Enhancing inclusion of diverse populations in genomics: A competence framework. Issue 2 (6th April 2020)

• Record Type: Journal Article
• Authors: Sharif, Saghira M.; Blyth, Moira; Ahmed, Mushtaq; Sheridan, Eamonn; Saltus, Roiyah; Yu, Juping; Tonkin, Emma; Kirk, Maggie
• Is Part Of: Journal of genetic counseling. Volume 29:Issue 2(2020)
• Page Start: 282
• Page End: 292
• Publication Date: 2020-04-06
• Subjects: cultural competence -- diversity -- exome sequencing -- genome sequencing -- practice models -- underrepresented populations; Genetic counseling -- Periodicals; 616.042
• DOI: 10.1002/jgc4.1263
• Languages: English
• ISSNs: 1059-7700

Abstract

Abstract: Genomic knowledge and technology have developed rapidly over the last decade and increased our capabilities to diagnose and manage rare diseases. However, current genomic datasets lack ethnic diversity as many genomic studies have focused on participants of white European ancestry. Studies, such as the Deciphering Developmental Disorders study, have been available to participants of any ancestry but have been unsuccessful in recruiting diverse populations. The inclusion of diverse populations in exome and genome sequencing is important to ensure that clinical benefits of genomics advances are equally shared among all populations and to advance scientific knowledge. Our clinical and research experience with the British Pakistani population (the largest ethnic minority in Yorkshire and Humber, accounting for 4.3% of the population) has fostered the development of an innovative cultural competence framework to enhance the inclusion of diverse populations in clinical genomic research and service provision. The application of this framework has the potential to guide healthcare professionals to develop a wide range of competences, so they are ready to embrace genomic advances in order to improve health outcomes for all patients. This practice model will inform precision medicine and improve access of diverse populations to genomic studies. Although based upon work with the Pakistani population in the UK, it is anticipated that the model would be broadly applicable to all underrepresented populations across the world.