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Modeling diseases in multiple mouse strains for precision medicine studies.
1Telethon Institute of Genetics and Medicine, Pozzuoli (NA), Italy a.klein@tigem.it.
Physiological Genomics
|January 29, 2017
Summary
Mice models with known genetic backgrounds aid in studying rare genetic disorders and pharmacogenomics. This approach enhances genome-wide association studies (GWAS) by overcoming patient number limitations and reducing costs.
Area of Science:
- Genetics
- Pharmacogenomics
- Animal Models
Background:
- Phenotypic variability in patients with genetic disorders poses a challenge for research.
- Genome-wide association studies (GWAS) require large patient cohorts, which are often unavailable for rare diseases.
- Utilizing inbred mouse strains offers a controlled system to study genetic influences on disease.
Purpose of the Study:
- To explore the utility of mouse models for studying the genetic basis of phenotypic variability.
- To enhance the statistical power and reduce the cost of genome-wide association studies (GWAS) for rare disorders.
- To investigate the applicability of this approach in pharmacogenomics.
Main Methods:
- Generating disease models in mice through genetic or chemical interventions across diverse genetic backgrounds.
- Assessing clinical phenotypes in these mouse models.
- Leveraging known single nucleotide polymorphism (SNP) catalogs of inbred strains for bioinformatics analysis.
Main Results:
- Mouse models provide a viable platform to investigate genetic contributions to phenotypic diversity.
- The use of inbred strains with available SNP data streamlines GWAS by eliminating the need for individual mouse genotyping.
- This methodology is applicable to both rare disease research and pharmacogenomics.
Conclusions:
- Mouse models are valuable tools for dissecting the genetic underpinnings of phenotypic variability in human diseases.
- Employing inbred strains significantly facilitates and economizes genome-wide association studies (GWAS), especially for rare conditions.
- The described approach holds promise for advancing pharmacogenomic research.

