The difference between maximal glomerular filtration rate (GFR) and resting GFR, or renal functional reserve (RFR), has been proposed as a complementary measure of kidney health and function. Just as clinicians order dynamic tests of other organ function (e.g., cardiac stress tests and pulmonary function tests) to obtain information not available through static measurements, a kidney function stress test such as RFR could provide valuable information not contained in a single estimate of GFR. In nephrology, RFR has not been tested adequately as a measure of kidney health or risk of AKI or CKD progression. A major barrier to more widespread testing of RFR is the complexity of the measurement, which requires injection of an exogenous filtration marker followed by urinary and/or plasma collections for measurement of GFR, both before and after a physiological stimulus such as an oral protein load. The overall goal of this R21 application is to develop novel and simpler tools for RFR estimation through an innovative study that includes classical physiological measurements and state of the art metabolomic profiling. In Aim 1, we propose to study RFR in 100 individuals, including 50 healthy volunteers and 50 with chronic kidney disease (CKD). Subjects will have GFR measured through urinary clearance of cold iothalamate before and after a physiological stimulus (oral protein, 1g/kg; or intravenous dopamine, 1.5-2.0 g/kg/min). We will test the within-person reproducibility of RFR and investigate relevant biological variables and diet as determinants of RFR and its reproducibility. We will also test whether changes in urinary creatinine clearance correlate sufficiently with change in GFR as measured by urinary iothalamate clearance. In Aim 2, we will perform untargeted metabolomic profiling of plasma samples collected in Aim 1 to discover metabolites that correlate with RFR. The metabolome consists of small molecules (typically < 1500 daltons, including sugars, amino acids, organic acids, nucleotides, acylcarnitines, and lipids) in a cell or biological specimen. Advances in metabolomics technologies now permit the relative quantification of ~1000 known metabolites. The kidneys exert a major impact on the plasma metabolome. The discovery of metabolites from baseline samples that predict RFR could allow RFR to be estimated with a one- time blood test, without the need for a protein or other physiological stimulus. Metabolites whose changes from pre- to post-stimulus correlate with RFR could be used for the development of a test analogous to oral glucose tolerance testing for diabetes. The expected result from this R21 proposal is a true paradigm shift through the development of new diagnostic tests in nephrology to improve diagnosis, risk prediction, and clinical trial design.