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Meta-Analysis
. 2022 Jun 13:13:881633.
doi: 10.3389/fendo.2022.881633. eCollection 2022.

A Genome-Wide Association Study of Prediabetes Status Change

Tingting Liu  1 , Hongjin Li  2 , Yvette P Conley  3 , Brian A Primack  4 , Jing Wang  1 , Wen-Juo Lo  4 , Changwei Li  5
Affiliations
Meta-Analysis

A Genome-Wide Association Study of Prediabetes Status Change

Tingting Liu et al. Front Endocrinol (Lausanne). .

Abstract

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.

Keywords: diabetes mellitus; genome-wide association study; normoglycemia; prediabetes status change; type 2.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow Chart of Participant Selection in ARIC Cohort Study.
Figure 2
Figure 2
Flow Chart of Participant Selection in FHS Cohort Study.
Figure 3
Figure 3
Manhattan Plot for Genome-Wide Single SNP-Based Analysis for Prediabetes Status Change.
Figure 4
Figure 4
QQ Plot for Single SNP-Based Analysis Results.
Figure 5
Figure 5
Manhattan Plot for Genome-Wide Gene-Based Analysis Results.
Figure 6
Figure 6
QQ Plot for Gene-Based Analysis Results.
Figure 7
Figure 7
Regional Association Plots for Significant Genes.
See this image and copyright information in PMC

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