Machine learning optimized polygenic scores for blood cell traits identify sex-specific trajectories and genetic correlations with disease

• Main Authors: Yu Xu (Author), Dragana Vuckovic (Author), Scott C. Ritchie (Author), Parsa Akbari (Author), Tao Jiang (Author), Jason Grealey (Author), Adam S. Butterworth (Author), Willem H. Ouwehand (Author), David J. Roberts (Author), Emanuele Di Angelantonio (Author), John Danesh (Author), Nicole Soranzo (Author), Michael Inouye (Author)
• Format: Book
• Published: Elsevier, 2022-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Summary: Genetic association studies for blood cell traits, which are key indicators of health and immune function, have identified several hundred associations and defined a complex polygenic architecture. Polygenic scores (PGSs) for blood cell traits have potential clinical utility in disease risk...