Metabolites associate with kidney function decline and incident chronic kidney disease in the general population
Abstract
BACKGROUND: Serum metabolites are associated cross-sectionally with kidney function in population-based studies. METHODS: Using flow injection and liquid chromatography tandem mass spectrometry methods, we examined longitudinal associations of baseline concentrations of 140 metabolites and their 19 460 ratios with kidney function decline and chronic kidney disease (CKD) incidence over 7 years in 1104 participants of the Cooperative Health Research in the Region of Augsburg S4/F4 study. RESULTS: Corrected for multiple testing, a significant association with annual change in the estimated glomerular filtration rate was observed for spermidine (P = 5.8 × 10(-7)) and two metabolite ratios, the phosphatidylcholine diacyl C42:5-to-phosphatidylcholine acyl-alkyl C36:0 ratio (P = 1.5 × 10(-6)) and the kynurenine-to-tryptophan ratio (P = 1.9 × 10(-6)). The kynurenine-to-tryptophan ratio was also associated with significantly higher incidence of CKD at the follow-up visit with an odds ratio of 1.36 per standard deviation increase; 95% confidence interval 1.11-1.66, P = 2.7 × 10(-3)). In separate analyses, the predictive ability of the metabolites was assessed: both the three significantly associated metabolite (ratios) as well as a panel of 35 metabolites selected from all metabolites in an unbiased fashion provided as much but not significantly more prognostic information than selected clinical predictors as judged by the area under the curve. CONCLUSIONS: Baseline serum concentrations of spermidine and two metabolite ratios were associated with kidney function change over subsequent years in the general population. In separate analyses, baseline serum metabolites were able to predict incident CKD to a similar but not better extent than selected clinical parameters. Our longitudinal findings provide a basis for targeted studies of certain metabolic pathways, e.g. tryptophan metabolism, and their relation to kidney function decline.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Dysregulation of the tryptophan kynurenine pathway is associated with eGFR decline and chronic kidney disease incidence in a population-based study.
“Such dys-regulation was associated with eGFR decline and CKD incidence in a population-based study183.”
From The gut microbiota and the brain–gut–kidney axis in hypertension and chronic kidney disease (2018) · cites this paper as [183]
Numerous plasma metabolites have been associated with longitudinal eGFR decline or cross-sectional eGFR decline in the general population.
“In addition, numerous plasma metabolites have been associated with longitudinal eGFR183 or cross-sectional eGFR decline230 in the general population.”
From The gut microbiota and the brain–gut–kidney axis in hypertension and chronic kidney disease (2018) · cites this paper as [183]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
A New Equation to Estimate Glomerular Filtration Rate
Levey, A. S., Stevens, L. A., Schmid, C. H., Zhang, Y. (., Castro, A. F., Feldman, H. I., Kusek, J. W., Eggers, P., Van Lente, F., Greene, T., et al. (2009) · Annals of Internal Medicine · doi:10.7326/0003-4819-150-9-200905050-00006 · Cited by 25,603 · see citing works
Predictors of New-Onset Kidney Disease in a Community-Based Population
Fox, C. S. (2004) · JAMA · doi:10.1001/jama.291.7.844 · Cited by 1,241 · cited 1× · see citing works
“Associations of changes in eGFR with metabolites and ratios were obtained from linear regression analyses, adjusted for known CKD risk factors measured at baseline: age (years) [11], gender, body mass index (BMI, kg/m(2)), systolic blood pressure (mmHg), current smoking status, antihypertensive medication use, antihyp…”
MethodPrevalence of chronic kidney disease in population-based studies: Systematic review
Zhang, Q.-L., & Rothenbacher, D. (2008) · BMC Public Health · doi:10.1186/1471-2458-8-117 · Cited by 1,020 · see citing works
Coresh, J., Astor, B. C., McQuillan, G. M., Kusek, J. W., Greene, T., Lente, F. V., & Levey, A. S. (2002) · American Journal of Kidney Diseases · doi:10.1053/ajkd.2002.32765 · Cited by 714 · see citing works
A genome-wide perspective of genetic variation in human metabolism
Illig, T., Gieger, C., Zhai, G., Römisch-Margl, W., Wang-Sattler, R., Prehn, C., Altmaier, E., Kastenmüller, G., Kato, B. S., Mewes, H.-W., et al. (2010) · Nature Genetics · doi:10.1038/ng.507 · Cited by 653 · see citing works
Self-citationKynurenine is an endothelium-derived relaxing factor produced during inflammation
Wang, Y., Liu, H., McKenzie, G. A., Witting, P. K., Stasch, J., Hahn, M. G., Changsirivathanathamrong, D., Wu, B. J., Ball, H. J., Thomas, S. R., et al. (2010) · Nature Medicine · doi:10.1038/nm.2092 · Cited by 446 · see citing works
KORA-gen - Resource for Population Genetics, Controls and a Broad Spectrum of Disease Phenotypes
Wichmann, H. ‐., Gieger, C., & Illig, T. (2005) · Das Gesundheitswesen · doi:10.1055/s-2005-858226 · Cited by 417 · see citing works
Self-citationDiscovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers
Mittelstraß, K., Ried, J. S., Yu, Z., Krumsiek, J., Gieger, C., Prehn, C. P., Roemisch‐Margl, W., Polonikov, A., Peters, A., Theis, F. J., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002215 · Cited by 385 · see citing works
Self-citationAssociation between a literature-based genetic risk score and cardiovascular events in women
Paynter, N. P. (2010) · JAMA · doi:10.1001/jama.2010.119 · Cited by 361 · see citing works
Selvin, E., Manzi, J., Stevens, L. A., Lente, F. V., Lacher, D. A., Levey, A. S., & Coresh, J. (2007) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2007.08.020 · Cited by 307 · see citing works
Römisch‐Margl, W., Prehn, C. P., Bogumil, R., Röhring, C., Suhre, K., & Adamski, J. (2011) · Metabolomics · doi:10.1007/s11306-011-0293-4 · Cited by 292 · see citing works
Self-citationThe role of asymmetric and symmetric dimethylarginines in renal disease
Schwedhelm, E., & Böger, R. H. (2011) · Nature Reviews Nephrology · doi:10.1038/nrneph.2011.31 · Cited by 262 · see citing works
Schefold, J. C., Zeden, J.-P., Fotopoulou, C., von Haehling, S., Pschowski, R., Hasper, D., Volk, H., Schuett, C., & Reinke, P. (2009) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfn739 · Cited by 256 · see citing works
Petersen, A.-K., Krumsiek, J., Wägele, B., Theis, F. J., Wichmann, H. ‐., Gieger, C., & Suhre, K. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-120 · Cited by 127 · see citing works
Self-citationSerum Metabolite Concentrations and Decreased GFR in the General Population
Goek, O.-N., Döring, A., Gieger, C., Heier, M., Koenig, W., Prehn, C., Römisch-Margl, W., Wang-Sattler, R., Illig, T., Suhre, K., et al. (2012) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2012.01.014 · Cited by 121 · cited 3× · see citing works
“While prior studies documented cross-sectional associations between serum metabolites and eGFR in the general population [2, 3], this is—to our knowledge—the first populationbased study to assess such associations longitudinally over a time period of years [13, 14].”
BackgroundResultSelf-citationIgarashi, K., Ueda, S., Yoshida, K., & Kashiwagi, K. (2006) · Amino Acids · doi:10.1007/s00726-006-0264-7 · Cited by 116 · see citing works
Pawlak, K., Myśliwiec, M., & Pawlak, D. (2010) · Advances in Medical Sciences · doi:10.2478/v10039-010-0015-6 · Cited by 107 · see citing works
Arginase-2 Mediates Diabetic Renal Injury
Morris, S. M., Gao, T., Cooper, T. K., Kepka‐Lenhart, D., & Awad, A. S. (2011) · Diabetes · doi:10.2337/db11-0901 · Cited by 85 · see citing works
Serum levels of polyamines in patients with chronic renal failure.
Saito, A., Takagi, T., Chung, T., & Ohta, K. (1983) · PubMed · Cited by 68 · see citing works
Update of uremic toxin research by mass spectrometry
Niwa, T. (2011) · Mass Spectrometry Reviews · doi:10.1002/mas.20323 · Cited by 68 · see citing works
Mashima, R., Nakanishi‐Ueda, T., & Yamamoto, Y. (2003) · Analytical Biochemistry · doi:10.1016/s0003-2697(02)00537-7 · Cited by 62 · see citing works
Nicoletti, R. (2003) · British Journal of Ophthalmology · doi:10.1136/bjo.87.8.1038 · Cited by 51 · see citing works
Kato, A., Suzuki, Y., Suda, T., Suzuki, M., Fujie, M., Takita, T., Furuhashi, M., Maruyama, Y., Chida, K., & Hishida, A. (2010) · Hemodialysis international. International Symposium on Home Hemodialysis · doi:10.1111/j.1542-4758.2010.00464.x · Cited by 47 · see citing works
Performance of a Genetic Risk Score for CKD Stage 3 in the General Population
O’Seaghdha, C. M., Yang, Q., Wu, H., Hwang, S., & Fox, C. S. (2011) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2011.08.030 · Cited by 33 · see citing works
Seghieri, G., Anichini, R., Ciuti, M., Gironi, A., Bennardini, F., & Franconi, F. (1997) · Diabetes Research and Clinical Practice · doi:10.1016/s0168-8227(97)00050-8 · Cited by 12 · see citing works
Kidney Function Decline in the Elderly: Impact of Lipoprotein-Associated Phospholipase A2
Peralta, C. A., Katz, R., Shlipak, M. G., Dubin, R. F., DeBoer, I., Jenny, N. S., Fitzpatrick, A. L., Koro, C. E., Kestenbaum, B. R., Ix, J. H., et al. (2011) · American Journal of Nephrology · doi:10.1159/000333045 · Cited by 10 · see citing works
Spermidine/Spermine-N1-Acetyltransferase in Kidney Ischemia Reperfusion Injury
Zahedi, K. A., & Soleimani, M. (2011) · Methods in molecular biology · doi:10.1007/978-1-61779-034-8_24 · Cited by 8 · see citing works
Pawlak, K., Mysliwiec, M., & Pawlak, D. (2011) · Atherosclerosis Supplements · doi:10.1016/s1567-5688(11)70332-4 · Cited by 3 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Zahedi K, Soleimani M. Spermidine/spermine-N(1)-acetyltrans- ferase in kidney ischemia reperfusion injury. Methods Mol Biol 2011; 720: 379-394
Cited by
Sorted by citations
The gut microbiota and the brain–gut–kidney axis in hypertension and chronic kidney disease
Yang, T., Richards, E. M., Pepine, C. J., & Raizada, M. K. (2018) · Nature Reviews Nephrology · doi:10.1038/s41581-018-0018-2 · Cited by 753 · see citing works
Metabolomics for clinical use and research in chronic kidney disease
Hocher, B., & Adamski, J. (2017) · Nature Reviews Nephrology · doi:10.1038/nrneph.2017.30 · Cited by 335 · see citing works
Self-citationNAD+ homeostasis in renal health and disease
Ralto, K. M., Rhee, E. P., & Parikh, S. M. (2019) · Nature Reviews Nephrology · doi:10.1038/s41581-019-0216-6 · Cited by 288 · see citing works
Targeted Metabolomics Identifies Reliable and Stable Metabolites in Human Serum and Plasma Samples
Breier, M., Wahl, S., Prehn, C. P., Fugmann, M., Ferrari, U., Weise, M., Banning, F., Seißler, J., Grallert, H., Adamski, J., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0089728 · Cited by 240 · see citing works
Self-citationA metabolome-wide association study of kidney function and disease in the general population
Sekula, P., Goek, O.-N., Quaye, L., Barrios, C., Levey, A. S., Römisch-Margl, W., Menni, C., Yet, I., Gieger, C., Inker, L. A., et al. (2016) · Journal of the American Society of Nephrology · doi:10.1681/asn.2014111099 · Cited by 203 · see citing works
Self-citationFeng, Y., Cao, G., Chen, D., Vaziri, N. D., Chen, L., Zhang, J., Wang, M., Guo, Y. P., & Zhao, Y. (2019) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-019-03155-9 · Cited by 201 · see citing works
Measuring Biological Age via Metabonomics: The Metabolic Age Score
Hertel, J., Friedrich, N., Wittfeld, K., Pietzner, M., Budde, K., Van der Auwera, S., Lohmann, T., Teumer, A., Völzke, H., Nauck, M., et al. (2016) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5b00561 · Cited by 181 · see citing works
An overview of renal metabolomics
Kalim, S., & Rhee, E. P. (2016) · Kidney International · doi:10.1016/j.kint.2016.08.021 · Cited by 175 · see citing works
Long-Term Stability of Human Plasma Metabolites during Storage at −80 °C
Haid, M., Muschet, C., Wahl, S., Römisch‐Margl, W., Prehn, C. P., Möller, G., & Adamski, J. (2017) · Journal of Proteome Research · doi:10.1021/acs.jproteome.7b00518 · Cited by 160 · see citing works
Self-citationHallan, S. I., Afkarian, M., Zelnick, L. R., Kestenbaum, B. R., Sharma, S., Saito, R., Darshi, M., Barding, G. A., Raftery, D., Ju, W., et al. (2017) · EBioMedicine · doi:10.1016/j.ebiom.2017.10.027 · Cited by 159 · see citing works
Chronic kidney disease: Biomarker diagnosis to therapeutic targets
Wang, Y., Ma, S., Chen, Y., Chen, L., Liu, B., Liu, Q., & Zhao, Y.-Y. (2019) · Clinica Chimica Acta · doi:10.1016/j.cca.2019.08.030 · Cited by 129 · see citing works
Debnath, S., Velagapudi, C., Redus, L., Thameem, F., Kasinath, B. S., Hura, C., Lorenzo, C., Abboud, H. E., & O’Connor, J. C. (2017) · International Journal of Tryptophan Research · doi:10.1177/1178646917694600 · Cited by 126 · see citing works
Nkuipou‐Kenfack, E., Duranton, F., Gayrard, N., Argilés, À., Lundin, U., Weinberger, K. M., Dakna, M., Delles, C., Mullen, W., Husi, H., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0096955 · Cited by 108 · see citing works
Chen, L., Chen, D., Liu, J., Zhang, J., Vaziri, N. D., Zhuang, S., Chen, H., Feng, Y., Guo, Y. P., & Zhao, Y. (2019) · Experimental & Molecular Medicine · doi:10.1038/s12276-019-0234-2 · Cited by 105 · see citing works
Direct Infusion Mass Spectrometry for Metabolomic Phenotyping of Diseases
González‐Domínguez, R., Sayago, A., & Fernández‐Recamales, Á. (2016) · Bioanalysis · doi:10.4155/bio-2016-0202 · Cited by 98 · see citing works
Brück, K., Jager, K. J., Dounousi, E. C., Kainz, A., Nitsch, D., Ärnlöv, J., Rothenbacher, D., Browne, G. M., Capuano, V., Ferraro, P. M., et al. (2015) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfv131 · Cited by 90 · see citing works
Metabolomics Approaches for the Diagnosis and Understanding of Kidney Diseases
Abbiss, H., Maker, G. L., & Trengove, R. D. (2019) · Metabolites · doi:10.3390/metabo9020034 · Cited by 89 · see citing works
Blydt‐Hansen, T. D., Sharma, A., Gibson, I. W., Mandal, R., & Wishart, D. S. (2014) · American Journal of Transplantation · doi:10.1111/ajt.12837 · Cited by 81 · see citing works
Chen, X., Wang, H., Liao, H., Hu, W., Gewin, L. S., Mernaugh, G., Zhang, S., Zhang, Z., Vega‐Montoto, L., Vanacore, R., et al. (2014) · Journal of Clinical Investigation · doi:10.1172/jci71668 · Cited by 76 · see citing works
Rhee, E. P., Clish, C. B., Wenger, J., Roy, J., Elmariah, S., Pierce, K. A., Bullock, K. H., Anderson, A. H., Gerszten, R. E., & Feldman, H. I. (2016) · American Journal of Nephrology · doi:10.1159/000446484 · Cited by 76 · see citing works
The Kynurenine Pathway in Acute Kidney Injury and Chronic Kidney Disease
Wee, H. N., Liu, J., Ching, J., Kovalik, J., & Lim, S. C. (2021) · American Journal of Nephrology · doi:10.1159/000519811 · Cited by 73 · see citing works
Urine Metabolite Profiles Predictive of Human Kidney Allograft Status
Suhre, K., Schwartz, J. E., Sharma, V. K., Chen, Q., Lee, J. R., Muthukumar, T., Dadhania, D. M., Ding, R., Iklé, D. N., Bridges, N. D., et al. (2015) · Journal of the American Society of Nephrology · doi:10.1681/asn.2015010107 · Cited by 73 · see citing works
Self-citationLee, H., Jang, H. B., Yoo, M., Park, S. I., & Lee, H. (2020) · Biomedicines · doi:10.3390/biomedicines8070222 · Cited by 71 · see citing works
Clotet‐Freixas, S., Zaslaver, O., Kotlyar, M., Pastrello, C., Quaile, A. T., McEvoy, C. M., Saha, A. D., Farkona, S., Boshart, A., Zorcic, K., et al. (2024) · Science Translational Medicine · doi:10.1126/scitranslmed.abm2090 · Cited by 70 · see citing works
Self-citationKimura, T., Yasuda, K., Yamamoto, R., Soga, T., Rakugi, H., Hayashi, T., & Isaka, Y. (2016) · Scientific Reports · doi:10.1038/srep26138 · Cited by 70 · see citing works
Iwaki, T., Bennion, B. G., Stenson, E. K., Lynn, J. C., Otinga, C., Djukovic, D., Raftery, D., Fei, L., Wong, H. R., Liles, W. C., et al. (2019) · Physiological Reports · doi:10.14814/phy2.14078 · Cited by 67 · see citing works
Yamaguchi, Y., Zampino, M., Moaddel, R., Chen, T. K., Tian, Q., Ferrucci, L., & Semba, R. D. (2021) · Metabolomics · doi:10.1007/s11306-020-01762-3 · Cited by 68 · see citing works
Proteomic and metabolomic approaches in the search for biomarkers in chronic kidney disease
Cañadas‐Garre, M., Anderson, K., McGoldrick, J., Maxwell, A. P., & McKnight, A. J. (2018) · Journal of Proteomics · doi:10.1016/j.jprot.2018.09.020 · Cited by 66 · see citing works
Huang, J., Huth, C., Covic, M., Troll, M., Adam, J., Zukunft, S., Prehn, C., Wang, L., Nano, J., Scheerer, M. F., et al. (2020) · Diabetes · doi:10.2337/db20-0586 · Cited by 60 · see citing works
Self-citationMcMahon, G. M., Hwang, S., Clish, C. B., Tin, A., Yang, Q., Larson, M. G., Rhee, E. P., Li, M., Levy, D. A., O’Donnell, C. J., et al. (2017) · Kidney International · doi:10.1016/j.kint.2017.01.007 · Cited by 58 · see citing works
Cheng, Y., Li, Y., Benkowitz, P., Lamina, C., Köttgen, A., & Sekula, P. (2020) · Scientific Reports · doi:10.1038/s41598-020-69559-x · Cited by 56 · see citing works
Self-citationCarstensen‐Kirberg, M., Kannenberg, J. M., Huth, C., Meisinger, C., Köenig, W., Heier, M., Peters, A., Rathmann, W., Roden, M., Herder, C., et al. (2017) · Cardiovascular Diabetology · doi:10.1186/s12933-017-0591-x · Cited by 55 · see citing works
Self-citationLiu, J., Ching, J., Wee, H. N., Liu, S., Gurung, R. L., Lee, J., Yiamunaa, M., Zheng, H., Lee, L. S., Ang, K., et al. (2023) · Diabetes Care · doi:10.2337/dc23-1147 · Cited by 54 · see citing works
Metabolomic profiling to improve glomerular filtration rate estimation: a proof-of-concept study
Coresh, J., Inker, L. A., Sang, Y., Chen, J., Shafi, T., Post, W. S., Shlipak, M. G., Ford, L. A., Goodman, K. D., Périchon, R., et al. (2018) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfy094 · Cited by 52 · see citing works
Metabolic biomarkers for chronic kidney disease
Breit, M., & Weinberger, K. M. (2015) · Archives of Biochemistry and Biophysics · doi:10.1016/j.abb.2015.07.018 · Cited by 52 · see citing works
Hui, Y., Zhao, J., Yu, Z., Wang, Y., Qin, Y., Zhang, Y., Xing, Y., Han, M., Wang, A., Guo, S., et al. (2023) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.202300218 · Cited by 51 · see citing works
Metabolomics and renal disease
Rhee, E. P. (2015) · Current Opinion in Nephrology & Hypertension · doi:10.1097/mnh.0000000000000136 · Cited by 49 · see citing works
Blood, urine and faecal metabolite profiles in the study of adult renal disease
Barrios, C., Spector, T. D., & Menni, C. (2015) · Archives of Biochemistry and Biophysics · doi:10.1016/j.abb.2015.10.006 · Cited by 48 · see citing works
Polyamine biomarkers as indicators of human disease
Amin, M., Tang, S., Shalamanova, L., Taylor, R. L., Wylie, S. R., Abdullah, B. M., & Whitehead, K. A. (2021) · Biomarkers · doi:10.1080/1354750x.2021.1875506 · Cited by 48 · see citing works
Biomarkers in Transplantation—Proteomics and Metabolomics
Christians, U., Klawitter, J., & Klawitter, J. (2015) · Therapeutic Drug Monitoring · doi:10.1097/ftd.0000000000000243 · Cited by 44 · see citing works
Variability of Two Metabolomic Platforms in CKD
Rhee, E. P., Waikar, S. S., Rebholz, C. M., Zheng, Z., Périchon, R., Clish, C. B., Evans, A. M., Ávila-Pacheco, J., Denburg, M., Anderson, A. H., et al. (2018) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.07070618 · Cited by 44 · see citing works
Sekula, P., Dettmer, K., Vogl, F. C., Gronwald, W., Ellmann, L., Mohney, R. P., Eckardt, K., Suhre, K., Kastenmüller, G., Oefner, P. J., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-17107-5 · Cited by 42 · see citing works
Self-citationSteinbrenner, I., Schultheiß, U. T., Kotsis, F., Schlosser, P., Stockmann, H., Mohney, R. P., Schmid, M. C., Oefner, P. J., Eckardt, K., Köttgen, A., et al. (2021) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2021.01.018 · Cited by 43 · see citing works
Self-citationIndoxyl sulfate associates with cardiovascular phenotype in children with chronic kidney disease
Holle, J. B., Querfeld, U., Kirchner, M., Anninos, A., Okun, J. G., Thurn‐Valsassina, D., Bayazıt, A. K., Niemirska, A., Canpolat, N., Bulut, İ. K., et al. (2019) · Pediatric Nephrology · doi:10.1007/s00467-019-04331-6 · Cited by 42 · see citing works
Integrated genomics and metabolomics in nephrology
Atzler, D., Schwedhelm, E., & Zeller, T. (2013) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gft492 · Cited by 38 · see citing works
Hanifa, M. A., Skott, M., Maltesen, R. G., Rasmussen, B. S., Nielsen, S. U., Frøkiær, J., Ring, T., & Wimmer, R. (2019) · Metabolomics · doi:10.1007/s11306-019-1569-3 · Cited by 39 · see citing works
Tavares, G. F., Venturini, G., Padilha, K., Zatz, R., Pereira, A. C., Thadhani, R., Rhee, E. P., & Titan, S. (2018) · Metabolomics · doi:10.1007/s11306-018-1337-9 · Cited by 38 · see citing works
Genome-Wide Association Studies of Metabolite Concentrations (mGWAS): Relevance for Nephrology
Köttgen, A., Raffler, J., Sekula, P., & Kastenmüller, G. (2018) · Seminars in Nephrology · doi:10.1016/j.semnephrol.2018.01.009 · Cited by 37 · see citing works
Self-citationBlydt‐Hansen, T. D., Sharma, A., Gibson, I. W., Wishart, D. S., Mandal, R., Ho, J., Nickerson, P. W., & Rush, D. N. (2017) · Transplantation · doi:10.1097/tp.0000000000001662 · Cited by 37 · see citing works
Wang, F., Sun, L., Sun, Q., Liang, L., Gao, X., Li, R., Pan, A., Li, H., Deng, Y., Hu, F. B., et al. (2018) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.07650717 · Cited by 36 · see citing works
Metabolites Associated with Coffee Consumption and Incident Chronic Kidney Disease
He, W. J., Chen, J., Razavi, A. C., Hu, E. A., Grams, M. E., Yu, B., Parikh, C. R., Boerwinkle, E., Bazzano, L., Qi, L., et al. (2021) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.05520421 · Cited by 36 · see citing works
Mathew, S., Krug, S., Skurk, T., Halama, A., Stank, A., Artati, A., Prehn, C. P., Malek, J. A., Kastenmüller, G., Römisch‐Margl, W., et al. (2014) · Journal of Translational Medicine · doi:10.1186/1479-5876-12-161 · Cited by 33 · see citing works
Self-citationLee, J. E., Lee, Y. H., Kim, S.-Y., Kim, Y., Moon, J.-Y., Jeong, K. H., Lee, T. W., Ihm, C., Kim, S., Kim, K. H., et al. (2016) · Journal of Chromatography A · doi:10.1016/j.chroma.2016.05.058 · Cited by 34 · see citing works
Metabolomics in chronic kidney disease: Strategies for extended metabolome coverage
Gagnebin, Y., Boccard, J., Ponte, B., & Rudaz, S. L. (2018) · Journal of Pharmaceutical and Biomedical Analysis · doi:10.1016/j.jpba.2018.08.046 · Cited by 35 · see citing works
A Systems-Level View of Renal Metabolomics
Rhee, E. P. (2018) · Seminars in Nephrology · doi:10.1016/j.semnephrol.2018.01.005 · Cited by 31 · see citing works
Wiesenhofer, F. M., Herzog, R., Boehm, M., Wagner, A., Unterwurzacher, M., Kasper, D. C., Alper, S. L., Vychytil, A., Aufricht, C., & Kratochwill, K. (2019) · Frontiers in Physiology · doi:10.3389/fphys.2018.01961 · Cited by 31 · see citing works
An Update of Urine and Blood Metabolomics in Chronic Kidney Disease
Kalantari, S., & Nafar, M. (2019) · Biomarkers in Medicine · doi:10.2217/bmm-2019-0008 · Cited by 31 · see citing works
Chen, Y., Weng, S., Liu, J., Chuang, H.-L., Hsu, C.-C., & Tarng, D. (2017) · Scientific Reports · doi:10.1038/srep42690 · Cited by 32 · see citing works
Herold, J. M., Wiegrebe, S., Nano, J., Jung, B., Gorski, M., Thorand, B., Köenig, W., Zeller, T., Zimmermann, M. E., Burkhardt, R., et al. (2024) · Kidney International · doi:10.1016/j.kint.2024.06.024 · Cited by 31 · see citing works
Machine learning distilled metabolite biomarkers for early stage renal injury
Guo, Y. P., Yu, H., Chen, D., & Zhao, Y. (2019) · Metabolomics · doi:10.1007/s11306-019-1624-0 · Cited by 28 · see citing works
Herder, C., Kannenberg, J. M., Niersmann, C., Huth, C., Carstensen‐Kirberg, M., Wittenbecher, C., Schulze, M. B., Blüher, M., Rathmann, W., Peters, A., et al. (2017) · European Journal of Endocrinology · doi:10.1530/eje-17-0100 · Cited by 27 · see citing works
Self-citationEpidemiology research to foster improvement in chronic kidney disease care
Luo, S., & Grams, M. E. (2019) · Kidney International · doi:10.1016/j.kint.2019.11.010 · Cited by 26 · see citing works
NAD+ Metabolism and Interventions in Premature Renal Aging and Chronic Kidney Disease
Chanvillard, L., Tammaro, A., & Sorrentino, V. (2022) · Cells · doi:10.3390/cells12010021 · Cited by 25 · see citing works
Zacharias, H. U., Altenbuchinger, M., Schultheiß, U. T., Samol, C., Kotsis, F., Poguntke, I., Sekula, P., Krumsiek, J., Köttgen, A., Spang, R., et al. (2019) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00983 · Cited by 24 · see citing works
Self-citationNon‐invasive staging of chronic kidney allograft damage using urine metabolomic profiling
Landsberg, A., Sharma, A., Gibson, I. W., Rush, D. N., Wishart, D. S., & Blydt‐Hansen, T. D. (2018) · Pediatric Transplantation · doi:10.1111/petr.13226 · Cited by 23 · see citing works
Colas, L., Royer, A., Massias, J., Raux, A., Chesneau, M., Kerleau, C., Guérif, P., Giral, M., Guitton, Y., & Brouard, S. (2022) · EBioMedicine · doi:10.1016/j.ebiom.2022.103844 · Cited by 22 · see citing works
Gagnebin, Y., Pezzatti, J., Lescuyer, P., Boccard, J., Ponte, B., & Rudaz, S. L. (2019) · Journal of Chromatography B · doi:10.1016/j.jchromb.2019.03.031 · Cited by 22 · see citing works
Endothelin-1 Overexpression Improves Renal Function in eNOS Knockout Mice
Tsuprykov, O., Chaykovska, L., Kretschmer, A., Stasch, J., Pfab, T., Relle, K., Reichetzeder, C., Kalk, P., Adamski, J., & Hocher, B. (2015) · Cellular Physiology and Biochemistry · doi:10.1159/000438516 · Cited by 18 · see citing works
Self-citationArtemether Alleviates Diabetic Kidney Disease by Modulating Amino Acid Metabolism
Rong, G., Weng, W., Huang, J., Chen, Y., Yu, X., Yuan, R., Gu, X., Wu, X., Cai, Y., Han, P., et al. (2022) · BioMed Research International · doi:10.1155/2022/7339611 · Cited by 17 · see citing works
Oxidative stress increases 1-deoxysphingolipid levels in chronic kidney disease
Gui, T., Li, Y., Zhang, S., Alecu, I., Chen, Q., Zhao, Y., Hornemann, T., Kullak-Ublick, G. A., & Gai, Z. (2021) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2021.01.011 · Cited by 17 · see citing works
Metabolomics for the Identification of Biomarkers in Kidney Diseases
Pandey, S. (2025) · Nanotheranostics · doi:10.7150/ntno.108320 · Cited by 17 · see citing works
Nierenberg, J. L., He, J., Li, C., Gu, X., Shi, M., Razavi, A. C., Mi, X., Li, S., Bazzano, L., Anderson, A. H., et al. (2019) · Metabolomics · doi:10.1007/s11306-019-1613-3 · Cited by 15 · see citing works
Novel Filtration Markers for GFR Estimation.
Karger, A. B., Inker, L. A., Coresh, J., Levey, A. S., & Eckfeldt, J. H. (2017) · Europe PMC (PubMed Central) · Cited by 15 · see citing works
Urine 6-Bromotryptophan: Associations with Genetic Variants and Incident End-Stage Kidney Disease
Sekula, P., Tin, A., Schultheiß, U. T., Baid‐Agrawal, S., Mohney, R. P., Steinbrenner, I., Yu, B., Luo, S., Boerwinkle, E., Eckardt, K., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-66334-w · Cited by 14 · see citing works
Self-citationUromodulin and its association with urinary metabolites: the German Chronic Kidney Disease Study
Bächle, H., Sekula, P., Schlosser, P., Steinbrenner, I., Cheng, Y., Kotsis, F., Meiselbach, H., Stockmann, H., Schönherr, S., Eckardt, K., et al. (2022) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfac187 · Cited by 13 · see citing works
Self-citationPrecision Medicine in Diabetic Kidney Disease: A Narrative Review Framed by Lived Experience
Downie, M. L., Desjarlais, A., Verdin, N., Woodlock, T., & Collister, D. (2023) · Canadian Journal of Kidney Health and Disease · doi:10.1177/20543581231209012 · Cited by 14 · see citing works
Blood metabolites and chronic kidney disease: a Mendelian randomization study
Hou, Y., Xiao, Z., Zhu, Y., Li, Y., Liu, Q., & Wang, Z. (2024) · BMC Medical Genomics · doi:10.1186/s12920-024-01918-3 · Cited by 12 · see citing works
Metabolomic profiles in serum and urine uncover novel biomarkers in children with nephrotic syndrome
Hu, L., Lin, L., Huang, G., Xie, Y., Peng, Z., Liu, F., Bai, G., Li, W., Gao, L., Wang, Y., et al. (2023) · European Journal of Clinical Investigation · doi:10.1111/eci.13978 · Cited by 12 · see citing works
Mogos, M., Socaciu, C., Socaciu, A. I., Vlad, A., Gădălean, F., Bob, F. R., Milas, L. O., Cretu, O. M., Suteanu‐Simulescu, A., Glavan, M., et al. (2023) · Biomedicines · doi:10.3390/biomedicines11061527 · Cited by 11 · see citing works
Prognostic Significance of Amino Acid and Biogenic Amines Profiling in Chronic Kidney Disease
Gervasini, G., Verde, Z., González, L. M., Chicharro, C., González-Rodríguez, L., Araque, A. F., Mota-Zamorano, S., Cancho, B., Pérez-Hernández, A., García‐López, V., et al. (2023) · Biomedicines · doi:10.3390/biomedicines11102775 · Cited by 11 · see citing works
Mulders, L. V., Broecke, E. V., Paepe, E. D., Mortier, F., Vanhaecke, L., & Daminet, S. (2025) · Veterinary Quarterly · doi:10.1080/01652176.2024.2447601 · Cited by 11 · see citing works
Li, K., Tang, H., Wang, Y., & Wang, X. (2025) · Diabetes Obesity and Metabolism · doi:10.1111/dom.16536 · Cited by 11 · see citing works
Martin‐Lorenzo, M., Ramos-Barron, M. A., Gutierrez-Garcia, P., Martín-Blázquez, A., Santiago‐Hernandez, A., Rodrigo, E., Gómez-Alamillo, C., & Álvarez‐Llamas, G. (2021) · Antioxidants · doi:10.3390/antiox10060896 · Cited by 11 · see citing works
Tubular dysfunction impairs renal excretion of pseudouridine in diabetic kidney disease
Mathew, A. V., Kayampilly, P. P., Byun, J., Nair, V., Afshinnia, F., Chai, B., Brosius, F. C., Kretzler, M., & Pennathur, S. (2023) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00252.2022 · Cited by 10 · see citing works
Rhee, E. P., Clish, C. B., Pierce, K. A., Saad, A., Lerman, L. O., & Textor, S. C. (2014) · Journal of Hypertension · doi:10.1097/hjh.0000000000000470 · Cited by 10 · see citing works
Reichetzeder, C., Heunisch, F., von Einem, G. F., Tsuprykov, O., Kellner, K.-H., Dschietzig, T. B., Kretschmer, A., & Hocher, B. (2017) · Kidney & Blood Pressure Research · doi:10.1159/000477222 · Cited by 10 · see citing works
Local Inhibition of Indoleamine 2,3-Dioxygenase Mitigates Renal Fibrosis
Grønkjær, C., Jensen, M. S., Tingskov, S. J., Olinga, P., Nørregaard, R., & Mutsaers, H. A. M. (2021) · Biomedicines · doi:10.3390/biomedicines9080856 · Cited by 10 · see citing works
Zhou, M. L., Tan, X., Luo, P., Xu, J., Yin, Z., Liao, T., Wang, S., Wang, Z., & Jin, Y. (2021) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2021.166289 · Cited by 10 · see citing works
Biomarkers and personalized therapy in chronic kidney diseases
Schena, F. P. (2014) · Expert Opinion on Investigational Drugs · doi:10.1517/13543784.2014.922953 · Cited by 10 · see citing works
Lim, C. C., He, F., Li, J., Tham, Y. C., Tan, C. S., Cheng, C., Wong, T. Y., & Sabanayagam, C. (2021) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2021-002364 · Cited by 9 · see citing works
Chronic Kidney Disease Cohort Studies: A Guide to Metabolome Analyses
Schultheiß, U. T., Kosch, R., Kotsis, F., Altenbuchinger, M., & Zacharias, H. U. (2021) · Metabolites · doi:10.3390/metabo11070460 · Cited by 8 · see citing works
Plasma Kynurenine: A Promising Marker for the Assessment of Renal Functions
Brekdar, F., Khayat, M. I., & Zrieki, A. (2022) · International Journal of Tryptophan Research · doi:10.1177/11786469221102093 · Cited by 9 · see citing works
Metabolomic Patterns in Adolescents With Mild to Moderate CKD
Brooks, E. R., Lin, D. C., Langman, C. B., Thompson, J. W., John‐Williams, L. S., Furth, S. L., Warady, B. A., & Haymond, S. (2019) · Kidney International Reports · doi:10.1016/j.ekir.2019.01.009 · Cited by 9 · see citing works
Ling, T., Chang, C., Li, C., Sung, J., Sun, C., Tsai, K., Cheng, Y., Wu, J., Kuo, Y.-T., & Chang, Y. (2021) · European Journal of Neurology · doi:10.1111/ene.15123 · Cited by 8 · see citing works
Circulating metabolites improve the prediction of renal impairment in patients with type 2 diabetes
Trischitta, V., Mastroianno, M., Scarale, M. G., Prehn, C. P., Salvemini, L., Fontana, A., Adamski, J., Schena, F. P., Cosmo, S. D., Copetti, M., et al. (2023) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2023-003422 · Cited by 9 · see citing works
Self-citationLi, S., Xu, P. H., Han, L., Mao, W., Wang, Y., Luo, G., & Yang, N. (2017) · Scientific Reports · doi:10.1038/s41598-017-09311-0 · Cited by 8 · see citing works
van der Burgh, A. C., Geurts, S., Ahmad, S., Ikram, M. A., Chaker, L., Ferraro, P. M., & Ghanbari, M. (2023) · Clinical Kidney Journal · doi:10.1093/ckj/sfad286 · Cited by 7 · see citing works
Kondou, A., Begou, O., Dotis, J., Karava, V., Panteris, E., Ταπάρκου, Ά., Gika, H., & Printza, N. (2022) · Metabolites · doi:10.3390/metabo12020145 · Cited by 7 · see citing works
NAD+ enhancers as therapeutic agents in the cardiorenal axis
Marin-Blazquez, M., Rovira, J., Ramírez-Bajo, M. J., Perez, R. Z., & Rabadán-Ros, R. (2024) · Cell Communication and Signaling · doi:10.1186/s12964-024-01903-4 · Cited by 6 · see citing works
Avin, K. G., Hughes, M. C., Chen, N. X., Srinivasan, S., O’Neill, K. D., Evan, A. P., Bacallao, R. L., Schulte, M. I., Moorthi, R. N., Gisch, D. L., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-89120-8 · Cited by 6 · see citing works
- Authors
- Goek, O.-N., Prehn, C., Sekula, P., Römisch-Margl, W., Döring, A., Gieger, C., Heier, M., Koenig, W., Wang-Sattler, R., Illig, T., Suhre, K., Adamski, J., Köttgen, A., & Meisinger, C.
- Affiliations
- University Medical Center Freiburg (DE)
- Helmholtz Munich (DE)
- Johns Hopkins University (US)
- Corresponding author
- Goek, Oemer-Necmi
- ORCID
- Venue
- Nephrology Dialysis Transplantation
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-06-05
- Volume
- 28
- Issue
- 8
- Pages
- 2131-2138
- ISSN
- 0931-0509 (ISSN-L)
- 1460-2385
- OpenAlex
- W2147888063
- Cited by
- 143
- References
- 28
- Citations by year
- 2026: 8 · 2025: 10 · 2024: 9 · 2023: 13 · 2022: 8 · 2021: 17 · 2020: 7 · 2019: 18 · 2018: 11 · 2017: 15 · 2016: 8 · 2015: 9 · 2014: 9 · 2013: 1
- FWCI
- 4.03
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Nephrology Dialysis Transplantation (publishedVersion)
- PubMed (publishedVersion)
- Site cant be reached (submittedVersion)
- OPUS (Augsburg University) (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Health Sciences › Medicine › Nephrology › Chronic Kidney Disease and Diabetes
- Health Sciences › Medicine › Nephrology › Acute Kidney Injury Research
- Keywords
- serum metabolites, renal function decline, estimated glomerular filtration rate, spermidine, kynurenine/tryptophan ratio, tryptophan metabolism, metabolite ratios, prognostic factors, metabolic pathways
- MeSH terms
- Aged, Female, Follow-Up Studies, Germany, Glomerular Filtration Rate, Humans, Kidney Function Tests, Longitudinal Studies, Male, Middle Aged, Prognosis, Risk Factors, ROC Curve, Spectrometry, Mass, Electrospray Ionization, Renal Insufficiency, Chronic, Tandem Mass Spectrometry, Metabolomics, Metabolome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
