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GWAS meta-analyses clarify the genetics of cervical phenotypes and inform risk stratification for cervical cancer

  • Mariann Koel
  • , Urmo Võsa
  • , Maarja Jõeloo
  • , Kristi Läll
  • , Natàlia P. Gualdo
  • , Hannele Laivuori
  • , Susanna Lemmelä
  • , Estonian Biobank Research Team
  • , FinnGen
  • , Mark Daly
  • , Priit Palta
  • , Reedik Mägi
  • , Triin Laisk*
  • *Tämän työn vastaava kirjoittaja

Tutkimustuotos: ArtikkeliTieteellinenvertaisarvioitu

23 Sitaatiot (Scopus)
25 Lataukset (Pure)

Abstrakti

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.

AlkuperäiskieliEnglanti
Sivut2103-2116
Sivumäärä14
JulkaisuHuman Molecular Genetics
Vuosikerta32
Numero12
DOI - pysyväislinkit
TilaJulkaistu - kesäk. 2023
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Rahoitus

This study was supported by European Union through Horizon 2020 research and innovation programme under grant agreement No 101016775 (INTERVENE), the Estonian Research Council grants (PRG687, PRG1291, PRG1911 and PSG776), and by MATER Marie Sklodowska-Curie, which received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 813707. Computational analyses of EstBB data were performed in the High-Performance Computing Centre, University of Tartu. U.V. was funded by the European Regional Development Fund and the programme Mobilitas Pluss (MOBTP108). This study was supported by European Union through Horizon 2020 research and innovation programme under grant agreement No 101016775 (INTERVENE), the Estonian Research Council grants (PRG687, PRG1291, PRG1911 and PSG776), and by MATER Marie Sklodowska-Curie, which received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 813707. Computational analyses of EstBB data were performed in the High-Performance Computing Centre, University of Tartu. U.V. was funded by the European Regional Development Fund and the programme Mobilitas Pluss (MOBTP108).

YK:n kestävän kehityksen tavoitteet

Tämä tuotos edistää seuraavia kestävän kehityksen tavoitteita:

  1. SDG 3 – Hyvä terveys ja hyvinvointi
    SDG 3 – Hyvä terveys ja hyvinvointi

Julkaisufoorumi-taso

  • Jufo-taso 2

!!ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • Genetics(clinical)

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