دورية أكاديمية
High-Throughput Metabolomics and Diabetic Kidney Disease Progression: Evidence from the Chronic Renal Insufficiency (CRIC) Study
| العنوان: | High-Throughput Metabolomics and Diabetic Kidney Disease Progression: Evidence from the Chronic Renal Insufficiency (CRIC) Study |
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| المؤلفون: | Zhang, Jing, Fuhrer, Tobias, id_orcid:0 000-0001-5006-6874, Ye, Hongping, Kwan, Brian, Montemayor, Daniel, Tumova, Jana, Darshi, Manjula, Afshinnia, Farsad, Scialla, Julia J., Anderson, Amanda, Porter, Anna C., Taliercio, Jonathan J., Rincon-Choles, Hernan, Rao, Panduranga, Xie, Dawei, Feldman, Harold, Sauer, Uwe, id_orcid:0 000-0002-5923-0770, Sharma, Kumar, Natarajan, Loki |
| المصدر: | American Journal of Nephrology, 53 (2-3) |
| بيانات النشر: | Karger |
| سنة النشر: | 2022 |
| المجموعة: | ETH Zürich Research Collection |
| مصطلحات موضوعية: | Diabetes, Kidney disease, Metabolomics, Prognostic modeling, Lasso, Random forest, Pathways |
| الوصف: | Introduction: Metabolomics could offer novel prognostic biomarkers and elucidate mechanisms of diabetic kidney disease (DKD) progression. Via metabolomic analysis of urine samples from 995 CRIC participants with diabetes and state-of-the-art statistical modeling, we aimed to identify metabolites prognostic to DKD progression. Methods: Urine samples (N = 995) were assayed for relative metabolite abundance by untargeted flow-injection mass spectrometry, and stringent statistical criteria were used to eliminate noisy compounds, resulting in 698 annotated metabolite ions. Utilizing the 698 metabolites' ion abundance along with clinical data (demographics, blood pressure, HbA1c, eGFR, and albuminuria), we developed univariate and multivariate models for the eGFR slope using penalized (lasso) and random forest models. Final models were tested on time-to-ESKD (end-stage kidney disease) via cross-validated C-statistics. We also conducted pathway enrichment analysis and a targeted analysis of a subset of metabolites. Results: Six eGFR slope models selected 9-30 variables. In the adjusted ESKD model with highest C-statistic, valine (or betaine) and 3-(4-methyl-3-pentenyl)thiophene were associated (p < 0.05) with 44% and 65% higher hazard of ESKD per doubling of metabolite abundance, respectively. Also, 13 (of 15) prognostic amino acids, including valine and betaine, were confirmed in the targeted analysis. Enrichment analysis revealed pathways implicated in kidney and cardiometabolic disease. Conclusions: Using the diverse CRIC sample, a high-throughput untargeted assay, followed by targeted analysis, and rigorous statistical analysis to reduce false discovery, we identified several novel metabolites implicated in DKD progression. If replicated in independent cohorts, our findings could inform risk stratification and treatment strategies for patients with DKD. ; ISSN:0250-8095 ; ISSN:1421-9670 |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/application/pdf |
| اللغة: | English |
| العلاقة: | info:eu-repo/semantics/altIdentifier/wos/000761075400001; http://hdl.handle.net/20.500.11850/536916Test |
| DOI: | 10.3929/ethz-b-000536916 |
| الإتاحة: | https://doi.org/20.500.11850/536916Test https://doi.org/10.3929/ethz-b-000536916Test https://doi.org/10.1159/000521940Test https://hdl.handle.net/20.500.11850/536916Test |
| حقوق: | info:eu-repo/semantics/openAccess ; http://creativecommons.org/licenses/by-nc/4.0Test/ ; Creative Commons Attribution-NonCommercial 4.0 International |
| رقم الانضمام: | edsbas.5684CC34 |
| قاعدة البيانات: | BASE |
| DOI: | 10.3929/ethz-b-000536916 |
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