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Use of Artificial Intelligence leading to better understanding of the molecular pathogenesis of Asthma”.

Asthma is a multifactorial disease with bronchial hyperresponsiveness, inflammation and airway obstruction episodes as the main characteristic features of the disease. Many theories on the factors that made people at risk of developing asthma with no conclusive results. There are many issues in Asthma research that hinder the reach for proper understanding of what makes people develop asthma or what makes fully controlled asthmatic cases to convert into severe or fatal ones. On the top of that a major issue in asthma start to emerge to make the issue more complicated which is the Heterogeneity of Asthma. The view of asthma as a single disease with main characteristics of airflow obstruction, bronchial hyperresponsiveness, and underlying inflammation was found to be a oversimplified understanding as all these characteristics are not necessarily to be found in all patients. Such heterogeneity can be attributed to the fact that the airways constrict heterogeneously in response to some provoking stimuli leading to variable airflow obstruction that will give rise to heterogenous clinical presentation that indicate the heterogenous underlying pathogenesis. Transcriptomic analysis of the airways has the potential to discover gene expression profiles that are characteristic in Asthma. Transcriptomic analysis of bronchial epithelial cells showed promising power to identify different molecular mechanisms that separate asthmatic phenotypes . Such approach in a broader range of patients with asthma has not yet been performed. Sharjah Asthma Research Group lead by Prof. Qutayba Hamid, Vice Chancellor of Medicine and Health Sciences, Dean College of Medicine, University of Sharjah and directed by Dr. Rifat Hamoudi and Dr.Bassam Mahboub start using the Artificial Intelligence approach to decipher the puzzle of Asthma Heterogeneity, such novel approach which benefited from the in house scripts made by Dr. Rifat who trained the first PhD Student and medical doctor, Dr. Mahmood Yaseen Hachim to explore publically available data to collect big data from large number of Asthmatic patients to predict the trend of upregulated genes that are differentially expressed across normal versus severe asthmatic. The promising results were presented by Dr. Mahmood in the Pan Arab Human Genetics Conference (PAHGC) organized by the Centre for Arab Genomic Studies (CAGS) and won the Best Oral Presentation http://pahgc.org/ .


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