Nonsyndromic cleft lip with or without cleft palate and cancer: Evaluation of a possible common genetic background through the analysis of GWAS data

Eva Dunkhase, Kerstin U. Ludwig, Michael Knapp, Christine F. Skibola, Jane C. Figueiredo, Fay Julie Hosking, Eva Ellinghaus, Maria Teresa Landi, Hongxia Ma, Hidewaki Nakagawa, Jong Won Kim, Jiali Han, Ping Yang, Anne C. Böhmer, Manuel Mattheisen, Markus M. Nöthen, Elisabeth Mangold

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Previous research suggests a genetic overlap between nonsyndromic cleft lip with or without cleft palate (NSCL/P) and cancer. The aim of the present study was to identify common genetic risk loci for NSCL/P and cancer entities that have been reported to co-occur with orofacial clefting. This was achieved through the investigation of large genome-wide association study datasets. Investigations of 12 NSCL/P single nucleotide polymorphisms (SNPs) in 32 cancer datasets, and 204 cancer SNPs in two NSCL/P datasets, were performed. The SNPs rs13041247 (20q12) and rs6457327 (6p21.33) showed suggestive evidence for an association with both NSCL/P and a specific cancer entity. These loci harbor genes of biological relevance to oncogenesis (MAFB and OCT4, respectively). This study is the first to characterize possible pleiotropic risk loci for NSCL/P and cancer in a systematic manner. The data represent a starting point for future research by identifying a genetic link between NSCL/P and cancer.

Original languageEnglish (US)
Pages (from-to)22-29
Number of pages8
JournalGenomics Data
Volume10
DOIs
StatePublished - Dec 1 2016

Keywords

  • Cancer
  • Cleft lip
  • Cleft palate
  • Genome-wide association study
  • Single nucleotide polymorphism

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Molecular Medicine
  • Genetics

Fingerprint

Dive into the research topics of 'Nonsyndromic cleft lip with or without cleft palate and cancer: Evaluation of a possible common genetic background through the analysis of GWAS data'. Together they form a unique fingerprint.

Cite this