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A Genome-Wide Association Study of Prediabetes Status Change
We conducted the first genome-wide association study of prediabetes status change (to diabetes or normal glycaemia) among 900 White participants of the Atherosclerosis Risk in Communities (ARIC) study. Single nucleotide polymorphism (SNP)-based analysis was performed by logistic regression models, c...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9234217/ https://www.ncbi.nlm.nih.gov/pubmed/35769078 http://dx.doi.org/10.3389/fendo.2022.881633 |
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author | Liu, Tingting Li, Hongjin Conley, Yvette P. Primack, Brian A. Wang, Jing Lo, Wen-Juo Li, Changwei |
author_facet | Liu, Tingting Li, Hongjin Conley, Yvette P. Primack, Brian A. Wang, Jing Lo, Wen-Juo Li, Changwei |
author_sort | Liu, Tingting |
collection | PubMed |
description | We conducted the first genome-wide association study of prediabetes status change (to diabetes or normal glycaemia) among 900 White participants of the Atherosclerosis Risk in Communities (ARIC) study. Single nucleotide polymorphism (SNP)-based analysis was performed by logistic regression models, controlling for age, gender, body mass index, and the first 3 genetic principal components. Gene-based analysis was conducted by combining SNP-based p values using effective Chi-square test method. Promising SNPs (p < 1×10-5) and genes (p < 1×10-4) were further evaluated for replication among 514 White participants of the Framingham Heart Study (FHS). To accommodate familial correlations, generalized estimation equation models were applied for SNP-based analyses in the FHS. Analysis results across ARIC and FHS were combined using inverse-variance-weighted meta-analysis method for SNPs and Fisher’s method for genes. We robustly identified 5 novel genes that are associated with prediabetes status change using gene-based analyses, including SGCZ (ARIC p = 9.93×10-6, FHS p = 2.00×10-3, Meta p = 3.72×10-7) at 8p22, HPSE2 (ARIC p = 8.26×10-19, FHS p = 5.85×10-3, Meta p < 8.26×10-19) at 10q24.2, ADGRA1 (ARIC p = 1.34×10-5, FHS p = 1.13×10-3, Meta p = 2.88×10-7) at 10q26.3, GLB1L3 (ARIC p = 3.71×10-6, FHS p = 4.51×10-3, Meta p = 3.16×10-7) at 11q25, and PCSK6 (ARIC p = 6.51×10-6, FHS p = 1.10×10-2, Meta p = 1.25×10-6) at 15q26.3. eQTL analysis indicated that these genes were highly expressed in tissues related to diabetes development. However, we were not able to identify any novel locus in single SNP-based analysis. Future large scale genomic studies of prediabetes status change are warranted. |
format | Online Article Text |
id | pubmed-9234217 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92342172022-06-28 A Genome-Wide Association Study of Prediabetes Status Change Liu, Tingting Li, Hongjin Conley, Yvette P. Primack, Brian A. Wang, Jing Lo, Wen-Juo Li, Changwei Front Endocrinol (Lausanne) Endocrinology We conducted the first genome-wide association study of prediabetes status change (to diabetes or normal glycaemia) among 900 White participants of the Atherosclerosis Risk in Communities (ARIC) study. Single nucleotide polymorphism (SNP)-based analysis was performed by logistic regression models, controlling for age, gender, body mass index, and the first 3 genetic principal components. Gene-based analysis was conducted by combining SNP-based p values using effective Chi-square test method. Promising SNPs (p < 1×10-5) and genes (p < 1×10-4) were further evaluated for replication among 514 White participants of the Framingham Heart Study (FHS). To accommodate familial correlations, generalized estimation equation models were applied for SNP-based analyses in the FHS. Analysis results across ARIC and FHS were combined using inverse-variance-weighted meta-analysis method for SNPs and Fisher’s method for genes. We robustly identified 5 novel genes that are associated with prediabetes status change using gene-based analyses, including SGCZ (ARIC p = 9.93×10-6, FHS p = 2.00×10-3, Meta p = 3.72×10-7) at 8p22, HPSE2 (ARIC p = 8.26×10-19, FHS p = 5.85×10-3, Meta p < 8.26×10-19) at 10q24.2, ADGRA1 (ARIC p = 1.34×10-5, FHS p = 1.13×10-3, Meta p = 2.88×10-7) at 10q26.3, GLB1L3 (ARIC p = 3.71×10-6, FHS p = 4.51×10-3, Meta p = 3.16×10-7) at 11q25, and PCSK6 (ARIC p = 6.51×10-6, FHS p = 1.10×10-2, Meta p = 1.25×10-6) at 15q26.3. eQTL analysis indicated that these genes were highly expressed in tissues related to diabetes development. However, we were not able to identify any novel locus in single SNP-based analysis. Future large scale genomic studies of prediabetes status change are warranted. Frontiers Media S.A. 2022-06-13 /pmc/articles/PMC9234217/ /pubmed/35769078 http://dx.doi.org/10.3389/fendo.2022.881633 Text en Copyright © 2022 Liu, Li, Conley, Primack, Wang, Lo and Li https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Liu, Tingting Li, Hongjin Conley, Yvette P. Primack, Brian A. Wang, Jing Lo, Wen-Juo Li, Changwei A Genome-Wide Association Study of Prediabetes Status Change |
title | A Genome-Wide Association Study of Prediabetes Status Change |
title_full | A Genome-Wide Association Study of Prediabetes Status Change |
title_fullStr | A Genome-Wide Association Study of Prediabetes Status Change |
title_full_unstemmed | A Genome-Wide Association Study of Prediabetes Status Change |
title_short | A Genome-Wide Association Study of Prediabetes Status Change |
title_sort | genome-wide association study of prediabetes status change |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9234217/ https://www.ncbi.nlm.nih.gov/pubmed/35769078 http://dx.doi.org/10.3389/fendo.2022.881633 |
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