Developing a precise and equitable diagnostic kit for early detection and risk prediction of COPD | LC 25

Biography

Dr Basharat Bhat is a distinguished researcher and educator with over 10 years of experience in the fields of applied bioinformatics and computational biology. Currently serving as an Assistant Professor in the Center for Artificial Intelligence and Machine Learning at SKUAST-Kashmir, Dr Bhat has made significant contributions to the fields of drug development, and marker identification for disease detection and precision medicine. Basharat completed his postdoctoral fellowship at the University of Otago, New Zealand, where his research focused on epigenomics and epitranscriptomics, with particular attention to their implications for human health and development of diagnostic tests for COPD and cardiovascular disease. He is actively involved in several innovative projects that uses omics technologies for advancements in human health and precision medicine. With over 50 high-impact publications in international journals, Dr Bhat is also an author of several books and serves as an editorial board member and reviewer for various reputed journals.

Abstract

Chronic obstructive pulmonary disease (COPD) has been one of the significant causes of morbidity and mortality, with limited tools available for early detection before clinical symptoms manifest. This study was based on developing a diagnostic test to detect early COPD based on epigenetic biomarkers. We used samples from 500 Pacific island populations, 168 Indians, 1,135 Europeans, and 498 Americans, for generation of methylation profiles through HumanMethylationEPIC microarray, interrogating approximately 850,000 genome-wide methylation markers. Epigenome-wide association studies performed between healthy controls and COPD patients from different ethnic groups showed differential methylation patterns, especially in the AHRR gene, which was consistent across all populations. To confirm these results, we used Oxford Nanopore sequencing to study 96 selected methylation sites, which showed strong concordance with Illumina microarray results. This approach proved to be cost-effective as well as accurate, indicating its potential for scalable methylation validation. Currently, large-scale validation is being conducted on samples from different ethnic groups. Multiplexing is conducted on the Oxford Nanopore PromethION 24 platform for better robustness and reproducibility. Our conclusions derived are of two kinds and have very important results in them: 1. The constant methylation of the AHRR gene across ethnic groups for both patients with COPD and susceptible persons offers an authentic biomarker for a kit for diagnosis at early stages of COPD. 2. The cost-effectiveness and accuracy of the Oxford Nanopore sequencing makes it a promising platform for high-throughput methylation analysis, offering scalability for population-wide screening and diagnostics. This ongoing study is a big step toward an early identification of COPD, and it may contribute to early intervention and outcomes in the patients.