Literature DB >> 31438069

Racial Representation Disparity of Population-Level Genomic Sequencing Efforts.

Isaac E Kim1, Indra Neil Sarkar1.   

Abstract

To develop personalized treatments for diseases, it is essential that they reflect the population of individuals that may be affected by a given disease. Amidst claims that there may be racial disparities in research populations, there have been no direct studies to explore this disparity in disease incidence and research projects that involve genomic sequencing. The precise relationship between underrepresentation of certain races in genomic sequencing studies and health outcomes relative to these races is unknown. Here, we examine the disparities in racial representation of national datasets pertaining to clinical data, mortality rates, and a major initiative involving genomic sequence analysis (The Cancer Genome Atlas [TCGA]). The results suggest that black Americans are underrepresented for most cancers in TCGA compared to clinical and mortality datasets, whereas Asian Americans are overrepresented. These findings accentuate the importance of targeted efforts to recruit representative patient populations into studies involving genomic sequencing.

Entities:  

Keywords:  Cohort Studies; Healthcare Disparities; Precision Medicine

Mesh:

Year:  2019        PMID: 31438069     DOI: 10.3233/SHTI190369

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  5 in total

1.  Racial and ethnic disparities in communication study enrollment for young people with cancer: A descriptive analysis of the literature.

Authors:  Bryan A Sisk; Megan Keenan; Melody S Goodman; Argentina E Servin; Lauren H Yaeger; Jennifer W Mack; James M DuBois
Journal:  Patient Educ Couns       Date:  2021-12-30

2.  Enhancing African American Participation in Biospecimens: A Case in Point for Pancreatic Cancer.

Authors:  Linda Behar-Horenstein; Rueben C Warren; V Wendy Setiawan; Corey Perkins; Thomas D Schmittgen
Journal:  Cancer Health Disparities       Date:  2020-12

3.  Deep transfer learning for reducing health care disparities arising from biomedical data inequality.

Authors:  Yan Gao; Yan Cui
Journal:  Nat Commun       Date:  2020-10-12       Impact factor: 14.919

Review 4.  Contributions from the 2019 Literature on Bioinformatics and Translational Informatics.

Authors:  Malika Smaïl-Tabbone; Bastien Rance
Journal:  Yearb Med Inform       Date:  2020-08-21

5.  Precision Population Medicine in Primary Care: The Sanford Chip Experience.

Authors:  Kurt D Christensen; Megan Bell; Carrie L B Zawatsky; Lauren N Galbraith; Robert C Green; Allison M Hutchinson; Leila Jamal; Jessica L LeBlanc; Jennifer R Leonhard; Michelle Moore; Lisa Mullineaux; Natasha Petry; Dylan M Platt; Sherin Shaaban; April Schultz; Bethany D Tucker; Joel Van Heukelom; Elizabeth Wheeler; Emilie S Zoltick; Catherine Hajek
Journal:  Front Genet       Date:  2021-03-12       Impact factor: 4.599

  5 in total

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