Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p
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Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p. / Weiner, Daniel J.; Ling, Emi; Erdin, Serkan; Tai, Derek J.C.; Yadav, Rachita; Grove, Jakob; Fu, Jack M.; Nadig, Ajay; Carey, Caitlin; Baya, Nikolas; Bybjerg-Grauholm, Jonas; Mortensen, Preben B.; Werge, Thomas; Demontis, Ditte; Mors, Ole; Nordentoft, Merete; Als, Thomas D.; Baekvad-Hansen, Marie; Rosengren, Anders; Havdahl, Alexandra; Hedemand, Anne; Palotie, Aarno; Chakravarti, Aravinda; Arking, Dan; Sulovari, Arvis; Starnawska, Anna; Thiruvahindrapuram, Bhooma; de Leeuw, Christiaan; Carey, Caitlin; Ladd-Acosta, Christine; van der Merwe, Celia; Devlin, Bernie; Cook, Edwin H.; Eichler, Evan; Corfield, Elisabeth; Dieleman, Gwen; Schellenberg, Gerard; Hakonarson, Hakon; Coon, Hilary; Dziobek, Isabel; Vorstman, Jacob; Girault, Jessica; Sutcliffe, James S.; Duan, Jinjie; Nurnberger, John; Hallmayer, Joachim; Buxbaum, Joseph; Hinney, Anke; Larsson, Henrik; Dalsgaard, Soren; iPSYCH Consortium; ASD Working Group of the Psychiatric Genomics Consortium; ADHD Working Group of the Psychiatric Genomics Consortium.
I: Nature Genetics, Bind 54, 2022, s. 1630-1639.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p
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
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 - Hinney, Anke
AU - Larsson, Henrik
AU - Dalsgaard, Soren
AU - iPSYCH Consortium
AU - ASD Working Group of the Psychiatric Genomics Consortium
AU - ADHD Working Group of the Psychiatric Genomics Consortium
N1 - Publisher Copyright: © 2022, The Author(s).
PY - 2022
Y1 - 2022
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.
U2 - 10.1038/s41588-022-01203-y
DO - 10.1038/s41588-022-01203-y
M3 - Journal article
C2 - 36280734
AN - SCOPUS:85140719036
VL - 54
SP - 1630
EP - 1639
JO - Nature Genetics
JF - Nature Genetics
SN - 1061-4036
ER -
ID: 324384192