Effect of betel chewing, tobacco smoking and alcohol consumption on oral submucous fibrosis: a case-control study in Sri Lanka.
ABSTRACT Oral submucous fibrosis (OSMF) is a chronic, insidious, disabling potentially malignant condition of the oral mucosa seen predominantly in south and Southeast Asia. No reports are hitherto available on the aetiological factors of OSMF based on Sri Lankan patients.
A total of 74 patients with OSMF and 74 controls who consecutively attended the Oral Medicine clinic at the Dental Hospital (Teaching) Faculty of Dental Sciences, University of Peradeniya, Sri Lanka were included in the study. Binary logistic regression analyses were performed to model the influence of betel chewing, smoking and alcohol use and to determine the effects of different combinations of chewing habits on OSMF.
Betel chewing was the only significantly associated factor in the aetiology of OSMF (OR = 171.83, 95% CI: 36.35-812.25). There were no interaction effects of chewing, smoking and alcohol consumption in the causation of OSMF.
The present study has shown a strong association of betel quid chewing (including tobacco as an ingredient) with the causation of OSMF.
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ABSTRACT: Regarding oral squamous cell carcinoma (OSCC) development, chewing areca is known to be a strong risk factor in many Asian cultures. Therefore, we established an OSCC induced mouse model by 4-nitroquinoline-1-oxide (4-NQO), or arecoline, or both treatments, respectively. These are the main two components of the areca nut that could increase the occurrence of OSCC. We examined the effects with the noncommercial MCGI (mouse CpG islands) microarray for genome-wide screening the DNA methylation aberrant in induced OSCC mice. The microarray results showed 34 hypermethylated genes in 4-NQO plus arecoline induced OSCC mice tongue tissues. The examinations also used methylation-specific polymerase chain reaction (MS-PCR) and bisulfite sequencing to realize the methylation pattern in collected mouse tongue tissues and human OSCC cell lines of different grades, respectively. These results showed that retinoic acid receptor β (RARB) was indicated in hypermethylation at the promoter region and the loss of expression during cancer development. According to the results of real-time PCR, it was shown that de novo DNA methyltransferases were involved in gene epigenetic alternations of OSCC. Collectively, our results showed that RARB hypermethylation was involved in the areca-associated oral carcinogenesis.BioMed Research International 01/2014; 2014:378358. · 2.71 Impact Factor
- Progress in Brain Research - PROG BRAIN RES. 01/1995; 106:323-331.
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ABSTRACT: BACKGROUND: This case-control study investigates the role of xenobiotic-metabolizing genes, including glutathione S-transferases (GSTs) and cytochrome P450 1A1 (CYP1A1) and 2E1 (CYP2E1), in the susceptibility to oral potentially malignant disorders (OPMDs).METHODS: The genotypes of GSTM1, GSTT1, GSTP1, CYP1A1*2C, and CYP2E1 PstI/RsaI polymorphisms were determined for 217 OPMD cases and 492 age- and sex-matched controls from a Taiwanese penitentiary.RESULTS: Compared to the GSTM1-present genotype, the GSTM1-null genotype was significantly associated with increased risk of leukoplakia (odds ratio [OR]=1.46, 95% confidence interval [CI]=1.01-2.10). Similarly, compared to the CYP1A1*2C A/G+G/G genotype, the CYP1A1*2C A/A genotype was significantly associated with increased risk of leukoplakia (OR=1.64, 95% CI=1.12-2.40), particularly for smokers consuming > 13 pack-years of cigarettes (OR=2.40, 95% CI=1.40-4.11) (Interaction P=0.039). In addition, participants with 4-5 risk genotypes (OR > 1) experienced higher risks for leukoplakia than those with 0-1 risk genotypes (OR=3.19, 95% CI=1.65-6.15) (Trend test P=0.001).CONCLUSIONS: Our findings suggest that the CYP1A1*2C A/A genotype may increase the risk of leukoplakia, especially for heavy smokers. Xenobiotic-metabolizing genes may simultaneously modulate this disease risk. These observations require further confirmation with larger samples.Disease markers 02/2013; · 2.17 Impact Factor