2. Academic Validation
  3. Integrating Mouse and Human Genetic Data to Move beyond GWAS and Identify Causal Genes in Cholesterol Metabolism

Integrating Mouse and Human Genetic Data to Move beyond GWAS and Identify Causal Genes in Cholesterol Metabolism

  • Cell Metab. 2020 Apr 7;31(4):741-754.e5. doi: 10.1016/j.cmet.2020.02.015.
Zhonggang Li 1,  James A Votava 1,  Gregory J M Zajac 2,  Jenny N Nguyen 3,  Fernanda B Leyva Jaimes 1,  Sophia M Ly 1,  Jacqueline A Brinkman 4,  Marco De Giorgi 5,  Sushma Kaul 6,  Cara L Green 4,  Samantha L St Clair 1,  Sabrina L Belisle 1,  Julia M Rios 1,  David W Nelson 1,  Mary G Sorci-Thomas 6,  William R Lagor 7,  Dudley W Lamming 4,  Chi-Liang Eric Yen 1,  Brian W Parks 8
Affiliations

Affiliations

  • 1 Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, USA.
  • 2 Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
  • 3 Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA.
  • 4 Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA; William S. Middleton Memorial Veterans Hospital, Madison, WI, USA.
  • 5 William S. Middleton Memorial Veterans Hospital, Madison, WI, USA.
  • 6 Department of Medicine, Division of Endocrinology, Medical College of Wisconsin, Milwaukee, WI, USA.
  • 7 Department of Molecular Physiology and Biophysics, Baylor College of Medicine, Houston, TX, USA.
  • 8 Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, USA. Electronic address: [email protected].
PMID: 32197071 DOI: 10.1016/j.cmet.2020.02.015
Abstract

Identifying the causal gene(s) that connects genetic variation to a phenotype is a challenging problem in genome-wide association studies (GWASs). Here, we develop a systematic approach that integrates mouse liver co-expression networks with human lipid GWAS data to identify regulators of Cholesterol and lipid metabolism. Through our approach, we identified 48 genes showing replication in mice and associated with plasma lipid traits in humans and six genes on the X chromosome. Among these 54 genes, 25 have no previously identified role in lipid metabolism. Based on functional studies and integration with additional human lipid GWAS datasets, we pinpoint Sestrin1 as a causal gene associated with plasma Cholesterol levels in humans. Our validation studies demonstrate that Sestrin1 influences plasma Cholesterol in multiple mouse models and regulates Cholesterol biosynthesis. Our results highlight the power of combining mouse and human datasets for prioritization of human lipid GWAS loci and discovery of lipid genes.

Keywords

GWAS; SREBP2; Sestrin1; cholesterol; co-expression networks; computational biology; human genetics; lipoproteins; mouse genetics; plasma lipids.

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