as instruments for making causal inferences in epidemiology.

              Observational epidemiological studies suffer from many potential biases, from confounding and from reverse causation, and this limits their ability to robustly identify causal associations. Several high-profile situations exist in which randomized controlled trials of precisely the same intervention that has been examined in observational studies have produced markedly different findings. In other observational sciences, the use of instrumental variable (IV) approaches has been one approach to strengthening causal inferences in non-experimental situations. The use of germline genetic variants that proxy for environmentally modifiable exposures as instruments for these exposures is one form of IV analysis that can be implemented within observational epidemiological studies. The method has been referred to as 'Mendelian randomization', and can be considered as analogous to randomized controlled trials. This paper outlines Mendelian randomization, draws parallels with IV methods, provides examples of implementation of the approach and discusses limitations of the approach and some methods for dealing with these.
                Bookmark

                Author and article information

                Contributors
                Wangdeguang@ahmu.edu.cn
                Journal
                Lipids Health Dis
                Lipids Health Dis
                Lipids in Health and Disease
                BioMed Central (London )
                1476-511X
                20 March 2024
                20 March 2024
                2024
                : 23
                : 84
                Affiliations
                [1 ]GRID grid.452696.a, ISNI 0000 0004 7533 3408, Department of Nephrology, , the Second Affiliated Hospital of Anhui Medical University, ; 678 Furong Road, Hefei, 230601 Anhui China
                [2 ]GRID grid.452696.a, ISNI 0000 0004 7533 3408, Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, , the Second Affiliated Hospital of Anhui Medical University, ; 678 Furong Road, Hefei, 230601 Anhui China
                Article
                2072
                10.1186/s12944-024-02072-6
                10953263
                38509588
                4b61dd46-3b63-42bc-98c9-6a4b9072a22e
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 3 January 2024
                : 5 March 2024
                Funding
                Funded by: Anhui Provincial Natural Science Foundation
                Award ID: 2008085MH244
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Biochemistry
                sodium-glucose cotransporter 2 inhibition,high-density lipoprotein,kidney function,mendelian randomization

                Comments

                Comment on this article