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Photo: KG Pressfoto

Marju Orho-Melander

Professor

Photo: KG Pressfoto

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

Author

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

Summary, in English

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.

Department/s

  • Genomics, Diabetes and Endocrinology
  • EXODIAB: Excellence of Diabetes Research in Sweden
  • EpiHealth: Epidemiology for Health

Publishing year

2011

Language

English

Pages

1139-1149

Publication/Series

Journal of Lipid Research

Volume

52

Issue

6

Document type

Journal article

Publisher

American Society for Biochemistry and Molecular Biology

Topic

  • Endocrinology and Diabetes

Keywords

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

Status

Published

Research group

  • Genomics, Diabetes and Endocrinology

ISBN/ISSN/Other

  • ISSN: 1539-7262