Introduction

Chronic kidney disease (CKD) and end stage renal disease (ESRD) are associated with significant cardiovascular morbidity and mortality, with substantial economic burden [1]–[4]. Diabetes and hypertension are the primary risk factors for CKD and ESRD [5]–[8] but do not fully account for CKD and ESRD risk [9]–[11]. Studies indicate familial aggregation of ESRD [12]. In African Americans, high risk common variants in the MYH9/APOL1 locus account for much of the excess genetic risk for non-diabetic ESRD compared to their counterparts of European descent. In contrast, comparable genetic risk loci of severe renal phenotypes have not been identified in individuals of European ancestry [13]–[15].

Recently, 16 genetic risk loci associated with estimated glomerular filtration rate (eGFR) and prevalent CKD were identified and replicated by genome wide association studies (GWAS) in about 70,000 individuals of European ancestry in the CKDGen consortium [16], [17]. Two of these loci were also identified by an independent consortium [18]. However, these studies focused on eGFR and prevalent CKD (defined as eGFR <60 ml/min/1.73m²) at one time point, which encompasses the entire spectrum of CKD, and does not does not address the question of whether these genetic factors are involved in the initiation of CKD or in the progression to ESRD, the most advanced stage of CKD. We thus sought to analyze the association of the previously identified 16 eGFR-associated loci with the development of CKD and with ESRD in a total of over 34,000 individuals of European descent.

Results

Association of SNPs with Incident CKD

Overall, 26,308 individuals of European descent, from eight population-based prospective studies, who were free of CKD at baseline were included in the incident CKD analysis (Table 1). At baseline, mean age ranged from 40.5 to 71.7 years. After a median follow-up of 7.2 years, 2122 participants developed incident CKD.

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Table 1. Cohort characteristics of the incident CKD analysis (n = 26,308).

https://doi.org/10.1371/journal.pgen.1002292.t001

Of the 16 SNPs analyzed, 11 were associated with incident CKD (Table 2): SNPs in UMOD, PRKAG2, ANXA9, DAB2, SHROOM3, DACH1, STC1, SLC34A1, ALMS1/NAT8, UBE2Q2 and GCKR showed p-values ranging from p = 4.1×10⁻⁹ in UMOD to p = 0.03 in GCKR. The odds ratios (OR) for incident CKD of the minor alleles at each of the 11 loci ranged from 0.76 per copy of the T allele (allele frequency 18%) at the UMOD locus to 1.19 per copy of the A allele (allele frequency 22%) at PRKAG2. After additional adjustment for baseline eGFR, 6 SNPs (at the UMOD, PRKAG2, ANXA9, DAB2, DACH1 and STC1 loci) remained significantly associated with incident CKD, with minimal attenuation of effect size (Table 2).

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Table 2. Results for incident CKD and ESRD, CKDGen consortium.

https://doi.org/10.1371/journal.pgen.1002292.t002

At each of the significant loci, the direction and the magnitude of the association was similar to those from the discovery analyses of eGFR and prevalent CKD [17]. For example, at the UMOD locus, each copy of the minor T allele at rs12917707 was associated with a 24% reduced risk for incident CKD, while in the CKDGen consortium the same allele was associated with higher eGFR [17]. Though the associations between incident CKD and SNPs in SLC7A9, ATXN2, PIP5K1B and VEGFA were not significant, the direction and magnitude of associations were consistent with our previous findings for the phenotypes eGFR and prevalent CKD [16], [17]. TFDP2 was the only locus where we did not observe association with incident CKD. Of the 16 SNPs tested, 15 had the same direction of association with incident CKD as their original associations with prevalent CKD. The probability of observing this many SNPs with consistency in direction of associations is 0.0002. We did not observe evidence for heterogeneity between studies at any of the 16 loci (test for heterogeneity p>0.05 for all SNPs).

Association of SNPs with ESRD

For the ESRD analysis, we included four case-control studies with a total of 3775 ESRD patients and 4577 controls of European descent without CKD (Table 3). Mean age ranged from 50.7 to 66.2 years in cases and from 47.7 to 62.1 years in controls. Although the direction and magnitude of association for 8 SNPs (at the UMOD, GCKR, PIP5K1B, PRKAG2, STC1, VEGFA, SHROOM3, and ALMS1/NAT8 loci) were consistent with our previous findings for eGFR and prevalent CKD [16], [17], only two SNPs showed nominally significant associations with ESRD (Table 2): rs1260326 in GCKR (OR =  0.93; p-value = 0.03) and rs12917707 in UMOD (OR =  0.92; p-value = 0.04). The lack of association was not likely due to heterogeneity of ESRD cases as only two SNPs showed moderate heterogeneity in their associations with ESRD (Table 2): rs4744712 at the PIP5K1B locus (p = 0.04 for heterogeneity) and rs626277 at the DACH1 locus (p = 0.02 for heterogeneity).

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Table 3. Characteristics of the ESRD case-control studies (n = 3,775 cases, n = 4,577 controls).^§

https://doi.org/10.1371/journal.pgen.1002292.t003

Discussion

Among individuals of European Ancestry, most genetic loci associated with the quantitative trait eGFR are also associated with risk for initiation of CKD, with more than half of these associations independent of eGFR at the baseline examination. In contrast, only two SNPs were nominally associated with ESRD.

To date, the genetic loci showing significant and replicated associations with ESRD are limited [13]–[15], [19]–[26], and genetic studies for incident CKD or for renal function decline in established kidney disease are only recently emerging [27]–[29]. The loci we analyzed were identified in association with renal function cross-sectionally and with prevalent CKD by GWAS in the general population. Typical of many SNPs uncovered in GWAS, the majority of these SNPs reside in intronic regions with unknown functional consequences, although several are associated with cis expression levels in liver tissue or leukocytes (Table S3) [16], [17]. These newly identified loci are non-overlapping with those previously identified in individuals of European or Asian descent with advanced diabetic nephropathy [19]–[26], or in African Americans with non-diabetic ESRD [13]–[15].

For the ESRD analysis, we had adequate power to detect effects that were similar to those for prevalent CKD in the discovery GWAS, where odds ratios ranged from 0.8 to 1.19 [16], [17]. In the present study, where associations were observed, the odds ratios for ESRD tended to be smaller and ranged from 0.92 to 1.11. There are several potential explanations for this effect dilution. First, the mechanisms involved in the initiation of CKD, the progression of CKD, and the incidence of ESRD may differ [30]–[33]. Experimental animal data and gene expression profiling in human kidney biopsies suggest differential biological pathways contributing to kidney disease initiation and progression [34]–[36]. Second, the majority of patients with CKD die of cardiovascular disease before developing ESRD [37]–[39]. Thus, the genetic findings for kidney function in the general population may not apply to the highly selected group of dialysis populations. Finally, the process of progression from CKD to ESRD often involves repeated insults including episodes of acute kidney injury by diagnostic and operative procedures and therapies [40]–[43], cardiac function deterioration [44], variation in access to adequate health care [45], [46] and other non-genetic factors [47]. Jointly, these factors may further decrease the relative impact of the small effects of SNPs derived from GWAS of eGFR in the general population at the earliest stage of disease initiation.

The observed small effect sizes for ESRD in our study are in contrast to the large effect sizes observed in relatively small cohorts of individuals of African descent for variants in the MYH9/APOL1 locus, where odds ratios for ESRD ranged from 7.3 for the G1–G2 haplotype at the APOL1 locus to 2.38 for the E1 haplotype in the MYH9 locus [13]–[15]. However, the strong effect at this locus is an exceptional case and may be a consequence of a pronounced positive selection against vulnerability for Trypanosoma brucei rhodesiense infection at the price of a higher susceptibility for non-diabetic ESRD in African Americans not observed in other ethnicities. The establishment of large cohorts is thus needed for performing GWAS of CKD initiation and progression as well as ESRD to overcome the challenge of identifying novel loci significantly associated with these phenotypes with small effect sizes.

The strength of our work lies in the large number of individuals studied. Further, we exclusively analyzed candidate SNPs identified by the unbiased method of GWAS [16], [17]. However, some limitations warrant mention. First, seven of the eight cohorts used for the incident CKD analysis were also part of the CKDGen discovery effort; thus the two samples are not entirely “independent”. However, the phenotype studied differs substantially: in Köttgen et al [17], we used prevalent eGFR data including those with CKD, while follow-up data in those without CKD at the baseline examination was used for the present incident CKD analysis. In the present work, we demonstrate robustness of our findings independent of baseline GFR. Second, we relied on only two serum creatinine measurements to define incident CKD, which may have introduced misclassification and biased our findings towards the null. Third, we did not account for pharmacological treatment with inhibitors of the renin-angiotensin-aldosterone system. Since these drugs may affect kidney function independently of kidney damage, their use may have diluted observable genetic effects [48]. Fourth, our study was not designed to detect fluctuations in eGFR. Furthermore, the etiology of ESRD in the cases we examined may vary between studies, though we observed a low degree of heterogeneity. Finally, our sample consisted of individuals of European ancestry; findings may not be generalizable to other ethnicities.

SNPs associated with eGFR in population-based studies are associated with incident CKD, whereas modest associations were observed with ESRD. Additional work is necessary to characterize the genetic underpinnings across the full range of kidney disease phenotypes, which could ultimately lead to novel diagnostic and therapeutic strategies.

Materials and Methods

Supporting Information

Acknowledgments

Atherosclerosis Risk in Communities Study (ARIC)

The authors thank the staff and participants of the ARIC study for their important contributions.

Cardiovascular Health Study (CHS)

A full list of principal CHS investigators and institutions can be found at http://www.chs-nhlbi.org/pi.htm.

CoLaus

The CoLaus authors thank Yolande Barreau, Mathieu Firmann, Vladimir Mayor, Anne-Lise Bastian, Binasa Ramic, Martine Moranville, Martine Baumer, Marcy Sagette, Jeanne Ecoffey, and Sylvie Mermoud for data collection.

Framingham Heart Study (FHS)

This research was conducted in part using data and resources from the Framingham Heart Study of the National Heart Lung and Blood Institute of the National Institutes of Health and Boston University School of Medicine. The analyses reflect intellectual input and resource development from the Framingham Heart Study investigators participating in the SNP Health Association Resource (SHARe) project.

The Rotterdam Study

We thank Pascal Arp, Mila Jhamai, Dr Michael Moorhouse, Marijn Verkerk, and Sander Bervoets for their help in creating the GWAS database. The authors are very grateful to the participants and staff from the Rotterdam Study, the participating general practioners, and the pharmacists. We would like to thank Dr. Tobias A. Knoch, Luc V. de Zeeuw, Anis Abuseiris, and Rob de Graaf, as well as their institution the Erasmus Computing Grid, Rotterdam, The Netherlands.

Accelerated Mortality on Renal Replacement (ArMORR)

The authors thank the participants, nurse and laboratory staff, medical doctors and directors of the ArMORR study for their important contributions to the study.

4D

We thank all investigators and study nurses who participated in the 4D study (www.nephrologie.uni-wuerzburg.de).

CHOICE

The authors thank the participants, staff, laboratory and medical directors from the participating clinics of DCI for their contributions to this study.

Family Heart and Kidney Study (FHKS)

We appreciate the collaboration with the following members of the Family Heart and Kidney Study (FHKS) Group: Paul König (Innsbruck University Hospital, Innsbruck, Austria); Michael Koch and Iva Poludniak (Nephrologisches Zentrum Mettmann, Germany); Ulrich Neyer, Susanne Linder, Christine Stüttler-Gut, Kathrin Berchtold, Hannelore Sprenger-Mähr, Sabina Smodek, Lisa Schuler (Feldkirch Hospital, Feldkirch, Austria); Martin Auinger (Krankenhaus Hietzing, Vienna, Austria); Martin Wiesholzer (St. Pölten Hospital, Austria); Nikolaus Zambelis and Wilfried V. Jilly (Pörtschach am Wörther See and Klagenfurt, Austria); Josef Kovarik, Ursula Lang and Heinz Fuhrmann (Wilhelminenspital Vienna, Austria); Ludwig Knabl (Zams Hospital, Austria).

GENDIAN

The support of the physicians, the patients, and the staff of the Diabetes Zentrum Mergentheim (Head: Prof. Dr. Thomas Haak), the diabetes outpatient clinic Dr Nusser+Dr Kreisel, the dialysis centers KfH Amberg, KfH Bayreuth, KfH Deggendorf, KfH Donauwörth, KfH Freising, KfH Freyung, KfH Fürth, KfH Hof, KfH Ingolstadt, KfH Kelheim, KfH München Elsenheimerstraße, KfH München-Schwabing, KfH Neumarkt, KfH Neusäß, KfH Oberschleißheim, KfH Passau, KfH Plauen, KfH Regensburg Günzstraße, KfH Regensburg Caritas-Krankenhaus, KfH Straubing, KfH Sulzbach-Rosenberg, KfH Weiden, Dialysezentrum Augsburg Dr. Kirschner, Dialysezentrum Bad Alexandersbad, KfH Bamberg, Dialysezentrum Emmering, Dialysezentrum Klinikum Landshut, Dialysezentrum Landshut, Dialysezentrum Pfarrkirchen, Dialysezentrum Schwandorf, Dr. Angela Götz, the medical doctoral students Emilia Ruff and Johanna Christ and the Study Nurse Ingrid Lugauer. The expert technical assistance of Claudia Strohmeier is gratefully acknowledged.

Mild to Moderate Kidney Disease Study (MMKD)

We appreciate the collaboration with the following members of the Mild and Moderate Kidney Disease (MMKD) Study Group: Erich Kuen, Division of Genetic Epidemiology, Innsbruck Medical University (Innsbruck, Austria); Paul König, Innsbruck University Hospital (Innsbruck, Austria); Günter Kraatz, Ernst Moritz Arndt University (Greifswald, Germany); Johannes F.E. Mann, München Schwabing Hospital (Munich, Germany); Gerhard A. Müller, Georg August University (Göttingen, Germany); Ulrich Neyer, Feldkirch Hospital (Feldkirch, Austria); Hans Köhler, Medizinische Universitätskliniken des Saarlandes (Homburg/Saar, Germany); Peter Riegler, Bozen Hospital (Bozen, Italy).