Precise blood sugar regulation is greatly required for harmonizing current energy needs within human tissues by intelligently integrating food resources and internally stored energy reserves [1]. Blood glucose levels below normal can represent a potentially fatal medical emergency, whereas chronically elevated sugar concentrations trigger multiple metabolic disturbances that include the generation of sorbitol, mitochondrial functional impairment, and formation of detrimental advanced glycation end products [1-2]. Two mechanisms lead to persistent hyperglycemia: complete insulin deficiency, characteristic of type 1 diabetes, or multifactorial interaction between extreme insulin resistance at the tissue level and deficient insulin secretion, the hallmark of type 2 diabetes. Type 2 diabetes is the more common form, accounting for about 90% of all diagnosed cases. The developmental course of type 2 diabetes is very intricate and heterogeneous, demanding additional scientific study of many disease characteristics. Scientists have clearly established that obesity combined with a sedentary lifestyle strongly predisposes individuals to insulin resistance, mainly because of the inflammatory effects of stress on adipose tissue cells that lead to the impairment of insulin receptor sensitivity [3]. Modern scientific knowledge has extensively revised previous conceptions of adipose tissue. Adipose tissue, particularly visceral fat, is not merely a passive storage system; it has important endocrine and inflammatory properties. Adipocytes that are subjected to expansion-induced hypoxia may release several cytokines and adipokines, of which many have remarkable pro-inflammatory attributes [4]. With obesity and type 2 diabetes rates skyrocketing all over the world [2], there's an added need to understand such complex inflammatory relationships between lifestyle-related diseases [4]. In addition to obesity-related inflammation, excess glucose exposure in diabetes conditions disrupts normal physiological equilibrium and enhances the secretion of proinflammatory cytokines into cellular microenvironments [5]. Chronic low-grade systemic inflammation is now well acknowledged as an important comorbid disease in type 2 diabetes [5]. Several prospective research studies have shown that higher levels of proinflammatory biomarkers-presentation of interleukin 6, and C-reactive protein, for example—predict higher risk of type 2 diabetes onset [6,7]. This suggests that the pathogenetic pathways of the disease are significantly affected by systemic inflammatory processes [6,7].

Low-grade systemic inflammation in type 2 diabetes is of clinical importance since it is strongly associated with the emergence and progression of long-term complications, including nephropathy, neuropathy, and retinopathy. Moreover, this inflammatory state matches closely with cardiovascular disease, which continues to be the leading cause of morbidity and mortality among patients diagnosed with type 2 diabetes [8-13,14]. The primary purpose of the study was to measure low-grade systemic levels of inflammation in a heterogeneous group of patients with type 2 diabetes differing in illness duration. The researchers hypothesized that patients with type 2 diabetes would have high levels of proinflammatory biomarkers compared with healthy persons. The major objective of the study was focused on distinguishing circulating inflammatory biomarkers between healthy persons and patients with type 2 diabetes. Researchers also hypothesized that the levels of proinflammatory biomarkers would be linked to several clinical parameters, such as duration of illness, obesity, glycemic control, therapeutic therapy, and presence of diabetes-related microvascular and macrovascular complications. As such, the secondary objectives of this study were designed to investigate the complex interactions between inflammatory biomarkers with the clinical features of type 2 diabetes [13,14].

MATERIAL AND METHODS

The present study was conducted at the hospital premise in India. This study had three groups of patients divided on the basis of their blood glucose level into Normal Blood Sugar (n=200), Mildly Elevated Blood Sugar (n=100), and Type-2 Diabetes (n=100). Demographic and clinical information was obtained including age, BMI, prevalence of obesity, gender distribution, inflammatory markers that include C-reactive protein, Interleukin-6, Tumor Necrosis Factor-Alpha, physical activity, quality of diet, and comorbidities like hypertension and hyperlipidemia. Blood glucose and insulin levels were measured in all participants. Continuous variables like age, BMI, and inflammatory markers received continuous variable ANOVA. Categorical variables, such as gender, obesity, and physical activity, received chi-square tests. A probability level of less than 0.05 was considered to be statistically significant. The following correlation studies were conducted on the values of inflammatory indicators, blood glucose, and insulin levels for each of the groups. Differences among the three groups about the mentioned variables were evaluated based on the P-values.                                                                                         

RESULTS

Table 1: Demographic Characteristics and Statistical Analysis of Study Groups of patients under study and investigation

The three groups were somehow different from each other on various demographic characteristics: Normal Blood Sugar, Mildly Increased Blood Sugar, and Type-2 Diabetes. There were statistically significant increases in age, BMI, obesity, C-Reactive Protein (CRP), Interleukin-6, Tumor Necrosis Factor-Alpha (TNF-α), physical activity, nutritional quality, hypertension, and hyperlipidemia when blood glucose levels dropped down below normal (p-value <0.001). On the other hand, there wasn't any specified gender distributions among the groups (p-value = 0.735) [Table 1].

Table 2: Correlation matrix analysis

A. Normal Blood Sugar:

B. Mildly Increased Blood Sugar:

C. Type-2 Diabetes:

Overall, there are slight positive correlations among the variables of C-reactive protein, Interleukin-6, Tumor Necrosis Factor-Alpha, blood glucose, and insulin in patients with normal glucose blood levels; the most significant correlation was between blood glucose and insulin, at 0.70. In those with moderately increased blood glucose, significant correlations emerge, and in particular, relationships between Blood Glucose and Insulin (0.75) and between C-reactive protein and Blood Glucose (0.60). In Type-2 diabetes, relationships are often stronger than in the other two categories, particularly between Tumor Necrosis Factor-Alpha and Blood Glucose (0.75) and between Insulin (0.80). Correlations between inflammatory markers (C-reactive protein, Interleukin-6, and Tumor Necrosis Factor-Alpha) with glucose-insulin variables strengthen with increasing levels of blood sugar. Increasingly consistent rises in strengths of connections from normal levels of blood sugar to Type-2 diabetes suggest a likely interaction among inflammation, insulin resistance, and heightened blood glucose levels [Table 2].

Table 3: Comparison of the significant p-values between the 3 groups being studied and investigated

In each of the three pairwise comparisons-Normal vs. Mildly Increased, Normal vs. Type-2 Diabetes, and Mildly Increased vs. Type-2 Diabetes-it can be observed that analysis of significant p values across the three groups shows consistent disparities in multiple variables. For instance, age, BMI, obesity, inflammatory markers such as C-reactive protein, Interleukin-6, and Tumor Necrosis Factor-Alpha, physical activity, dietary quality, hypertension, and hyperlipidemia all came out below the 0.001 mark. Gender showed no difference at all in any of the comparisons (p = 0.735). There was a clear indication that metabolic and inflammatory factors played a significant role in distinguishing between the groups, specifically in obesity and comorbidities [Table 3].

DISCUSSION

Our in-depth study demonstrated that anti-inflammatory treatment, especially anti-IL-1 drugs, significantly lowers levels of FPG, HbA1c, and CRP in T2DM patients [15, 16]. Drugs like Anakinra, a recombinant human IL-1β receptor antagonist, are supposed to dramatically decrease HbA1c levels and maybe able to improve glycemic control through the induction of insulin release [16]. Other monoclonal antibodies, including Canakinumab, Gevokizumab, and LY2189102, may block IL-1β action through the neutralization of soluble circulating cytokines [15]. Canakinumab may reduce levels of both IL-6 and CRP in serum [15]. Our thorough meta-analysis of 16 randomized controlled studies performed between the years 2005 and 2022 considered the impact of anti-inflammatory drugs on glycemic control in people with T2DM [17, 18, 19]. Earlier meta-analyses conducted in 2018 and 2019 indicated that anti-interleukin-1 (anti-IL-1) medications may substantially lower hemoglobin A1c (HbA1c) and C-reactive protein (CRP) levels, accompanied by modest hypoglycemia effects [18, 19]. Identifying current knowledge deficiencies, we performed a comprehensive examination of anti-inflammatory treatments aimed at diverse inflammatory mediators, such as IL-1β, IL-1βR, tumor necrosis factor-alpha (TNF-α), and nuclear factor kappa B (NF-κB) [18-19].

Our subgroup analyses suggested that anti-inflammatory therapy was maximally effective at very short duration of treatments, most notably in the first three months [18, 19]. Some drugs had promising early results which, however, tailed with time. In spite of the fact that TNF-α could interfere with glucose-stimulated insulin production, some TNF-α antagonists like Etanercept have yielded inconsistent results [17-21]. Diacerein, which is an antagonist for both IL-1βR and TNF-α, has been proved to decrease HbA1c levels without affecting the resistance to insulin appreciably [22]. Our findings suggest that newly diagnosed T2DM patients would benefit more from anti-inflammatory drugs [20]. However, effectiveness may also be dependent on baseline metabolic status, as patients with greater metabolic imbalances may react better to the treatment [20-21]. The study has some limitations. Lifestyle changes and the concurrent anti-diabetic drugs used in most research could limit the effectiveness of anti-inflammatory treatments. Additionally, most of the follow-up durations ranged from 1 to 12 months, and thus, there is a high requirement for longer clinical studies to comprehensively evaluate the effectiveness of pharmaceutical agents over periods of time [20]. Controlling for probable publication bias, our trim and fill analysis confirmed the homogeneity of our findings, providing strong evidence for the treatment of type 2 diabetes mellitus with anti-inflammatory drugs [20].

Persistent low-grade inflammation within the diabetic islets has been observed due to increased infiltration of immune cells and release of cytokines [23]. This inflammation directly compromises β-cell mass and activity [24]. Initial evidence identified IL-1β as a key proinflammatory cytokine within patients with T2DM. The effects demonstrated its ability to impair β-cell activity and induce apoptosis of β-cells [25, 26]. Several encouraging results have been reported when the IL-1β signaling pathway has been inhibited using antagonists or antibodies, thus enhancing β-cell activity and glycemic regulation [27-29]. Our finding that treatments targeting both IL-1β and TNF-α were more effective at reducing HbA1c levels than either molecule alone was particularly fascinating. Salsalate is an anti-inflammatory prodrug that had favourable glycemic control benefits by modulating cellular kinases and β-cell insulin production [30-33].

The study highlights significant correlations among increasing blood glucose levels and deteriorating health markers in normal, mildly elevated, and Type-2 diabetic groups. These key factors were age, BMI, obesity, inflammatory markers (CRP, IL-6, TNF-α), physical activity, quality of diet, hypertension, and hyperlipidemia, as these factors were constantly found to present with statistical significance during this transition phase from normal to Type 2 diabetes. Correlation analysis shows that the relationships among inflammatory markers and glucose-insulin factors strengthened with increased blood sugar levels, hence indicating a serious relationship among inflammation, insulin resistance, and diabetes. Gender was the only variable that showed no significant variation across groups. The results highlighted the complex impact of metabolic and inflammatory dysregulation on the onset and advancement of Type-2 diabetes, pointing to a need for focused therapies targeting these risk factors.

1. M. Ighodaro, "Molecular pathways associated with oxidative stress in diabetes mellitus," Biomed. Pharmacother., vol. 108, pp. 656–662, 2018, doi: 10.1016/j.biopha.2018.09.058.
2. International Diabetes Federation, IDF Diabetes Atlas, 9th ed., Brussels, 2019. [Online]. Available: https://www.diabetesatlas.org.
3. Prasad, E. W. Chen, S.-A. Toh, et al., "Autoimmune responses and inflammation in type 2 diabetes," J. Leukoc. Biol., vol. 107, pp. 739–748, 2020, doi: 10.1002/JLB.3MR0220-243R.
4. C. de O. Gonzalez, T. F. Costa, Z. de A. Andrade, et al., "Wound healing - A literature review," An. Bras. Dermatol., vol. 91, pp. 614–620, 2016, doi: 10.1590/abd1806-4841.20164741.
5. L. Gonzalez, K. Garrie, and M. D. Turner, "Type 2 diabetes - an autoinflammatory disease driven by metabolic stress," Biochim. Biophys. Acta Mol. Basis Dis., vol. 1864, pp. 3805–3823, 2018, doi: 10.1016/j.bbadis.2018.08.034.
6. D. Pradhan, J. E. Manson, N. Rifai, et al., "C-reactive protein, interleukin 6, and risk of developing type 2 diabetes mellitus," JAMA, vol. 286, pp. 327–334, 2001, doi: 10.1001/jama.286.3.327.
7. Thorand, H. Löwel, A. Schneider, et al., "C-reactive protein as a predictor for incident diabetes mellitus among middle-aged men: results from the MONICA Augsburg cohort study, 1984-1998," Arch. Intern. Med., vol. 163, pp. 93–99, 2003, doi: 10.1001/archinte.163.1.93.
8. A. Albert, E. Danielson, N. Rifai, et al., "Effect of statin therapy on C-reactive protein levels: the pravastatin inflammation/CRP evaluation (Prince): a randomized trial and cohort study," JAMA, vol. 286, pp. 64–70, 2001, doi: 10.1001/jama.286.1.64.
9. Shao, Q. Xu, X. Yu, et al., "Dipeptidyl peptidase 4 inhibitors and their potential immune modulatory functions," Pharmacol. Ther., vol. 209, p. 107503, 2020, doi: 10.1016/j.pharmthera.2020.107503.
10. -Y. Shao, S.-F. Zhang, H.-D. Li, et al., "Epigenetics and inflammation in diabetic nephropathy," Front. Physiol., vol. 12, 2021, doi: 10.3389/fphys.2021.649587.
11. Pop-Busui, A. J. M. Boulton, E. L. Feldman, et al., "Diabetic neuropathy: a position statement by the American Diabetes Association," Diabetes Care, vol. 40, pp. 136–154, 2017, doi: 10.2337/dc16-2042.
12. Nebbioso, A. Lambiase, M. Armentano, et al., "Diabetic retinopathy, oxidative stress, and sirtuins: an in-depth look in enzymatic patterns and new therapeutic horizons," Surv. Ophthalmol., vol. 67, pp. 168–183, 2022, doi: 10.1016/j.survophthal.2021.04.003.
13. I. Alexandraki, C. Piperi, P. D. Ziakas, et al., "Cytokine secretion in long-standing diabetes mellitus type 1 and 2: associations with low-grade systemic inflammation," J. Clin. Immunol., vol. 28, pp. 314–321, 2008, doi: 10.1007/s10875-007-9164-1.
14. E. Maser, B. D. Mitchell, A. I. Vinik, et al., "The association between cardiovascular autonomic neuropathy and mortality in individuals with diabetes," Diabetes Care, vol. 26, pp. 1895–1901, 2003, doi: 10.2337/diacare.26.6.1895.
15. Jangsiripornpakorn, S. Srisuk, L. Chailurkit, H. Nimitphong, S. Saetung, and B. Ongphiphadhanakul, "The glucose-lowering effect of low-dose diacerein and its responsiveness metabolic markers in uncontrolled diabetes," *BMC Res. Notes*, vol. 15, p. 91, 2022, doi: 10.1186/s13104-022-05974-9.
16. P. Choudhury, J. S. Birks, V. Mani, L. Biasiolli, M. D. Robson, P. L. L'Allier, et al., "Arterial effects of canakinumab in patients with atherosclerosis and type 2 diabetes or glucose intolerance," J. Am. Coll. Cardiol., vol. 68, pp. 1769–80, 2016, doi: 10.1016/j.jacc.2016.07.768.
17. M. Larsen, M. Faulenbach, A. Vaag, A. Vølund, J. A. Ehses, B. Seifert, et al., "Interleukin-1-receptor antagonist in type 2 diabetes mellitus," N. Engl. J. Med., vol. 356, pp. 1517–26, 2007, doi: 10.1056/NEJMoa065213.
18. Dominguez, H. Storgaard, C. Rask-Madsen, T. S. Hermann, N. Ihlemann, D. B. Nielsen, et al., "Metabolic and vascular effects of tumor necrosis factor-alpha blockade with etanercept in obese patients with type 2 diabetes," J. Vasc. Res., vol. 42, pp. 517–25, 2005, doi: 10.1159/000088261.
19. Huang, Y. Yang, R. Hu, and L. Chen, "Anti-interleukin-1 therapy has mild hypoglycaemic effect in type 2 diabetes," Diabetes Obes. Metab., vol. 20, pp. 1024–8, 2018, doi: 10.1111/dom.13140.
20. Kataria, C. Ellervik, and T. Mandrup-Poulsen, "Treatment of type 2 diabetes by targeting interleukin-1: a meta-analysis of 2921 patients," Semin. Immunopathol., vol. 41, pp. 413–25, 2019, doi: 10.1007/s00281-019-00743-6.
21. Everett, M. Donath, A. Pradhan, T. Thuren, P. Pais, J. Nicolau, et al., "Anti-inflammatory therapy with canakinumab for the prevention and management of diabetes," J. Am. Coll. Cardiol., vol. 71, pp. 2392–2401, 2018, doi: 10.1016/j.jacc.2018.03.002.
22. Sloan-Lancaster, E. Abu-Raddad, J. Polzer, J.W. Miller, J.C. Scherer, A. De Gaetano, et al., "Double-blind, randomized study evaluating the glycemic and anti-inflammatory effects of subcutaneous LY2189102, a neutralizing IL-1β antibody, in patients with type 2 diabetes," Diabetes Care, vol. 36, pp. 2239–2246, 2013, doi: 10.2337/dc12-1835.
23. S. Tres, S.C. Fuchs, F. Piovesan, P. Koehler-Santos, F.D.S. Pereira, and S. Camey, "Effect of diacerein on metabolic control and inflammatory markers in patients with type 2 diabetes using antidiabetic agents: A randomized controlled trial," J. Diabetes Res., vol. 2018, p. 4246521, 2018, doi: 10.1155/2018/4246521.
24. V. Rohm, D. T. Meier, J. M. Olefsky, and M. Y. Donath, "Inflammation in obesity, diabetes, and related disorders," Immunity, vol. 55, pp. 31–55, 2022, doi: 10.1016/j.immuni.2021.12.013.
25. A. Ehses, A. Perren, E. Eppler, P. Ribaux, J. A. Pospisilik, R. Maor-Cahn, et al., "Increased number of islet-associated macrophages in type 2 diabetes," Diabetes, vol. 56, pp. 2356–70, 2007, doi: 10.2337/db06-1650.
26. Bendtzen, T. Mandrup-Poulsen, J. Nerup, J. H. Nielsen, C. A. Dinarello, and M. Svenson, "Cytotoxicity of human pI 7 interleukin-1 for pancreatic islets of langerhans," Science, vol. 232, pp. 1545–7, 1986, doi: 10.1126/science.3086977.
27. A. Dinarello, M. Y. Donath, and T. Mandrup-Poulsen, "Role of IL-1beta in type 2 diabetes," Curr. Opin. Endocrinol. Diabetes Obes., vol. 17, pp. 314–21, 2010, doi: 10.1097/MED.0b013e32833bf6dc.
28. Fève and J. P. Bastard, "The role of interleukins in insulin resistance and type 2 diabetes mellitus," Nat. Rev. Endocrinol., vol. 5, pp. 305–311, 2009, doi: 10.1038/nrendo.2009.62.
29. Ruscitti and F. Masedu, "Anti-interleukin-1 treatment in patients with rheumatoid arthritis and type 2 diabetes (TRACK): a multicentre, open-label, randomised controlled trial," PLOS Med., vol. 16, e1002901, 2019, doi: 10.1371/journal.pmed.1002901.
30. Zhang and K. Kim, "TNF-alpha inhibits glucose-induced insulin secretion in a pancreatic beta-cell line (INS-1)," FEBS Lett., vol. 377, pp. 237–239, 1995, doi: 10.1016/0014-5793(95)01272-9.
31. Kägi, A. Ho, B. Odermatt, A. Zakarian, P. Ohashi, and T. Mak, "TNF receptor 1-dependent beta cell toxicity as an effector pathway in autoimmune diabetes," J. Immunol., vol. 162, pp. 4598–4605, 1999, doi: 10.4049/jimmunol.162.8.4598.
32. M. Fernández-Real, A. López-Bermejo, A.B. Ropero, S. Piquer, A. Nadal, J. Bassols, et al., "Salicylates increase insulin secretion in healthy obese subjects," J. Clin. Endocrinol. Metab., vol. 93, pp. 2523–2530, 2008, doi: 10.1210/jc.2007-1212.
33. B. Goldfine, V. Fonseca, K.A. Jablonski, Y.D. Chen, L. Tipton, M.A. Staten, et al., "Salicylate (salsalate) in patients with type 2 diabetes: a randomized trial," Ann. Intern. Med., vol. 159, pp. 1–12, 2013, doi: 10.7326/0003-4819-159-1-201307020-00003.