Kidney disease affects 19 million adults in the United States 1. Chronic kidney disease (CKD) is associated with cardiovascular disease 234, stroke 5, peripheral arterial disease 56, and all-cause mortality 78. CVD risk factors are associated with the development of kidney disease 9, and the prevalence of traditional and novel CVD risk factors is elevated among those with kidney disease 710. Urinary albumin excretion (UAE) is an early marker of kidney function that predicts CKD progression 11121314. While glomerular filtration rate (GFR) and UAE are both measurements for kidney function, they represent different phenotypes and identify different subsets of at-risk individuals 15.

Genetic factors play a role in the progression of renal disease. Familial aggregation of end-stage renal disease has been identified 16. Linkage analyses of kidney function have been conducted 1718192021, and novel loci have been mapped to chromosomes 1 18, 2 2122, 3 17, 7 22, 10 192022, and 18 22. In the Framingham Heart Study, we have shown that kidney function is heritable 23, suggesting a role for genetic mechanisms in its etiology. Results of the linkage study from the Framingham Heart Study suggested linkage between kidney disease and a locus on chromosome 4 with a LOD score of 2.2 23. Familial clustering of UAE has been observed in siblings of subjects with diabetes 24, and UAE has been shown to be heritable among the offspring of diabetic subjects 25. Genome-wide linkage analyses have mapped novel loci to chromosomes 12 26 and 19 26 among families enriched for hypertension. Among families with more severe forms of nephropathy, suggestive evidence for linkage has been found on chromosome 10p 27 and 9q31–32 28. In the Framingham Heart Study, we observed a LOD score of 2.2 for UAE on chromosome 8 29.

Thyroid disease, including Hashimoto's thyroiditis and Graves' disease, has a known familial component 30, and the same genes may underlie both conditions 31. Measures of thyroid function have been shown to be heritable 323334, and linkage has been reported to chromosome 18 for autoimmune thyroid disease in at least 2 studies 3536.

As part of the Framingham Heart Study 100K Project, we sought to test the relation of multiple kidney and endocrine traits to 70,987 SNPs. In this manuscript, we focus the results of association studies for GFR, UAE, cysC, and thyroid stimulating hormone (TSH), a sensitive measure of thyroid function.

Overall, 1345 participants were genotyped for the Affymetrix GeneChip Human Mapping 100K SNP set. For this manuscript, we focused on GFR from examination 7, UAE from examination 6, serum cysC from examination 7, and mean TSH from examinations 3 and 4. Phenotypes were available in 1010 participants for GFR at exam cycle 7, 822 participants for UAE at exam cycle 6, 981 participants for cysC at exam cycle 7, and 810 participants for mean TSH at exam cycles 3 and 4. Details about the selection process and genotyping are provided in the Overview 37. Age-sex- and multivariable-adjusted residuals were generated; we present here only the results for multivariable-adjusted traits (all available results can be found in the website http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007). We evaluated associations with 70,987 SNPs on autosomes with minor allele frequencies of at least 0.10, HWE p-value ≥ 0.001, and genotypic call rates of at least 80%.

A description of all traits and phenotypes, including relevant examination cycles and multivariable-adjustments, is presented in Table 1. The median eGFR among individuals with CKD in our sample is 53.7 ml/min/1.73 m². Table 2a presents the top 25 SNPs with the lowest p-values obtained via GEE for GFR, cysC, UAE, and mean TSH; additional results can be found on the National Center for Biotechnology Information website http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007. The top SNP associated with GFR, cysC, and UAE were rs2829235 (p-value 1.6*10^-05), rs1158167 (p-value 8.5*10^-09) near the cysC precursor gene family (CST3, CST4, CST9), and rs1712790 (p-value 1.9*10^-06), respectively (Table 2a). The top SNP to be associated with mean TSH was rs6977660 (p-value 3.7*10^-06). Three SNPs were not shown on Table 2a due to the linkage disequilibrium (LD) (r² > 0.8) with the other top SNPs. These three SNPs were significantly associated with UAE at exam 6: rs9305355 (p-value 2.1*10^-5) in LD with rs9305354, rs725304 (p-value 2.5*10^-5) in LD with rs723464, and rs725307 (p-value 3.2 *10^-5) in LD with rs723464. Table 2b presents the top SNPs based on the FBAT procedure. One SNP, rs10511594 (p = 9.0*10^-5) was in LD (r² > 0.8) with rs7865184 (p = 4.0*10^-5) for mean TSH.

Table 2c presents all traits examined with LOD scores of at least 2.5. One locus on chromosome 1 (nearest marker on the 100K GeneChip, rs10489578) was linked to GFR with a LOD score of 3.08. We observed a LOD score of 4.28 for uric acid to chromosome 2 (nearest marker rs10495487), a location we have previously identified using Marshfield linkage analysis to uric acid 45.

Table 3 presents the top SNPs for our multiple phenotype analysis for GFR, UAE, and TSH with a total of 24 SNPs showing consistently significant associations with multiple related phenotypes. Tables 4a and 4b present results looking at replication of genes that have been associated with kidney traits in the published literature. Four SNPs in or near the CST3 gene were highly correlated with cysC levels (p-value 8.5*10^-09 to 0.007). All four SNPs have minor allele frequencies greater than 10% and none were in linkage disequilibrium (defined by R² > 0.8) as shown on Table 4. The proportion of the cysC variation that can be explained by these SNPs is shown in Table 4. rs1158167 accounts for 2.5% of the cysC variation. We found nominal significance between a SNP near the APOE gene and CKD (p = 0.04).

In our analysis of kidney-related traits, we have found strong evidence for association between multiple kidney-related traits and TSH with SNPs on the Affymetrix 100K GeneChip. We found strong evidence for association between cysC levels and 4 SNPs in or near the CST3 gene. For UAE, we observed strong association with ADAM23, a gene involved in the metalloproteinase family, which may be involved in the pathophysiology of glomerulosclerosis 46, and PCDH9, a gene that is a member of the cadherin superfamily. For TSH, we observed significant association with the HSPA4L gene with a mean p-value for all three TSH measurements, a gene that is part of the heat shock protein family, which may be involved in the pathophysiology of thyroid disease 47. We also observed association with the SCD4 gene, a gene involved in the conversion of saturated to monounsaturated fatty acids; TSH is an important correlate of lipid levels 48.

In our linkage results, we observed a region we have previously noted for uric acid 45, albeit with a significantly higher LOD score. We identified a LOD score of 2.78 on chromosome 3, approximately 18 Mb away from a region previously noted in association with kidney function in hypertensive individuals 17, a region that lies within our 1.5 support LOD interval. We also report novel loci for GFR and TSH.

We show significant association between cysC levels and the CST3 gene, an observation that has been previously noted 49. Our top SNP reaches genome-wide significance, and may represent a true finding. In our candidate gene approach, we found nominal significance for a SNP near the APOE gene, a gene that has been associated with CKD 50. Unfortunately, poor coverage of the APOE gene by the Affymetrix 100K Genechip precluded a more in-depth test of association with SNPs in the APOE gene and CKD.

Strengths of our study lie in our assessment of multiple measures of kidney function and endocrine traits in a sample unselected for these traits, thus reducing bias. We also have excellent assessment of potential confounders that we are able to adjust for in our residual creation. Because the Framingham Heart Study has measured multiple traits, we are able to examine phenotype clustering. Limitations exist as well. Kidney function was ascertained by a single serum creatinine measure, which may lead to misclassification. Our sample was not selected for CKD, and as a result, affected individuals had moderate CKD as reflected by the median eGFR of 53.7 ml/min/1.73 m² among participants with CKD. The MDRD equation, which was used to estimate GFR, has been shown to underestimate GFR by 29% in healthy individuals 51; therefore, we may have introduced additional misclassification into our trait definition. We used a spot urine specimen to assess UAE instead of a 24-hour collection. However, spot UAE approximates 24-hour collections 40, and are not prone to the error inherent in collecting 24-hour urine specimens. We used cysC as a continuous trait and did not use transforming equations to estimate GFR, as most existing equations have been developed in small, selected samples 5253, or developed using immunoturbimetric method 5354 instead of nephelometry and therefore we did not feel as though they were appropriate for use in our large population-based cohort. Further, we used cystatin C as a marker of kidney function but can not rule out that it may also reflect cardiovascular disease risk above and beyond its relation to kidney function 5556575859. Our focus on multivariable models may have led us to miss important bivariate associations between SNPs and measures of kidney function. Given that our findings have not yet been replicated, many p-values may represent false positive findings. We used TSH as an indicator of thyroid function, as we do not have measures of free thyroxine or a reliable assessment of thyroid disease in our study sample. Our sample is neither ethnically diverse nor nationally representative, and it is uncertain how our results would apply to other ethnic groups. However, in genetics studies, sample homogeneity is beneficial in order to reduce population stratification. For limitations pertaining to our genotyping or statistical methods, please see the Overview 37.

Kidney function traits and TSH are associated with SNPs on the Affymetrix 100K SNP GeneChip. Replication of association between these traits and SNPs requires follow-up in independent samples. These data will serve as a valuable resource for replication as more SNPs associated with kidney function and endocrine traits are identified.

CKD = chronic kidney disease; cysC = cystatin-C; DHEAS = dehydroepiandrosterone sulfate; FBAT = family-based association tests; FSH = follicle stimulating hormone; GEE = generalized estimating equations; GFR = glomerular filtration rate; LD = linkage disequilibrium; LH = luteinizing hormone; MDRD = Modification of Diet in Renal Disease; SNP = single nucleotide polymorphism; TSH = thyroid stimulating hormone; UAE = urinary albumin excretion.

The authors declare that they have no competing interests.

SH generated the phenotype data, participated in the analysis, and drafted the manuscript. CF helped generate the phenotype data, interpret the results, and draft the manuscript. QY generated the phenotype data, interpreted the results, and helped draft the manuscript. JBM helped generate the phenotype data, interpret the results, and revised the manuscript critically for important intellectual content; and has given final approval of the version to be published. EP assisted in the acquisition and cleaning of the TSH data and critically reviewed a draft of the manuscript. All authors gave final approval to the manuscript.