Summary of Study ST002820

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001762. The data can be accessed directly via it's Project DOI: 10.21228/M8ZB1D This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST002820
Study TitleEvaluation of Novel Candidate Filtration Markers from a Global Metabolomics Discovery for Glomerular Filtration Rate Estimation (AASKG1)
Study SummaryBackground: Creatinine and cystatin-C are recommended for estimating glomerular filtration rate (eGFR) but accuracy is suboptimal. Using untargeted metabolomics data, we sought to identify candidate filtration markers using a novel approach based on their maximal joint association with measured GFR (mGFR) with flexibility to consider their biological and chemical properties later. Methods: We analyzed metabolites measured in seven diverse studies of 2,851 participants on the Metabolon H4 platform that had Pearson correlations with log mGFR <-0.5. We used a stepwise approach to develop models to estimate mGFR including two to 15 metabolites with and without inclusion of creatinine and demographics. We then selected candidate filtration markers from those metabolites found >20% in models that did not demonstrate substantial overfitting in cross-validation and with small (<0.1 in absolute value) coefficients for demographics. Results: In total, 456 named metabolites were present in all studies, and 36 had correlations <-0.5 with mGFR. We developed 2,225 models including these metabolites; all had lower RMSEs and smaller coefficients for demographic variables compared to estimates using untargeted creatinine. Cross-validated RMSEs (0.187-0.213) were similar to original RMSEs for models with ≤ 10 metabolites. Our criteria identified 17 metabolites, including 12 new candidate filtration markers. Conclusion: We identified candidate metabolites with maximal joint association with mGFR and minimal association with demographic variables across varied clinical settings. Future analyses will assess metabolite biological and chemical characteristics in the path towards development of a panel eGFR that is more accurate and less reliant on demographic variables than current eGFR. ACRONYMS AASKG1: African American Study of Kidney (patient data at G1 visit). ALTOLD: Assessing Long Term Outcomes in Living Kidney Donors study. MDRD: The Modification of Diet in Renal Disease study.
Institute
Tufts Medical Center
DepartmentNephrology
Last NameInker
First NameLesley
Address800 Washington Street
EmailLesley.Inker@tuftsmedicine.org
Phone6176368783
Submit Date2023-08-17
Analysis Type DetailOther
Release Date2023-09-06
Release Version1
Lesley Inker Lesley Inker
https://dx.doi.org/10.21228/M8ZB1D
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Factors:

Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)

mb_sample_id local_sample_id study
SA3036823900716AASKG1
SA3036833900715AASKG1
SA3036843900717AASKG1
SA3036853900719AASKG1
SA3036863900720AASKG1
SA3036873900713AASKG1
SA3036883900718AASKG1
SA3036893900711AASKG1
SA3036903900707AASKG1
SA3036913900706AASKG1
SA3036923900708AASKG1
SA3036933900709AASKG1
SA3036943900721AASKG1
SA3036953900710AASKG1
SA3036963900712AASKG1
SA3036973900723AASKG1
SA3036983900732AASKG1
SA3036993900731AASKG1
SA3037003900733AASKG1
SA3037013900734AASKG1
SA3037023900736AASKG1
SA3037033900735AASKG1
SA3037043900730AASKG1
SA3037053900729AASKG1
SA3037063900724AASKG1
SA3037073900705AASKG1
SA3037083900725AASKG1
SA3037093900726AASKG1
SA3037103900728AASKG1
SA3037113900727AASKG1
SA3037123900722AASKG1
SA3037133900704AASKG1
SA3037143900684AASKG1
SA3037153900683AASKG1
SA3037163900685AASKG1
SA3037173900686AASKG1
SA3037183900688AASKG1
SA3037193900687AASKG1
SA3037203900682AASKG1
SA3037213900681AASKG1
SA3037223900676AASKG1
SA3037233900675AASKG1
SA3037243900677AASKG1
SA3037253900678AASKG1
SA3037263900680AASKG1
SA3037273900679AASKG1
SA3037283900689AASKG1
SA3037293900690AASKG1
SA3037303900699AASKG1
SA3037313900698AASKG1
SA3037323900700AASKG1
SA3037333900701AASKG1
SA3037343900703AASKG1
SA3037353900702AASKG1
SA3037363900697AASKG1
SA3037373900696AASKG1
SA3037383900692AASKG1
SA3037393900691AASKG1
SA3037403900693AASKG1
SA3037413900694AASKG1
SA3037423900695AASKG1
SA3037433900737AASKG1
SA3037443900739AASKG1
SA3037453900780AASKG1
SA3037463900779AASKG1
SA3037473900781AASKG1
SA3037483900782AASKG1
SA3037493900784AASKG1
SA3037503900783AASKG1
SA3037513900778AASKG1
SA3037523900777AASKG1
SA3037533900772AASKG1
SA3037543900771AASKG1
SA3037553900773AASKG1
SA3037563900774AASKG1
SA3037573900776AASKG1
SA3037583900775AASKG1
SA3037593900785AASKG1
SA3037603900786AASKG1
SA3037613900797AASKG1
SA3037623900796AASKG1
SA3037633900798AASKG1
SA3037643900799AASKG1
SA3037653900801AASKG1
SA3037663900800AASKG1
SA3037673900795AASKG1
SA3037683900794AASKG1
SA3037693900788AASKG1
SA3037703900787AASKG1
SA3037713900789AASKG1
SA3037723900790AASKG1
SA3037733900793AASKG1
SA3037743900792AASKG1
SA3037753900770AASKG1
SA3037763900769AASKG1
SA3037773900749AASKG1
SA3037783900748AASKG1
SA3037793900750AASKG1
SA3037803900751AASKG1
SA3037813900753AASKG1
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