Whole-genome sequence-based analysis of thyroid function

Taylor, Peter N., Porcu, Eleonora, Chew, Shelby, Campbell, Purdey J., Traglia, Michela, Brown, Suzanne J., Mullin, Benjamin H., Shihab, Hashem A., Min, Josine, Walter, Klaudia, Memari, Yasin, Huang, Jie, Barnes, Michael R., Beilby, John P., Charoen, Pimphen, Danecek, Petr, Dudbridge, Frank, Forgetta, Vincenzo, Greenwood, Celia, Grundberg, Elin, Johnson, Andrew D., Hui, Jennie, Lim, Ee M., McCarthy, Shane, Muddyman, Dawn, Panicker, Vijay, Perry, John R. B., Bell, Jordana T., Yuan, Wei, Relton, Caroline, Gaunt, Tom, Schlessinger, David, Abecasis, Goncalo, Cucca, Francesco, Surdulescu, Gabriela L., Woltersdorf, Wolfram, Zeggini, Eleftheria, Zheng, Hou-Feng, Toniolo, Daniela, Dayan, Colin M., Naitza, Silvia, Walsh, John P., Spector, Tim, Smith, George Davey, Durbin, Richard, Richards, J. Brent, Sanna, Serena, Soranzo, Nicole, Timpson, Nicholas J., Wilson, Scott G., UK10K Consortium, Evans, David, Kemp, John, Visscher, Peter M. and Yang, Jian (2015) Whole-genome sequence-based analysis of thyroid function. Nature Communications, 6 5681.1-5681.10. doi:10.1038/ncomms6681

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Author Taylor, Peter N.
Porcu, Eleonora
Chew, Shelby
Campbell, Purdey J.
Traglia, Michela
Brown, Suzanne J.
Mullin, Benjamin H.
Shihab, Hashem A.
Min, Josine
Walter, Klaudia
Memari, Yasin
Huang, Jie
Barnes, Michael R.
Beilby, John P.
Charoen, Pimphen
Danecek, Petr
Dudbridge, Frank
Forgetta, Vincenzo
Greenwood, Celia
Grundberg, Elin
Johnson, Andrew D.
Hui, Jennie
Lim, Ee M.
McCarthy, Shane
Muddyman, Dawn
Panicker, Vijay
Perry, John R. B.
Bell, Jordana T.
Yuan, Wei
Relton, Caroline
Gaunt, Tom
Schlessinger, David
Abecasis, Goncalo
Cucca, Francesco
Surdulescu, Gabriela L.
Woltersdorf, Wolfram
Zeggini, Eleftheria
Zheng, Hou-Feng
Toniolo, Daniela
Dayan, Colin M.
Naitza, Silvia
Walsh, John P.
Spector, Tim
Smith, George Davey
Durbin, Richard
Richards, J. Brent
Sanna, Serena
Soranzo, Nicole
Timpson, Nicholas J.
Wilson, Scott G.
UK10K Consortium
Evans, David
Kemp, John
Visscher, Peter M.
Yang, Jian
Title Whole-genome sequence-based analysis of thyroid function
Journal name Nature Communications   Check publisher's open access policy
ISSN 2041-1723
Publication date 2015-03-06
Year available 2015
Sub-type Article (original research)
DOI 10.1038/ncomms6681
Open Access Status DOI
Volume 6
Start page 5681.1
End page 5681.10
Total pages 10
Place of publication London, United Kingdom
Publisher Nature Publishing Group
Language eng
Subject 1600 Chemistry
1300 Biochemistry, Genetics and Molecular Biology
3100 Physics and Astronomy
Abstract Normal thyroid function is essential for health, but its genetic architecture remains poorly understood. Here, for the heritable thyroid traits thyrotropin (TSH) and free thyroxine (FT4), we analyse whole-genome sequence data from the UK10K project (N = 2,287). Using additional whole-genome sequence and deeply imputed data sets, we report meta-analysis results for common variants (MAF >= 1%) associated with TSH and FT4 (N = 16,335). For TSH, we identify a novel variant in SYN2 (MAF = 23.5%, P = 6.15 x 10(-9)) and a new independent variant in PDE8B (MAF = 10.4%, P = 5.94 x 10(-14)). For FT4, we report a low-frequency variant near B4GALT6/ SLC25A52 (MAF = 3.2%, P = 1.27 x 10(-9)) tagging a rare TTR variant (MAF = 0.4%, P = 2.14 x 10(-11)). All common variants explain >= 20% of the variance in TSH and FT4. Analysis of rare variants (MAF<1%) using sequence kernel association testing reveals a novel association with FT4 in NRG1. Our results demonstrate that increased coverage in whole-genome sequence association studies identifies novel variants associated with thyroid function.
Formatted abstract
Normal thyroid function is essential for health, but its genetic architecture remains poorly understood. Here, for the heritable thyroid traits thyrotropin (TSH) and free ​thyroxine (FT4), we analyse whole-genome sequence data from the UK10K project (N=2,287). Using additional whole-genome sequence and deeply imputed data sets, we report meta-analysis results for common variants (MAF≥1%) associated with TSH and FT4 (N=16,335). For TSH, we identify a novel variant in ​SYN2 (MAF=23.5%, P=6.15 × 10−9) and a new independent variant in ​PDE8B (MAF=10.4%, P=5.94 × 10−14). For FT4, we report a low-frequency variant near ​B4GALT6/​SLC25A52 (MAF=3.2%, P=1.27 × 10−9) tagging a rare ​TTR variant (MAF=0.4%, P=2.14 × 10−11). All common variants explain ≥20% of the variance in TSH and FT4. Analysis of rare variants (MAF<1%) using sequence kernel association testing reveals a novel association with FT4 in ​NRG1. Our results demonstrate that increased coverage in whole-genome sequence association studies identifies novel variants associated with thyroid function.
Keyword Multidisciplinary Sciences
Science & Technology - Other Topics
Q-Index Code C1
Q-Index Status Provisional Code
Grant ID WT091310
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Queensland Brain Institute Publications
Official 2016 Collection
UQ Diamantina Institute Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 27 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 28 times in Scopus Article | Citations
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