Correlation of TNF-α and IL-6 expression with vitamin D levels in insulin-resistant type 2 diabetes mellitus patients: exploring the role of vitamin D in inflammation and disease pathogenesis

Abstract

Background

Chronic low-grade inflammation is often seen in individuals with insulin resistance, characterised by increased levels of pro-inflammatory cytokines, such as TNF-α (tumour necrosis factor-alpha) and IL-6 (interleukin-6). Insulin resistance (IR) and vitamin D deficiency are increasingly recognised as interconnected metabolic issues. Research indicated that low vitamin D levels may impair insulin sensitivity, while insulin resistance can worsen vitamin D deficiency, creating a vicious cycle. This study aims to explore the relationship between TNF-α and IL-6 expression levels and vitamin D levels in insulin-resistant patients with type 2 diabetes mellitus (DM), and compare them with non-diabetic controls to better understand the role of vitamin D in inflammation, disease development, and progression.

Methods

From a total of 150 participants, 30 were healthy individuals (the control group), and 120 were patients with type II diabetes. The current case-control study compared TNF-α, IL-6 expression levels, and serum vitamin D levels between insulin-resistant patients and non-diabetic controls.

Results

The demographic and clinical variables were statistically significant. The case-to-control ratio was 4:1. Higher levels of TNF-α and IL-6 were found in DM patients compared to non-diabetic controls. Insulin-resistant patients exhibited higher IL-6 levels (5.47 ± 0.30 pg/ml) than healthy participants (2.64 ± 0.83 pg/ml), with p-value < 0.001. Vitamin D levels were significantly lower in DM patients (22.33 ± 11.43 ng/ml) compared to healthy subjects (34.12 ± 2.08 ng/ml), with p-value < 0.001. TNF-α levels were also significantly higher in DM patients (7.99 ± 0.35 pg/ml) (p-value < 0.001) than in the healthy group (4.24 ± 0.27 pg/ml). Using qPCR and measuring disease severity, the relationship between cytokine gene expression and insulin resistance was assessed. The positive associations between TNF-α, IL-6, vitamin D deficiency, poor glycaemic control, and other disease conditions reflect a fundamental pathophysiological mechanism in insulin resistance in DM patients. This ultimately leads to increased inflammation and tissue damage, worsening the complications of diabetes.

Background

Insulin resistance is a key feature of metabolic disorders such as type 2 diabetes mellitus and obesity. It is characterized by the body’s diminished ability to respond to insulin, leading to elevated blood glucose levels [1]. To compensate for the lower response of these tissues, pancreatic beta cells start producing higher insulin concentrations, leading to hyperinsulinemia [2]. It owns a diverse range of physiology inside the human body. Al Ghadeer and his colleagues investigated and suggested a potential link between vitamin D levels and the regulation of these inflammatory markers, prompting interest in the role of vitamin D in the pathogenesis of insulin resistance [3]. TNF-α is a cytokine produced primarily by adipose tissue and is known to interfere with insulin signaling pathways. Elevated levels of TNF-α are associated with metabolic syndrome and contribute to insulin resistance by promoting inflammation and apoptosis in pancreatic beta cells [4].

IL-6 is produced by various cells, including adipocytes, and plays a dual role in metabolism. While it is involved in acute inflammation, chronic elevation of IL-6 is linked to insulin resistance and the development of type 2 diabetes [5]. Vitamin D, a fat-soluble vitamin obtained from sunlight exposure and dietary sources, is known for its role in bone health and calcium metabolism. However, it also possesses immune-modulating properties [6]. Vitamin D can inhibit the production of pro-inflammatory cytokines like TNF-α and IL-6 while promoting the expression of anti-inflammatory cytokines [7]. This suggests a potential mechanism by which adequate vitamin D levels may mitigate inflammation in insulin-resistant patients.

Numerous studies have reported that low vitamin D levels are associated with increased levels of TNF-α and IL-6. Research indicates that individuals with vitamin D deficiency exhibit higher inflammatory marker levels, which may impair insulin resistance [8, 9]. Vitamin D influences gene expression related to inflammation and immune response, leading to a reduction in the secretion of TNF-α and IL-6 [10, 11].

Studies have shown that vitamin D supplementation can lead to a decrease in the levels of TNF-α and IL-6 in insulin-resistant individuals. This underscores the potential therapeutic role of vitamin D in managing inflammation and improving insulin sensitivity [12]. Some studies have shown improvements in insulin sensitivity, glucose, and lipid metabolism; others have found no positive effects on inflammation or glycemic management [10]. The interplay between vitamin D deficiency, elevated TNF-α, and IL-6 levels may contribute to the development of metabolic syndrome, characterized by obesity, hypertension, dyslipidemia, and insulin resistance [13]. Chronic inflammation driven by elevated cytokines can impair insulin signaling and pancreatic function, increasing the risk of type 2 diabetes mellitus [14].

The correlation between TNF-α and IL-6 expression with vitamin D levels in insulin-resistant patients highlights the complex interplay between inflammation, vitamin D, and metabolic health [15]. Adequate vitamin D levels may modulate this inflammatory response, potentially reducing diabetes risk [16]. In the present study, the relationship between TNF-α expression levels and glycemic control markers (e.g., HbA1c, fasting blood glucose) was investigated. We investigated the potential correlations between TNF-α expression levels and insulin resistance-related complications, such as hypercholesterolemia, hyperuricemia, unbalanced lipid profile, and inflammatory diseases. The gene expression of pro-inflammatory cytokines such as IL-6 and TNF-α was quantitatively assessed using qPCR. The output of relative quantification by qPCR is classically reported as cycle threshold (Ct) values, critical for understanding the relative expression levels of these genes.

Methods

Study design and sample collection

A total of one hundred and fifty patients were included in this study. Out of the 150 patients, 30 patients were healthy individuals considered as the control group (enrolled age- and sex-matched individuals without diabetes), and 120 patients were insulin resistant (individuals diagnosed with type 2 diabetes. This study is a case-control study as we compared TNF-α, IL-6 expression levels, and serum vitamin D levels between insulin-resistant patients and non-diabetic controls. The samples were collected based on random sampling.

Exclusion criteria

Patients with type 1 diabetes were excluded because the study focuses on elderly patients with type II DM, diagnosed with related metabolic complications.

The demographic and clinical variables were observed, such as age, gender, medical history, diabetes duration, and relevant laboratory results as vitamin D levels, serum uric acid, lipid profile, HbA1c, fasting blood glucose, and blood grouping. Ethical approval was obtained from the research ethics committee, Combined Military Hospital (CMH), Kharian Medical College, Kharian Cantt. Informed written consent was obtained from all study participants, and they adhered to confidentiality and privacy regulations.

Blood samples were collected for different biochemical measurements. Blood samples were centrifuged for 15 min at 12,000 ×g at 40 °C to separate serum and were stored at − 70 °C. The tissues (subcutaneous adipose tissue biopsies) were treated with liquid nitrogen for RNA extraction.

Biochemical analysis of serum

The serum was used for the estimation of vitamin D level, TNF-α, and IL-6 by using a Mybiosource Elisa kit (Catalogue # MBS704497), Human TNF-α Elisa Kit (Invitrogen, Catalogue # KHC 3011), and Human IL-6 Elisa Kit (Invitrogen, Catalogue # EH2IL6), respectively.

Serum uric acid, lipid profile, HbA1c, and fasting blood glucose, as determined by AMP diagnostic kits according to the manufacturer’s instructions.

RNA extraction and cDNA synthesis by reverse transcription

Total RNA was extracted from a tissue sample (The Subcutaneous adipose tissue biopsies in the abdominal area were done by needle-based technique) of 50–100 mg and minced in 100µL of Trizole Reagent. Then shifted the minced sample in a 1.5 mL Eppendorf tube. Trizole (400µL) was added and homogenised properly. Incubated for 5 min. Then, 400 µL of Chloroform was added and incubated for 3 min. Centrifugation was done at 12,000 rpm for 10 min at 4 °C. The aqueous layer was transferred to a new Eppendorf tube. An equal volume of chilled Isopropanol (0.5 mL) was added and incubated for 10 min at a horizontal position. Centrifuged at 12,000 rpm for 10 min at 4 °C, and the supernatant was carefully discarded. The Pellet was washed twice with 1 mL 70% Ethanol. Centrifuged at 7500 rpm for 5 min at 4 ⁰ C. Pellet was dried, and 35 µL PCR water was added and stored at −80 °C.

cDNA synthesis was performed by using the Revert Aid First Strand cDNA synthesis kit (Catalogue # K1621), Thermo Fisher Scientific, Vilnius, Lithuania) containing 10x Reaction Buffer 2 µl, Ribolock RNase Inhibitor 0.5 µl, 10 mM dNTPs 2 µl, Reverse Transcriptase 1 µl, Hexamer Primer 1 µl, RNAase Free Water 3.5 µl, RNA 10 µl to make a total volume of 20 µl. Purified PCR products were run on a 1.5% Agarose gel. A 30 mL 1.5% gel is prepared by adding 0.45 g of Agarose to 30 mL 1x TBE buffer. Ethidium Bromide 5 µL was added. Purified PCR sample of 5 µL is then loaded on the gel after adding 2µL loading dye to it.

qPCR gene expression assay

The expression analysis of IL-6 and TNF-α was performed by the quantitative real-time PCR Expression Assay. The relative quantification (RQ) of the gene was done using glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Samples were used in triplicate to minimize the error and for valid data interpretation. Gene expression assay was performed on a Bio-Rad C1000 Thermal Cycler. Thermocycling conditions were 10 min at 95 °C, 40 cycles of denaturation at 95 °C for 15 s, and annealing and extension for 1 min at 60 °C. The relative fold change in the expression of the target gene was determined by 2–ΔΔCt and analyzed using QuantStudio™ Design and Analysis Software v2. The primers used are shown in Table 1.

Table 1.

List of primers

Cytokines	Primer sequence (Forward and Reverse)	Region	Reaction Condition (°C)	Product Size (bp)
IL-6	F’ CTTCGGTCCAGTTGCCTTCT R’ GAAGAGGTGAGTGGCTGTCT	Promoter	56	126
TNF-α	F’ CGTGGAGCTGAGAGATAACCA R’ ATGGCAGAGAGGAGGTTGAC	Promoter	52	171

Statistical analysis

Descriptive statistics were calculated. SPSS version 22.0 was used to find statistical significance at p ≤ 0.05. The mean ± SD of variables was calculated. The Independent t-test was used to compare the means of two independent groups. The Pearson correlation coefficient (r) was used to determine associations between TNF-α, IL-6 expression levels, vitamin D levels, glycemic control markers, uric acid, and lipid profile. Anova was used to assess the association between TNF-α, IL-6 expression levels and disease severity (n = 150).

Results

TNF-α and IL-6, and serum vitamin D levels in insulin-resistant patients

The significant cytokine levels were found to be associated with vitamin D levels in selected participants. Vitamin D levels were significantly low in insulin-resistant patients (22.33 ± 11.43ng/m) as compared to healthy individuals (34.12 ± 2.08 ng/m), p value < 0.001. However, TNF-α was statistically significantly high in insulin-resistant patients (7.99 ± 0.35 pg/ml) as compared to healthy individuals (4.24 ± 0.27 pg/ml), i.e. p value < 0.001. A statistically significant difference (p < 0.001) between the control group and the insulin-resistant patients was seen, indicating that both inflammatory markers (TNF-α and IL-6) were elevated. At the same time, serum vitamin D level was decreased in the insulin-resistant group, as shown in Table 2.

Table 2.

Comparison of TNF-α and IL-6, and serum vitamin D levels in insulin-resistant patients compared to healthy individuals (n = 150)

Serum	Control (n = 30) Mean ± SD	Cases (n = 120) Mean ± SD	p-value
vitamin D (ng/mL)	34.12 ± 2.08	22.33 ± 11.43	< 0.001*
TNF-α (pg/mL)	4.24 ± 0.27	7.99 ± 0.35	< 0.001*
IL-6 (pg/mL)	2.64 ± 0.83	5.47 ± 0.30	< 0.001*

(Significant p < 0.05) *Indicate p < 0.01

Association between TNF-α, IL-6 and different types of diabetes (type 2) and disease severity

Table 3 showed increased levels of HbA1c along with increased levels of TNF-α and IL-6. The p-values indicate that there is a significant association between both TNF-α and IL-6 levels with the severity of Type II diabetes, with IL-6 showing a stronger association. The findings suggested that the severity of diabetes increases, both TNF-α and IL-6 levels also increase significantly, reflecting the inflammatory state related to diabetes severity.

Table 3.

Measure the association between TNF-α, IL-6 expression levels and different types of diabetes (type 2) and disease severity (n = 150)

Variable	HBA1c (%)			p-value
	Mild (6.5–7.4) (n = 9)	Moderate (7.5–8.9) (n = 43)	Severe (≥ 9) (n = 68)
TNF-α (pg/mL)	7.85 ± 0.29	7.98 ± 0.40	8.01 ± 0.33	0.0167
IL-6 (pg/mL)	5.42 ± 0.22	5.44 ± 0.30	5.50 ± 0.32	< 0.001*

(Significant p < 0.05) *Indicate p < 0.01

Relationship between TNF-α and glycemic control markers

The correlation coefficient (r value) of HbA1c (%) is 0.120 with a p-value of 0.192, in the case of TNF-α, indicating no significant relationship. While the correlation coefficient (r value) of fasting blood glucose is 0.220 with a p-value of 0.015*, indicating a significant positive relationship. In case of IL-6 Levels, the correlation coefficient (r value) of HbA1c (%) is 0.223 with a p-value of 0.015*, indicating a significant positive relationship, and the correlation coefficient (r value) of fasting blood glucose is 0.084 with a p-value of 0.223, indicating no significant relationship.

TNF-α showed a significant positive correlation with fasting blood glucose levels but not with HbA1c levels. IL-6 exhibits a significant positive correlation with HbA1c, indicating that as IL-6 levels increase, HbA1c levels also tend to increase. The results suggested that while TNF-α may be more closely related to fasting blood glucose levels, IL-6 is associated with overall glycemic control as measured by HbA1c (Table 4).

Table 4.

Relationship between TNF-α and glycemic control markers (n = 150)

Parameters	TNF-α		IL-6
	r value	p-value	r value	p-value
HbA1c (%)	0.120	0.192	0.223	0.015*
Fasting Blood Glucose	0.220	0.015*	0.084	0.223

(Significant p < 0.05) *Indicate p < 0.01

Association of clinical variables with HBA1c categories

The level of uric acid was increased from mild (7.85 ± 0.29 mg/dL) to severe (8.01 ± 0.33 mg/dL) with HBA1c; however, the difference was not statistically significant (p value = 0.115). Cholesterol levels were higher in the moderate and severe groups compared to the mild group. Similarly, the difference did not find statistical significance (p = 0.560). HDL levels remained relatively stable across all groups, with no statistically significant difference (p = 0.806). LDL levels increased with HbA1c levels, but the difference was not significant (p = 0.544). Triglyceride levels were highest in the moderate group (266.67 ± 65.43 mg/dL), though the overall difference among the groups was not significant (p = 0.881) shown in Table 5.

Table 5.

Comparison of clinical variables with HBA1c categories (n = 150)

Variable	HBA1c (%)			p-value
	Mild (6.5–7.4) (n = 9)	Moderate (7.5–8.9) (n = 43)	Severe (≥ 9) (n = 68)
Uric Acid (mg/dL)	7.85 ± 0.29	7.98 ± 0.40	8.01 ± 0.33	0.115
Cholesterol(mg/dL)	195.55 ± 44.49	210.13 ± 62.50	217.99 ± 60.09	0.560
HDL (mg/dL)	45.66 ± 12.29	44.93 ± 11.48	45.86 ± 11.99	0.806
LDL (mg/dL)	125.00 ± 50.12	131.00 ± 41.88	135.13 ± 47.02	0.544
Triglycerides(mg/dL)	217.11 ± 37.05	266.67 ± 65.43	236.35 ± 32.23	0.881

(Significant p < 0.05) *Indicate p < 0.01

Relationship between TNF-α and IL-6 expression levels with clinical variables

Cholesterol exhibited a significant positive correlation with TNF-α (r = 0.296, p = 0.001), higher cholesterol levels are associated with elevated TNF-α concentrations. Furthermore, other parameters such as uric acid (r = −0.155, p = 0.091), HDL, LDL, and triglycerides showed non-significant correlations with TNF-α. Moreover, Triglycerides had a significant positive correlation with IL-6 (r = 0.197, p = 0.031), indicating that higher triglyceride levels may be associated with elevated IL-6 levels. All other biochemical parameters, including uric acid, cholesterol, HDL, and LDL, showed non-significant correlations with IL-6 (Table 6).

Table 6.

Relationship between TNF-α and IL-6 expression levels with clinical variables (n = 150)

Parameters	TNF-α		IL-6
	r value	p-value	r value	p-value
Uric Acid (mg/dL)	0.155	0.091	0.021	0.821
Cholesterol(mg/dL)	0.296	0.001	0.146	0.111
HDL (mg/dL)	0.023	0.801	−0.157	0.086
LDL (mg/dL)	0.214	0.091	−0.019	0.833
Triglycerides(mg/dL)	0.159	0.082	0.197	0.031*

(Significant p < 0.05) *Indicate p < 0.01

Data analysis for real time PCR (Relative Expression)

Ct values can be used for relative quantification of gene expression by comparing the expression of target genes (IL-6 and TNF-alpha) to a reference gene (housekeeping gene), GAPDH, expressed using the ΔCt method:

When measuring IL-6 expression, a lower Ct value indicates higher levels of IL-6 mRNA, suggesting an increased inflammatory state in insulin-resistant patients. Ct values of 25 with vitamin D deficiency may indicate high IL-6 expression, while Ct values of 30 or above could suggest low expression. A Ct value of 24.51 with poor glycemic control and in patients with hypercholesterolemia might point to an active inflammatory response, whereas other markers show minimal expression. The delta Ct (Δ Ct) value for vitamin D-deficient patients is −2.06, indicating higher IL-6 expression, and the ΔΔ Ct value is −0.59 compared to the control. The relative fold change (2^-(∆∆Ct)) of 1.51 suggests increased IL-6 gene expression. Consequently, patients with poor glycemic control, hyperuricemia, and hypercholesterolemia exhibited increases of 2.35-, 1.93-, and 1.28-fold respectively compared to the reference sample and control (Fig. 1).

Fig. 1.

The relative expression of IL-6 is compared with the disease severity in insulin-resistant patients with the reference gene GAPDH

In case of TNF-α, patients with vitamin D deficiency, there is a significant increase in TNF-α expression with a mean Ct value of 24.22, a Δ Ct is −2.15 and a 1.61-fold increase. Patients with poor glycemic control, hyperuricemia and hypercholesterolemia exhibited 0.65, 0.93 and 0.53-fold increase in TNF-α gene expression as compared to control (Fig. 2).

Fig. 2.

The relative expression of TNF-α is compared with the disease severity in insulin-resistant patients with the reference gene GAPDH

Discussion

The observations from the study participants emphasise a significant link between inflammation and the pathology of diabetes, especially regarding insulin resistance, hyperglycemia, and the onset of complications. It is widely recognised that vitamin D possesses anti-inflammatory properties. Reports indicate that vitamin D inhibits the production of myeloperoxidase and reactive oxygen species in neutrophils, leading to a reduction in pro-inflammatory cytokine levels [7]. Furthermore, the transcription factor NF-κB, which plays a crucial role in producing pro-inflammatory cytokines, is inhibited by vitamin D [17]. Consistent with Tareen et al. (2024), our study demonstrates that vitamin D deficiency amplifies systemic inflammation, as indicated by elevated IL-6 and TNF-α, likely through NF-κB dysregulation. This may contribute to chronic inflammation, potentially resulting in type 2 diabetes and insulin resistance.

Generally, IL-6 promotes leukocyte migration to inflammatory sites and enhances B cell proliferation that produces antibodies [18]. Tissue factor, which plays a key role in the blood coagulation cascade, is activated by TNF-α. In reported cases, TNF-α alongside IL-6 expression may differ between Vitamin D-deficient diabetics and correlate with disease severity [19]. Positive correlations were observed between TNF-α and IL-6 levels and markers of poor glycemic control. Levels of TNF-α and IL-6 may be positively associated with the presence and progression of diabetes-related complications, as recently reported by Shuo Wang and his colleagues [20]. The relationship between cholesterol levels and TNF-α concentrations is complex and can vary depending on the context. It has been observed that TNF-α affects lipid metabolism, potentially influencing cholesterol levels. Both positive and negative correlations were found between cholesterol and TNF-α, along with differing Ct values, indicating a complex relationship. This suggests that, in certain circumstances, inflammation may impact lipid metabolism, leading to reduced cholesterol levels. Frequent changes in lipid metabolism is associated with increased inflammation, reinforcing the importance of early detection and intervention to mitigate cardiovascular and metabolic risks [21]. The impact of TNF-α on cholesterol may vary depending on the underlying condition or disease state, ranging from protective (acute) to harmful (chronic), highlighting the need for tailored therapeutic approaches [22].

Our research specified a significant positive correlation (p < 0.05) between TNF-α, and HbA1c in study patients. TNF-α could serve as a predictive biomarker for diabetes progression or complications e.g., cardiovascular risk [23]. Our findings align further with mechanistic evidence that vitamin D deficiency exacerbates insulin resistance and β-cell dysfunction, contributing to elevated HbA1c, and may have a role in the etiology of type 2 diabetes. Further studies, randomised control trials, should clarify optimal thresholds and dosing strategies. Our data align with mechanistic studies positioning IL-6 as a key mediator of diabetes pathogenesis. Elevated IL-6 may precede hyperglycemia, offering a window for early intervention. Therefore, IL-6 is a part of a broader inflammatory network, including TNF-α, and is thus considered a robust epidemiological biomarker for insulin resistance and chronic inflammation. The clinical use of IL-6 depends on integrating it with other metabolic and inflammatory indicators.

Ct values serve as a valuable tool for quantifying the expression of IL-6 and TNF-α in various biological contexts, including insulin resistance [24]. Our data suggest IL-6/TNF-α Ct thresholds (e.g., ≤ 22 for IL-6) could identify candidates for anti-inflammatory therapies (e.g., GLP-1 agonists, vitamin D) before overt diabetes onset. While biologics like TNF-α inhibitors may show promise, lifestyle modification remains foundational. Future studies should test stratified approaches based on cytokine profiles. The inverse relationship between vitamin D and cytokine Ct values suggests that vitamin D modulates inflammatory gene expression, potentially disrupting the insulin resistance-inflammation cycle. Since TNF-α and IL-6 have distinct regulatory mechanisms, even though both are pro-inflammatory [24].

Thus, the observations in the study presented significantly different mean Ct values for inflammatory cytokines between groups of vitamin D deficiency, poor glycemic markers, hyperuricemia, hypercholesterolemia, and deranged lipid profile, providing strong experimental evidence consistent with the well-established hypothesis about insulin resistance and disease severity, suppressing the expression of pro-inflammatory cytokines like TNF-α and IL-6. Figures 1 and 2 in the results section help compare directional effects across several disease conditions in measuring relative quantification of cytokine gene expression.

Based on this research, it is evident that vitamin D may play a protective role against inflammation in normal individuals. Insulin-resistant patients with disease severity (mentioned in the results) may affect the inflammatory markers and their pathophysiology. Further investigation is warranted to explore the therapeutic potential of modulating inflammation. Future studies should focus on long-term intervention trials assessing the impact of vitamin D supplementation on inflammatory markers and metabolic outcomes in diverse populations. The longitudinal study should be performed to assess changes in TNF-α expression levels over time in individuals with insulin resistance with Vitamin D deficiency.

Conclusion

The positive associations between TNF-α, IL-6, vitamin D deficiency, poor glycemic control, and other disease conditions reflect a fundamental pathophysiological system during insulin resistance in DM patients. This leads ultimately to amplifying inflammation and directly damaging tissues, increasing devastating complications of diabetes.

Significance and implications

• This research will contribute to understanding the role of TNF-α and IL-6 expression along with Vitamin D deficiency in insulin resistance pathogenesis and its association with inflammation.

• The findings may provide insights into the potential use of TNF-α and IL-6 expression as a biomarker for diabetes diagnosis, prognosis, and monitoring.

• Understanding the relationship between TNF-α expression levels and complications can guide the development of targeted interventions to mitigate their impact on diabetic patients.

Authors’ contributions

MRH, SS, SNH, RZ, HS, SR, DD, and TA designed the study, conceived the study and analyzed the results. MRH, SS, SNH, RZ, HS, SR, DD, and TA conceived an initial part of the study, performed the experiment, and helped in compiling the results. AH experimented, MRH, SS SNH, RZ, HS, SR, DD, and TA helped in writing the results. MRH, SS, SNH, RZ, HS, SR, DD, and TA wrote the paper with input from all other authors. MRH, SS, SNH, RZ, HS, SR, DD, and TA made substantial contributions to the interpretation of data and revising the manuscript for intellectual content. MS performed bioinformatics. All authors read and approved of the final manuscript.

Funding

The authors extend their appreciation to the Researchers Supporting project number (ORFFT-2025-007-2), King Saud University, Riyadh, Saudi Arabia for funding this project. The funding body has no role in designing the study.

Data availability

All data generated or analyzed during this study are included in this article.

Declarations

Ethics approval and consent to participate

The protocol was approved (Ref: No. IRB No. 05-2023-05/01) from ethical approval was obtained from the research ethics committee, Combined Military Hospital (CMH), Kharian Medical College, Kharian Cantt, Pakistan. Informed written consent was obtained from all study participants, and they adhered to confidentiality and privacy regulations. Research was conducted in accordance with the Helsinki Declaration.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.