Genomic convergence association studies of expression and aging in the human kidney
Abstract/Contents
- Abstract
- 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.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2010 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Wheeler, Heather Elizabeth |
|---|---|
| Associated with | Stanford University, Department of Genetics |
| Primary advisor | Kim, Stuart |
| Thesis advisor | Kim, Stuart |
| Thesis advisor | Barsh, Gregory Stefan |
| Thesis advisor | Brunet, Anne, 1972- |
| Thesis advisor | Tang, Hua |
| Advisor | Barsh, Gregory Stefan |
| Advisor | Brunet, Anne, 1972- |
| Advisor | Tang, Hua |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Heather Elizabeth Wheeler. |
|---|---|
| Note | Submitted to the Department of Genetics. |
| Thesis | Ph.D. Stanford University 2010 |
| Location | electronic resource |
Access conditions
- Copyright
- © 2010 by Heather Elizabeth Wheeler
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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