Format

Send to

Choose Destination
Hum Genet. 2019 Jul;138(7):691-701. doi: 10.1007/s00439-019-02033-5. Epub 2019 Jun 3.

Mind the gap: resources required to receive, process and interpret research-returned whole genome data.

Author information

1
Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA. dana.crawford@case.edu.
2
Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA. dana.crawford@case.edu.
3
Cleveland Institute for Computational Biology, Case Western Reserve University, 2103 Cornell Road. Wolstein Research Building, Suite 2-527, Cleveland, OH, 44106, USA. dana.crawford@case.edu.
4
Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA.
5
Cleveland Institute for Computational Biology, Case Western Reserve University, 2103 Cornell Road. Wolstein Research Building, Suite 2-527, Cleveland, OH, 44106, USA.

Abstract

Most genotype-phenotype studies have historically lacked population diversity, impacting the generalizability of findings and thereby limiting the ability to equitably implement precision medicine. This well-documented problem has generated much interest in the ascertainment of new cohorts with an emphasis on multiple dimensions of diversity, including race/ethnicity, gender, age, socioeconomic status, disability, and geography. The most well known of these new cohort efforts is arguably All of Us, formerly known as the Precision Medicine Cohort Initiative Program. All of Us intends to ascertain at least one million participants in the United States representative of the multiple dimensions of diversity. As an incentive to participate, All of Us is offering the return of research results, including whole genome sequencing data, as well as the opportunity to contribute to the scientific process as non-scientists. The scale and scope of the proposed return of research results are unprecedented. Here, we briefly review possible return of genetic data models, including the likely data file formats and modes of data transfer or access. We also review the resources required to access and interpret the genetic or genomic data once received by the average participant, highlighting the nuanced anticipated barriers that will challenge both the digitally, computationally literate and illiterate participant alike. This inventory of resources required to receive, process, and interpret return of research results exposes the potential for access disparities and warns the scientific community to mind the gap so that all participants have equal access and understanding of the benefits of human genetic research.

PMID:
31161416
DOI:
10.1007/s00439-019-02033-5
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Springer
Loading ...
Support Center