Literature DB >> 31534799

Novel Haplotype Indicator for End-Stage Renal Disease Progression among Saudi Patients.

Cyril Cyrus1, Shahanas Chathoth1, Chittibabu Vatte1, Nafie Alrubaish2, Othman Almuhanna2, J Francis Borgio3, Samir Al-Mueilo2, Fahd Al Muhanna2, Amein K Al Ali1.   

Abstract

BACKGROUND: End-stage renal disease (ESRD) is the result of hypertensive nephrosclerosis and chronic glomerular diseases and is associated with high morbidity and mortality. There are strong heritable components in the manifestation of the disease with a genetic predisposition to renal disorders, including focal segmental glomerulosclerosis and arterionephrosclerosis. Recent studies in genetics have examined modifiable risk factors that contribute to renal disease, and this has provided a deep insight into progressive kidney disease. Single-nucleotide polymorphisms at the proximity of SHROOM3, CST3, SLC7A9, and MYH9 genes have been associated with an increased risk of developing CKD and ESRD.
METHODS: A total of 160 CKD patients and 189 control subjects of Saudi origin participated in the study. Eight polymorphisms (SHROOM3-rs9992101, rs17319721; SLC7A9-rs4805834; MYH9-rs4821480, rs4821481, rs2032487, rs3752462; CST3-rs13038305) were genotyped using TaqMan assay, and the haplotype analysis was done using the HaploView 4.2 software.
RESULTS: Haplotype analysis revealed a novel haplotype "E6"-GTTT to be associated significantly with an increased risk for ESRD (p=0.0001) and CKD (p=0.03).
CONCLUSION: CKD is often silent until symptomatic uremia during the advanced stages of the disease. The newly identified haplotype will help recognize patients at risk for a rapid progression of CKD to ESRD. Accurate detection and mapping of the genetic variants facilitates improved risk stratification and development of improved and targeted therapeutic management for CKD.

Entities:  

Year:  2019        PMID: 31534799      PMCID: PMC6724424          DOI: 10.1155/2019/1095215

Source DB:  PubMed          Journal:  Int J Nephrol


1. Introduction

End-stage renal disease (ESRD) is commonly caused by hypertensive nephrosclerosis and chronic glomerular diseases [1] although a causative link between nephrosclerosis and hypertension is yet to be established [2]. Studies have examined modifiable risk factors that contribute to CKD. However, there are strong heritable components in the manifestation of the disease [3, 4], with the vast majority of individuals suffering from comorbid conditions, such as hypertension or diabetes [5, 6]. Since the advent of genome-wide association studies (GWAS), many novel loci associated with common human diseases have been identified [7], including CKD [3, 8–10]. A genetic polymorphism in shroom family member 3 (SHROOM3) has been identified as a CKD susceptibility locus through GWAS. SHROOM3 is a regulator of epithelial cellular arrangement and planar remodeling [11], which contributes to glomerular filtration barrier integrity [12]. Many studies have suggested that SHROOM3 plays an important role in mammalian kidney development and human kidney disease through estimated GFR (eGFR). One of these CKD-associated SHROOM3 variants, rs17319721, has been shown to impact cis-expression and renal allograft fibrosis [13]. Genetic polymorphisms in solute carrier family 7-member 9 (SLC7A9) gene, an amino acid transporter in renal proximal tubule cells, cause cystinuria [14], showing an association with GFR [3, 15], and have been identified as a risk factor for CKD patients of European ancestry [8]. Variants of cystatin C (CST3) have been also shown to impact altered eGFR and kidney disease [16]. Polymorphisms in myosin heavy chain 9 (MYH9) gene on chromosome 22 have been shown to be associated with a risk for focal segmental glomerulosclerosis (FSGS), HIV-associated nephropathy CKD with admixed nondiabetic kidney disease, hypertension-associated ESRD, and nondiabetic etiologies of ESRD [17-20]. The MYH9 risk polymorphisms are common among African Americans, contributing approximately 40–45% of all ESRD and 70% of nondiabetic ESRD [21]. The United States Renal Data System 2016 [22] reported the prevalence of ESRD to be 2,067 per million with an incidence rate of 370/million/year in the country. Genetic underpinnings of pediatric renal diseases, such as congenital and infantile nephrotic syndromes, are significantly higher in the Kingdom of Saudi Arabia (KSA) than in the Western world [23]. The prevalence of ESRD in KSA has exhibited a rapid increase in the past decades resulting in a rate that exceeds those seen in European and American populations [24]. The incidence and prevalence of CKD in the KSA is estimated to be approximately 1.72 million, equating to about 6% of the population. Out of these, only 7.1% are aware of their disease status, and this unawareness often results in poorer outcomes in such patients [25]. Furthermore, there is a sharp annual increase in the rate of CKD patients who develop ESRD, and this accounts for 2.21% deaths annually [24]. The prevalence of diabetic nephropathy among adult ESRD patients is 42.5% with a mortality rate of 18.6% compared to 6.9% of nondiabetic patients. While ethnicity is thought to play a large role in CKD genetics, very few genotyping studies of established CKD associations have been performed to date in Saudi Arabia and the surrounding regions. Our earlier study [26] highlighted the association of the eight SNPs in these four genetic regions and proposed a statistically significant method of predicting the CKD using FGF23, vitamin D3 level, and MYH9 genotypes [26]. Haplotypes represent a combination of genetic determinants along a single chromosome that are either preserved intact or separated by recombination over time. Haplotypes are commonly used in research to identify a disease-conferring gene or locus. Presently, much interest surrounds the use of genetic association studies, which have an advisedly more powerful study design than the linkage- or family-based studies in localizing susceptibility loci for common diseases that confer moderate risk [27]. Here, we present the haplotype association of these SNPs in 160 Saudi CKD and 189 non-CKD subjects from KSA towards the CKD progression risk assessment.

2. Materials and Methods

2.1. Study Population

The study included 160 Saudi CKD patients reporting to the Department of Nephrology at the King Fahd Hospital of the University, Al Khobar. Stringent inclusion criteria for both, cases and controls, were followed due to the high prevalence rate of CKD in the Saudi population. Patients with a history of any phosphate wasting disorder, including tumor-induced osteomalacia (TIO), X-linked hypophosphatemia (XLH), autosomal dominant hypophosphatemic rickets (ADHR), and untreated primary hyperthyroidism, and those undergoing renal replacement therapy were excluded from the study. Controls consisted of 189 healthy subjects of Saudi origin without evidence of renal disorders (serum creatinine <1.4 and <1.2 mg/dl in men and women, respectively). This study was approved by the Ethical Committee of the Imam Abdulrahman Bin Faisal University and conducted according to the Declaration of Helsinki. Signed written informed consent was obtained from all participants.

2.2. Genotyping Assay

DNA was isolated from the blood of 349 individuals using QIAamp DNA Mini Kit (Qiagen, USA) as per the manufacturer's instructions. Genotyping analysis was performed by ABI TaqMan SNP genotyping assays on 160 CKD patients and 189 controls. Allele-specific TaqMan® PCR technology is a highly sensitive assay and was performed using ABI 7500 Fast real-time PCR. Disease-associated SNPs selected from published articles, namely, rs9992101, rs17319721 (SHROOM3), rs4805834 (SLC7A9), rs4821480, rs4821481, rs2032487, rs3752462 (MYH9), and rs13038305 (CST3), were included. An additional 100 coronary artery disease patients with hypertension were genotyped for the MYH9 (rs4821480, rs4821481, rs2032487, and rs3752462) SNPs.

2.3. E Haplotyping

MYH9 haplotypes spanning 12–23 introns were reconstructed by 4 tagging SNPs. The haplotypes comprised the four SNP loci of the MYH9 gene in the order rs4821480 (T/g), rs4821481 (T/c), rs2032487 (C/t), and rs3752462 (C/t). The 4 SNPs were genotyped, and the haplotype blocks were determined using the HaploView 4.2 software that assigned haplotypes into chromosome-specific blocks based on the partition-ligation approach through EM algorithm [28]. To identify the nonrandom association of the eight SNPs by estimates of linkage disequilibrium (LD), each pair of SNPs was computed using the standard D-prime method. Patient population was further stratified into cohorts as CKD (eGFR > 15) and ESRD (eGFR < 15) to assess the significance of the haplotype variations.

2.4. Statistical Analysis

SPSS version 19 (Chicago, Illinois) was used to complete the statistical analysis. Mutation status was classified as positive or negative qualitatively. The genotype frequencies were tested for Hardy–Weinberg equilibrium among the control subjects.

3. Results

The present study investigated 160 CKD cases, in which 85 were males and 75 were females, with a mean age of 47.68 ± 17.27 years. The baseline characteristics of the study participants are shown in Supplementary . TaqMan analysis for genetic variants rs9992101, rs17319721 (SHROOM3), rs4805834 (SLC7A9), rs4821480, rs4821481, rs2032487, and rs3752462 (MYH9), and rs13038305 (CST3) was carried out for all samples. The control group was consistent with Hardy–Weinberg equilibrium for all SNPs. The distribution of the analyzed genotype polymorphisms was reported in our previous study [26]. The HaploView analysis results are represented in Figure 1. Tables 1 and 2 indicate the frequency of various MYH9 E and SHROOM3 haplotypes and their association, respectively. A new haplotype “E6”-GTTT is revealed to be significantly associated with the patient cohort (p=0.03), stratified CKD cohort (p=0.002), and ESRD cohort (p=0.0001). The common haplotype GTTC (E4) (p=0.0009) was also found to be associated with CKD (Table 1). On further stratification, E6 haplotype was found to be strongly associated with ESRD (p=0.0001) in ESRD vs. control and in CKD vs. ESRD (p=0.04) analysis.
Figure 1

Linkage disequilibrium (LD) analysis. LD patterns between the two SHROOM and four MYH9 SNPs in CKD patients vs. control cohort. The pairwise correlation between the SNPs were measured as r and are shown (×100) in each diamond. Coordinates are according to the NCBI build dbSNP 144 (r107). (a) Control vs. patients. (b) CKD vs. ESRD. (c) Control vs. CKD. (d) Control vs ESRD. (e) Control vs. CAD. (f) ESRD vs. CAD.

Table 1

Frequency of MYH9 E haplotypes compared between stratified groups such as CKD, ESRD, and CAD.

GroupsHaplotypeFrequencyChi square p value
Control vs. patientsTTTC0.431.0750.2998
TTTT0.271.4610.2268
GCCT0.230.3390.5603
GTTC0.0310.979 9 × 10 −4
TCCT0.0200.9923
GTTT0.014.663 0.0308
TTT0.75.295 0.0214
GCC0.240.3910.532
GTT0.0415.934 6.6 × 10 −5
TCC0.0200.9896

Control vs. CKDTTTC0.431.7180.19
TTTT0.281.6250.2024
GCCT0.242.6130.106
GTTC0.029.492 0.0021
TCCT0.020.070.7919
TTT0.77.108 0.0077
GCC0.252.5840.1079
GTT0.0310.934 9 × 10 −4
TCC0.020.0670.7954

CAD vs. ESRDTTTC0.4180.0090.9256
TTTT0.2693.6320.0567
GCCT0.2280.5510.4581
GTTC0.0388.051 0.0045
GTTT0.0286.615 0.0101
TCCT0.0150.460.4975

Control vs. ESRDTTTC0.440.2940.5876
TTTT0.272.9680.0849
GCCT0.220.0840.7723
GTTC0.0315.431 8.6 × 10 −5
TCCT0.020.0220.8828
GTTT0.0214.495 1 × 10 −4
TTT0.715.181 0.0228
GCC0.220.060.8066
GTT0.0530.498 3.34 × 10 −5
TCC0.020.0210.8838

CKD vs. ESRDTTTC0.40.5170.4723
GCCT0.252.5420.1108
TTTT0.230.260.6104
GTTC0.060.4940.4821
GTTT0.034.217 0.04
TCCT0.020.0080.9302
TTT0.630.0820.7747
GCC0.262.4420.1181
GTT0.093.3290.0681
TCC0.020.0070.9338

CAD vs. ControlTTTC0.4360.5330.4656
TTTT0.2980.2140.644
GCCT0.2280.3690.5435
TCCT0.0180.9330.3342
GTTC0.0110.1540.6946
Table 2

Frequency of SHROOM3 haplotypes compared between patient stratified by CKD, ESRD, and control cohorts.

GroupsHaplotypeFrequencyChi square p value
Control vs. patientsGG0.690.5070.4765
AA0.241.5250.2168
GA0.040.0350.8512
AG0.031.910.1669

Control vs. CKDGG0.690.5630.4531
AA0.242.0980.1475
GA0.040.0020.963
AG0.032.3830.1227

Control vs. ESRDGG0.690.8240.3639
AA0.230.1550.6939
GA0.051.9980.1575
AG0.040.0520.8203

CKD vs. ESRDGG0.660.0140.9052
AA0.270.8070.369
GA0.051.490.2222
AG0.021.5140.2186
To validate the new E6 haplotype, an additional 100 CAD patients with hypertension were genotyped for the MYH9 (rs4821480, rs4821481, rs2032487, and rs3752462) SNPs. Haplotype analysis revealed that the new haplotype was insignificant in the CAD patients. Also, the novel E6 haplotype was still found to be significantly associated (p=0.010) when ESRD was compared to the CAD cohort (Table 1).

4. Discussion

CKD is becoming an important health issue worldwide and a major cause for morbidity and mortality. Genetic searches for vital markers of CKD are essential to identify individuals who are at risk for ESRD. Numerous genes have been shown to be associated with CKD. SHROOM3, a regulator of epithelial cellular arrangement contributes to glomerular filtration barrier integrity while, CST3 which is involved in creatinine and cystatin synthesis, is strongly associated with multiple kidney-related traits. The SLC7A9 gene, which is expressed in renal proximal tubule cells, was shown to be strongly associated with the markers of kidney function, creatinine, and eGFR. MYH9 gene encodes a protein which is expressed in the glomerular podocyte [26]. MYH9 gene mutations result in nephritis to varying degrees in Epstein and Fechtner syndromes [21]. MYH9 SNPs and haplotypes are associated with a risk for T2D and non-T2D nephropathy, lupus nephritis, hypertensive nephropathy, and FSGS [17, 18, 20, 29–32]. The haplotype analysis of this study shows more combinatorial importance for the MYH9 gene region than SNPs. Oleksyk et al. [33] reported that the E1 haplotype of the MYH9 gene region, prominent in sub-Saharan Africa, is probably involved in the increased risk of developing CKD by increasing glomerulosclerosis and proteinuria through activation of nephritis by the deregulation of podocyte function and not by immunological mechanisms. In the present study, the E1 (GCCT) haplotype lacked any association towards CKD or ESRD, contradictory to the findings of Colares et al. [34]. The rare E5 (GCTC) is the only other haplotype carrying the C allele at rs4821481, which was noted in only two of the human genome diversity project populations, with frequencies of 0.02 in Mandenka, a West African ethnic group, and 0.01 in Palestinians [33]. Kopp et al. [18] reported the E2 haplotype prominent in the European, Middle Eastern, and South and Central Asian populations to be protective against renal disease, and Tavira et al. [35] reported the same protective effect in a Spanish cohort. The E2 (TTTC) and E3 (TTTT) haplotypes lacked an association in the present study. Interestingly, the haplotype frequencies of the present study were divergent from those reported from other populations [33]. The E4 and E6 haplotypes were found to be significantly associated with an increased risk of CKD and ESRD, respectively. Even in the stratified groups, ESRD (eGFR < 15 mL/min/1.73 m2) and CKD (eGFR > 15 mL/min/1.73 m2), the E4 (GTTC) was associated with an increased risk of CKD, although the novel haplotype GTTT (p = 0.0001) was found to be only associated with ESRD. The SNPs rs9992101 and rs17319721 located in the SHROOM3 gene on chromosome 4q21 are closely associated with CKD [8], and the former is in high linkage disequilibrium (LD) with rs17319721. The rs17319721 (A) allele is associated with increased SHROOM3 transcription and is therefore associated with an increased glomerular filtration rate, thereby increasing the risk for CKD [3]. Both these SNPs and their haplotypes were not associated with a risk of CKD in the present study.

5. Conclusion

CKD is often silent until the advanced stages of the disorder. Thus, many individuals remain unaware until symptomatic uremia is detected, and they begin to suffer from renal ailments. The newly identified haplotype will help identify the patients at risk for quicker progression of CKD towards ESRD. This study will further our understanding of the biological mechanisms of kidney function by identifying loci which may potentially influence metabolic renal functions.
  34 in total

1.  Haploview: analysis and visualization of LD and haplotype maps.

Authors:  J C Barrett; B Fry; J Maller; M J Daly
Journal:  Bioinformatics       Date:  2004-08-05       Impact factor: 6.937

Review 2.  Definition and clinical importance of haplotypes.

Authors:  Dana C Crawford; Deborah A Nickerson
Journal:  Annu Rev Med       Date:  2005       Impact factor: 13.739

3.  MYH9 is a major-effect risk gene for focal segmental glomerulosclerosis.

Authors:  Jeffrey B Kopp; Michael W Smith; George W Nelson; Randall C Johnson; Barry I Freedman; Donald W Bowden; Taras Oleksyk; Louise M McKenzie; Hiroshi Kajiyama; Tejinder S Ahuja; Jeffrey S Berns; William Briggs; Monique E Cho; Richard A Dart; Paul L Kimmel; Stephen M Korbet; Donna M Michel; Michele H Mokrzycki; Jeffrey R Schelling; Eric Simon; Howard Trachtman; David Vlahov; Cheryl A Winkler
Journal:  Nat Genet       Date:  2008-09-14       Impact factor: 38.330

4.  Polymorphisms in the non-muscle myosin heavy chain 9 gene (MYH9) are strongly associated with end-stage renal disease historically attributed to hypertension in African Americans.

Authors:  Barry I Freedman; Pamela J Hicks; Meredith A Bostrom; Mary E Cunningham; Yongmei Liu; Jasmin Divers; Jeffrey B Kopp; Cheryl A Winkler; George W Nelson; Carl D Langefeld; Donald W Bowden
Journal:  Kidney Int       Date:  2009-01-28       Impact factor: 10.612

Review 5.  Cystinuria.

Authors:  Aditya Mattoo; David S Goldfarb
Journal:  Semin Nephrol       Date:  2008-03       Impact factor: 5.299

6.  The association of the MYH9 gene and kidney outcomes in American Indians: the Strong Heart Family Study.

Authors:  Nora Franceschini; V Saroja Voruganti; Karin Haack; Laura Almasy; Sandy Laston; Harald H H Goring; Jason G Umans; Elisa T Lee; Lyle G Best; Richard R Fabsitz; Jean W MacCluer; Barbara V Howard; Kari E North; Shelley A Cole
Journal:  Hum Genet       Date:  2010-03       Impact factor: 4.132

7.  MYH9 is associated with nondiabetic end-stage renal disease in African Americans.

Authors:  W H Linda Kao; Michael J Klag; Lucy A Meoni; David Reich; Yvette Berthier-Schaad; Man Li; Josef Coresh; Nick Patterson; Arti Tandon; Neil R Powe; Nancy E Fink; John H Sadler; Matthew R Weir; Hanna E Abboud; Sharon G Adler; Jasmin Divers; Sudha K Iyengar; Barry I Freedman; Paul L Kimmel; William C Knowler; Orly F Kohn; Kristopher Kramp; David J Leehey; Susanne B Nicholas; Madeleine V Pahl; Jeffrey R Schelling; John R Sedor; Denyse Thornley-Brown; Cheryl A Winkler; Michael W Smith; Rulan S Parekh
Journal:  Nat Genet       Date:  2008-09-14       Impact factor: 38.330

8.  Shroom3-mediated recruitment of Rho kinases to the apical cell junctions regulates epithelial and neuroepithelial planar remodeling.

Authors:  Tamako Nishimura; Masatoshi Takeichi
Journal:  Development       Date:  2008-03-13       Impact factor: 6.868

9.  Polymorphisms in the nonmuscle myosin heavy chain 9 gene (MYH9) are associated with albuminuria in hypertensive African Americans: the HyperGEN study.

Authors:  Barry I Freedman; Jeffrey B Kopp; Cheryl A Winkler; George W Nelson; D C Rao; John H Eckfeldt; Mark F Leppert; Pamela J Hicks; Jasmin Divers; Carl D Langefeld; Steven C Hunt
Journal:  Am J Nephrol       Date:  2009-01-20       Impact factor: 3.754

10.  Prevalence and risk factors of chronic kidney disease in the Thai adult population: Thai SEEK study.

Authors:  Atiporn Ingsathit; Ammarin Thakkinstian; Amnart Chaiprasert; Pornpen Sangthawan; Pongsathorn Gojaseni; Kriwiporn Kiattisunthorn; Leena Ongaiyooth; Somlak Vanavanan; Dhavee Sirivongs; Prapaipim Thirakhupt; Bharati Mittal; Ajay K Singh
Journal:  Nephrol Dial Transplant       Date:  2009-12-27       Impact factor: 5.992

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