1 Introduction

Smoking is a major public health concern associated with several comorbidities and substantially increased mortality rates globally. Tobacco is recognized as the third leading risk factor contributing to Daily Adjusted Life Years (DALYs) by the Global Burden of Disease study [1, 2]. The ill effects of the high pervasiveness of smoking and alcohol consumption contribute to increased risk for various physical and mental health complications [3, 4]. Smoking bidi and hookah are considered to be more harmful smoking habits than smoking cigarettes. Studies have reported increased risk for smoking associated chronic diseases among bidi smokers than those who smoke cigarette. Bidi contain 3–5 times increased content of nicotine, carbon monoxide (CO) and 1.5 times higher carcinogenic hydrocarbon than those of cigarette [5]. Similarly, hookah is known to have 36 times higher content of nicotine than cigarette. Further, the higher burning temperature required in smoking hookah leads to emission of various harmful gases, exposing the user to two times increased concentration of CO than cigarette [6]. However, despite innumerable adverse health consequences of smoking hookah and bidi, it is espoused as a cultural practice in several communities [7], including the Jats of Palwal, Haryana (the community being studied in the present study) [8].

Smoking has been suggested to influence the epigenetics of an individual via different mechanisms Tobacco contains various toxic substances such as heavy metals, aromatic hydrocarbons, aromatic amines, cotinine, nicotine, etc., whose regular intake in one form or another, leads to epigenetic alterations, cell senescence, inflammations, immune dysfunction, etc. [9]. Epigenetic mechanisms, for instance DNA methylation, histone modification and non-coding RNA, can affect the gene activity at translational and post-translational level, resulting in cell differentiation, chromatin modifications, imprinting, X chromosome inactivation etc. [10]. DNA methylation is the most extensively studied epigenetic mechanism for its potential role in regulation of various biological processes such as cell development, differentiation, aging, cellular imprinting, etc. [11]. DNA methylation refers to the covalent transfer of methyl group to the fifth carbon of cytosine residues in CpG dinucleotides via DNA methyltransferases (DNMTs) [12]. Being reversible in nature, DNA methylation is governed by various intrinsic (genetic framework) and extrinsic factors (smoking, alcohol, physical activity, diet, and eating habits) [13].

Smoking tobacco is recognized as one of the chief environmental alternants of DNA methylation [14]. DNA methylation is now emerging as a signature bio-marker for the present, never, and former smokers. Previous studies have shown that DNA methylation changes associated with smoking predispose individuals to various chronic diseases [15]. A number of studies have tried to explore the dynamic interaction of smoking and DNA methylation [16, 17] and reported smoking-related global hypomethylation and promoter (site-specific) hypermethylation in different genes [17].

However, despite advances in research exploring the relationship between smoking and gene-specific and genome-wide DNA methylation, there is a lack of studies investigating the smoking-induced modifications in global DNA methylation, especially in communities where smoking has been adopted as a culture for ages. Considering this research gap, the present study aims to investigate the variances in Peripheral blood leucocytes (PBL) global DNA methylation levels with smoking in the Jat community of Palwal, Haryana.

Jat community is a large, ethnic, and endogamous community of North and North-west India [18]. Smoking hookah is a widely practiced cultural trait among the Jats of Haryana, leading to a very high prevalence of smoking in the community, even among females and young adults. Hookah is a type of waterpipe in which a flexible long tube connected with a water bowl, used to smoke tobacco. Though, in modernistic way, it is now becoming popular among youth and western culture, hookah smoking has been practiced for generations in rural parts of North and North West India [19]. Hookah is an integral part of Jat identity and is associated with the feeling of pride in Haryanvi culture, often manifested through idioms like “Jat ke that, hookah aur khaat” (Hookah and Khat are the pride of Jats) [20]. Besides hookah, smoking bidi is also becoming prevalent in the community. All these practices lead to continuous exposure of commoners to harmful smoke (either actively or passively).

Further, in our previous study on the same population, a significant decline in PBL global DNA methylation levels in older individuals (≥ 60 years) was observed [21]. Thus, the present study also investigates the relationship between smoking and PBL global DNA methylation levels separately among those < 60 and ≥ 60 years of age.

2 Material and methods

2.1 Study design and recruitment of participants

A community-based cross-sectional study design was adopted for the present study. The data for the present investigation has been derived from a major research project. Altogether 1075 individuals of either sex (69.8% females), aged 30–75 years, unrelated up to first cousin, belonging to the Jat community from rural areas of Palwal, Haryana, North India, were recruited for the present investigation.

Pregnant women, lactating mothers, and individuals with self-reported chronic cardiovascular disease (CVDs) (viz coronary heart disease, congenital heart disease, stroke), other chronic disease conditions for instance renal failure, liver failure, cancer, hepatitis etc., and mental disorders were excluded from the study as these factors can affect DNA methylation. Notably, cardiovascular risk factors such as hypertension, obesity, dyslipidemia were not the basis for exclusion.

Informed written voluntary consent in their local language was taken from each recruited participant. Ethical clearance for the research protocol was procured from the institutional ethics committee, Department of Anthropology, University of Delhi (Ref No. Anth/2018/2890/1/28-12-2018).

2.2 Data collection and blood collection

Data on socio-demographic variables (age, sex, education, occupation), smoking status and patterns and other lifestyle variables (diet) were collected using pre-tested interview schedules. Overnight fasting blood (5 ml) sample was collected from willing participants by a phlebotomist. DNA was extracted from blood samples by the salting out method [22]. DNA quality check was executed via nanodrop spectrophotometer with A260/A280 ~ 1.8 as a standard. For further analysis, DNA samples were kept at − 80 °C.

2.3 Categorization of smokers

The following criteria were used to classify participants into different smoking categories: Non-smokers: Those participants who reported having never smoked in their lifetime were categorized as non-smokers (n = 476).

Smokers: Those individuals who were active smokers at the time of the interview and had smoked at least 30 doses of hookah or 100 bidis or an equivalent combination of the two in their lifetime were categorized as smokers (n = 572). Based on the use of hookah/bidi or both per day, smokers were further categorized into light smokers (n = 359) and heavy smokers (n = 185). The median numbers of bidis (median bidi/day = 10) and hookahs per day (median hookah/day = 3) were calculated for reference. Individuals who smoked (i) more than 10 bidis/day, (ii) more than 3 hookah/day, or (iii) an equivalent combination of both bidi and hookah in a day were considered heavy smokers. Others were categorized as light smokers.

Former smokers: Those individuals who reported having smoked at least 30 doses of hookah or 100 bidis or an equivalent combination of the two in their lifetime but had not smoked at least for the last one month were classified as former smokers (n = 27).

2.4 Global DNA methylation analysis

Global DNA methylation of PBL DNA samples was performed using Epigentek Methylflash™ kits (Epigentek Group Inc., New York, U.S.A.), which worked on the principle of ELISA-based colorimetric method. The methylated antibodies provided by manufacturers in the kit were used for estimating global DNA methylation in terms of percentage of 5-methylcytosine (5mC%) content in PBL DNA samples, followed by reading absorbance at 450 nm through MultiscanGo Spectrophotometer, Thermo Fisher Scientific, Waltham, Massachusetts, USA. 200 ng of each DNA samples were used, and methylation assays were performed in duplicates. Inter and intra-assay variances were observed to be less than 5%. Global DNA methylation was performed by a single individual to constrain handling variation.

2.5 Calculation of percentage of methylated DNA

To calculate percentage of methylated DNA, a standard curve was generated by plotting the optical density (OD) values versus the Positive Control at each percentage point (including Negative control, 0.1, 0.2, 0.5, 1, 2, 5%). After this, slope (OD/1%) of the standard curve was determined using linear regression and the most linear part of the standard curve was used for optimal slope calculation. The percentage of methylated DNA (5mC%) was calculated in total DNA using the following formula.

$$5mC\% = \frac{Sample\;OD - NCOD}{{Slope\;X S}} X 100\%$$

where Sample OD = Optical density of samples at 450 nm; NC OD = Optical density of Negative Control at 450 nm; Slope = Slope (OD/1%) of the standard curve will be determined using linear regression and the most linear part of the standard curve will be used for optimal slope calculation; S = amount amount of input sample DNA in ng.

The calculated 5mC% values are the estimated percentage of methylated cytosine content relative to the whole DNA content (A + T + G + C).

2.6 Statistical analysis

Statistical analysis was done using SPSS version 22.0. All continuous variables were tested for normality using the Kolmogorov–Smirnov normality test. Variables with non-normal distribution were represented by their median and respective inter-quartile range (IQR). Chi-square was used to determine variations in the frequency distribution. The Mann–Whitney U test was used to determine the significance of differences in median levels of the two groups. Non-smokers, smokers, and former smokers were categorized into < 60 years and ≥ 60 years of age groups to study the impact of age in modulating smoking-induced alterations in global DNA methylation. Spearman correlation and linear regression were used to understand the correlation and association of DNA methylation levels with smoking status in the studied sample. Three correlation models and equivalent regression models were used to understand the correlation and association between DNA methylation levels and smoking status. To construct the models, DNA methylation values were loaded as a continuous variable along with smoking statuses coded as the dichotomous variable (i) non-smoker (coded 0) versus smoker (coded 1); (ii) non-smoker (coded 0) versus former smoker (coded 1); and (iii) smoker (coded 0) versus former smoker (coded 1), one at a time. Statistical significance was considered at p value ≤ 0.05.

3 Results

3.1 General characteristics among non-smokers, smokers, and former smokers

The distribution of sociodemographic and lifestyle variables (age, sex, education, occupation, and diet) among non-smokers, smokers, and formers smokers suggested that the proportions of older participants, males, non-vegetarians, and employed individuals were significantly higher in smokers and former smokers as compared to non-smokers (Table 1).

Table 1 Distribution of socio-demographic and lifestyle variables among non-smokers, smokers, and former smokers

3.2 Variation in global DNA methylation with different smoking statuses

To study the variations in global DNA methylation levels among non-smokers, smokers, and former smokers, the median (IQR) global DNA methylation levels of each group were compared (Table 2). Further, to understand the age-wise differences in median global DNA methylation levels of non-smokers, smokers, and former smokers, further categorization was done in two age groups of < 60 years and ≥ 60 years (Table 2). Overall and also in age-cohort-wise analysis, no significant differences in the median global DNA methylation level of non-smokers and smokers were observed. However, the median global DNA methylation level of former smokers was significantly lower than that of smokers and non-smokers (Table 2).

Table 2 Overall and age-wise percentage of global DNA methylation level among non-smokers, smokers, and former smokers

3.3 Correlation and regression analysis

Non-smoker versus smoker correlation and regression models revealed no significant correlation or association between global DNA methylation levels and smoking. However, both the non-smoker versus former smoker and smoker versus former smoker correlation models revealed a significant negative correlation between global DNA methylation and former smoker status. Again, the non-smoker versus former smoker and smoker versus former smoker regression models found former smoker status to be associated with a significant decline of 0.493 units and 0.442 units in global DNA methylation levels, respectively (Table 3).

Table 3 Variations in global DNA methylation with change in smoking status

3.4 Variation in global DNA methylation with the intensity of smoking

To understand the differences in global DNA methylation levels with the intensity of smoking (frequency of bidi and hookah use per day), the median global DNA methylation levels for heavy smokers and light smokers were calculated (Table 4). No significant difference in the median global DNA methylation levels of heavy and light smokers was found (Table 4).

Table 4 Median (IQR) global DNA methylation level (5mC%) among heavy smokers and light smokers

4 Discussion

The present cross-sectional study has attempted to evaluate the effect of smoking on PBL global DNA methylation in healthy controls and the effect of age (< 60 years and ≥ 60 years) in regulating this relationship. The perusal of various factors (genetics, lifestyle, environment) contributing to aberrant epigenetics has caught the attention of health scientists in understanding the etiology of numerous chronic diseases [23]. Smoking is one of the most important lifestyle variables that affect epigenetics and gene transcription. Altered DNA methylation patterns attributable to smoking have been explored as an early biomarker for infertility and various comorbidities [24, 25].

The present study revealed no significant differences in median global DNA methylation levels of smokers and non-smokers in the overall as well as age-stratified analysis. Further smokers, against non-smokers, were not found to be significantly associated with alterations in global DNA methylation levels in correlation and regression models. However, former smokers were found to be hypomethylated in both overall and age-stratified analysis (< 60 years and ≥ 60 years) when compared to smokers and non-smokers. The adjusted regression model (adjusted for age, sex, diet, and occupation) also suggested a significant negative association between global DNA methylation and former smoker status against both non-smokers and smokers. These observations are in concordance with several previous studies that have reported no significant difference in global DNA methylation levels of non-smokers and smokers [17, 23]. Further, Avram et al., estimated global DNA methylation using buccal cells and reported global DNA hypomethylation among former smokers [17]. Previous studies, using genomic DNA extracted from blood cells, have also examined association between Alu, Line global methylation, and cigarette smoking. Their findings suggested no significant association between global DNA methylation and smoking [26,27,28]. On contrary, research using oral epithelial cells, have reported global DNA hypomethylation and gene-specific hypermethylation in smokers [29]

However, other studies (EWAS, genome-wide, and gene-specific), measured DNA methylation using DNA extracted from alveolar macrophage [30] and blood cells [14, 31, 32] have reported hypomethylation in individuals who smoke cigarette as compared to non-smokers [14, 30,31,32]. Moreover, a positive correlation between DNA methylation and time of smoking abstinence has also been reported [14]. Nevertheless, several studies have revealed both hypermethylation and hypomethylation of differential CpG islands with respect to smoking status [33].

The possible reason for no significant differences in global DNA methylation levels of smokers and non-smokers in the present study may be the high prevalence of smoking in this community leading to the constant exposure of participants to harmful smoking environments, either by active or passive smoking. The varying sociocultural aspects of different communities play a pivotal role in this complex interplay of prohibition or permittance of smoking tobacco [34]. Smoking hookah is highly prevalent in the Jat community, representing their traditional custom. Owing to the cultural acceptance of smoking in the studied community, besides males, a high proportion of females (42.4%) as well practice smoking without any hindrances. One crucial aspect worth highlighting is maternal smoking during pregnancy and the breastfeeding period in the studied community, which is likely to expose fetuses and infants to tobacco/hookah smoke during the pre- and postnatal periods.

Several studies have suggested the effect of maternal behavior and habits on the development of the fetus (both lifelong and transgenerational) [35]. For instance, the differential stages (such as reprogramming and maintenance of methylation followed by genome-wide demethylation of other genes excluding imprinted genes and reestablishment of methylation patterns in non-imprinted genes before embryo implantation) during fetal development are the potential susceptible windows to the epigenetic aberrations [36]. Previous studies have reported increased risk for various chronic health conditions [37, 38], global hypomethylation, and gene-specific hypermethylation among children who were exposed to tobacco smoke prenatally/antenatally in comparison to children who were not [39, 40]. Hence, continuous exposure to tobacco smoke during the prenatal stage and also in later stages of life may be contributing to the new environmental adaptations resulting in no significant epigenetic alterations among individuals belonging to the communities where smoking is practiced on a regular basis.

Coming to the hypomethylation status of former smokers in this study, the apparent reasons for this finding are not very clear. Nonetheless, it has been observed that people usually stop smoking as a result of one or the other serious health conditions necessitating the cessation of smoking. Studies have reported that former smokers were at increased risk for cardiovascular diseases even after five years of smoking cessation [41]. Further, obesity, hypertension etc. are well known risk factors for chronic CVDs, and were also observed to be associated with hypomethylation [42, 43]. Further, studies have suggested that during initial phase of smoking cessation, various physiological changes occur due to nicotine withdrawal resulting in adverse health conditions such as indigestion, sudden weight gain, oral ulcers etc., which may alter DNA methylation [44]. Therefore, DNA hypomethylation among former smokers in the present study may be attributable to the underlying health condition.

Further, no significant difference in median global DNA methylation levels of heavy and light smokers was observed. This observation is in contrast to previous reports, where a significant increase in global DNA methylation levels has been reported among heavy smokers in comparison to light smokers [17]. Despite an expanding body of literature exploring smoking-mediated alterations in DNA methylation, the clear-cut magnitude and direction of change in DNA methylation remain enigmatic. More studies are needed to explain the relationship between smoking patterns and alterations in DNA methylations in varying environmental and cultural contexts.

There are certain limitations of the current study that must be stated. The present study is cross-sectional in nature, which limits the ability to establish the causality of hypomethylation among former smokers. Further, the precise duration of smoking was not recorded, which may have affected the results. Also, the results are subjected to responder bias as the data analysis has been performed on the information provided by participants about their smoking behavior.

5 Conclusion

Overall, no significant differences were observed in median global DNA methylation levels of smokers and non-smokers and of heavy smokers compared to light smokers. However, the study revealed a significant relative global DNA hypomethylation among former smokers compared to non-smokers and smokers. The findings suggest that in communities where smoking has been accepted as a traditional trait, the constant and lifelong exposure of commoners to harmful tobacco smoke may result in new environmental adaptations. Owing to this, smoking may be influencing the global DNA methylation levels in a unique manner in such communities. The observed hypomethylation in formers smokers may be due to smoking-related health conditions. However, larger studies in parallel communities need to be taken up to explore the relationship between smoking and global DNA methylation and the role of constant exposure to smoke in influencing this relationship.