Genotype first: Clinical genomics research through a reverse phenotyping approach.
Am J Hum Genet
; 110(1): 3-12, 2023 01 05.
Article
em En
| MEDLINE
| ID: mdl-36608682
Although genomic research has predominantly relied on phenotypic ascertainment of individuals affected with heritable disease, the falling costs of sequencing allow consideration of genomic ascertainment and reverse phenotyping (the ascertainment of individuals with specific genomic variants and subsequent evaluation of physical characteristics). In this research modality, the scientific question is inverted: investigators gather individuals with a genomic variant and test the hypothesis that there is an associated phenotype via targeted phenotypic evaluations. Genomic ascertainment research is thus a model of predictive genomic medicine and genomic screening. Here, we provide our experience implementing this research method. We describe the infrastructure we developed to perform reverse phenotyping studies, including aggregating a super-cohort of sequenced individuals who consented to recontact for genomic ascertainment research. We assessed 13 studies completed at the National Institutes of Health (NIH) that piloted our reverse phenotyping approach. The studies can be broadly categorized as (1) facilitating novel genotype-disease associations, (2) expanding the phenotypic spectra, or (3) demonstrating ex vivo functional mechanisms of disease. We highlight three examples of reverse phenotyping studies in detail and describe how using a targeted reverse phenotyping approach (as opposed to phenotypic ascertainment or clinical informatics approaches) was crucial to the conclusions reached. Finally, we propose a framework and address challenges to building collaborative genomic ascertainment research programs at other institutions. Our goal is for more researchers to take advantage of this approach, which will expand our understanding of the predictive capability of genomic medicine and increase the opportunity to mitigate genomic disease.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Informática Médica
/
Genoma
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Am J Hum Genet
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Estados Unidos