Differential effects of MYH9 and APOL1 risk variants on FRMD3 association with diabetic ESRD in African Americans

Section on Nephrology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.
PLoS Genetics (Impact Factor: 7.53). 06/2011; 7(6):e1002150. DOI: 10.1371/journal.pgen.1002150
Source: PubMed


Single nucleotide polymorphisms (SNPs) in MYH9 and APOL1 on chromosome 22 (c22) are powerfully associated with non-diabetic end-stage renal disease (ESRD) in African Americans (AAs). Many AAs diagnosed with type 2 diabetic nephropathy (T2DN) have non-diabetic kidney disease, potentially masking detection of DN genes. Therefore, genome-wide association analyses were performed using the Affymetrix SNP Array 6.0 in 966 AA with T2DN and 1,032 non-diabetic, non-nephropathy (NDNN) controls, with and without adjustment for c22 nephropathy risk variants. No associations were seen between FRMD3 SNPs and T2DN before adjusting for c22 variants. However, logistic regression analysis revealed seven FRMD3 SNPs significantly interacting with MYH9-a finding replicated in 640 additional AA T2DN cases and 683 NDNN controls. Contrasting all 1,592 T2DN cases with all 1,671 NDNN controls, FRMD3 SNPs appeared to interact with the MYH9 E1 haplotype (e.g., rs942280 interaction p-value = 9.3E⁻⁷ additive; odds ratio [OR] 0.67). FRMD3 alleles were associated with increased risk of T2DN only in subjects lacking two MYH9 E1 risk haplotypes (rs942280 OR = 1.28), not in MYH9 E1 risk allele homozygotes (rs942280 OR = 0.80; homogeneity p-value = 4.3E⁻⁴). Effects were weaker stratifying on APOL1. FRMD3 SNPS were associated with T2DN, not type 2 diabetes per se, comparing AAs with T2DN to those with diabetes lacking nephropathy. T2DN-associated FRMD3 SNPs were detectable in AAs only after accounting for MYH9, with differential effects for APOL1. These analyses reveal a role for FRMD3 in AA T2DN susceptibility and accounting for c22 nephropathy risk variants can assist in detecting DN susceptibility genes.

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    • "Both groups found that African-American glomerulosclerosis correlates more strongly with the G1 and G2 alleles of APOL1, which lies immediately centromeric to MYH9 [12], [13]. When APOL1 G1 and G2 alleles are accounted for, the strength of the correlation between MYH9 SNPs and African-American kidney disease is either significantly reduced [13], [14], or effectively eliminated [12] due to linkage between APOL1 and MYH9. In addition, analysis of the worldwide distribution of MYH9 polymorphisms demonstrated that the high allele frequency of the MYH9 ”risk haplotype” among African-Americans and West Africans could be accounted for by linkage with a nearby site of selection, such as within APOL1 [15]. "
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    ABSTRACT: Background: Among African-Americans, genome wide association revealed a strong correlation between the G1 and G2 alleles of APOL1 (apolipoproteinL1, also called trypanolytic factor) and kidney diseases including focal and segmental glomerulosclerosis, HIV-associated nephropathy and hypertensive nephrosclerosis. In the prevailing hypothesis, heterozygous APOL1 G1 and G2 alleles increase resistance against Trypanosoma that cause African sleeping sickness, resulting in positive selection of these alleles, but when homozygous the G1 and G2 alleles predispose to glomerulosclerosis. While efforts are underway to screen patients for G1 and G2 alleles and to better understand "APOL1 glomerulopathy," no data prove that these APOL1 sequence variants cause glomerulosclerosis. G1 and G2 correlate best with glomerulosclerosis as recessive alleles, which suggests a loss of function mutation for which proof of causality is commonly tested with homozygous null alleles. This test cannot be performed in rodents as the APOL gene cluster evolved only in primates. However, there is a homozygous APOL1 null human being who lives in a village in rural India. This individual and his family offer a unique opportunity to test causality between APOL1 null alleles and glomerulosclerosis. Methods and findings: We obtained clinical data, blood and urine from this APOL1 null patient and 50 related villagers. Based on measurements of blood pressure, BUN, creatinine, albuminuria, genotyping and immunoblotting, this APOL1 null individual does not have glomerulosclerosis, nor do his relatives who carry APOL1 null alleles. Conclusions: This small study cannot provide definitive conclusions but the absence of glomerulosclerosis in this unique population is consistent with the possibility that African-American glomerulosclerosis is caused, not by loss of APOL1 function, but by other mechanisms including a subtle gain of function or by the "genetic hitchhiking" of deleterious mutations in a gene linked to APOL1 G1 and G2.
    PLoS ONE 12/2012; 7(12):e51546. DOI:10.1371/journal.pone.0051546 · 3.23 Impact Factor
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    • "Freedman et al [11] proposed that the association between MYH9 and diabetes associated ESRD could have resulted from MYH9 causing susceptibility to type 2 diabetes. Later the authors showed MYH9 polymorphisms specifically the E-1 haplotype to modulate the genetic effect of FERM domain-containing protein 3 (FRMD3) for diabetes susceptibility [30]. However, FRMD3 alleles were not associated with increased risk of type 2 diabetes in subjects carrying MYH9 E-1 risk alleles. "
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    ABSTRACT: Though single nucleotide polymorphisms (SNPs) in the non-muscle myosin gene (MYH9) have been reported to explain most of the excess risk of nondiabetic chronic kidney disease (CKD), in African-Americans, some studies have also shown associations with diabetic end-stage renal disease. We investigated the association of MYH9 SNPs with renal traits in a mixed-ancestry South African population prone to diabetes. Three SNPs known to be associated with CKD (rs4821480, rs5756152 and rs12107) were genotyped using Taqman assay in 716 adults (198 with diabetes) from the Bellville-South community, Cape Town. Glomerular filtration rate was estimated (eGFR) and urinary albumin/creatinine ratio (ACR) assessed. Multivariable regressions were used to relate the SNPs with renal traits. Mean age was 53.6 years, with the expected differences observed in characteristics by diabetic status. Significant associations were found between rs575152 and serum creatinine, and eGFR in the total population, and in diabetic participants (all p≤0.003), but not in non-diabetics (all p≥0.16), with significant interactions by diabetes status (interaction-p≤0.009). The association with ACR was borderline in diabetic participants (p = 0.05) and non-significant in non-diabetics (p = 0.85), with significant interaction (interaction p = 0.02). rs12107 was associated with fasting-, 2-hour glucose and HbA1c in diabetic participants only (interaction-p≤0.003), but not with renal traits. MYH9 SNPs were associated with renal traits only in diabetic participants in this population. Our findings and other studies suggest that MYH9 may have a broader genetic risk effect on kidney diseases.
    PLoS ONE 12/2012; 7(12):e52529. DOI:10.1371/journal.pone.0052529 · 3.23 Impact Factor
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    ABSTRACT: Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs. This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list.
    BMC Genomics 07/2011; 12(1):344. DOI:10.1186/1471-2164-12-344 · 3.99 Impact Factor
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