Genetic diversity fuels gene discovery for tobacco and alcohol use.

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

Identifying risk factors involved in the common versus specific liabilities to substance use: A genetically informed approach.

Individuals most often use several rather than one substance among alcohol, cigarettes or cannabis. This widespread co-occurring use of multiple substances is thought to stem from a common liability that is partly genetic in origin. Genetic risk may indirectly contribute to a common liability to substance use through genetically influenced mental health vulnerabilities and individual traits. To test this possibility, we used polygenic scores indexing mental health and individual traits and examined their association with the common versus specific liabilities to substance use. We used data from the Avon Longitudinal Study of Parents and Children (N = 4218) and applied trait-state-occasion models to delineate the common and substance-specific factors based on four classes of substances (alcohol, cigarettes, cannabis and other illicit substances) assessed over time (ages 17, 20 and 22). We generated 18 polygenic scores indexing genetically influenced mental health vulnerabilities and individual traits. In multivariable regression, we then tested the independent contribution of selected polygenic scores to the common and substance-specific factors. Our results implicated several genetically influenced traits and vulnerabilities in the common liability to substance use, most notably risk taking (bstandardised = 0.14; 95% confidence interval [CI] [0.10, 0.17]), followed by extraversion (bstandardised = -0.10; 95% CI [-0.13, -0.06]), and schizophrenia risk (bstandardised = 0.06; 95% CI [0.02, 0.09]). Educational attainment (EA) and body mass index (BMI) had opposite effects on substance-specific liabilities such as cigarette use (bstandardised-EA = -0.15; 95% CI [-0.19, -0.12]; bstandardised-BMI = 0.05; 95% CI [0.02, 0.09]) and alcohol use (bstandardised-EA = 0.07; 95% CI [0.03, 0.11]; bstandardised-BMI = -0.06; 95% CI [-0.10, -0.02]). These findings point towards largely distinct sets of genetic influences on the common versus specific liabilities.

Proper conditional analysis in the presence of missing data: Application to large scale meta-analysis of tobacco use phenotypes.

Meta-analysis of genetic association studies increases sample size and the power for mapping complex traits. Existing methods are mostly developed for datasets without missing values, i.e. the summary association statistics are measured for all variants in contributing studies. In practice, genotype imputation is not always effective. This may be the case when targeted genotyping/sequencing assays are used or when the un-typed genetic variant is rare. Therefore, contributed summary statistics often contain missing values. Existing methods for imputing missing summary association statistics and using imputed values in meta-analysis, approximate conditional analysis, or simple strategies such as complete case analysis all have theoretical limitations. Applying these approaches can bias genetic effect estimates and lead to seriously inflated type-I or type-II errors in conditional analysis, which is a critical tool for identifying independently associated variants. To address this challenge and complement imputation methods, we developed a method to combine summary statistics across participating studies and consistently estimate joint effects, even when the contributed summary statistics contain large amounts of missing values. Based on this estimator, we proposed a score statistic called PCBS (partial correlation based score statistic) for conditional analysis of single-variant and gene-level associations. Through extensive analysis of simulated and real data, we showed that the new method produces well-calibrated type-I errors and is substantially more powerful than existing approaches. We applied the proposed approach to one of the largest meta-analyses to date for the cigarettes-per-day phenotype. Using the new method, we identified multiple novel independently associated variants at known loci for tobacco use, which were otherwise missed by alternative methods. Together, the phenotypic variance explained by these variants was 1.1%, improving that of previously reported associations by 71%. These findings illustrate the extent of locus allelic heterogeneity and can help pinpoint causal variants.

Evaluating the relationship between alcohol consumption, tobacco use, and cardiovascular disease: A multivariable Mendelian randomization study.

BACKGROUND: Alcohol consumption and smoking, 2 major risk factors for cardiovascular disease (CVD), often occur together. The objective of this study is to use a wide range of CVD risk factors and outcomes to evaluate potential total and direct causal roles of alcohol and tobacco use on CVD risk factors and events. METHODS AND FINDINGS: Using large publicly available genome-wide association studies (GWASs) (results from more than 1.2 million combined study participants) of predominantly European ancestry, we conducted 2-sample single-variable Mendelian randomization (SVMR) and multivariable Mendelian randomization (MVMR) to simultaneously assess the independent impact of alcohol consumption and smoking on a wide range of CVD risk factors and outcomes. Multiple sensitivity analyses, including complementary Mendelian randomization (MR) methods, and secondary alcohol consumption and smoking datasets were used. SVMR showed genetic predisposition for alcohol consumption to be associated with CVD risk factors, including high-density lipoprotein cholesterol (HDL-C) (beta 0.40, 95% confidence interval (CI), 0.04-0.47, P value = 1.72 × 10-28), triglycerides (TRG) (beta -0.23, 95% CI, -0.30, -0.15, P value = 4.69 × 10-10), automated systolic blood pressure (BP) measurement (beta 0.11, 95% CI, 0.03-0.18, P value = 4.72 × 10-3), and automated diastolic BP measurement (beta 0.09, 95% CI, 0.03-0.16, P value = 5.24 × 10-3). Conversely, genetically predicted smoking was associated with increased TRG (beta 0.097, 95% CI, 0.014-0.027, P value = 6.59 × 10-12). Alcohol consumption was also associated with increased myocardial infarction (MI) and coronary heart disease (CHD) risks (MI odds ratio (OR) = 1.24, 95% CI, 1.03-1.50, P value = 0.02; CHD OR = 1.21, 95% CI, 1.01-1.45, P value = 0.04); however, its impact was attenuated in MVMR adjusting for smoking. Conversely, alcohol maintained an association with coronary atherosclerosis (OR 1.02, 95% CI, 1.01-1.03, P value = 5.56 × 10-4). In comparison, after adjusting for alcohol consumption, smoking retained its association with several CVD outcomes including MI (OR = 1.84, 95% CI, 1.43, 2.37, P value = 2.0 × 10-6), CHD (OR = 1.64, 95% CI, 1.28-2.09, P value = 8.07 × 10-5), heart failure (HF) (OR = 1.61, 95% CI, 1.32-1.95, P value = 1.9 × 10-6), and large artery atherosclerosis (OR = 2.4, 95% CI, 1.41-4.07, P value = 0.003). Notably, using the FinnGen cohort data, we were able to replicate the association between smoking and several CVD outcomes including MI (OR = 1.77, 95% CI, 1.10-2.84, P value = 0.02), HF (OR = 1.67, 95% CI, 1.14-2.46, P value = 0.008), and peripheral artery disease (PAD) (OR = 2.35, 95% CI, 1.38-4.01, P value = 0.002). The main limitations of this study include possible bias from unmeasured confounders, inability of summary-level MR to investigate a potentially nonlinear relationship between alcohol consumption and CVD risk, and the generalizability of the UK Biobank (UKB) to other populations. CONCLUSIONS: Evaluating the widest range of CVD risk factors and outcomes of any alcohol consumption or smoking MR study to date, we failed to find a cardioprotective impact of genetically predicted alcohol consumption on CVD outcomes. However, alcohol was associated with and increased HDL-C, decreased TRG, and increased BP, which may indicate pathways through impact CVD risk, warranting further study. We found smoking to be a risk factor for many CVDs even after adjusting for alcohol. While future studies incorporating alcohol consumption patterns are necessary, our data suggest causal inference between alcohol, smoking, and CVD risk, further supporting that lifestyle modifications might be able to reduce overall CVD risk.

Variants in the CHRNA5-CHRNA3-CHRNB4 Region of Chromosome 15 Predict Gastrointestinal Adverse Events in the Transdisciplinary Tobacco Use Research Center Smoking Cessation Trial.

INTRODUCTION: Reducing adverse events from pharmacologic treatment is an important goal of precision medicine and identifying genetic predictors of adverse events is a step toward this goal. In 2012, King et al. reported associations between genetic variants and adverse events in a placebo-controlled smoking cessation trial of varenicline and bupropion. Strong associations were found between gastrointestinal adverse events and 11 variants in the CHRNA5-CHRNA3-CHRNB4 region of chromosome 15, a region repeatedly associated with smoking-related phenotypes. Our goal was to replicate, in an independent sample, the impact of variants in the CHRNA5-CHRNA3-CHRNB4 region on gastrointestinal adverse events and to extend the analyses to adherence and smoking cessation. METHODS: The University of Wisconsin Transdisciplinary Tobacco Use Research Center (TTURC) conducted a multiarmed, placebo-controlled smoking cessation trial of bupropion and nicotine replacement therapy that included 985 genotyped European-ancestry participants. We evaluated relationships between our key variables using logistic regression. RESULTS: Gastrointestinal adverse events were experienced by 31.6% TTURC participants. Each of the CHRNA5-CHRNA3-CHRNB4 associations from the King et al. study was found in TTURC, with the same direction of effect. Neither these variants nor the gastrointestinal adverse events themselves were associated with adherence to medication or successful smoking cessation. CONCLUSIONS: Variants in the CHRNA5-CHRNA3-CHRNB4 region of chromosome 15 are associated with gastrointestinal adverse events in smoking cessation. Additional independent variants in this region strengthen the association. The consistency between the results of these two independent studies supports the conclusion that these findings reflect biological response to the use of smoking cessation medication. IMPLICATIONS: The fact that our findings from the TTURC smoking cessation trial support the independent findings of King et al. suggest that associations of variants in the CHRNA5-CHRNA3-CHRNB4 region of chromosome 15 with gastrointestinal adverse events while taking medications for smoking cessation reflect biology. However, although adherence to medication was a strong predictor of successful smoking cessation in TTURC, neither adverse events nor the genetic variants associated with them predicted either adherence or successful cessation in this study. Thus, although we should strive to minimize adverse events during treatment, we should not expect that to increase successful smoking cessation substantially.

Systematic Review of Polygenic Gene-Environment Interaction in Tobacco, Alcohol, and Cannabis Use.

Studies testing the effect of single genetic variants on substance use have had modest success. This paper reviewed 39 studies using polygenic measures to test interaction with any type of environmental exposure (G×E) in alcohol, tobacco, and cannabis use. Studies using haplotype combinations, sum scores of candidate-gene risk alleles, and polygenic scores (PS) were included. Overall study quality was moderate, with lower ratings for the polygenic methods in the haplotype and candidate-gene score studies. Heterogeneity in investigated environmental exposures, genetic factors, and outcomes was substantial. Most studies (N = 30) reported at least one significant G×E interaction, but overall evidence was weak. The majority (N = 26) found results in line with differential susceptibility and diathesis-stress frameworks. Future studies should pay more attention to methodological and statistical rigor, and focus on replication efforts. Additional work is needed before firm conclusions can be drawn about the importance of G×E in the etiology of substance use.

Tobacco and alcohol-induced epigenetic changes in oral carcinoma.

PURPOSE OF REVIEW: The present review aims to describe the epigenetic alterations observed in oral cancer linked to the exposure to alcohol and/or tobacco. RECENT FINDINGS: Recent findings emphasize the importance of epigenetics in oral cancer progression and in how risk factors (as tobacco and alcohol) affect the basal epigenetic profiles. Deeper techniques and detailed approaches allowed the perception that individual CG changes and even subtle changes may represent important epigenetic alterations resulting in expression changes and other carcinogenic consequences. New classes of epigenetic alterations including noncoding RNAs have been gaining attention. SUMMARY: Many epigenetic alterations have been described in oral carcinoma progression induced by tobacco and/or alcohol, including: promoter hypermethylation in genes with tumor suppressive activity, global (genome-wide) hypomethylation, change in methylation patterns throughout the genes, alteration in noncoding RNAs, and histones modifications. These changes represent progress in the knowledge of how these risk factors act in a molecular level. There is an urgent need for large independent studies to move these potential makers further and validate them to identify risk assessment, early diagnostic markers, and therapeutic targets, as well as to be the base for prevention and intervention strategies.

Pathways to smoking behaviours: biological insights from the Tobacco and Genetics Consortium meta-analysis.

By running gene and pathway analyses for several smoking behaviours in the Tobacco and Genetics Consortium (TAG) sample of 74 053 individuals, 21 genes and several chains of biological pathways were implicated. Analyses were carried out using the HYbrid Set-based Test (HYST) as implemented in the Knowledge-based mining system for Genome-wide Genetic studies software. Fifteen genes are novel and were not detected with the single nucleotide polymorphism-based approach in the original TAG analysis. For quantity smoked, 14 genes passed the false discovery rate of 0.05 (corrected for multiple testing), with the top association signal located at the IREB2 gene (P=1.57E-37). Three genomic loci were significantly associated with ever smoked. The top signal is located at the noncoding antisense RNA transcript BDNF-AS (P=6.25E-07) on 11p14. The SLC25A21 gene (P=2.09E-08) yielded the top association signal in the analysis of smoking cessation. The 19q13 noncoding RNA locus exceeded the genome-wide significance in the analysis of age at initiation (P=1.33E-06). Pathways belonging to the Neuronal system pathways, harbouring the nicotinic acetylcholine receptor genes expressing the α (CHRNA 1-9), ß (CHRNB 1-4), γ, δ and ɛ subunits, yielded the smallest P-values in the pathway analysis of the quantity smoked (lowest P=4.90E-42). Additionally, pathways belonging to 'a subway map of cancer pathways' regulating the cell cycle, mitotic DNA replication, axon growth and synaptic plasticity were found significantly enriched for genetic variants in ever smokers relative to never smokers (lowest P=1.61E-07). In addition, these pathways were also significantly associated with the quantity smoked (lowest P=4.28E-17). Our results shed light on one of the world's leading causes of preventable death and open a path to potential therapeutic targets. These results are informative in decoding the biological bases of other disease traits, such as depression and cancers, with which smoking shares genetic vulnerabilities.

All in the Family? A Twin-Based Analysis of Associations Between Occupational Risk Factors, Drinking, and Tobacco Use in Employed Men.

BACKGROUND: Employment-related substance use can negatively affect both workplace and worker. Relationships between workplace characteristics and substance use may be explained by genetic and environmental effects; this research uses a co-twin control (discordant twin) design to disentangle these influences. METHODS: This study compared population-level to discordant twin pair relationships to analyze the genetic and environmental influences of work-related risks on substance use in N = 2,138 dizygotic and monozygotic male twins from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders. Negative binomial and logistic regressions were fit to predict differences in the frequency of drinking, typical and maximum number of drinks, the number of cigarettes per day, and any binge drinking or any tobacco use across occupation, work hours, job strain, problems with coworkers, and perceived job insecurity. RESULTS: In population-level analyses, several work-related variables were associated with substance use. The population-level associations of occupation with typical and maximum drinks per day and of problems with coworkers to binge drinking were not significant at the twin level. At both the population and discordant twin levels, only higher occupational status was associated with a lower likelihood of regular tobacco use (odds ratio 0.44, 95% confidence interval 0.21, 0.94). CONCLUSIONS: Variation in genes and shared environment appears to account for many of the population-level relationships between work-related stressors and substance use. Work stressors may not be the most fruitful intervention point when aiming to reduce alcohol or tobacco use, although men in certain high-stress occupations may be at greater risk for substance use.

Tobacco carcinogen-metabolizing genes CYP1A1, GSTM1, and GSTT1 polymorphisms and their interaction with tobacco exposure influence the risk of head and neck cancer in Northeast Indian population.

Genetic polymorphisms in tobacco-metabolizing genes may modulate the risk of head and neck cancer (HNC). In Northeast India, head and neck cancers and tobacco consumption remains most prevalent. The aim of the study was to investigate the combined effect of cytochrome P450 1A1 (CYP1A1) T3801C, glutathione S-transferases (GSTs) genes polymorphisms and smoking and tobacco-betel quid chewing in the risk of HNC. The study included 420 subjects (180 cases and 240 controls) from Northeast Indian population. Polymorphisms of CYP1A1 T3801C and GST (M1 & T1) were studied by polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) and multiplex PCR, respectively. Logistic regression (LR) and multifactor dimensionality reduction (MDR) approach were applied for statistical analysis. LR analysis revealed that subjects carrying CYP1A1 TC/CC + GSTM1 null genotypes had 3.52-fold (P < 0.001) increase the risk of head and neck squamous cell carcinoma (HNSCC). Smokers carrying CYP1A1 TC/CC + GSTM1 null and CYP1A1 TC/CC + GSTT1 null genotypes showed significant association with HNC risk (odds ratio [OR] = 6.42; P < 0.001 and 3.86; P = 0.005, respectively). Similarly, tobacco-betel quid chewers carrying CYP1A1 TC/CC + GSTM1 null genotypes also had several fold increased risk of HNC (P < 0.001). In MDR analysis, the best model for HNSCC risk was the four-factor model of tobacco-betel quid chewing, smoking, CYP1A1 TC/CC, and GSTM1 null genotypes (testing balance accuracy [TBA] = 0.6292; cross-validation consistency [CVC] = 9/10 and P < 0.0001). These findings suggest that interaction of combined genotypes of carcinogen-metabolizing genes with environmental factors might modulate susceptibility of HNC in Northeast Indian population.

Gene-by-Environment Interactions in Pancreatic Cancer: Implications for Prevention.

Pancreatic cancer (PC) has been estimated to have higher incidence and correspondingly higher mortality rates in more developed regions worldwide. Overall, the age-adjusted incidence rate is 4.9/10(5) and age-adjusted mortality rate is at 4.8/10(5). We review here our current knowledge of modifiable risk factors (cigarette smoking, obesity, diet, and alcohol) for PC, genetic variants implicated by genome-wide association studies, possible genetic interactions with risk factors, and prevention strategies to provide future research directions that may further our understanding of this complex disease. Cigarette smoking is consistently associated with a two-fold increased PC risk. PC associations with dietary intake have been largely inconsistent, with the potential exception of certain unsaturated fatty acids decreasing risk and well-done red meat or meat mutagens increasing risk. There is strong evidence to support that obesity (and related measures) increase risk of PC. Only the heaviest alcohol drinkers seem to be at an increased risk of PC. Currently, key prevention strategies include avoiding tobacco and excessive alcohol consumption and adopting a healthy lifestyle. Screening technologies and PC chemoprevention are likely to become more sophisticated, but may only apply to those at high risk. Risk stratification may be improved by taking into account gene environment interactions. Research on these modifiable risk factors is key to reducing the incidence of PC and understanding who in the population can be considered high risk.

An Insight into Survivin in Relevance to Hematological, Biochemical and Genetic Characteristics in Tobacco Chewers with Oral Squamous Cell Carcinoma.

BACKGROUND: Survivin is an inhibitor of apoptosis protein (IAP), encoded by the Baculoviral IAP Repeat Containing 5 (BIRC5) gene located on q arm (25.3) on chromosome 17. It is expressed in various human cancers and involved in tumor resistance to radiation and chemotherapy. The genetic analysis of the BIRC5 gene and its protein survivin levels in buccal tissue related to oral squamous cell carcinoma (OSCC) in South Indian tobacco chewers has not been studied. Hence, the study was designed to quantify survivin in buccal tissue and its association with pretreatment hematological parameters and to analyze the BIRC5 gene sequence. METHOD: In a single centric case control study, buccal tissue survivin levels were measured by ELISA. A total of 189 study subjects were categorized into Group 1 (n = 63) habitual tobacco chewers with OSCC, Group 2 (n = 63) habitual tobacco chewers without OSCC, and Group 3 (n = 63) healthy subjects as control. Retrospective hematological data were collected from Group 1 subjects and statistically analyzed. The BIRC5 gene was sequenced and data were analyzed using a bioinformatics tool. RESULTS: Survivin protein mean ± SD in Group 1 was (1670.9 ± 796.21 pg/mL), in Group 2 it was (1096.02 ± 346.17 pg/mL), and in Group 3 it was (397.5 ± 96.1 pg/mL) with significance (p < 0.001). Survivin levels showed significance with cut-off levels of absolute monocyte count (AMC), neutrophil/lymphocyte ratio (NLR), and lymphocyte/monocyte ratio (LMR) at (p = 0.001). The unique variants found only in OSCC patients were T → G in the promoter region, G → C in exon 3, C → A, A → G, G → T, T → G, A → C, G → A in exon 4, C → A, G → T, G → C in the exon 5 region. CONCLUSIONS: The tissue survivin level increased in OSCC patients compared to controls; pretreatment AMC, LMR, and NLR may serve as add-on markers along with survivin to measure the progression of OSCC. Unique mutations in the promoter and exons 3-5 were observed in sequence analysis and were associated with survivin concentrations.

Blood DNA methylation signatures of lifestyle exposures: tobacco and alcohol consumption.

BACKGROUND: Smoking and alcohol consumption may compromise health by way of epigenetic modifications. Epigenetic signatures of alcohol and tobacco consumption could provide insights into the reversibility of phenotypic changes incurred with differing levels of lifestyle exposures. This study describes and validates two novel epigenetic signatures of tobacco (EpiTob) and alcohol (EpiAlc) consumption and investigates their association with disease outcomes. METHODS: The epigenetic signatures, EpiTob and EpiAlc, were developed using data from the Swiss Kidney Project on Genes in Hypertension (SKIPOGH) (N = 689). Epigenetic and phenotypic data available from the 1921 (N = 550) and 1936 (N = 1091) Lothian Birth Cohort (LBC) studies, and two publicly available datasets on GEO Accession (GSE50660, N = 464; and GSE110043, N = 94) were used to validate the signatures. A multivariable logistic regression model, adjusting for age and sex, was used to assess the association between self-reported tobacco or alcohol consumption and the respective epigenetic signature, as well as to estimate the association between CVD and epigenetic signatures. A Cox proportional hazard model was used to estimate the risk of mortality in association with the EpiTob and EpiAlc signatures. RESULTS: The EpiTob signature was positively associated with self-reported tobacco consumption for current or never smokers with explained variance ranging from 0.49 (LBC1921) to 0.72 (LBC1936) (pseudo-R2). In the SKIPOGH, LBC1921 and LBC1936 cohorts, the epigenetic signature for alcohol consumption explained limited variance in association with self-reported alcohol status [i.e., non-drinker, moderate drinker, and heavy drinker] (pseudo-R2 = 0.05, 0.03 and 0.03, respectively), although this improved considerably when measuring self-reported alcohol consumption with standardized units consumed per week (SKIPOGH R2 = 0.21; LBC1921 R2 = 0.31; LBC1936 R2 = 0.41). Both signatures were associated with history of CVD in SKIPOGH and LBC1936, but not in LBC1921. The EpiTob signature was associated with increased risk of all-cause and lung-cancer specific mortality in the 1936 and 1921 LBC cohorts. CONCLUSIONS: This study found the EpiTob and EpiAlc signatures to be well-correlated with self-reported exposure status and associated with long-term health outcomes. Epigenetic signatures of lifestyle exposures may reduce measurement issues and biases and could aid in risk stratification for informing early-stage targeted interventions.

The impact of prehistoric human dispersals on the presence of tobacco-related oral cancer in Northeast India.

BACKGROUND: Northeast (NE) India is a subject of debate for predicting its involvement in prehistoric anatomically modern human (AMH) dispersal. The unique lifestyle and genetic characteristics of native ethnic groups in this region are believed to be responsible for their susceptibility to tobacco-related oral cancer (TrOC). The present study assessed mitochondrial macro-haplogroup (mHG) diversity and TrOC susceptibility autosomal loci to evaluate the impact of prehistoric AMH dispersal on the present day's high TrOC prevalence in major NE Indian ethnics. METHODS: We considered 175 unrelated individuals from 35 ethnic groups and previously published 374 sequences for sequencing-based assessment of mtDNA-based marker by subsequent analyses like haplogroup diversity, phylogenetic, genetic structure by AMOVA, and MDS, descriptive statistics of demographic parameters, and migration analysis. Besides, we selected prolonged tobacco-chewing 124 case-control individuals from similar ethnic backgrounds for genotyping 115 autosomal loci in Sequenom iPLEX MassARRAY™ platform and mined 1000genome data (n = 398) for consequent global admixture and ancestry-specific allele frequencies-based analyses. RESULTS: Our mtDNA-based findings suggested that NE populations were distinct from other Indian populations, owing to the first wave of migration from ancient southern China (∼54kya) and two successive spatial expansion events at âˆ¼45kya and âˆ¼43kya. Consequently, it probably acted as another source for prehistoric AMH dispersal in N/NE Asia. Besides, the second wave of back-migration from SE Asia (∼40kya) probably replaced the mitochondrial footprints of survivors from the first migrants and introduced the TrOC susceptibility traits in this region. Afterward, the autosomal marker-based observations on the transition of the disease-associated admixture component 'K6' from SE Asia reconfirmed these results. Moreover, we also observed that the mitochondrial mHG 'R' is significantly associated with the risk of TrOC (OR > 9.5) in NE India. Furthermore, the possible onset of the phenotypic expression of those traits was predicted at âˆ¼4kya, thus, contributing to present-day's TrOC prevalence. CONCLUSIONS: This study reflects its uniqueness by revealing an updated AMH dispersal route for the peopling in and out of NE India, which probably introduced the disease-causing traits in the ancestral NE Indian population. Those traits were then imprinted in their genome to get transferred through their respective generations, forming the present-day's TrOC-prevalent NE Indian population.

Promoter Hypermethylation of LATS1 Gene in Oral Squamous Cell Carcinoma (OSCC) among North Indian Population.

BACKGROUND: LATS1 (Large Tumor Suppressor, isoform 1) is a gene that forms a complex with the cyclin-dependent kinase, CDK1, and regulates cell cycle progression. Genetic modifications lead to a loss in the activity of LATS1 gene. OSCC is the most commonly emerging cancer caused by genetic as well as epigenetic changes. Epigenetics changes vary from one population to another because these are influenced by dietary factors and environmental factors.  Tobacco chewing and smoking has been reported as major risk factors in OSCC. No report was found in the previous literature showing promoter hypermethylation of LATS1 gene. METHODS: A total of 50 OSCC patients and 20 normal individuals were recruited in this study. Blood samples (50) from OSCC patients and blood samples (20) from healthy individuals as controls were used in the present study. Isolation of genomic DNA was carried out from blood using the standard phenol-chloroform extraction. Further Isolated DNA was modified with sodium bisulfite using the agarose bead method and finally, the methylation studies of LATS1 gene were carried out using Methylation-Specific PCR (MSP-PCR). RESULTS: 19 out of 50 patients (38.0%) were found to be methylated for LATS1 gene.; a statistically significant result was obtained (p -value= < 0.05) with an odds ratio of 0.37 in cases compared to controls. The status of methylation of LATS1 genes was also found to be statistically significantly associated with smokers and tobacco chewers (p-value = < 0.05). The methylation of LATS1 gene showed a significant risk of developing OSCC in patients. CONCLUSION: These results suggest that the LATS1 gene may provide a better alternative as a diagnostic biomarker. This is the first report on the promoter hypermethylation of LATS1 gene in OSCC patients among the North Indian population.
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Cytogenetic Consequences of Food Industry Workers Occupationally Exposed to Cooking Oil Fumes (COFs).

BACKGROUND: Cooking oil fumes (COFs) with smoking habits is a substantial risk that aggravates genetic modifications. The current study was to estimate the biological markers of genetic toxicity counting Micronucleus changes (MN), Chromosome Aberrations (CA) and DNA modifications among COFs exposures and control subjects inherent from South India. MATERIALS AND METHODS: Present analysis comprised 212 COFs with tobacco users and equivalent number of control subjects. RESULTS: High frequency of CA (Chromatid type: and chromosome type) were identified in group II experimental subjects also high amount of MN and DNA damage frequency were significantly (p < 0.05) in both subjects (experimental smokers and non-smokers). Present analysis was observed absence of consciousness among the COFs exposures about the destructive level of health effects of tobacco habits in working environment. CONCLUSION: COFs exposed workers with tobacco induce the significant alteration in chromosomal level. Furthermore, a high level of rate of genetic diseases (spontaneous abortion) were identified in the experimental subjects. This finding will be helpful for preventive measures of COFs exposed workers and supportive for further molecular analysis.

Comprehensive analysis reveals common DNA methylation patterns of tobacco-associated cancers: A pan-cancer analysis.

The role of tobacco in carcinogenesis has received increasing attention across a number of disciplines in recent years. Accumulating evidences reveal that tobacco consumption affects various epigenetic modifications, especially DNA methylation. However, the genetic modifications of methylation patterns involved in tobacco-attributable cancers remain poorly understood. In this manuscript, aberrant DNA methylation patterns were investigated in 9 tobacco-attributable cancers. Differential methylated probes (DMPs) were identified in each cancer type and a total of 2,392 hyper- and 736 hypomethylated pan-cancer DMPs (PDMPs) were screened out for further analysis. PDMP-associated genes were mostly enriched in metabolism-associated pathways, suggesting the potential roles of methylation alternation in reprogramming cancer cell metabolism. Hypomethylated PDMPs cg12422154, cg02772121 and cg06051311 constituted an enhancer region, significantly downregulating TRIM15, TRIM26 and RPP21, which serve as epigenetically therapeutic biomarkers. Forty-three hypermethylated and 13 hypomethylated transcription factor motifs were clustered into 6 groups, and exhibited various biological functions. Forty-nine PDMPs were reported to be associated with prognosis, providing effective tools to predict clinical outcomes. In summary, our studies revealed the characteristics, influences and potential mechanisms of DNA methylation patterns of tobacco-attributable cancer.

Potential Effect of Tobacco Consumption through Smoking and Chewing Tobacco on IL1beta Protein Expression in Chronic Periodontitis Patients: In Silico Molecular Docking Study.

Detrimental effect of bad oral habits, such as smoking and chewing tobacco, on chronic periodontitis (CP) manifest chronic inflammation of gingival tissues which majorly results in gum bleeding, and teeth loss. A genetic association study of Interleukin 1 beta (IL1ß) has been conducted in CP patients having smoking and chewing tobacco habits in regular life style. A molecular docking study has been consequently done to analyze the effect of tobacco on CP progression in depth. All statistical evaluation has been done by using SPSS v16.0. The findings of the study show the significant association of IL1ß gene polymorphisms with CP increased susceptibility in combination of oral habits as mentioned earlier. The docking profile has showed the highest binding affinity of IL1ß protein with the Nicotine derived Nitrosamine Ketone (NNK), one of the derivatives of nicotine which is in-taken through the habits associated with smoking and chewing tobacco. Nicotine, N-nitrosoanabasine, and N-nitrosonornicotine, the other derivatives, have also demonstrated significant impact over the IL1ß protein-caused altered expression. Thus, this study concluded that the harmful effect of tobacco may increase the inflammation in periodontia by inducing the inflammatory active site of the IL1ß protein in the CP patients.

Transcriptome and methylome analysis of periodontitis and peri-implantitis with tobacco use.

Peri-implantitis is similar to periodontitis in both symptoms and treatment; however, their level of similarity remains controversial. Here, we compared multiple cases of periodontitis and peri-implantitis through transcriptome and methylome profiling, and analyzed the effects of smoking as a typical risk factor. Human gingival tissues were obtained from 20 patients with periodontitis or peri-implantitis via periodontal surgical procedures. Total RNA and genomic DNA were isolated, and transcriptome and methylome datasets were generated. Comprehensive analysis of differential gene expression, DNA methylation, and protein-protein interactions indicated that periodontitis and peri-implantitis share biological similarities; however, hierarchical clustering between the two disease groups revealed distinct molecular characteristics. These differences might be related to structural differences in natural tooth-bone and implant-bone. Additionally, smoking differentially affected periodontitis and peri-implantitis in terms of host-defense mechanism impairment. Within the limitations of this study, the results provide evidence that peri-implantitis is distinct from periodontitis and that smoking potentially affects disease progression. Our study provides a foundation for the rational design of a large-scale study in the future for a more comprehensive analysis that includes microbiome and clinical data.

Epigenome-Wide Tobacco-Related Methylation Signature Identification and Their Multilevel Regulatory Network Inference for Lung Adenocarcinoma.

Tobacco exposure is one of the major risks for the initiation and progress of lung cancer. The exact corresponding mechanisms, however, are mainly unknown. Recently, a growing body of evidence has been collected supporting the involvement of DNA methylation in the regulation of gene expression in cancer cells. The identification of tobacco-related signature methylation probes and the analysis of their regulatory networks at different molecular levels may be of a great help for understanding tobacco-related tumorigenesis. Three independent lung adenocarcinoma (LUAD) datasets were used to train and validate the tobacco exposure pattern classification model. A deep selecting method was proposed and used to identify methylation signature probes from hundreds of thousands of the whole epigenome probes. Then, BIMC (biweight midcorrelation coefficient) algorithm, SRC (Spearman's rank correlation) analysis, and shortest path tracing method were explored to identify associated genes at gene regulation level and protein-protein interaction level, respectively. Afterwards, the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis and GO (Gene Ontology) enrichment analysis were used to analyze their molecular functions and associated pathways. 105 probes were identified as tobacco-related DNA methylation signatures. They belong to 95 genes which are involved in hsa04512, hsa04151, and other important pathways. At gene regulation level, 33 genes are uncovered to be highly related to signature probes by both BIMC and SRC methods. Among them, FARSB and other eight genes were uncovered as Hub genes in the gene regulatory network. Meanwhile, the PPI network about these 33 genes showed that MAGOH, FYN, and other five genes were the most connected core genes among them. These analysis results may provide clues for a clear biological interpretation in the molecular mechanism of tumorigenesis. Moreover, the identified signature probes may serve as potential drug targets for the precision medicine of LUAD.