Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Meta-Analysis
. 2016 Jan 21;7:10023.
doi: 10.1038/ncomms10023.

Genetic Associations at 53 Loci Highlight Cell Types and Biological Pathways Relevant for Kidney Function

Cristian Pattaro  1 Alexander Teumer  2   3 Mathias Gorski  4   5 Audrey Y Chu  6 Man Li  7 Vladan Mijatovic  8 Maija Garnaas  9 Adrienne Tin  7 Rossella Sorice  10 Yong Li  11 Daniel Taliun  1 Matthias Olden  4   5 Meredith Foster  12 Qiong Yang  13 Ming-Huei Chen  13   14 Tune H Pers  15   16 Andrew D Johnson  17 Yi-An Ko  18 Christian Fuchsberger  1 Bamidele Tayo  19 Michael Nalls  20 Mary F Feitosa  21 Aaron Isaacs  22   23 Abbas Dehghan  24 Pio d'Adamo  25 Adebowale Adeyemo  26 Aida Karina Dieffenbach  27   28 Alan B Zonderman  29 Ilja M Nolte  30 Peter J van der Most  30 Alan F Wright  31 Alan R Shuldiner  32   33 Alanna C Morrison  34 Albert Hofman  24 Albert V Smith  35   36 Albert W Dreisbach  37 Andre Franke  38 Andre G Uitterlinden  39 Andres Metspalu  40   41 Anke Tonjes  42 Antonio Lupo  43 Antonietta Robino  25 Åsa Johansson  44 Ayse Demirkan  22 Barbara Kollerits  45 Barry I Freedman  46 Belen Ponte  47 Ben A Oostra  48 Bernhard Paulweber  49 Bernhard K Krämer  50 Braxton D Mitchell  32   33 Brendan M Buckley  51 Carmen A Peralta  52 Caroline Hayward  31 Catherine Helmer  53   54 Charles N Rotimi  26 Christian M Shaffer  55 Christian Müller  56   57 Cinzia Sala  58 Cornelia M van Duijn  22 Aude Saint-Pierre  1   59 Daniel Ackermann  47 Daniel Shriner  26 Daniela Ruggiero  10 Daniela Toniolo  58   60 Yingchang Lu  61 Daniele Cusi  62 Darina Czamara  63 David Ellinghaus  38 David S Siscovick  64 Douglas Ruderfer  65 Christian Gieger  66 Harald Grallert  67   68   69 Elena Rochtchina  70 Elizabeth J Atkinson  71 Elizabeth G Holliday  72   73 Eric Boerwinkle  34 Erika Salvi  62 Erwin P Bottinger  61 Federico Murgia  74 Fernando Rivadeneira  39 Florian Ernst  2 Florian Kronenberg  45 Frank B Hu  75 Gerjan J Navis  76 Gary C Curhan  77 George B Ehret  78 Georg Homuth  2 Stefan Coassin  45 Gian-Andri Thun  79   80 Giorgio Pistis  58 Giovanni Gambaro  81 Giovanni Malerba  8 Grant W Montgomery  82 Gudny Eiriksdottir  35 Gunnar Jacobs  83 Guo Li  64 H-Erich Wichmann  84   85   86 Harry Campbell  87 Helena Schmidt  88 Henri Wallaschofski  89   90 Henry Völzke  3   90 Hermann Brenner  27   28 Heyo K Kroemer  91 Holly Kramer  19 Honghuang Lin  92 I Mateo Leach  93 Ian Ford  94 Idris Guessous  95   96   97 Igor Rudan  87 Inga Prokopenko  98 Ingrid Borecki  21 Iris M Heid  4   66 Ivana Kolcic  99 Ivana Persico  74 J Wouter Jukema  100   101   102   103 James F Wilson  87 Janine F Felix  24 Jasmin Divers  104 Jean-Charles Lambert  105 Jeanette M Stafford  104 Jean-Michel Gaspoz  95 Jennifer A Smith  106 Jessica D Faul  107 Jie Jin Wang  108 Jingzhong Ding  109 Joel N Hirschhorn  15   16   110 John Attia  71   72 John B Whitfield  82 John Chalmers  111 Jorma Viikari  112 Josef Coresh  7   113 Joshua C Denny  114 Juha Karjalainen  115 Jyotika K Fernandes  116 Karlhans Endlich  117 Katja Butterbach  27 Keith L Keene  118 Kurt Lohman  46 Laura Portas  74 Lenore J Launer  119 Leo-Pekka Lyytikäinen  120 Loic Yengo  121   122   123 Lude Franke  115 Luigi Ferrucci  124 Lynda M Rose  6 Lyudmyla Kedenko  49 Madhumathi Rao  12 Maksim Struchalin  125   126 Marcus E Kleber  127 Margherita Cavalieri  128 Margot Haun  45 Marilyn C Cornelis  75 Marina Ciullo  10 Mario Pirastu  74 Mariza de Andrade  71 Mark A McEvoy  129 Mark Woodward  7   111   112   130 Martin Adam  79   80 Massimiliano Cocca  58 Matthias Nauck  89   90 Medea Imboden  79   80 Melanie Waldenberger  67 Menno Pruijm  131 Marie Metzger  132 Michael Stumvoll  42 Michele K Evans  133 Michele M Sale  134 Mika Kähönen  135 Mladen Boban  99 Murielle Bochud  136 Myriam Rheinberger  5 Niek Verweij  93 Nabila Bouatia-Naji  137   138 Nicholas G Martin  82   139 Nick Hastie  31 Nicole Probst-Hensch  79   80 Nicole Soranzo  140 Olivier Devuyst  141 Olli Raitakari  142 Omri Gottesman  61 Oscar H Franco  24 Ozren Polasek  99 Paolo Gasparini  25 Patricia B Munroe  143   144 Paul M Ridker  145 Paul Mitchell  108 Paul Muntner  146   147 Christa Meisinger  68 Johannes H Smit  148 ICBP ConsortiumAGEN ConsortiumCARDIOGRAMCHARGe-Heart Failure GroupECHOGen ConsortiumPeter Kovacs  149 Philipp S Wild  150 Philippe Froguel  121   122   123 Rainer Rettig  151 Reedik Mägi  40 Reiner Biffar  152 Reinhold Schmidt  128 Rita P S Middelberg  82 Robert J Carroll  114 Brenda W Penninx  148 Rodney J Scott  153 Ronit Katz  154 Sanaz Sedaghat  24 Sarah H Wild  87 Sharon L R Kardia  106 Sheila Ulivi  155 Shih-Jen Hwang  17 Stefan Enroth  44 Stefan Kloiber  63 Stella Trompet  100 Benedicte Stengel  132 Stephen J Hancock  72   73 Stephen T Turner  156 Sylvia E Rosas  18 Sylvia Stracke  105   157 Tamara B Harris  119 Tanja Zeller  56   57 Tatijana Zemunik  99 Terho Lehtimäki  120 Thomas Illig  68 Thor Aspelund  35   36 Tiit Nikopensius  40   41 Tonu Esko  15   40   41 Toshiko Tanaka  124 Ulf Gyllensten  44 Uwe Völker  2   90 Valur Emilsson  35   158 Veronique Vitart  31 Ville Aalto  159 Vilmundur Gudnason  35   36 Vincent Chouraki  105 Wei-Min Chen  134 Wilmar Igl  44 Winfried März  160 Wolfgang Koenig  161 Wolfgang Lieb  83 Ruth J F Loos  61   162 Yongmei Liu  46 Harold Snieder  30 Peter P Pramstaller  1   163   164 Afshin Parsa  165 Jeffrey R O'Connell  32 Katalin Susztak  18 Pavel Hamet  166 Johanne Tremblay  166 Ian H de Boer  154 Carsten A Böger  5 Wolfram Goessling  9 Daniel I Chasman  6   145 Anna Köttgen  7   11 W H Linda Kao  7   113 Caroline S Fox  17   167
Collaborators, Affiliations
Free PMC article
Meta-Analysis

Genetic Associations at 53 Loci Highlight Cell Types and Biological Pathways Relevant for Kidney Function

Cristian Pattaro et al. Nat Commun. .
Free PMC article

Abstract

Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways.

Conflict of interest statement

J.T. and P.H. are consultants for Servier. J.C. received research grants and honoraria from Servier. K.S. obtained research support from Boehringer Ingelheim. The remaining authors declared no competing financial interests.

Figures

Figure 1
Figure 1. Discovery stage genome-wide association analysis.
Manhattan plots for eGFRcrea, CKD and eGFRcys. Previously reported loci are highlighted in light blue (grey labels). (a) Novel loci uncovered for eGFRcrea in the overall and in the non-diabetes groups are highlighted in blue and green, respectively. (b) Results from CKD analysis with highlighted known and novel loci for eGFRcrea. (c) Results from eGFRcys with highlighted known and novel loci for eGFRcrea and known eGFRcys loci.
Figure 2
Figure 2. Association eGFRcrea loci in subjects with and without diabetes.
Novel (a) and known (b) loci were considered. Displayed are effects and their 95% confidence intervals on ln(eGFRcrea). Results are sorted by increasing effects in the diabetes group. The majority of loci demonstrated similar effect sizes in the diabetes as compared with non-diabetes strata. SNP-specific information and detailed sample sizes are reported in Supplementary Table 5.
Figure 3
Figure 3. Bioinformatic analysis of eGFR-associated SNPs.
Connection of eGFR-associated SNPs to gene expression and variant function across a variety of tissues, pathways and regulatory marks was considered. (a) The DEPICT method shows that implicated eGFR-associated genes are highly expressed in particular tissues, including kidney and urinary tract. Shown are permutation test P values (see Methods). (b) Enrichment of eGFRcrea-associated SNPs in DHS according to discovery P value threshold. SNPs from the eGFR discovery genome-wide scan meeting a series of P value thresholds in the range 10−4–10−16 preferentially map to DHSs, when compared with a set of control SNPs, in 6 of 123 cell types. Represented are main effects odds ratios from a logistic mixed effect model. Cell types indicated with coloured lines had nominally significant enrichment (* indicate P values <0.05) at the P value <10−16 threshold and/or were derived from renal tissues (H7esDiffa2d: H7 embryonic stem cells, differentiated 2 days with BMP4, activin A and bFGF; Hae, amniotic epithelial cells; Hrce, renal cortical epithelial cells; Hre, renal epithelial cells; Hrgec, renal glomerular endothelial cells; Rptec, renal proximal tubule epithelial cells; Saec, small airway epithelial cells). (c) ENCODE/Chromatin ChIP-seq mapping: known and replicated novel eGFRcrea-associated SNPs and their perfect proxies were annotated based on genomic location using chromatin annotation maps from different tissues including adult kidney epithelial cells. P values from Fishers' exact tests for 2 × 2 tables are reported (significance level=5.6 × 10−3, see Methods). There is significant enrichment of variants mapping to enhancer regions specifically in kidney but not other non-renal tissues.
Figure 4
Figure 4. Gene set overlap analysis.
The 19 reconstituted gene sets with P value<10−5 were considered. Their overlap was estimated by computing the pairwise Pearson correlation coefficient ρ between each pair of gene sets followed by discretization into one of three bins: 0.3≤ρ<0.5, low overlap; 0.5≤ρ<0.7, medium overlap; ρ⩾0.7, high overlap. Overlap is shown by edges between gene set nodes and edges representing overlap corresponding to ρ<0.3 are not shown. The network was drawn with Cytoscape.

Comment in

Similar articles

  • Genome-Wide Association Study of Renal Function Traits: Results from the Japan Multi-Institutional Collaborative Cohort Study.
    Hishida A, Nakatochi M, Akiyama M, Kamatani Y, Nishiyama T, Ito H, Oze I, Nishida Y, Hara M, Takashima N, Turin TC, Watanabe M, Suzuki S, Ibusuki R, Shimoshikiryo I, Nakamura Y, Mikami H, Ikezaki H, Furusyo N, Kuriki K, Endoh K, Koyama T, Matsui D, Uemura H, Arisawa K, Sasakabe T, Okada R, Kawai S, Naito M, Momozawa Y, Kubo M, Wakai K; Japan Multi-Institutional Collaborative Cohort (J-MICC) Study Group. Hishida A, et al. Am J Nephrol. 2018;47(5):304-316. doi: 10.1159/000488946. Epub 2018 May 18. Am J Nephrol. 2018. PMID: 29779033 Clinical Trial.
  • A catalog of genetic loci associated with kidney function from analyses of a million individuals.
    Wuttke M, Li Y, Li M, Sieber KB, Feitosa MF, Gorski M, Tin A, Wang L, Chu AY, Hoppmann A, Kirsten H, Giri A, Chai JF, Sveinbjornsson G, Tayo BO, Nutile T, Fuchsberger C, Marten J, Cocca M, Ghasemi S, Xu Y, Horn K, Noce D, van der Most PJ, Sedaghat S, Yu Z, Akiyama M, Afaq S, Ahluwalia TS, Almgren P, Amin N, Ärnlöv J, Bakker SJL, Bansal N, Baptista D, Bergmann S, Biggs ML, Biino G, Boehnke M, Boerwinkle E, Boissel M, Bottinger EP, Boutin TS, Brenner H, Brumat M, Burkhardt R, Butterworth AS, Campana E, Campbell A, Campbell H, Canouil M, Carroll RJ, Catamo E, Chambers JC, Chee ML, Chee ML, Chen X, Cheng CY, Cheng Y, Christensen K, Cifkova R, Ciullo M, Concas MP, Cook JP, Coresh J, Corre T, Sala CF, Cusi D, Danesh J, Daw EW, de Borst MH, De Grandi A, de Mutsert R, de Vries APJ, Degenhardt F, Delgado G, Demirkan A, Di Angelantonio E, Dittrich K, Divers J, Dorajoo R, Eckardt KU, Ehret G, Elliott P, Endlich K, Evans MK, Felix JF, Foo VHX, Franco OH, Franke A, Freedman BI, Freitag-Wolf S, Friedlander Y, Froguel P, Gansevoort RT, Gao H, Gasparini P, Gaziano JM, Giedraitis V, Gieger C, Girotto G, Giulianini F, Gögele M, Gordon SD, Gudbjartsson DF, Gudnason V, Haller T, Hamet P, Harris TB, Hartman CA, Hayward C, Hellwege JN, Heng CK, Hicks AA, Hofer E, Huang W, Hutri-Kähönen N, Hwang SJ, Ikram MA, Indridason OS, Ingelsson E, Ising M, Jaddoe VWV, Jakobsdottir J, Jonas JB, Joshi PK, Josyula NS, Jung B, Kähönen M, Kamatani Y, Kammerer CM, Kanai M, Kastarinen M, Kerr SM, Khor CC, Kiess W, Kleber ME, Koenig W, Kooner JS, Körner A, Kovacs P, Kraja AT, Krajcoviechova A, Kramer H, Krämer BK, Kronenberg F, Kubo M, Kühnel B, Kuokkanen M, Kuusisto J, La Bianca M, Laakso M, Lange LA, Langefeld CD, Lee JJ, Lehne B, Lehtimäki T, Lieb W; Lifelines Cohort Study, Lim SC, Lind L, Lindgren CM, Liu J, Liu J, Loeffler M, Loos RJF, Lucae S, Lukas MA, Lyytikäinen LP, Mägi R, Magnusson PKE, Mahajan A, Martin NG, Martins J, März W, Mascalzoni D, Matsuda K, Meisinger C, Meitinger T, Melander O, Metspalu A, Mikaelsdottir EK, Milaneschi Y, Miliku K, Mishra PP; V. A. Million Veteran Program, Mohlke KL, Mononen N, Montgomery GW, Mook-Kanamori DO, Mychaleckyj JC, Nadkarni GN, Nalls MA, Nauck M, Nikus K, Ning B, Nolte IM, Noordam R, O'Connell J, O'Donoghue ML, Olafsson I, Oldehinkel AJ, Orho-Melander M, Ouwehand WH, Padmanabhan S, Palmer ND, Palsson R, Penninx BWJH, Perls T, Perola M, Pirastu M, Pirastu N, Pistis G, Podgornaia AI, Polasek O, Ponte B, Porteous DJ, Poulain T, Pramstaller PP, Preuss MH, Prins BP, Province MA, Rabelink TJ, Raffield LM, Raitakari OT, Reilly DF, Rettig R, Rheinberger M, Rice KM, Ridker PM, Rivadeneira F, Rizzi F, Roberts DJ, Robino A, Rossing P, Rudan I, Rueedi R, Ruggiero D, Ryan KA, Saba Y, Sabanayagam C, Salomaa V, Salvi E, Saum KU, Schmidt H, Schmidt R, Schöttker B, Schulz CA, Schupf N, Shaffer CM, Shi Y, Smith AV, Smith BH, Soranzo N, Spracklen CN, Strauch K, Stringham HM, Stumvoll M, Svensson PO, Szymczak S, Tai ES, Tajuddin SM, Tan NYQ, Taylor KD, Teren A, Tham YC, Thiery J, Thio CHL, Thomsen H, Thorleifsson G, Toniolo D, Tönjes A, Tremblay J, Tzoulaki I, Uitterlinden AG, Vaccargiu S, van Dam RM, van der Harst P, van Duijn CM, Velez Edward DR, Verweij N, Vogelezang S, Völker U, Vollenweider P, Waeber G, Waldenberger M, Wallentin L, Wang YX, Wang C, Waterworth DM, Bin Wei W, White H, Whitfield JB, Wild SH, Wilson JF, Wojczynski MK, Wong C, Wong TY, Xu L, Yang Q, Yasuda M, Yerges-Armstrong LM, Zhang W, Zonderman AB, Rotter JI, Bochud M, Psaty BM, Vitart V, Wilson JG, Dehghan A, Parsa A, Chasman DI, Ho K, Morris AP, Devuyst O, Akilesh S, Pendergrass SA, Sim X, Böger CA, Okada Y, Edwards TL, Snieder H, Stefansson K, Hung AM, Heid IM, Scholz M, Teumer A, Köttgen A, Pattaro C. Wuttke M, et al. Nat Genet. 2019 Jun;51(6):957-972. doi: 10.1038/s41588-019-0407-x. Epub 2019 May 31. Nat Genet. 2019. PMID: 31152163 Free PMC article.
  • Trans-ethnic Fine Mapping Highlights Kidney-Function Genes Linked to Salt Sensitivity.
    Mahajan A, Rodan AR, Le TH, Gaulton KJ, Haessler J, Stilp AM, Kamatani Y, Zhu G, Sofer T, Puri S, Schellinger JN, Chu PL, Cechova S, van Zuydam N; SUMMIT Consortium; BioBank Japan Project, Arnlov J, Flessner MF, Giedraitis V, Heath AC, Kubo M, Larsson A, Lindgren CM, Madden PAF, Montgomery GW, Papanicolaou GJ, Reiner AP, Sundström J, Thornton TA, Lind L, Ingelsson E, Cai J, Martin NG, Kooperberg C, Matsuda K, Whitfield JB, Okada Y, Laurie CC, Morris AP, Franceschini N. Mahajan A, et al. Am J Hum Genet. 2016 Sep 1;99(3):636-646. doi: 10.1016/j.ajhg.2016.07.012. Am J Hum Genet. 2016. PMID: 27588450 Free PMC article.
  • Chronic kidney disease: novel insights from genome-wide association studies.
    Böger CA, Heid IM. Böger CA, et al. Kidney Blood Press Res. 2011;34(4):225-34. doi: 10.1159/000326901. Epub 2011 Jun 21. Kidney Blood Press Res. 2011. PMID: 21691125 Review.
  • Genetic epidemiology in kidney disease.
    Ainsworth HC, Langefeld CD, Freedman BI. Ainsworth HC, et al. Nephrol Dial Transplant. 2017 Apr 1;32(suppl_2):ii159-ii169. doi: 10.1093/ndt/gfw270. Nephrol Dial Transplant. 2017. PMID: 28201750 Free PMC article. Review.
See all similar articles

Cited by 139 articles

  • The genetic architecture of membranous nephropathy and its potential to improve non-invasive diagnosis.
    Xie J, Liu L, Mladkova N, Li Y, Ren H, Wang W, Cui Z, Lin L, Hu X, Yu X, Xu J, Liu G, Caliskan Y, Sidore C, Balderes O, Rosen RJ, Bodria M, Zanoni F, Zhang JY, Krithivasan P, Mehl K, Marasa M, Khan A, Ozay F, Canetta PA, Bomback AS, Appel GB, Sanna-Cherchi S, Sampson MG, Mariani LH, Perkowska-Ptasinska A, Durlik M, Mucha K, Moszczuk B, Foroncewicz B, Pączek L, Habura I, Ars E, Ballarin J, Mani LY, Vogt B, Ozturk S, Yildiz A, Seyahi N, Arikan H, Koc M, Basturk T, Karahan G, Akgul SU, Sever MS, Zhang D, Santoro D, Bonomini M, Londrino F, Gesualdo L, Reiterova J, Tesar V, Izzi C, Savoldi S, Spotti D, Marcantoni C, Messa P, Galliani M, Roccatello D, Granata S, Zaza G, Lugani F, Ghiggeri G, Pisani I, Allegri L, Sprangers B, Park JH, Cho B, Kim YS, Kim DK, Suzuki H, Amoroso A, Cattran DC, Fervenza FC, Pani A, Hamilton P, Harris S, Gupta S, Cheshire C, Dufek S, Issler N, Pepper RJ, Connolly J, Powis S, Bockenhauer D, Stanescu HC, Ashman N, Loos RJF, Kenny EE, Wuttke M, Eckardt KU, Köttgen A, Hofstra JM, Coenen MJH, Kiemeney LA, Akilesh S, Kretzler M, Beck LH, Stengel B, Debiec H, Ronco P, Wetzels JFM, Zoledziewska M, Cucca F, Ionita-Laza I, Lee H, Hoxha E, Stahl RAK, Brenchley P, Scolari F, Zhao MH, Gharavi AG, Kleta R, Chen N, Kiryluk K. Xie J, et al. Nat Commun. 2020 Mar 30;11(1):1600. doi: 10.1038/s41467-020-15383-w. Nat Commun. 2020. PMID: 32231244 Free PMC article.
  • A Mutation in γ-Adducin Impairs Autoregulation of Renal Blood Flow and Promotes the Development of Kidney Disease.
    Fan F, Geurts AM, Pabbidi MR, Ge Y, Zhang C, Wang S, Liu Y, Gao W, Guo Y, Li L, He X, Lv W, Muroya Y, Hirata T, Prokop J, Booz GW, Jacob HJ, Roman RJ. Fan F, et al. J Am Soc Nephrol. 2020 Apr;31(4):687-700. doi: 10.1681/ASN.2019080784. Epub 2020 Feb 6. J Am Soc Nephrol. 2020. PMID: 32029431
  • Genetic polymorphism in C3 is associated with progression in chronic kidney disease (CKD) patients with IgA nephropathy but not in other causes of CKD.
    Ibrahim ST, Chinnadurai R, Ali I, Payne D, Rice GI, Newman WG, Algohary E, Adam AG, Kalra PA. Ibrahim ST, et al. PLoS One. 2020 Jan 31;15(1):e0228101. doi: 10.1371/journal.pone.0228101. eCollection 2020. PLoS One. 2020. PMID: 32004338 Free PMC article.
  • Hypothyroidism and Kidney Function: A Mendelian Randomization Study.
    Ellervik C, Mora S, Ridker PM, Chasman DI. Ellervik C, et al. Thyroid. 2020 Mar;30(3):365-379. doi: 10.1089/thy.2019.0167. Epub 2020 Feb 14. Thyroid. 2020. PMID: 31910748
  • Factors influencing harmonized health data collection, sharing and linkage in Denmark and Switzerland: A systematic review.
    Geneviève LD, Martani A, Mallet MC, Wangmo T, Elger BS. Geneviève LD, et al. PLoS One. 2019 Dec 12;14(12):e0226015. doi: 10.1371/journal.pone.0226015. eCollection 2019. PLoS One. 2019. PMID: 31830124 Free PMC article.
See all "Cited by" articles

References

    1. Eckardt K. U. et al. . Evolving importance of kidney disease: from subspecialty to global health burden. Lancet 382, 158–169 (2013) . - PubMed
    1. El Nahas M. The global challenge of chronic kidney disease. Kidney Int. 68, 2918–2929 (2005) . - PubMed
    1. Baumeister S. E. et al. . Effect of chronic kidney disease and comorbid conditions on health care costs: A 10-year observational study in a general population. Am. J. Nephrol. 31, 222–229 (2010) . - PubMed
    1. Fox C. S. et al. . Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without diabetes: a meta-analysis. Lancet 380, 1662–1673 (2012) . - PMC - PubMed
    1. Mahmoodi B. K. et al. . Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without hypertension: a meta-analysis. Lancet 380, 1649–1661 (2012) . - PMC - PubMed

Publication types

Grant support

Feedback