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Reimagining Gene-Environment Interaction Analysis for Human Complex Traits

View ORCID ProfileJiacheng Miao, Gefei Song, Yixuan Wu, Jiaxin Hu, Yuchang Wu, Shubhashrita Basu, James S. Andrews, Katherine Schaumberg, Jason M. Fletcher, Lauren L. Schmitz, View ORCID ProfileQiongshi Lu
doi: https://doi.org/10.1101/2022.12.11.519973
Jiacheng Miao
1Department of Biostatistics and Medical Informatics, University of Wisconsin–Madison, WI, USA 53706
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  • ORCID record for Jiacheng Miao
Gefei Song
2University of Wisconsin–Madison, Madison, WI, USA 53706
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Yixuan Wu
2University of Wisconsin–Madison, Madison, WI, USA 53706
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Jiaxin Hu
3Department of Statistics, University of Wisconsin–Madison, Madison, WI, USA 53706
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Yuchang Wu
1Department of Biostatistics and Medical Informatics, University of Wisconsin–Madison, WI, USA 53706
4Center for Demography of Health and Aging, University of Wisconsin–Madison, Madison, WI, USA 53706
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Shubhashrita Basu
4Center for Demography of Health and Aging, University of Wisconsin–Madison, Madison, WI, USA 53706
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James S. Andrews
5Division of Rheumatology, Department of Medicine, University of Washington, Seattle, WA, USA 98122
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Katherine Schaumberg
6Department of Psychiatry, University of Wisconsin–Madison, Madison, WI, USA 53719
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Jason M. Fletcher
4Center for Demography of Health and Aging, University of Wisconsin–Madison, Madison, WI, USA 53706
7Robert M. La Follette School of Public Affairs, University of Wisconsin–Madison, Madison, WI, USA 53706
8Department of Sociology, University of Wisconsin–Madison, Madison, WI, USA 53706
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Lauren L. Schmitz
4Center for Demography of Health and Aging, University of Wisconsin–Madison, Madison, WI, USA 53706
7Robert M. La Follette School of Public Affairs, University of Wisconsin–Madison, Madison, WI, USA 53706
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Qiongshi Lu
1Department of Biostatistics and Medical Informatics, University of Wisconsin–Madison, WI, USA 53706
3Department of Statistics, University of Wisconsin–Madison, Madison, WI, USA 53706
4Center for Demography of Health and Aging, University of Wisconsin–Madison, Madison, WI, USA 53706
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  • ORCID record for Qiongshi Lu
  • For correspondence: qlu@biostat.wisc.edu
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Abstract

In this study, we introduce PIGEON—a novel statistical framework for quantifying and estimating polygenic gene-environment interaction (GxE) using a variance component analytical approach. Based on PIGEON, we outline the main objectives in GxE studies, demonstrate the flaws in existing GxE approaches, and introduce an innovative estimation procedure which only requires summary statistics as input. We demonstrate the statistical superiority of PIGEON through extensive theoretical and empirical analyses and showcase its performance in multiple analytic settings, including a quasi-experimental GxE study of health outcomes, gene-by-sex interaction for 530 traits, and gene-by-treatment interaction in a randomized clinical trial. Our results show that PIGEON provides an innovative solution to many long-standing challenges in GxE inference and may fundamentally reshape analytical strategies in future GxE studies.

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted December 14, 2022.
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Reimagining Gene-Environment Interaction Analysis for Human Complex Traits
Jiacheng Miao, Gefei Song, Yixuan Wu, Jiaxin Hu, Yuchang Wu, Shubhashrita Basu, James S. Andrews, Katherine Schaumberg, Jason M. Fletcher, Lauren L. Schmitz, Qiongshi Lu
bioRxiv 2022.12.11.519973; doi: https://doi.org/10.1101/2022.12.11.519973
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Reimagining Gene-Environment Interaction Analysis for Human Complex Traits
Jiacheng Miao, Gefei Song, Yixuan Wu, Jiaxin Hu, Yuchang Wu, Shubhashrita Basu, James S. Andrews, Katherine Schaumberg, Jason M. Fletcher, Lauren L. Schmitz, Qiongshi Lu
bioRxiv 2022.12.11.519973; doi: https://doi.org/10.1101/2022.12.11.519973

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