The transcription factor Gli-similar 3 (GLIS3) is essential for the maturation pancreatic cells, as well as the control of insulin gene expression in adults .
GLIS3 interacts with transcription factors specific for beta cells to directly and indirectly activate insulin gene transcription in rat insulinoma cells . GLIS3 knockdown enhanced proinflammatory cytokines and palmitate-induced beta-cell death, suggesting that GLIS3 expression is necessary for beta-cell survival . Both T2DM and T1DM are thought to be caused by malfunction of these pathways. GLIS3 may also play a role in compensatory insulin resistance (IR)-induced beta-cell proliferation and expansion in mice, which can lead to T2DM if disturbed 
An association has been identified between common GLIS3 polymorphisms and T1DM, T2DM, and gestational diabetes mellitus (GDM), in addition to different measures of β-cell function, such as fasting blood glucose or Homeostatic Model Assessment of cell function (HOMA-B) . Although it has been suggested that T1DM and T2DM have a shared genetic loci, only a few susceptibility genes have been related to the two forms of DM, including GLIS3, cordon-bleu WH2 repeat protein (COBL) and insulin (INS) .
The current investigation investigated the possible relationship of the GLIS3 rs10758593 (A/G) gene polymorphism with T2DM patients based on previous findings. One hundred (100) T2DM patients from the Endocrinology Clinic and 100 non-diabetic control participants who were age and sex matched and satisfied the exclusion criteria were included in our research. Using real-time PCR, we looked for the GLIS3 rs10758593 (A/G) polymorphism in our chosen population.
Our results revealed the presence of the mutant genotype (AA) in 39% of the patients’ group and in 18% of the control group (p < 0.05). The AG (heterozygous) genotype was found in 61% of the patients’ group and in 81% of the control group (p < 0.05). Unexpectedly, the GG genotype was detected in only 1% of the controls, while it could not be detected in any of our patients’ samples. This may be attributed to the genetic variation in different population, and to relatively small sample size included in the study.
Our data showed that the frequencies of the mutant genotypes; AA and AG, significantly varied between patients and controls. This finding goes with the GWAS meta-analysis which demonstrated that rs10758593 A allele was associated with risk for T2DM in European population . According to Boesgaard et al., GLIS3 polymorphism is linked to a reduced glucose-stimulated insulin response, resulting in hyperglycemia and T2DM . Furthermore, GLIS3 polymorphism is linked to T2DM and impaired fasting glucose in the Chinese population, according to LIU and colleagues , which is largely mediated by poor beta-cell activity .
Several studies were also done with this SNP in T1DM patients [8,9,10]. Grant et al.  found that The A allele was related with an increased risk of T1DM in European population . Bradfield and his co-workers  found that The A allele was associated with risk for T1DM in Japanese population. On the other hand, Duarte and colleagues found no evidence of individual associations between the rs7020673 and rs10758593 SNPs and T1DM. They did state, however, that the frequency of haplotypes with more than three minor alleles of these SNPs was higher in T1DM patients compared to controls .
Dooley et al.  explained previous results by stating that there are numerous chromosomal loci that impact risk of both T1DM and T2DM and identified a high enrichment of T1DM link among known T2DM risk loci. Another study by Liston et al.  argued that T1DM and T2DM are both caused by β cell fragility, which results in significant cell death.
Therefore, given that the SNP identified is located in the intronic regions, the precise mechanisms by which these SNPs may contribute to T2DM pathogenesis are still unknown . After searching the database for potential functional evidence of the analyzed SNP, we discovered evidence of CTCF (transcriptional repressor) and CEBPB (CCAAT/enhancer-binding protein beta) transcription factor binding sites (TFBS) overlapping this SNP's position . Furthermore, Duarte et al.  discovered long noncoding RNA (lncRNA) predicted to bind in the positions of the rs7020673 and rs10758593 SNPs . As a result, the rs7020673C and rs1075859A alleles may influence GLIS3 gene expression by altering potential TFBS or lncRNA binding. The expression and regulation of GLIS3 are required for proper cell development and maintenance of postnatal function .
In our study, we attempted to investigate the relationship between genotypic distribution and glycemic control. When AA genotype patients were compared to AG genotype patients, there was a statistically significant increase in HbA1C. Furthermore, the AA genotype had a highly significant increase in fasting blood glucose, fasting insulin, and HOMA-IR. These findings were consistent with the findings of Duarte et al. , who encountered that HbA1c levels were higher in subjects with the rs10758593 A/A genotype compared to G allele carriers . Similarly, Aylward et al.  revealed that GLIS3 rs10758593 risk alleles were linked to higher fasting glucose levels and lower homeostatic model assessment for beta-cell function (HOMA-B). These findings suggest that the presence of the A allele is linked to insulin resistance and poor glycemic control .
We attempted to investigate the relationship between genotypic distribution and diabetic complications. Surprisingly, we discovered a statistically significant difference in genotypic distribution between patients with retinopathy and patients without retinopathy. According to Dimitri et al. , in mouse models, GLIS3 is expressed in a dynamic pattern during eye development, first in the dorsal optic vesicle and then in the lens and the retina, which supports the presentation of eye diseases in patients with GLIS3 mutations. On the contrary, Duarte et al.  in their study could not find statistical significant difference between patients with retinopathy and patients without retinopathy regarding genotypic distribution .
Although our results showed no statistically significant difference in kidney function test (creatinine, BUN and uric acid), however, our data revealed a statistical significant difference in urinary albumin/creatinine ratio (p < 0.05). Duarte et al.  did not find statistically significant difference between patients with and without nephropathy regarding genotypic distribution . In our study, we did not find statistically significant difference between patients with neuropathy and patients without neuropathy regarding GLIS3 gene polymorphism.
In our study, we found significant correlation between HbA1C and fasting glucose levels. Dave et al.  also found that HbA1 C level was increased in diabetics, and it showed correlation with fasting blood glucose. Same results has been reported by various workers as Shrestha et al. , Swetha , and Rosediani et al. . The more FPG values increase, the more HbA1c values increase. The increase in plasma glucose values contribute to bind glucose-hemoglobin more (glycation reaction) and consequently make higher values of HbA1c .
Moreover, we found significant correlation between HbA1C and fasting insulin and HOMA-IR. Similarly, Al-Hakeim et al.  found HbA1c increased in T2DM patients and had correlation with levels of fasting insulin, HOMA-IR. Also, Hou et al.  found significant correlation between HbA1c, fasting glucose levels, fasting insulin, and insulin resistance. Insulin resistance has a correlation with the decrease in fasting insulin value. As insulin maintains the glucose blood homeostasis by facilitating cellular glucose uptake, the increase in serum glucose will induce β-cells to increase insulin secretion. This will affect the increase in blood glucose value .
We found significant correlation between HbA1c and alb/creat ratio. This come in agreement with Haque et al.  who stated that serum creatinine and alb/creat ratio had significant positive correlation with HbA1c. Moreover, Chiu et al.  also reported that Higher HbA1C variability is more likely to progress to microalbuminuria. Fluctuating or persisting high glucose levels can induce oxidative stress, overproduction of reactive oxygen species, and endothelial dysfunction and contribute to microvascular (nephropathy, retinopathy, and neuropathy) in T2DM patients .
Many factors can explain the disparities in the findings and conclusions of diverse studies. Single-locus effects were shown to be insufficient to explain complex chronic illnesses. Thus, when the single polymorphism effect is absent or insufficient, it is critical to characterize the other gene polymorphisms associated with susceptibility, keeping in mind the concept of multilocus genetic interactions.
Furthermore, the duration of diabetes and other characteristics, such as differences in various genetics, environmental factors, ethnic stratification, research design variation, and sample size, vary between studies and impact the outcomes.
Our results provide the insight into the contribution of GLIS3 gene polymorphism 10758593(A/G) to T2DM in the Egyptian population. However, we encountered some limitations, such as the relatively small sample size. Therefore, further large, multi-ethnic studies on larger sample size are recommended to clarify the statistical significance of the association of the A allele and the AA genotype of the GLIS3 rs 10758593 with T2DM and to confirm the role of GLIS3 gene polymorphism in disease susceptibility and pathogenesis.