Introduction
The increasing global prevalence and high morbidity and mortality associated with progressive CKD are well established (1,2). However, despite varied efforts, we often frustratingly remain unable to adequately account for who develops CKD or does not, given similar exposure to kidney stressors. Similarly, our ability to delineate specific pathways and develop needed novel treatments has not progressed adequately.
These factors, along with improved genomics technologies, have provided the impetus for increasing efforts to define genetic factors that would account for variable outcomes. Although initial studies focused primarily on candidate genes, most findings were not validated, demonstrating a limited ability to identify, a priori, pathophysiologic genes pertaining to CKD. As our ability to perform rapid and economical genotyping progressed, a milestone was achieved in 2005 when the first genome-wide association study (GWAS) was published (3) (see Figure 1). In this agnostic approach, single nucleotide polymorphisms (SNPs) that are interspersed through the genome are genotyped and tested for association with measure of physiologic or pathophysiologic processes, providing a broad scan of genetic contributions to such traits. Since then, DNA genotyping technologies have continued to progress, both in terms of density of coverage and diminished cost, with recent large-scale GWAS including up to 10 million SNPs, whereas full genome sequencing in thousands of individuals is rapidly becoming a practical reality. These agnostic genomic scans have, in turn, led to a wide number of novel discoveries, many of which were unexpected (4). Regarding CKD genomics, although some of these findings such as APOL1 and UMOD are paving their way into the clinical domain, most findings have not yet been sufficiently studied to have any immediate clinical applications.
;)
Figure 1.: Genome -wide association studies approach summary. K, thousand; M, million; MN, membranous nephropathy; SNP, single nucleotide polymorphism.
Several reviews have already discussed different aspects of kidney genetics in detail, including the excellent recent article by Wuttke and Köttgen (5). Here, we summarize the main findings from kidney function and CKD-related GWAS studies (Figure 2), and discuss some of the lessons learned (Table 1) and challenges the nephrology community has to face to accelerate the translation of these new discoveries to the clinical domain.
Figure 2.: Karyotype representing primary genome-wide significant associations ( P <5×10 −8 ) between single nucleotide polymorphisms and kidney-related phenotypes. The figure was generated using the PhenoGram tool (
83). The ethnicity of the studied population is symbol-coded whereas the phenotype is color-coded. DKD, diabetic kidney disease; HIVAN, HIV-associated nephropathy; IgAN, IgA nephropathy; MN, membranous nephropathy.
Table 1. -
Summary of selected main GWAS category based findings and lessons learned
| Primary Phenotype |
Chr |
Gene |
Selected Top SNP |
Study Population |
Comments |
Lessons Learned |
| eGFR (general population) |
2 |
NAT8 |
rs13538; rs10206899 |
European, Transethnic |
Also associated with CKD |
Close to 100 loci identified with small effect size
Reasonable gene-level consistency across ancestral background
Numerous loci were also associated with CKD, but not ESRD (e.g., SHROOM3,NAT8, DAB2, and WDR37)
Most gene variants identified in general population cohorts have minimal prognostic power, but are able to identify many novel pathways, delineate underlying pathophysiology, and identify potential therapeutic treatments (e.g., UMOD) |
| 4 |
SHROOM3 |
rs13146355; rs17319721; rs5020545 |
Asian, European, Transethnic |
Also associated with CKD |
| 5 |
DAB2 |
rs11959928 |
European, Transethnic |
Also associated with CKD |
| 6 |
SLC22A2 |
rs2279463; rs316009 |
European, Transethnic |
|
| 10 |
WDR37 |
rs10794720 |
European |
Also associated with CKD |
| 15 |
WDR72 |
rs17730436; rs491567; rs1031755 |
Asian, European, Transethnic |
|
| 16 |
UMOD |
rs11864909; rs12917707 |
Asian, European |
Also associated with CKD, ESRD, and hypertension. Would lead to kidney lesions through activation of the NKCC2 transporter, which can be blocked by furosemide (potential translation to clinical care) |
| Progression rate of CKD |
15 |
LINC00923 |
rs653747 |
African ancestry |
Also associated with ESRD and proteinuria. Similar trend in European Americans. Minimal overlap noted with eGFR-associated SNPs |
Context-specificity of genotype-phenotype associations (established CKD versus general population) |
| Albuminuria |
10 |
CUBN |
rs1801239 |
European |
Similar trend in blacks. Also associated with ESRD in Europeans and ESRD in diabetic blacks. Also associated with kidney graft failure in Europeans |
Context-specificity of genotype-phenotype associations (CKD versus general population versus diabetic population) |
| Diabetic nephropathy |
2 |
AFF3 |
rs7583877 |
European |
Type 1 diabetes–associated ESRD |
None of these signals were consistently replicated demonstrating a complex genetic landscape
Possible role for epigenetic mechanisms and/or multiple interactions |
| 2 |
CDCA7-SP3 |
rs4972593 |
European |
Type 1 diabetes–associated ESRD in women |
| 6 |
SCAF8 |
rs955333 |
Transethnic |
Type 2 diabetic nephropathy |
| 13 |
MYO16-IRS2 |
rs9521445; rs1411766 |
Transethnic |
Both type 1 and type 2 diabetic nephropathy |
| 15 |
RGMA-MCTP2 |
rs12437854 |
European |
Type 1 diabetes–associated ESRD |
| Membranous nephropathy |
2 |
PLA2R1 |
rs4664308 |
European |
Correlated with anti-PLA2R1 antibodies in patients with MN
Antibody dosing used for diagnosis, response prediction to immunosuppressive therapy, long-term outcomes prediction (translation to clinical care) |
Focus on homogeneous disease phenotype even in face of small sample sizes can reveal strong associations
Major epistatic effect involved (OR, 78 CI, 34.6–178.2) |
| 6 |
HLA-DQA1 |
rs2187668 |
European |
Also associated with lupus nephritis, type 1 diabetic nephropathy, and FSGS in adults. Associated with steroid-sensitive nephrotic syndrome |
| IgA nephropathy |
1 |
VAV3 |
rs17019602 |
Transethnic |
Numerous variants identified. High overlap with diverse autoimmune genes |
Complex, multilocus model may be needed to better capture overall genotypic effect. Importance of pathogen-driven selective pressure to shape beneficial versus pathogenic immune responses |
| 6 |
HLA genes |
rs2523946; rs1883414; rs1794275; rs660895 |
Asian, Transethnic |
| 8 |
DEFA |
rs2738048; rs10086568 |
Asian, Transethnic |
| 16 |
ITGAM |
rs7190997; rs11574637 |
Asian, Transethnic |
| FSGS-HIVAN, Hypertension-attributed ESRD |
22 |
APOL1 |
rs73885319; rs71785313 |
African ancestry |
Strong recessive pattern Associated with CKD progression rate from diverse etiologies. Modest association with proteinuria. Associated with faster kidney allograft failure (potential translation to clinical care) |
Can have common variant with strong effect in face of strong selection factors. Importance of well characterized homogeneous phenotypes (e.g., HIVAN)
Highly variable gene effect on the basis of studied population (e.g., minimal association with eGFR in general population) |
Chr, chromosome; SNP, single nucleotide polymorphism; OR, odds ratio; HIVAN, HIV-associated nephropathy.
Studies of CKD-Defining Traits
Kidney Function in the General Population
Several large GWAS have been completed in European ancestry general population cohorts to explore eGFR genetic determinants (6–12). With sample size increasing over time (from 41,000 in 2009 to 175,000 individuals in 2016), up to 90 associations with cross-sectional measures of eGFR were progressively unveiled (see blue in Figure 2). Several studies also explored the genetic determinants of kidney function in non-European ancestry background (one East Asian GWAS [13] and two transethnic studies [12,14]) and showed the consistency of loci associations across ancestry groups despite variability in allele distribution (Figure 2).
One of the early lessons learned from these very large studies is that common variants are generally associated with small effect sizes, especially for non–disease specific and multifactorial traits such as eGFR (see Figure 1, Table 1). Indeed, all noted eGFR signals were estimated to account for <4% of eGFR phenotypic variance in the general population. However, it should be pointed out that although these signals are not necessarily well suited to predict individual eGFR level, they are of high scientific value because they are helping delineate novel pathways related to kidney physiology and CKD, and are identifying potential therapeutic targets (12,15).
Kidney Function Decline and CKD
The following studies aimed at determining the genetic contribution to kidney function decline in general, CKD, and ESRD populations. In one European population-based meta-GWAS, UMOD variants, that were previously associated with eGFR, were associated with kidney function decline over time (16). Additional studies determined that most eGFR-associated loci (including SHROOM3 and NAT8) were affecting CKD (6–8,11–13,17,18), but were only modestly affecting progression to ESRD (17). Most significantly, promoter polymorphisms in UMOD have been associated with eGFR, CKD, ESRD (6,7,9,17,19), and hypertension (20). Specifically, the rs4293393 risk variant was associated with higher uromodulin expression in human kidney samples, which has presumably been selected secondary to providing increased protection from urinary tract infections (21,22). Interestingly, in transgenic mice, overexpression of uromodulin led to salt-sensitive hypertension and age-dependent kidney lesions via activation of the NKCC2 kidney sodium transporter. These results could translate to clinical care, because the pharmacologic inhibition of NKCC2 (furosemide) was more effective in lowering BP in hypertensive patients carrying UMOD promoter risk variants (21), and hypothetically in preserving kidney function (22).
More recently, we looked for variants associated with the loss of kidney function in both African ancestry and European ancestry individuals with established CKD who were enrolled in the prospective Chronic Renal Insufficiency Cohort study (18). In this study, LINC00923 variants were associated with nondiabetic CKD progression rate, time to ESRD, and proteinuria in blacks, with a similar trend in whites (see green in Figure 2).
The overall minimal overlap between identified loci associated with kidney function decline in general population and CKD-specific cohorts highlights the context-specific nature of genotype-phenotype associations.
Albuminuria
Albuminuria remains one of the strongest predictors of CKD outcomes; however, to date, the only reliable association with albuminuria remains the CUBN locus, which was identified in a European ancestry general population (23,24) (see red in Figure 2), with a similar trend in blacks (23). Moreover, CUBN variants were modestly associated with an increased risk for ESRD and a trend for kidney graft failure in whites (25), and with ESRD in black patients with diabetes (26).
Interestingly, variants associated with cross-sectional measure of eGFR in the population-based cohorts were not found to be associated with albuminuria, which would suggest a distinct genetic contribution to these factors (24). Conversely, in individuals with established CKD, we noted nearly a third of loci associated with eGFR decline to be associated with proteinuria, suggesting a potential shared genetic contribution for progressive CKD and proteinuria (18). Lastly, several variants were associated with albuminuria in type 2 diabetic populations (24,27), demonstrating again the context specificity of genotype-phenotype associations and the importance of replication in similar populations.
Specific Etiologies
Diabetic Nephropathy
Diabetic nephropathy remains the leading cause for ESRD and has a high heritability of approximately 35% (28). Nevertheless, despite numerous efforts, the identification of gene variants robustly associated with type 1 and type 2 diabetic nephropathy has been limited. Interestingly, a transethnic meta-analysis revealed that the MYO16/IRS2 locus would be associated with susceptibility to both type 1 and 2 diabetic nephropathies (29), and a SCAF8 variant was consistently associated with type 2 diabetic nephropathy across populations of different ancestry (30) (see dark gray in Figure 2). In addition, GWAS carried out in European populations highlighted several associations with type 1 diabetes–associated ESRD (31,32), and other studies revealed candidates for both type 1– and type 2–associated ESRD (26,33–37). However, a subsequent comprehensive, large, meta-GWAS effort was unable to identify clear loci consistently associated with diabetic nephropathy and many of the previous identified candidate signals were not validated (28). However, given the general modest effect size for the associated loci in each of the discovery cohorts, it is challenging to discern between lack of reproducibility due to difference in populations, study design, outcome ascertainment, and/or false positives. Overall, these studies demonstrate the genetic landscape of diabetic nephropathy to be more complex than anticipated and bring forth the possibility that epigenetic factors, as well as potential higher order interactions, may play a prominent role.
Epigenetic modifications consist of dynamic acquired and at times heritable changes on our genome, which, although not modifying the DNA nucleotide sequence, can strongly affect gene regulation. Epigenetic profiles can adjust in response to the environment, including nutrition, glycemic levels, drug exposures, inflammation, and oxidative stress. Even though the study of epigenetic contribution to diabetic nephropathy is in its early stage (most reports were performed in vitro and in animal models—see review [38]), it is believed that epigenetic modifications could mediate the “metabolic memory” phenomenon. This was highlighted in large studies where long-term protection from diabetes complications, including nephropathy, was observed for >10 years after a tight control of glycemia (39,40). This could potentially also account, in part, for why SNP-based studies have failed to identify more consistent associations with diabetic nephropathy.
Membranous Nephropathy
Membranous nephropathy (MN) is a common cause of GN and nephrotic syndrome leading to progressive CKD. A European GWAS revealed two loci strongly associated with MN risk using a discovery cohort of only 146 cases and further extending the results in 556 cases (see gray in Figure 2): PLA2R1 (odds ratio [OR], 2.3 CI, 2–2.6; P=8.6×10−29) and HLA-DQA1 (OR, 4.3 CI, 3.5–5; P=8.0×10−93) (41). Remarkably, the effect size of these loci was even stronger when analyzed jointly with a striking OR of 78 CI, 34.6–178.2, indicating an epistatic effect between PLA2R1 and HLA-DQA1 variants. Interestingly, it was shown that PLA2R1 associations are specific to MN (42), whereas HLA-DQA1 variants also associated with lupus nephritis, type 1 diabetic nephropathy, and FSGS in adults (42), as well as with steroid-sensitive nephrotic syndrome in children (43). Of note, the exploration of acquired nephrotic syndrome in Japanese did not identify HLA-DQA1 associations, but revealed GPC5 as another susceptibility factor (44).
The PLA2R1 specificity for MN is consistent with the presence of anti-PLA2R1 antibodies in approximately 70% of patients with MN (45,46), some of the remaining variability being explained by THSD7A autoantibodies (47). This has enabled a rapid translation to clinical practice for improved diagnosis and for predicting response to immunosuppressive therapy (48) and long-term outcomes (49) for patients with MN (see [50] for a review).
Lessons from these studies do not only pertain to the importance of and interaction between the production of autoantigens and heightened immune response in MN, but even more so demonstrate the possibility of very strong single gene effects that can be uncovered in small-sized cohorts of individuals with homogenous disease etiologies (Figure 1, Table 1).
IgA Nephropathy
IgA nephropathy (IgAN), the most common form of primary GN (51), perfectly exemplifies how multiple gene interactions can affect kidney injury. The increasing number of larger GWAS in European and Asian populations has progressively unveiled numerous loci associated with IgAN, including HLA, DEFA, ITGAM, and VAV3 (see pink in Figure 2) (52–55). The distribution of the combined risk alleles strongly correlates with the worldwide geographic prevalence gradient (high prevalence in Asians, intermediate in Europeans, and rare in Africans), and suggests that the selective pressure exerted on the host by intestinal pathogens, particularly by helminths, during evolution would have shaped the susceptibility to IgAN (56,57). In addition to these common genetic variations, two recent studies involving exon sequencing suggested a potential role for rare variants in IgAN susceptibility (58,59).
Overall, these studies highlight a more complex multilocus model for IgAN compared with MN, and also reveal the extent of pathogen selective pressures to shape strong protective immune responses versus detrimental increased autoimmune disease risk (including IgAN, lupus nephritis, and inflammatory bowel diseases [57,60,61]).
APOL1-Related Kidney Disease
The disparity in ESRD in individuals of African ancestry compared with European ancestry has long been noted (62). The identification of APOL1 risk variants as the genetic determinant explaining most of the disparity for FSGS-HIV-associated nephropathy (HIVAN) (OR, 17 CI, 11–26 for FSGS; and OR, 29 CI, 13–68.5 for HIVAN) and hypertensive-associated nephropathy represents one of the most significant GWAS discoveries within the medical field (see yellow in Figure 2) (63–65). The APOL1 high-risk genotypes only occur in African-derived chromosomes (66). These variants are believed to have reached such high frequencies due to a recent selection event in West Africa that is primarily attributed to providing protection from Trypanosoma brucei rhodesiense, the pathogen causing acute African sleeping sickness (65,67).
The APOL1 high-risk signal was extended to numerous kidney conditions, including hypertension-attributed ESRD (65), SLE-associated glomerulopathy (68), proteinuria (69), and CKD progression rate (70). Interestingly, whereas cross-sectional prevalent ESRD studies did not demonstrate a significant association between APOL1 high-risk genotype and nephropathy in patients with diabetes, we identified a clear and consistent association with faster CKD progression in APOL1 high-risk individuals regardless of diabetes status. We notably found that CKD individuals with diabetes and APOL1 high-risk genotype progressed much faster than any other groups, including the APOL1 risk individuals with no diabetes (rate of eGFR loss of −4.3 versus −2.9 ml/min per year), demonstrating that APOL1 risk effect is additive to diabetic nephropathy. Our observation therefore suggests that although APOL1 high-risk genotype does not appear to cause diabetic nephropathy (hyperglycemic milieu does), it causes a more rapid progression of established diabetic nephropathy (70).
APOL1 genotyping could soon affect kidney transplantation practice. Indeed, a strong association between the kidney donor APOL1 risk genotype and halving of time to kidney allograft failure has been shown (71,72), whereas the allograft recipient genotype does not seem to affect graft survival (73). These findings raise some important issues: should kidneys from APOL1 risk genotype donors be used? Given the ongoing shortage of organs and that most risk genotype kidneys are still viable, they should arguably be used. However, the approximately two-fold increased risk for failure warrants further discussion regarding potential reclassification of such kidneys as higher-risk organs. Another critical question pertains to the risk assessment for living donors with APOL1 risk genotype. Because APOL1 risk genotypes appear to affect the progression of all CKD causes and because the rate of postdonation CKD is relatively high in blacks, one should presume that donors carrying APOL1 risk genotypes are at increased risk for progressive CKD. Although at this time no definitive risk estimates can be provided, given the lack of long-term outcome data for such donors, it is encouraging to see the new APOL1 Long-term Kidney Transplantation Outcomes Network (APOLLO) initiative by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) that aims at initiating a large, observational, multicenter cohort of APOL1 risk donors and kidney recipients across the United States to more precisely quantify the risk to both donors and recipients. In the meantime, a conservative approach, notably in young potential donors in whom long-term CKD risk estimation is challenging, is fitting in our quest to “first do no harm.”
Sickle Cell Trait
Sickle cell trait (SCT) is present in 7%–9% of blacks and had typically been described as a relatively benign carrier state. However, this assumption was recently proven wrong in two large seminal analyses of nearly 10,000 and 16,000 individuals, where a near two-fold increase in incident CKD and albuminuria (74), as well as a two-fold increase in incident ESRD (75), were noted in individuals with SCT. Although the role of SCT in CKD was not realized by standard GWAS analyses, it is fitting and important enough to mention in this review, notably because it is common, and the noted effect sizes for incident CKD and ESRD are similar to that conferred by APOL1 high-risk genotype in the general population. SCT may indeed account for a significant portion of the remaining racial disparity in CKD that is unaccounted for by APOL1 genotype. Accordingly, efforts to better define the phenotype of SCT-associated CKD are sorely needed to shed further light on this longstanding underappreciated genetic and potentially modifiable CKD risk factor. This also further demonstrates the counter-selective pressures for gene variants’ beneficial effects in protecting from infectious diseases versus inducing kidney injury (e.g., UMOD, SCT, APOL1, and IgAN variants), and demonstrates that many of these variants are not simply random disease variants, but the end result of balancing multiple environmental/evolutionary pressures.
Discussion
The rate of discovery and identification of novel gene loci related to kidney function and CKD over the last 10 years has greatly exceeded our ability to synthesize the information. Despite the nice genomic success stories which are moving into the clinical domain (e.g., APOL1, PLA2R1, and UMOD), the nephrology field has also faced similar challenges and, for some, disappointments to those experienced by every single discipline that has dived into the genomics waters: (1) finding the balance between exploring large population cohorts with increased statistical power or smaller specific, homogeneous, and even extreme, well defined phenotypes; (2) most findings only account for a very small amount of the trait variance; and (3) translating the genetic association–based findings to the clinical domain. However, it is essential to bear in mind that the strength of a single gene variant may convey little of the overall functional relevance of the gene. For example, although common SNPs in CUBN and UMOD showed weak-to-modest association with albuminuria and CKD, respectively, rare UMOD mutations have been associated with tubular dysfunction, microcysts, and progressive CKD (76), whereas a CUBN mutation has been strongly associated with overt proteinuria (77), which better illustrates the overall effect of the gene on outcomes, and the potential for pharmacologic intervention.
At this point, there is no doubt that kidney genomics has led to numerous novel discoveries and elucidated new pathways, and that it will continue to do so, notably within disease-specific cohorts, further diversification of studied populations, and with next-generation sequencing technologies. The question at hand now is, whether further refinement of established methods will soon reach a point of diminishing returns and whether new approaches will be required, if we are to efficiently translate genomics-based findings to improving outcomes for individuals with, or at risk for, kidney disease.
Moving Forward
We have long taken a reductionist approach to medical research. Breaking down complex interactive processes into individual components has undoubtedly worked in greatly advancing science, but is not necessarily suitable to predict complex interactions nor to capture multifaceted processes leading to kidney disease (78,79). At this point, genomics can no longer be viewed as single SNPs working independently to meaningfully affect clinical outcomes; it must be viewed in the context of its transcriptional and translational regulation and dynamic interactions. Correspondingly, we must also appreciate that the effect of a genetic variant is often not fixed, but highly variable and situational. For example, APOL1 risk genotype has a range of no significant association with eGFR in the general population, to approximately two-fold increase in CKD, seven-fold increase in hypertensive-associated ESRD, 17-fold increased odds for FSGS, and near 30-fold increased odds of HIVAN. Moreover, given the sizeable gap related to the number of steps and potential pathways leading from any given gene variation to clinical outcomes, it stands that the association and integration of gene variants with intermediate processes (e.g., transcriptome, proteome, epigenome, and metabolome) using systems-based analytic approaches (e.g., Bayesian and neural network based) will be necessary. This will allow both leveraging multiomics outputs and capturing complex biologic processes to help bridge the gap. Accordingly, we feel that maximizing efforts to bring forth systems-based analytic approaches is now, more than ever, necessary.
It had long been hypothesized that, irrespective of the cause of kidney injury, progression of CKD converged into a common pathway of local inflammation followed by injury, fibrosis, and decline in GFR; but this did not necessarily bear out. Moreover, this view inadvertently supported the often nonspecific staging of CKD based primarily on GFR and levels of proteinuria, with insufficient attention to metrics of tubular function and disease heterogeneity (80). Indeed, this grouping of diverse processes such as “hypertensive nephropathy” could account, in part, for the contrast in single gene variant effect size between broad eGFR population-based cohorts and disease-specific homogenous cohorts (e.g., MN and HIVAN), and perhaps for the lack of success with most CKD clinical trials targeted at heterogeneous groups of individuals with CKD.
Contrasting with the nephrology field, cancer biologists have been able to obtain various tissue samples pertaining to clinical cases and unveil many of the molecular pathophysiology mechanisms underlying cancer diversity (81,82). This strategy has allowed the delineation of numerous disease subtypes, increased accuracy of prognostic models, and tailoring of clinical trials. In order to help overcome this serious limitation within the nephrology domain, the NIDDK has recently launched the Kidney Precision Medicine Project (KPMP) initiative to prospectively collect kidney biopsy tissue from individuals with primarily non–immune mediated CKD and AKI. The goal will then be to apply state-of-the-art agnostic “omics” techniques to develop a detailed molecular atlas of healthy and diseased kidney tissues. This should, in turn, allow the critically needed detailed phenotypic classification of new homogenous disease subgroups on the basis of the underlying molecular pathophysiology and, secondarily, enhance our ability to identify genetic and nongenetic processes leading to them. Indeed, even FSGS, which is a kidney biopsy–based diagnosis, refers to a pattern of injuries and is likely the end result of a wide variety of pathophysiologic processes. Importantly, such endeavors should significantly improve our ability to provide more precise diagnoses and prognoses and identify specific targets needed for treatment.
Achieving the promise of genomics-based tailored treatment modalities will undoubtedly require a conscious effort in moving from a longstanding culture of reductionism to true integrative systems-based approaches, as well as redefining many of the existing heterogeneous clinical-based kidney disease classifications to those on the basis of specific molecular pathways. Fortunately, key steps toward these achievable paradigm shifts are being put in place. So, although the patience needed to translate, validate, and implement the vast amount of novel genomics-related data may be more than some had hoped for, the harvest is as promising as ever.
Disclosures
None.
References
1. Hill NR, Fatoba ST, Oke JL, Hirst JA, O’Callaghan CA, Lasserson DS, Hobbs FDR: Global prevalence of
chronic kidney disease - a systematic review and meta-analysis. PLoS One 11: e0158765, 201627383068
2. Gansevoort RT, Correa-Rotter R, Hemmelgarn BR, Jafar TH, Heerspink HJL, Mann JF, Matsushita K, Wen CP:
Chronic kidney disease and cardiovascular risk: Epidemiology, mechanisms, and prevention. Lancet 382: 339–352, 201323727170
3. Klein RJ, Zeiss C, Chew EY, Tsai J-Y, Sackler RS, Haynes C, Henning AK, SanGiovanni JP, Mane SM, Mayne ST, Bracken MB, Ferris FL, Ott J, Barnstable C, Hoh J: Complement factor H polymorphism in age-related macular degeneration. Science 308: 385–389, 200515761122
4. MacArthur J, Bowler E, Cerezo M, Gil L, Hall P, Hastings E, Junkins H, McMahon A, Milano A, Morales J, Pendlington ZM, Welter D, Burdett T, Hindorff L, Flicek P, Cunningham F, Parkinson H: The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog). Nucleic Acids Res 45[D1]: D896–D901, 201727899670
5. Wuttke M, Köttgen A: Insights into kidney diseases from genome-wide association studies. Nat Rev Nephrol 12: 549–562, 201627477491
6. Köttgen A, Glazer NL, Dehghan A, Hwang S-J, Katz R, Li M, Yang Q, Gudnason V, Launer LJ, Harris TB, Smith AV, Arking DE, Astor BC, Boerwinkle E, Ehret GB, Ruczinski I, Scharpf RB, Chen YD, de Boer IH, Haritunians T, Lumley T, Sarnak M, Siscovick D, Benjamin EJ, Levy D, Upadhyay A, Aulchenko YS, Hofman A, Rivadeneira F, Uitterlinden AG, van Duijn CM, Chasman DI, Paré G, Ridker PM, Kao WHL, Witteman JC, Coresh J, Shlipak MG, Fox CS: Multiple loci associated with indices of renal function and
chronic kidney disease. Nat Genet 41: 712–717, 200919430482
7. Köttgen A, Pattaro C, Böger CA, Fuchsberger C, Olden M, Glazer NL, Parsa A, Gao X, Yang Q, Smith AV, O’Connell JR, Li M, Schmidt H, Tanaka T, Isaacs A, Ketkar S, Hwang SJ, Johnson AD, Dehghan A, Teumer A, Paré G, Atkinson EJ, Zeller T, Lohman K, Cornelis MC, Probst-Hensch NM, Kronenberg F, Tönjes A, Hayward C, Aspelund T, Eiriksdottir G, Launer LJ, Harris TB, Rampersaud E, Mitchell BD, Arking DE, Boerwinkle E, Struchalin M, Cavalieri M, Singleton A, Giallauria F, Metter J, de Boer IH, Haritunians T, Lumley T, Siscovick D, Psaty BM, Zillikens MC, Oostra BA, Feitosa M, Province M, de Andrade M, Turner ST, Schillert A, Ziegler A, Wild PS, Schnabel RB, Wilde S, Munzel TF, Leak TS, Illig T, Klopp N, Meisinger C, Wichmann HE, Koenig W, Zgaga L, Zemunik T, Kolcic I, Minelli C, Hu FB, Johansson A, Igl W, Zaboli G, Wild SH, Wright AF, Campbell H, Ellinghaus D, Schreiber S, Aulchenko YS, Felix JF, Rivadeneira F, Uitterlinden AG, Hofman A, Imboden M, Nitsch D, Brandstätter A, Kollerits B, Kedenko L, Mägi R, Stumvoll M, Kovacs P, Boban M, Campbell S, Endlich K, Völzke H, Kroemer HK, Nauck M, Völker U, Polasek O, Vitart V, Badola S, Parker AN, Ridker PM, Kardia SL, Blankenberg S, Liu Y, Curhan GC, Franke A, Rochat T, Paulweber B, Prokopenko I, Wang W, Gudnason V, Shuldiner AR, Coresh J, Schmidt R, Ferrucci L, Shlipak MG, van Duijn CM, Borecki I, Krämer BK, Rudan I, Gyllensten U, Wilson JF, Witteman JC, Pramstaller PP, Rettig R, Hastie N, Chasman DI, Kao WH, Heid IM, Fox CS: New loci associated with kidney function and
chronic kidney disease. Nat Genet 42: 376–384, 201020383146
8. Chambers JC, Zhang W, Lord GM, van der Harst P, Lawlor DA, Sehmi JS, Gale DP, Wass MN, Ahmadi KR, Bakker SJL, Beckmann J, Bilo HJG, Bochud M, Brown MJ, Caulfield MJ, Connell JM, Cook HT, Cotlarciuc I, Davey Smith G, de Silva R, Deng G, Devuyst O, Dikkeschei LD, Dimkovic N, Dockrell M, Dominiczak A, Ebrahim S, Eggermann T, Farrall M, Ferrucci L, Floege J, Forouhi NG, Gansevoort RT, Han X, Hedblad B, Homan van der Heide JJ, Hepkema BG, Hernandez-Fuentes M, Hypponen E, Johnson T, de Jong PE, Kleefstra N, Lagou V, Lapsley M, Li Y, Loos RJ, Luan J, Luttropp K, Maréchal C, Melander O, Munroe PB, Nordfors L, Parsa A, Peltonen L, Penninx BW, Perucha E, Pouta A, Prokopenko I, Roderick PJ, Ruokonen A, Samani NJ, Sanna S, Schalling M, Schlessinger D, Schlieper G, Seelen MA, Shuldiner AR, Sjögren M, Smit JH, Snieder H, Soranzo N, Spector TD, Stenvinkel P, Sternberg MJ, Swaminathan R, Tanaka T, Ubink-Veltmaat LJ, Uda M, Vollenweider P, Wallace C, Waterworth D, Zerres K, Waeber G, Wareham NJ, Maxwell PH, McCarthy MI, Jarvelin MR, Mooser V, Abecasis GR, Lightstone L, Scott J, Navis G, Elliott P, Kooner JS: Genetic loci influencing kidney function and
chronic kidney disease. Nat Genet 42: 373–375, 201020383145
9. Gudbjartsson DF, Holm H, Indridason OS, Thorleifsson G, Edvardsson V, Sulem P, de Vegt F, d’Ancona FCH, den Heijer M, Wetzels JF, Franzson L, Rafnar T, Kristjansson K, Bjornsdottir US, Eyjolfsson GI, Kiemeney LA, Kong A, Palsson R, Thorsteinsdottir U, Stefansson K: Association of variants at UMOD with
chronic kidney disease and kidney stones-role of age and comorbid diseases. PLoS Genet 6: e1001039, 201020686651
10. Li M, Li Y, Weeks O, Mijatovic V, Teumer A, Huffman JE, Tromp G, Fuchsberger C, Gorski M, Lyytikäinen LP, Nutile T, Sedaghat S, Sorice R, Tin A, Yang Q, Ahluwalia TS, Arking DE, Bihlmeyer NA, Böger CA, Carroll RJ, Chasman DI, Cornelis MC, Dehghan A, Faul JD, Feitosa MF, Gambaro G, Gasparini P, Giulianini F, Heid I, Huang J, Imboden M, Jackson AU, Jeff J, Jhun MA, Katz R, Kifley A, Kilpeläinen TO, Kumar A, Laakso M, Li-Gao R, Lohman K, Lu Y, Mägi R, Malerba G, Mihailov E, Mohlke KL, Mook-Kanamori DO, Robino A, Ruderfer D, Salvi E, Schick UM, Schulz CA, Smith AV, Smith JA, Traglia M, Yerges-Armstrong LM, Zhao W, Goodarzi MO, Kraja AT, Liu C, Wessel J, Boerwinkle E, Borecki IB, Bork-Jensen J, Bottinger EP, Braga D, Brandslund I, Brody JA, Campbell A, Carey DJ, Christensen C, Coresh J, Crook E, Curhan GC, Cusi D, de Boer IH, de Vries AP, Denny JC, Devuyst O, Dreisbach AW, Endlich K, Esko T, Franco OH, Fulop T, Gerhard GS, Glümer C, Gottesman O, Grarup N, Gudnason V, Hansen T, Harris TB, Hayward C, Hocking L, Hofman A, Hu FB, Husemoen LL, Jackson RD, Jørgensen T, Jørgensen ME, Kähönen M, Kardia SL, König W, Kooperberg C, Kriebel J, Launer LJ, Lauritzen T, Lehtimäki T, Levy D, Linksted P, Linneberg A, Liu Y, Loos RJ, Lupo A, Meisinger C, Melander O, Metspalu A, Mitchell P, Nauck M, Nürnberg P, Orho-Melander M, Parsa A, Pedersen O, Peters A, Peters U, Polasek O, Porteous D, Probst-Hensch NM, Psaty BM, Qi L, Raitakari OT, Reiner AP, Rettig R, Ridker PM, Rivadeneira F, Rossouw JE, Schmidt F, Siscovick D, Soranzo N, Strauch K, Toniolo D, Turner ST, Uitterlinden AG, Ulivi S, Velayutham D, Völker U, Völzke H, Waldenberger M, Wang JJ, Weir DR, Witte D, Kuivaniemi H, Fox CS, Franceschini N, Goessling W, Köttgen A, Chu AY; CHARGE Glycemic-T2D Working Group; CHARGE Blood Pressure Working Group: SOS2 and ACP1 loci identified through large-scale exome chip analysis regulate kidney development and function. J Am Soc Nephrol 28: 981–994, 2017
11. Pattaro C, Köttgen A, Teumer A, Garnaas M, Böger CA, Fuchsberger C, Olden M, Chen M-H, Tin A, Taliun D, Li M, Gao X, Gorski M, Yang Q, Hundertmark C, Foster MC, O’Seaghdha CM, Glazer N, Isaacs A, Liu C-T, Smith AV, O’Connell JR, Struchalin M, Tanaka T, Li G, Johnson AD, Gierman HJ, Feitosa M, Hwang S-J, Atkinson EJ, Lohman K, Cornelis MC, Johansson Å, Tönjes A, Dehghan A, Chouraki V, Holliday EG, Sorice R, Kutalik Z, Lehtimäki T, Esko T, Deshmukh H, Ulivi S, Chu AY, Murgia F, Trompet S, Imboden M, Kollerits B, Pistis G, Harris TB, Launer LJ, Aspelund T, Eiriksdottir G, Mitchell BD, Boerwinkle E, Schmidt H, Cavalieri M, Rao M, Hu FB, Demirkan A, Oostra BA, de Andrade M, Turner ST, Ding J, Andrews JS, Freedman BI, Koenig W, Illig T, Döring A, Wichmann HE, Kolcic I, Zemunik T, Boban M, Minelli C, Wheeler HE, Igl W, Zaboli G, Wild SH, Wright AF, Campbell H, Ellinghaus D, Nöthlings U, Jacobs G, Biffar R, Endlich K, Ernst F, Homuth G, Kroemer HK, Nauck M, Stracke S, Völker U, Völzke H, Kovacs P, Stumvoll M, Mägi R, Hofman A, Uitterlinden AG, Rivadeneira F, Aulchenko YS, Polasek O, Hastie N, Vitart V, Helmer C, Wang JJ, Ruggiero D, Bergmann S, Kähönen M, Viikari J, Nikopensius T, Province M, Ketkar S, Colhoun H, Doney A, Robino A, Giulianini F, Krämer BK, Portas L, Ford I, Buckley BM, Adam M, Thun GA, Paulweber B, Haun M, Sala C, Metzger M, Mitchell P, Ciullo M, Kim SK, Vollenweider P, Raitakari O, Metspalu A, Palmer C, Gasparini P, Pirastu M, Jukema JW, Probst-Hensch NM, Kronenberg F, Toniolo D, Gudnason V, Shuldiner AR, Coresh J, Schmidt R, Ferrucci L, Siscovick DS, van Duijn CM, Borecki I, Kardia SL, Liu Y, Curhan GC, Rudan I, Gyllensten U, Wilson JF, Franke A, Pramstaller PP, Rettig R, Prokopenko I, Witteman JC, Hayward C, Ridker P, Parsa A, Bochud M, Heid IM, Goessling W, Chasman DI, Kao WH, Fox CS; CARDIoGRAM Consortium; ICBP Consortium; CARe Consortium; Wellcome Trust Case Control Consortium 2 (WTCCC2): Genome-wide association and functional follow-up reveals new loci for kidney function. PLoS Genet 8: e1002584, 201222479191
12. Pattaro C, Teumer A, Gorski M, Chu AY, Li M, Mijatovic V, Garnaas M, Tin A, Sorice R, Li Y, Taliun D, Olden M, Foster M, Yang Q, Chen M-H, Pers TH, Johnson AD, Ko YA, Fuchsberger C, Tayo B, Nalls M, Feitosa MF, Isaacs A, Dehghan A, d’Adamo P, Adeyemo A, Dieffenbach AK, Zonderman AB, Nolte IM, van der Most PJ, Wright AF, Shuldiner AR, Morrison AC, Hofman A, Smith AV, Dreisbach AW, Franke A, Uitterlinden AG, Metspalu A, Tonjes A, Lupo A, Robino A, Johansson Å, Demirkan A, Kollerits B, Freedman BI, Ponte B, Oostra BA, Paulweber B, Krämer BK, Mitchell BD, Buckley BM, Peralta CA, Hayward C, Helmer C, Rotimi CN, Shaffer CM, Müller C, Sala C, van Duijn CM, Saint-Pierre A, Ackermann D, Shriner D, Ruggiero D, Toniolo D, Lu Y, Cusi D, Czamara D, Ellinghaus D, Siscovick DS, Ruderfer D, Gieger C, Grallert H, Rochtchina E, Atkinson EJ, Holliday EG, Boerwinkle E, Salvi E, Bottinger EP, Murgia F, Rivadeneira F, Ernst F, Kronenberg F, Hu FB, Navis GJ, Curhan GC, Ehret GB, Homuth G, Coassin S, Thun GA, Pistis G, Gambaro G, Malerba G, Montgomery GW, Eiriksdottir G, Jacobs G, Li G, Wichmann HE, Campbell H, Schmidt H, Wallaschofski H, Völzke H, Brenner H, Kroemer HK, Kramer H, Lin H, Leach IM, Ford I, Guessous I, Rudan I, Prokopenko I, Borecki I, Heid IM, Kolcic I, Persico I, Jukema JW, Wilson JF, Felix JF, Divers J, Lambert JC, Stafford JM, Gaspoz JM, Smith JA, Faul JD, Wang JJ, Ding J, Hirschhorn JN, Attia J, Whitfield JB, Chalmers J, Viikari J, Coresh J, Denny JC, Karjalainen J, Fernandes JK, Endlich K, Butterbach K, Keene KL, Lohman K, Portas L, Launer LJ, Lyytikäinen LP, Yengo L, Franke L, Ferrucci L, Rose LM, Kedenko L, Rao M, Struchalin M, Kleber ME, Cavalieri M, Haun M, Cornelis MC, Ciullo M, Pirastu M, de Andrade M, McEvoy MA, Woodward M, Adam M, Cocca M, Nauck M, Imboden M, Waldenberger M, Pruijm M, Metzger M, Stumvoll M, Evans MK, Sale MM, Kähönen M, Boban M, Bochud M, Rheinberger M, Verweij N, Bouatia-Naji N, Martin NG, Hastie N, Probst-Hensch N, Soranzo N, Devuyst O, Raitakari O, Gottesman O, Franco OH, Polasek O, Gasparini P, Munroe PB, Ridker PM, Mitchell P, Muntner P, Meisinger C, Smit JH, Kovacs P, Wild PS, Froguel P, Rettig R, Mägi R, Biffar R, Schmidt R, Middelberg RP, Carroll RJ, Penninx BW, Scott RJ, Katz R, Sedaghat S, Wild SH, Kardia SL, Ulivi S, Hwang SJ, Enroth S, Kloiber S, Trompet S, Stengel B, Hancock SJ, Turner ST, Rosas SE, Stracke S, Harris TB, Zeller T, Zemunik T, Lehtimäki T, Illig T, Aspelund T, Nikopensius T, Esko T, Tanaka T, Gyllensten U, Völker U, Emilsson V, Vitart V, Aalto V, Gudnason V, Chouraki V, Chen WM, Igl W, März W, Koenig W, Lieb W, Loos RJ, Liu Y, Snieder H, Pramstaller PP, Parsa A, O’Connell JR, Susztak K, Hamet P, Tremblay J, de Boer IH, Böger CA, Goessling W, Chasman DI, Köttgen A, Kao WH, Fox CS; ICBP Consortium; AGEN Consortium; CARDIOGRAM; CHARGe-Heart Failure Group; ECHOGen Consortium: Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function. Nat Commun 7: 10023, 201626831199
13. Okada Y, Sim X, Go MJ, Wu J-Y, Gu D, Takeuchi F, Takahashi A, Maeda S, Tsunoda T, Chen P, Lim S-C, Wong T-Y, Liu J, Young TL, Aung T, Seielstad M, Teo Y-Y, Kim YJ, Lee J-Y, Han B-G, Kang D, Chen C-H, Tsai F-J, Chang L-C, Fann S-JC, Mei H, Rao DC, Hixson JE, Chen S, Katsuya T, Isono M, Ogihara T, Chambers JC, Zhang W, Kooner JS, Albrecht E, Yamamoto K, Kubo M, Nakamura Y, Kamatani N, Kato N, He J, Chen Y-T, Cho YS, Tai E-S, Tanaka T; KidneyGen Consortium; CKDGen Consortium; GUGC consortium: Meta-analysis identifies multiple loci associated with kidney function-related traits in east Asian populations. Nat Genet 44: 904–909, 201222797727
14. Mahajan A, Rodan AR, Le TH, Gaulton KJ, Haessler J, Stilp AM, Kamatani Y, Zhu G, Sofer T, Puri S, Schellinger JN, Chu P-L, Cechova S, van Zuydam N, 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; SUMMIT Consortium; BioBank Japan Project: Trans-ethnic fine mapping highlights kidney-function genes linked to salt sensitivity. Am J Hum Genet 99: 636–646, 201627588450
15. Ledo N, Ko Y-A, Park A-SD, Kang H-M, Han S-Y, Choi P, Susztak K: Functional genomic annotation of genetic risk loci highlights inflammation and epithelial biology networks in CKD. J Am Soc Nephrol 26: 692–714, 201525231882
16. Gorski M, Tin A, Garnaas M, McMahon GM, Chu AY, Tayo BO, Pattaro C, Teumer A, Chasman DI, Chalmers J, Hamet P, Tremblay J, Woodward M, Aspelund T, Eiriksdottir G, Gudnason V, Harris TB, Launer LJ, Smith AV, Mitchell BD, O’Connell JR, Shuldiner AR, Coresh J, Li M, Freudenberger P, Hofer E, Schmidt H, Schmidt R, Holliday EG, Mitchell P, Wang JJ, de Boer IH, Li G, Siscovick DS, Kutalik Z, Corre T, Vollenweider P, Waeber G, Gupta J, Kanetsky PA, Hwang SJ, Olden M, Yang Q, de Andrade M, Atkinson EJ, Kardia SL, Turner ST, Stafford JM, Ding J, Liu Y, Barlassina C, Cusi D, Salvi E, Staessen JA, Ridker PM, Grallert H, Meisinger C, Müller-Nurasyid M, Krämer BK, Kramer H, Rosas SE, Nolte IM, Penninx BW, Snieder H, Fabiola Del Greco M, Franke A, Nöthlings U, Lieb W, Bakker SJ, Gansevoort RT, van der Harst P, Dehghan A, Franco OH, Hofman A, Rivadeneira F, Sedaghat S, Uitterlinden AG, Coassin S, Haun M, Kollerits B, Kronenberg F, Paulweber B, Aumann N, Endlich K, Pietzner M, Völker U, Rettig R, Chouraki V, Helmer C, Lambert JC, Metzger M, Stengel B, Lehtimäki T, Lyytikäinen LP, Raitakari O, Johnson A, Parsa A, Bochud M, Heid IM, Goessling W, Köttgen A, Kao WH, Fox CS, Böger CA: Genome-wide association study of kidney function decline in individuals of European descent. Kidney Int 87: 1017–1029, 201525493955
17. Böger CA, Gorski M, Li M, Hoffmann MM, Huang C, Yang Q, Teumer A, Krane V, O’Seaghdha CM, Kutalik Z, Wichmann H-E, Haak T, Boes E, Coassin S, Coresh J, Kollerits B, Haun M, Paulweber B, Köttgen A, Li G, Shlipak MG, Powe N, Hwang S-J, Dehghan A, Rivadeneira F, Uitterlinden A, Hofman A, Beckmann JS, Krämer BK, Witteman J, Bochud M, Siscovick D, Rettig R, Kronenberg F, Wanner C, Thadhani RI, Heid IM, Fox CS, Kao WH; CKDGen Consortium: Association of eGFR-related loci identified by GWAS with incident CKD and ESRD. PLoS Genet 7: e1002292, 201121980298
18. Parsa A, Kanetsky PA, Xiao R, Gupta J, Mitra N, Limou S, Xie D, Xu H, Anderson AH, Ojo A, Kusek JW, Lora CM, Hamm LL, He J, Sandholm N, Jeff J, Raj DE, Böger CA, Bottinger E, Salimi S, Parekh RS, Adler SG, Langefeld CD, Bowden DW, Groop PH, Forsblom C, Freedman BI, Lipkowitz M, Fox CS, Winkler CA, Feldman HI; FIND Consortium; The Chronic Renal Insufficiency Cohort (CRIC) Study Investigators: Genome-wide association of CKD progression: The Chronic Renal Insufficiency Cohort study. J Am Soc Nephrol 28: 923–934, 2017
19. Reznichenko A, Böger CA, Snieder H, van den Born J, de Borst MH, Damman J, van Dijk MCRF, van Goor H, Hepkema BG, Hillebrands J-L, Leuvenink HGD, Niesing J, Bakker SJL, Seelen M, Navis G; REGaTTA (REnal GeneTics TrAnsplantation) Groningen group: UMOD as a susceptibility gene for end-stage renal disease. BMC Med Genet 13: 78, 201222947327
20. Padmanabhan S, Melander O, Johnson T, Di Blasio AM, Lee WK, Gentilini D, Hastie CE, Menni C, Monti MC, Delles C, Laing S, Corso B, Navis G, Kwakernaak AJ, van der Harst P, Bochud M, Maillard M, Burnier M, Hedner T, Kjeldsen S, Wahlstrand B, Sjögren M, Fava C, Montagnana M, Danese E, Torffvit O, Hedblad B, Snieder H, Connell JMC, Brown M, Samani NJ, Farrall M, Cesana G, Mancia G, Signorini S, Grassi G, Eyheramendy S, Wichmann HE, Laan M, Strachan DP, Sever P, Shields DC, Stanton A, Vollenweider P, Teumer A, Völzke H, Rettig R, Newton-Cheh C, Arora P, Zhang F, Soranzo N, Spector TD, Lucas G, Kathiresan S, Siscovick DS, Luan J, Loos RJF, Wareham NJ, Penninx BW, Nolte IM, McBride M, Miller WH, Nicklin SA, Baker AH, Graham D, McDonald RA, Pell JP, Sattar N, Welsh P, Munroe P, Caulfield MJ, Zanchetti A, Dominiczak AF; Global BPgen Consortium: Genome-wide association study of blood pressure extremes identifies variant near UMOD associated with hypertension. PLoS Genet 6: e1001177, 201021082022
21. Trudu M, Janas S, Lanzani C, Debaix H, Schaeffer C, Ikehata M, Citterio L, Demaretz S, Trevisani F, Ristagno G, Glaudemans B, Laghmani K, Dell’Antonio G, Loffing J, Rastaldi MP, Manunta P, Devuyst O, Rampoldi L; SKIPOGH team: Common noncoding UMOD gene variants induce salt-sensitive hypertension and kidney damage by increasing uromodulin expression. Nat Med 19: 1655–1660, 201324185693
22. Devuyst O, Olinger E, Rampoldi L: Uromodulin: From physiology to rare and complex kidney disorders. Nat Rev Nephrol 13: 525–544, 201728781372
23. Böger CA, Chen M-H, Tin A, Olden M, Köttgen A, de Boer IH, Fuchsberger C, O’Seaghdha CM, Pattaro C, Teumer A, Liu C-T, Glazer NL, Li M, O’Connell JR, Tanaka T, Peralta CA, Kutalik Z, Luan J, Zhao JH, Hwang S-J, Akylbekova E, Kramer H, van der Harst P, Smith AV, Lohman K, de Andrade M, Hayward C, Kollerits B, Tönjes A, Aspelund T, Ingelsson E, Eiriksdottir G, Launer LJ, Harris TB, Shuldiner AR, Mitchell BD, Arking DE, Franceschini N, Boerwinkle E, Egan J, Hernandez D, Reilly M, Townsend RR, Lumley T, Siscovick DS, Psaty BM, Kestenbaum B, Haritunians T, Bergmann S, Vollenweider P, Waeber G, Mooser V, Waterworth D, Johnson AD, Florez JC, Meigs JB, Lu X, Turner ST, Atkinson EJ, Leak TS, Aasarød K, Skorpen F, Syvänen A-C, Illig T, Baumert J, Koenig W, Krämer BK, Devuyst O, Mychaleckyj JC, Minelli C, Bakker SJL, Kedenko L, Paulweber B, Coassin S, Endlich K, Kroemer HK, Biffar R, Stracke S, Völzke H, Stumvoll M, Mägi R, Campbell H, Vitart V, Hastie ND, Gudnason V, Kardia SLR, Liu Y, Polasek O, Curhan G, Kronenberg F, Prokopenko I, Rudan I, Arnlöv J, Hallan S, Navis G, Parsa A, Ferrucci L, Coresh J, Shlipak MG, Bull SB, Paterson NJ, Wichmann HE, Wareham NJ, Loos RJ, Rotter JI, Pramstaller PP, Cupples LA, Beckmann JS, Yang Q, Heid IM, Rettig R, Dreisbach AW, Bochud M, Fox CS, Kao WH; CKDGen Consortium: CUBN is a gene locus for albuminuria. J Am Soc Nephrol 22: 555–570, 201121355061
24. Teumer A, Tin A, Sorice R, Gorski M, Yeo NC, Chu AY, Li M, Li Y, Mijatovic V, Ko Y-A, Taliun D, Luciani A, Chen M-H, Yang Q, Foster MC, Olden M, Hiraki LT, Tayo BO, Fuchsberger C, Dieffenbach AK, Shuldiner AR, Smith AV, Zappa AM, Lupo A, Kollerits B, Ponte B, Stengel B, Krämer BK, Paulweber B, Mitchell BD, Hayward C, Helmer C, Meisinger C, Gieger C, Shaffer CM, Müller C, Langenberg C, Ackermann D, Siscovick D, Boerwinkle E, Kronenberg F, Ehret GB, Homuth G, Waeber G, Navis G, Gambaro G, Malerba G, Eiriksdottir G, Li G, Wichmann HE, Grallert H, Wallaschofski H, Völzke H, Brenner H, Kramer H, Mateo Leach I, Rudan I, Hillege HL, Beckmann JS, Lambert JC, Luan J, Zhao JH, Chalmers J, Coresh J, Denny JC, Butterbach K, Launer LJ, Ferrucci L, Kedenko L, Haun M, Metzger M, Woodward M, Hoffman MJ, Nauck M, Waldenberger M, Pruijm M, Bochud M, Rheinberger M, Verweij N, Wareham NJ, Endlich N, Soranzo N, Polasek O, van der Harst P, Pramstaller PP, Vollenweider P, Wild PS, Gansevoort RT, Rettig R, Biffar R, Carroll RJ, Katz R, Loos RJ, Hwang SJ, Coassin S, Bergmann S, Rosas SE, Stracke S, Harris TB, Corre T, Zeller T, Illig T, Aspelund T, Tanaka T, Lendeckel U, Völker U, Gudnason V, Chouraki V, Koenig W, Kutalik Z, O’Connell JR, Parsa A, Heid IM, Paterson AD, de Boer IH, Devuyst O, Lazar J, Endlich K, Susztak K, Tremblay J, Hamet P, Jacob HJ, Böger CA, Fox CS, Pattaro C, Köttgen A; DCCT/EDIC: Genome-wide association studies identify genetic loci associated with albuminuria in diabetes. Diabetes 65: 803–817, 201626631737
25. Reznichenko A, Snieder H, van den Born J, de Borst MH, Damman J, van Dijk MCRF, van Goor H, Hepkema BG, Hillebrands J-L, Leuvenink HGD, Niesing J, Bakker SJL, Seelen M, Navis G; REGaTTA (REnal GeneTics TrAnsplantation) Groningen group: CUBN as a novel locus for end-stage renal disease: Insights from renal transplantation. PLoS One 7: e36512, 201222574174
26. Ma J, Guan M, Bowden DW, Ng MCY, Hicks PJ, Lea JP, Ma L, Gao C, Palmer ND, Freedman BI: Association analysis of the Cubilin (CUBN) and Megalin (LRP2) genes with ESRD in African Americans. Clin J Am Soc Nephrol 11: 1034–1043, 201627197912
27. Maeda S, Kobayashi MA, Araki S, Babazono T, Freedman BI, Bostrom MA, Cooke JN, Toyoda M, Umezono T, Tarnow L, Hansen T, Gaede P, Jorsal A, Ng DPK, Ikeda M, Yanagimoto T, Tsunoda T, Unoki H, Kawai K, Imanishi M, Suzuki D, Shin HD, Park KS, Kashiwagi A, Iwamoto Y, Kaku K, Kawamori R, Parving H-H, Bowden DW, Pedersen O, Nakamura Y: A single nucleotide polymorphism within the acetyl-coenzyme A carboxylase beta gene is associated with proteinuria in patients with type 2 diabetes. PLoS Genet 6: e1000842, 201020168990
28. Sandholm N, Van Zuydam N, Ahlqvist E, Juliusdottir T, Deshmukh HA, Rayner NW, Di Camillo B, Forsblom C, Fadista J, Ziemek D, Salem RM, Hiraki LT, Pezzolesi M, Trégouët D, Dahlström E, Valo E, Oskolkov N, Ladenvall C, Marcovecchio ML, Cooper J, Sambo F, Malovini A, Manfrini M, McKnight AJ, Lajer M, Harjutsalo V, Gordin D, Parkkonen M, Lyssenko V, McKeigue PM, Rich SS, Brosnan MJ, Fauman E, Bellazzi R, Rossing P, Hadjadj S, Krolewski A, Paterson AD, Hirschhorn JN, Maxwell AP, Cobelli C, Colhoun HM, Groop L, McCarthy MI, Groop PH; FinnDiane Study Group, Jaakko Tuomilehto; DCCT/EDIC Study Group, Jose C. Florez; GENIE Consortium, David Dunger; SUMMIT Consortium: The genetic landscape of renal complications in type 1 diabetes. J Am Soc Nephrol 28: 557–574, 201727647854
29. Pezzolesi MG, Poznik GD, Skupien J, Smiles AM, Mychaleckyj JC, Rich SS, Warram JH, Krolewski AS: An intergenic region on chromosome 13q33.3 is associated with the susceptibility to kidney disease in type 1 and 2 diabetes. Kidney Int 80: 105–111, 201121412220
30. Iyengar SK, Sedor JR, Freedman BI, Kao WH, Kretzler M, Keller BJ, Abboud HE, Adler SG, Best LG, Bowden DW, Burlock A, Chen YD, Cole SA, Comeau ME, Curtis JM, Divers J, Drechsler C, Duggirala R, Elston RC, Guo X, Huang H, Hoffmann MM, Howard BV, Ipp E, Kimmel PL, Klag MJ, Knowler WC, Kohn OF, Leak TS, Leehey DJ, Li M, Malhotra A, März W, Nair V, Nelson RG, Nicholas SB, O’Brien SJ, Pahl MV, Parekh RS, Pezzolesi MG, Rasooly RS, Rotimi CN, Rotter JI, Schelling JR, Seldin MF, Shah VO, Smiles AM, Smith MW, Taylor KD, Thameem F, Thornley-Brown DP, Truitt BJ, Wanner C, Weil EJ, Winkler CA, Zager PG, Igo RP Jr ., Hanson RL, Langefeld CD; Family Investigation of Nephropathy and Diabetes (FIND): Genome-wide association and trans-ethnic meta-analysis for advanced diabetic kidney disease: Family Investigation of Nephropathy and Diabetes (FIND). PLoS Genet 11: e1005352, 201526305897
31. Sandholm N, Salem RM, McKnight AJ, Brennan EP, Forsblom C, Isakova T, McKay GJ, Williams WW, Sadlier DM, Mäkinen V-P, Swan EJ, Palmer C, Boright AP, Ahlqvist E, Deshmukh HA, Keller BJ, Huang H, Ahola AJ, Fagerholm E, Gordin D, Harjutsalo V, He B, Heikkilä O, Hietala K, Kytö J, Lahermo P, Lehto M, Lithovius R, Österholm A-M, Parkkonen M, Pitkäniemi J, Rosengård-Bärlund M, Saraheimo M, Sarti C, Söderlund J, Soro-Paavonen A, Syreeni A, Thorn LM, Tikkanen H, Tolonen N, Tryggvason K, Tuomilehto J, Wadén J, Gill GV, Prior S, Guiducci C, Mirel DB, Taylor A, Hosseini SM, Parving HH, Rossing P, Tarnow L, Ladenvall C, Alhenc-Gelas F, Lefebvre P, Rigalleau V, Roussel R, Tregouet DA, Maestroni A, Maestroni S, Falhammar H, Gu T, Möllsten A, Cimponeriu D, Ioana M, Mota M, Mota E, Serafinceanu C, Stavarachi M, Hanson RL, Nelson RG, Kretzler M, Colhoun HM, Panduru NM, Gu HF, Brismar K, Zerbini G, Hadjadj S, Marre M, Groop L, Lajer M, Bull SB, Waggott D, Paterson AD, Savage DA, Bain SC, Martin F, Hirschhorn JN, Godson C, Florez JC, Groop PH, Maxwell AP; DCCT/EDIC Research Group: New susceptibility loci associated with kidney disease in type 1 diabetes. PLoS Genet 8: e1002921, 201223028342
32. Sandholm N, McKnight AJ, Salem RM, Brennan EP, Forsblom C, Harjutsalo V, Mäkinen V-P, McKay GJ, Sadlier DM, Williams WW, Martin F, Panduru NM, Tarnow L, Tuomilehto J, Tryggvason K, Zerbini G, Comeau ME, Langefeld CD, Godson C, Hirschhorn JN, Maxwell AP, Florez JC, Groop PH; FIND Consortium; FinnDiane Study Group and the GENIE Consortium: Chromosome 2q31.1 associates with ESRD in women with type 1 diabetes. J Am Soc Nephrol 24: 1537–1543, 201324029427
33. Pezzolesi MG, Poznik GD, Mychaleckyj JC, Paterson AD, Barati MT, Klein JB, Ng DPK, Placha G, Canani LH, Bochenski J, Waggott D, Merchant ML, Krolewski B, Mirea L, Wanic K, Katavetin P, Kure M, Wolkow P, Dunn JS, Smiles A, Walker WH, Boright AP, Bull SB, Doria A, Rogus JJ, Rich SS, Warram JH, Krolewski AS; DCCT/EDIC Research Group: Genome-wide association scan for diabetic nephropathy susceptibility genes in type 1 diabetes. Diabetes 58: 1403–1410, 200919252134
34. Germain M, Pezzolesi MG, Sandholm N, McKnight AJ, Susztak K, Lajer M, Forsblom C, Marre M, Parving H-H, Rossing P, Toppila I, Skupien J, Roussel R, Ko Y-A, Ledo N, Folkersen L, Civelek M, Maxwell AP, Tregouet D-A, Groop P-H, Tarnow L, Hadjadj S: SORBS1 gene, a new candidate for diabetic nephropathy: Results from a multi-stage genome-wide association study in patients with type 1 diabetes. Diabetologia 58: 543–548, 201525476525
35. Hanson RL, Craig DW, Millis MP, Yeatts KA, Kobes S, Pearson JV, Lee AM, Knowler WC, Nelson RG, Wolford JK: Identification of PVT1 as a candidate gene for end-stage renal disease in type 2 diabetes using a pooling-based genome-wide single nucleotide polymorphism association study. Diabetes 56: 975–983, 200717395743
36. McDonough CW, Palmer ND, Hicks PJ, Roh BH, An SS, Cooke JN, Hester JM, Wing MR, Bostrom MA, Rudock ME, Lewis JP, Talbert ME, Blevins RA, Lu L, Ng MC, Sale MM, Divers J, Langefeld CD, Freedman BI, Bowden DW: A genome-wide association study for diabetic nephropathy genes in African Americans. Kidney Int 79: 563–572, 201121150874
37. Maeda S, Osawa N, Hayashi T, Tsukada S, Kobayashi M, Kikkawa R: Genetic variations associated with diabetic nephropathy and type II diabetes in a Japanese population. Kidney Int Suppl 72: S43–S48, 200717653210
38. Thomas MC: Epigenetic mechanisms in diabetic kidney disease. Curr Diab Rep 16: 31, 201626908156
39. Chalmers J, Cooper ME: UKPDS and the legacy effect. N Engl J Med 359: 1618–1620, 200818843126
40. Writing Team for the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Research Group: Sustained effect of intensive treatment of type 1
diabetes mellitus on development and progression of diabetic nephropathy: The Epidemiology of Diabetes Interventions and Complications (EDIC) study. JAMA 290: 2159–2167, 200314570951
41. Stanescu HC, Arcos-Burgos M, Medlar A, Bockenhauer D, Kottgen A, Dragomirescu L, Voinescu C, Patel N, Pearce K, Hubank M, Stephens HA, Laundy V, Padmanabhan S, Zawadzka A, Hofstra JM, Coenen MJ, den Heijer M, Kiemeney LA, Bacq-Daian D, Stengel B, Powis SH, Brenchley P, Feehally J, Rees AJ, Debiec H, Wetzels JF, Ronco P, Mathieson PW, Kleta R: Risk HLA-DQA1 and PLA(2)R1 alleles in idiopathic membranous nephropathy. N Engl J Med 364: 616–626, 201121323541
42. Sekula P, Li Y, Stanescu HC, Wuttke M, Ekici AB, Bockenhauer D, Walz G, Powis SH, Kielstein JT, Brenchley P, Eckardt KU, Kronenberg F, Kleta R, Köttgen A; GCKD Investigators: Genetic risk variants for membranous nephropathy: Extension of and association with other
chronic kidney disease aetiologies. Nephrol Dial Transplant 32: 325–332, 201727333618
43. Gbadegesin RA, Adeyemo A, Webb NJA, Greenbaum LA, Abeyagunawardena A, Thalgahagoda S, Kale A, Gipson D, Srivastava T, Lin J-J, Chand D, Hunley TE, Brophy PD, Bagga A, Sinha A, Rheault MN, Ghali J, Nicholls K, Abraham E, Janjua HS, Omoloja A, Barletta G-M, Cai Y, Milford DD, O’Brien C, Awan A, Belostotsky V, Smoyer WE, Homstad A, Hall G, Wu G, Nagaraj S, Wigfall D, Foreman J, Winn MP; Mid-West Pediatric
Nephrology Consortium: HLA-DQA1 and PLCG2 are candidate risk loci for childhood-onset steroid-sensitive nephrotic syndrome. J Am Soc Nephrol 26: 1701–1710, 201525349203
44. Okamoto K, Tokunaga K, Doi K, Fujita T, Suzuki H, Katoh T, Watanabe T, Nishida N, Mabuchi A, Takahashi A, Kubo M, Maeda S, Nakamura Y, Noiri E: Common variation in GPC5 is associated with acquired nephrotic syndrome. Nat Genet 43: 459–463, 201121441931
45. Lv J, Hou W, Zhou X, Liu G, Zhou F, Zhao N, Hou P, Zhao M, Zhang H: Interaction between PLA2R1 and HLA-DQA1 variants associates with anti-PLA2R antibodies and membranous nephropathy. J Am Soc Nephrol 24: 1323–1329, 201323813219
46. Beck LH Jr ., Bonegio RGB, Lambeau G, Beck DM, Powell DW, Cummins TD, Klein JB, Salant DJ: M-type phospholipase A2 receptor as target antigen in idiopathic membranous nephropathy. N Engl J Med 361: 11–21, 200919571279
47. Tomas NM, Beck LH Jr ., Meyer-Schwesinger C, Seitz-Polski B, Ma H, Zahner G, Dolla G, Hoxha E, Helmchen U, Dabert-Gay A-S, Debayle D, Merchant M, Klein J, Salant DJ, Stahl RAK, Lambeau G: Thrombospondin type-1 domain-containing 7A in idiopathic membranous nephropathy. N Engl J Med 371: 2277–2287, 201425394321
48. Bullich G, Ballarín J, Oliver A, Ayasreh N, Silva I, Santín S, Díaz-Encarnación MM, Torra R, Ars E: HLA-DQA1 and PLA2R1 polymorphisms and risk of idiopathic membranous nephropathy. Clin J Am Soc Nephrol 9: 335–343, 201424262501
49. Kanigicherla D, Gummadova J, McKenzie EA, Roberts SA, Harris S, Nikam M, Poulton K, McWilliam L, Short CD, Venning M, Brenchley PE: Anti-PLA2R antibodies measured by ELISA predict long-term outcome in a prevalent population of patients with idiopathic membranous nephropathy. Kidney Int 83: 940–948, 201323364522
50. Ronco P, Debiec H: Membranous nephropathy: A fairy tale for immunopathologists, nephrologists and patients. Mol Immunol 68: 57–62, 201526597209
51. Barratt J, Feehally J: IgA nephropathy. J Am Soc Nephrol 16: 2088–2097, 200515930092
52. Feehally J, Farrall M, Boland A, Gale DP, Gut I, Heath S, Kumar A, Peden JF, Maxwell PH, Morris DL, Padmanabhan S, Vyse TJ, Zawadzka A, Rees AJ, Lathrop M, Ratcliffe PJ: HLA has strongest association with IgA nephropathy in genome-wide analysis. J Am Soc Nephrol 21: 1791–1797, 201020595679
53. Gharavi AG, Kiryluk K, Choi M, Li Y, Hou P, Xie J, Sanna-Cherchi S, Men CJ, Julian BA, Wyatt RJ, Novak J, He JC, Wang H, Lv J, Zhu L, Wang W, Wang Z, Yasuno K, Gunel M, Mane S, Umlauf S, Tikhonova I, Beerman I, Savoldi S, Magistroni R, Ghiggeri GM, Bodria M, Lugani F, Ravani P, Ponticelli C, Allegri L, Boscutti G, Frasca G, Amore A, Peruzzi L, Coppo R, Izzi C, Viola BF, Prati E, Salvadori M, Mignani R, Gesualdo L, Bertinetto F, Mesiano P, Amoroso A, Scolari F, Chen N, Zhang H, Lifton RP: Genome-wide association study identifies susceptibility loci for IgA nephropathy. Nat Genet 43: 321–327, 201121399633
54. Li M, Foo J-N, Wang J-Q, Low H-Q, Tang X-Q, Toh K-Y, Yin P-R, Khor C-C, Goh Y-F, Irwan ID, Xu R-C, Andiappan AK, Bei J-X, Rotzschke O, Chen M-H, Cheng C-Y, Sun L-D, Jiang G-R, Wong T-Y, Lin H-L, Aung T, Liao Y-H, Saw S-M, Ye K, Ebstein RP, Chen Q-K, Shi W, Chew S-H, Chen J, Zhang F-R, Li S-P, Xu G, Tai ES, Wang L, Chen N, Zhang X-J, Zeng Y-X, Zhang H, Liu Z-H, Yu X-Q, Liu J-J: Identification of new susceptibility loci for IgA nephropathy in Han Chinese. Nat Commun 6: 7270, 201526028593
55. Yu X-Q, Li M, Zhang H, Low H-Q, Wei X, Wang J-Q, Sun L-D, Sim K-S, Li Y, Foo J-N, Wang W, Li Z-J, Yin X-Y, Tang X-Q, Fan L, Chen J, Li R-S, Wan J-X, Liu Z-S, Lou T-Q, Zhu L, Huang X-J, Zhang X-J, Liu Z-H, Liu J-J: A genome-wide association study in Han Chinese identifies multiple susceptibility loci for IgA nephropathy. Nat Genet 44: 178–182, 201122197929
56. Kiryluk K, Li Y, Sanna-Cherchi S, Rohanizadegan M, Suzuki H, Eitner F, Snyder HJ, Choi M, Hou P, Scolari F, Izzi C, Gigante M, Gesualdo L, Savoldi S, Amoroso A, Cusi D, Zamboli P, Julian BA, Novak J, Wyatt RJ, Mucha K, Perola M, Kristiansson K, Viktorin A, Magnusson PK, Thorleifsson G, Thorsteinsdottir U, Stefansson K, Boland A, Metzger M, Thibaudin L, Wanner C, Jager KJ, Goto S, Maixnerova D, Karnib HH, Nagy J, Panzer U, Xie J, Chen N, Tesar V, Narita I, Berthoux F, Floege J, Stengel B, Zhang H, Lifton RP, Gharavi AG: Geographic differences in genetic susceptibility to IgA nephropathy: GWAS replication study and geospatial risk analysis. PLoS Genet 8: e1002765, 201222737082
57. Kiryluk K, Li Y, Scolari F, Sanna-Cherchi S, Choi M, Verbitsky M, Fasel D, Lata S, Prakash S, Shapiro S, Fischman C, Snyder HJ, Appel G, Izzi C, Viola BF, Dallera N, Del Vecchio L, Barlassina C, Salvi E, Bertinetto FE, Amoroso A, Savoldi S, Rocchietti M, Amore A, Peruzzi L, Coppo R, Salvadori M, Ravani P, Magistroni R, Ghiggeri GM, Caridi G, Bodria M, Lugani F, Allegri L, Delsante M, Maiorana M, Magnano A, Frasca G, Boer E, Boscutti G, Ponticelli C, Mignani R, Marcantoni C, Di Landro D, Santoro D, Pani A, Polci R, Feriozzi S, Chicca S, Galliani M, Gigante M, Gesualdo L, Zamboli P, Battaglia GG, Garozzo M, Maixnerová D, Tesar V, Eitner F, Rauen T, Floege J, Kovacs T, Nagy J, Mucha K, Pączek L, Zaniew M, Mizerska-Wasiak M, Roszkowska-Blaim M, Pawlaczyk K, Gale D, Barratt J, Thibaudin L, Berthoux F, Canaud G, Boland A, Metzger M, Panzer U, Suzuki H, Goto S, Narita I, Caliskan Y, Xie J, Hou P, Chen N, Zhang H, Wyatt RJ, Novak J, Julian BA, Feehally J, Stengel B, Cusi D, Lifton RP, Gharavi AG: Discovery of new risk loci for IgA nephropathy implicates genes involved in immunity against intestinal pathogens. Nat Genet 46: 1187–1196, 201425305756
58. Zhai Y-L, Meng S-J, Zhu L, Shi S-F, Wang S-X, Liu L-J, Lv J-C, Yu F, Zhao M-H, Zhang H: Rare variants in the complement factor H-related protein 5 gene contribute to genetic susceptibility to IgA nephropathy. J Am Soc Nephrol 27: 2894–2905, 2016
59. Cox SN, Pesce F, El-Sayed Moustafa JS, Sallustio F, Serino G, Kkoufou C, Giampetruzzi A, Ancona N, Falchi M, Schena FP; The European IgAN Consortium: Multiple rare genetic variants co-segregating with familial IgA nephropathy all act within a single immune-related network. J Intern Med 281: 189–205, 2017
60. Zhou X-J, Nath SK, Qi Y-Y, Sun C, Hou P, Zhang Y-M, Lv J-C, Shi S-F, Liu L-J, Chen R, Yang W, He KZ, Li Y, Zhang H: Novel identified associations of RGS1 and RASGRP1 variants in IgA Nephropathy. Sci Rep 6: 35781, 201627804980
61. Zhou XJ, Nath SK, Qi YY, Cheng FJ, Yang HZ, Zhang Y, Yang W, Ma JY, Zhao MH, Shen N, Zhang H: Brief Report: Identification of MTMR3 as a novel susceptibility gene for lupus
nephritis in northern Han Chinese by shared-gene analysis with IgA nephropathy. Arthritis Rheumatol 66: 2842–2848, 201424943867
62. Xue JL, Eggers PW, Agodoa LY, Foley RN, Collins AJ: Longitudinal study of racial and ethnic differences in developing end-stage renal disease among aged medicare beneficiaries. J Am Soc Nephrol 18: 1299–1306, 200717329578
63. Kopp JB, Smith MW, Nelson GW, Johnson RC, Freedman BI, Bowden DW, Oleksyk T, McKenzie LM, Kajiyama H, Ahuja TS, Berns JS, Briggs W, Cho ME, Dart RA, Kimmel PL, Korbet SM, Michel DM, Mokrzycki MH, Schelling JR, Simon E, Trachtman H, Vlahov D, Winkler CA: MYH9 is a major-effect risk gene for focal segmental glomerulosclerosis. Nat Genet 40: 1175–1184, 200818794856
64. Kao WHL, Klag MJ, Meoni LA, Reich D, Berthier-Schaad Y, Li M, Coresh J, Patterson N, Tandon A, Powe NR, Fink NE, Sadler JH, Weir MR, Abboud HE, Adler SG, Divers J, Iyengar SK, Freedman BI, Kimmel PL, Knowler WC, Kohn OF, Kramp K, Leehey DJ, Nicholas SB, Pahl MV, Schelling JR, Sedor JR, Thornley-Brown D, Winkler CA, Smith MW, Parekh RS; Family Investigation of Nephropathy and Diabetes Research Group: MYH9 is associated with nondiabetic end-stage renal disease in African Americans. Nat Genet 40: 1185–1192, 200818794854
65. Genovese G, Friedman DJ, Ross MD, Lecordier L, Uzureau P, Freedman BI, Bowden DW, Langefeld CD, Oleksyk TK, Uscinski Knob AL, Bernhardy AJ, Hicks PJ, Nelson GW, Vanhollebeke B, Winkler CA, Kopp JB, Pays E, Pollak MR: Association of trypanolytic ApoL1 variants with kidney disease in African Americans. Science 329: 841–845, 201020647424
66. Limou S, Nelson GW, Kopp JB, Winkler CA: APOL1 kidney risk alleles: Population genetics and disease associations. Adv Chronic Kidney Dis 21: 426–433, 201425168832
67. Limou S, Dummer PD, Nelson GW, Kopp JB, Winkler CA: APOL1 toxin, innate immunity, and kidney injury. Kidney Int 88: 28–34, 201525853332
68. Larsen CP, Beggs ML, Saeed M, Walker PD: Apolipoprotein L1 risk variants associate with systemic lupus erythematosus-associated collapsing glomerulopathy. J Am Soc Nephrol 24: 722–725, 201323520206
69. Lipkowitz MS, Freedman BI, Langefeld CD, Comeau ME, Bowden DW, Kao WHL, Astor BC, Bottinger EP, Iyengar SK, Klotman PE, Freedman RG, Zhang W, Parekh RS, Choi MJ, Nelson GW, Winkler CA, Kopp JB; SK Investigators: Apolipoprotein L1 gene variants associate with hypertension-attributed nephropathy and the rate of kidney function decline in African Americans. Kidney Int 83: 114–120, 201322832513
70. Parsa A, Kao WHL, Xie D, Astor BC, Li M, Hsu CY, Feldman HI, Parekh RS, Kusek JW, Greene TH, Fink JC, Anderson AH, Choi MJ, Wright JT Jr ., Lash JP, Freedman BI, Ojo A, Winkler CA, Raj DS, Kopp JB, He J, Jensvold NG, Tao K, Lipkowitz MS, Appel LJ; AASK Study Investigators; CRIC Study Investigators: APOL1 risk variants, race, and progression of
chronic kidney disease. N Engl J Med 369: 2183–2196, 201324206458
71. Freedman BI, Pastan SO, Israni AK, Schladt D, Julian BA, Gautreaux MD, Hauptfeld V, Bray RA, Gebel HM, Kirk AD, Gaston RS, Rogers J, Farney AC, Orlando G, Stratta RJ, Mohan S, Ma L, Langefeld CD, Bowden DW, Hicks PJ, Palmer ND, Palanisamy A, Reeves-Daniel AM, Brown WM, Divers J: APOL1 genotype and kidney transplantation outcomes from deceased African American donors. Transplantation 100: 194–202, 201626566060
72. Reeves-Daniel AM, DePalma JA, Bleyer AJ, Rocco MV, Murea M, Adams PL, Langefeld CD, Bowden DW, Hicks PJ, Stratta RJ, Lin J-J, Kiger DF, Gautreaux MD, Divers J, Freedman BI: The APOL1 gene and allograft survival after kidney transplantation. Am J Transplant 11: 1025–1030, 201121486385
73. Lee BT, Kumar V, Williams TA, Abdi R, Bernhardy A, Dyer C, Conte S, Genovese G, Ross MD, Friedman DJ, Gaston R, Milford E, Pollak MR, Chandraker A: The APOL1 genotype of African American kidney transplant recipients does not impact 5-year allograft survival. Am J Transplant 12: 1924–1928, 201222487534
74. Naik RP, Derebail VK, Grams ME, Franceschini N, Auer PL, Peloso GM, Young BA, Lettre G, Peralta CA, Katz R, Hyacinth HI, Quarells RC, Grove ML, Bick AG, Fontanillas P, Rich SS, Smith JD, Boerwinkle E, Rosamond WD, Ito K, Lanzkron S, Coresh J, Correa A, Sarto GE, Key NS, Jacobs DR, Kathiresan S, Bibbins-Domingo K, Kshirsagar AV, Wilson JG, Reiner AP: Association of sickle cell trait with
chronic kidney disease and albuminuria in African Americans. JAMA 312: 2115–2125, 201425393378
75. Naik RP, Irvin MR, Judd S, Gutiérrez OM, Zakai NA, Derebail VK, Peralta C, Lewis MR, Zhi D, Arnett D, McClellan W, Wilson JG, Reiner AP, Kopp JB, Winkler CA, Cushman M: Sickle cell rrait and the risk of ESRD in blacks. J Am Soc Nephrol 28: 2180–2187, 201728280138
76. Eckardt K-U, Alper SL, Antignac C, Bleyer AJ, Chauveau D, Dahan K, Deltas C, Hosking A, Kmoch S, Rampoldi L, Wiesener M, Wolf MT, Devuyst O; Kidney Disease: Improving Global Outcomes: Autosomal dominant tubulointerstitial kidney disease: Diagnosis, classification, and management--A KDIGO consensus report. Kidney Int 88: 676–683, 201525738250
77. Ovunc B, Otto EA, Vega-Warner V, Saisawat P, Ashraf S, Ramaswami G, Fathy HM, Schoeb D, Chernin G, Lyons RH, Yilmaz E, Hildebrandt F: Exome sequencing reveals cubilin mutation as a single-gene cause of proteinuria. J Am Soc Nephrol 22: 1815–1820, 201121903995
78. Cisek K, Krochmal M, Klein J, Mischak H: The application of multi-omics and
systems biology to identify therapeutic targets in
chronic kidney disease. Nephrol Dial Transplant 31: 2003–2011, 201626487673
79. Limou S, Parsa A: Diving into the abyss of undiscovered kidney function-related factors. Kidney Int 90: 724–726, 201627633863
80. Mariani LH, Pendergraft WF 3rd, Kretzler M: Defining glomerular disease in mechanistic terms: Implementing an integrative biology approach in
nephrology. Clin J Am Soc Nephrol 11: 2054–2060, 201627630182
81. Brat DJ, Verhaak RG, Aldape KD, Yung WK, Salama SR, Cooper LA, Rheinbay E, Miller CR, Vitucci M, Morozova O, Robertson AG, Noushmehr H, Laird PW, Cherniack AD, Akbani R, Huse JT, Ciriello G, Poisson LM, Barnholtz-Sloan JS, Berger MS, Brennan C, Colen RR, Colman H, Flanders AE, Giannini C, Grifford M, Iavarone A, Jain R, Joseph I, Kim J, Kasaian K, Mikkelsen T, Murray BA, O'Neill BP, Pachter L, Parsons DW, Sougnez C, Sulman EP, Vandenberg SR, Van Meir EG, von Deimling A, Zhang H, Crain D, Lau K, Mallery D, Morris S, Paulauskis J, Penny R, Shelton T, Sherman M, Yena P, Black A, Bowen J, Dicostanzo K, Gastier-Foster J, Leraas KM, Lichtenberg TM, Pierson CR, Ramirez NC, Taylor C, Weaver S, Wise L, Zmuda E, Davidsen T, Demchok JA, Eley G, Ferguson ML, Hutter CM, Mills Shaw KR, Ozenberger BA, Sheth M, Sofia HJ, Tarnuzzer R, Wang Z, Yang L, Zenklusen JC, Ayala B, Baboud J, Chudamani S, Jensen MA, Liu J, Pihl T, Raman R, Wan Y, Wu Y, Ally A, Auman JT, Balasundaram M, Balu S, Baylin SB, Beroukhim R, Bootwalla MS, Bowlby R, Bristow CA, Brooks D, Butterfield Y, Carlsen R, Carter S, Chin L, Chu A, Chuah E, Cibulskis K, Clarke A, Coetzee SG, Dhalla N, Fennell T, Fisher S, Gabriel S, Getz G, Gibbs R, Guin R, Hadjipanayis A, Hayes DN, Hinoue T, Hoadley K, Holt RA, Hoyle AP, Jefferys SR, Jones S, Jones CD, Kucherlapati R, Lai PH, Lander E, Lee S, Lichtenstein L, Ma Y, Maglinte DT, Mahadeshwar HS, Marra MA, Mayo M, Meng S, Meyerson ML, Mieczkowski PA, Moore RA, Mose LE, Mungall AJ, Pantazi A, Parfenov M, Park PJ, Parker JS, Perou CM, Protopopov A, Ren X, Roach J, Sabedot TS, Schein J, Schumacher SE, Seidman JG, Seth S, Shen H, Simons JV, Sipahimalani P, Soloway MG, Song X, Sun H, Tabak B, Tam A, Tan D, Tang J, Thiessen N, Triche T Jr ., Van Den Berg DJ, Veluvolu U, Waring S, Weisenberger DJ, Wilkerson MD, Wong T, Wu J, Xi L, Xu AW, Yang L, Zack TI, Zhang J, Aksoy BA, Arachchi H, Benz C, Bernard B, Carlin D, Cho J, DiCara D, Frazer S, Fuller GN, Gao J, Gehlenborg N, Haussler D, Heiman DI, Iype L, Jacobsen A, Ju Z, Katzman S, Kim H, Knijnenburg T, Kreisberg RB, Lawrence MS, Lee W, Leinonen K, Lin P, Ling S, Liu W, Liu Y, Liu Y, Lu Y, Mills G, Ng S, Noble MS, Paull E, Rao A, Reynolds S, Saksena G, Sanborn Z, Sander C, Schultz N, Senbabaoglu Y, Shen R, Shmulevich I, Sinha R, Stuart J, Sumer SO, Sun Y, Tasman N, Taylor BS, Voet D, Weinhold N, Weinstein JN, Yang D, Yoshihara K, Zheng S, Zhang W, Zou L, Abel T, Sadeghi S, Cohen ML, Eschbacher J, Hattab EM, Raghunathan A, Schniederjan MJ, Aziz D, Barnett G, Barrett W, Bigner DD, Boice L, Brewer C, Calatozzolo C, Campos B, Carlotti CG Jr ., Chan TA, Cuppini L, Curley E, Cuzzubbo S, Devine K, DiMeco F, Duell R, Elder JB, Fehrenbach A, Finocchiaro G, Friedman W, Fulop J, Gardner J, Hermes B, Herold-Mende C, Jungk C, Kendler A, Lehman NL, Lipp E, Liu O, Mandt R, McGraw M, Mclendon R, McPherson C, Neder L, Nguyen P, Noss A, Nunziata R, Ostrom QT, Palmer C, Perin A, Pollo B, Potapov A, Potapova O, Rathmell WK, Rotin D, Scarpace L, Schilero C, Senecal K, Shimmel K, Shurkhay V, Sifri S, Singh R, Sloan AE, Smolenski K, Staugaitis SM, Steele R, Thorne L, Tirapelli DP, Unterberg A, Vallurupalli M, Wang Y, Warnick R, Williams F, Wolinsky Y, Bell S, Rosenberg M, Stewart C, Huang F, Grimsby JL, Radenbaugh AJ, Zhang J; Cancer Genome Atlas Research Network: Comprehensive, integrative genomic analysis of diffuse lower-grade gliomas. N Engl J Med 372: 2481–2498, 2015
82. Mariani M, He S, McHugh M, Andreoli M, Pandya D, Sieber S, Wu Z, Fiedler P, Shahabi S, Ferlini C: Integrated multidimensional analysis is required for accurate prognostic biomarkers in colorectal cancer. PLoS One 9: e101065, 201424988459
83. Wolfe D, Dudek S, Ritchie MD, Pendergrass SA: Visualizing genomic information across chromosomes with PhenoGram. BioData Min 6: 18, 201324131735
