There are thousands of rare human disorders that are caused by single deleterious, protein-coding genetic variants1. However, patients with the same genetic defect can have different clinical presentations2,3,4, and some individuals who carry known disease-causing variants can appear unaffected5. Here, to understand what explains these differences, we study a cohort of 6,987 children assessed by clinical geneticists to have severe neurodevelopmental disorders such as global developmental delay and autism, often in combination with abnormalities of other organ systems. Although the genetic causes of these neurodevelopmental disorders are expected to be almost entirely monogenic, we show that 7.7% of variance in risk is attributable to inherited common genetic variation. We replicated this genome-wide common variant burden by showing, in an independent sample of 728 trios (comprising a child plus both parents) from the same cohort, that this burden is over-transmitted from parents to children with neurodevelopmental disorders. Our common-variant signal is significantly positively correlated with genetic predisposition to lower educational attainment, decreased intelligence and risk of schizophrenia. We found that common-variant risk was not significantly different between individuals with and without a known protein-coding diagnostic variant, which suggests that common-variant risk affects patients both with and without a monogenic diagnosis. In addition, previously published common-variant scores for autism, height, birth weight and intracranial volume were all correlated with these traits within our cohort, which suggests that phenotypic expression in individuals with monogenic disorders is affected by the same variants as in the general population. Our results demonstrate that common genetic variation affects both overall risk and clinical presentation in neurodevelopmental disorders that are typically considered to be monogenic.
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The raw genotype data, post-quality-control genotype data and discovery GWAS summary statistics generated and/or analysed during the current study are available through European Genome-phenome Archive, under EGAS00001000775. This study makes use of data generated by the DECIPHER community: a full list of centres that contributed to the generation of the data is available from http://decipher.sanger.ac.uk, and via email from email@example.com. Information on how to access the data from the UKHLS can be found on the ‘Understanding Society’ website, at https://www.understandingsociety.ac.uk/.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
We thank the families involved in the DDD study for their participation and patience, the DDD study clinicians, research nurses and clinical scientists in the recruiting centres for their hard work on behalf of families, M. Niemi for help making Fig. 1 and V. Warrier for useful discussions. The DDD study presents independent research commissioned by the Health Innovation Challenge Fund (grant number HICF-1009-003), a parallel funding partnership between Wellcome and the Department of Health, and the Wellcome Sanger Institute (grant number WT098051). The views expressed in this publication are those of the author(s) and not necessarily those of Wellcome or the Department of Health. The research team acknowledges the support of the National Institute for Health Research, through the Comprehensive Clinical Research Network. This study makes use of data generated by the DECIPHER community. Funding for the project was provided by the Wellcome Trust. We used data from ‘Understanding Society: The UK Household Longitudinal Study’, which is led by the Institute for Social and Economic Research at the University of Essex and funded by the Economic and Social Research Council (grant number ES/M008592/1). The data were collected by NatCen and the genome-wide scan data were analysed by the Wellcome Trust Sanger Institute. Data governance was provided by the METADAC data access committee, funded by ESRC, Wellcome and MRC (grant number MR/N01104X/1). Australian controls from the Brisbane Longitudinal Twin Study were collected and genotyped with grants from the National Health and Medical Research Council. We thank A. Pardiñas for producing the PGC-CLOZUK summary statistics without the Australian controls.
Nature thanks D. Arking, C. Lewis and S. Ripke for their contribution to the peer review of this work.
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medizinische genetik (2018)