Summary of Study ST002819

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 IDST002819
Study TitleEvaluation of Novel Candidate Filtration Markers from a Global Metabolomics Discovery for Glomerular Filtration Rate Estimation (MDRD)
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
SA3029312908197MDRD
SA3029322908198MDRD
SA3029332908200MDRD
SA3029342908196MDRD
SA3029352908199MDRD
SA3029362908194MDRD
SA3029372908191MDRD
SA3029382908192MDRD
SA3029392908193MDRD
SA3029402908201MDRD
SA3029412908195MDRD
SA3029422908203MDRD
SA3029432908209MDRD
SA3029442908210MDRD
SA3029452908211MDRD
SA3029462908212MDRD
SA3029472908208MDRD
SA3029482908207MDRD
SA3029492908190MDRD
SA3029502908204MDRD
SA3029512908205MDRD
SA3029522908206MDRD
SA3029532908202MDRD
SA3029542908189MDRD
SA3029552908174MDRD
SA3029562908175MDRD
SA3029572908176MDRD
SA3029582908177MDRD
SA3029592908173MDRD
SA3029602908172MDRD
SA3029612908168MDRD
SA3029622908169MDRD
SA3029632908170MDRD
SA3029642908171MDRD
SA3029652908178MDRD
SA3029662908179MDRD
SA3029672908185MDRD
SA3029682908186MDRD
SA3029692908187MDRD
SA3029702908188MDRD
SA3029712908184MDRD
SA3029722908183MDRD
SA3029732908180MDRD
SA3029742908181MDRD
SA3029752908182MDRD
SA3029762908213MDRD
SA3029772908215MDRD
SA3029782908244MDRD
SA3029792908245MDRD
SA3029802908246MDRD
SA3029812908247MDRD
SA3029822908243MDRD
SA3029832908242MDRD
SA3029842908238MDRD
SA3029852908239MDRD
SA3029862908240MDRD
SA3029872908241MDRD
SA3029882908248MDRD
SA3029892908249MDRD
SA3029902908256MDRD
SA3029912908257MDRD
SA3029922908258MDRD
SA3029932908259MDRD
SA3029942908255MDRD
SA3029952908254MDRD
SA3029962908250MDRD
SA3029972908251MDRD
SA3029982908252MDRD
SA3029992908253MDRD
SA3030002908237MDRD
SA3030012908236MDRD
SA3030022908221MDRD
SA3030032908222MDRD
SA3030042908223MDRD
SA3030052908224MDRD
SA3030062908220MDRD
SA3030072908219MDRD
SA3030082908167MDRD
SA3030092908216MDRD
SA3030102908217MDRD
SA3030112908218MDRD
SA3030122908225MDRD
SA3030132908226MDRD
SA3030142908232MDRD
SA3030152908233MDRD
SA3030162908234MDRD
SA3030172908235MDRD
SA3030182908231MDRD
SA3030192908230MDRD
SA3030202908227MDRD
SA3030212908228MDRD
SA3030222908229MDRD
SA3030232908214MDRD
SA3030242908165MDRD
SA3030252908103MDRD
SA3030262908104MDRD
SA3030272908105MDRD
SA3030282908106MDRD
SA3030292908102MDRD
SA3030302908101MDRD
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