Identification of chromosome 3q28 and ALPK1 as susceptibility loci for chronic kidney disease in Japanese individuals by a genome-wide association study
- Yoshiji Yamada1,
- Tamotsu Nishida1,
- Sahoko Ichihara1,
- Kimihiko Kato1,2,
- Tetsuo Fujimaki3,
- Mitsutoshi Oguri4,
- Hideki Horibe5,
- Tetsuro Yoshida6,
- Sachiro Watanabe7,
- Kei Satoh8,
- Yukitoshi Aoyagi9,
- Michio Fukuda10,
- Motoji Sawabe11
- 1Department of Human Functional Genomics, Life Science Research Center, Mie University, Tsu, Mie, Japan
- 2Meitoh Hospital, Nagoya, Aichi, Japan
- 3Department of Cardiovascular Medicine, Inabe General Hospital, Inabe, Mie, Japan
- 4Department of Cardiology, Japanese Red Cross Nagoya First Hospital, Nagoya, Aichi, Japan
- 5Department of Cardiovascular Medicine, Gifu Prefectural Tajimi Hospital, Tajimi, Gifu, Japan
- 6Department of Cardiovascular Medicine, Onga Nakama Medical Association Onga Hospital, Onga, Fukuoka, Japan
- 7Department of Cardiology, Gifu Prefectural General Medical Center, Gifu, Gifu, Japan
- 8Department of Vascular Biology, Institute of Brain Science, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori, Japan
- 9Department of Genomics for Longevity, Tokyo Metropolitan Institute of Gerontology, Tokyo, Tokyo, Japan
- 10Department of Cardio-Renal Medicine and Hypertension, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, Japan
- 11Section of Molecular Pathology, Graduate School of Health Care Sciences, Tokyo Medical and Dental University, Tokyo, Tokyo, Japan
- Correspondence to Professor Yoshiji Yamada, Department of Human Functional Genomics, Life Science Research Center, Mie University, 1577 Kurima-machiya, Tsu, Mie 514-8507, Japan;
- Received 3 January 2013
- Revised 21 February 2013
- Accepted 10 March 2013
- Published Online First 28 March 2013
Background Although genome-wide association studies (GWASs) have implicated several genes in the predisposition to chronic kidney disease (CKD) in Caucasian or African American populations, the genes that confer susceptibility to CKD in Asian populations remain to be identified definitively. We performed a GWAS to identify genetic variants that confer susceptibility to CKD in Japanese individuals.
Methods 3851 Japanese individuals from three independent subject panels were examined. Subject panels A, B, and C comprised 252, 910, and 190 individuals with CKD and 249, 838, and 1412 controls, respectively. A GWAS for CKD was performed in subject panel A.
Results Five single nucleotide polymorphisms (SNPs) at chromosome 3q28, ALPK1, FAM78B, and UMODL1 were significantly (false discovery rate<0.05) associated with CKD by the GWAS. The relation of these five SNPs and of an additional 22 SNPs at these loci to CKD was examined in subject panel B, revealing that rs9846911 at 3q28 was significantly associated with CKD in all individuals and that rs2074381 and rs2074380 in ALPK1 were associated with CKD in individuals with diabetes mellitus. These three SNPs were further examined in subject panel C, revealing that rs2074381 and rs2074380 were significantly associated with CKD. For subject panels B and C combined, rs9846911 was significantly associated with CKD in all individuals and rs2074381 and rs2074380 were associated with CKD in diabetic individuals.
Conclusions Chromosome 3q28 may be a susceptibility locus for CKD in Japanese individuals, and ALPK1 may be a susceptibility gene for CKD in such individuals with diabetes mellitus.
Chronic kidney disease (CKD) is a global public health problem, with affected individuals being at increased risk not only for end stage renal disease (ESRD) but also for a poor cardiovascular outcome and premature death.1–3 Disease prevention is an important strategy for reducing the overall burden of CKD and ESRD, and the identification of markers for disease risk is key both for risk prediction and for potential intervention to reduce the chance of future cardiovascular events.4
In addition to conventional risk factors such as diabetes mellitus and hypertension, recent studies have shown the importance of genetic factors and of interactions between multiple genes and environmental factors in the development of CKD.5 ,6 Although recent genome-wide association studies (GWASs) have implicated several loci and genes in renal function or predisposition to CKD or ESRD in Caucasian7–11 or African American12 ,13 populations, or in renal function related traits in East Asian populations,14 the genes that contribute to genetic susceptibility to CKD in Japanese individuals remain to be identified definitively.
We have now performed a GWAS and two replication studies for CKD that included a total of 3851 Japanese individuals. Our aim was to identify genetic variants that confer susceptibility to CKD in Japanese individuals and thereby to contribute to the personalised prevention of this condition.
The overall strategy of the study is presented in the online supplementary figure S1.
Estimated glomerular filtration rate and CKD
The glomerular filtration rate was estimated with the use of the simplified prediction equation derived from the modified version of that described in the Modification of Diet in Renal Disease Study, as proposed by the Japanese Society of Nephrology15: estimated glomerular filtration rate (eGFR) (ml min−1 1.73 m−2)=194×(age (years))−0.287×(serum creatinine (mg/dl))−1.094×(0.739 if female). The National Kidney Foundation–Kidney Disease Outcomes Quality Initiative guidelines recommend a diagnosis of CKD if eGFR is <60 ml min−1 1.73 m−2.4 Non-linear relations between GFR and the risk of adverse events, such as death, cardiovascular events, and hospitalisation, have been demonstrated, with an increased risk being associated with an eGFR of <60 ml min−1 1.73 m−2 and the risk notably rising further when values fall below 45 ml min−1 1.73 m−2.16 In addition, the rate of GFR decline was significantly higher in Japanese individuals with an initial value of <50 ml min−1 1.73 m−2, suggestive of a poor outcome for such individuals.17 Given that eGFR is a continuous trait, we adopted the criteria of an eGFR <50 ml min−1 1.73 m−2 for CKD (patients with ESRD were included) and an eGFR ≥90 ml min−1 1.73 m−2 for controls in order to exclude individuals with borderline CKD in the present study.
A total of 3851 Japanese individuals (1352 subjects with CKD, 2499 controls) from three independent subject panels was examined (table 1). Subject panel A comprised 501 individuals; the 252 subjects with CKD were selected from people who either visited the outpatient clinics of participating hospitals, or were admitted to these hospitals, between October 2002 and March 2009, and the 249 controls were selected from people who visited these hospitals for an annual health checkup. The selection criteria for subject panel A were as follows: (1) an eGFR for subjects with CKD <40 ml min−1 1.73 m−2 (actual range 2.8–39.8 ml min−1 1.73 m−2); (2) an eGFR for controls ≥90 ml min−1 1.73 m−2 (actual range 90–327.2 ml min−1 1.73 m−2); (3) an age of control individuals ≥64 years (actual range 64–89 years); (4) no renal disease for control individuals; and (5) no or only minor health problems for control individuals. Although some control individuals had hypertension, diabetes mellitus, or hypercholesterolaemia, they had no complications related to these conditions. Given the small number of subjects in panel A, we selected middle-aged individuals with severe CKD and elderly controls for the GWAS in order to accentuate effects of genetic factors on the development of CKD.
Subject panel B comprised 1748 individuals (910 subjects with CKD, 838 controls) who either visited outpatient clinics of participating hospitals, or were admitted to these hospitals, between October 2002 and December 2011. The selection criteria for subject panel B were as follows: (1) an eGFR for subjects with CKD <50 ml min−1 1.73 m−2 (actual range 2.5–49.9 ml min−1 1.73 m−2); (2) an eGFR for controls ≥90 ml min−1 1.73 m−2 (actual range 90–584.9 ml min−1 1.73 m−2); (3) no renal disease for control individuals; and (4) no or only minor health problems for control individuals.
Subject panel C comprised 1602 community dwelling individuals (190 subjects with CKD, 1412 controls) who were recruited to a population based cohort study in Inabe or Nakanojo. The selection criteria for subject panel C were as follows: (1) an eGFR for subjects with CKD <50 ml min−1 1.73 m−2 (actual range 13.0–49.9 ml min−1 1.73 m−2); (2) an eGFR for controls ≥90 ml min−1 1.73 m−2 (actual range 90–156.7 ml min−1 1.73 m−2); (3) no renal disease for control individuals; and (4) no or only minor health problems for control individuals. Given that subject panel C comprised community dwelling individuals, the number of subjects with CKD was small and they were elderly. The eGFR of 103 age matched (mean age 72.6 years) control individuals (99.1±8.8 ml min−1 1.73 m−2) was significantly (p<1.0×10−40) greater than that of the CKD subjects (42.1±7.8 ml min−1 1.73 m−2).
The relation of single nucleotide polymorphisms (SNPs) to CKD was also examined among subjects with type 2 diabetes mellitus or hypertension. Type 2 diabetes was defined according to the criteria accepted by the World Health Organization and described previously18 ,19 (fasting plasma glucose concentration ≥6.93 mmol/l, blood glycosylated haemoglobin (haemoglobin A1c) content ≥6.5%, or taking antidiabetes medication). Individuals with type 1 diabetes mellitus, maturity onset diabetes of the young, or other endocrinologic diseases were excluded from the analysis. For the examination of CKD associated with diabetes mellitus, controls were defined as individuals who had type 2 diabetes but did not have CKD. Hypertension was defined as a systolic blood pressure ≥140 mm Hg, a diastolic blood pressure ≥90 mm Hg, or taking antihypertensive medication. For the examination of CKD associated with hypertension, controls were defined as individuals who had hypertension but did not have CKD.
The study protocol complied with the Declaration of Helsinki and was approved by the Committees on the Ethics of Human Research of Mie University Graduate School of Medicine, Hirosaki University Graduate School of Medicine, Tokyo Metropolitan Institute of Gerontology, Nagoya City University Graduate School of Medicine, and participating hospitals. Written informed consent was obtained from all subjects.
A GWAS for CKD was performed in Japanese subject panel A (252 subjects with CKD, 249 controls) with the use of the HumanCytoSNP-12 array (Illumina, San Diego, California, USA), which includes 297 707 SNPs distributed throughout the entire genome. Genotyping data with a call rate of <98% were discarded. The mean call rate for the remaining data was 99.7%. We examined the relation of allele frequencies of each SNP to CKD with the χ2 test. A quantile–quantile plot for p values of allele frequencies in the GWAS for CKD is shown in online supplementary figure S2. To compensate for multiple comparisons of genotypes with CKD, we calculated the false discovery rate (FDR) by the method of Benjamini and Hochberg20 and adopted the criterion of an FDR of <0.05 for statistical significance of association. The genotype data in the GWAS were examined for population stratification by principal components analysis with the EIGENSTRAT method.21 The p values and FDRs corrected for population stratification by principal components analysis are shown in table 2, and the two dimensional display of the samples examined by such analysis is shown in online supplementary figure S3. We eliminated SNPs with an FDR corrected for population stratification by principal components analysis of ≥0.05. We also discarded SNPs with a minor allele frequency of <0.05 or those whose genotype distributions deviated significantly (FDR<0.05) from Hardy–Weinberg equilibrium in combined case and control data. We eliminated 66 SNPs by these procedures and finally selected the remaining five SNPs (table 2) for the further studies with subject panels B and C.
Genotyping of SNPs
Venous blood (7 ml) was collected into tubes containing 50 mmol/l EDTA (disodium salt), peripheral blood leucocytes were isolated, and genomic DNA was extracted from these cells with a DNA extraction kit (Genomix, Talent, Trieste, Italy). Genotypes of SNPs in subject panels B and C were determined at G&G Science (Fukushima, Japan) by the multiplex bead based Luminex assay, a method that combines the PCR and sequence specific oligonucleotide probes with suspension array technology (Luminex, Austin, Texas, USA). Genotyping involved PCR amplification, hybridisation, streptavidin-phycoerythrin reaction, and measurement of fluorescence. In brief, target DNA was amplified by PCR with 5′-biotin-labelled primers that are highly specific for the targeted gene sequences. After denaturation at 95°C, amplified DNA was allowed to hybridise to cDNA probes coupled to microbeads. The hybridised PCR products were allowed to react with streptavidin-phycoerythrin, and the fluorescence intensity of phycoerythrin associated with the biotin labelled PCR products on the microbeads was measured by the Luminex apparatus. Primers, probes, and other conditions for genotyping of the 27 SNPs examined in subject panel B are shown in online supplementary table S1. Genotyping methodology was described in detail previously.22 The reproducibility of genotyping by suspension array technology was also described previously.23
Human kidneys obtained postmortem from individuals with diabetic glomerulosclerosis or normal renal function were subjected to immunohistochemical analysis. Formalin fixed and paraffin embedded sections were depleted of paraffin, hydrated, immersed in 0.01 mol/l citrate buffer (pH 6.0), and heated for 10 min in a pressure cooker. Staining was performed with the use of an EnVision+ Rabbit/HRP kit (Dako, Glostrup, Denmark). Rabbit polyclonal antibodies to ALPK1 (ab60161; Abcam, Cambridge, UK) were applied at a dilution of 1:50.
Transfection, immunoblot analysis, and quantitative reverse transcription PCR analysis
HEK293T cells were transfected for 48 h with the expression vector pFLAG-CMV-2 (Sigma, St Louis, Missouri, USA) containing human ALPK1 cDNA (or with the empty vector alone) with the use of the Lipofectamine 2000 reagent (Invitrogen, Carlsbad, California, USA). The cells were then lysed by the addition of 2× Laemmli sample buffer and heating at 100°C, and were subjected to immunoblot analysis with mouse polyclonal antibodies to human ALPK1 (ab89140, Abcam) at a dilution of 1:1000 or with mouse monoclonal antibodies to the FLAG epitope (M2, Sigma) at a dilution of 1:10 000. Immune complexes were detected with enhanced chemiluminescence reagents (GE Healthcare Bio-Science, Piscataway, New Jersey, USA). Total RNA was also isolated from the transfected cells with the use of an RNeasy kit (Qiagen, Düsseldorf, Germany) and was subjected to reverse transcription (RT) and real-time PCR analysis with primers and probes specific for cDNAs corresponding to 84 human genes related to nephrotoxicity (RT2 Profiler PCR array; SABiosciences, Frederick, Maryland, USA).
Quantitative data were compared between subjects with CKD and controls by the unpaired Student's t test. Categorical data were compared with the χ2 test. Allele frequencies were estimated by the gene counting method, and the χ2 test was used to identify departure from Hardy–Weinberg equilibrium. Allele frequencies of SNPs were compared between subjects with CKD and controls by the χ2 test. Multivariable logistic regression analysis was performed with CKD as a dependent variable and independent variables including age, sex (0, woman; 1, man), body mass index (BMI), smoking status (0, non-smoker; 1, current or former smoker), the prevalence of hypertension, diabetes mellitus, or hypercholesterolaemia (0, no history of these conditions; 1, positive history), and genotype of each SNP. Each genotype was assessed according to dominant (0, wild-type homozygote; 1, heterozygote and variant homozygote), recessive (0, wild-type homozygote and heterozygote; 1, variant homozygote), and additive ((0, 0), wild-type homozygote; (1, 0), heterozygote; (0, 1), variant homozygote) genetic models, and the p value, odds ratio, and 95% confidence interval were calculated. Additive models included the additive 1 (heterozygotes vs wild-type homozygotes) and additive 2 (variant homozygotes vs wild-type homozygotes) models, which were analysed simultaneously with a single statistical model. To compensate for multiple comparisons of genotypes with CKD, we calculated the FDR20 and adopted the criterion of an FDR of <0.05 for statistical significance of association. For other analyses, a p value of <0.05 was considered statistically significant. Statistical tests were performed with JMP Genomics V.6.0 software (SAS Institute, Cary, North Carolina, USA). Linkage disequilibrium and haplotype analyses were performed with SNPAlyze V.6 software (Dynacom, Yokohama, Japan).
Characteristics of subjects
The characteristics of the subjects enrolled in the study are shown in table 1. For subject panel A, the frequency of men, BMI, and the prevalence of hypertension, diabetes mellitus, and hypercholesterolaemia were greater, whereas age was lower (given that elderly controls were selected) in subjects with CKD than in controls. For subject panel B, age, the frequency of men, and the prevalence of smoking, hypertension, diabetes mellitus, and hypercholesterolaemia were greater in subjects with CKD than in controls. For subject panel C, age, the frequency of men, BMI, and the prevalence of smoking, hypertension, diabetes mellitus, and hypercholesterolaemia were greater in subjects with CKD than in controls.
GWAS for CKD in subject panel A
The GWAS for CKD in subject panel A revealed that five SNPs were significantly (FDR<0.05) associated with CKD (table 2). The relations of these SNPs to CKD were also significant after correction by principal components analysis for population stratification with the EIGENSTRAT method.
Selection of SNPs in FAM78B, ALPK1, and UMODL1 and analysis of subject panel B
We searched the dbSNP database (NCBI) to find SNPs located in the 5′ untranslated region or non-synonymous SNPs (each with a minor allele frequency ≥0.05 in Japanese individuals) for FAM78B, ALPK1, and UMODL1. We thereby selected 22 SNPs in addition to the five SNPs isolated by the GWAS (see online supplementary table S2). Examination of the relation of these 27 SNPs to CKD in subject panel B revealed that rs9846911 at chromosome 3q28 was significantly (FDR <0.05) associated with CKD (table 3, see online supplementary table S2). Given that diabetes mellitus and hypertension are important risk factors for CKD, the relation of SNPs to CKD was also examined in individuals with diabetes mellitus or hypertension. For individuals with diabetes mellitus, rs2074381 and rs2074380 in ALPK1 as well as rs9846911 were significantly associated with CKD, whereas rs9846911 was significantly associated with CKD in individuals with hypertension (table 3). The genotype distributions of these SNPs were in Hardy–Weinberg equilibrium among subjects with CKD and controls in all groups (table 3).
Association of SNPs with CKD in subject panel C
We next examined the relation of rs9846911 at 3q28 and of rs2074381 and rs2074380 in ALPK1 to CKD in subject panel C. Both SNPs in ALPK1 were significantly associated with CKD among all individuals in subject panel C (see online supplementary table S3). The genotype distributions of all three SNPs were in Hardy–Weinberg equilibrium among subjects with CKD and controls in all groups (see online supplementary table S3).
Association of three SNPs with CKD in combined subject panels B and C
Given that the allele frequencies of the three selected SNPs were similar in subject panels B and C, we combined genotype data from both subject panels. Analysis of subjects in combined subject panels B and C revealed that rs9846911 at 3q28 was significantly associated with CKD (table 4). For individuals with diabetes mellitus, rs2074381 and rs2074380 in ALPK1 as well as rs9846911 were significantly associated with CKD. For individuals with hypertension, rs9846911 was also significantly associated with CKD (table 4). The genotype distributions of these SNPs were in Hardy–Weinberg equilibrium among subjects with CKD and controls in all groups (table 4). The relation of the three SNPs to eGFR is shown in online supplementary table S4, with eGFR being found to differ significantly (p<0.05) between genotypes (dominant model) for each SNP.
Multivariable logistic regression analysis of SNPs and CKD
The relation of the three SNPs at 3q28 or in ALPK1 to CKD in combined subject panels B and C was also examined by multivariable logistic regression analysis with adjustment for age, sex, BMI, smoking status, and the prevalence of hypertension, diabetes mellitus, or hypercholesterolaemia (see online supplementary table S5). The rs9846911 SNP at 3q28 was significantly associated with CKD in dominant and recessive models, with the minor G allele being protective against this condition. For individuals with diabetes mellitus, rs2074381 and rs2074380 in ALPK1 as well as rs9846911 were significantly associated with CKD in a dominant model, with the minor allele of each SNP being protective. For individuals with hypertension, rs9846911 was significantly associated with CKD in dominant and recessive models, with the minor G allele again being protective.
Given that rs2074381 and rs2074380 of ALPK1 were in linkage disequilibrium (standard linkage disequilibrium coefficient (r2)=0.9454, p=9.0×10−214) in combined subject panels B and C, we performed haplotype analysis for these SNPs. Such analysis revealed that the frequency of the major haplotype, A (rs2074381)–G (rs2074380), was significantly higher, whereas that of the minor haplotype G–A was significantly lower, in subjects with CKD than in controls among individuals with diabetes mellitus in combined subject panels B and C (see online supplementary table S6).
Combined genotype analysis
We performed multivariable logistic regression analysis of combined genotypes for the three SNPs rs9846911, rs2074381, and rs2074380 to assess the genetic risk for CKD among individuals with diabetes mellitus in combined subject panels B and C. Combined genotype analysis revealed that the highest odds ratio of 4.2 was obtained with the combined genotype of AA for rs9846911, AA for rs2074381, and GG for rs2074380 compared with the combined genotype of AG or GG for rs9846911, AG or GG for rs2074381, and GA or AA for rs2074380 (see online supplementary table S7).
Immunohistochemical analysis of ALPK1
We performed immunohistochemical staining for ALPK1 in human kidney specimens (figure 1). Renal tubular epithelial cells were positive for ALPK1 in both normal kidneys (figure 1A) and those affected by diabetic glomerulosclerosis (figure 1B), but the abundance of ALPK1 in these cells was greater for the diseased kidneys than for normal kidneys. The atrophic renal tubules and urinary casts associated with diabetic glomerulosclerosis were also strongly positive for ALPK1 (figure 1B).
Effect of overexpression of ALPK1 on expression of genes related to nephrotoxicity
Given that the abundance of ALPK1 in renal tubular epithelial cells was increased in individuals with diabetic glomerulosclerosis compared with those with normal kidneys, we examined the effect of overexpression of ALPK1 on mRNA abundance for 84 genes related to nephrotoxicity. The amount of ALPK1 was notably increased after transfection of HEK293T cells with pFLAG-CMV-2 containing human ALPK1 cDNA (figure 2A). RT and real-time PCR analysis revealed that overexpression of ALPK1 resulted in a pronounced increase in the expression of solute carrier family 22, member 1 (SLC22A1) and cystatin C (CST3) genes (figure 2B).
We have shown that the rs9846911 SNP at chromosome 3q28 was significantly associated with CKD in Japanese individuals, with the minor G allele being protective against this condition. We also found that the rs2074381 and rs2074380 SNPs of ALPK1 at chromosome 4q25 were significantly associated with CKD in individuals with diabetes mellitus, with the minor G and A alleles, respectively, being protective. Combined genotype analysis of these three SNPs revealed that the largest odds ratio for the high risk genotype was 4.2 compared with the low risk genotype.
The rs9846911 SNP is located in a non-gene region at 3q28 that is situated downstream from the genes for receptor transporter protein 4 (RTP4, ∼130 kbp), somatostatin (SST, ∼170 kbp), receptor transporter protein 2 (RTP2, ∼200 kbp), and B cell CLL/lymphoma 6 (BCL6, ∼220 kbp) as well as upstream from the mannan binding lectin serine peptidase 1 gene (MASP1, ∼210 kbp). Given the presence of a large linkage disequilibrium block in this region, it is possible that rs9846911 is in linkage disequilibrium with other polymorphisms in the nearby genes that are actually responsible for the development of CKD. The functional relevance of the association of rs9846911 with the pathogenesis of CKD thus remains unclear.
ALPK1 (α-kinase 1) is implicated in the sorting of proteins in apical transport vesicles or the trans-Golgi network in Madin-Darby canine kidney cells, suggesting that the protein plays a role in exocytic transport to the apical plasma membrane in epithelial cells.24 Evidence suggests that it may act synergistically with monosodium urate monohydrate crystals to promote the production of proinflammatory cytokines through the activation of nuclear factor–κB (NF-κB) and mitogen activated protein kinase (ERK1/2 and p38) signalling in cultured HEK293 cells,25 indicating that ALPK1 may contribute to the inflammatory process associated with the development of gout. Our immunohistochemical analysis showed that ALPK1 is abundant in the atrophic renal tubules and urinary casts of individuals with diabetic glomerulosclerosis. These previous and our present observations thus suggest that ALPK1 may contribute to chronic inflammation of the kidney, although it remains to be determined whether ALPK1 actually plays a role in the development of diabetic glomerulosclerosis. The functional relevance of rs2074381 and rs2074380 in ALPK1 to the pathogenesis of CKD also remains unclear.
Overexpression of ALPK1 resulted in upregulation of the expression of SLC22A1 and CST3 in cultured HEK293T cells. SLC22A1 is a major organic cation transporter in the kidney, liver, intestine, and other organs that contribute to the elimination of endogenous small organic cations as well as a wide array of drugs and environmental toxins.26 CST3 is a potent endogenous inhibitor of the cysteine proteases that are present in a variety of human fluids and secretions, and are implicated in various biological processes such as degradation of cellular proteins and regulation of proenzymes and prohormones. It is also thought to contribute to other cellular functions, such as regulation of the phagocytic activity and chemotactic response of polymorphonuclear neutrophils as well as upregulation of nitric oxide release from activated macrophages.27 The plasma concentration of CST3 serves as a measure of GFR and may be a predictive marker for the risk of cardiovascular events and death as well as CKD.28 Although SLC22A1 and CST3 may play important roles in renal excretion and tissue remodelling, respectively, the functional relevance of these proteins to the pathogenesis of CKD remains to be elucidated.
We did not detect loci or genes previously implicated in CKD by GWASs in Caucasian,7–11 African American,12 ,13 or East Asian14 populations. We checked the p values in our GWAS for SNPs identified in the previous GWASs.7–14 Given the differences in GWAS platforms, however, genotype data for many of these SNPs were not available in our study. We observed that rs1260326 at GCKR9 ,10 ,13 was related (p=0.0137) to CKD in subject panel A. Conversely, neither 3q28 nor ALPK1 was identified as a susceptibility locus for CKD or renal function related traits in these previous GWASs.7–14 Although the reason for these differences remains unclear, they might be attributable to ethnic differences7–13 or to selection of study subjects.14 A lack of statistical power to detect association in the initial GWAS of our study might also be responsible. In addition, the genes previously identified as susceptibility loci for diabetic nephropathy in Japanese individuals29–31 were not related to CKD in our GWAS with subject panel A. Although the reason for this discrepancy also remains unclear, it may be attributable to the small population sizes for initial GWASs in the previous (94 cases and 94 controls29–31) and present (252 cases and 249 controls) studies, to the difference in GWAS platforms between the previous (56 648 SNPs29 or 81 315 SNPs30 ,31) and present (297 707 SNPs of the HumanCytoSNP-12 array) studies, or to the difference in statistical significance levels between the previous (p<0.0129–31) and present (FDR<0.05) studies.
There are several limitations to the present study. (1) Given that the study subjects comprised only Japanese individuals, validation of our findings will be required in other ethnic groups. (2) We were not able to obtain information on the pathological cause of CKD in a substantial proportion of the subjects with this condition. Such information can be obtained by detailed clinical examination, including renal biopsy, but such diagnostic procedures are not considered feasible for a genetic epidemiological study. (3) Given the small size of the study population in subject panel A, the statistical power of the initial GWAS was not optimal. (4) Given that quantitative data for urinary protein in the study subjects were not available, the relation of the three identified SNPs to the ratio of urinary protein to creatinine could not be examined. We also did not perform a GWAS with eGFR as a continuous trait. (5) The molecular mechanisms underlying the effects of SNPs identified in the present study on the development of CKD have not been determined.
In conclusion, our present results suggest that 3q28 may be a susceptibility locus for CKD in Japanese individuals, and that ALPK1 may be a susceptibility gene for CKD in such individuals with diabetes mellitus. Determination of genotypes for the identified SNPs may prove informative for assessment of the genetic risk for CKD in Japanese.
Contributors YY had substantial contributions to conception and design, acquisition of data, analysis and interpretation of data, drafting the article, and final approval of the version to be published. TN, SI, and MS had substantial contributions to acquisition of data, analysis and interpretation of data, revising the article critically for important intellectual content, and final approval of the version to be published. KK, TF, MO, HH, TY, SW, KS, YA, and MF had substantial contributions to acquisition of data, revising the article critically for important intellectual content, and final approval of the version to be published.
Funding This work was supported by a Grant-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science, and Technology of Japan (no. 24590746 to YY) and by Research Grants from the Japan Health Foundation and Okasan Kato Culture Promotion Foundation (to YY).
Competing interests None.
Patient consent Obtained.
Ethics approval The Committees on the Ethics of Human Research of Mie University Graduate School of Medicine, Hirosaki University Graduate School of Medicine, Tokyo Metropolitan Institute of Gerontology, Nagoya City University Graduate School of Medicine, and participating hospitals.
Provenance and peer review Not commissioned; externally peer reviewed.