Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: Greater adherence to plant-based diets is associated with a lower risk of incident chronic kidney disease (CKD). Metabolomics can help identify blood biomarkers of plant-based diets and enhance understanding of underlying mechanisms.
Objectives: Using untargeted metabolomics, we aimed to identify metabolites associated with 4 plant-based diet indices (PDIs) (overall PDI, provegetarian diet, healthful PDI, and unhealthful PDI) and incident CKD in 2 subgroups within the Atherosclerosis Risk in Communities study.
Methods: We calculated 4 PDIs based on participants' responses on an FFQ. We used multivariable linear regression to examine the association between 4 PDIs and 374 individual metabolites, adjusting for confounders. We used Cox proportional hazards regression to evaluate associations between PDI-related metabolites and incident CKD. Estimates were meta-analyzed across 2 subgroups (n1 = 1762; n2 = 1960). We calculated C-statistics to assess whether metabolites improved the prediction of those in the highest quintile compared to the lower 4 quintiles of PDIs, and whether PDI- and CKD-related metabolites predicted incident CKD beyond the CKD prediction model.
Results: We identified 82 significant PDI-metabolite associations (overall PDI = 27; provegetarian = 17; healthful PDI = 20; unhealthful PDI = 18); 11 metabolites overlapped across the overall PDI, provegetarian diet, and healthful PDI. The addition of metabolites improved prediction of those in the highest quintile as opposed to the lower 4 quintiles of PDIs compared with participant characteristics alone (range of differences in C-statistics = 0.026-0.104; P value ≤ 0.001 for all tests). Six PDI-related metabolites (glycerate, 1,5-anhydroglucitol, γ-glutamylalanine, γ-glutamylglutamate, γ-glutamylleucine, γ-glutamylvaline), involved in glycolysis, gluconeogenesis, pyruvate metabolism, and γ-glutamyl peptide metabolism, were significantly associated with incident CKD and improved prediction of incident CKD beyond the CKD prediction model (difference in C-statistics for 6 metabolites = 0.005; P value = 0.006).
Conclusions: In a community-based study of US adults, we identified metabolites that were related to plant-based diets and predicted incident CKD. These metabolites highlight pathways through which plant-based diets are associated with incident CKD.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9257476 | PMC |
http://dx.doi.org/10.1093/ajcn/nqac054 | DOI Listing |
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