The goal of our approach was to converge on genes that influence human kidney aging through sequential genomic analyses. We began with a genome-wide transcriptional profile of aging in the human kidney, which gave an unbiased view of gene expression changes that occur with age 
. Then, we used total expression analysis and allele-specific expression analysis to determine which alleles are differentially expressed. We identified 101 age-regulated eQTLs. SNPs in one of these genes, MMP20
, showed a statistically significant association with normal kidney aging. Although significant by combining the data from two independent populations, the best way to confirm our gene association with renal aging is to replicate the findings in additional populations.
The populations used to identify aging SNPs, BLSA and InCHIANTI, stand out for their usefulness in studying normal kidney aging. Both of these studies were purposefully designed to study healthy individuals, instead of those harboring diseases associated with old age. The BLSA study includes longitudinal measurements of traits associated with normal aging, which added considerable power to the analysis.
Two SNPs in MMP20
significantly associated with age-related decline in GFR of the kidney. Matrix metalloproteinases are involved in the breakdown of extracellular matrix in normal physiological processes, such as embryonic development, reproduction, and tissue remodeling, as well as in disease processes, such as arthritis and metastasis 
. Matrix metalloproteinases degrade extracellular matrix proteins including laminin, elastin, proteoglycans, fibronectin, and collagens 
. A role for MMP20
in renal function has not been described before, although previous studies show that MMP20
plays an important role in tooth development 
. The finding that a matrix metalloproteinase is involved in kidney aging is striking because changes in the extracellular matrix play a key role in aging of the kidney. The glomerular basement membrane thickens, and the mesangial matrix increases in volume with age 
. Interstitial fibrosis occurs during aging because of an increase in matrix and fibrillar collagen accumulation in the subintimal space 
was included in our candidate aging gene set not because the gene itself is significantly age-regulated in the kidney. Instead, MMP20
was included because it is a component of the extracellular matrix, one of the pathways that coordinately increased expression with age in three human tissues including the kidney 
. Therefore, polymorphisms in MMP20
may not only associate with aging of the kidney, but may associate with phenotypes of aging in other tissues as well. Additionally, if MMP20
is a common regulator of aging, certain alleles may also be enriched in centenarians.
The second-highest scoring gene in our kidney aging association study is the insulin-like growth factor 1 receptor. Although the SNP in this gene did not reach statistical significance in this study, this result is interesting because this gene is part of the insulin-like signaling pathway that has been shown in be involved in aging in worms, flies and mice 
. Specifically, reduced signaling in this pathway results in longer lifespans for these model organisms. In worms, the orthologous gene is called daf-2
(GeneID 175410), and daf-2
mutants can have lifespans that are 100% longer than wild-type worms 
. In humans, rare variants in the IGF1R
gene in centenarians are associated with reduced IGF1R levels and defective IGF signaling 
Sequential use of transcriptional profiling and eQTL mapping could be used as a general method to increase the statistical power for any human gene association study. Like candidate gene approaches, an advantage of our approach to identify variants associated with kidney aging is that it increases the statistical power of the gene association study by decreasing the number of SNPs that are tested to potentially functional SNPs. An advantage of our sequential approach over a candidate gene approach is that the entire genome was screened for genes that are age-regulated in the first step.
Several groups have used DNA microarrays to measure gene expression in lymphoblastoid cell lines and have found polymorphisms that associate with expression level 
. In a total expression analysis of human brain cortical tissue, 21% of genes have SNPs that associate with expression levels 
. Other groups have used the allele-specific expression approach to identify differentially-expressed genes in lymphoblastoid cell lines 
, brain 
, white blood cells 
, fetal kidney and fetal liver 
. These studies found that 20–50% of the genes in the genome are differentially expressed. Sixteen of the genes showing allele-specific expression found by our study were also found in previous studies (Table S5
. Thus, 77 of the 93 allele-specifically expressed genes identified in this work represent novel findings. Our finding that 41% of tested genes showed allele-specific expression is similar to the percentage found in previous studies 
Of the expression-associated SNPs we identified, most were found using allele-specific expression measurements within heterozygotes. Specifically, 41% of genes assayed contained eSNPs using the allele-specific expression method, whereas only 2% of genes assayed contained eSNPs using the total expression method. The statistical cutoff for finding eSNPs using the allele-specific method was more stringent than the one used for the total expression method. Thus, our results may underestimate the improved sensitivity of the allele-specific method over the total expression method.
Unlike the total expression method, the allele-specific method examines alleles within the same cellular environment in heterozygous individuals. This maximizes the sensitivity of the assay because the alleles are expressed from the same environment and genetic background. Previous work with a smaller set of 64 genes also showed that allele-specific analysis in heterozygotes was more sensitive than total expression methods for finding SNPs associated with expression levels in cis 
. The results from the allele-specific analysis demonstrate that differential expression is widespread across the human genome and suggest that differential expression could be a major factor contributing to differences in phenotype among individuals. As the Genotype-Tissue Expression (GTEx) project 
moves forward, it will be important to consider allele-specific expression data to maximize sensitivity to detect differential expression.
Finding new human aging genes, possibly MMP20, contributes to our understanding of molecular mechanisms underlying the human aging process. Among young individuals, an unfavorable SNP genotype may indicate risk for rapid decline in kidney function and this information could be extremely useful to identify patients who may require early intervention. Among older individuals, a favorable SNP genotype may indicate that they may still be eligible as kidney donors even though they are over the current upper age limit. As more aging genes are confirmed, the alleles belonging to a patient can be combined to better predict the aging trajectory of the kidney.