Anna Solini1, Maria Laura Manca1, Giuseppe Penno1, Giuseppe Pugliese1, Jeff E Cobb1, Ele Ferrannini1. 1. Department of Clinical and Experimental Medicine (A.S., M.L.M., G.Pe., E.F.), and Department of Mathematics (M.L.M.), University of Pisa, 56126 Pisa, Italy; Department of Clinical and Molecular Medicine (G.Pu.), "La Sapienza" University, 00185 Rome, Italy; Metabolon, Inc (J.E.C.), Durham, North Carolina 27713; and National Research Council Institute of Clinical Physiology (E.F.), 56124 Pisa, Italy.
Abstract
CONTEXT: Renal disease in type 2 diabetes mellitus (T2DM) is associated with excess morbidity/mortality. Although estimated glomerular filtration rate (eGFR) and albuminuria are routine for assessing renal impairment, novel biomarkers could improve risk stratification and prediction. OBJECTIVE: To identify specific biomarkers of progression of renal dysfunction. DESIGN: Prospective observational. SETTING: Academic diabetes clinics. PATIENTS: A total of 286 T2DM patients (age, 62 ± 8 y; glycosylated hemoglobin, 7.2 ± 0.9%; eGFR, 85 ± 20 mL · min(-1) · 1.73 m(2)). INTERVENTIONS: None. MAIN OUTCOME MEASURES: Progression of eGFR and albuminuria. RESULTS: We performed screening metabolomics in serum and urine samples by gas chromatography/mass spectroscopy (MS) and ultra-high performance liquid chromatography/MS/MS. Biomarker identification was performed by random forest using an eGFR cutoff of < 60 mL · min(-1) · 1.73 m(2) or an albumin/creatinine ratio (ACR) cutoff ≥ 30 mg/g as response variables. At follow-up, eGFR had declined by 16 [9] (median [interquartile ratio]) mL · min(-1) · 1.73 m(2), and ACR had increased by 41 [135] mg/g in patients in the respective top quartile of changes from baseline. Clinical parameters (gender, age, fasting glucose, and baseline eGFR) predicted outcome, with receiver operator characteristics curve (ROC) = 0.671. The five serum metabolites best correlated with either eGFR < 60 or ACR ≥ 30 at baseline were tested for their ability to improve clinical prediction. The sum of C-glycosyl tryptophan, pseudouridine, and N-acetylthreonine (MetIndex) raised the ROC to 0.739 (P < .0001). eGFR decline was predicted by the top MetIndex quartile (odds ratio = 5.48 [95% confidence interval, 2.23-14.47]). MetIndex also predicted an ACR increase with an odds ratio of 2.82 [1.20-7.03] and a ROC of 0.750. Top urine metabolites did not add significant predictivity. CONCLUSIONS: A limited number of circulating intermediates of amino acid and nucleotide pathways carry clinically significant predictivity for deterioration of renal function in well-controlled T2DM.
CONTEXT: Renal disease in type 2 diabetes mellitus (T2DM) is associated with excess morbidity/mortality. Although estimated glomerular filtration rate (eGFR) and albuminuria are routine for assessing renal impairment, novel biomarkers could improve risk stratification and prediction. OBJECTIVE: To identify specific biomarkers of progression of renal dysfunction. DESIGN: Prospective observational. SETTING: Academic diabetes clinics. PATIENTS: A total of 286 T2DM patients (age, 62 ± 8 y; glycosylated hemoglobin, 7.2 ± 0.9%; eGFR, 85 ± 20 mL · min(-1) · 1.73 m(2)). INTERVENTIONS: None. MAIN OUTCOME MEASURES: Progression of eGFR and albuminuria. RESULTS: We performed screening metabolomics in serum and urine samples by gas chromatography/mass spectroscopy (MS) and ultra-high performance liquid chromatography/MS/MS. Biomarker identification was performed by random forest using an eGFR cutoff of < 60 mL · min(-1) · 1.73 m(2) or an albumin/creatinine ratio (ACR) cutoff ≥ 30 mg/g as response variables. At follow-up, eGFR had declined by 16 [9] (median [interquartile ratio]) mL · min(-1) · 1.73 m(2), and ACR had increased by 41 [135] mg/g in patients in the respective top quartile of changes from baseline. Clinical parameters (gender, age, fasting glucose, and baseline eGFR) predicted outcome, with receiver operator characteristics curve (ROC) = 0.671. The five serum metabolites best correlated with either eGFR < 60 or ACR ≥ 30 at baseline were tested for their ability to improve clinical prediction. The sum of C-glycosyl tryptophan, pseudouridine, and N-acetylthreonine (MetIndex) raised the ROC to 0.739 (P < .0001). eGFR decline was predicted by the top MetIndex quartile (odds ratio = 5.48 [95% confidence interval, 2.23-14.47]). MetIndex also predicted an ACR increase with an odds ratio of 2.82 [1.20-7.03] and a ROC of 0.750. Top urine metabolites did not add significant predictivity. CONCLUSIONS: A limited number of circulating intermediates of amino acid and nucleotide pathways carry clinically significant predictivity for deterioration of renal function in well-controlled T2DM.
Authors: Jovia L Nierenberg; Jiang He; Changwei Li; Xiaoying Gu; Mengyao Shi; Alexander C Razavi; Xuenan Mi; Shengxu Li; Lydia A Bazzano; Amanda H Anderson; Hua He; Wei Chen; Jason M Kinchen; Casey M Rebholz; Josef Coresh; Andrew S Levey; Lesley A Inker; Michael Shlipak; Tanika N Kelly Journal: Metabolomics Date: 2019-11-13 Impact factor: 4.290
Authors: Tiffany A Freed; Josef Coresh; Lesley A Inker; Douglas R Toal; Regis Perichon; Jingsha Chen; Kelli D Goodman; Qibo Zhang; Jessie K Conner; Deirdre M Hauser; Kate E T Vroom; Maria L Oyaski; Jacob E Wulff; Gudný Eiríksdóttir; Vilmundur Gudnason; Vicente E Torres; Lisa A Ford; Andrew S Levey Journal: Clin Chem Date: 2019-01-15 Impact factor: 8.327
Authors: Lauren E Harrison; Charles Giardina; Lawrence E Hightower; Caesar Anderson; George A Perdrizet Journal: Cell Stress Chaperones Date: 2018-10-30 Impact factor: 3.667
Authors: Subrata Debnath; Chakradhar Velagapudi; Laney Redus; Farook Thameem; Balakuntalam Kasinath; Claudia E Hura; Carlos Lorenzo; Hanna E Abboud; Jason C O'Connor Journal: Int J Tryptophan Res Date: 2017-03-10
Authors: Michelle R Denburg; Yunwen Xu; Alison G Abraham; Josef Coresh; Jingsha Chen; Morgan E Grams; Harold I Feldman; Paul L Kimmel; Casey M Rebholz; Eugene P Rhee; Ramachandran S Vasan; Bradley A Warady; Susan L Furth Journal: Clin J Am Soc Nephrol Date: 2021-08 Impact factor: 10.614