The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.
Gut microbiome-derived phenyl sulfate contributes to albuminuria in diabetic kidney disease
Open accessAbstract
Diabetic kidney disease is a major cause of renal failure that urgently necessitates a breakthrough in disease management. Here we show using untargeted metabolomics that levels of phenyl sulfate, a gut microbiota-derived metabolite, increase with the progression of diabetes in rats overexpressing human uremic toxin transporter SLCO4C1 in the kidney, and are decreased in rats with limited proteinuria. In experimental models of diabetes, phenyl sulfate administration induces albuminuria and podocyte damage. In a diabetic patient cohort, phenyl sulfate levels significantly correlate with basal and predicted 2-year progression of albuminuria in patients with microalbuminuria. Inhibition of tyrosine phenol-lyase, a bacterial enzyme responsible for the synthesis of phenol from dietary tyrosine before it is metabolized into phenyl sulfate in the liver, reduces albuminuria in diabetic mice. Together, our results suggest that phenyl sulfate contributes to albuminuria and could be used as a disease marker and future therapeutic target in diabetic kidney disease.
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Conditionally immortalized human podocyte cell lines established from urine
Sakairi, T., Abe, Y., Kajiyama, H., Bartlett, L. D., Howard, L., Jat, P., & Kopp, J. B. (2009) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00509.2009 · Cited by 84
Self-citationRetractedControlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
QIIME allows analysis of high-throughput community sequencing data
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Peña, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010) · Nature Methods · doi:10.1038/nmeth.f.303 · Cited by 34,887
FLASH: fast length adjustment of short reads to improve genome assemblies
Magoč, T., & Salzberg, S. L. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr507 · Cited by 15,366
R: A Language for Data Analysis and Graphics
Ihaka, R., & Gentleman, R. (1996) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.1996.10474713 · Cited by 11,220
A metagenome-wide association study of gut microbiota in type 2 diabetes
Qin, J., Li, Y., Cai, Z., Li, S., Zhu, J., Zhang, F., Liang, S., Zhang, W., Guan, Y., Shen, D., et al. (2012) · Nature · doi:10.1038/nature11450 · Cited by 6,762
Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease
Wang, Z., Klipfell, E., Bennett, B. J., Koeth, R., Levison, B. S., DuGar, B., Feldstein, A. E., Britt, E. B., Fu, X., Chung, Y.-M., et al. (2011) · Nature · doi:10.1038/nature09922 · Cited by 5,597
Cani, P. D., Bibiloni, R., Knauf, C., Waget, A., Neyrinck, A. M., Delzenne, N. M., & Burcelin, R. (2008) · Diabetes · doi:10.2337/db07-1403 · Cited by 4,819
Hsiao, E. Y., McBride, S. W., Hsien, S., Sharon, G., Hyde, E. R., McCue, T., Codelli, J. A., Chow, J., Reisman, S. E., Petrosino, J. F., et al. (2013) · Cell · doi:10.1016/j.cell.2013.11.024 · Cited by 3,283
The Treatment-Naive Microbiome in New-Onset Crohn’s Disease
Gevers, D., Kugathasan, S., Denson, L. A., Vázquez-Baeza, Y., Van Treuren, W., Ren, B., Schwager, E., Knights, D., Song, S. J., Yassour, M., et al. (2014) · Cell Host & Microbe · doi:10.1016/j.chom.2014.02.005 · Cited by 3,220
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Yang, G., Wei, J., Liu, P., Zhang, Q., Tian, Y., Hou, G., Meng, L., Xin, Y., & Jiang, X. (2021) · Metabolism · doi:10.1016/j.metabol.2021.154712 · Cited by 418
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Mohandes, S., Doke, T., Hu, H., Mukhi, D., Dhillon, P., & Susztak, K. (2023) · Journal of Clinical Investigation · doi:10.1172/jci165654 · Cited by 341
Diabetes and the Gut Microbiome
Lau, W. L., Tran, T., Rhee, C. M., Kalantar-Zadeh, K., & Vaziri, N. D. (2021) · Seminars in Nephrology · doi:10.1016/j.semnephrol.2021.03.005 · Cited by 65
Metadata
- Authors
- Kikuchi, K., Saigusa, D., Kanemitsu, Y., Matsumoto, Y., Thanai, P., Suzuki, N., Mise, K., Yamaguchi, H., Nakamura, T., Asaji, K., Mukawa, C., Tsukamoto, H., Sato, T., Oikawa, Y., Iwasaki, T., Oe, Y., Tsukimi, T., Fukuda, N. N., HO, H.-J., Nanto-Hara, F., Ogura, J., Saito, R., Nagao, S., Ohsaki, Y., Shimada, S., Suzuki, T., Toyohara, T., Mishima, E., Shima, H., Akiyama, Y., Akiyama, Y., Ichijo, M., Matsuhashi, T., Matsuo, A., Ogata, Y., Yang, C.-C., Suzuki, C., Breeggemann, M. C., Heymann, J., Shimizu, M., Ogawa, S., Takahashi, N., Suzuki, T., Owada, Y., Kure, S., Mano, N., Soga, T., Wada, T., Kopp, J. B., Fukuda, S., Hozawa, A., Yamamoto, M., Ito, S., Wada, J., Tomioka, Y., & Abe, T.
- Venue
- Nature Communications
- Published
- 2019-04-23
- Volume
- 10
- Issue
- 1
- Pages
- 1835-1835
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W2940995627
- Cited by
- 298
- References
- 65
- FWCI
- 21.03
- Type
- journal article
- Language
- en
- Open access
- gold
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- Kikuchi, K., Saigusa, D., Kanemitsu, Y., Matsumoto, Y., Thanai, P., Suzuki, N., Mise, K., Yamaguchi, H., Nakamura, T., Asaji, K., Mukawa, C., Tsukamoto, H., Sato, T., Oikawa, Y., Iwasaki, T., Oe, Y., Tsukimi, T., Fukuda, N. N., HO, H.-J., . . . Abe, T. (2019). Gut microbiome-derived phenyl sulfate contributes to albuminuria in diabetic kidney disease. Nature Communications. https://doi.org/10.1038/s41467-019-09735-4
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.