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A combined epidemiologic and metabolomic approach improves CKD prediction.

ABSTRACT: Metabolomic approaches have begun to catalog the metabolic disturbances that accompany CKD, but whether metabolite alterations can predict future CKD is unknown. We performed liquid chromatography/mass spectrometry-based metabolite profiling on plasma from 1434 participants in the Framingham Heart Study (FHS) who did not have CKD at baseline. During the following 8 years, 123 individuals developed CKD, defined by an estimated GFR of <60 ml/min per 1.73 m(2). Numerous metabolites were associated with incident CKD, including 16 that achieved the Bonferroni-adjusted significance threshold of P?0.00023. To explore how the human kidney modulates these metabolites, we profiled arterial and renal venous plasma from nine individuals. Nine metabolites that predicted CKD in the FHS cohort decreased more than creatinine across the renal circulation, suggesting that they may reflect non-GFR-dependent functions, such as renal metabolism and secretion. Urine isotope dilution studies identified citrulline and choline as markers of renal metabolism and kynurenic acid as a marker of renal secretion. In turn, these analytes remained associated with incident CKD in the FHS cohort, even after adjustment for eGFR, age, sex, diabetes, hypertension, and proteinuria at baseline. Addition of a multimarker metabolite panel to clinical variables significantly increased the c-statistic (0.77-0.83, P<0.0001); net reclassification improvement was 0.78 (95% confidence interval, 0.60 to 0.95; P<0.0001). Thus, the addition of metabolite profiling to clinical data may significantly improve the ability to predict whether an individual will develop CKD by identifying predictors of renal risk that are independent of estimated GFR.

SUBMITTER: Rhee EP

PROVIDER: S-EPMC3736702 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature

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A combined epidemiologic and metabolomic approach improves CKD prediction.

Rhee Eugene P EP Clish Clary B CB Ghorbani Anahita A Larson Martin G MG Elmariah Sammy S McCabe Elizabeth E Yang Qiong Q Cheng Susan S Pierce Kerry K Deik Amy A Souza Amanda L AL Farrell Laurie L Domos Carly C Yeh Robert W RW Palacios Igor I Rosenfield Kenneth K Vasan Ramachandran S RS Florez Jose C JC Wang Thomas J TJ Fox Caroline S CS Gerszten Robert E RE

Journal of the American Society of Nephrology : JASN 20130516 8

Metabolomic approaches have begun to catalog the metabolic disturbances that accompany CKD, but whether metabolite alterations can predict future CKD is unknown. We performed liquid chromatography/mass spectrometry-based metabolite profiling on plasma from 1434 participants in the Framingham Heart Study (FHS) who did not have CKD at baseline. During the following 8 years, 123 individuals developed CKD, defined by an estimated GFR of <60 ml/min per 1.73 m(2). Numerous metabolites were associated ...[more]

PMID: 23687356

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Project description:Background and objectivesCauses of CKD differ in prognosis and treatment. Metabolomic indicators of CKD cause may provide clues regarding the different physiologic processes underlying CKD development and progression.Design, setting, participants & measurementsMetabolites were quantified from serum samples of participants in the Modification of Diet in Renal Disease (MDRD) Study, a randomized controlled trial of dietary protein restriction and BP control, using untargeted reverse phase ultraperformance liquid chromatography tandem mass spectrometry quantification. Known, nondrug metabolites (n=687) were log-transformed and analyzed to discover associations with CKD cause (polycystic kidney disease, glomerular disease, and other cause). Discovery was performed in Study B, a substudy of MDRD with low GFR (n=166), and replication was performed in Study A, a substudy of MDRD with higher GFR (n=423).ResultsOverall in MDRD, average participant age was 51 years and 61% were men. In the discovery study (Study B), 29% of participants had polycystic kidney disease, 28% had glomerular disease, and 43% had CKD of another cause; in the replication study (Study A), the percentages were 28%, 24%, and 48%, respectively. In the discovery analysis, adjusted for demographics, randomization group, body mass index, hypertensive medications, measured GFR, log-transformed proteinuria, and estimated protein intake, seven metabolites (16-hydroxypalmitate, kynurenate, homovanillate sulfate, N2,N2-dimethylguanosine, hippurate, homocitrulline, and 1,5-anhydroglucitol) were associated with CKD cause after correction for multiple comparisons (P<0.0008). Five of these metabolite associations (16-hydroxypalmitate, kynurenate, homovanillate sulfate, N2,N2-dimethylguanosine, and hippurate) were replicated in Study A (P<0.007), with all replicated metabolites exhibiting higher levels in polycystic kidney disease and lower levels in glomerular disease compared with CKD of other causes.ConclusionsMetabolomic profiling identified several metabolites strongly associated with cause of CKD.

Project description:BackgroundSperm selection is essential for the health of offspring conceived via assistive reproductive technology (ART). Various methods of sperm preparation for in vitro fertilization and intracytoplasmic sperm injection have been developed to acquire sperm with better quality and to avoid potential genetic disorders. However, current sperm processing and selection techniques bypass the natural selection that occurs during fertilization in vivo. The aim of this study was to present a novel distance-progesterone-combined selection approach with an original device based on the human female reproductive tract, and to report on its effectiveness based on sperm progressive motility, as well as chemotaxis.MethodsA novel device with long distance channels which mimicked the female human reproductive system was designed and fabricated. This ready-to-be-used device was developed using a progesterone gradient and human tube fluid media. Sperm swam for 150 min in the device under conditions of 37 °C air temperature with 5% CO2 after separation from seminal plasma via discontinuous Percoll gradient treatment. The selected sperm were assessed for normal morphology using Diff-Quik staining. A chromatin diffusion assay assessed sperm for DNA fragments and apoptosis was assessed using annexin V-fluorescein isothiocyanate/propidium iodide fluorescent staining.ResultsOur distance-progesterone-combined sperm selection method was successfully established. After sperm were selected, the percentage of sperm with normal morphology increased (before vs. after selection, 11.2 ± 1.3% vs. 40.3 ± 6.6%, P = 0.000), the percentage of sperm with DNA fragmentation decreased (before vs. after selection, 15.4 ± 4.0% vs. 6.8 ± 3.3%, P = 0.001), and the percentage of sperm with apoptosis did not change significantly.ConclusionsOur newly-developed method is capable of successfully selecting sperm of high quality. The method will be benefit clinical ART practice as it can reduce sperm-related genetic risks.

Project description:Novel biomarkers that more accurately reflect kidney function and predict future CKD are needed. The human metabolome is the product of multiple physiologic or pathophysiologic processes and may provide novel insight into disease etiology and progression. This study investigated whether estimated kidney function would be associated with multiple metabolites and whether selected metabolomic factors would be independent risk factors for incident CKD.In total, 1921 African Americans free of CKD with a median of 19.6 years follow-up among the Atherosclerosis Risk in Communities Study were included. A total of 204 serum metabolites quantified by untargeted gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry was analyzed by both linear regression for the cross-sectional associations with eGFR (specified by the Chronic Kidney Disease Epidemiology Collaboration equation) and Cox proportional hazards model for the longitudinal associations with incident CKD.Forty named and 34 unnamed metabolites were found to be associated with eGFR specified by the Chronic Kidney Disease Epidemiology Collaboration equation with creatine and 3-indoxyl sulfate showing the strongest positive (2.8 ml/min per 1.73 m(2) per +1 SD; 95% confidence interval, 2.1 to 3.5) and negative association (-14.2 ml/min per 1.73 m(2) per +1 SD; 95% confidence interval, -17.0 to -11.3), respectively. Two hundred four incident CKD events with a median follow-up time of 19.6 years were included in the survival analyses. Higher levels of 5-oxoproline (hazard ratio, 0.70; 95% confidence interval, 0.60 to 0.82) and 1,5-anhydroglucitol (hazard ratio, 0.68; 95% confidence interval, 0.58 to 0.80) were significantly related to lower risk of incident CKD, and the associations did not appreciably change when mutually adjusted.These data identify a large number of metabolites associated with kidney function as well as two metabolites that are candidate risk factors for CKD and may provide new insights into CKD biomarker identification.

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A combined epidemiologic and metabolomic approach improves CKD prediction.

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A combined epidemiologic and metabolomic approach improves CKD prediction.

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