Abstract
Inflammation plays an important role in chronic obstructive pulmonary disease (COPD). Increasing evidence points to the role of inflammation in the pathogenesis of type 2 diabetes mellitus (T2DM). We investigated the adiponectin: leptin and IL-8 genes in COPD-induced T2DM patients, along with the effect of polymorphism on the levels of these cytokines. We enrolled COPD, COPD plus T2DM, and healthy subjects from the institution according to standard criteria. Further, we drew a blood sample and performed genotypic analysis and an enzyme-linked immunosorbent assay (ELISA). We enrolled a total of 500 subjects in this study, including 250 controls, 191 COPD patients, and 59 COPD patients with T2DM. Genotyping of leptin (C/T), adiponectin (C/G), and IL-8 (C/T) polymorphisms was performed. Serum levels of leptin, adiponectin, and IL-8 were significantly higher (P < 0.001) in COPD with diabetes when compared with COPD in healthy individuals. The genotype frequency of the “CT” leptin gene variant was significantly associated with the risk of developing COPD by 3.7 folds, although it was not associated with the development of T2DM in COPD. Whereas genotype ‘TT’ was significantly associated with the risk of developing T2DM in COPD patients by 2.4 folds. It indicates that individuals with genotype ‘TT’ are at higher risk of developing COPD, and moreover, they are at higher risk of developing T2DM. We conclude that genotypes ‘TT’ of leptin, ‘GG’ diponectin, and ‘TT’ of IL-8 may be exploited as biomarkers for the prognosis and diagnosis of T2DM in COPD and COPD, respectively. While ‘CT’ of IL-8 was a protective biomarker against COPD.
Keywords: Chronic obstructive pulmonary disease, Type 2 diabetes mellitus, ELISA, Genotyping, Correlation, Inflammation
Introduction
Inflammation plays an important role in chronic obstructive pulmonary disease (COPD) [1]. Increasing evidence points to the role of inflammation in the pathogenesis of type 2 diabetes (T2D) [2]. Irritation in COPD is a risk factor for the development of type 2 diabetes mellitus (T2DM) as a comorbid condition. While COPD is a persistent lung problem, perhaps the most significant idea is the irritation occurring in the disease, which is caused mainly by neutrophils. The prevalence of T2D is increasing significantly, while COPD is the third leading cause of death worldwide. The complications of T2D and COPD impact the quality of life, and shorten life expectancy as well as increase the financial burden. Apart from being a major cause of sickness within oneself, COPD can be a potential risk factor for the development of pro-inflammatory conditions such as T2D. Many studies have found that diabetes mellitus (DM) causes an accelerated decline in lung functions as compared to non-diabetics [3]. Mannino et al., found that there is a high risk of diabetes in patients with moderate or higher COPD [4]. A study investigating the factors that are associated with new-onset diabetes in the UK concluded that patients with frequent exacerbations of COPD were more likely to develop T2DM. Higher exposure to inhaled corticosteroid (ICS), a commonly prescribed treatment for COPD was also found to be associated with an increased incidence of T2DM. People who suffer from an exacerbation of COPD experience longer hospital stays and a higher risk of death when they have uncontrolled diabetes. The need to use corticosteroid therapy during exacerbations can complicate the status of DM in those patients [5].
India is a major contributor to the burden of COPD, which is considered to be one of the highest in the world. Mortality from COPD is four times higher in India than in the US and Europe. Increased exposure to smoking and biomass fuel is expected to dramatically increase this number. Researchers understand COPD as a novel risk factor for emerging T2DM due to chronic inflammation, oxidative stress, insulin resistance, weight gain, and fat dysfunction. On the other hand, the spread of DM is increasing rapidly worldwide. India is considered the diabetes capital of the world, with 41 million people suffering from DM, and one in five diabetics in the world is Indian. A growing DM epidemic has emerged in both rural and urban areas, given the significant change in lifestyle, eating habits, decrease in physical activity, and obesity in the urban population of India.
Adipose tissues act as an endocrine organ, secreting various adipokines that are involved in metabolic processes [6]. T2DM is caused by problems with the body’s hormones and fat cells that get worse over time. This leads to inflammation and insulin resistance in obese individuals. Adiponectin-Secreted Frizzled-Related Protein 5 (SFRP5) calms adipokines created by fat tissues. It is the most popular and most copious adipokine found in human serum, with fixations ordinarily in the µg/Ml. Leptin is a primarily pro-inflammatory adipokine that affects both innate and adaptive immune responses [4]. Leptin is a 16-kDa protein copied by the ‘obese’ (ob) gene. It is a member of the cytokine family and performs a variety of biological functions. Genius fiery cytokines are associated with COPD [7]. Pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs) trigger a cytokine cascade that initially is composed of the pro-inflammatory cytokines (IL-1, IL-6, IL-8, IL-12, IFN-γ, IL-18, and TNF itself) [8]. These cytokines serve to contain and resolve the inflammatory foci through the activation of local and systemic inflammatory responses.
We intend to investigate the biomarkers in adiponectin, leptin and the IL-8 gene in COPD-induced T2DM patients. Along with this, we analyzed the effect of polymorphism on the levels of these cytokines.
Materials and Methods
Study Design and Setting
This was a case-control study of patients diagnosed with COPD as per the Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria 2019 carried out at the inpatient and outpatient departments of respiratory medicine of our institution from July 2020 to April 2021. A total of 500 subjects, including 250 controls, 191 COPD, and 59 COPD with T2DM each, aged 30–70 years, were enrolled in the study after meeting the inclusion criteria. Each subject provided written informed consent before inclusion in the study. Age-and sex-matched controls were selected. Study subjects were enrolled with no history of respiratory or any other disease. The institutional ethics committee (Ref No. 90th ECM II B-FS/P2) of the institution approved the study protocol. Study flow chart is stated in Fig. 1.
Fig. 1.
Study flow-chart. COPD, chronic obstructive pulmonary disease; T2DM, type 2 diabetes mellitus; ELISA, enzyme linked immunosorbent assay
Diagnostic Criteria for COPD
The criteria for diagnosis and severity of COPD were taken as per GOLD guidelines 2019. According to it, COPD is diagnosed if the post-bronchodilator FEV1/FVC ratio is < 0.70. Based on the level of obstruction, COPD severity was determined (GOLD, 2019). The patients were excluded from the study if they had pulmonary conditions other than COPD (e.g., TB, HIV infection), connective tissue disorders, chronic renal failure, chronic liver disease, malignancies on long-term steroid or cytotoxic drug therapy, or were chronic alcoholics. The information on the same was obtained from the detailed history, clinical examination, chest radiography, and medications used by the patient currently or previously.
Diagnostic Criteria for Diabetes
The screening and diagnosis of T2DM were done according to guidelines, which stipulated that fasting blood glucose (FBG) be used with cut-off thresholds in line with those recommended by the WHO. In brief, FBG > 126 mg/dL indicates DM; FBG from 110 to < 126 mg/dL indicates impaired fasting glucose; and FBG < 110 mg/dL is normal. We enrolled the patients who were already diagnosed with T2DM as “known DM” cases with COPD in the study. Patients whose diabetes status was not clear had gone for random blood sugar (RBS) testing, and if it was more than 126 mg/dL, the subjects were further evaluated with FBS and post-prandial blood sugar (PPBS). If FBS was more than 126 mg/dL or PPBS was more than 200 mg/dL, the subjects were confirmed as having DM, after which they were classified as new T2DM cases with COPD. All the participants will undergo a glycosylated hemoglobin (HbA1C) evaluation.
Blood Sampling and Analysis
5.0 ml of the whole blood sample was collected from each participant in plain vials for serum separation, and after that, it was stored at − 80 °C for further estimation of adiponectin, leptin, and IL-8 levels by the ELISA method. All the variables that were to be estimated in the study group comprised three types of subjects: healthy controls, COPD, and COPD with T2DM.
Genotyping
We extracted DNA from frozen EDTA blood samples using the salting-out method (Miller et al., 1988) with slight modifications. We performed isolation, quantification, and quality assessment. We determined the quality of DNA using gel electrophoresis and quantitated the amount using a UV–Vis spectrophotometer (Shimadzu, Japan). We performed genotyping of adiponectin, leptin, and IL-8 using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis. The primers were designed by Primer 3.0 (ver online) software, and restriction enzymes were selected using NEB cutter (ver online). The reaction mixture for PCR contained DNA template (100 ng, Taq Buffer (1X, forward and reverse primers (10 pmol each), dNTPs (200 µM, taq polymerase-0.5U, and MQ water for final volume makeup. We digested the amplified PCR products according to the enzyme specifications. The digested fragments representing genotypes were electrophoresed on 12% polyacrylamide gel electrophoresis (PAGE)/ 2.5% agarose gels. The details of primers, annealing temperature, restriction enzymes (RE), and product sizes are given in Table 1.
Table 1.
Summary of SNPs, primer sequences, annealing temperatures, restriction enzyme and product sizes
| Gene variant (rs ID) |
Primer sequences | Restriction enzymes | Annealing temperature (°C)/ Product size (bp) | Product size after digestion |
|---|---|---|---|---|
| Adiponectin A/G (rs710445) |
F:5′GAATTGTCTGAACCTGGGAG3′ R:5′CAGCTCAAAACAACCAGGAT3′ |
Nla111 (CATG) |
56/300 | 300, 159, 141 |
|
Leptin C/T (rs2060713) |
F:5′GGGGCTCCACATTCTACTCT3′ R:5′TTTCCTCTGAGTGCTACTGAAG3′ |
BslHKAI (GWGCWC) |
59/271 | 271, 192, 91 |
|
IL-8 C/T (rs2227306) |
F-5′CTCTAACTCTTTATATAGGAATT-3′ R:5′GATTGATTTTATCAACAGGCA-3′ |
EcoRI (CCCTTT) |
58/278 | 278, 168, 98 |
SNP, single nucleotide polymorphism; bp, base pair
Measurement of Serum Levels of Adiponectin, Leptin, and IL-8
We have measured the serum levels by ELISA kit- adiponectin [Human Adiponectin (ADP) ELISA Kit, Cat no. KTE60939; Abbkine, Inc, China], leptin [Elikine Human Leptin ELISA Kit, Cat no. KTE6026; Abbkine, Inc, China], IL-8 [EliKine Human IL-8 ELISA Kit, Cat no. KET6018; Abbkine, Inc, China] following manufactures’ protocol.
Statistical Analysis
We performed the analysis using SPSS 20.0 (Chicago, Inc., USA). The analysis presents the results as mean ± SD and percentages. The Kolmogorov test was used to test patterns for a normal distribution. Reconstruction showed a non-normal pattern of these parameters. For two-group comparisons, we used the Mann-Whitney U test, and for multiple comparisons between the groups, we used the Kruskal-Wallis test followed by Tukey’s post hoc comparisons to compare the levels of leptin, adiponectin, IL-4, IL-6, and IL-8 among different severity levels of COPD. For determining associations between COPD, BMI, and smoke pack years, Spearman’s rank correlation tests were performed. The p-value < 0.05 was considered significant.
Results
In the present study, a total of 250 healthy controls and 250 COPD subjects were enrolled. Out of 250 COPD patients, 59 had COPD with T2DM. The demographic profile, age-wise distribution, HbA1C, and glycemic levels of COPD patients are given in Table 1. The maximum number of patients (32.0%) were in the age range of 60–70. The HbA1C and glycemic levels were increasing with increasing severity and were highest for the GOLD IV stage in COPD with T2DM patients (Table 2). All the pulmonary function test (spirometry) parameters are given in Table 3. It was observed that the post-vital capacities were significantly different in all three categories. The values of category third, which is COPD with T2DM, were most severely affected.
Table 2.
Demographic profile, age wise distribution, HbA1C and glycemic levels in patients of COPD and COPD + T2DM
| S. no. | Variables | Number (%) |
|---|---|---|
| 1. | Total COPD patients | 191 |
| 2. | COPD patients with T2DM | 59 (24) |
| 3. | Age distribution of COPD patients | |
| 40–50 | 46 (18.4) | |
| 51–60 | 63 (25.2) | |
| 61–70 | 80 (32.0) | |
| 71–80 | 61 (24.4) | |
| 4. | Gender distribution of COPD patients | |
| Male | 139 (55.6) | |
| Female | 111 (44.4) | |
| 5. | Smoking status of COPD patients | |
| Smoker | 204 (81.6) | |
| Non-Smoker | 46 (18.4) | |
| 6. | HbA1C levels of COPD with T2DM patients (mean ± SD) | |
| GOLD I | 3.2 ± 0.9 | |
| GOLD II | 4.2 ± 0.9 | |
| GOLD III | 5.6 ± 0.9 | |
| GOLD IV | 6.25 ± 1.8 | |
| 7. | Glycemia (mmol/l) levels of COPD with T2DM patients (mean ± SD) | |
| GOLD I | 2.63 ± 0.7 | |
| GOLD II | 3.89 ± 0.8 | |
| GOLD III | 5.62 ± 0.9 | |
| GOLD IV | 7.67 ± 3.7 | |
HbA1C, glycosylated hemoglobin; COPD, chronic obstructive pulmonary disease; T2DM, type 2 diabetes mellitus; %, percentage; SD, standard deviation; GOLD, Global Initiative for Chronic Obstructive Lung Disease.
Table 3.
Spirometry parameters of controls, COPD and COPD + T2DM
| S. no. | Spirometry parameters | Healthy control (n = 250) |
COPD (n = 191) |
COPD with diabetes (n = 59) | P-value |
|---|---|---|---|---|---|
| 1. | Post FVC (Lt) | 4.03 ± 0.7 | 2.1 ± 0.7 | 2.9 ± 0.7 | < 0.001 |
| 2. . | Post FEV1/FVC (%) | 101.4 ± 7.1 | 55.1 ± 9.5 | 62.1 ± 9.5 | < 0.001 |
| 3. | Post FEV1 (Lt) | 2.5 ± 0.6 | 1.13 ± 0.5 | 1.9 ± 0.5 | < 0.001 |
| 4. | Post FEV1 (%) predicted | 89.9 ± 7.7 | 44.7 ± 18.8 | 52.7 ± 18.8 | < 0.001 |
| 5. | % Change in FEV1 | 7.9 ± 7.1 | 10.3 ± 13.2 | 11.3 ± 13.2 | 0.015 |
*p < 0.05, **p < 0.01, ***p < 0.001
COPD, chronic obstructive pulmonary disease; T2DM, type 2 diabetes mellitus; FVC, forced vital capacity; FEV1, forced expiratory volume in 1 s
Estimation of Cytokine Levels in Serum
The distribution of adiponectin levels in the serum of healthy controls, COPD patients, and COPD patients with diabetes is shown in Fig. 2. Adiponectin serum levels (ng/mL) were significantly (P < 0.001) higher in COPD with T2DM patients when compared with COPD and healthy control subjects. It shows that the levels of leptin (ng/mL) in the blood were significantly (P < 0.001) higher in COPD patients with T2DM compared to COPD patients without T2DM and healthy control subjects (Fig. 3). There was a significant difference (P < 0.001) in the levels of IL-8 (pg/mL) between COPD patients with T2DM and healthy control subjects who did not have diabetes (Fig. 4).
Fig. 2.
Adiponectin serum levels in healthy control, COPD, and COPD + T2DM patients. COPD, chronic obstructive pulmonary disease; T2DM, type 2 diabetes mellitus
Fig. 3.
Leptin serum levels in healthy control, COPD, and COPD + T2DM patients. COPD, chronic obstructive pulmonary disease; T2DM, type 2 diabetes mellitus
Fig. 4.
IL-8 serum levels in healthy control, COPD, and COPD + T2DM patients. IL-8, interleukin-8, COPD, chronic obstructive pulmonary disease; T2DM, type 2 diabetes mellitus
Genotyping
Genotyping of leptin (C/T), adiponectin (C/G), and IL-8 (C/T) polymorphisms was performed in all 250 healthy controls, 191 COPD subjects, and 59 COPD subjects with T2DM. It was observed that the leptin genotypes ‘CT’ and ‘TT’ were significantly associated with COPD with a high odds ratio (3.728, 4.579, respectively). Interestingly, genotype ‘TT’ was also associated with COPD + T2DM and increased the risk of developing T2DM in COPD patients by 2.4 folds (Table 4). Adiponectin (C/G) polymorphism was not associated with COPD, but it showed a significant association with COPD + T2DM and increased the risk of developing T2DM in COPD patients by 2.6 fold (Table 3). IL-8 (C/T) polymorphism was significantly associated with COPD; genotype ‘TT’ was seen to increase the risk by 5.1 folds. IL-8 (C/T) was not found to be associated with COPD + T2DM.
Table 4.
Genotype frequency of leptin (C/T), adiponectin (C/G) and IL-8 (C/T) polymorphisms in controls, COPD and COPD + T2DM
| Genotype | Control (n = 250) |
COPD (n = 191) |
P-value | OR (95% CI) |
COPD + T2DM (n = 59) |
P-value | OR (95% CI) |
|---|---|---|---|---|---|---|---|
| Leptin C/T (rs710445) | |||||||
| CC | 208 (83.2) | 106 (55.5) | Ref. | Ref. | 28 (47.5) | Ref. | Ref. |
| CT | 30 (12.0) | 57 (29.8) | 0.001*** |
3.73 (2.26–6.15) |
13 (22.0) | 0.694 |
0.86 (0.42–1.80) |
| TT | 12 (4.8) | 28 (14.7) | 0.001*** |
4.58 (2.24–9.37) |
18 (30.5) | 0.016* |
2.43 (1.18–5.02) |
| Adiponectin C/G (rs2060713) | |||||||
| CC | 140 (56.0) | 114 (59.7) | Ref. | Ref. | 36 (61.1) | Ref. | Ref. |
| CG | 87 (34.8) | 66 (34.5) | 0.731 |
0.93 (0.62–1.39) |
14 (23.7) | 0.26 |
0.67 (0.34–1.34) |
| GG | 23 (9.2) | 11 (5.8) | 0.170 |
0.59 (0.28–1.26) |
09 (15.2) | 0.051 |
2.59 (0.99–6.75) |
| IL-8 C/T(rs2227306) | |||||||
| CC | 90 (36.0) | 34 (17.8) | Ref. | Ref. | 13 (22.0) | Ref. | Ref. |
| CT | 120 (48.0) | 80 (41.9) | 0.022* |
1.77 (1.09–2.87) |
28 (47.5) | 0.82 |
0.91 (0.42–1.98) |
| TT | 40 (16.0) | 77 (40.3) | 0.001*** |
5.10 (2.94–8.83) |
18 (30.5) | 0.24 |
0.611 (0.27–1.39) |
*p < 0.05, **p < 0.01, ***p < 0.001
COPD, chronic obstructive pulmonary disease; T2DM, type 2 diabetes mellitus; n, number of participants; OR, odds ratio; CI, confidence interval
The allele ‘T’ of leptin C/T (rs710445) was significantly associated with the risk of developing COPD by 3.5 folds, and it was also associated with the risk of developing T2DM along with COPD by 1.7 folds (Table 4). Adiponectin C/G (rs2060713) allele ‘G’ was significantly associated with COPD with T2DM (Table 5). IL-8 C/T (rs2227306) allele ‘T’ was significantly associated with the risk of developing COPD by 2.4 folds, but it was not showing association with COPD with T2DM (Table 5).
Table 5.
Allele frequency of Leptin (C/T), Adiponectin (C/G) and IL-8(C/T) polymorphisms in controls, COPD and COPD + T2DM
| Allele | Control (n = 500) |
COPD (n = 382) |
P-value | OR (95% CI) |
COPD + T2DM (n = 118) |
P-value | OR (95% CI) |
|---|---|---|---|---|---|---|---|
| Leptin C/T (rs710445) | |||||||
| C | 446(89.2) | 269(70.4) | 0.001*** |
3.47 (2.43–4.96) |
69 (58.5) | 0.016* |
1.69 (1.10–2.59) |
| T | 54 (10.8) | 113(29.6) | 49 (41.5) | ||||
| Adiponectin C/G (rs2060713) | |||||||
| C | 367 (73.4) | 294 (76.9) | 0.227 |
0.83 (0.61–1.13) |
86 (72.9) | 0.034* |
0.505 (0.27–0.95) |
| G | 133 (26.6) | 88 (23.1) | 73 (27.1) | ||||
| IL-8 C/T (rs2227306) | |||||||
| C | 300 (60.0) | 148 (38.7) | 0.001*** |
2.372 (1.81–3.12) |
54 (45.8) | 0.18 |
0.750 (0.49–1.14) |
| T | 200 (40.0) | 234 (61.3) | 64 (54.2) | ||||
*p < 0.05, **p < 0.01, ***p < 0.001
COPD, chronic obstructive pulmonary disease; T2DM, type 2 diabetes mellitus; n, number of participants; OR, odds ratio; CI, confidence interval
Discussion
Our study found that T2DM affected 24% of patients with COPD, showing significant gender differences and smoking status. Mahishale et al. observed that the prevalence of DM in COPD patients was 25.63% [9]. In a few other studies, it was observed that deranged blood glucose was seen in more than 50% of the patients admitted with acute exacerbations of COPD [5, 10, 11]. Our study showed that a significant number of diabetics—59 (24%)—were newly detected. They were not aware of their diabetic status. It is proven beyond doubt that COPD is a condition that predisposes to developing T2DM. Similarly, Rana et al. observed that COPD patients had a multivariate relative risk of 1.38 folds for new-onset T2DM [11]. Feary et al. showed an odds ratio of 2.04 for the development of new-onset diabetes in COPD patients [2].
The present study showed that COPD patients with T2DM had a statistically significant decline in FEV1, and the duration of COPD was longer. Our findings are in line with other studies. The third National Health and Nutrition Examination Survey observed declining lung functions in people with diabetes compared to nondiabetics. Another important aspect worth mentioning here is that impaired pulmonary function is likely to deteriorate rapidly in uncontrolled diabetes. This is in agreement with the Fremantle Diabetes Study, which showed that comorbid DM was associated with lower values of FEV1, FVC, peak expiratory flow (PEF), and VC. A significant decrease in pulmonary function was found among diabetic patients (FEV1, FEV1/FVC%, forced expiratory flow (25–75%), maximal voluntary ventilation, and PEF) compared with healthy controls, further proving that the decline was exaggerated in poorly controlled DM.
This study signifies that adipokine and pro-inflammatory cytokines were higher in COPD with T2DM when compared to COPD and the healthy control group. Our data showed that the association of T2DM with COPD was present; there was also a significant association with pack years and BMI with COPD and COPD with diabetes in all biomarkers that we had studied. To the best of our knowledge, this is the first study to quantitatively clarify the association between COPD, lung function, and T2DM. A previous meta-analysis by Malte Rasmussen et al. [12] found that people with COPD had a higher risk of T2DM (OR 1.17, 95% CI 1.01–1.35). However, this meta-analysis included four cohort studies and three case control studies. Subgroup analyses that separated cohort studies and case-control studies did not find a link between COPD and T2DM, which was different from what we found.
In our study, we found statistically significant results for serum biomarkers in the studied groups. Leptin serum levels were significantly higher (P < 0.001) in COPD with diabetes when compared with COPD and healthy controls. Likewise, adiponectin serum levels were also increased in both groups of COPD with diabetes when compared with COPD and healthy controls. Proinflammatory cytokines were also increased in the COPD/diabetes group and were statistically significant with a P < 0.001 when they were compared with COPD and healthy controls. Hence, adipokine and proinflammatory cytokines play an important role in all the studied groups. The association between diabetes and a decline in lung function is linked at multiple levels, mainly systemic inflammation, glucotoxicity, and insulin resistance. A large body of evidence has demonstrated systemic inflammation to be the major culprit underlying the impairment of lung function by diabetes.
Adipokine and pro-inflammatory cytokine biomarkers are increased in patients with COPD and have been observed to be up-regulated in patients with T2D when compared to the healthy control group, suggesting that inflammation may be the common link [10]. Elevated levels of leptin, adiponectin, IL-8, IL-6, and IL-4 have been shown to predict the development of the insulin resistance syndrome and T2D, supporting a role for inflammation in the pathogenesis of diabetes. We also found that the incidence of DM was statistically more significant in a COPD-diagnosed patient than in those without COPD [11].
When COPD patients were contrasted with healthy subjects, patients with COPD had higher insulin levels, which are identified with incendiary markers, for example, IL-8, IL-6, IL-4, and solvent receptors for TNF-α, adipokine, leptin, and adiponectin. The methodology of our examination didn’t permit us to verify or refute this speculation. In any case, it demonstrated that cigarette smoking isn’t a connection between DM and COPD. This is critical data since tobacco is key to the advancement of COPD and a free and modifiable determinant of DM. Smoking produces oxidative pressure that can enact neighborhood and foundational irritation. In the event that cigarette smoking isn’t a connection, it is conceivable that different instruments past fundamental irritation may clarify the connection between DM and COPD.
A noteworthy correlation between COPD and the risk of T2DM has enormously raised interest in studying the underlying biological mechanisms. It is well known that genetic susceptibility is one of the notable characteristics of T2DM, with a 40% life-time risk of T2DM for descendants when a parent has T2DM and the risk increasing to 70% when both parents have T2DM. This feature might indicate that COPD and diabetes tend to develop simultaneously and indirectly support the hypothesis that COPD and diabetes mellitus could be two different expressions of the systemic inflammatory syndrome [13].
Our results also support this hypothesis when correlation was done with pack years versus leptin, adiponectin), IL-8, IL-6, and IL-4 among healthy control, COPD, COPD with diabetes, respectively. There was a significant positive correlation found in all the groups with a P-value (< 0.001), or we can say that as the pack years and BMI increases, the serum markers also increase accordingly.
In terms of prognostic implications, there is the need to better understand the link between COPD and T2DM, and in particular, whether the centre of therapy should be shifted to the systemic inflammatory state [14]. We should also understand whether treatment of COPD influences the course of DM or is altered by the presence of the concomitant comorbid disease. It is also important to know whether the treatment of T2DM can alter the natural history of concomitant COPD [8].
Leptin is increased in COPD and COPD with diabetes when compared with healthy controls, resulting in a significant increase in both diseases with a significant P-value (< 0.001). Leptin differentially increases the production of TH1 cytokines (IL-2, INF-γ, and TNF-alpha) and suppresses the production of TH2 cytokines (IL-4, IL-5, and IL-10). When BMI (kg/m2) and pack years were correlated with leptin serum levels in healthy control, COPD, and COPD with diabetes, we found a significant positive correlation with a statistically significant P-value (< 0.001), so we can say that as the BMI and pack years of patients increase, leptin serum levels also increase in all three groups, i.e., healthy control, COPD, and COPD with diabetes, so they are directionally proportional to each other.
Some human studies have detected higher circulating adiponectin levels in COPD and COPD with diabetes patients when compared with healthy controls. Both normal- and underweight patients with COPD and COPD with diabetes exhibited elevated plasma adiponectin levels, as demonstrated by some researchers. Moreover, investigators have found that previous smoking decreases serum adiponectin levels in a dose-dependent manner [14]. Recently, it was claimed that higher plasma adiponectin levels were associated with decreased BMI, female sex, older age, and lower bronchial reversibility in patients with COPD. These findings suggest that adiponectin is associated with BMI and smoke pack years with COPD and COPD with diabetes, but virtually nothing is known about the associations of adiponectin with important clinical parameters like lung function, symptoms, or treatment responsiveness [15]. When BMI (kg/m2) and pack years were correlated with adiponectin serum levels in healthy control, COPD, and COPD with diabetes, we found a significant positive correlation with a statistically significant P-value (< 0.001), so we can say that as the BMI and pack years of patients increase, adiponectin serum levels also increase in all three groups: healthy control, COPD, and COPD with diabetes, so they are directionally proportional to each other.
Various cell types secrete IL-8, a pro-neutrophilic chemokine. IL-8 has been suggested to play an important role in COPD, especially in the severity of the disease. In our study, analyzing IL-8 serum levels with regard to clinical parameters of COPD demonstrated several significant results. IL-8 is a selective chemoattractant of neutrophils [16]. In this study, the concentration of serum IL-8 in asthmatic and COPD patients was significantly higher than that in controls [17]. One study found a significant increase in levels of IL-8 in the plasma and sputum of asthmatic and COPD patients compared with normal subjects. The increased levels of IL-8 in the airway secretions of patients with asthma, asthma with diabetes, and COPD may be a marker of an ongoing inflammatory process that is pronounced in patients with asthma and COPD. IL-8 may play a primary role in the activation of neutrophils in asthma and COPD, and it may serve as a marker in evaluating the severity of airway inflammation [18]. When BMI (kg/m2) and pack years were correlated with IL-8 serum levels in healthy control, COPD, and COPD with diabetes, we found a significant positive correlation with a statistically significant P-value (< 0.001), so we can say that as the BMI and pack years of patients increase, IL-8 serum levels also increase in all three groups, i.e., healthy control, COPD, and COPD with diabetes, so they are directionally proportional to each other.
It is obscure why individuals with COPD are influenced with T2DM more frequently than controls. There are a few systems, for example, expanded corpulence, decreased physical movement, expanded tobacco smoke and corticosteroid presentation and sickness related irritation, oxidative pressure and hypoxia, which may add to the expanded commonness of diabetes in COPD patients [19].
The characteristic pathological change of COPD is a chronic inflammatory response in the respiratory tract and lung parenchyma, particularly during acute exacerbations. Moreover, available evidence has found that insulin resistance in COPD patients is associated with inflammation mediators such as C-reactive protein (CRP), IL-6, and TNF-α. Some studies have suggested that increased levels of inflammation and oxidative stress are plausible links with insulin resistance in COPD patients. This is an interesting theory considering that cigarette smoking can expand the danger of insulin obstruction and diabetes by activating fundamental irritation and oxidative pressure, the two of which are normal in COPD [20].
Lin et al. [20] suggested that basic irritation could be a possible explanation for the link between respiratory problems and diabetes, even though the exact reasons for this are still unknown. Researchers demonstrated an increase in the levels of obstruction (e.g., TNF-alpha, IL-6, or CRP) in patients with COPD [20]. As per a similar report, these mediators may contribute to the development of T2DM [21].
It is not fully understood how COPD can pose a T2DM hazard. The most conceivable clarification is that these diseases can give T2DM a typical provocative premise. COPD is a burning lung problem that involves various routes of provocation [22]. The atomic factor-kB (NF-kB) signaling pathway may play a central role in the pathogenesis of COPD. NF-kB is a translation factor that makes a number of cool burn properties happen, such as IL-6, TNF-α, and binding atoms. Elevated circulating levels of these provocative cytokines have been linked to the progression of prediabetic insulin obstruction and the movement toward clear T2DM. The etiology of T2DM is enigmatic and multifactorial, including various hereditary and ecological variables. COPD and T2DM all had strong effects, indicating that there may be a typical route of exacerbation and that the expert’s key provocative components largely reach mirror levels for both diseases [23].
The genotype frequency of ‘CT’ of the leptin gene variant was showing a significant association with the risk of developing COPD by 3.7 folds. But it was not associated with the development of T2DM in COPD cases. Whereas genotype ‘TT’ had a highly significant association with the risk of developing T2DM in COPD patients by 2.4 fold. This means individuals with genotype ‘TT’ are at higher risk of developing COPD, and they are also at higher risk of developing T2DM (Table 3). Adiponectin (C/G) polymorphism did not show association with COPD, but it was showing significant association with COPD + T2DM, i.e., COPD cases with genotype ‘GG’ are at increased risk of encountering COPD by 2.6 folds (Table 3). The genotype frequency of ‘TT’ of IL-8 (C/T) polymorphism was significantly associated with the risk of COPD by 5.1 fold. Whereas in heterozygous conditions, it was seen to be protective against the risk of COPD by 1.8 fold. IL-8 (C/T) was not found to be associated with COPD + T2DM.
Limitations
A particular population was studied; hence, the results may not apply to other demographic locations. Ethnicity, socioeconomic level, and geography affect COPD and T2DM prevalence and features. The study may have overlooked confounding variables that could affect COPD, T2DM, and biomarkers. Comorbidities, medicine, and lifestyle choices may complicate correlations. Diabetes is identified by self-reporting or detection during the study, which may induce recall bias or underestimate diabetes prevalence. The study examines biomarkers, although they’re typically nonspecific and affected by several circumstances. The study genotypes polymorphisms, but genetics may complicate the correlations revealed. Future research could address these shortcomings and use a prospective design, random sampling, and a more thorough investigation of potential confounding variables to improve the study’s findings and external validity. Research with varied populations and validation studies would improve our understanding of COPD, T2DM, and biomarkers.
Conclusion
Leptin, adiponectin, and IL-8 are involved in COPD pathogenesis hence, these cytokines may cause metabolic changes in COPD patients. IL-8 also has the role of reducing the aspiration and increasing the severity in COPD patients. COPD patients are at a higher risk of developing type 2 diabetes regardless of common risk factors for diabetes, including smoking. Our results confirm the theory that the inexorable deterioration of the airways can increase the risk of type 2 diabetes due to hidden pro-inflammatory components. The link between COPD and comorbid diabetes mellitus shows the importance of expanding care and reducing the risk of diabetes for patients with pneumonia. We also conclude that genotypes ‘TT’ of leptin, ‘GG’ of adiponectin, and ‘TT’ of IL-8 may be exploited as biomarkers for the prognosis and diagnosis of T2DM in COPD and COPD, respectively. While ‘CT’ of IL-8 was a protective biomarker against COPD. It is crucial to develop and update prevention methods to enhance the overall health of potential COPD patients, who are also at a high risk for other persistent comorbidities.
Acknowledgements
We would like to thank all the participants who were given their consent to participate in the study. Authors are grateful to Indian Council of Medical Research (ICMR), New Delhi for fellowship to SS.
Author Contributions
All the authors significantly contributed to the manuscript. SS wrote the early draft of the manuscript, and all of the authors have read, approved, and agreed to be responsible for all parts of the work.
Funding
Financial support was obtained from Indian Council of Medical Research (ICMR), New Delhi, India (Ref No. 67/02/2018-IMM/BMS, dated: 27/03/2018).
Declarations
Conflict of interest
Authors declare no conflict of interest.
Ethical Approval
Study protocol was approved by Institutional Ethics Committee (IEC), King George’s Medical University, Lucknow, Uttar Pradesh, India (Ref Code: 90th ECM II B-FS/P2, dated 01-10-2018).
Consent for Publication
Written informed consent was obtained from all the participants.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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