Effect of Common Genetic Variants of Growth Arrest-Specific 6 Gene on Insulin Resistance, Obesity and Type 2 Diabetes in an Asian Population

<div><p>Objectives</p><p>Growth arrest-specific 6 (Gas6), a vitamin K-dependent protein, has been implicated in systemic inflammation, obesity, and insulin resistance (IR). Data from recent studies suggest that polymorphisms in the <i>Gas6</i> gene are associated with cardiovascular disorders and type 2 diabetes (T2D). However, the association of <i>Gas6</i> gene variants with obesity, IR, and T2D development has not been explored.</p><p>Materials and Methods</p><p>Four common single nucleotide polymorphisms (SNPs) in the <i>Gas6</i> gene were genotyped in 984 participants from the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance (SAPPHIRe) family cohort. An insulin suppression test was performed to determine IR based on steady-state plasma glucose (SSPG). Associations between IR indices and obesity, and SNP genotypes, based on previously-reported data for this cohort (Phase I), were analyzed. In the present follow-up study (Phase II), the effects of gene variants of <i>Gas6</i> on the progression to T2D were explored in individuals who were free of T2D in Phase I. The mean follow-up period for Phase II was 5.7 years.</p><p>Results</p><p>The mean age of the study population in Phase I was 49.5 years and 16.7% of individuals developed T2D during follow-up. After adjusting for covariates, three SNPs (rs8191973, rs8197974, and rs7323932) were found to be associated with SSPG levels (<i>p</i> = 0.007, <i>p</i> = 0.03, and <i>p</i> = 0.011, respectively). This association remained significant after multiple testing and showed a significant interaction with physical activity for SNP rs8191973. However, no other significant correlations were observed between <i>Gas6</i> polymorphisms and other indices of IR or obesity. A specific haplotype, AACG (from rs8191974, rs7323932, rs7331124, and rs8191973), was positively associated with SSPG levels (<i>p</i> = 0.0098). None of the polymorphisms were associated with an increased risk of T2D development.</p><p>Conclusions</p><p>Our results suggest that <i>Gas6</i> gene variants are associated with IR, although their effects on subsequent progression to T2D were minimal in this prospective Asian cohort.</p></div

LD between <i>Gas6</i> SNPs in the study cohort.

<p>Two SNPs, rs7323932 and rs8191973, show moderate LD with <i>r</i>² = 0.34, while other SNP pairs are in linkage equilibrium.</p

LD between <i>Gas6</i> SNPs in the study cohort.

<p>Two SNPs, rs7323932 and rs8191973, show moderate LD with <i>r</i>² = 0.34, while other SNP pairs are in linkage equilibrium.</p

Haplotype analysis of <i>Gas6</i> SNPs and SSPG.

<p>SNP: single nucleotide polymorphism, SSPG: steady-state plasma glucose.</p><p>Haplotype analysis of <i>Gas6</i> SNPs and SSPG.</p

Summary of characteristics in Phase I and Phase II studies.

<p>Data presented as mean ± standard deviation unless otherwise indicated. BMI: body mass index, DM: diabetes mellitus, FPG: fasting plasma glucose, FPI: fasting plasma insulin, HOMA-IR: homeostasis model assessment of insulin resistance, SSPG: steady-state plasma glucose, T2D: type 2 diabetes.</p><p>Summary of characteristics in Phase I and Phase II studies.</p

Analysis of peak sequences identifies TCF21 binding motifs as well as motifs for JUN related and other transcription factors that likely cooperate with TCF21.

<p>A) HOMER analysis of known TF motif enrichment within TCF21 peaks in the Ab_Shared data revealed several distinct motif families. The bHLH motif CAGCTG is identical to that attributed to TCF12, a known heterodimer partner of TCF21 [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005202#pgen.1005202.ref026" target="_blank">26</a>], and a second highly enriched bHLH motif CATCTG is attributed to nervous system TF OLIG2, suggesting that TCF21 can bind either of these two motifs. The bZIP motif TGA(G/C)TCA most closely resembles the binding sequence for TFs within the AP-1/ATF super family. Other motifs found to be enriched in the TCF21 peaks include those mediating binding of TEAD, CEBP, and ATF transcription factor family members, and an unknown element identified by ChIP-Seq with NANOG in human embryonic stem cells (ESC). B) Distribution (density) plots for top 7 motifs from panel A: TCF12, OLIG2, AP-1, unknown-NANOG (left), and CEBP, TEAD4, ATF1 (right). C) TCF21 binds in close proximity to JUN and JUND in a number of loci, including developmentally important <i>WT1</i> and <i>PDGFRB</i> loci.</p

Two TCF21 antibodies show overlapping patterns of TCF21 chromosomal binding.

<p>A) Two replicate experiments with Antibody 2 (Ab2) identified 4828 binding sites. All but 72 of these peaks were also identified by similar replicate experiments with Ab1, which recognized an additional 5695 peaks. B) In addition to analyzing data for each of the two antibody ChIP-Seq datasets, we have intersected those identified with both Ab1 and Ab2 (Ab_Shared), with the smaller of the peaks being employed if there was complete overlap of one versus the other, and the region of overlap used if the two peaks shared incomplete overlap. C) High throughput next-generation sequencing reads were aligned to the genome, peaks present in both biological replicates of each of the two antibody precipitations were identified by IDR, and visualized on the UCSC browser [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005202#pgen.1005202.ref008" target="_blank">8</a>]. In addition to the TCF21 ChIP-Seq data, also shown are ATAC-Seq data for HCASMC and DNse I hypersensitivity data obtained with human aortic smooth muscle cells (HAoSMC DHS) indicating that TCF21 peaks localize to regions of active chromatin conformation.</p

Characterization of TCF21 Downstream Target Regions Identifies a Transcriptional Network Linking Multiple Independent Coronary Artery Disease Loci

<div><p>To functionally link coronary artery disease (CAD) causal genes identified by genome wide association studies (GWAS), and to investigate the cellular and molecular mechanisms of atherosclerosis, we have used chromatin immunoprecipitation sequencing (ChIP-Seq) with the CAD associated transcription factor TCF21 in human coronary artery smooth muscle cells (HCASMC). Analysis of identified TCF21 target genes for enrichment of molecular and cellular annotation terms identified processes relevant to CAD pathophysiology, including “growth factor binding,” “matrix interaction,” and “smooth muscle contraction.” We characterized the canonical binding sequence for TCF21 as CAGCTG, identified AP-1 binding sites in TCF21 peaks, and by conducting ChIP-Seq for JUN and JUND in HCASMC confirmed that there is significant overlap between TCF21 and AP-1 binding loci in this cell type. Expression quantitative trait variation mapped to target genes of TCF21 was significantly enriched among variants with low <i>P</i>-values in the GWAS analyses, suggesting a possible functional interaction between TCF21 binding and causal variants in other CAD disease loci. Separate enrichment analyses found over-representation of TCF21 target genes among CAD associated genes, and linkage disequilibrium between TCF21 peak variation and that found in GWAS loci, consistent with the hypothesis that TCF21 may affect disease risk through interaction with other disease associated loci. Interestingly, enrichment for TCF21 target genes was also found among other genome wide association phenotypes, including height and inflammatory bowel disease, suggesting a functional profile important for basic cellular processes in non-vascular tissues. Thus, data and analyses presented here suggest that study of GWAS transcription factors may be a highly useful approach to identifying disease gene interactions and thus pathways that may be relevant to complex disease etiology.</p></div

Analysis of linkage disequilibrium between SNPs in GWAS loci of select phenotypes and TCF21 peak regions for chosen phenotypes.

<p>*GWAS catalog genes were supplemented with additional CAD genes identified from CARDIoGRAM+C4D, which are not currently included in the GWAS catalog. Traits with bold text are those significant at P<0.05 in both the GWAS gene enrichment analysis shown in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005202#pgen.1005202.t004" target="_blank">Table 4</a> and the current analysis.</p><p>Analysis of linkage disequilibrium between SNPs in GWAS loci of select phenotypes and TCF21 peak regions for chosen phenotypes.</p

Enrichment of TCF21 target genes from Ab_Shared among GWAS candidate trait genes using all GWAS genes as background and a permutation strategy to correct for the differences in the numbers of GWAS genes between traits.

<p>*GWAS catalog genes were supplemented with additional CAD genes identified from CARDIoGRAM+C4D, these genes are not currently included in the GWAS catalog.</p><p>Enrichment of TCF21 target genes from Ab_Shared among GWAS candidate trait genes using all GWAS genes as background and a permutation strategy to correct for the differences in the numbers of GWAS genes between traits.</p