Journal
NATURE COMMUNICATIONS
Volume 12, Issue 1, Pages -Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41467-021-21952-4
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Funding
- Severo Ochoa Program - Spanish Government [SEV-2011-00067, SEV2015-0493]
- Spanish Ministry of Science and Innovation [TIN201565316-P]
- Generalitat de Catalunya [2014-SGR-1051]
- EFSD/Lilly research fellowship
- Sara Borrell Fellowship from the Instituto Carlos III
- American Diabetes Association Innovative and Clinical Translational Award [1-19-ICTS-068]
- FI-DGR Fellowship from FIDGR 2013 from Agencia de Gestio d'Ajuts Universitaris i de Recerca (AGAUR, Generalitat de Catalunya)
- `Juan de la Cierva' postdoctoral fellowship (MINECO) [FJCI-2017-32090]
- European Union [H2020-MSCA-COFUND-2016754433]
- Spanish Ministry of Science, Innovation, and Universities [BES-2016-076791]
- National Institutes of Mental Health [K01MH121659, T32MH017119]
- NIH/NIDDK [K24 DK110550]
- Wellcome Trust [WT091310]
- Netherlands Organization for Scientific Research [184021007]
- Common Fund of the Office of the Director of the National Institutes of Health
- NCI
- NHGRI
- NHLBI
- NIDA
- NIMH
- NINDS
- Agency for Management of University and Research Grants (AGAUR)
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This study utilized an extensive GWAS strategy called GUIDANCE to improve genotype imputation by using multiple reference panels, including the X chromosome and non-additive models. By applying this methodology, 94 genome-wide associated loci were identified for 22 age-related diseases, with 26 previously unreported loci. The study also revealed that 27.7% of these loci would have been missed if standard imputation strategies with a single reference panel and only testing the additive model were used.
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. Most genome-wide association studies assume an additive model, exclude the X chromosome, and use one reference panel. Here, the authors implement a strategy including non-additive models and find that the number of loci for age-related traits increases as compared to the additive model alone.
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