SUPERGNOVA: local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits

Local genetic correlation quantifies the genetic similarity of complex traits in specific genomic regions. However, accurate estimation of local genetic correlation remains challenging, due to linkage disequilibrium in local genomic regions and sample overlap across studies. We introduce SUPERGNOVA,...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Yiliang, Lu, Qiongshi, Ye, Yixuan, Huang, Kunling, Liu, Wei, Wu, Yuchang, Zhong, Xiaoyuan, Li, Boyang, Yu, Zhaolong, Travers, Brittany G., Werling, Donna M., Li, James J., Zhao, Hongyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8422619/
https://www.ncbi.nlm.nih.gov/pubmed/34493297
http://dx.doi.org/10.1186/s13059-021-02478-w
_version_ 1783749311328157696
author Zhang, Yiliang
Lu, Qiongshi
Ye, Yixuan
Huang, Kunling
Liu, Wei
Wu, Yuchang
Zhong, Xiaoyuan
Li, Boyang
Yu, Zhaolong
Travers, Brittany G.
Werling, Donna M.
Li, James J.
Zhao, Hongyu
author_facet Zhang, Yiliang
Lu, Qiongshi
Ye, Yixuan
Huang, Kunling
Liu, Wei
Wu, Yuchang
Zhong, Xiaoyuan
Li, Boyang
Yu, Zhaolong
Travers, Brittany G.
Werling, Donna M.
Li, James J.
Zhao, Hongyu
author_sort Zhang, Yiliang
collection PubMed
description Local genetic correlation quantifies the genetic similarity of complex traits in specific genomic regions. However, accurate estimation of local genetic correlation remains challenging, due to linkage disequilibrium in local genomic regions and sample overlap across studies. We introduce SUPERGNOVA, a statistical framework to estimate local genetic correlations using summary statistics from genome-wide association studies. We demonstrate that SUPERGNOVA outperforms existing methods through simulations and analyses of 30 complex traits. In particular, we show that the positive yet paradoxical genetic correlation between autism spectrum disorder and cognitive performance could be explained by two etiologically distinct genetic signatures with bidirectional local genetic correlations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02478-w.
format Online
Article
Text
id pubmed-8422619
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-84226192021-09-09 SUPERGNOVA: local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits Zhang, Yiliang Lu, Qiongshi Ye, Yixuan Huang, Kunling Liu, Wei Wu, Yuchang Zhong, Xiaoyuan Li, Boyang Yu, Zhaolong Travers, Brittany G. Werling, Donna M. Li, James J. Zhao, Hongyu Genome Biol Method Local genetic correlation quantifies the genetic similarity of complex traits in specific genomic regions. However, accurate estimation of local genetic correlation remains challenging, due to linkage disequilibrium in local genomic regions and sample overlap across studies. We introduce SUPERGNOVA, a statistical framework to estimate local genetic correlations using summary statistics from genome-wide association studies. We demonstrate that SUPERGNOVA outperforms existing methods through simulations and analyses of 30 complex traits. In particular, we show that the positive yet paradoxical genetic correlation between autism spectrum disorder and cognitive performance could be explained by two etiologically distinct genetic signatures with bidirectional local genetic correlations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02478-w. BioMed Central 2021-09-07 /pmc/articles/PMC8422619/ /pubmed/34493297 http://dx.doi.org/10.1186/s13059-021-02478-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Method
Zhang, Yiliang
Lu, Qiongshi
Ye, Yixuan
Huang, Kunling
Liu, Wei
Wu, Yuchang
Zhong, Xiaoyuan
Li, Boyang
Yu, Zhaolong
Travers, Brittany G.
Werling, Donna M.
Li, James J.
Zhao, Hongyu
SUPERGNOVA: local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits
title SUPERGNOVA: local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits
title_full SUPERGNOVA: local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits
title_fullStr SUPERGNOVA: local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits
title_full_unstemmed SUPERGNOVA: local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits
title_short SUPERGNOVA: local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits
title_sort supergnova: local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8422619/
https://www.ncbi.nlm.nih.gov/pubmed/34493297
http://dx.doi.org/10.1186/s13059-021-02478-w
work_keys_str_mv AT zhangyiliang supergnovalocalgeneticcorrelationanalysisrevealsheterogeneousetiologicsharingofcomplextraits
AT luqiongshi supergnovalocalgeneticcorrelationanalysisrevealsheterogeneousetiologicsharingofcomplextraits
AT yeyixuan supergnovalocalgeneticcorrelationanalysisrevealsheterogeneousetiologicsharingofcomplextraits
AT huangkunling supergnovalocalgeneticcorrelationanalysisrevealsheterogeneousetiologicsharingofcomplextraits
AT liuwei supergnovalocalgeneticcorrelationanalysisrevealsheterogeneousetiologicsharingofcomplextraits
AT wuyuchang supergnovalocalgeneticcorrelationanalysisrevealsheterogeneousetiologicsharingofcomplextraits
AT zhongxiaoyuan supergnovalocalgeneticcorrelationanalysisrevealsheterogeneousetiologicsharingofcomplextraits
AT liboyang supergnovalocalgeneticcorrelationanalysisrevealsheterogeneousetiologicsharingofcomplextraits
AT yuzhaolong supergnovalocalgeneticcorrelationanalysisrevealsheterogeneousetiologicsharingofcomplextraits
AT traversbrittanyg supergnovalocalgeneticcorrelationanalysisrevealsheterogeneousetiologicsharingofcomplextraits
AT werlingdonnam supergnovalocalgeneticcorrelationanalysisrevealsheterogeneousetiologicsharingofcomplextraits
AT lijamesj supergnovalocalgeneticcorrelationanalysisrevealsheterogeneousetiologicsharingofcomplextraits
AT zhaohongyu supergnovalocalgeneticcorrelationanalysisrevealsheterogeneousetiologicsharingofcomplextraits

Ejemplares similares