S M Titan1, G Venturini2, K Padilha2, G Tavares3, R Zatz3, I Bensenor4, P A Lotufo4, E P Rhee5, R I Thadhani6, A C Pereira2. 1. Nephrology Division, University of Sao Paulo Medical School, Sao Paulo, SP, Brazil. Electronic address: smotitan@gmail.com. 2. Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, Sao Paulo, SP, Brazil. 3. Nephrology Division, University of Sao Paulo Medical School, Sao Paulo, SP, Brazil. 4. Epidemiological and Clinical Research Center, Universitary Hospital, Sao Paulo Univ, Sao Paulo, Brazil. 5. Division of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States; Division of Endocrinology, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States. 6. Division of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States; Vice Dean of Research, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Abstract
BACKGROUND: Metabolomics can be used to identify novel metabolites related to renal function and that could therefore be used for estimating GFR. We evaluated metabolites replicated and related to eGFR in 3 studies (CKD and general population). METHODS: Metabolomics was performed by GC-MS. The Progredir Cohort (n = 454, class 3 and 4 CKD) was used as the derivation study and adjusted linear regression models on eGFR-CKDEPI were built. Bonferroni correction was applied for selecting metabolites to be independently validated in the Diabetic Nephropathy Study (n = 56, macroalbuminuric DN) and in the Baependi Heart Study (BHS, n = 1145, general population). RESULTS: In the Progredir Cohort, 72 metabolites where associated with eGFR. Of those, 11 were also significantly associated to eGFR in the DN Study and 8 in the BHS. Four metabolites were replicated and significantly associated to eGFR in all 3 studies: d-threitol, myo-inositol, 4-deoxierythronic acid and galacturonic acid. In addition, pseudouridine was strongly correlated to eGFR only in the 2 CKD populations. CONCLUSIONS: Our results demonstrate metabolites that are potential biomarkers of renal function: d-threitol, myo-inositol, 4-deoxierythronic acid, galacturonic acid and pseudouridine. Further investigation is needed to determine their performance against otherwise gold-standard methods, most notably among those with normal eGFR.
BACKGROUND: Metabolomics can be used to identify novel metabolites related to renal function and that could therefore be used for estimating GFR. We evaluated metabolites replicated and related to eGFR in 3 studies (CKD and general population). METHODS: Metabolomics was performed by GC-MS. The Progredir Cohort (n = 454, class 3 and 4 CKD) was used as the derivation study and adjusted linear regression models on eGFR-CKDEPI were built. Bonferroni correction was applied for selecting metabolites to be independently validated in the Diabetic Nephropathy Study (n = 56, macroalbuminuric DN) and in the Baependi Heart Study (BHS, n = 1145, general population). RESULTS: In the Progredir Cohort, 72 metabolites where associated with eGFR. Of those, 11 were also significantly associated to eGFR in the DN Study and 8 in the BHS. Four metabolites were replicated and significantly associated to eGFR in all 3 studies: d-threitol, myo-inositol, 4-deoxierythronic acid and galacturonic acid. In addition, pseudouridine was strongly correlated to eGFR only in the 2 CKD populations. CONCLUSIONS: Our results demonstrate metabolites that are potential biomarkers of renal function: d-threitol, myo-inositol, 4-deoxierythronic acid, galacturonic acid and pseudouridine. Further investigation is needed to determine their performance against otherwise gold-standard methods, most notably among those with normal eGFR.
Authors: Silvia M Titan; Gabriela Venturini; Kallyandra Padilha; Alessandra C Goulart; Paulo A Lotufo; Isabela J Bensenor; Jose E Krieger; Ravi I Thadhani; Eugene P Rhee; Alexandre C Pereira Journal: PLoS One Date: 2019-03-18 Impact factor: 3.240