Sequential use of transcriptional profiling, expression quantitative trait mapping, and gene association implicates MMP20 in human kidney aging

Heather E. Wheeler, E. Jeffrey Metter, Toshiko Tanaka, Devin Absher, John Higgins, Jacob M. Zahn, Julie Wilhelmy, Ronald W. Davis, Andrew Singleton, Richard M. Myers, Luigi Ferrucci, Stuart K. Kim

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Abstract

Kidneys age at different rates, such that some people show little or no effects of aging whereas others show rapid functional decline. We sequentially used transcriptional profiling and expression quantitative trait loci (eQTL) mapping to narrow down which genes to test for association with kidney aging. We first performed whole-genome transcriptional profiling to find 630 genes that change expression with age in the kidney. Using two methods to detect eQTLs, we found 101 of these ageregulated genes contain expression-associated SNPs. 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 = 3.6×10-5, 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.

Original languageEnglish (US)
Article numbere1000685
JournalPLoS Genetics
Volume5
Issue number10
DOIs
StatePublished - Oct 2009
Externally publishedYes

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ASJC Scopus subject areas

  • Genetics
  • Molecular Biology
  • Ecology, Evolution, Behavior and Systematics
  • Cancer Research
  • Genetics(clinical)

Cite this

Wheeler, H. E., Metter, E. J., Tanaka, T., Absher, D., Higgins, J., Zahn, J. M., Wilhelmy, J., Davis, R. W., Singleton, A., Myers, R. M., Ferrucci, L., & Kim, S. K. (2009). Sequential use of transcriptional profiling, expression quantitative trait mapping, and gene association implicates MMP20 in human kidney aging. PLoS Genetics, 5(10), [e1000685]. https://doi.org/10.1371/journal.pgen.1000685