Abstract
Prior studies have identified common genetic variants influencing diabetic and non-diabetic nephropathy, diseases which disproportionately affect African Americans. Recently, exome sequencing techniques have facilitated identification of coding variants on a genome-wide basis in large samples. Exonic variants in known or suspected end-stage kidney disease (ESKD) or nephropathy genes can be tested for their ability to identify association either singly or in combination with known associated common variants. Coding variants in genes with prior evidence for association with ESKD or nephropathy were identified in the NHLBI-ESP GO database and genotyped in 5045 African Americans (3324 cases with type 2 diabetes associated nephropathy [T2D-ESKD] or non-T2D ESKD, and 1721 controls) and 1465 European Americans (568 T2D-ESKD cases and 897 controls). Logistic regression analyses were performed to assess association, with admixture and APOL1 risk status incorporated as covariates. Ten of 31 SNPs were associated in African Americans; four replicated in European Americans. In African Americans, SNPs in OR2L8, OR2AK2, C6orf167 (MMS22L), LIMK2, APOL3, APOL2, and APOL1 were nominally associated (P=1.8×10−4-0.044). Haplotype analysis of common and coding variants increased evidence of association at the OR2L13 and APOL1 loci (P=6.2×10−5 and 4.6×10−5, respectively). SNPs replicating in European Americans were in OR2AK2, LIMK2, and APOL2 (P=0.0010-0.037). Meta-analyses highlighted four SNPs associated in T2DESKD and all-cause ESKD. Results from this study suggest a role for coding variants in the development of diabetic, non-diabetic, and/or all-cause ESKD in African Americans and/or European Americans.
Keywords: African Americans, Association, European Americans, Exonic Variants, Type 2 Diabetes, Nephropathy
Introduction
Kidney disease affects approximately 40% of patients with type 2 diabetes (T2D) (de Boer et al. 2011) and 10-20% of individuals with diabetes ultimately die from renal complications (WHO 2011). Diabetes accounts for more than 40% of new cases of end-stage kidney disease (ESKD) (USRDS 2009). Despite increased use of diabetes-related medications over the last two decades, diabetes-associated kidney disease has increased and this trend is expected to continue (de Boer et al. 2011).
African Americans have the highest adjusted incidence and prevalence of ESKD in the U.S., with rates 3.5 times higher than in European Americans (USRDS 2011). ESKD incidence is higher among ethnic minorities regardless of uniform health care coverage, supporting the role of genetics and/or unknown environmental influences in kidney disease (Karter et al. 2002; Lipworth et al. 2012). Genetic variants with low minor allele frequencies (MAF) are more likely than common variants to be population-specific and are a possible source of the unaccounted-for risk for common diseases (Bustamante et al. 2011; Gravel et al. 2011; Manolio et al. 2009). It has been proposed that these coding variants will elucidate part of the “missing heritability” of diseases left undiscovered by genome-wide association studies (GWAS) (Manolio et al. 2009; Zeggini 2011). Exome sequencing technology has motivated the creation of data resources facilitating unbiased interrogation of genetic variation present in protein-coding regions (Teer and Mullikin 2010).
In this report we evaluated whether coding variants identified from large-scale exome sequencing resources were associated with nephropathy in African Americans and European Americans. Variants were chosen in genes with prior evidence of association with diabetic and non-diabetic forms of nephropathy, possible functional impact, and MAF in African Americans. We asked two specific questions: 1) can exonic variants alone demonstrate evidence of association with ESKD and 2) can exonic variants contribute to evidence of association with ESRD in combination with known common variants?
Subjects and Methods
Subjects
All subjects were unrelated, born in North Carolina, South Carolina, Georgia, Virginia, or Tennessee, of self-reported ethnicity. Diagnostic criteria for individuals with T2D-ESKD were diabetes diagnosis at age >30 years (in the absence of diabetic ketoacidosis), with either renal histologic evidence of diabetic nephropathy or diabetes duration ≥5 years before renal replacement therapy initiation, in the presence of diabetic retinopathy or proteinuria ≥500mg/24h and absence of other causes of nephropathy (Freedman et al. 2009b; McDonough et al. 2011). Patients with non-T2D ESKD were also evaluated and included those undergoing renal replacement therapy with no history of diabetes and meeting the same criteria for nephropathy diagnosis. Individuals with cystic renal diseases, hereditary nephritis, or urologic causes of ESKD were excluded from this group. Non-diabetic, non-nephropathy controls were recruited based on low risk for nephropathy due to the lack of a personal or family history of kidney disease; therefore, renal function testing was not routinely performed. The African American subject group included 2172 T2D-ESKD cases, 1152 non-T2D ESKD cases and 1721 controls. Thus, a combined total of 3324 African Americans with nephropathy diagnosis in the presence or absence of diabetes, referred to as “all-cause” ESKD, were evaluated. The European American subject group included 568 cases with T2D-ESKD and 897 non-diabetic, nonnephropathy controls. All participants provided written informed consent and studies were approved by the Wake Forest School of Medicine Institutional Review Board and adhere to the tenets of the Declaration of Helsinki.
In African Americans, ancestry proportions were evaluated using 70 ancestry informative markers (AIMs; (Keene et al. 2008)). Ancestral proportions were generated for each subject based on individual ancestral allele frequencies estimated by genotyping the 70 AIMs in Yoruba Nigerians and European Americans; results were evaluated under a two-population model implemented in FRAPPE (Tang et al. 2005). African ancestry (± standard deviation) was 0.80±0.11, 0.80±0.11, and 0.78±0.11, T2D-ESKD cases, non-T2D ESKD cases, and controls, respectively.
Variant Selection and Genotyping
The National Heart Lung and Blood Institute (NHLBI) ESP GO resource (https://esp.gs.washington.edu/drupal/, (Tennessen et al. 2012)) was used to identify single nucleotide polymorphisms (SNPs) in African Americans. SNPs were identified in genes with prior evidence for association with nephropathy (ACACB, AGER, APOL1, APOL2, APOL3, C6orf66, C6orf167 (MMS22L), C6orf191, CNDP1, CNDP2, LIMK2, MYH9, OR2AK2, OR2L8, OR2L13, SFI1, TMEM5, and UNC5C). Genotyping was carried out using the iPLEX™ Sequenom MassARRAY platform (Sequenom; San Diego, CA). The genotyping efficiency of each SNP exceeded 95.5%. Only individual DNA samples with genotyping efficiency ≥75% were retained for analysis. Blind duplicates were included in genotyping and were 100% concordant.
Statistical Analyses
Genotypic association was evaluated using the SNPGWA statistical package (www.phs.wfubmc.edu), which performs the two degrees of freedom global test of genotypic association in addition to individual genetic models including dominant, additive, recessive, and lack-of-fit to additivity. This is consistent with the Fisher’s protected least significant difference multiple comparisons procedure. Haplotype analysis was evaluated using PLINK (Purcell et al. 2007) for haplotype-specific and omnibus tests of association. LD between variants was determined using the Haploview program (Barrett et al. 2005) by evaluating variants in the African American samples.
Variants in the APOL1 gene have been shown to be powerfully associated with non-diabetic nephropathy in African Americans (Genovese et al. 2010) and their presence in both T2D-ESKD and non-diabetic nephropathy cases has the potential to confound evidence of association (Freedman et al. 2011). To minimize the potential influence of risk alleles at the APOL1 G1 and G2 risk variants (Genovese et al. 2010), each African American sample was genotyped for the two APOL1 G1 haplotype SNPs (rs73885319 [S342G] and rs60910145 [I384M]) and the G2 six base pair deletion (rs71785313) (Genovese et al. 2010); genotyping was performed using the iPLEX™ Sequenom MassARRAY platform (Sequenom; San Diego, CA). Data from this genotyping was used as a covariate in association analyses. Parenthetically we have shown that the APOL1 G1 and G2 risk alleles are very rare in European Americans (<0.33%) (Cooke et al. 2012) and therefore were not taken into account in European American analyses.
African American and European American data were analyzed for association separately and, when appropriate, were combined in a meta-analysis implementing the inverse variance weighted method in METAL (http://www.sph.umich.edu/csg/abecasis/metal/) to determine the overall association of each SNP with T2D-ESKD and all-cause ESKD.
Results
Clinical characteristics of study samples are shown in Table 1. On average, there were more females in all groups, with the exception of the African American non-T2D ESKD cohort. T2D-ESKD and non-T2D ESKD cases were older than controls, although age at T2D diagnosis was lower than the average age in control groups. On average, all participants were overweight or obese at the time of enrollment.
Table 1.
Clinical characteristics of study samples.
| African Americans |
European Americans |
||||
|---|---|---|---|---|---|
| T2D-ESRD | Non-T2D ESRD | Controls | T2D-ESRD | Controls | |
| n | 2172 | 1152 | 1721 | 568 | 897 |
| Female (%) | 57.5 | 43.4 | 54.9 | 50.4 | 63.2 |
| Age (years) | |||||
| at enrollment | 61.6 ± 10.7 | 54.6 ± 14.6 | 47.5 ± 12.4 | 66.0 ± 10.3 | 54.5 ± 15.2 |
| at T2D diagnosis | 41.2 ± 13.0 | --- | --- | 45.5 ± 13.7 | --- |
| Duration of diabetes (years) | 20.2 ± 10.7 | --- | --- | 20.5 ± 10.1 | --- |
| BMI (kg/m2) | 30.0 ± 0.1 | 27.2 ± 7.0 | 29.8 ± 7.23 | 29.5 ± 7.0 | 28.2 ± 5.5 |
Categorical data are expressed as percentage; continuous data as mean ± SD
Thirty-one SNPs from 19 genes met criteria for selection and were genotyped (Supplementary Table 1). Genes were selected based on prior evidence of association with ESKD or nephropathy; therefore, SNPs with P-values<0.05 were considered nominally associated. APOL3, C6orf167 (MMS22L), C6orf191, C12orf66, LIMK2, MYH9, OR2L13, OR2L8, OR2AK2, SASH1, SFI1, TMEM5, and UNC5C were selected from a prior GWAS of diabetic nephropathy in African Americans (McDonough et al. 2011). MYH9 was chosen based on its implication in non-diabetic nephropathy in various ethnic groups but most prominently in African Americans (Behar et al. ; Freedman et al. 2009b; Freedman et al. 2009c; Kao et al. 2008; Kopp et al. 2008; O’Seaghdha et al. 2011), prior to identification of the nearby APOL1 ESRD risk gene (Genovese et al. 2010), which was also selected for analysis. Advanced glycation end-products (AGEs), for which AGER is a receptor, have been implicated in diabetic complications (reviewed in (King and Loeken 2004)). ACACB was selected because a variant in this gene associated with diabetic nephropathy in Japanese and European Americans (Maeda et al. 2010). CNDP1 was selected because variants in this gene have been reported to influence glucose metabolism (Sauerhofer et al. 2007) and were associated with T2D-ESKD and diabetic nephropathy in European Americans and African Americans (Freedman et al. 2007; Janssen et al. 2005; McDonough et al. 2009); variants in CNDP2 have been implicated in T2D-ESKD in African Americans (McDonough et al. 2009).
Several analyses were performed given the various subjects groups: African American and European American, T2D-ESKD and non-T2D ESKD. In addition, in contrast to common non-coding variants which are conventionally thought to act through additive genetic effects, the impact of coding variants could be expressed in various ways, e.g. dominant, additive, or recessive models. Supplementary Figure 1 illustrates the progression of the study. The primary inferences were drawn from analysis of all African American samples together, all European American samples, and the combination of the two with subgroup analysis in African Americans, as appropriate to assess impact on etiology of ESKD, e.g. T2D-ESKD or non-T2D ESKD.
Table 2 lists all SNPs nominally associated (P<0.05) with all-cause ESKD in African Americans with their analysis presented in all-cause ESKD, T2D-ESKD, and non-T2D-ESKD. The best genetic model is reported for each SNP except where a lack-of-fit to additivity was observed. MAFs differed greatly between European Americans and African Americans, as shown in Supplementary Table 1. African American all-cause ESKD analyses identified seven associated SNPs in seven genes including OR2L8, OR2L13, C6orf167 (MMS22L), LIMK2, APOL3, APOL2, and APOL1 (P-values=5.4×10−4-0.037, OR=0.65-1.22). In all but two cases (rs61098917 in LIMK2 and rs7285167 in APOL2), the minor allele was associated with ESKD protection. Results for analysis in stratified T2D-ESKD and non-T2D-ESKD samples showed substantial differences in association suggesting preferential influence on one form of ESKD, e.g. rs4925583 in OR2L8. In addition, SNPs rs4478844 in OR2AK2 and rs3747154 in LIMK2 were nominally associated with T2D-ESKD and non-T2D-ESKD, respectively, but not with all-cause ESKD. Results for all SNPs in the African American populations are shown in Supplementary Tables 2-4.
Table 2.
Individual SNP analysis in diabetic, non-diabetic, and all-cause ESRD in African Americans.
| Variant Info |
All-Cause ESRD Cases (n= 3024) vs. Controls (n=1672) |
T2D-ESRD Cases (n= 1896) vs. Controls (n=1672) |
Non-T2D ESRD Cases n=1128) vs. Controls (n=1672) |
|||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SNP Position (hg19) |
Alleles (minor/ major)* |
Gene | MAF (cases/ controls) |
Best Model |
MAF (cases/ controls) |
Best Model |
MAF (cases/ controls) Cases |
Best Model |
||||||
| P | OR (95% CI) |
Model | P | OR (95% CI) |
Model | P | OR (95% CI) |
Model | ||||||
| rs4925583 1:248112809 |
G/A | OR2L8 | 0.32/0.36 | 0.014 | 0.89 (0.81-0.98) |
add | 0.33/0.36 | 0.11 | 0.92 (0.83-1.02) |
add | 0.31/0.36 | 1.8E-04 | 0.57 (0.43-0.77) |
rec |
| rs4478844 1:248129240 |
A/G | OR2AK2 | 0.16/0.18 | 0.15 | 0.92 (0.82-1.03) |
add | 0.16/0.18 | 0.044 | 0.86 (0.74-1.00) |
dom | 0.17/0.18 | 0.69 | 0.97 (0.83-1.13) |
add |
| rs74153072 1:248263495 |
G/T | OR2L13 | 0.19/0.19 | 0.037 | 0.65 (0.43-0.98) |
rec | 0.20/0.19 | 0.57 | 1.04 (0.92-1.17) |
add | 0.19/0.19 | 0.86 | 0.99 (0.84-1.16) |
add |
| rs9481410 6:97677118 |
G/A | MMS22L | 0.48/0.50 | 0.019 | 0.84 (0.73-0.97) |
dom | 0.48/0.50 | 0.017 | 0.89 (0.81-0.98) |
add | 0.49/0.50 | 0.18 | 0.92 (0.82-1.04) |
add |
| rs61098917 22:31668720 |
T/C | LIMK2 | 0.26/0.22 | 0.019 | 1.14 (1.02-1.26) |
add | 0.24/0.22 | 0.15 | 1.09 (0.97-1.22) |
add | 0.28/0.22 | 0.0030 | 1.29 (1.09-1.52) |
dom |
| rs3747154 22:31673116 |
G/A | LIMK2 | 0.05/0.04 | 0.49 | 1.08 (0.88-1.32) |
add | 0.04/0.04 | 0.26 | 0.87 (0.69-1.10) |
add | 0.06/0.04 | 0.0036 | 1.48 (1.14-1.93) |
dom |
| rs116147257 22:36537798 |
A/G | APOL3 | 0.04/0.05 | 9.4E- 04 |
0.69 (0.56-0.86) |
dom | 0.04/0.05 | 0.0013 | 0.67 (0.53-0.86) |
dom | 0.04/0.05 | 0.063 | 0.77 (0.58-1.01) |
add |
| rs7285167 22:36623920 |
A/G | APOL2 | 0.38/0.29 | 0.0023 | 1.22 (1.07-1.39) |
dom | 0.35/0.29 | 0.0066 | 1.21 (1.06-1.40) |
dom | 0.44/0.29 | 0.0092 | 1.26 (1.06-1.51) |
dom |
| rs2239785 22:36661330 |
A/G | APOL1 | 0.28/0.38 | 5.4E- 04 |
0.77 (0.67-0.90) |
dom | 0.31/0.38 | 5.0E-04 | 0.76 (0.65-0.89) |
dom | 0.23/0.38 | 0.025 | 0.80 (0.65-0.97) |
dom |
All analyses adjusted for percentage of African ancestry and APOL1 risk; best model reported unless SNP not associated in analysis, then additive model reported (add);
minor/major allele refers to African Americans
To determine if the SNPs contributed to association across ethnicity, the 31 SNPs were genotyped in a cohort of European Americans including 568 T2D-ESKD cases and 897 controls (Table 3). This analysis did not include an ability to capture non-T2D ESKD variants in European Americans. Four SNPs in four genes, OR2AK2 (rs4478844), OR2L13 (rs74153072), LIMK2 (rs3747154), and APOL2 (rs7285167), had evidence of association in European Americans in the same direction as in African Americans. In addition, a SNP in CNDP1 (rs73973908) was associated in European Americans but not in African Americans. Results for all SNPs in the European American population are shown in Supplementary Table 5.
Table 3.
Individual SNP analysis in European American T2D-ESRD.
| Variant Info |
Minor Allele Frequency |
T2D-ESRD Cases (n=568) vs. Controls (n=897) |
|||||||
|---|---|---|---|---|---|---|---|---|---|
| SNP | Chr | Position (hg19) |
Alleles (minor/major)* |
Gene | T2D-ESRD | Controls | Best Model |
||
| P | OR (95% CI) | Model | |||||||
| rs4925583 | 1 | 248112809 | G/A | OR2L8 | 0.94 | 0.95 | 0.066 | 0.74 (0.54-1.02) | add |
| rs4478844 | 1 | 248129240 | A/G | OR2AK2 | 0.65 | 0.65 | 0.0087 | 0.66 (0.48-0.90) | dom |
| rs74153072 | 1 | 248263495 | G/T | OR2L13 | 0.19 | 0.19 | 0.037 | 0.65 (0.43-0.98) | rec |
| rs9481410 | 6 | 97677118 | G/A | MMS22L | 0.27 | 0.24 | 0.077 | 1.17 (0.98-1.39) | add |
| rs73973908 | 18 | 72238472 | A/C | CNDP1 | 0.13 | 0.16 | 0.025 | 0.76 (0.60-0.97) | dom |
| rs61098917 | 22 | 31668720 | T/C | LIMK2 | 0.0062 | 0.0022 | 0.11 | 2.23 (0.80-6.25) | add |
| rs3747154 | 22 | 31673116 | G/A | LIMK2 | 0.011 | 0.0011 | 0.0010 | 6.43 (1.81-22.88) | dom |
| rs116147257 | 22 | 36537798 | A/G | APOL3 | 0.00090 | 0.0017 | 0.89 | 0.90 (0.23-3.56) | add |
| rs7285167 | 22 | 36623920 | A/G | APOL2 | 0.091 | 0.064 | 0.0065 | 1.47 (1.11-1.94) | add |
| rs2239785 | 22 | 36661330 | A/G | APOL1 | 0.79 | 0.80 | 0.61 | 0.95 (0.79-1.15) | add |
Analyses unadjusted; best model reported unless SNP not associated in analysis, then additive model reported (add);
minor/major allele refers to African Americans.
Meta-analysis of African Americans and European Americans examined the overall association of each SNP with T2D-ESKD (MetaPT2D-ESKD) and all-cause ESKD (MetaPN) (Table 4). Four SNPs were associated in both T2D-ESKD and all-cause ESKD analyses; including rs4925583 (MetaPT2D-ESKD=0.038, MetaPN=0.0051) in OR2L8, rs116147257 (MetaPT2D-ESKD=0.0014, MetaPN=7.2×10−4) in APOL3, rs7285167 (MetaPT2D-ESKD=0.0032, MetaPN=8.5×10−4) in APOL2, and rs2239785 (MetaPT2D-ESKD=0.0025, MetaPN=0.0023) in APOL1. rs2269529 in MYH9 was nominally associated in the T2D-ESKD meta-analysis (MetaPT2D-ESKD=0.048) and trended toward association with all-cause ESKD (MetaPN=0.053) but was not associated in individual cohorts. rs61098917 in LIMK2 was associated in the all-cause ESKD meta-analysis (MetaPN=0.0069) and also in African American non-T2D ESKD (P=0.0030) and all-cause ESKD (P=0.019).
Table 4.
Meta-analysis of SNPs in African Americans and European Americans.
| Variant Details |
T2D-ESRD only |
All Nephropathy |
||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| SNP | Chr | Location (hg19) |
Alleles (minor/major)* |
Gene | Meta P-value |
Heterogeneity P-value |
Odds Ratio | Meta P-value |
Heterogeneity P-value |
Odds Ratio |
| rs4925583 | 1 | 248112809 | G/A | OR2L8 | 0.038 | 0.21 | 0.90 | 0.0051 | 0.28 | 0.88 |
| rs74153218 | 1 | 248129195 | T/C | OR2AK2 | 0.99 | 0.97 | 1.00 | 0.57 | 0.89 | 1.09 |
| rs4478844 | 1 | 248129240 | A/G | OR2AK2 | 0.10 | 1.00 | 0.94 | 0.15 | 1.00 | 0.95 |
| rs74153072 | 1 | 248263495 | G/T | OR2L13 | 0.47 | 0.44 | 1.04 | 0.82 | 0.41 | 1.01 |
| rs34585936 | 4 | 96091414 | T/C | UNC5C | 0.15 | 0.49 | 1.35 | 0.14 | 0.52 | 1.35 |
| rs77170610 | 6 | 32150047 | T/C | AGER | 0.75 | 0.48 | 1.06 | 0.62 | 0.50 | 1.08 |
| rs74540092 | 6 | 97676810 | C/T | MMS22L | 0.38 | 0.89 | 1.27 | 0.23 | 0.96 | 1.35 |
| rs9481410 | 6 | 97677118 | G/A | MMS22L | 0.23 | 0.007 | 0.95 | 0.24 | 0.010 | 0.95 |
| rs9492393 | 6 | 130154667 | C/T | C6orf191 | 0.88 | 0.28 | 0.99 | 0.88 | 0.28 | 0.99 |
| rs61996289 | 6 | 148869636 | T/G | SASH1 | 0.60 | 0.67 | 0.92 | 0.32 | 0.61 | 0.87 |
| rs141536395 | 12 | 64202766 | G/A | TMEM5 | 0.21 | 1.00 | 1.22 | 0.14 | 1.00 | 1.25 |
| rs188114016 | 12 | 64587684 | G/C | C12orf66 | 0.53 | 0.94 | 0.91 | 0.54 | 0.95 | 0.92 |
| rs17848802 | 12 | 109634834 | G/A | ACACB | 0.74 | 0.71 | 0.94 | 0.81 | 0.85 | 0.96 |
| rs113576948 | 12 | 109687886 | C/G | ACACB | 0.29 | 0.69 | 1.36 | 0.33 | 0.73 | 1.31 |
| rs34916325 | 18 | 72178130 | A/G | CNDP2 | 0.92 | 0.42 | 1.01 | 0.58 | 0.45 | 1.05 |
| rs4263028 | 18 | 72228124 | A/G | CNDP1 | 0.58 | 0.65 | 1.06 | 0.42 | 0.67 | 1.08 |
| rs73973908 | 18 | 72238472 | A/C | CNDP1 | 0.29 | 0.06 | 0.94 | 0.61 | 0.032 | 0.98 |
| rs62621182 | 18 | 72244208 | A/G | CNDP1 | 0.99 | 0.54 | 1.00 | 0.55 | 0.46 | 0.96 |
| rs61098917 | 22 | 31668720 | T/C | LIMK2 | 0.10 | 0.18 | 1.10 | 0.0069 | 0.20 | 1.15 |
| rs3747154 | 22 | 31673116 | G/A | LIMK2 | 0.55 | 0.0043 | 0.93 | 0.23 | 0.012 | 1.13 |
| rs16989291 | 22 | 31971282 | C/T | SFI1 | 0.66 | 0.32 | 1.04 | 0.75 | 0.38 | 1.03 |
| var22_32007810 | 22 | 32007810 | A/G | SFI1 | 0.64 | 0.29 | 0.88 | 0.29 | 0.20 | 0.76 |
| rs116147257 | 22 | 36537798 | A/G | APOL3 | 0.0014 | 0.69 | 0.69 | 7.2E-04 | 0.72 | 0.70 |
| rs6000152 | 22 | 36538053 | A/G | APOL3 | 0.47 | 0.34 | 0.93 | 0.82 | 0.39 | 0.98 |
| rs79419411 | 22 | 36556729 | C/T | APOL3 | 0.64 | 0.31 | 0.96 | 0.70 | 0.32 | 0.97 |
| rs7285167 | 22 | 36623920 | A/G | APOL2 | 0.0032 | 0.087 | 1.18 | 8.5E-04 | 0.091 | 1.17 |
| rs2239785 | 22 | 36661330 | A/G | APOL1 | 0.0025 | 0.23 | 0.86 | 0.0023 | 0.31 | 0.87 |
| rs136175 | 22 | 36661566 | G/A | APOL1 | 0.24 | 1.00 | 1.14 | 0.61 | 0.16 | 0.96 |
| rs16996616 | 22 | 36661891 | A/G | APOL1 | 0.87 | 0.72 | 0.99 | 0.87 | 0.72 | 0.99 |
| rs2269529 | 22 | 36684354 | C/T | MYH9 | 0.048 | 0.74 | 0.87 | 0.053 | 0.67 | 0.88 |
| rs139134727 | 22 | 36685292 | A/G | MYH9 | 0.70 | 0.80 | 1.20 | 0.46 | 0.75 | 1.40 |
Fixed effects meta-analysis performed using METAL (http://www.sph.umich.edu/csg/abecasis/metal/), SE output presented.
minor/major allele refers to African Americans.
To extend these findings, we evaluated whether combining data from these exonic variants with known common variants would increase evidence for association between a specific genetic locus and ESKD. Table 5 lists two haplotype P-values: the omnibus P-value compares the overall distribution of haplotypes between cases and controls, while the risk haplotype P-value compares the frequency of the risk haplotype (i.e. the haplotype combination made up of the risk alleles for each SNP) between cases and controls. Supplementary Table 6 summarizes risk alleles, haplotype frequencies, and odds ratios in addition to P-values. For example, a common SNP in OR2L3 (rs10888287) was associated with T2D-ESKD (P-value=2.7×10−4) with three coding variants (rs4925583, rs4478844, rs74153072) possessing individual P-values ranging from 6.9×10−4 to 0.79. In haplotype analysis of the most strongly associated coding variant (rs4925583) and rs10888287, the resulting omnibus P-value was 2.69×10−4 and comparable to either individual SNP and the risk haplotype was nominally more strongly associated, P-value=6.2×10−5. Other analyses provide a range of results: addition of coding variants and haplotype analysis reduces the evidence of association (C6orf167; rs3822908/rs9481410) to stronger evidence for association (APOL1; rs16996381/rs2239785). In most cases, however, the combination of common and coding variant data does not appreciably improve evidence for association.
Table 5.
Haplotype analysis of loci associated in diabetic, non-diabetic, and all-cause ESRD in African Americans.
| Gene | Common Variant | Common Variant P-value | Coding Variant | Coding variant P-value |
Omnibus P-value | Risk Haplotype P-value |
|---|---|---|---|---|---|---|
| OR2L13 | rs10888287 | 2.7E-04 | rs4925583 | 6.9E-04 | 2.69E-04 | 6.2E-05 |
| rs4478844 | 0.030 | 0.0011 | 0.0027 | |||
| rs74153072 | 0.79 | 0.0019 | 0.20 | |||
| C6orf167 | rs3822908 | 1.0E-04 | rs9481410 | 0.049 | 0.013 | 0.13 |
| LIMK2 | rs2106294 | 2.9E-05 | rs61098917 | 0.0041 | 1.0E-05 | 3.8E-03 |
| rs4820043 | 3.3E-05 | rs3747157 | 0.15 | 9.0E-05 | 0.15 | |
| APOL3 | rs16996381 | 0.0083 | rs116147257 | 2.6E-04 | 2.3E-04 | 0.0047 |
| APOL2 | rs16996381 | 0.0083 | rs7285167 | 0.015 | 0.0081 | 0.0024 |
| APOL1 | rs16996381 | 0.0083 | rs2239785 | 7.5E-05 | 0.0081 | 4.6E-05 |
| MYH9 | rs735853 | 0.016 | rs2269529 | 0.36 | 0.040 | 0.014 |
Discussion
The purpose of this study was to assess the value of coding variants identified in exome sequencing studies for detecting association with ESKD susceptibility. This was accomplished by performing a locus-wide analysis of coding variants in genes previously associated with nephropathy in cohorts with different etiologies of renal disease. Assessing known or suspected ESKD genes is a logical first step in evaluating coding variants. With prior evidence of association with ESKD, it is more likely that a coding variant in these genes would contribute to ESKD risk. This approach facilitated comparison testing to ascertain the potential effect of each of the 31 SNPs. Analyses revealed nominal evidence of association with multiple SNPs. Individual coding variants were associated with ESRD, but, in the sample tested, the strength of association alone would not provide compelling proof of association unless the prior evidence of association was taken into consideration. While the effect size of individual, nominally associated coding SNPs was in general greater than that observed for common variants, the odds ratios are not dramatically higher (or lower). When combined with the low MAF of most coding variants, this results in, at best, nominal evidence of association. In addition, with the exception of a few loci, combining common and coding variant data added little to evidence of association.
Of the 31 SNPs in 19 genes, 10 showed nominal evidence (P<0.05) of association African Americans. SNPs in genes on chromosome 22 were notably represented. The importance of chromosome 22 in African American nephropathy has been established by various reports in non-diabetic (Behar et al. 2010; Freedman et al. 2009b; Freedman et al. 2010; Freedman et al. 2009c; Freedman et al. 2012; Genovese et al. 2010; Kao et al. 2008; Kopp et al. 2008; O’Seaghdha et al. 2011; Pattaro et al. 2009), T2D-associated (Cooke et al. 2012; Freedman et al. 2009a; McDonough et al. 2011), and type 1 diabetic nephropathy (Wessman et al. 2011). With the established importance of chromosome 22, many of the genes targeted in this study, including APOL3, APOL2, APOL1, LIMK2, and MYH9, were from this chromosome. Analyses conditioned on APOL1 G1 (rs73885319 and rs60910145) and G2 (rs71785313) variants (Genovese et al. 2010) minimized the influence of these alleles. This approach has been useful for identifying association signals in complex traits and disorders (Lango Allen et al. 2010; Ripke et al. 2011; Sklar et al. 2011; Yang et al. 2012). Accounting for APOL1 G1/G2 variants, coding variants in APOL3, APOL2, and APOL1 were associated with all-cause ESKD, T2D-ESKD, and non-T2D ESKD in African Americans with little correlation among variants (r2<0.28 for all comparisons).
We previously reported a common SNP in APOL3, rs16996381, associated with protection in all-cause ESKD in a GWAS of T2D-ESKD in African Americans (McDonough et al. 2011). Here the APOL3 coding SNP rs116147257, a missense (I220T) variant with MAF≈4.5% in African Americans, was also protective in African American and European American T2D-ESKD (Tables 2-3). This lends further support to a role for the APOL3 gene in nephropathy and suggests a more complex combination of alleles leading to risk or protection from ESKD in this region. Parenthetically, rs16996381 and rs116147257 have no evidence of correlation (r2=0.03). Further, a missense (C182R) SNP in APOL2 (rs7285167) was associated with risk in African American T2D-ESKD, non-T2D ESKD, and all-cause ESKD (Table 2), and in European American T2D-ESKD (Table 3). It was also significant in the meta-analyses of African American and European American T2D-ESKD (MetaP=0.0032) and all-cause ESKD (MetaP=8.5×10−4) (Table 4), and therefore appears to be associated with ESKD in both African Americans and European Americans.
APOL1 was also notable in these analyses. A missense (K150E; rs2239785) SNP in APOL1 was associated with protection in African American T2D-ESKD, non-T2D ESKD, and all-cause ESKD (Table 2), and in meta-analyses of T2D-ESKD and all-cause ESKD in African Americans and European Americans (Table 4). Based on observed P-values in the individual cohorts and the lack of association in European American T2D-ESKD, it appears that this SNP is an African American all-cause ESKD variant.
Two common SNPs in LIMK2 on chromosome 22, rs2106294 and rs4820043, were associated with protection in a GWAS of T2D-ESKD in African Americans (McDonough et al. 2011). In the analysis reported here, two SNPs in LIMK2, rs61098917 (intronic) and rs3747154 (R684Q), were associated with risk in African American non-T2D ESKD (Table 2). Further, rs61098917 was also associated with risk in African American all-cause ESKD (Table 2) and in the African American and European American all-cause ESKD meta-analysis (Table 4), while rs3747154 was associated with risk in European American T2D-ESKD (Table 3). rs61098917 and rs3747154 were not correlated with one another or with previously implicated SNPs (r2<0.015). rs61098917 and rs3747154 appeared to be African American non-T2D ESKD risk variants, and rs3747154 may also be a European American T2DESKD risk variant. Although a lower P-value and higher OR for risk were observed in European Americans (Table 4), risk allele frequencies were lower compared to African Americans (Table 2).
Several other SNPs had evidence of nominal association consistent with protection from nephropathy in African Americans. These included SNPs in the OR2L13/OR2L8/OR2AK2 region and in C6orf167 (MMS22L). SNPs in the olfactory receptor-encoding genes OR2L13, OR2L8, and OR2AK2, whose coding sequences overlap on chromosome 1, included rs4925583, rs4478844, and rs74153072, were associated with T2D-ESKD, non-T2D ESKD and/or all-cause ESKD in African Americans (Table 2). SNPs rs4478844 and rs74153072 were also associated and rs4925583 trended toward association (P=0.066) in European Americans (Table 3). There was moderate correlation between rs4925583 and rs4478844 (r2=0.37), but no correlation between either of these SNPs and rs74153072 (r2≤0.02). A common intronic SNP in this region, rs10888287, was associated with protection in an African American GWAS of T2D-ESKD (McDonough et al. 2011). The LD between this non-coding SNP and the coding SNPs reported here was nominal to moderate (r2≤0.60). The olfactory receptor gene family is large and the chromosomal organization is complex (Malnic et al. 2004). The coding sequence of OR2L13 overlaps OR2L8 and OR2AK2. The role of this class of genes in nephropathy requires further elucidation, but it does appear to represent an independent nephropathy locus.
Two additional missense SNPs associated with protection were located in C6orf167 (MMS22L) and CNDP1. rs9481410 (M564T) in C6orf167 (MMS22L) was associated in African American T2D-ESKD and all-cause ESKD (Table 2). A SNP in this gene, rs3822908, was associated with protection in T2D-ESKD and all-cause ESKD in the prior African American GWAS (McDonough et al. 2011); however, the LD between these SNPs was low (r2=0.13). In European American T2D-ESRD analyses, rs73973908 (N270H) in CNDP1 was associated (Table 3) but was not associated in analyses of or including African Americans. CNDP1 encodes secreted serum carnosinase that degrades carnosine (Teufel et al. 2003), a free oxygen radical scavenger with anti-glycating effects which inhibits the formation of AGEs (Boldyrev 2000; Hipkiss et al. 1998) and influences glucose metabolism (Sauerhofer et al. 2007). Variants in CNDP1 have previously been associated with diabetic nephropathy in Europeans (Janssen et al. 2005), European Americans (Freedman et al. 2007), and African Americans (McDonough et al. 2009).
In addition, we assessed whether the coding SNPs tested in this study added to evidence for association with ESKD in combination with previously identified GWAS SNPs (McDonough et al. 2011). Haplotype analyses in a subset of African American individuals (n=2488 all-cause ESKD cases, n=1561 controls) resulted in moderately stronger evidence for association in particular cases. For example, evaluating SNPs in LIMK2, rs4820043 (McDonough et al. 2011) and rs61098917, yielded a two-marker haplotype P=5.7×10−14, compared to individual P-values (rs4820043 P=3.8×10−12, rs61098917 P=4.2×10−6) in this subset of individuals. This suggests that the combination of common non-coding and coding SNPs will be useful, especially in a comprehensive genome-wide analysis.
A striking characteristic of the associated SNPs is the difference in MAF between African Americans and European Americans. Differences in allele frequencies are >16.9% for seven of 11 associated SNPs (difference in MAF for all associated SNPs 4.4-32.5%). This observation, in conjunction with the observation that many of the coding variants were protective, suggests the possibility that protective variants have arisen in African-origin populations to compensate for the ancillary health risks associated with the anti-trypanosomal APOL1 G1 and G2 alleles. While this is speculative, it bares additional investigation.
We appreciate that there are limitations to the current study. The number of SNPs that were tested was small and odds ratios of associated SNPs were not striking and did not provide dramatic evidence of association. However, a test of whether coding variants were associated with nephropathy is most easily tested in genes with a prior history of nephropathy association. Additionally, it is noteworthy that seven of the associated variants were predicted to be probably or possibly damaging by PolyPhen (http://genetics.bwh.harvard.edu/pph2/). The power to detect significant effects, afforded by the relatively large sample size (for studies of nephropathy) examined in this study (>5000 African Americans and >1450 European Americans), is a strength. In the combined African American sample we estimate that we have 80% power to detect an OR of 1.30 for a 5% MAF variant (additive model).
Coding variants lack an intrinsic likelihood that a specific model (e.g. dominant, additive, recessive) is likely to be more appropriate. Power for recessive models was limited and moreover, power to assess association in European Americans was limited. Investigation of SNPs in a large sample of African Americans with multiple etiologies of nephropathy allowed for the detection of variants associated with T2D-ESKD, non-T2D ESKD, and/or all-cause ESKD. As we have noted (Bowden and Freedman 2012) it remains unclear whether individual nephropathy genes contribute to multiple etiologies of disease. This is complicated further by the high frequency of the APOL1 G1 and G2 risk alleles in the African American population. Replication of four of the associated variants in a small European American cohort (in which the APOL1 G1/G2 risk variants are virtually absent) supports the case that several SNPs were indeed associated with ESKD.
In summary, coding variants in previously implicated nephropathy genes can be useful additions to genetic analyses of ESKD. This was particularly true in analysis of the APOL gene cluster on chromosome 22. Based on these data, studies of coding variants complement common variant analyses. It is notable that odds ratios of associated SNPs were not striking and did not provide dramatic evidence of association. Thus, genome-wide searches for coding variants influencing nephropathy risk are likely to be productive, but will also likely require sample sizes comparable to GWAS using common variants.
Supplementary Material
Acknowledgements
We wish to thank the patients, their relatives and staff of the Southeastern Kidney Council, Inc./ESRD Network 6 for their participation. This work was supported by National Institutes of Health grants R01 DK066358 (D.W.B.), R01 DK053591 (D.W.B.), R00 DK081350 (N.D.P.), R01 HL56266 (B.I.F.), R01 DK070941 (B.I.F.), R01DK 084149 (B.I.F.), and in part by the General Clinical Research Center of the Wake Forest School of Medicine Grant M01 RR07122. The authors would like to thank the NHLBI GO Exome Sequencing Project and its ongoing studies which produced and provided exome variant calls for comparison: the Lung GO Sequencing Project (HL102923), the WHI Sequencing Project (HL102924), the Broad GO Sequencing Project (HL102925), the Seattle GO Sequencing Project (HL102926) and the Heart GO Sequencing Project (HL103010).
The authors acknowledge the analytic assistance of Jianzhao Xu, BS, of the Center for Diabetes Research at Wake Forest School of Medicine, Winston-Salem, North Carolina.
Footnotes
No potential conflicts of interest relevant to this article were reported.
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