Identification of shared and differentiating genetic architecture for autism spectrum disorder, attention-deficit hyperactivity disorder and case subgroups
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- Identification of shared and differentiating genetic architecture for autism spectrum disorder-2-45
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Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are highly heritable neurodevelopmental conditions, with considerable overlap in their genetic etiology. We dissected their shared and distinct genetic etiology by cross-disorder analyses of large datasets. We identified seven loci shared by the disorders and five loci differentiating them. All five differentiating loci showed opposite allelic directions in the two disorders and significant associations with other traits, including educational attainment, neuroticism and regional brain volume. Integration with brain transcriptome data enabled us to identify and prioritize several significantly associated genes. The shared genomic fraction contributing to both disorders was strongly correlated with other psychiatric phenotypes, whereas the differentiating portion was correlated most strongly with cognitive traits. Additional analyses revealed that individuals diagnosed with both ASD and ADHD were double-loaded with genetic predispositions for both disorders and showed distinctive patterns of genetic association with other traits compared with the ASD-only and ADHD-only subgroups. These results provide insights into the biological foundation of the development of one or both conditions and of the factors driving psychopathology discriminatively toward either ADHD or ASD.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | Nature Genetics |
| Vol/bind | 54 |
| Sider (fra-til) | 1470–1478 |
| ISSN | 1061-4036 |
| DOI | |
| Status | Udgivet - 2022 |
Bibliografisk note
Funding Information:
The iPSYCH team was supported by grants from the Lundbeck Foundation (R102-A9118, R155-2014-1724 and R248-2017-2003), the EU H2020 Program (grant no. 667302, CoCA), NIMH (1U01MH109514-01 to A.D.B.) and the Universities and University Hospitals of Aarhus and Copenhagen. The Danish National Biobank resource was supported by the Novo Nordisk Foundation. High-performance computer capacity for handling and statistical analysis of iPSYCH data on the GenomeDK HPC facility was provided by the Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark (grant to A.D.B.). G.V. was funded by NIMH grant K08MH122911 and the 2020 NARSAD Young Investigator Grant no. 29350 from the Brain & Behavior Research Foundation. P.R. was funded by NIMH grants R01MH125246, U01MH116442 and R01MH109677. Support for this research was further received by B.C. from the Spanish Ministerio de Ciencia, Innovación y Universidades (RTI2018-100968-B-100), Ministerio de Economía y Competitividad, AGAUR/Generalitat de Catalunya (2017-SGR-738), the European Union H2020 Program (H2020/2014-2020) under grant agreements 667302 (CoCA), 643051 (MiND) and 728018 (Eat2beNICE), and the ECNP network ‘ADHD across the lifespan’. S.V.F. is supported by the European Union’s Horizon 2020 research and innovation programme under grant agreements 667302 and 965381; NIMH grants U01MH109536-01, U01AR076092-01A1, R0MH116037 and 5R01AG06495502; Oregon Health and Science University, Otsuka Pharmaceuticals and Supernus Pharmaceutical Company. We thank all participants in the cohorts included in this analysis.
Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Nature America, Inc.
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