Epigenetic Alterations Induced by Smoking: Applications of Artificial Intelligence in Understanding and Preventing Addiction: A Comprehensive Review

Introduction Cigarette smoking is unquestionably associated with an increase in morbidity and mortality worldwide, exerting significant adverse effects on respiratory health. It has become apparent that the impact of tobacco persists within the genome even long after cessation of smoking. Furthermore, the offspring of smokers may also be affected by the detrimental effects of smoking.Material and method The modifications made to the body, such as DNA methylation, histone modification, and regulation by non-coding RNAs, do not change the DNA sequence but can influence gene expression. In respiratory disease, the transgenerational effects of smoking are associated with an increased risk of asthma or COPD and decreased lung function in offspring, despite them not being exposed to smoke. Prenatal nicotine exposure leads to pulmonary pathology that persists across three consecutive generations, supported by animal studies conducted by Rehan et al. Significant advances in high-throughput genomic and epigenomic technologies have enabled the discovery of molecular phenotypes. These either reflect or are influenced by them. Due to the hidden environmental effects and the rise of artificial intelligence (AI) in this domain, we now have the means to develop models that explain complex data related to disease risk.By compiling the latest research on how smoking affects gene function and structure, we emphasise how tobacco can increase vulnerability to multiple diseases. Discussion For many years, it was widely believed that diseases are solely inherited through genetics. However, recent research in epigenetics has led to a significant realisation: environmental factors play a crucial role in an individual's life. External influences leave a mark on DNA that can influence future health and offer insights into potential illnesses. In this context, it is possible that in the future, doctors might treat people not as a whole but as individual beings, with personalised medication, tests, and other approaches. Conclusion The accumulated evidence suggests that exposure to various environmental factors has a significant impact on transgenerational gene expression patterns, which may contribute to the development of multiple diseases. The application of artificial intelligence in this domain is currently a crucial tool for researching potential future health issues in individuals, and it holds a powerful prospect that could transform medicine as we know it.