The mouse QTL map helps interpret human genome-wide association studies for HDL cholesterol

Magalie S. Leduc, Malcolm Lyons, Katayoon Darvishi, Kenneth Walsh, Susan Sheehan, Sarah Amend, Allison Cox, Marju Orho-Melander, Sekar Kathiresan, Beverly Paigen, Ron Korstanje

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20 Citations (SciVal)


Genome-wide association (GWA) studies represent a powerful strategy for identifying susceptibility genes for complex diseases in human populations but results must be confirmed and replicated. Because of the close homology between mouse and human genomes, the mouse can be used to add evidence to genes suggested by human studies. We used the mouse quantitative trait loci (QTL) map to interpret results from a GWA study for genes associated with plasma HDL cholesterol levels. We first positioned single nucleotide polymorphisms (SNPs) from a human GWA study on the genomic map for mouse HDL QTL. We then used mouse bioinformatics, sequencing, and expression studies to add evidence for one well-known HDL gene (Abca1) and three newly identified genes (Galnt2, Wwox, and Cdh13), thus supporting the results of the human study. For GWA peaks that occur in human haplotype blocks with multiple genes, we examined the homologous regions in the mouse to prioritize the genes using expression, sequencing, and bioinformatics from the mouse model, showing that some genes were unlikely candidates and adding evidence for candidate genes Mvk and Mmab in one haplotype block and Fads1 and Fads2 in the second haplotype block. Our study highlights the value of mouse genetics for evaluating genes found in human GWA studies.-Leduc, M. S., M. Lyons, K. Darvishi, K. Walsh, S. Sheehan, S. Amend, A. Cox, M. Orho-Melander, S. Kathiresan, B. Paigen, and R. Korstanje. The mouse QTL map helps interpret human genome-wide association studies for HDL cholesterol. J. Lipid Res. 2011. 52: 1139-1149.
Original languageEnglish
Pages (from-to)1139-1149
JournalJournal of Lipid Research
Issue number6
Publication statusPublished - 2011

Subject classification (UKÄ)

  • Endocrinology and Diabetes


  • genomics
  • high density lipoprotein
  • comparative genomics
  • quantitative
  • trait loci
  • mouse model


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