GWAS meta-analyses clarify the genetics of cervical phenotypes and inform risk stratification for cervical cancer.
Hum Mol Genet
; 32(12): 2103-2116, 2023 06 05.
Article
en En
| MEDLINE
| ID: mdl-36929174
ABSTRACT
Genome-wide association studies (GWAS) have successfully identified associations for cervical cancer, but the underlying mechanisms of cervical biology and pathology remain uncharacterised. Our GWAS meta-analyses fill this gap, as we characterise the genetic architecture of cervical phenotypes, including cervical ectropion, cervicitis, cervical dysplasia, as well as up to 9229 cases and 490 304 controls for cervical cancer from diverse ancestries. Leveraging the latest computational methods and gene expression data, we refine the association signals for cervical cancer and propose potential causal variants and genes at each locus. We prioritise PAX8/PAX8-AS1, LINC00339, CDC42, CLPTM1L, HLA-DRB1 and GSDMB as the most likely candidate genes for cervical cancer signals, providing insights into cervical cancer pathogenesis and supporting the involvement of reproductive tract development, immune response and cellular proliferation/apoptosis. We construct a genetic risk score (GRS) that is associated with cervical cancer [hazard ratios (HR) = 3.1 (1.7-5.6) for the top 15% vs lowest 15% of individuals], and with other HPV- and immune-system-related diagnoses in a phenome-wide association study analysis. Our results propose valuable leads for further functional studies and present a GRS for cervical cancer that allows additional risk stratification and could potentially be used to personalise the conventional screening strategies for groups more susceptible to cervical cancer.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Neoplasias del Cuello Uterino
/
Estudio de Asociación del Genoma Completo
Tipo de estudio:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Female
/
Humans
Idioma:
En
Revista:
Hum Mol Genet
Asunto de la revista:
BIOLOGIA MOLECULAR
/
GENETICA MEDICA
Año:
2023
Tipo del documento:
Article
País de afiliación:
Estonia