GMEPS: a fast and efficient likelihood approach for genome-wide mediation analysis under extreme phenotype sequencing

Liyanage Janaka S. S., Estepp Jeremie H., Srivastava Kumar, Li Yun, Mori Motomi and Kang Guolian ()
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Liyanage Janaka S. S.: Department of Biostatistics, St. Jude Children’s Research Hospital, Memphis 38105, TN, USA
Estepp Jeremie H.: Departments of Global Pediatric Medicine and Hematology, St. Jude Children’s Research Hospital, Memphis 38105, TN, USA
Srivastava Kumar: Department of Biostatistics, St. Jude Children’s Research Hospital, Memphis 38105, TN, USA
Li Yun: Department of Biostatistics, Department of Genetics, Department of Computer Science, The University of North Carolina at Chapel Hill, Chapel Hill 27599, NC, USA
Mori Motomi: Department of Biostatistics, St. Jude Children’s Research Hospital, Memphis 38105, TN, USA
Kang Guolian: Department of Biostatistics, St. Jude Children’s Research Hospital, Memphis 38105, TN, USA

Statistical Applications in Genetics and Molecular Biology, 2022, vol. 21, issue 1, 22

Abstract: Due to many advantages such as higher statistical power of detecting the association of genetic variants in human disorders and cost saving, extreme phenotype sequencing (EPS) is a rapidly emerging study design in epidemiological and clinical studies investigating how genetic variations associate with complex phenotypes. However, the investigation of the mediation effect of genetic variants on phenotypes is strictly restrictive under the EPS design because existing methods cannot well accommodate the non-random extreme tails sampling process incurred by the EPS design. In this paper, we propose a likelihood approach for testing the mediation effect of genetic variants through continuous and binary mediators on a continuous phenotype under the EPS design (GMEPS). Besides implementing in EPS design, it can also be utilized as a general mediation analysis procedure. Extensive simulations and two real data applications of a genome-wide association study of benign ethnic neutropenia under EPS design and a candidate-gene study of neurocognitive performance in patients with sickle cell disease under random sampling design demonstrate the superiority of GMEPS under the EPS design over widely used mediation analysis procedures, while demonstrating compatible capabilities under the general random sampling framework.

Keywords: extreme phenotype sequencing; genome-wide association studies; mediation analysis; mediation effect; next generation sequencing studies (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1515/sagmb-2021-0071

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