Cigarette smoking is one of the most common habits of the modern world. It is reported by the World Health Organization (WHO) that 30% of the world’s population over the age of 15 smoked cigarettes (Kulikowska-Karpińska and Czerw 2015).
Oxidative stress caused by smoking reflects an imbalance between the systemic manifestation of reactive oxygen species (ROS) and a biological system’s ability to promptly detoxify the reactive intermediates or to repair the subsequent harm. Disturbances in the typical redox condition of cells can cause lethal impacts through the creation of peroxides and free radicals that harm all segments of the cell, including lipids, proteins, and DNA (Andersson 2017). The potential damage caused by free radicals found in tobacco smoke is minimized by biological antioxidant mechanisms including enzymatic and non-enzymatic reactions (Mahapatra et al. 2008). Antioxidant enzymes such as superoxide dismutase are an important line of defense against oxidative cell damage preventing lipid peroxidation and overproduction of malondialdehyde (Kamceva et al. 2016). Total antioxidant capacity is frequently used to assess the cumulative effects of antioxidants in a biological sample and can evaluate the antioxidant response against the free radicals produced (Rubio et al. 2016).
Damage to DNA is indicated by increased levels of 8-OHdG, a repair product of the oxidation of guanine in DNA. It can be detected in human tissues, blood or urine, and is considered a reliable and pivotal biomarker of generalized and cellular oxidative stress (Liu et al. 2018). Also, it is an important biomarker for various pathological conditions such as aging, carcinogenesis, neurodegenerative, and cardiovascular diseases as estimated by quantitative analytical techniques in blood and urine (Valavanidis et al. 2009).
Cotinine, a metabolite of nicotine, is a specific biomarker of tobacco smoking exposure. Using this biomarker increases the measured precision for the association between 8-OHdG and smoking (Lu et al. 2014).
Therefore, the current study aimed to investigate nicotine-induced oxidative stress by estimating blood 8-OHdG level and assessing its relation with some lifestyle determinants. Oxidant stress marker (MDA) and antioxidant defense enzyme (SOD) as well as cotinine and TAC levels were also measured.
Participants and methods
The current study is a case control study in which healthy male participants were randomly selected and interviewed after taking their informed consent as well as obtaining the approval of the study design from the Research Ethics Committee at KasrAlainy, Faculty of Medicine.
The study represented collaboration between Forensic Medicine and Clinical Toxicology Department and Medical Biochemistry Department, Faculty of Medicine, Cairo University, Egypt. The study was conducted according to the Declaration of Helsinki (World Medical Association 2013).
A premade Arabic questionnaire was answered; it included questions about socio-demographic data, smoking status, space ventilation, exercise, tea, coffee, energy drinks, and alcohol consumption, present, past, and family history of diseases.
Inclusion criteria
Ninety male participants, aged 20–60 years, were enrolled in the study. According to Lodovici et al. (2005), participants were classified according to their smoking history into three groups:
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Non-smokers (20 cases) ➔ never smoked and not exposed to environmental tobacco smoking (ETS).
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Passive smokers (30 cases) ➔ non-smokers but exposed to ETS in poorly ventilated areas for > 3 h/day in the year.
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Active smokers (40 cases) ➔ > 3 cigarettes/day for over 1 year.
Exclusion criteria
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Medical disorders ➔ diabetes, autoimmune diseases, cardiovascular and neurodegenerative diseases, hepatic and renal diseases, infections, cancer, chronic skin ulcerations, and endocrine and hematologic disorders (Chen et al. 2017).
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Medications ➔ steroids, non-steroidal anti-inflammatory, diuretics, anticonvulsants, antidepressants, antibiotics, and vitamin supplementation.
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Participants receiving mutagenic and carcinogenic drugs, chemotherapy, and/or radiotherapy.
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Participants living near or working in industrial areas.
Study measurements and estimations
Body weight and height were measured for all participants. Peripheral venous blood samples were withdrawn (3 ml) into EDTA tubes. The collected whole blood was centrifuged for approximately 20 min at 1000–3000 rpm (rpm) within 30 min after collection. The supernatant was collected carefully and stored at − 80 °C.8-OHdG, cotinine, SOD, and TAC levels were estimated in plasma using ELISA kits, while MDA was estimated by colorimetry.
ELISA kits
Human 8-OHdG ELISA kit (Cat No. MBS267161) was provided by My Biosource Company, USA. According to manual instructions provided by the applied kit, double-sandwich ELISA technique was used where the pre-coated antibody was human 8-OHdG monoclonal antibody and the detecting antibody was polyclonal antibody which was biotin-labeled. Samples and biotin labeling antibody were added into ELISA plate wells and washed out with phosphate-buffered saline (PBS) followed by avidin-peroxidase conjugates which were added in order.
The reactant was washed out thoroughly by PBS, tetramethylbenzidine (TMB) substrate was then used for coloring. It turned blue in peroxidase and finally yellow under the action of acid. Human cotinine ELISA kit (Cat No. MBS019457) was provided by My Biosource Company, USA, while Human SOD and TAC ELISA kits (Cat No. BYEK1111) were provided by Chongqing Biospes Company, China. According to manual instructions provided by the applied kits, purified anti-substance antibody was pre-coated onto well plates and the horseradish peroxidase (HRP) conjugated anti-substance antibody was used as detection antibodies. Standards, test samples, and HRP conjugated detection antibody were added to the wells subsequently, mixed and incubated, then, the unbound conjugates were washed away with wash buffer. Tetramethylbenzidine substrates (A and B) were used to visualize HRP enzymatic reaction. It is catalyzed by HRP to produce a blue color product that changes into yellow after adding acidic stop solution. The density of yellow was proportional to the substance amount of sample captured in plate (Mamsen et al. 2010; Gao et al. 2018; Antunes-Lopes et al. 2018).
Calculation: Absorbance of the optical density (O.D.) was read at 450 nm in a microplate reader and then the concentration of substance was calculated.
$$ \mathrm{Relative}\ \mathrm{O}.\mathrm{D}.450=O.D.450\ \mathrm{of}\ \mathrm{each}\ \mathrm{well}-\mathrm{O}.\mathrm{D}.450\ \mathrm{of}\ \mathrm{blank}/\mathrm{control}\ \mathrm{well} $$
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The standard curve can be plotted as the relative O.D. 450 of each standard solution (Y) versus the respective concentration of the standard solution (X). A line was drawn to connect each coordinate point of standard solution. Sample concentrations were found by checking sample O.D. reading. It is recommended to employ the professional curve software (e.g., curve expert 1.3) to analyze and compute the results.
Colorimetric method
Malondialdehydecolorimetric kit (Cat No. MD 25 29) was provided by Biodiagnostic Company, Egypt. According to manual instructions provided by the applied kit, thiobarbituric acid (TBA) reacted with MDA in acidic medium at 95 °C for 30 min to form TBA-reactive product, and this is a sensitive assay method for lipid peroxidation (Aboutaleb et al. 2019).
$$ \mathrm{Plasma}=\kern0.5em \frac{\mathrm{A}\ \mathrm{sample}}{\mathrm{A}\ \mathrm{standard}}\times 10\ \mathrm{nmol}/\mathrm{ml} $$
Statistical analysis of data
Microsoft excel 2013 was used for data entry after coding and the statistical package for social science (SPSS) version 21 (SPSS, Armonk, NY: International Business Machines Corporation) was used for data analysis. Simple descriptive statistics (arithmetic mean and standard deviation) were used for summary of quantitative data and frequencies were used for qualitative data. Bivariate relationship was displayed in cross tabulations and comparison of proportions was performed using the chi-square test. Independent t test, one-way analysis of variance (ANOVA), and post hoc tests were used to compare normally distributed quantitative data. The level of significance was set at probability (p) value ≤ 0.05 and p value < 0.001 was considered as highly significant. Correlations between variables were done using Pearson correlation coefficient (r) which was able to describe both correlation direction (positive or negative according to the sign) and power (weak correlation if < 0.5, moderate correlation from 0.5 and 0.7 and strong correlation if > 0.7) (Dawson and Trapp 2004).