The impact of non-additive genetic associations on age-related complex diseases

Marta Guindo-Martínez, Ramon Amela, Silvia Bonàs-Guarch, Montserrat Puiggròs, Cecilia Salvoro, Irene Miguel-Escalada, Caitlin E. Carey, Joanne B. Cole, Sina Rüeger, Elizabeth Atkinson, Aaron Leong, Friman Sanchez, Cristian Ramon-Cortes, Jorge Ejarque, Duncan S. Palmer, Mitja Kurki, Krishna Aragam, Jose C. Florez, Rosa M. Badia, Josep M. Mercader () and David Torrents ()
Additional contact information
Marta Guindo-Martínez: Barcelona Supercomputing Center (BSC)
Ramon Amela: Barcelona Supercomputing Center (BSC)
Silvia Bonàs-Guarch: Barcelona Supercomputing Center (BSC)
Montserrat Puiggròs: Barcelona Supercomputing Center (BSC)
Cecilia Salvoro: Barcelona Supercomputing Center (BSC)
Irene Miguel-Escalada: Barcelona Supercomputing Center (BSC)
Caitlin E. Carey: Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard
Joanne B. Cole: Broad Institute of MIT and Harvard
Sina Rüeger: University of Helsinki
Elizabeth Atkinson: Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard
Aaron Leong: Harvard Medical School
Friman Sanchez: Barcelona Supercomputing Center (BSC)
Cristian Ramon-Cortes: Barcelona Supercomputing Center (BSC)
Jorge Ejarque: Barcelona Supercomputing Center (BSC)
Duncan S. Palmer: Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard
Mitja Kurki: University of Helsinki
Krishna Aragam: Broad Institute of MIT and Harvard
Jose C. Florez: Broad Institute of MIT and Harvard
Rosa M. Badia: Barcelona Supercomputing Center (BSC)
Josep M. Mercader: Barcelona Supercomputing Center (BSC)
David Torrents: Barcelona Supercomputing Center (BSC)

Nature Communications, 2021, vol. 12, issue 1, 1-14

Abstract: Abstract Genome-wide association studies (GWAS) are not fully comprehensive, as current strategies typically test only the additive model, exclude the X chromosome, and use only one reference panel for genotype imputation. We implement an extensive GWAS strategy, GUIDANCE, which improves genotype imputation by using multiple reference panels and includes the analysis of the X chromosome and non-additive models to test for association. We apply this methodology to 62,281 subjects across 22 age-related diseases and identify 94 genome-wide associated loci, including 26 previously unreported. Moreover, we observe that 27.7% of the 94 loci are missed if we use standard imputation strategies with a single reference panel, such as HRC, and only test the additive model. Among the new findings, we identify three novel low-frequency recessive variants with odds ratios larger than 4, which need at least a three-fold larger sample size to be detected under the additive model. This study highlights the benefits of applying innovative strategies to better uncover the genetic architecture of complex diseases.

Date: 2021
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DOI: 10.1038/s41467-021-21952-4

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