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; Matthew E. Hurles

doi:10.1038/s41467-020-20852-3

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

Hilary C. Martin (Lead / Corresponding author), 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, Matthew E. Hurles

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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.

Original language	English
Article number	627
Number of pages	13
Journal	Nature Communications
Volume	12
Early online date	27 Jan 2021
DOIs	https://doi.org/10.1038/s41467-020-20852-3
Publication status	Published - Dec 2021

Keywords

Genetic association study
Medical genetics
Neurodevelopmental disorders

ASJC Scopus subject areas

General Chemistry
General Biochemistry,Genetics and Molecular Biology
General Physics and Astronomy

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Martin, H. C., Gardner, E. J., Samocha, K. E., Kaplanis, J., Akawi, N., Sifrim, A., Eberhardt, R. Y., Tavares, A. L. T., Neville, M. D. C., Niemi, M. E. K., Gallone, G., McRae, J., Wright, C. F., Fitzpatrick, D. R., & Firth, H. V., & Hurles, M. E. (2021). The contribution of X-linked coding variation to severe developmental disorders. Nature Communications, 12, Article 627. https://doi.org/10.1038/s41467-020-20852-3

@article{c65872d034cb41aca77b79e47adabdb7,

title = "The contribution of X-linked coding variation to severe developmental disorders",

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.",

keywords = "Genetic association study, Medical genetics, Neurodevelopmental disorders",

author = "Martin, {Hilary C.} and Gardner, {Eugene J.} and Samocha, {Kaitlin E.} and Joanna Kaplanis and Nadia Akawi and Alejandro Sifrim and Eberhardt, {Ruth Y.} and Tavares, {Ana Lisa Taylor} and Neville, {Matthew D. C.} and Niemi, {Mari E. K.} and Giuseppe Gallone and Jeremy McRae and Silvia Borras and Caroline Clark and John Dean and Zosia Miedzybrodzka and Alison Ross and Stephen Tennant and Tabib Dabir and Deirdre Donnelly and Mervyn Humphreys and Alex Magee and Vivienne McConnell and Shane McKee and Susan McNerlan and Morrison, {Patrick J.} and Gillian Rea and Fiona Stewart and Trevor Cole and Nicola Cooper and Lisa Cooper-Charles and Helen Cox and Lily Islam and Joanna Jarvis and Rebecca Keelagher and Derek Lim and Dominic McMullan and Jenny Morton and Swati Naik and Mary O{\textquoteright}Driscoll and Ong, {Kai Ren} and Deborah Osio and Nicola Ragge and Jonathan Berg and David Goudie and Catherine McWilliam and Andrew Jackson and Carol Gardiner and Ian Ellis and Alison Stewart and Wright, {Caroline F.} and Fitzpatrick, {David R.} and Firth, {Helen V.} and Hurles, {Matthew E.}",

note = "Funding Information: We thank the DDD families for participating, the DDD clinicians for recruiting patients, the Sanger Sample Management and Sequencing pipelines teams for generating the data, the Sanger Human Genome Informatics team for helping to process the exome data, and Nicola Whiffin for helpful comments on the manuscript. The study was approved by the UK Research Ethics Committee (10/H0305/83, granted by the Cambridge South Research Ethics Committee and GEN/284/12, granted by the Republic of Ireland Research Ethics Committee). This work has been conducted using the UK Biobank Resource under Application Number 44165. The DDD study presents independent research commissioned by the Health Innovation Challenge Fund (grant HICF-1009-003), a parallel funding partnership between the Wellcome Trust and the UK Department of Health, and the Wellcome Trust Sanger Institute (grant WT098051). The views expressed in this publication are those of the author(s) and not necessarily those of the Wellcome Trust or the UK Department of Health. The study has UK Research Ethics Committee approval (10/H0305/83, granted by the Cambridge South Research Ethics Committee and GEN/284/12, granted by the Republic of Ireland Research Ethics Committee). The research team acknowledges the support of the National Institutes for Health Research, through the Comprehensive Clinical Research Network. This study makes use of DECIPHER (http://decipher.sanger.ac.uk), which is funded by the Wellcome Trust. Publisher Copyright: {\textcopyright} 2021, The Author(s). Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",

year = "2021",

month = dec,

doi = "10.1038/s41467-020-20852-3",

language = "English",

volume = "12",

journal = "Nature Communications",

issn = "2041-1723",

publisher = "Nature Research",

}

Martin, HC, Gardner, EJ, Samocha, KE, Kaplanis, J, Akawi, N, Sifrim, A, Eberhardt, RY, Tavares, ALT, Neville, MDC, Niemi, MEK, Gallone, G, McRae, J, Wright, CF, Fitzpatrick, DR & Firth, HV & Hurles, ME 2021, 'The contribution of X-linked coding variation to severe developmental disorders', Nature Communications, vol. 12, 627. https://doi.org/10.1038/s41467-020-20852-3

TY - JOUR

T1 - The contribution of X-linked coding variation to severe developmental disorders

AU - Martin, Hilary C.

AU - Gardner, Eugene J.

AU - Samocha, Kaitlin E.

AU - Kaplanis, Joanna

AU - Akawi, Nadia

AU - Sifrim, Alejandro

AU - Eberhardt, Ruth Y.

AU - Tavares, Ana Lisa Taylor

AU - Neville, Matthew D. C.

AU - Niemi, Mari E. K.

AU - Gallone, Giuseppe

AU - McRae, Jeremy

AU - Borras, Silvia

AU - Clark, Caroline

AU - Dean, John

AU - Miedzybrodzka, Zosia

AU - Ross, Alison

AU - Tennant, Stephen

AU - Dabir, Tabib

AU - Donnelly, Deirdre

AU - Humphreys, Mervyn

AU - Magee, Alex

AU - McConnell, Vivienne

AU - McKee, Shane

AU - McNerlan, Susan

AU - Morrison, Patrick J.

AU - Rea, Gillian

AU - Stewart, Fiona

AU - Cole, Trevor

AU - Cooper, Nicola

AU - Cooper-Charles, Lisa

AU - Cox, Helen

AU - Islam, Lily

AU - Jarvis, Joanna

AU - Keelagher, Rebecca

AU - Lim, Derek

AU - McMullan, Dominic

AU - Morton, Jenny

AU - Naik, Swati

AU - O’Driscoll, Mary

AU - Ong, Kai Ren

AU - Osio, Deborah

AU - Ragge, Nicola

AU - Berg, Jonathan

AU - Goudie, David

AU - McWilliam, Catherine

AU - Jackson, Andrew

AU - Gardiner, Carol

AU - Ellis, Ian

AU - Stewart, Alison

AU - Wright, Caroline F.

AU - Fitzpatrick, David R.

AU - Firth, Helen V.

AU - Hurles, Matthew E.

N1 - Funding Information: We thank the DDD families for participating, the DDD clinicians for recruiting patients, the Sanger Sample Management and Sequencing pipelines teams for generating the data, the Sanger Human Genome Informatics team for helping to process the exome data, and Nicola Whiffin for helpful comments on the manuscript. The study was approved by the UK Research Ethics Committee (10/H0305/83, granted by the Cambridge South Research Ethics Committee and GEN/284/12, granted by the Republic of Ireland Research Ethics Committee). This work has been conducted using the UK Biobank Resource under Application Number 44165. The DDD study presents independent research commissioned by the Health Innovation Challenge Fund (grant HICF-1009-003), a parallel funding partnership between the Wellcome Trust and the UK Department of Health, and the Wellcome Trust Sanger Institute (grant WT098051). The views expressed in this publication are those of the author(s) and not necessarily those of the Wellcome Trust or the UK Department of Health. The study has UK Research Ethics Committee approval (10/H0305/83, granted by the Cambridge South Research Ethics Committee and GEN/284/12, granted by the Republic of Ireland Research Ethics Committee). The research team acknowledges the support of the National Institutes for Health Research, through the Comprehensive Clinical Research Network. This study makes use of DECIPHER (http://decipher.sanger.ac.uk), which is funded by the Wellcome Trust. Publisher Copyright: © 2021, The Author(s). Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/12

Y1 - 2021/12

N2 - 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.

AB - 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.

KW - Genetic association study

KW - Medical genetics

KW - Neurodevelopmental disorders

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U2 - 10.1038/s41467-020-20852-3

DO - 10.1038/s41467-020-20852-3

M3 - Article

C2 - 33504798

AN - SCOPUS:85099943870

SN - 2041-1723

VL - 12

JO - Nature Communications

JF - Nature Communications

M1 - 627

ER -

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

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