Quantitative genetics of renal function: tackling complexities of the eGFR phenotype in gene mapping studies

Variation in genes that regulate blood pressure are associated with glomerular filtration rate in Chinese

Chronic kidney disease (CKD) can be a consequence of diabetes, hypertension, immunologic disorders, and other exposures, as well as genetic factors that are still largely unknown. Glomerular filtration rate (GFR), which is widely used to measure kidney function, has a heritability ranging from 25% to 75%, but only 1.5% of this heritability is explained by genetic loci that have been identified to date. In this study we tested for associations between GFR and 234 SNPs in 26 genes from pathways of blood pressure regulation in 3,025 rural Chinese participants of the "Genetic Epidemiology Network of Salt Sensitivity" (GenSalt) study. We estimated GFR (eGFR) using baseline serum creatinine measurements obtained prior to dietary intervention. We identified significant associations between eGFR and 12 SNPs in 6 genes (ACE, ADD1, AGT, GRK4, HSD11B1, and SCNN1G). The cumulative effect of the protective alleles was an increase in mean eGFR of 4 mL/min per 1.73 m2, while the cumulative effect of the risk alleles was a decrease in mean eGFR of 3 mL/min per 1.73 m2. In addition, we identified a significant interaction between SNPs in CYP11B1 and ADRB2. We have identified common variants in genes from pathways that regulate blood pressure and influence kidney function as measured by eGFR, providing new insights into the genetic determinants of kidney function. Complex genetic effects on kidney function likely involve interactions among genes as we observed for CYP11B1 and ADRB2.

A genome-wide search for linkage of estimated glomerular filtration rate (eGFR) in the Family Investigation of Nephropathy and Diabetes (FIND)

Objective

Estimated glomerular filtration rate (eGFR), a measure of kidney function, is heritable, suggesting that genes influence renal function. Genes that influence eGFR have been identified through genome-wide association studies. However, family-based linkage approaches may identify loci that explain a larger proportion of the heritability. This study used genome-wide linkage and association scans to identify quantitative trait loci (QTL) that influence eGFR.

Methods

Genome-wide linkage and sparse association scans of eGFR were performed in families ascertained by probands with advanced diabetic nephropathy (DN) from the multi-ethnic Family Investigation of Nephropathy and Diabetes (FIND) study. This study included 954 African Americans (AA), 781 American Indians (AI), 614 European Americans (EA) and 1,611 Mexican Americans (MA). A total of 3,960 FIND participants were genotyped for 6,000 single nucleotide polymorphisms (SNPs) using the Illumina Linkage IVb panel. GFR was estimated by the Modification of Diet in Renal Disease (MDRD) formula.

Results

The non-parametric linkage analysis, accounting for the effects of diabetes duration and BMI, identified the strongest evidence for linkage of eGFR on chromosome 20q11 (log of the odds [LOD] = 3.34; P = 4.4×10⁻⁵) in MA and chromosome 15q12 (LOD = 2.84; P = 1.5×10⁻⁴) in EA. In all subjects, the strongest linkage signal for eGFR was detected on chromosome 10p12 (P = 5.5×10⁻⁴) at 44 cM near marker rs1339048. A subsequent association scan in both ancestry-specific groups and the entire population identified several SNPs significantly associated with eGFR across the genome.

Conclusion

The present study describes the localization of QTL influencing eGFR on 20q11 in MA, 15q21 in EA and 10p12 in the combined ethnic groups participating in the FIND study. Identification of causal genes/variants influencing eGFR, within these linkage and association loci, will open new avenues for functional analyses and development of novel diagnostic markers for DN.

Susceptibility gene search for nephropathy and related traits in Mexican-Americans

The rising global epidemic of diabetic nephropathy (DN) will likely lead to increase in the prevalence of cardiovascular morbidity and mortality posing a serious burden for public health care. Despite greater understanding of the etiology of diabetes and the development of novel treatment strategies to control blood glucose levels, the prevalence and incidence rate of DN is increasing especially in minority populations including Mexican-Americans. Mexican-Americans with type 2 diabetes (T2DM) are three times more likely to develop microalbuminuria, and four times more likely to develop clinical proteinuria compared to non-Hispanic whites. Furthermore, Mexican-Americans have a sixfold increased risk of developing renal failure secondary to T2DM compared to Caucasians. Prevention and better treatment of DN should be a high priority for both health-care organizations and society at large. Pathogenesis of DN is multi-factorial. Familial clustering of DN-related traits in MAs show that DN and related traits are heritable and that genes play a susceptibility role. While, there has been some progress in identifying genes which when mutated influence an individual's risk, major gene(s) responsible for DN are yet to be identified. Knowledge of the genetic causes of DN is essential for elucidation of its mechanisms, and for adequate classification, prognosis, and treatment. Self-identification and collaboration among researchers with suitable genomic and clinical data for meta-analyses in Mexican-Americans is critical for progress in replicating/identifying DN risk genes in this population. This paper reviews the approaches and recent efforts made to identify genetic variants contributing to risk for DN and related phenotypes in the Mexican-American population.

Meta-analysis of genome-wide linkage scans for renal function traits

BACKGROUND

Several genome scans have explored the linkage of chronic kidney disease phenotypes to chromosomic regions with disparate results. Genome scan meta-analysis (GSMA) is a quantitative method to synthesize linkage results from independent studies and assess their concordance.

METHODS

We searched PubMed to identify genome linkage analyses of renal function traits in humans, such as estimated glomerular filtration rate (GFR), albuminuria, serum creatinine concentration and creatinine clearance. We contacted authors for numerical data and extracted information from individual studies. We applied the GSMA nonparametric approach to combine results across 14 linkage studies for GFR, 11 linkage studies for albumin creatinine ratio, 11 linkage studies for serum creatinine and 4 linkage studies for creatinine clearance.

RESULTS

No chromosomal region reached genome-wide statistical significance in the main analysis which included all scans under each phenotype; however, regions on Chromosomes 7, 10 and 16 reached suggestive significance for linkage to two or more phenotypes. Subgroup analyses by disease status or ethnicity did not yield additional information.

CONCLUSIONS

While heterogeneity across populations, methodologies and study designs likely explain this lack of agreement, it is possible that linkage scan methodologies lack the resolution for investigating complex traits. Combining family-based linkage studies with genome-wide association studies may be a powerful approach to detect private mutations contributing to complex renal phenotypes.

Renal function and genetic variation in dopamine D(1) receptor: is the case strong enough?

Polymorphisms in the genes involved in the dopaminergic system have been implicated in susceptibility to hypertension. A new study by Fung et al. takes a closer look at the association of genetic variants in the dopamine D(1) receptor gene (DRD1) with blood pressure and renal parameters. Although the study does not confirm an association with blood pressure, it suggests a new link between a common variant in the 5'-untranslated region of the DRD1 gene and low glomerular filtration rate.

Unravelling the genetic basis of renal diseases; from single gene to multifactorial disorders

Chronic kidney disease is common with up to 5% of the adult population reported to have an estimated glomerular filtration rate of < 60 ml/min/1.73 m(2). A large number of pathogenic mutations have been identified that are responsible for 'single gene' renal disorders, such as autosomal dominant polycystic kidney disease and X-linked Alport syndrome. These single gene disorders account for < 15% of the burden of end-stage renal disease that requires dialysis or kidney transplantation. It has proved more difficult to identify the genetic susceptibility underlying common, complex, multifactorial kidney conditions, such as diabetic nephropathy and hypertensive nephrosclerosis. This review describes success to date and explores strategies currently employed in defining the genetic basis for a number of renal disorders. The complementary use of linkage studies, candidate gene and genome-wide association analyses are described and a collation of renal genetic resources highlighted.