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Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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Co-expression-wide association studies link genetically regulated interactions with complex traits.

Mykhaylo M Malakhov1, Wei Pan1

  • 1Division of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN, USA.

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Summary
This summary is machine-generated.

We developed a new method, co-expression-wide association study (COWAS), to find gene and protein interactions linked to complex diseases. This approach identifies how pairs of genes or proteins, through their co-expression, influence traits like cholesterol levels and neurodegenerative diseases.

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Area of Science:

  • Genetics
  • Proteomics
  • Systems Biology

Background:

  • Traditional methods like TWAS/PWAS identify genes/proteins influencing disease risk but overlook co-expression and interaction effects.
  • Understanding molecular interactions is crucial for a comprehensive view of genetic influences on complex traits.

Purpose of the Study:

  • Introduce the co-expression-wide association study (COWAS) method to identify gene/protein pairs associated with complex traits through their genetically regulated co-expression.
  • Address the limitation of existing methods that ignore interaction effects in genetic association studies.

Main Methods:

  • COWAS models genetically regulated expression and co-expression.
  • It tests for associations between imputed co-expression and traits, controlling for direct effects.
  • The method was applied to UK Biobank plasma proteomic data.

Main Results:

  • Identified numerous interacting protein pairs associated with cholesterol levels, Alzheimer's disease, and Parkinson's disease.
  • Demonstrated that protein co-expression can influence complex traits even when individual proteins do not show a significant effect.
  • Showcased COWAS's ability to differentiate direct and interaction effects in molecular networks.

Conclusions:

  • COWAS provides a novel framework for analyzing genetically regulated co-expression in relation to complex traits.
  • The method enhances our understanding of molecular networks underlying genetic effects on disease.
  • COWAS reveals the importance of considering protein-protein interactions in genetic studies of complex diseases.