Publications
Developing clinician-centred design principles for Genomic Test Reports in Pakistan
Agha et al, medRxiv, 2023
#clinical #genomics
Despite rapid technological progress being made in genomics, a growing disparity is emerging between healthcare in developed and developing countries. This genomic divide can be partly explained by the scarcity of available genomics workforce and in some parts by limited genomic literacy of healthcare professionals that reportedly deters them from proposing genomic testing in a clinical setting. This study aims to study this gap in a local context and learn how we can reduce this genomic divide by developing a user-centred design of genomic test reports in Pakistan. The user being the clinician in this study.
We selected two commonly used genomic reports which varied in language, content, and layout. Report A was a one-page genomic report from the Laboratory for Molecular Medicine at Partner’s Healthcare. Report B was a report with multiple pages of information from FoundationOneCDx. We employed a qualitative descriptive study design, including a survey of trainees, non-specialists, and specialists. The parameters recorded were: subjective comprehension, overall visual impression, level of difficulty of the language, and communication efficacy depending on the reports’ graphical representation, along with actionability and degree of reliability.
A total of 49 medical professionals across 11 institutes in Pakistan participated in the survey. Based on the answers and suggestions provided by the participants, we extracted 11 recommendations and broadly grouped them into four categories, i.e. language, content, layout and reliability.
Our findings highlights key areas that need to be taken into consideration when designing impactful genomic reports for clinicians in Pakistan. This incudes accessible and appropriate language, adequate content and a non-overwhelming and friendly layout as well as an emphasis on establishing reliability and actionability of what the clinician finds in the report. This can be instrumental in helping us improve the adoption of genomic testing in clinics around Pakistan, and potentially in other similar contexts.
Intelligent analysis of methylation data in Head and Neck Squamous Cell Carcinoma (HNSCC) interactomes
Zaheer et al, IEEE, 2021
#Data #Epigenetics
Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease which arises due to various genetic, epigenetic and environmental factors. DNA methylation is an epigenetic factor that is found to have a role in the development and progression of HNSCC through genetic and epigenetic silencing. Analysis of the methylation data can facilitate us to explore variations in several gene sites and can narrow down our search for curing HNSCC. The aim of this study was to explore and analyze the DNA Methylation data of HNSCC and make intelligent machine learning (ML) models that can predict the expression levels of a particular gene site based on various features. Difference between the gene expression levels of normal and tumor samples obtained from TCGA was calculated and then the genes were classified into hypo-methylated, hyper-methylated and non-methylated, respectively. Moreover, network analysis and functional enrichment analysis was performed to identify the protein-protein interaction (PPI) and involvement in the biological process followed by training logistic regression, support vector machine (SVM) and k-nearest neighbors (KNN) models for prediction. Logistic regression was found to have the highest accuracy of 65% among all the ML models. Furthermore, MYC, POLR2A, ALB, MTOR, H2AFX, SMARCA4, PAX6, GATA3 and MDM2 were identified as the hub genes in the HNSCC network. Whereas, hyper-methylated, hypo-methylated and non-methylated genes were found to be enriched in neuroactive ligand-receptor interaction, neurogenesis, ion transport channels, cell cycle and plasma membrane. In future, more data and features are required for validation and improving the accuracy of the ML models.