Genomic convergence association studies of expression and aging in the human kidney
- Heather Elizabeth Wheeler.
- Mar. 2010.
- Physical description
- online resource (xi, 100 pages) : illustrations (some color)
- Wheeler, Heather Elizabeth.
- Barsh, Gregory Stefan. thesis advisor.
- Brunet, Anne, 1972- thesis advisor.
- Kim, Stuart thesis advisor (primary).
- Tang, Hua (Geneticist). thesis advisor.
- Stanford University. Committee on Graduate Studies. degree grantor.
- Stanford University. Department of Genetics. degree grantor.
- Includes bibliographical references (p. 87-100).
- Although family studies have shown that genes play a role in longevity and tissue aging, it has proven difficult to identify the specific genetic variants involved. Kidneys age at different rates, such that some people show little or no effects of aging whereas others show rapid functional decline. We developed a sequential transcriptional profiling and expression quantitative trait loci (eQTL) mapping approach known as genomic convergence to find genes associated with aging in the kidney. We first performed whole-genome transcriptional profiling to find 630 genes that change expression with age in the kidney. Next, we used two methods to determine which of these age-regulated genes are eQTLs, which means they contain SNPs whose alleles associate with expression level. We found that 101 of the age-regulated genes are eQTLs. We also found that the allele-specific eQTL detection method, which compares the mRNA levels of the two alleles within heterozygous individuals, was more sensitive than the total expression method in detecting allelic expression differences. We tested the eQTLs for association with kidney aging, measured by glomerular filtration rate (GFR) using combined data from the Baltimore Longitudinal Study of Aging (BLSA) and the InCHIANTI study. We found a SNP association (rs1711437 in MMP20) with kidney aging (uncorrected p = 3.6E-05, empirical p = 0.01) that explains 1-2% of the variance in GFR among individuals. The results of this sequential analysis may provide the first evidence for a gene association with kidney aging in humans. Our approach of combining both expression and genotype data can be applied to any phenotype of interest to increase the power to find genetic associations.
- Publication date
- Submitted to the Department of Genetics and the Committee on Graduate Studies of Stanford University.
- Thesis (Ph.D.)--Stanford University, 2010.