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Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey
To identify genetic contributions to type 2 diabetes (T2D) and related glycemic traits (fasting glucose, fasting insulin, and HbA1c), we conducted genome-wide association analyses (GWAS) in up to 7,178 Chinese subjects from nine provinces in the China Health and Nutrition Survey (CHNS). We examined...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5886383/ https://www.ncbi.nlm.nih.gov/pubmed/29621232 http://dx.doi.org/10.1371/journal.pgen.1007275 |
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author | Spracklen, Cassandra N. Shi, Jinxiu Vadlamudi, Swarooparani Wu, Ying Zou, Meng Raulerson, Chelsea K. Davis, James P. Zeynalzadeh, Monica Jackson, Kayla Yuan, Wentao Wang, Haifeng Shou, Weihua Wang, Ying Luo, Jingchun Lange, Leslie A. Lange, Ethan M. Popkin, Barry M. Gordon-Larsen, Penny Du, Shufa Huang, Wei Mohlke, Karen L. |
author_facet | Spracklen, Cassandra N. Shi, Jinxiu Vadlamudi, Swarooparani Wu, Ying Zou, Meng Raulerson, Chelsea K. Davis, James P. Zeynalzadeh, Monica Jackson, Kayla Yuan, Wentao Wang, Haifeng Shou, Weihua Wang, Ying Luo, Jingchun Lange, Leslie A. Lange, Ethan M. Popkin, Barry M. Gordon-Larsen, Penny Du, Shufa Huang, Wei Mohlke, Karen L. |
author_sort | Spracklen, Cassandra N. |
collection | PubMed |
description | To identify genetic contributions to type 2 diabetes (T2D) and related glycemic traits (fasting glucose, fasting insulin, and HbA1c), we conducted genome-wide association analyses (GWAS) in up to 7,178 Chinese subjects from nine provinces in the China Health and Nutrition Survey (CHNS). We examined patterns of population structure within CHNS and found that allele frequencies differed across provinces, consistent with genetic drift and population substructure. We further validated 32 previously described T2D- and glycemic trait-loci, including G6PC2 and SIX3-SIX2 associated with fasting glucose. At G6PC2, we replicated a known fasting glucose-associated variant (rs34177044) and identified a second signal (rs2232326), a low-frequency (4%), probably damaging missense variant (S324P). A variant within the lead fasting glucose-associated signal at SIX3-SIX2 co-localized with pancreatic islet expression quantitative trait loci (eQTL) for SIX3, SIX2, and three noncoding transcripts. To identify variants functionally responsible for the fasting glucose association at SIX3-SIX2, we tested five candidate variants for allelic differences in regulatory function. The rs12712928-C allele, associated with higher fasting glucose and lower transcript expression level, showed lower transcriptional activity in reporter assays and increased binding to GABP compared to the rs12712928-G, suggesting that rs12712928-C contributes to elevated fasting glucose levels by disrupting an islet enhancer, resulting in reduced gene expression. Taken together, these analyses identified multiple loci associated with glycemic traits across China, and suggest a regulatory mechanism at the SIX3-SIX2 fasting glucose GWAS locus. |
format | Online Article Text |
id | pubmed-5886383 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-58863832018-04-20 Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey Spracklen, Cassandra N. Shi, Jinxiu Vadlamudi, Swarooparani Wu, Ying Zou, Meng Raulerson, Chelsea K. Davis, James P. Zeynalzadeh, Monica Jackson, Kayla Yuan, Wentao Wang, Haifeng Shou, Weihua Wang, Ying Luo, Jingchun Lange, Leslie A. Lange, Ethan M. Popkin, Barry M. Gordon-Larsen, Penny Du, Shufa Huang, Wei Mohlke, Karen L. PLoS Genet Research Article To identify genetic contributions to type 2 diabetes (T2D) and related glycemic traits (fasting glucose, fasting insulin, and HbA1c), we conducted genome-wide association analyses (GWAS) in up to 7,178 Chinese subjects from nine provinces in the China Health and Nutrition Survey (CHNS). We examined patterns of population structure within CHNS and found that allele frequencies differed across provinces, consistent with genetic drift and population substructure. We further validated 32 previously described T2D- and glycemic trait-loci, including G6PC2 and SIX3-SIX2 associated with fasting glucose. At G6PC2, we replicated a known fasting glucose-associated variant (rs34177044) and identified a second signal (rs2232326), a low-frequency (4%), probably damaging missense variant (S324P). A variant within the lead fasting glucose-associated signal at SIX3-SIX2 co-localized with pancreatic islet expression quantitative trait loci (eQTL) for SIX3, SIX2, and three noncoding transcripts. To identify variants functionally responsible for the fasting glucose association at SIX3-SIX2, we tested five candidate variants for allelic differences in regulatory function. The rs12712928-C allele, associated with higher fasting glucose and lower transcript expression level, showed lower transcriptional activity in reporter assays and increased binding to GABP compared to the rs12712928-G, suggesting that rs12712928-C contributes to elevated fasting glucose levels by disrupting an islet enhancer, resulting in reduced gene expression. Taken together, these analyses identified multiple loci associated with glycemic traits across China, and suggest a regulatory mechanism at the SIX3-SIX2 fasting glucose GWAS locus. Public Library of Science 2018-04-05 /pmc/articles/PMC5886383/ /pubmed/29621232 http://dx.doi.org/10.1371/journal.pgen.1007275 Text en © 2018 Spracklen et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Spracklen, Cassandra N. Shi, Jinxiu Vadlamudi, Swarooparani Wu, Ying Zou, Meng Raulerson, Chelsea K. Davis, James P. Zeynalzadeh, Monica Jackson, Kayla Yuan, Wentao Wang, Haifeng Shou, Weihua Wang, Ying Luo, Jingchun Lange, Leslie A. Lange, Ethan M. Popkin, Barry M. Gordon-Larsen, Penny Du, Shufa Huang, Wei Mohlke, Karen L. Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey |
title | Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey |
title_full | Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey |
title_fullStr | Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey |
title_full_unstemmed | Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey |
title_short | Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey |
title_sort | identification and functional analysis of glycemic trait loci in the china health and nutrition survey |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5886383/ https://www.ncbi.nlm.nih.gov/pubmed/29621232 http://dx.doi.org/10.1371/journal.pgen.1007275 |
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