The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.
A bidirectional Mendelian randomization study supports causal effects of kidney function on blood pressure
Open accessAbstract
Blood pressure and kidney function have a bidirectional relation. Hypertension has long been considered as a risk factor for kidney function decline. However, whether intensive blood pressure control could promote kidney health has been uncertain. The kidney is known to have a major role in affecting blood pressure through sodium extraction and regulating electrolyte balance. This bidirectional relation makes causal inference between these two traits difficult. Therefore, to examine the causal relations between these two traits, we performed two-sample Mendelian randomization analyses using summary statistics of large-scale genome-wide association studies. We selected genetic instruments more likely to be specific for kidney function using meta-analyses of complementary kidney function biomarkers (glomerular filtration rate estimated from serum creatinine [eGFRcr], and blood urea nitrogen from the CKDGen Consortium). Systolic and diastolic blood pressure summary statistics were from the International Consortium for Blood Pressure and UK Biobank. Significant evidence supported the causal effects of higher kidney function on lower blood pressure. Based on the mode-based Mendelian randomization method, the effect estimates for one standard deviation (SD) higher in log-transformed eGFRcr was -0.17 SD unit (95 % confidence interval: -0.09 to -0.24) in systolic blood pressure and -0.15 SD unit (95% confidence interval: -0.07 to -0.22) in diastolic blood pressure. In contrast, the causal effects of blood pressure on kidney function were not statistically significant. Thus, our results support causal effects of higher kidney function on lower blood pressure and suggest preventing kidney function decline can reduce the public health burden of hypertension.
Overview
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
Verification
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?
In the citing paper
“An important distinction is that unlike other BP lowering agents, 24 there appears to be no association between baseline values and the magnitude of BP reduction, an observation which we have extended to people with CKD.”
From Blood Pressure Effects of Canagliflozin and Clinical Outcomes in Type 2 Diabetes and Chronic Kidney Disease: Insights From the CREDENCE Trial (2021) · cites this paper as [24]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
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
Self-citationTissue-based map of the human proteome
Uhlén, M., Fagerberg, L., Hallström, B. M., Lindskog, C., Oksvold, P., Mardinoglu, A., Sivertsson, Å., Kampf, C., Sjöstedt, E., Asplund, A., et al. (2015) · Science · doi:10.1126/science.1260419 · Cited by 15,286
Sudlow, C., Gallacher, J., Allen, N., Beral, V., Burton, P., Danesh, J., Downey, P., Elliott, P., Green, J., Landray, M., et al. (2015) · PLOS Medicine · doi:10.1371/journal.pmed.1001779 · Cited by 12,728
Bowden, J., Davey Smith, G., Haycock, P. C., & Burgess, S. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21965 · Cited by 8,922
An integrated map of genetic variation from 1,092 human genomes
The 1000 Genomes Project Consortium (2012) · Nature · doi:10.1038/nature11632 · Cited by 7,711
Mendelian Randomization Analysis With Multiple Genetic Variants Using Summarized Data
Burgess, S., Butterworth, A., & Thompson, S. G. (2013) · Genetic Epidemiology · doi:10.1002/gepi.21758 · Cited by 6,050
Mendelian randomization: genetic anchors for causal inference in epidemiological studies
Davey Smith, G., & Hemani, G. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu328 · Cited by 4,677
Mills, K. T., Bundy, J. D., Kelly, T. N., Reed, J. E., Kearney, P. M., Reynolds, K., Chen, J., & He, J. (2016) · Circulation · doi:10.1161/circulationaha.115.018912 · Cited by 3,531
Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption
Hartwig, F. P., Davey Smith, G., & Bowden, J. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyx102 · Cited by 3,485
A reference panel of 64,976 haplotypes for genotype imputation
the Haplotype Reference Consortium (2016) · Nature Genetics · doi:10.1038/ng.3643 · Cited by 2,836
Orienting the causal relationship between imprecisely measured traits using GWAS summary data.
Hemani, G., Tilling, K., & Davey Smith, G. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1007081 · Cited by 2,607
Global Burden of Hypertension and Systolic Blood Pressure of at Least 110 to 115 mm Hg, 1990-2015
Forouzanfar, M. H., Liu, P., Roth, G. A., Ng, M., Biryukov, S., Marczak, L., Alexander, L., Estep, K., Hassen Abate, K., Akinyemiju, T. F., et al. (2017) · JAMA · doi:10.1001/jama.2016.19043 · Cited by 2,381
Burgess, S., Bowden, J., Fall, T., Ingelsson, E., & Thompson, S. G. (2017) · Epidemiology · doi:10.1097/ede.0000000000000559 · Cited by 2,017
Chronic Kidney Disease and Mortality Risk
Tonelli, M. A., Wiebe, N., Culleton, B. F., House, A. A., Rabbat, C., Fok, M. N., McAlister, F. A., & Garg, A. X. (2006) · Journal of the American Society of Nephrology · doi:10.1681/asn.2005101085 · Cited by 1,680
Bias due to participant overlap in two‐sample Mendelian randomization
Burgess, S., Davies, N. M., & Thompson, S. G. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21998 · Cited by 1,624
Evaluating the potential role of pleiotropy in Mendelian randomization studies
Hemani, G., Bowden, J., & Davey Smith, G. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy163 · Cited by 1,496
Program, T. M. V., Evangelou, E., Warren, H. R., Mosen-Ansorena, D., Mifsud, B., Pazoki, R., Gao, H., Ntritsos, G., Dimou, N., Cabrera, C. P., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0205-x · Cited by 1,381
Self-citationEvolving importance of kidney disease: from subspecialty to global health burden
Eckardt, K.-U., Coresh, J., Devuyst, O., Johnson, R. J., Köttgen, A., Levey, A. S., & Levin, A. (2013) · The Lancet · doi:10.1016/s0140-6736(13)60439-0 · Cited by 1,159
Self-citationRecent Developments in Mendelian Randomization Studies
Zheng, J., Baird, D. A., Borges, M. C., Bowden, J., Hemani, G., Haycock, P., Evans, D. M., & Smith, G. D. (2017) · Current Epidemiology Reports · doi:10.1007/s40471-017-0128-6 · Cited by 1,147
Xie, X., Atkins, E., Lv, J., Bennett, A., Neal, B., Ninomiya, T., Woodward, M., MacMahon, S., Turnbull, F., Hillis, G. S., et al. (2016) · The Lancet · doi:10.1016/s0140-6736(15)00805-3 · Cited by 980
Hartwig, F. P., Davies, N. M., Hemani, G., & Davey Smith, G. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyx028 · Cited by 860
A catalog of genetic loci associated with kidney function from analyses of a million individuals
Study, L. C., Wuttke, M., Program, V. A. M. V., Li, Y., Li, M., Sieber, K. B., Feitosa, M. F., Gorski, M., Tin, A., Wang, L., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0407-x · Cited by 842
Self-citationAPOL1 Risk Variants, Race, and Progression of Chronic Kidney Disease
Parsa, A., Kao, W. H. L., Xie, D., Astor, B. C., Li, M., Hsu, C., Feldman, H. I., Parekh, R. S., Kusek, J. W., Greene, T., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1310345 · Cited by 786
Lv, J., Neal, B. C., Ehteshami, P., Ninomiya, T., Woodward, M., Rodgers, A., Wang, H., MacMahon, S. W., Turnbull, F., Hillis, G. S., et al. (2012) · PLoS Medicine · doi:10.1371/journal.pmed.1001293 · Cited by 777
Tobin, M. D., Sheehan, N. A., Scurrah, K. J., & Burton, P. R. (2005) · Statistics in Medicine · doi:10.1002/sim.2165 · Cited by 695
Levey, A. S., Gansevoort, R. T., Coresh, J., Inker, L. A., Heerspink, H. L., Grams, M. E., Greene, T., Tighiouart, H., Matsushita, K., Ballew, S. H., et al. (2020) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2019.06.009 · Cited by 591
Self-citationSchwartz, G. J., Schneider, M. F., Maier, P. S., Moxey‐Mims, M., Dharnidharka, V. R., Warady, B. A., Furth, S. L., & Muñoz, Á. (2012) · Kidney International · doi:10.1038/ki.2012.169 · Cited by 560
Renal Autoregulation in Health and Disease
Carlström, M., Wilcox, C. S., & Arendshorst, W. J. (2015) · Physiological Reviews · doi:10.1152/physrev.00042.2012 · Cited by 485
Ehret, G., Ferreira, T. C., Chasman, D. I., Jackson, A., Schmidt, E. M., Johnson, T., Þorleifsson, G., Luan, J., Donnelly, L. A., Kanoni, S., et al. (2016) · Nature Genetics · doi:10.1038/ng.3667 · Cited by 417
Self-citationAssociation between blood pressure and the rate of decline in renal function with age
Lindeman, R. D., Tobin, J. D., & Shock, N. W. (1984) · Kidney International · doi:10.1038/ki.1984.229 · Cited by 363
Orth, S. R., & Hallan, S. I. (2007) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.03740907 · Cited by 297
Item, C. B., Stöckler-Ipsiroglu, S., Stromberger, C., Mühl, A., Alessandrì, M. G., Bianchi, M. C., Tosetti, M., Fornai, F., & Cioni, G. (2001) · The American Journal of Human Genetics · doi:10.1086/323765 · Cited by 233
Qi, G., & Chatterjee, N. (2019) · Nature Communications · doi:10.1038/s41467-019-09432-2 · Cited by 207
Self-citationTime-Updated Systolic Blood Pressure and the Progression of Chronic Kidney Disease
Anderson, A. H., Yang, W. P., Townsend, R. R., Pan, Q., Chertow, G. M., Kusek, J. W., Charleston, J. B., He, J., Kallem, R. R., Lash, J. P., et al. (2015) · Annals of Internal Medicine · doi:10.7326/m14-0488 · Cited by 178
The role of the kidney in regulating arterial blood pressure
Wadei, H. M., & Textor, S. C. (2012) · Nature Reviews Nephrology · doi:10.1038/nrneph.2012.191 · Cited by 167
Smoking is a risk factor in the progression to kidney failure
Hallan, S. I., & Orth, S. R. (2011) · Kidney International · doi:10.1038/ki.2011.157 · Cited by 156
Tsai, W., Wu, H., Peng, Y., Yang, J., Chen, H., Chiu, Y., Hsu, S., Ko, M., Pai, M., Tu, Y., et al. (2017) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2017.0197 · Cited by 154
Hypertension as a risk factor for renal disease. Review of clinical and epidemiological evidence.
Whelton, P. K., & Klag, M. J. (1989) · Hypertension · doi:10.1161/01.hyp.13.5_suppl.i19 · Cited by 149
Morris, A. P., Le, T. H., Wu, H., Akbarov, A., van der Most, P. J., Hemani, G., Smith, G. D., Mahajan, A., Gaulton, K. J., Nadkarni, G. N., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-07867-7 · Cited by 141
Self-citationDifferences in Kidney Function and Incident Hypertension: The Multi-Ethnic Study of Atherosclerosis
Kestenbaum, B. R., Rudser, K. D., de Boer, I. H., Peralta, C. A., Fried, L. F., Shlipak, M. G., Palmas, W., Stehman‐Breen, C. O., & Siscovick, D. S. (2008) · Annals of Internal Medicine · doi:10.7326/0003-4819-148-7-200804010-00006 · Cited by 133
Genetic Association of Albuminuria with Cardiometabolic Disease and Blood Pressure
Haas, M. E., Aragam, K. G., Emdin, C. A., Bick, A. G., Hemani, G., Smith, G. D., & Kathiresan, S. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.08.004 · Cited by 131
Beddhu, S., Rocco, M. V., Toto, R. D., Craven, T. E., Greene, T., Bhatt, U. Y., Cheung, A. K., Cohen, D. L., Freedman, B. I., Hawfield, A. T., et al. (2017) · Annals of Internal Medicine · doi:10.7326/m16-2966 · Cited by 120
Molecular characterization of a new urea transporter in the human kidney
Olivès, B., Martial, S., Mattéi, M., Matassi, G., Rousselet, G., Ripoche, P., Cartron, J., & Bailly, P. (1996) · FEBS Letters · doi:10.1016/0014-5793(96)00425-5 · Cited by 115
GFR as the “Gold Standard”: Estimated, Measured, and True
Levey, A. S., & Inker, L. A. (2015) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2015.09.014 · Cited by 113
Baumeister, S. E., Böger, C. A., Krämer, B. K., Döring, A., Eheberg, D., Fischer, B., John, J., Köenig, W., & Meisinger, C. (2009) · American Journal of Nephrology · doi:10.1159/000272937 · Cited by 81
Rethinking hypertensive kidney disease
Kopp, J. B. (2013) · Current Opinion in Nephrology & Hypertension · doi:10.1097/mnh.0b013e3283600f8c · Cited by 80
Yu, Z., Rebholz, C. M., Wong, E., Chen, Y., Matsushita, K., Coresh, J., & Grams, M. E. (2019) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2019.02.015 · Cited by 71
Self-citationMendelian randomization with Egger pleiotropy correction and weakly informative Bayesian priors
Schmidt, A. F., & Dudbridge, F. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyx254 · Cited by 57
Zanetti, D., Rao, A. S., Gustafsson, S., Assimes, T. L., Montgomery, S. B., & Ingelsson, E. (2019) · Kidney International · doi:10.1016/j.kint.2018.12.017 · Cited by 51
Vaes, B., Beke, E., Truyers, C., Elli, S., Buntinx, F., Verbakel, J. Y. J., Goderis, G., & Pottelbergh, G. V. (2015) · BMJ Open · doi:10.1136/bmjopen-2015-007571 · Cited by 38
Huang, M., Matsushita, K., Sang, Y., Ballew, S. H., Astor, B. C., & Coresh, J. (2014) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2014.06.025 · Cited by 37
Self-citationLi, H., Hu, Q., Zhang, Q., Su, G., Xiao, H., Li, B., Shen, W., Qiu, X. Y., Lv, W., & Deng, H. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00415 · Cited by 35
Therapeutics for APOL1 nephropathies: putting out the fire in the podocyte
Heymann, J. A. W., Winkler, C. A., Hoek, M., Suszták, K., & Kopp, J. B. (2016) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfw402 · Cited by 34
Genomic Organization of the Mammalian SLC14a2 Urea Transporter Genes
Smith, C. P., & Fenton, R. A. (2006) · The Journal of Membrane Biology · doi:10.1007/s00232-006-0870-z · Cited by 33
Specific Blood Pressure Targets for Patients With Diabetic Nephropathy?
Grassi, G. M., Mancia, G., & Nilsson, P. M. (2016) · Diabetes Care · doi:10.2337/dcs15-3020 · Cited by 23
Qi, G., & Chatterjee, N. (2020) · International Journal of Epidemiology · doi:10.1093/ije/dyaa262 · Cited by 20
Self-citationJudson, G. L., Rubinsky, A. D., Shlipak, M. G., Katz, R., Kramer, H., Jacobs, D. R., Odden, M. C., & Peralta, C. A. (2017) · American Journal of Hypertension · doi:10.1093/ajh/hpx177 · Cited by 17
Qi, G., & Chatterjee, N. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/702787 · Cited by 9
Self-citationHypertension and glomerular function decline: the chicken or the egg?
Stengel, B. (2016) · Kidney International · doi:10.1016/j.kint.2016.04.016 · Cited by 8
Qi, G., & Chatterjee, N. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/367821 · Cited by 8
Self-citationIntensive Blood Pressure Targets and Kidney Disease
Chang, T. I., & Sarnak, M. J. (2018) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.02010218 · Cited by 7
Flagged first, then by citations
Cited by
Sorted by citations
Kidney damage causally affects the brain cortical structure: A Mendelian randomization study
Chen, X., Kong, J., Pan, J., Huang, K., Zhou, W., Diao, X., Cai, J., Zheng, J., Yang, X., Xie, W., et al. (2021) · EBioMedicine · doi:10.1016/j.ebiom.2021.103592 · Cited by 271
“Using MR analysis, several risk factors of CKD, and the causal relationship between CKD and other diseases have been reported [14-16]; however, the causal relation between CKD and the brain cortical structure has not been demonstrated yet [16].”
BackgroundChen, Y., Pei, P., Lei, Z., Zhang, X., Yin, D., & Zhang, F. (2021) · Angewandte Chemie International Edition · doi:10.1002/anie.202103071 · Cited by 124
Zheng, J., Zhang, Y., Rasheed, H., Walker, V. M., Sugawara, Y., Li, J., Leng, Y., Elsworth, B., Wootton, R. E., Fang, S., et al. (2021) · International Journal of Epidemiology · doi:10.1093/ije/dyab203 · Cited by 124
Self-citationMendelian Randomization Analysis as a Tool to Gain Insights into Causes of Diseases: A Primer
Tin, A., & Köttgen, A. (2021) · Journal of the American Society of Nephrology · doi:10.1681/asn.2020121760 · Cited by 118
Self-citationYe, N., Jardine, M. J., Oshima, M., Hockham, C., Heerspink, H. J. L., Agarwal, R., Bakris, G., Schutte, A. E., Arnott, C., Chang, T. I., et al. (2021) · Circulation · doi:10.1161/circulationaha.120.048740 · Cited by 115
“130 to <140 181/574 (32) 132/552 (24) 1.”
Metadata
- Authors
- Yu, Z., Coresh, J., Qi, G., Grams, M., Boerwinkle, E., Snieder, H., Teumer, A., Pattaro, C., Köttgen, A., Chatterjee, N., & Tin, A.
- Affiliations
- Johns Hopkins University (US)
- Baylor College of Medicine (US)
- University Medical Center Groningen (NL)
- Universitätsmedizin Greifswald (DE)
- Eurac Research (IT)
- Corresponding author
- Tin, Adrienne
- ORCID
- Venue
- Kidney International
- Publisher
- Elsevier BV
- Published
- 2020-09
- Volume
- 98
- Issue
- 3
- Pages
- 708-716
- ISSN
- 0085-2538 (ISSN-L)
- PMC
- PMC7784392
- OpenAlex
- W3028085141
- Cited by
- 135
- References
- 61
- Citations by year
- 2026: 8 · 2025: 25 · 2024: 29 · 2023: 17 · 2022: 24 · 2021: 26 · 2020: 6
- FWCI
- 10.70
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Kidney International (publishedVersion, other-oa)
- PubMed (publishedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion, other-oa)
- PubMed Central (acceptedVersion)
- Open Research (University of Surrey) (submittedVersion, cc-by)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- Funders
- National Human Genome Research Institute (R01 HG010480-01)
- Deutsche Forschungsgemeinschaft
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (R01 AR073178-01A1, HHSN268201100009C)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Blood Pressure and Hypertension Studies
- Health Sciences › Medicine › Nephrology › Chronic Kidney Disease and Diabetes
- Keywords
- renal function, blood pressure, bidirectional causality, estimated glomerular filtration rate, blood urea nitrogen, hypertension, renal function decline, intensive blood pressure control, systolic blood pressure, diastolic blood pressure, genetic instruments
- MeSH terms
- Blood Pressure, Humans, Hypertension, Kidney, Genome-Wide Association Study, Mendelian Randomization Analysis
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
