Skip to main content

Main menu

  • Home
  • Content
    • Published Ahead of Print
    • Current Issue
    • Podcasts
    • Subject Collections
    • Archives
    • Kidney Week Abstracts
    • Saved Searches
  • Authors
    • Submit a Manuscript
    • Author Resources
  • Trainees
    • Peer Review Program
    • Prize Competition
  • About CJASN
    • About CJASN
    • Editorial Team
    • CJASN Impact
    • CJASN Recognitions
  • More
    • Alerts
    • Advertising
    • Feedback
    • Reprint Information
    • Subscriptions
  • ASN Kidney News
  • Other
    • ASN Publications
    • JASN
    • Kidney360
    • Kidney News Online
    • American Society of Nephrology

User menu

  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
American Society of Nephrology
  • Other
    • ASN Publications
    • JASN
    • Kidney360
    • Kidney News Online
    • American Society of Nephrology
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Advertisement
American Society of Nephrology

Advanced Search

  • Home
  • Content
    • Published Ahead of Print
    • Current Issue
    • Podcasts
    • Subject Collections
    • Archives
    • Kidney Week Abstracts
    • Saved Searches
  • Authors
    • Submit a Manuscript
    • Author Resources
  • Trainees
    • Peer Review Program
    • Prize Competition
  • About CJASN
    • About CJASN
    • Editorial Team
    • CJASN Impact
    • CJASN Recognitions
  • More
    • Alerts
    • Advertising
    • Feedback
    • Reprint Information
    • Subscriptions
  • ASN Kidney News
  • Visit ASN on Facebook
  • Follow CJASN on Twitter
  • CJASN RSS
  • Community Forum
Original ArticlesGenetics
You have accessRestricted Access

Association Analysis of the Cubilin (CUBN) and Megalin (LRP2) Genes with ESRD in African Americans

Jun Ma, Meijian Guan, Donald W. Bowden, Maggie C.Y. Ng, Pamela J. Hicks, Janice P. Lea, Lijun Ma, Chuan Gao, Nicholette D. Palmer and Barry I. Freedman
CJASN June 2016, 11 (6) 1034-1043; DOI: https://doi.org/10.2215/CJN.12971215
Jun Ma
*Department of Internal Medicine, Section on Nephrology and
†Department of Nephrology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China; and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Meijian Guan
‡Department of Biochemistry and Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Donald W. Bowden
‡Department of Biochemistry and Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Maggie C.Y. Ng
‡Department of Biochemistry and Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Pamela J. Hicks
‡Department of Biochemistry and Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Janice P. Lea
§Division of Renal Medicine, Department of Medicine, Emory School of Medicine, Atlanta, Georgia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lijun Ma
*Department of Internal Medicine, Section on Nephrology and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Chuan Gao
‡Department of Biochemistry and Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nicholette D. Palmer
‡Department of Biochemistry and Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Barry I. Freedman
*Department of Internal Medicine, Section on Nephrology and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site

Abstract

Background and objectives Genetic variation in the cubilin (CUBN) gene is associated with albuminuria and CKD. Common and rare coding variants in CUBN and the gene encoding its transport partner megalin (LRP2) were assessed for association with ESRD in blacks.

Design, setting, participants, & measurements Sixty-six CUBN and LRP2 single–nucleotide polymorphisms (SNPs) were selected and analyzed in this multistage study. Exome sequencing data from 529 blacks with type 2 diabetes (T2D) –associated ESRD and 535 controls lacking T2D or nephropathy (the Type 2 Diabetes Genes [T2D-GENES] Consortium) were first evaluated, focusing on coding variants in CUBN and LRP2; 15 potentially associated SNPs identified from the T2D-GENES Consortium as well as 51 other selected SNPs were then assessed in an independent T2D-ESRD sample set of blacks (the Affymetrix Axiom Biobank Genotyping Array [AXIOM]; 2041 patients with T2D-ESRD, 627 patients with T2D without nephropathy, and 1140 nondiabetic, non–nephropathy controls). A meta-analysis combining the T2D-GENES Consortium and the AXIOM data was performed for 18 overlapping SNPs. Additionally, all 66 SNPs were genotyped in the Wake Forest School of Medicine samples of blacks with nondiabetic ESRD (885 patients with nondiabetic ESRD and 721 controls). Association testing with ESRD was performed in models including age, sex, African ancestry proportion, and apolipoprotein L1 gene renal-risk variants.

Results CUBN SNP rs1801239 (I2984V), previously associated with albuminuria, was significantly associated with T2D-ESRD in blacks (the T2D-GENES Consortium and the AXIOM meta-analysis, P=0.03; odds ratio, 1.31; 95% confidence interval, 1.03 to 1.67; minor allele frequency =0.028). A novel LRP2 missense variant, rs17848169 (N2632D), was also significantly protective from T2D-ESRD (the T2D-GENES Consortium and the AXIOM, P<0.002; odds ratio, 0.47; 95% confidence interval, 0.29 to 0.75; meta–analysis minor allele frequency =0.007). Neither SNP was associated with T2D when contrasting patients with T2D with controls lacking diabetes. CUBN and LRP2 SNPs were not associated with nondiabetic etiologies of ESRD.

Conclusions Evidence for genetic association exists between a cubilin and a rare megalin variant with diabetes-associated ESRD in populations with recent African ancestry.

  • chronic kidney disease
  • diabetic nephropathy
  • end stage kidney disease
  • African Americans
  • albuminuria
  • Diabetes Mellitus, Type 2
  • Genotype
  • Humans
  • Polymorphism, Single Nucleotide
  • Renal Insufficiency, Chronic

Introduction

Increasing evidence supports that inherited factors make major contributions to ESRD susceptibility (1,2). This is particularly true in blacks who have high rates of ESRD with marked familial aggregation of nephropathy (3). The incidence rate of ESRD in blacks is 3.3-fold higher than that in whites (4). Apolipoprotein L1 (APOL1) gene renal-risk alleles associate with approximately 70% of nondiabetic ESRD in blacks (5–7); however, they do not explain the excess risk for type 2 diabetes (T2D) –associated ESRD (8). Additional genetic loci likely contribute to this risk (9–11).

The cubilin (CUBN) gene was identified as a novel locus for albuminuria from a genome–wide association study–based meta–analysis (12). The missense single–nucleotide polymorphism (SNP) rs1801239 (I2984V) in CUBN was associated with elevated urine albumin-to-creatinine ratio in individuals of European and recent African ancestry. Another intronic CUBN variant, rs10795433, in moderate linkage disequilibrium with rs1801239 (r2=0.54), was associated with the urine albumin-to-creatinine ratio in patients with diabetes (13). Cubilin forms a functional receptor complex with megalin (encoded by the megalin [LRP2] gene) in the proximal tubule to reabsorb filtered urinary albumin (14,15). Megalin is important in facilitating the internalization of the cubilin-albumin complex (16).

Because albuminuria is an important risk factor for progression of kidney disease, we hypothesized that variation in CUBN and LRP2 could contribute to nephropathy susceptibility. A recent analysis in European kidney transplant donors and recipients showed that CUBN SNP rs7918972 was significantly associated with risk for ESRD (17). However, the role of CUBN genetic variation in ESRD susceptibility among blacks remains unknown. We analyzed next generation exome sequencing (NGES) data to survey the CUBN and LRP2 genes to determine whether variation in these genes affected risk for ESRD in blacks beyond reducing renal proximal tubule reabsorption of albumin.

Materials and Methods

Study Participants

This study was approved by the Institutional Review Board at the Wake Forest School of Medicine; all participants provided written informed consent. Detailed recruitment and sample collection procedures have been reported (11). T2D was diagnosed in those whose illness developed after 25 years of age and who lacked diabetic ketoacidosis or receipt of insulin alone since diagnosis. ESRD was attributed to T2D with ≥5 years diabetes duration before the start of RRT in the absence of other causes of nephropathy. Patients with nondiabetic ESRD had nephropathy caused by chronic glomerulosclerosis, FSGS, or HIV-associated nephropathy, attributed to hypertension, or because of unknown causes. Those with ESRD caused by urologic or surgical causes, polycystic kidney disease, IgA nephropathy, or membranous or membranoproliferative GN were excluded. Blacks with T2D lacking nephropathy were receiving insulin and/or oral hypoglycemic agents, had a hemoglobin A1C ≥6.5% or a fasting plasma glucose >126 mg/dl, and had a serum creatinine concentration ≤1.5 mg/dl (men) or ≤1.3 mg/dl (women). Unrelated blacks without diabetes or kidney disease (eGFR≥60 ml/min per 1.73 m2 and urine albumin-to-creatinine ratio <30 mg/g) were recruited as controls (described as non-T2D, non-nephropathy, or healthy controls). Genomic DNA was extracted with the PureGene System (Gentra Systems, Minneapolis, MN) according to the manufacturer’s instructions. Ethnicity was self-reported and confirmed using African ancestry proportions calculated with 70 ancestry informative markers (18,19).

SNP Selection, Genotyping, and Quality Control

In total, 66 SNPs in CUBN (n=50) and LRP2 (n=16) were selected to evaluate potential ESRD associations in blacks. Figure 1 displays the study design, and Supplemental Table 1 displays the SNPs and their sources of selection. Fifteen SNPs were selected from samples provided by the Wake Forest School of Medicine to the Type 2 Diabetes Genes [T2D-GENES] Consortium Exome Sequencing Project (https://t2d-genessph.umich.edu/), which included 529 blacks with T2D-ESRD and 535 nondiabetic, non–nephropathy controls. The T2D-GENES Consortium genotyping and quality control methods have been reported (10). Among the total of 407 CUBN SNPs and 581 LRP2 SNPs identified in the T2D-GENES Consortium, we selected four CUBN and 11 LRP2 SNPs for analysis on the basis of association results with T2D-ESRD with P values ≤0.10. Eleven additional coding variants were selected from the Exome Sequencing Project data based on minor allele frequencies (MAFs) in blacks >0.01 and probably damaging effects using Polyphen2 prediction; six were CUBN SNPs, and five were in LRP2. From the literature, two CUBN SNPs previously associated with kidney disease phenotypes, rs1801239 and rs7918972 (hereafter referred to as index SNPs), were included (12,17). In addition, 38 haplotype-tagging SNPs with MAF>5% across the HapMap region of linkage disequilibrium (chromosome 10: 16897609––17012313) and inclusive of the index variants were selected. Because the index SNPs were primarily identified in European populations, the borders of their linkage disequilibrium blocks in Utah residents with Northern and Western European ancestry were determined in Haploview, and tagging SNPs were selected between these regions in Yoruba in Ibadan, Nigeria to tag differential linkage disequilibrium block structures in populations with recent African ancestry.

Figure 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1.

Cubilin (CUBN) gene and megalin gene single–nucleotide polymorphism (SNP) selection and genetic association analysis workflow. AXIOM, Affymetrix Axiom Biobank Genotyping Array; ESKD, ESRD; ESP, Exome Sequencing Project; T2D-GENES, Type 2 Diabetes Genes Consortium.

Association analyses were performed in 2041 independent blacks with T2D-ESRD and 1807 independent non–nephropathy controls (667 controls with T2D lacking nephropathy and 1140 controls without T2D) who had been genotyped on the Affymetrix Axiom Biobank Genotyping Array (AXIOM) samples (Affymetrix, Santa Clara, CA; none of these individuals overlapped with those in the T2D-GENES Consortium). Detailed SNP information, genotyping methods, and the AXIOM quality control data are reported in Supplemental Material. Of the initial 66 SNPs selected in the discovery analysis, 35 were present in the AXIOM samples: 27 in CUBN and eight in LRP2. Of these, 10 CUBN SNPs and eight LRP2 SNPs were present in both the T2D-GENES Consortium and the AXIOM data; these 18 SNPs were included in a meta-analysis from both datasets (Figure 1).

To assess associations in nondiabetic ESRD, 885 blacks with nondiabetic ESRD and 721 nondiabetic, non–nephropathy controls were genotyped for the 66 CUBN and LRP2 SNPs. Genotyping was performed using the Sequenom MassArray System (Sequenom, San Diego, CA). PCR primers were designed using MassARRAY Assay Design 3.1 (Sequenom), and genotypes were analyzed using MassARRAY Typer (Sequenom). Of all 66 SNPs, 60 were successfully genotyped, had call rates >95%, and met quality control standards on the basis of 100% concordance with blind duplicates and Hardy–Weinberg Equilibrium P value =0.001. Two APOL1 G1 nephropathy risk SNPs (rs73885319 and rs60910145) and an insertion/deletion for the APOL1 G2 risk allele (rs71785313) were genotyped in all samples on the same platform.

Statistical Analyses

For data from the AXIOM custom array, a linear mixed model–based method was used to correct for population structure and cryptic relatedness (20). This resulted in an inflation factor <1.002 computed from 315,610 high–quality autosomal SNPs with an MAF>0.05. Because all samples in the T2D-GENES Consortium and the nondiabetic ESRD datasets from the Wake Forest School of Medicine were from unrelated individuals, logistic regression was performed using PLINK for the NGES and directly genotyped data.

Single SNP association tests in all sets were computed using an additive genetic model. The fully adjusted model for association with ESRD included participant age, sex, African ancestry proportion, and recessive APOL1 G1/G2 risk alleles. The adjusted model for association with T2D per se in the AXIOM samples (T2D only versus non–T2D, non–nephropathy controls) included participant age, sex, and African ancestry proportion (not APOL1). A corrected P value (Pcorr) was calculated for SNP associations by adjusting for the number of SNPs tested in each study. Pcorr values <0.05 were considered statistically significant.

Meta-Analyses

Summary statistics from 18 overlapping SNPs in the T2D-GENES Consortium and the AXIOM samples (10 CUBN and eight LRP2) were combined using the fixed effects meta–analysis method implemented in METAL (21). Of these, the CUBN index SNP rs1801239 was included, but the second CUBN index SNP rs7918972 was not present in the T2D-GENES Consortium and could not be meta-analyzed.

Results

Demographic data from patients and controls in the T2D-GENES Consortium, the AXIOM data, and the Wake Forest School of Medicine nondiabetic ESRD samples are summarized in Table 1. Participant characteristics were generally similar among patients with T2D-ESRD; however, age at onset of T2D was younger in patients with T2D-ESRD than in individuals with T2D lacking nephropathy. Patients with T2D-ESRD had older ages at enrollment compared with individuals with T2D lacking nephropathy and nondiabetic, non–nephropathy controls. Mean ages at enrollment and body mass index were lower in patients with nondiabetic ESRD than in those in the T2D-ESRD group, whereas the duration of ESRD was longer.

View this table:
  • View inline
  • View popup
Table 1.

Demographic and clinical characteristics of study samples

The initial evaluation of 15 SNPs in the T2D-GENES Consortium in 529 blacks with T2D-ESRD versus 535 nondiabetic, non–nephropathy controls identified six variants (three in CUBN and three in LRP2) nominally associated with T2D-ESRD (P<0.05 in additive models adjusted for age, sex, African ancestry proportion, and APOL1). Among these, common synonymous CUBN variant rs1873469 showed the strongest association: MAF=26% in patients with T2D-ESRD and MAF=33% in controls (P=0.003; odds ratio [OR], 0.72; 95% confidence interval [95% CI], 0.58 to 0.90). In addition, two low–frequency protective missense LRP2 variants were identified: rs17848169 (N2632D; P=0.01; OR, 0.19; 95% CI, 0.05 to 0.68) and rs34291900 (G669D; P=0.02; OR, 0.17; 95% CI, 0.04 to 0.71); MAFs were 0.39% and 0.29% in patients and 1.2% and 1.1% in controls, respectively. The other nine SNPs showed trends toward association (P<0.10) (Supplemental Table 2).

Thirty-five of the 66 SNPs selected for analysis could be surveyed in the AXIOM replication sample consisting of 2041 patients with T2D-ESRD, 667 individuals with T2D lacking nephropathy, and 1140 nondiabetic, non–nephropathy controls (Supplemental Table 1). In fully adjusted models, LRP2 SNP rs17848169 (P=0.02; OR, 0.54; 95% CI, 0.32 to 0.90) and CUBN index SNP rs1801239 (P=0.02; OR, 1.37; 95% CI, 1.06 to 1.78) were associated with T2D-ESRD (versus non-nephropathy controls). The LRP2 SNP rs34291900 detected in the T2D-GENES Consortium data showed a weak trend toward association (P=0.18; OR, 0.67; 95% CI, 0.38 to 1.20) (Table 2). Other SNPs tested in the AXIOM samples, including the second CUBN index SNP rs7918972, were not associated with T2D-ESRD (Supplemental Table 1).

View this table:
  • View inline
  • View popup
Table 2.

Association analysis between cubilin gene and megalin gene variants with type 2 diabetes and ESRD (additive, fully adjusted model)

A meta-analysis considering 10 CUBN and eight LRP2 SNPs genotyped in the T2D-GENES Consortium and the AXIOM samples was performed for association with T2D-ESRD (Table 2). LRP2 SNP rs17848169 was significantly associated with T2D-ESRD (versus non-nephropathy controls) after correction for multiple testing with Pcorr=0.04 (P value =0.002×18=0.04), and LRP2 SNP rs34291900 was nominally associated (P=0.03); both variants showed the same directions of effect in each sample set. CUBN index SNP rs1801239 also replicated association in the meta-analysis with P=0.03 and the same direction of effect in each set. The meta-analysis was repeated by removing patients and controls felt likely to be at risk for nondiabetic ESRD on the basis of possession of two APOL1 renal risk variants. Despite a smaller sample, results generally remained consistent (Supplemental Table 3).

Associations between CUBN and LRP2 variants with nondiabetic ESRD were next assessed. The 66 selected SNPs were genotyped in 885 blacks with nondiabetic ESRD and 721 nondiabetic, non–nephropathy controls at the Wake Forest School of Medicine (independent from the T2D-GENES Consortium); 60 SNPs were successfully genotyped and met quality control standards for analysis. Among these, two SNPs in LRP2 and four SNPs in CUBN were nominally associated with nondiabetic ESRD (versus non-nephropathy controls) in the fully adjusted model with P values of 0.02–0.05 under the additive model (Table 3). None remained significantly associated after correction for multiple comparisons (Pcorr>0.05). One CUBN index SNP rs7918972 trended toward significant association with non-T2D ESRD (P=0.06; OR, 1.25; 95% CI, 0.99 to 1.58), whereas the second CUBN index SNP rs1801239 was not associated (P=0.90; OR, 1.03; 95% CI, 0.61 to 1.74) (Supplemental Table 1).

View this table:
  • View inline
  • View popup
Table 3.

Strongest genetic associations in patients with nondiabetic ESRD (additive, fully adjusted model)

To determine whether SNPs associated with T2D-ESRD reflected association with T2D per se or kidney disease, trait discrimination analyses were performed in the AXIOM samples. None of the associated variants were associated with T2D per se comparing patients with T2D lacking nephropathy with nondiabetic, non–nephropathy controls (for example, P=0.40 and P=0.78 for LRP2 SNP rs17848169 and CUBN index SNP rs1801239, respectively) (Table 4). Furthermore, CUBN SNP rs1801239 was associated with nephropathy in patients with T2D-ESRD compared with those with T2D lacking nephropathy (P=0.04). These findings support risk or protective allele associations with nephropathy and do not support risk or protective allele associations with diabetes.

View this table:
  • View inline
  • View popup
Table 4.

Trait discrimination analysis of type 2 diabetes– and ESRD–associated single–nucleotide polymorphisms in the Affymetrix Axiom Biobank Genotyping Array samples

To assess the potential for synthetic association (association with one or more rare causal variants in long-range linkage disequilibrium (LD), where D′ is approximately one, but r2 is modest), we evaluated LD between rs1801239 and lower–frequency CUBN variants (rs74431427, rs148100631, rs2271460, and rs144360241) in both the 1000 Genomes Project and our own data (22–24). No evidence of LD (D′ or r2) was observed, in part because of the low frequency of rs1801239 (MAF=0.028) and the small number of rare variants. A conditional analysis was performed with rs1801239 incorporated in the statistical model, and no major differences in significance were detected. In addition, rs1801239 was tested for association with T2D-ESRD by adjusting for each of the four rarer SNPs, and it remained significant, suggesting that the association was not caused by these rarer SNPs (data not shown). Therefore, there was no evidence supporting synthetic association for rs1801239.

Discussion

This study investigated genetic association between CUBN and LRP2 gene variants with diabetic and nondiabetic etiologies of ESRD in blacks from the T2D-GENES Consortium, independent AXIOM array–based samples, and additional patients with nondiabetic etiologies of ESRD and controls from the Wake Forest School of Medicine. Because NGES is a powerful technology that allows one to comprehensively identify and test genetic variations in coding sequences of genes for disease association, we used NGES data (the T2D-GENES Consortium) to survey CUBN/LRP2 genes as a first step and identified 15 SNPs suggestively associated with T2D-ESRD (P<0.10). Considering that most of the SNPs from the T2D-GENES Consortium were rare variants, 11 additional coding variants from the Exome Sequencing Project were selected as a supplement on the basis of their allele enrichment (MAF>0.01) and in silico prediction. To explore the role of common variants in disease susceptibility, 38 tagging SNPs (MAF>0.05) across the HapMap region of linkage disequilibrium with the two index variants were also selected. Thus, this study provided a locus–wide association analysis instead of simple replication for the identified variants.

CUBN index SNP rs1801239 replicated risk for association with T2D-ESRD; this variant was previously associated with albuminuria. A novel LRP2 missense variant rs17848169 (N2632D) was also found to be protective from T2D-ESRD. In contrast, no CUBN or LRP2 SNPs were significantly associated with nondiabetic ESRD in blacks.

Trait discrimination analyses supported that the associated CUBN and LRP2 variants play roles in nephropathy susceptibility in blacks and not diabetes per se. These results suggest an important role of the cubilin-megalin complex in development of progressive diabetic kidney disease in populations with recent African ancestry beyond albuminuria caused by reduced proximal tubule reabsorption. Recent evidence supports the importance of endocytotic reabsorption of filtered albumin in health, because glomerular filtration of albumin seems to be greater than initially appreciated (25–27). Albumin reabsorption occurs in proximal tubule cells, where the cubilin-megalin receptor complex is expressed on the apical brush border and plays a critical role in receptor-mediated endocytosis (16,28,29). Although albuminuria often leads to nephropathy progression, roles of the CUBN and LRP2 genes in T2D-ESRD in blacks were not previously studied.

Several CUBN and cubilin–associated amnion–less gene variants cause Imerslund Grasbeck syndrome, a rare autosomal recessive disease characterized by megaloblastic anemia, recurrent infections, failure to thrive, and proteinuria (30,31). However, the common CUBN variants rs1801239 and rs7918972 were only recently found to associate with albuminuria and nephropathy. In initial studies, rs1801239 was associated with albuminuria and not associated with eGFR or ESRD (12). In this report, rs1801239 was associated with T2D-ESRD with the same direction of effect as for albuminuria, indicating that the C allele carries risk for T2D-ESRD in blacks. We did not replicate association with the rs7918972 index SNP in CUBN in these black patients; this SNP was previously associated with ESRD in a European sample (17). Additional studies with large sample sizes and in different ethnic groups are necessary to clarify the correlations between genetic variation in CUBN and LRP2 and diabetic ESRD.

An LRP2 missense variant, rs17848169 (N2632D), which is protective for T2D-ESRD in blacks, was identified for the first time. Although present at low frequency, concordance for MAFs in patients and controls was present in independent T2D-GENES Consortium (<0.004 patients and 0.012 controls) and AXIOM array (<0.005 patients and <0.01 controls) samples. The same trend was observed in the nondiabetic ESRD samples (<0.008 patients and 0.011 controls; P=0.14). Therefore, the association with T2D-ESRD seems credible.

Cubilin is a 460-kD multipurpose receptor that can bind to a range of ligands, including intrinsic factor/vitamin B12, transferrin, hemoglobin, HDL cholesterol, apolipoprotein A1, megalin, and albumin (32). As a peripheral membrane protein, cubilin contains a 110–residue N–terminal domain, an eight EGF–like repeat domain, and 27 CUB domains (33). Because cubilin lacks transmembrane and cytoplasmic domains, internalization of albumin is thought to be mediated via its interaction with megalin, a 600-kD transmembrane protein in the LDL receptor family (34).

LRP2 variant rs17848169 (N2632D) is located in the extracellular LDL receptor repeat segments of megalin, where ligand binding sites exist (35). Although megalin can bind albumin (36), animal studies reveal that the major role of megalin in albumin reabsorption is to drive internalization of cubilin-albumin complexes (16). CUBN index SNP rs1801239 (I2984V) is located in the 22nd CUB domain of cubilin, one of the three fragments that bind to megalin (37). Therefore, I2984V and N2632D may interfere with the interaction between cubilin and megalin to alter albumin reabsorption. Functional studies will be required to clarify potential mechanisms.

A recent report revealed that the CUBN rs1801239 risk variant appeared on a derived low–frequency European haplotype consisting of 19 SNPs and that the frequency of each SNP differed significantly in Africans (and was absent in West Africans). This European haplotype may represent a region of extended linkage disequilibrium, conceivably reflecting the effect of positive selective pressure under nutritional influences during evolution (38). On the basis of results in admixed blacks, we observed that variation at rs1801239 was slightly higher than that in the 1000 Genomes Project or the HapMap Yoruba data (0.024–0.031 in our AXIOM dataset versus 0.018 in public datasets). Among the 19 CUBN variants assessed by Tzur et al. (38), only rs1801239 and rs62619939 were available in this study on the basis of the differential selection strategy. Therefore, additional association studies using variants in continental African cohorts lacking this European origin haplotype will be important to clarify the causative variant.

It is noteworthy that none of the CUBN or LRP2 SNPs were associated with nondiabetic etiologies of ESRD in this sample of blacks. Although the nondiabetic ESRD sample was smaller than the T2D-ESRD cohorts with reduced statistical power (significance level of 8.3×10−4 on the basis of the 60 successfully genotyped SNPs in nondiabetic ESRD samples), the expected power to detect SNPs with a frequency of 0.05 and an OR of 1.5 was 0.31, and we feel that it is likely that mechanisms beyond impaired albumin reabsorption in proximal tubule cells contribute to nephropathy in blacks with nondiabetic kidney disease. Studies have shown that the APOL1 G1 and G2 renal risk alleles markedly increase risk for FSGS, focal global glomerulosclerosis, HIV-associated nephropathy, and lupus nephritis (6,7). The younger age of controls relative to patients in this report warrants comment, because this could bias results toward the null hypothesis. In analyses of T2D-ESRD, the mean age of controls was older than the age at onset of T2D in patients. Therefore, the controls are less likely to develop T2D and/or subsequent T2D-ESRD. In analyses of nondiabetic ESRD, the mean age of controls was nearly 4 years younger than the age at onset of ESRD in patients ([age at recruitment] − [ESRD duration]); therefore, they are also far less likely to develop ESRD within this short timeframe given that they were nondiabetic, were non-nephropathic, and had a normal serum creatinine concentration (0.97 mg/dl).

In conclusion, genetic association was explored between the CUBN and LRP2 genes for susceptibility to advanced nephropathy in blacks. CUBN variant rs1801239, previously associated with albuminuria in predominantly European populations, was associated with T2D-ESRD in individuals with recent African ancestry. A novel LRP2 missense variant rs17848169 (N2632D) was also found to be associated with lower risk for T2D-ESRD in this population. Variants in CUBN and LRP2 were not associated with T2D or nondiabetic etiologies of ESRD in blacks.

Disclosures

None.

Acknowledgments

The authors thank Dr. Mark D. Okusa (University of Virginia School of Medicine) for assistance with participant recruitment.

J.M. was supported by an International Society of Nephrology fellowship and the Shanghai Jiaotong University K.C. Wong Medical Fellowship Fund. This work was supported by National Institutes of Health grants R01DK53591 (to D.W.B.), R01DK070941 (to B.I.F.), and DK071891 (to B.I.F.) and National Natural Science Foundation of China grant 81200488.

Footnotes

  • Published online ahead of print. Publication date available at www.cjasn.org.

  • See related editorial, “Beyond APOL1: Genetic Inroads into Understanding Population Disparities in Diabetic Kidney Disease,” on pages 928–931.

  • This article contains supplemental material online at http://cjasn.asnjournals.org/lookup/suppl/doi:10.2215/CJN.12971215/-/DCSupplemental.

  • Received December 7, 2015.
  • Accepted February 23, 2016.
  • Copyright © 2016 by the American Society of Nephrology

References

    1. Köttgen A
    : Genome-wide association studies in nephrology research. Am J Kidney Dis 56: 743–758, 2010pmid:20728256
    1. Friedman DJ,
    2. Pollak MR
    : Genetics of kidney failure and the evolving story of APOL1. J Clin Invest 121: 3367–3374, 2011pmid:21881214
    1. Freedman BI,
    2. Tuttle AB,
    3. Spray BJ
    : Familial predisposition to nephropathy in African-Americans with non-insulin-dependent diabetes mellitus. Am J Kidney Dis 25: 710–713, 1995pmid:7747724
  1. Saran R, Li Y, Robinson B, Ayanian J, Balkrishnan R, Bragg-Gresham J, Chen JT, Cope E, Gipson D, He K, Herman W, Heung M, Hirth RA, Jacobsen SS, Kalantar-Zadeh K, Kovesdy CP, Leichtman AB, Lu Y, Molnar MZ, Morgenstern H, Nallamothu B, O'Hare AM, Pisoni R, Plattner B, Port FK, Rao P, Rhee CM, Schaubel DE, Selewski DT, Shahinian V, Sim JJ, Song P, Streja E, Kurella Tamura M, Tentori F, Eggers PW, Agodoa LY, Abbott KC: US Renal Data System 2014 Annual Data Report: Epidemiology of kidney disease in the United States. Am J Kidney Dis 66[1 Suppl 1]: S1–S105, 2015
    1. Kopp JB,
    2. Nelson GW,
    3. Sampath K,
    4. Johnson RC,
    5. Genovese G,
    6. An P,
    7. Friedman D,
    8. Briggs W,
    9. Dart R,
    10. Korbet S,
    11. Mokrzycki MH,
    12. Kimmel PL,
    13. Limou S,
    14. Ahuja TS,
    15. Berns JS,
    16. Fryc J,
    17. Simon EE,
    18. Smith MC,
    19. Trachtman H,
    20. Michel DM,
    21. Schelling JR,
    22. Vlahov D,
    23. Pollak M,
    24. Winkler CA
    : APOL1 genetic variants in focal segmental glomerulosclerosis and HIV-associated nephropathy. J Am Soc Nephrol 22: 2129–2137, 2011pmid:21997394
    1. Genovese G,
    2. Friedman DJ,
    3. Ross MD,
    4. Lecordier L,
    5. Uzureau P,
    6. Freedman BI,
    7. Bowden DW,
    8. Langefeld CD,
    9. Oleksyk TK,
    10. Uscinski Knob AL,
    11. Bernhardy AJ,
    12. Hicks PJ,
    13. Nelson GW,
    14. Vanhollebeke B,
    15. Winkler CA,
    16. Kopp JB,
    17. Pays E,
    18. Pollak MR
    : Association of trypanolytic ApoL1 variants with kidney disease in African Americans. Science 329: 841–845, 2010pmid:20647424
    1. Tzur S,
    2. Rosset S,
    3. Shemer R,
    4. Yudkovsky G,
    5. Selig S,
    6. Tarekegn A,
    7. Bekele E,
    8. Bradman N,
    9. Wasser WG,
    10. Behar DM,
    11. Skorecki K
    : Missense mutations in the APOL1 gene are highly associated with end stage kidney disease risk previously attributed to the MYH9 gene. Hum Genet 128: 345–350, 2010pmid:20635188
    1. McDonough CW,
    2. Palmer ND,
    3. Hicks PJ,
    4. Roh BH,
    5. An SS,
    6. Cooke JN,
    7. Hester JM,
    8. Wing MR,
    9. Bostrom MA,
    10. Rudock ME,
    11. Lewis JP,
    12. Talbert ME,
    13. Blevins RA,
    14. Lu L,
    15. Ng MC,
    16. Sale MM,
    17. Divers J,
    18. Langefeld CD,
    19. Freedman BI,
    20. Bowden DW
    : A genome-wide association study for diabetic nephropathy genes in African Americans. Kidney Int 79: 563–572, 2011pmid:21150874
    1. Palmer ND,
    2. Ng MC,
    3. Hicks PJ,
    4. Mudgal P,
    5. Langefeld CD,
    6. Freedman BI,
    7. Bowden DW
    : Evaluation of candidate nephropathy susceptibility genes in a genome-wide association study of African American diabetic kidney disease. PLoS One 9: e88273, 2014pmid:24551085
    1. Bonomo JA,
    2. Ng MC,
    3. Palmer ND,
    4. Keaton JM,
    5. Larsen CP,
    6. Hicks PJ,
    7. Langefeld CD,
    8. Freedman BI,
    9. Bowden DW, T2D-GENES Consortium
    : Coding variants in nephrin (NPHS1) and susceptibility to nephropathy in African Americans. Clin J Am Soc Nephrol 9: 1434–1440, 2014pmid:24948143
    1. Bonomo JA,
    2. Guan M,
    3. Ng MC,
    4. Palmer ND,
    5. Hicks PJ,
    6. Keaton JM,
    7. Lea JP,
    8. Langefeld CD,
    9. Freedman BI,
    10. Bowden DW
    : The ras responsive transcription factor RREB1 is a novel candidate gene for type 2 diabetes associated end-stage kidney disease. Hum Mol Genet 23: 6441–6447, 2014pmid:25027322
    1. Böger CA,
    2. Chen MH,
    3. Tin A,
    4. Olden M,
    5. Köttgen A,
    6. de Boer IH,
    7. Fuchsberger C,
    8. O’Seaghdha CM,
    9. Pattaro C,
    10. Teumer A,
    11. Liu CT,
    12. Glazer NL,
    13. Li M,
    14. O’Connell JR,
    15. Tanaka T,
    16. Peralta CA,
    17. Kutalik Z,
    18. Luan J,
    19. Zhao JH,
    20. Hwang SJ,
    21. Akylbekova E,
    22. Kramer H,
    23. van der Harst P,
    24. Smith AV,
    25. Lohman K,
    26. de Andrade M,
    27. Hayward C,
    28. Kollerits B,
    29. Tönjes A,
    30. Aspelund T,
    31. Ingelsson E,
    32. Eiriksdottir G,
    33. Launer LJ,
    34. Harris TB,
    35. Shuldiner AR,
    36. Mitchell BD,
    37. Arking DE,
    38. Franceschini N,
    39. Boerwinkle E,
    40. Egan J,
    41. Hernandez D,
    42. Reilly M,
    43. Townsend RR,
    44. Lumley T,
    45. Siscovick DS,
    46. Psaty BM,
    47. Kestenbaum B,
    48. Haritunians T,
    49. Bergmann S,
    50. Vollenweider P,
    51. Waeber G,
    52. Mooser V,
    53. Waterworth D,
    54. Johnson AD,
    55. Florez JC,
    56. Meigs JB,
    57. Lu X,
    58. Turner ST,
    59. Atkinson EJ,
    60. Leak TS,
    61. Aasarød K,
    62. Skorpen F,
    63. Syvänen AC,
    64. Illig T,
    65. Baumert J,
    66. Koenig W,
    67. Krämer BK,
    68. Devuyst O,
    69. Mychaleckyj JC,
    70. Minelli C,
    71. Bakker SJ,
    72. Kedenko L,
    73. Paulweber B,
    74. Coassin S,
    75. Endlich K,
    76. Kroemer HK,
    77. Biffar R,
    78. Stracke S,
    79. Völzke H,
    80. Stumvoll M,
    81. Mägi R,
    82. Campbell H,
    83. Vitart V,
    84. Hastie ND,
    85. Gudnason V,
    86. Kardia SL,
    87. Liu Y,
    88. Polasek O,
    89. Curhan G,
    90. Kronenberg F,
    91. Prokopenko I,
    92. Rudan I,
    93. Arnlöv J,
    94. Hallan S,
    95. Navis G,
    96. Parsa A,
    97. Ferrucci L,
    98. Coresh J,
    99. Shlipak MG,
    100. Bull SB,
    101. Paterson NJ,
    102. Wichmann HE,
    103. Wareham NJ,
    104. Loos RJ,
    105. Rotter JI,
    106. Pramstaller PP,
    107. Cupples LA,
    108. Beckmann JS,
    109. Yang Q,
    110. Heid IM,
    111. Rettig R,
    112. Dreisbach AW,
    113. Bochud M,
    114. Fox CS,
    115. Kao WH, CKDGen Consortium
    : CUBN is a gene locus for albuminuria. J Am Soc Nephrol 22: 555–570, 2011pmid:21355061
    1. Teumer A,
    2. Tin A,
    3. Sorice R,
    4. Gorski M,
    5. Yeo NC,
    6. Chu AY,
    7. Li M,
    8. Li Y,
    9. Mijatovic V,
    10. Ko YA,
    11. Taliun D,
    12. Luciani A,
    13. Chen MH,
    14. Yang Q,
    15. Foster MC,
    16. Olden M,
    17. Hiraki LT,
    18. Tayo BO,
    19. Fuchsberger C,
    20. Dieffenbach AK,
    21. Shuldiner AR,
    22. Smith AV,
    23. Zappa AM,
    24. Lupo A,
    25. Kollerits B,
    26. Ponte B,
    27. Stengel B,
    28. Krämer BK,
    29. Paulweber B,
    30. Mitchell BD,
    31. Hayward C,
    32. Helmer C,
    33. Meisinger C,
    34. Gieger C,
    35. Shaffer CM,
    36. Müller C,
    37. Langenberg C,
    38. Ackermann D,
    39. Siscovick D,
    40. Boerwinkle E,
    41. Kronenberg F,
    42. Ehret GB,
    43. Homuth G,
    44. Waeber G,
    45. Navis G,
    46. Gambaro G,
    47. Malerba G,
    48. Eiriksdottir G,
    49. Li G,
    50. Wichmann HE,
    51. Grallert H,
    52. Wallaschofski H,
    53. Völzke H,
    54. Brenner H,
    55. Kramer H,
    56. Leach IM,
    57. Rudan I,
    58. Hillege JL,
    59. Beckmann JS,
    60. Lambert JC,
    61. Luan J,
    62. Zhao JH,
    63. Chalmers J,
    64. Coresh J,
    65. Denny JC,
    66. Butterbach K,
    67. Launer LJ,
    68. Ferrucci L,
    69. Kedenko L,
    70. Haun M,
    71. Metzger M,
    72. Woodward M,
    73. Hoffman MJ,
    74. Nauck M,
    75. Waldenberger M,
    76. Pruijm M,
    77. Bochud M,
    78. Rheinberger M,
    79. Verweij N,
    80. Wareham NJ,
    81. Endlich N,
    82. Soranzo N,
    83. Polasek O,
    84. van der Harst P,
    85. Pramstaller PP,
    86. Vollenweider P,
    87. Wild PS,
    88. Gansevoort RT,
    89. Rettig R,
    90. Biffar R,
    91. Carroll RJ,
    92. Katz R,
    93. Loos RJ,
    94. Hwang SJ,
    95. Coassin S,
    96. Bergmann S,
    97. Rosas SE,
    98. Stracke S,
    99. Harris TB,
    100. Corre T,
    101. Zeller T,
    102. Illig T,
    103. Aspelund T,
    104. Tanaka T,
    105. Lendeckel U,
    106. Völker U,
    107. Gudnason V,
    108. Chouraki V,
    109. Koenig W,
    110. Kutalik Z,
    111. O’Connell JR,
    112. Parsa A,
    113. Heid IM,
    114. Paterson AD,
    115. de Boer IH,
    116. Devuyst O,
    117. Lazar J,
    118. Endlich K,
    119. Susztak K,
    120. Tremblay J,
    121. Hamet P,
    122. Jacob HJ,
    123. Böger CA,
    124. Fox CS,
    125. Pattaro C,
    126. Köttgen A, DCCT/EDIC
    : Genome-wide association studies identify genetic loci associated with albuminuria in diabetes. Diabetes : db151313, 2015pmid:26631737
    1. Dickson LE,
    2. Wagner MC,
    3. Sandoval RM,
    4. Molitoris BA
    : The proximal tubule and albuminuria: Really! J Am Soc Nephrol 25: 443–453, 2014pmid:24408874
    1. Birn H,
    2. Fyfe JC,
    3. Jacobsen C,
    4. Mounier F,
    5. Verroust PJ,
    6. Orskov H,
    7. Willnow TE,
    8. Moestrup SK,
    9. Christensen EI
    : Cubilin is an albumin binding protein important for renal tubular albumin reabsorption. J Clin Invest 105: 1353–1361, 2000pmid:10811843
    1. Amsellem S,
    2. Gburek J,
    3. Hamard G,
    4. Nielsen R,
    5. Willnow TE,
    6. Devuyst O,
    7. Nexo E,
    8. Verroust PJ,
    9. Christensen EI,
    10. Kozyraki R
    : Cubilin is essential for albumin reabsorption in the renal proximal tubule. J Am Soc Nephrol 21: 1859–1867, 2010pmid:20798259
    1. Reznichenko A,
    2. Snieder H,
    3. van den Born J,
    4. de Borst MH,
    5. Damman J,
    6. van Dijk MC,
    7. van Goor H,
    8. Hepkema BG,
    9. Hillebrands JL,
    10. Leuvenink HG,
    11. Niesing J,
    12. Bakker SJ,
    13. Seelen M,
    14. 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, 2012pmid:22574174
    1. Keene KL,
    2. Mychaleckyj JC,
    3. Smith SG,
    4. Leak TS,
    5. Perlegas PS,
    6. Langefeld CD,
    7. Freedman BI,
    8. Rich SS,
    9. Bowden DW,
    10. Sale MM
    : Association of the distal region of the ectonucleotide pyrophosphatase/phosphodiesterase 1 gene with type 2 diabetes in an African-American population enriched for nephropathy. Diabetes 57: 1057–1062, 2008pmid:18184924
    1. Tang H,
    2. Peng J,
    3. Wang P,
    4. Risch NJ
    : Estimation of individual admixture: Analytical and study design considerations. Genet Epidemiol 28: 289–301, 2005pmid:15712363
    1. Sawcer S,
    2. Hellenthal G,
    3. Pirinen M,
    4. Spencer CC,
    5. Patsopoulos NA,
    6. Moutsianas L,
    7. Dilthey A,
    8. Su Z,
    9. Freeman C,
    10. Hunt SE,
    11. Edkins S,
    12. Gray E,
    13. Booth DR,
    14. Potter SC,
    15. Goris A,
    16. Band G,
    17. Oturai AB,
    18. Strange A,
    19. Saarela J,
    20. Bellenguez C,
    21. Fontaine B,
    22. Gillman M,
    23. Hemmer B,
    24. Gwilliam R,
    25. Zipp F,
    26. Jayakumar A,
    27. Martin R,
    28. Leslie S,
    29. Hawkins S,
    30. Giannoulatou E,
    31. D’alfonso S,
    32. Blackburn H,
    33. Martinelli Boneschi F,
    34. Liddle J,
    35. Harbo HF,
    36. Perez ML,
    37. Spurkland A,
    38. Waller MJ,
    39. Mycko MP,
    40. Ricketts M,
    41. Comabella M,
    42. Hammond N,
    43. Kockum I,
    44. McCann OT,
    45. Ban M,
    46. Whittaker P,
    47. Kemppinen A,
    48. Weston P,
    49. Hawkins C,
    50. Widaa S,
    51. Zajicek J,
    52. Dronov S,
    53. Robertson N,
    54. Bumpstead SJ,
    55. Barcellos LF,
    56. Ravindrarajah R,
    57. Abraham R,
    58. Alfredsson L,
    59. Ardlie K,
    60. Aubin C,
    61. Baker A,
    62. Baker K,
    63. Baranzini SE,
    64. Bergamaschi L,
    65. Bergamaschi R,
    66. Bernstein A,
    67. Berthele A,
    68. Boggild M,
    69. Bradfield JP,
    70. Brassat D,
    71. Broadley SA,
    72. Buck D,
    73. Butzkueven H,
    74. Capra R,
    75. Carroll WM,
    76. Cavalla P,
    77. Celius EG,
    78. Cepok S,
    79. Chiavacci R,
    80. Clerget-Darpoux F,
    81. Clysters K,
    82. Comi G,
    83. Cossburn M,
    84. Cournu-Rebeix I,
    85. Cox MB,
    86. Cozen W,
    87. Cree BA,
    88. Cross AH,
    89. Cusi D,
    90. Daly MJ,
    91. Davis E,
    92. de Bakker PI,
    93. Debouverie M,
    94. D’hooghe MB,
    95. Dixon K,
    96. Dobosi R,
    97. Dubois B,
    98. Ellinghaus D,
    99. Elovaara I,
    100. Esposito F,
    101. Fontenille C,
    102. Foote S,
    103. Franke A,
    104. Galimberti D,
    105. Ghezzi A,
    106. Glessner J,
    107. Gomez R,
    108. Gout O,
    109. Graham C,
    110. Grant SF,
    111. Guerini FR,
    112. Hakonarson H,
    113. Hall P,
    114. Hamsten A,
    115. Hartung HP,
    116. Heard RN,
    117. Heath S,
    118. Hobart J,
    119. Hoshi M,
    120. Infante-Duarte C,
    121. Ingram G,
    122. Ingram W,
    123. Islam T,
    124. Jagodic M,
    125. Kabesch M,
    126. Kermode AG,
    127. Kilpatrick TJ,
    128. Kim C,
    129. Klopp N,
    130. Koivisto K,
    131. Larsson M,
    132. Lathrop M,
    133. Lechner-Scott JS,
    134. Leone MA,
    135. Leppä V,
    136. Liljedahl U,
    137. Bomfim IL,
    138. Lincoln RR,
    139. Link J,
    140. Liu J,
    141. Lorentzen AR,
    142. Lupoli S,
    143. Macciardi F,
    144. Mack T,
    145. Marriott M,
    146. Martinelli V,
    147. Mason D,
    148. McCauley JL,
    149. Mentch F,
    150. Mero IL,
    151. Mihalova T,
    152. Montalban X,
    153. Mottershead J,
    154. Myhr KM,
    155. Naldi P,
    156. Ollier W,
    157. Page A,
    158. Palotie A,
    159. Pelletier J,
    160. Piccio L,
    161. Pickersgill T,
    162. Piehl F,
    163. Pobywajlo S,
    164. Quach HL,
    165. Ramsay PP,
    166. Reunanen M,
    167. Reynolds R,
    168. Rioux JD,
    169. Rodegher M,
    170. Roesner S,
    171. Rubio JP,
    172. Rückert IM,
    173. Salvetti M,
    174. Salvi E,
    175. Santaniello A,
    176. Schaefer CA,
    177. Schreiber S,
    178. Schulze C,
    179. Scott RJ,
    180. Sellebjerg F,
    181. Selmaj KW,
    182. Sexton D,
    183. Shen L,
    184. Simms-Acuna B,
    185. Skidmore S,
    186. Sleiman PM,
    187. Smestad C,
    188. Sørensen PS,
    189. Søndergaard HB,
    190. Stankovich J,
    191. Strange RC,
    192. Sulonen AM,
    193. Sundqvist E,
    194. Syvänen AC,
    195. Taddeo F,
    196. Taylor B,
    197. Blackwell JM,
    198. Tienari P,
    199. Bramon E,
    200. Tourbah A,
    201. Brown MA,
    202. Tronczynska E,
    203. Casas JP,
    204. Tubridy N,
    205. Corvin A,
    206. Vickery J,
    207. Jankowski J,
    208. Villoslada P,
    209. Markus HS,
    210. Wang K,
    211. Mathew CG,
    212. Wason J,
    213. Palmer CN,
    214. Wichmann HE,
    215. Plomin R,
    216. Willoughby E,
    217. Rautanen A,
    218. Winkelmann J,
    219. Wittig M,
    220. Trembath RC,
    221. Yaouanq J,
    222. Viswanathan AC,
    223. Zhang H,
    224. Wood NW,
    225. Zuvich R,
    226. Deloukas P,
    227. Langford C,
    228. Duncanson A,
    229. Oksenberg JR,
    230. Pericak-Vance MA,
    231. Haines JL,
    232. Olsson T,
    233. Hillert J,
    234. Ivinson AJ,
    235. De Jager PL,
    236. Peltonen L,
    237. Stewart GJ,
    238. Hafler DA,
    239. Hauser SL,
    240. McVean G,
    241. Donnelly P,
    242. Compston A, International Multiple Sclerosis Genetics Consortium, Wellcome Trust Case Control Consortium 2
    : Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis. Nature 476: 214–219, 2011pmid:21833088
    1. Willer CJ,
    2. Li Y,
    3. Abecasis GR
    : METAL: Fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26: 2190–2191, 2010pmid:20616382
    1. Dickson SP,
    2. Wang K,
    3. Krantz I,
    4. Hakonarson H,
    5. Goldstein DB
    : Rare variants create synthetic genome-wide associations. PLoS Biol 8: e1000294, 2010pmid:20126254
    1. Chang D,
    2. Keinan A
    : Predicting signatures of “synthetic associations” and “natural associations” from empirical patterns of human genetic variation. PLOS Comput Biol 8: e1002600, 2012pmid:22792059
    1. Takeuchi F,
    2. Kobayashi S,
    3. Ogihara T,
    4. Fujioka A,
    5. Kato N
    : Detection of common single nucleotide polymorphisms synthesizing quantitative trait association of rarer causal variants. Genome Res 21: 1122–1130, 2011pmid:21441355
    1. Osicka TM,
    2. Strong KJ,
    3. Nikolic-Paterson DJ,
    4. Atkins RC,
    5. Jerums G,
    6. Comper WD
    : Renal processing of serum proteins in an albumin-deficient environment: An in vivo study of glomerulonephritis in the Nagase analbuminaemic rat. Nephrol Dial Transplant 19: 320–328, 2004pmid:14736954
    1. Gagliardini E,
    2. Conti S,
    3. Benigni A,
    4. Remuzzi G,
    5. Remuzzi A
    : Imaging of the porous ultrastructure of the glomerular epithelial filtration slit. J Am Soc Nephrol 21: 2081–2089, 2010pmid:21030599
    1. Russo LM,
    2. Sandoval RM,
    3. McKee M,
    4. Osicka TM,
    5. Collins AB,
    6. Brown D,
    7. Molitoris BA,
    8. Comper WD
    : The normal kidney filters nephrotic levels of albumin retrieved by proximal tubule cells: Retrieval is disrupted in nephrotic states. Kidney Int 71: 504–513, 2007pmid:17228368
    1. Grant BD,
    2. Donaldson JG
    : Pathways and mechanisms of endocytic recycling. Nat Rev Mol Cell Biol 10: 597–608, 2009pmid:19696797
    1. Christensen EI,
    2. Birn H
    : Megalin and cubilin: Multifunctional endocytic receptors. Nat Rev Mol Cell Biol 3: 256–266, 2002pmid:11994745
    1. Storm T,
    2. Zeitz C,
    3. Cases O,
    4. Amsellem S,
    5. Verroust PJ,
    6. Madsen M,
    7. Benoist JF,
    8. Passemard S,
    9. Lebon S,
    10. Jønsson IM,
    11. Emma F,
    12. Koldsø H,
    13. Hertz JM,
    14. Nielsen R,
    15. Christensen EI,
    16. Kozyraki R
    : Detailed investigations of proximal tubular function in Imerslund-Gräsbeck syndrome. BMC Med Genet 14: 111, 2013pmid:24156255
    1. Drögemüller M,
    2. Jagannathan V,
    3. Howard J,
    4. Bruggmann R,
    5. Drögemüller C,
    6. Ruetten M,
    7. Leeb T,
    8. Kook PH
    : A frameshift mutation in the cubilin gene (CUBN) in Beagles with Imerslund-Gräsbeck syndrome (selective cobalamin malabsorption). Anim Genet 45: 148–150, 2014pmid:24164695
    1. Christensen EI,
    2. Nielsen R,
    3. Birn H
    : From bowel to kidneys: The role of cubilin in physiology and disease. Nephrol Dial Transplant 28: 274–281, 2013pmid:23291372
    1. Moestrup SK,
    2. Kozyraki R,
    3. Kristiansen M,
    4. Kaysen JH,
    5. Rasmussen HH,
    6. Brault D,
    7. Pontillon F,
    8. Goda FO,
    9. Christensen EI,
    10. Hammond TG,
    11. Verroust PJ
    : The intrinsic factor-vitamin B12 receptor and target of teratogenic antibodies is a megalin-binding peripheral membrane protein with homology to developmental proteins. J Biol Chem 273: 5235–5242, 1998pmid:9478979
    1. Christensen EI,
    2. Verroust PJ,
    3. Nielsen R
    : Receptor-mediated endocytosis in renal proximal tubule. Pflugers Arch 458: 1039–1048, 2009pmid:19499243
    1. Saito A,
    2. Pietromonaco S,
    3. Loo AK,
    4. Farquhar MG
    : Complete cloning and sequencing of rat gp330/“megalin,” a distinctive member of the low density lipoprotein receptor gene family. Proc Natl Acad Sci U S A 91: 9725–9729, 1994pmid:7937880
    1. Cui S,
    2. Verroust PJ,
    3. Moestrup SK,
    4. Christensen EI
    : Megalin/gp330 mediates uptake of albumin in renal proximal tubule. Am J Physiol 271: F900–F907, 1996pmid:8898021
    1. Ahuja R,
    2. Yammani R,
    3. Bauer JA,
    4. Kalra S,
    5. Seetharam S,
    6. Seetharam B
    : Interactions of cubilin with megalin and the product of the amnionless gene (AMN): Effect on its stability. Biochem J 410: 301–308, 2008pmid:17990981
    1. Tzur S,
    2. Wasser WG,
    3. Rosset S,
    4. Skorecki K
    : Linkage disequilibrium analysis reveals an albuminuria risk haplotype containing three missense mutations in the cubilin gene with striking differences among European and African ancestry populations. BMC Nephrol 13: 142, 2012pmid:23114252

Articles

  • Current Issue
  • Early Access
  • Subject Collections
  • Article Archive
  • ASN Meeting Abstracts

Information for Authors

  • Submit a Manuscript
  • Trainee of the Year
  • Author Resources
  • ASN Journal Policies
  • Reuse/Reprint Policy

About

  • CJASN
  • ASN
  • ASN Journals
  • ASN Kidney News

Journal Information

  • About CJASN
  • CJASN Email Alerts
  • CJASN Key Impact Information
  • CJASN Podcasts
  • CJASN RSS Feeds
  • Editorial Board

More Information

  • Advertise
  • ASN Podcasts
  • ASN Publications
  • Become an ASN Member
  • Feedback
  • Follow on Twitter
  • Password/Email Address Changes
  • Subscribe to ASN Journals

© 2022 American Society of Nephrology

Print ISSN - 1555-9041 Online ISSN - 1555-905X

Powered by HighWire