The contribution of X-linked coding variation to severe developmental disorders

Hilary C. Martin (), Eugene J. Gardner, Kaitlin E. Samocha, Joanna Kaplanis, Nadia Akawi, Alejandro Sifrim, Ruth Y. Eberhardt, Ana Lisa Taylor Tavares, Matthew D. C. Neville, Mari E. K. Niemi, Giuseppe Gallone, Jeremy McRae, Caroline F. Wright, David R. FitzPatrick, Helen V. Firth and Matthew E. Hurles
Additional contact information
Hilary C. Martin: Wellcome Genome Campus
Eugene J. Gardner: Wellcome Genome Campus
Kaitlin E. Samocha: Wellcome Genome Campus
Joanna Kaplanis: Wellcome Genome Campus
Nadia Akawi: Wellcome Genome Campus
Alejandro Sifrim: Wellcome Genome Campus
Ruth Y. Eberhardt: Wellcome Genome Campus
Ana Lisa Taylor Tavares: Wellcome Genome Campus
Matthew D. C. Neville: Wellcome Genome Campus
Mari E. K. Niemi: Wellcome Genome Campus
Giuseppe Gallone: Wellcome Genome Campus
Jeremy McRae: Wellcome Genome Campus
Caroline F. Wright: University of Exeter Medical School
David R. FitzPatrick: University of Edinburgh, Western General Hospital
Helen V. Firth: Wellcome Genome Campus
Matthew E. Hurles: Wellcome Genome Campus

Nature Communications, 2021, vol. 12, issue 1, 1-13

Abstract: Abstract Over 130 X-linked genes have been robustly associated with developmental disorders, and X-linked causes have been hypothesised to underlie the higher developmental disorder rates in males. Here, we evaluate the burden of X-linked coding variation in 11,044 developmental disorder patients, and find a similar rate of X-linked causes in males and females (6.0% and 6.9%, respectively), indicating that such variants do not account for the 1.4-fold male bias. We develop an improved strategy to detect X-linked developmental disorders and identify 23 significant genes, all of which were previously known, consistent with our inference that the vast majority of the X-linked burden is in known developmental disorder-associated genes. Importantly, we estimate that, in male probands, only 13% of inherited rare missense variants in known developmental disorder-associated genes are likely to be pathogenic. Our results demonstrate that statistical analysis of large datasets can refine our understanding of modes of inheritance for individual X-linked disorders.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-020-20852-3

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DOI: 10.1038/s41467-020-20852-3

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