However, the aim of our study is to examine the anthropometric data and biochemical parameters of the case and control groups to better understand the clinical profiles associated with Type 2 diabetes mellitus (T2DM). Furthermore, we also looking to investigate the genetic variations of the ITLN1 gene polymorphism and its association with T2DM, focusing on specific single nucleotide polymorphisms (SNPs) in the gene's exonic region. In addition, our study aims to explore the correlation between genotype and phenotype data and to analyze haplotypes, providing a comprehensive view of the genetic influences on T2DM risk in the North Indian population. These objectives will help to deepen our understanding of the role of ITLN1 gene polymorphisms in T2DM and may contribute to developing more targeted prevention and treatment strategies.

Participants were between 30 and 70 years old. Blood samples were taken only from those diagnosed with diabetes. Individuals with any comorbidities or a medical history of cardiovascular disease, severe gastrointestinal disorders, or any severe disease were excluded from the study. The parameters measured included BMI (Body Mass Index) glucose, urea, creatinine, triglycerides, cholesterol, HDL (High-Density lipoprotein), VLDL (very low-density Lipoprotein), Hb1Ac (Glycated hemoglobin), and LDL (low-density lipoprotein) levels.

This study was conducted in the Department of Biotechnology at Babasaheb Bhimrao Ambedkar University, Lucknow, from 2021 to 2024. It was a hospital-based case-control study.

Based on a 95% confidence limit and 5% confidence interval, the prevalence of type 2 diabetes is 9%. The minimal sample size is 139. The present study used a sample size 150 of each control and case participant. The study was ethically approved by the Institutional Ethics Committee of Sardar Patel Postgraduate Institute of Dental and Medical Sciences, Lucknow, with the registration number EC/NEW/INST/2020/1173.

Recruitment of diabetic and control participants took place at O.P. Chaudhary Hospital and Research Center. Initially, a clinical research coordinator conducted interviews with the subjects, explaining the study's goals. Anthropometric (weight, height, and waist circumference), demographic data (age and gender), and medical history were recorded. During the second visit, blood samples were collected in fluoride tubes for glucose estimation and DNA isolation. Biochemical parameters such as lipid profiles and HbA1C readings were also collected. Participants with fasting glucose levels between 100 and 125 mg/dL were considered controls, while those with fasting glucose levels above 125 mg/dL were considered diabetic. No participants had comorbidities or medical histories of nephropathy or cardiovascular disease.

DNA isolation from blood samples was performed using the phenol-chloroform method. Qualitative and quantitative DNA analyses were conducted using agarose gel electrophoresis and a UV spectrophotometer, respectively.

The ITLN1 exon 4 sequence was obtained from NCBI (accession number NM_017625.3), and information on the restriction site was obtained from NCBI-SNP. Genotyping was carried out using the tetra-primer amplification refractory mutation system polymerase chain reaction (ARMS-PCR), employing four primers in a single PCR followed by gel electrophoresis. The amplification of ITLN1 rs2274907 was performed in a 15 µl reaction containing 7.5 µl Gene I master mix, 0.5 µl of each outer primer, 1.0 µl of each inner primer (10 mM concentration), 2 µl of DNA (50 ng/µl), and 2.5 µl Milli-Q water. The cycling conditions were 95°C for 5 minutes, followed by 30 cycles of 95°C for 30 seconds, annealing at 61°C for 30 seconds, extension at 72°C for 30 seconds, and a final extension at 72°C for 5 minutes. For rs2274908, allele-specific primers were used. Each sample had two tubes, one with the G allele-specific primer plus the common reverse primer and the other with the A allele-specific primer plus the common reverse primer.

The same cycling conditions as rs2274907 were used, with annealing at 63°C. After amplification, the products were run on 3% agarose gel electrophoresis, and genotype analysis of rs2274908 was carried out using allele-specific PCR (Figure 2). The primer sequences are given in Table 1.

To validate single nucleotide changes in both genetic variations, a random selection of 10% of samples and unpurified PCR products of these samples were sequenced by Barcode Biosciences, Bangalore, India. Detailed sequencing results are shown in Figure 3, Figure 4.

The chi-square test was used to determine allelic and genotype frequencies using 2x2 and 2x3 contingency tables, respectively. The significance levels of case and control groups were calculated using the t-test. ANOVA single-factor analysis was used to analyze significance based on genotype and phenotype data. Haplotype analysis and linkage disequilibrium were performed using SHESIS software 26. A P-value of <0.05 was declared statistically significant after following all test criteria. All data are presented as mean ± standard deviation.

In (Table 2), the T2DM group has a higher mean of fasting glucose, serum cholesterol, triglycerides, LDL (Low-density lipoproteins), Hb1AC, and BMI (Body mass index) but the mean of HDL was higher in the control group. We did not find any significant difference between the Urea, Creatinine, and VLDL of both case and control groups.

In Figure 2 B Detection of ITLN1 missense SNP was genotype in which non-synonymous SNP rs2274907(A>T), they have 8 Lane in which L1 has 100 bp ladder was loaded, L2, L6, and L7 was loaded with wildtype (AA) condition which amplicon is 435 bp and 191 bp, L4 was loaded with (AT) condition which amplicon size was 435 bp,300 bp and 191 bp, L3 and L8 was loaded with Mutant (TT) condition had amplicon size was 435 bp and 300 bp. L5 was loaded with 435 bp internal control.

Detection of ITLN1 missense SNP was genotype in which synonymous SNP rs2274908 (G>A) detailed are shown in Figure 2 A. After this random selection, a 10% sample was used for Sanger sequencing to verify genotype analysis. In Lane 1 100 bp Ladder was loaded; in Lanes 3 and 5 heterozygous conditions (GA) sample was loaded, in Lanes 2 and 6 Homozygous (GG) wildtype sample was loaded, in Lanes 4 and 7 it was a Homozygous condition AA mutant allele sample was loaded.

The case and control group enrolled in this study have significantly deviated from HWE at P<0.05 as (Table 3) shows genotypic data of both rs2274907 and rs2274908 SNP. In rs2274907 three model form out of which TT vs AA+AT model shown significant P value=0.0004*.

We observed AA genotype has a lower glucose level (143.71±55.09) as compared to AT and TT genotypes (158.43±41.44 and 168.39±35.10), the AT genotype has a high cholesterol and triglyceride level (181.62±33.41and163.50±35.49) as compared to AA (163.41±24.64 and 149.19±29.69) and TT (163.85±12.55 and 137.43±17.54) genotype. HDL level had increases in the AA genotype. In rs2274908 (G>A) have no significant correlation between the genotype and phenotype data of patients (Table 4).

These two SNP rs2274907(A>T) and rs2274908(G>A) were used for haplotype analysis (Table 5). The haplotype T^* of rs2274907 and haplotype A* of rs2274908 showed a significant association (P=0.001093) with T2DM. The correlation coefficient and Linkage Disequilibrium of both SNP (Figure 5). Haplotype analysis was done by SHEsis software 27.

ITLN1 genetic variation is associated with insulin resistance, as it can affect glucose absorption through the inactivation of insulin receptor substrate, protein kinase, and AMP protein kinase 10. Individuals with impaired glucose tolerance diagnosed with T2DM show reduced omentin protein levels compared to healthy controls. Previous literature reports that serum omentin levels increase during weight loss due to a hypocaloric diet, which is associated with improved insulin sensitivity 10, 13, 26. Multiple studies have noted a connection between omentin 1 levels and omentin V109D polymorphism in various diseases, including diabetes, osteoporosis, rheumatoid arthritis, CAD, and psoriasis 28, 29, 30.

Studies have shown that ITLN1 polymorphism affects risk factors such as lipid accumulation and reduced levels of omentin in T2DM individuals, although results have been contradictory. The hypothesis of the current study is to identify genetic variation in the ITLN1 gene exonic region associated with T2DM in the North Indian population. This is the first study in the North Indian population to identify a single nucleotide change from A to T at position +326, altering the amino acid from valine to aspartate at position 109. This case-control study investigated whether the mutant T allele is associated with the risk of T2DM and its impact on demographic data such as BMI and phenotypic data such as lipid profile. Similar findings were reported in the Iranian and Kyrgyz populations, where the rs2274907 polymorphism was associated with T2DM 31, 24, 25. Although omentin levels were not measured in this investigation, it was noted that ITLN1 gene polymorphism may increase BMI and affect lipid profiles. The absence of omentin measurement can be justified by stating that measuring genetic markers in isolation still provides valuable insights into disease susceptibility. However, the importance of correlating genetic findings with protein function (such as omentin levels) should be emphasized. This could be a key area for future investigation. Our study found that the T allele is highly associated with T2DM patients, supported by findings in Iranian women with the T/T genotype, who were more susceptible to obesity complications compared to those with the A/A genotype 31.

This study also revealed that the T/T homozygous genotype was more common in overweight or obese individuals, consistent with later findings. Additionally, a noteworthy correlation was observed between BMI and the allelic genotype of the omentin Val109Asp polymorphism. In the Iranian population, the impact of omentin V109D polymorphism in non-alcoholic fatty liver disease showed a substantial difference in the frequency of the omentin V109D gene polymorphism between affected individuals and healthy controls. The Omentin Val109Asp polymorphism is thought to be connected to hepatic lipid build-up, and omentin concentrations and polymorphisms are linked to fatty liver disease and BMI. Further research on the mechanism behind omentin's action on lipogenesis and lipid accumulation may yield useful findings 32. A recent case-control research in Germany and Gujarat found no significant difference in the allelic distribution of the +326 A>T SNP between T2D patients and healthy controls 16, 33. Another research in Poland found no significant correlation between the ITLN-1 polymorphism +326 A>T and T2DM or other metabolic syndrome risk factors 34. The genetic variation rs2274908 is a synonymous SNP showing a significant difference between case and control groups. Despite its synonymous nature, there is no amino acid change at position 86 due to codon degeneracy. These changes can affect pre-mRNA splicing, tRNA binding, microRNA binding sites, and translational and post-translational modification, impacting co-translational folding, secondary structure, mRNA stability, and ultimately protein structure. Thus, these elements may result in functionally meaningful modifications 35, 30.

The correlation studies between T2DM and ITLN1 variants rs2274907 and rs2274908 enhance our understanding of how genetic variations impact clinical phenotypes. These analyses might help predict T2DM and related morbidity in healthy individuals with a family history of diabetes. However, these observations require confirmation through large-scale research on the Indian population.

This study concluded that the TT genotype in rs2274907 polymorphisms and the AA genotype in rs2274908 are risk factors for T2DM. Variations in the ITLN1 gene may impact protein function and stability. Understanding the genetic basis of T2DM could inform the development of targeted treatments and interventions. This study will contribute to our understanding of the pathogenesis of diabetes due to genetic variation and may help regulate clinical phenotype changes through pharmaceutical interventions.