Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p

iPSYCH Consortium; ASD Working Group of the Psychiatric Genomics Consortium; ADHD Working Group of the Psychiatric Genomics Consortium; Daniel J. Weiner; Emi Ling; Serkan Erdin; Derek J.C. Tai; Rachita Yadav; Jakob Grove; Jack M. Fu; Ajay Nadig; Caitlin E. Carey; Nikolas Baya; Jonas Bybjerg-Grauholm; Preben B. Mortensen; Thomas Werge; Ditte Demontis; Ole Mors; Merete Nordentoft; Thomas D. Als; Marie Baekvad-Hansen; Anders Rosengren; Alexandra Havdahl; Anne Hedemand; Aarno Palotie; Aravinda Chakravarti; Dan Arking; Arvis Sulovari; Anna Starnawska; Bhooma Thiruvahindrapuram; Christiaan de Leeuw; Caitlin Carey; Christine Ladd-Acosta; Celia van der Merwe; Bernie Devlin; Edwin H. Cook; Evan Eichler; Elisabeth Corfield; Gwen Dieleman; Gerard Schellenberg; Hakon Hakonarson; Hilary Coon; Isabel Dziobek; Jacob Vorstman; Jessica Girault; James S. Sutcliffe; Jinjie Duan; John Nurnberger; Joachim Hallmayer; Joseph Buxbaum; Magdalena Janecka; Edmund Sonuga-Barke; Jonna Kuntsi

doi:10.1038/s41588-022-01203-y

Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p

iPSYCH Consortium, ASD Working Group of the Psychiatric Genomics Consortium, ADHD Working Group of the Psychiatric Genomics Consortium, Daniel J. Weiner^*, Emi Ling, Serkan Erdin, Derek J.C. Tai, Rachita Yadav, Jakob Grove, Jack M. Fu, Ajay Nadig, Caitlin E. Carey, Nikolas Baya, Jonas Bybjerg-Grauholm, Preben B. Mortensen, Thomas Werge, Ditte Demontis, Ole Mors, Merete Nordentoft, Thomas D. AlsMarie Baekvad-Hansen, Anders Rosengren, Alexandra Havdahl, Anne Hedemand, Aarno Palotie, Aravinda Chakravarti, Dan Arking, Arvis Sulovari, Anna Starnawska, Bhooma Thiruvahindrapuram, Christiaan de Leeuw, Caitlin Carey, Christine Ladd-Acosta, Celia van der Merwe, Bernie Devlin, Edwin H. Cook, Evan Eichler, Elisabeth Corfield, Gwen Dieleman, Gerard Schellenberg, Hakon Hakonarson, Hilary Coon, Isabel Dziobek, Jacob Vorstman, Jessica Girault, James S. Sutcliffe, Jinjie Duan, John Nurnberger, Joachim Hallmayer, Joseph Buxbaum, Magdalena Janecka, Edmund Sonuga-Barke, Jonna Kuntsi

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

Abstract

The canonical paradigm for converting genetic association to mechanism involves iteratively mapping individual associations to the proximal genes through which they act. In contrast, in the present study we demonstrate the feasibility of extracting biological insights from a very large region of the genome and leverage this strategy to study the genetic influences on autism. Using a new statistical approach, we identified the 33-Mb p-arm of chromosome 16 (16p) as harboring the greatest excess of autism’s common polygenic influences. The region also includes the mechanistically cryptic and autism-associated 16p11.2 copy number variant. Analysis of RNA-sequencing data revealed that both the common polygenic influences within 16p and the 16p11.2 deletion were associated with decreased average gene expression across 16p. The transcriptional effects of the rare deletion and diffuse common variation were correlated at the level of individual genes and analysis of Hi-C data revealed patterns of chromatin contact that may explain this transcriptional convergence. These results reflect a new approach for extracting biological insight from genetic association data and suggest convergence of common and rare genetic influences on autism at 16p.

Original language	English
Pages (from-to)	1630-1639
Number of pages	10
Journal	Nature Genetics
Volume	54
Issue number	11
Early online date	24 Oct 2022
DOIs	https://doi.org/10.1038/s41588-022-01203-y
Publication status	Published - Nov 2022

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10.1038/s41588-022-01203-y

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iPSYCH Consortium, ASD Working Group of the Psychiatric Genomics Consortium, ADHD Working Group of the Psychiatric Genomics Consortium, Weiner, D. J., Ling, E., Erdin, S., Tai, D. J. C., Yadav, R., Grove, J., Fu, J. M., Nadig, A., Carey, C. E., Baya, N., Bybjerg-Grauholm, J., Mortensen, P. B., Werge, T., Demontis, D., Mors, O., Nordentoft, M., ... Kuntsi, J. (2022). Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p. Nature Genetics, 54(11), 1630-1639. https://doi.org/10.1038/s41588-022-01203-y

@article{63dceb229c6745f88dc48693ba675b11,

title = "Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p",

abstract = "The canonical paradigm for converting genetic association to mechanism involves iteratively mapping individual associations to the proximal genes through which they act. In contrast, in the present study we demonstrate the feasibility of extracting biological insights from a very large region of the genome and leverage this strategy to study the genetic influences on autism. Using a new statistical approach, we identified the 33-Mb p-arm of chromosome 16 (16p) as harboring the greatest excess of autism{\textquoteright}s common polygenic influences. The region also includes the mechanistically cryptic and autism-associated 16p11.2 copy number variant. Analysis of RNA-sequencing data revealed that both the common polygenic influences within 16p and the 16p11.2 deletion were associated with decreased average gene expression across 16p. The transcriptional effects of the rare deletion and diffuse common variation were correlated at the level of individual genes and analysis of Hi-C data revealed patterns of chromatin contact that may explain this transcriptional convergence. These results reflect a new approach for extracting biological insight from genetic association data and suggest convergence of common and rare genetic influences on autism at 16p.",

author = "{iPSYCH Consortium} and {ASD Working Group of the Psychiatric Genomics Consortium} and {ADHD Working Group of the Psychiatric Genomics Consortium} and Weiner, {Daniel J.} and Emi Ling and Serkan Erdin and Tai, {Derek J.C.} and Rachita Yadav and Jakob Grove and Fu, {Jack M.} and Ajay Nadig and Carey, {Caitlin E.} and Nikolas Baya and Jonas Bybjerg-Grauholm and Mortensen, {Preben B.} and Thomas Werge and Ditte Demontis and Ole Mors and Merete Nordentoft and Als, {Thomas D.} and Marie Baekvad-Hansen and Anders Rosengren and Alexandra Havdahl and Anne Hedemand and Aarno Palotie and Aravinda Chakravarti and Dan Arking and Arvis Sulovari and Anna Starnawska and Bhooma Thiruvahindrapuram and {de Leeuw}, Christiaan and Caitlin Carey and Christine Ladd-Acosta and {van der Merwe}, Celia and Bernie Devlin and Cook, {Edwin H.} and Evan Eichler and Elisabeth Corfield and Gwen Dieleman and Gerard Schellenberg and Hakon Hakonarson and Hilary Coon and Isabel Dziobek and Jacob Vorstman and Jessica Girault and Sutcliffe, {James S.} and Jinjie Duan and John Nurnberger and Joachim Hallmayer and Joseph Buxbaum and Magdalena Janecka and Edmund Sonuga-Barke and Jonna Kuntsi",

note = "Funding Information: We thank the following for their generous support of this work: the SFARI (grant no. 704413 to E.B.R. and L.J.O.), the NIMH (grant nos. F30MH129009 to D.J.W., R01MH111813 to E.B.R., R01MH115957 to M.E.T. and 1R01MH124851-01 to A.D.B.), the National Institute of General Medical Sciences (grant nos. T32GM007753 and T32GM144273 to A.N. and D.J.W.), the National Institute of Child Health and Development (grant no. R01HD096326 to M.E.T.), the National Institute of Neurological Disorders and Stroke (grant no. R01NS093200 to M.E.T.), the National Library of Medicine (grant no. T15LM007092 to D.J.W.), the Lundbeck Foundation (grant nos. R102-A9118, R155-2014-1724, and R248-2017-2003 to iPSYCH), the Novo Nordisk Foundation (to the Danish National Biobank) and the universities and university hospitals of Aarhus and Copenhagen. 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 through a grant to A.D.B. Human tissue was obtained from the NIH NeuroBioBank. We thank all the families who participated in the cohorts included in this analysis, without whom this work would not have been possible. We also thank R. Collins and R. Walters for their assistance with these analyses. Finally, we thank the following members of the ADHD Working Group of the PGC: A. R. Hammerschlag, A. Corsico, A. Havdahl, A. Todorov, A. Charach, A. Ashley-Koch, A. Doyle, A. Hervas, A. Miranda, A. Borglum, A. Scherag, A. Thapar, A. Rommel, A. Starnawska, A. Wheeler, A. Rothenberger, A. Arnatkeviciute, B. Franke, B. Neale, C. Liao, C. Hartman, C. Burton, C. Cornforth, C. Bandeira, C. Bau, C. Sanchez, D. Posthuma, F. Cerrato, F. Mulas, F. Degenhardt, G. C. A. Martins, G. P. Stromstad Knudsen, H. C. Steinhausen, H. Hakonarson, H.-C. Steinhausen, H. Roeyers, H.-W. Kim, I. Gizer, I. Waldman, I. Brikell, J. Crosbie, J. Agnew-Blais, J. Martin, J. Gelernter, J. Hebebrand, J. A. Ramos-Quiroga, J. Biederman, J. Sergeant, J. Gamble, J. Pinsonneault, J. Deckert, K. Langley, L. Yang, L. Kent, L. Rohde, M. Mattheisen, M. J. Arranz Calderun, M. Soler Artigas, M. Ribases, M. Mariano, M. Gill, M. O{\textquoteright}Donovan, M. Casas, M. Bayes, N. Martin, N. P. Ole Mors, N. Williams, N. Roth Mota, O. A. Andreassen, P. Sham, P. Sullivan, P. Arnold, P. Lichtenstein, P. Rovira, P. Holmans, P. Asherson, P. B. Mortensen, R. Guerra, R. Walters, R. Anney, R. Ebstein, R. Karlsson Linn{\'e}r, R. Joober, R. Oades, R. Schachar, S. M. Sengupta, S. Johansson, S. H. Witt, S. Nelson, S. Smalley, S. Scherag, T. Zayats, T. Werge, T. Silk, T. Polderman, T. Banaschewski, T. Altar, V. Manikandan, Y. Zhang, Y. Athanasiadis and Y. Wang. Support for the title page creation and format was provided by AuthorArranger, a tool developed at the National Cancer Institute. Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

month = nov,

doi = "10.1038/s41588-022-01203-y",

language = "English",

volume = "54",

pages = "1630--1639",

journal = "Nature Genetics",

issn = "1061-4036",

number = "11",

}

iPSYCH Consortium, ASD Working Group of the Psychiatric Genomics Consortium, ADHD Working Group of the Psychiatric Genomics Consortium, Weiner, DJ, Ling, E, Erdin, S, Tai, DJC, Yadav, R, Grove, J, Fu, JM, Nadig, A, Carey, CE, Baya, N, Bybjerg-Grauholm, J, Mortensen, PB, Werge, T, Demontis, D, Mors, O, Nordentoft, M, Als, TD, Baekvad-Hansen, M, Rosengren, A, Havdahl, A, Hedemand, A, Palotie, A, Chakravarti, A, Arking, D, Sulovari, A, Starnawska, A, Thiruvahindrapuram, B, de Leeuw, C, Carey, C, Ladd-Acosta, C, van der Merwe, C, Devlin, B, Cook, EH, Eichler, E, Corfield, E, Dieleman, G, Schellenberg, G, Hakonarson, H, Coon, H, Dziobek, I, Vorstman, J, Girault, J, Sutcliffe, JS, Duan, J, Nurnberger, J, Hallmayer, J, Buxbaum, J, Janecka, M , Sonuga-Barke, E & Kuntsi, J 2022, 'Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p', Nature Genetics, vol. 54, no. 11, pp. 1630-1639. https://doi.org/10.1038/s41588-022-01203-y

Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p. / iPSYCH Consortium; ASD Working Group of the Psychiatric Genomics Consortium; ADHD Working Group of the Psychiatric Genomics Consortium et al.
In: Nature Genetics, Vol. 54, No. 11, 11.2022, p. 1630-1639.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p

AU - iPSYCH Consortium

AU - ASD Working Group of the Psychiatric Genomics Consortium

AU - ADHD Working Group of the Psychiatric Genomics Consortium

AU - Weiner, Daniel J.

AU - Ling, Emi

AU - Erdin, Serkan

AU - Tai, Derek J.C.

AU - Yadav, Rachita

AU - Grove, Jakob

AU - Fu, Jack M.

AU - Nadig, Ajay

AU - Carey, Caitlin E.

AU - Baya, Nikolas

AU - Bybjerg-Grauholm, Jonas

AU - Mortensen, Preben B.

AU - Werge, Thomas

AU - Demontis, Ditte

AU - Mors, Ole

AU - Nordentoft, Merete

AU - Als, Thomas D.

AU - Baekvad-Hansen, Marie

AU - Rosengren, Anders

AU - Havdahl, Alexandra

AU - Hedemand, Anne

AU - Palotie, Aarno

AU - Chakravarti, Aravinda

AU - Arking, Dan

AU - Sulovari, Arvis

AU - Starnawska, Anna

AU - Thiruvahindrapuram, Bhooma

AU - de Leeuw, Christiaan

AU - Carey, Caitlin

AU - Ladd-Acosta, Christine

AU - van der Merwe, Celia

AU - Devlin, Bernie

AU - Cook, Edwin H.

AU - Eichler, Evan

AU - Corfield, Elisabeth

AU - Dieleman, Gwen

AU - Schellenberg, Gerard

AU - Hakonarson, Hakon

AU - Coon, Hilary

AU - Dziobek, Isabel

AU - Vorstman, Jacob

AU - Girault, Jessica

AU - Sutcliffe, James S.

AU - Duan, Jinjie

AU - Nurnberger, John

AU - Hallmayer, Joachim

AU - Buxbaum, Joseph

AU - Janecka, Magdalena

AU - Sonuga-Barke, Edmund

AU - Kuntsi, Jonna

N1 - Funding Information: We thank the following for their generous support of this work: the SFARI (grant no. 704413 to E.B.R. and L.J.O.), the NIMH (grant nos. F30MH129009 to D.J.W., R01MH111813 to E.B.R., R01MH115957 to M.E.T. and 1R01MH124851-01 to A.D.B.), the National Institute of General Medical Sciences (grant nos. T32GM007753 and T32GM144273 to A.N. and D.J.W.), the National Institute of Child Health and Development (grant no. R01HD096326 to M.E.T.), the National Institute of Neurological Disorders and Stroke (grant no. R01NS093200 to M.E.T.), the National Library of Medicine (grant no. T15LM007092 to D.J.W.), the Lundbeck Foundation (grant nos. R102-A9118, R155-2014-1724, and R248-2017-2003 to iPSYCH), the Novo Nordisk Foundation (to the Danish National Biobank) and the universities and university hospitals of Aarhus and Copenhagen. 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 through a grant to A.D.B. Human tissue was obtained from the NIH NeuroBioBank. We thank all the families who participated in the cohorts included in this analysis, without whom this work would not have been possible. We also thank R. Collins and R. Walters for their assistance with these analyses. Finally, we thank the following members of the ADHD Working Group of the PGC: A. R. Hammerschlag, A. Corsico, A. Havdahl, A. Todorov, A. Charach, A. Ashley-Koch, A. Doyle, A. Hervas, A. Miranda, A. Borglum, A. Scherag, A. Thapar, A. Rommel, A. Starnawska, A. Wheeler, A. Rothenberger, A. Arnatkeviciute, B. Franke, B. Neale, C. Liao, C. Hartman, C. Burton, C. Cornforth, C. Bandeira, C. Bau, C. Sanchez, D. Posthuma, F. Cerrato, F. Mulas, F. Degenhardt, G. C. A. Martins, G. P. Stromstad Knudsen, H. C. Steinhausen, H. Hakonarson, H.-C. Steinhausen, H. Roeyers, H.-W. Kim, I. Gizer, I. Waldman, I. Brikell, J. Crosbie, J. Agnew-Blais, J. Martin, J. Gelernter, J. Hebebrand, J. A. Ramos-Quiroga, J. Biederman, J. Sergeant, J. Gamble, J. Pinsonneault, J. Deckert, K. Langley, L. Yang, L. Kent, L. Rohde, M. Mattheisen, M. J. Arranz Calderun, M. Soler Artigas, M. Ribases, M. Mariano, M. Gill, M. O’Donovan, M. Casas, M. Bayes, N. Martin, N. P. Ole Mors, N. Williams, N. Roth Mota, O. A. Andreassen, P. Sham, P. Sullivan, P. Arnold, P. Lichtenstein, P. Rovira, P. Holmans, P. Asherson, P. B. Mortensen, R. Guerra, R. Walters, R. Anney, R. Ebstein, R. Karlsson Linnér, R. Joober, R. Oades, R. Schachar, S. M. Sengupta, S. Johansson, S. H. Witt, S. Nelson, S. Smalley, S. Scherag, T. Zayats, T. Werge, T. Silk, T. Polderman, T. Banaschewski, T. Altar, V. Manikandan, Y. Zhang, Y. Athanasiadis and Y. Wang. Support for the title page creation and format was provided by AuthorArranger, a tool developed at the National Cancer Institute. Publisher Copyright: © 2022, The Author(s).

PY - 2022/11

Y1 - 2022/11

N2 - The canonical paradigm for converting genetic association to mechanism involves iteratively mapping individual associations to the proximal genes through which they act. In contrast, in the present study we demonstrate the feasibility of extracting biological insights from a very large region of the genome and leverage this strategy to study the genetic influences on autism. Using a new statistical approach, we identified the 33-Mb p-arm of chromosome 16 (16p) as harboring the greatest excess of autism’s common polygenic influences. The region also includes the mechanistically cryptic and autism-associated 16p11.2 copy number variant. Analysis of RNA-sequencing data revealed that both the common polygenic influences within 16p and the 16p11.2 deletion were associated with decreased average gene expression across 16p. The transcriptional effects of the rare deletion and diffuse common variation were correlated at the level of individual genes and analysis of Hi-C data revealed patterns of chromatin contact that may explain this transcriptional convergence. These results reflect a new approach for extracting biological insight from genetic association data and suggest convergence of common and rare genetic influences on autism at 16p.

AB - The canonical paradigm for converting genetic association to mechanism involves iteratively mapping individual associations to the proximal genes through which they act. In contrast, in the present study we demonstrate the feasibility of extracting biological insights from a very large region of the genome and leverage this strategy to study the genetic influences on autism. Using a new statistical approach, we identified the 33-Mb p-arm of chromosome 16 (16p) as harboring the greatest excess of autism’s common polygenic influences. The region also includes the mechanistically cryptic and autism-associated 16p11.2 copy number variant. Analysis of RNA-sequencing data revealed that both the common polygenic influences within 16p and the 16p11.2 deletion were associated with decreased average gene expression across 16p. The transcriptional effects of the rare deletion and diffuse common variation were correlated at the level of individual genes and analysis of Hi-C data revealed patterns of chromatin contact that may explain this transcriptional convergence. These results reflect a new approach for extracting biological insight from genetic association data and suggest convergence of common and rare genetic influences on autism at 16p.

UR - http://www.scopus.com/inward/record.url?scp=85140719036&partnerID=8YFLogxK

U2 - 10.1038/s41588-022-01203-y

DO - 10.1038/s41588-022-01203-y

M3 - Article

C2 - 36280734

AN - SCOPUS:85140719036

SN - 1061-4036

VL - 54

SP - 1630

EP - 1639

JO - Nature Genetics

JF - Nature Genetics

IS - 11

ER -

Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p

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