Genetic Variants in Decorin and Lumican and Ovarian Cancer Risk
Author Information
Author(s): Amankwah Ernest K., Wang Qinggang, Schildkraut Joellen M., Tsai Ya-Yu, Ramus Susan J., Fridley Brooke L., Beesley Jonathan, Johnatty Sharon E., Webb Penelope M., Chenevix-Trench Georgia, Dale Laura C., Lambrechts Diether, Amant Frederic, Despierre Evelyn, Vergote Ignace, Gayther Simon A., Gentry-Maharaj Aleksandra, Menon Usha, Chang-Claude Jenny, Wang-Gohrke Shan, Anton-Culver Hoda, Ziogas Argyrios, Dörk Thilo, Dürst Matthias, Antonenkova Natalia, Bogdanova Natalia, Brown Robert, Flanagan James M., Kaye Stanley B., Paul James, Bützow Ralf, Nevanlinna Heli, Campbell Ian, Eccles Diana M., Karlan Beth Y., Gross Jenny, Walsh Christine, Pharoah Paul D. P., Song Honglin, Krüger Kjær Susanne, Høgdall Estrid, Høgdall Claus, Lundvall Lene, Nedergaard Lotte, Kiemeney Lambertus A. L. M., Massuger Leon F. A. G., van Altena Anne M., Vermeulen Sita H. H. M., Le Nhu D., Brooks-Wilson Angela, Cook Linda S., Phelan Catherine M., Cunningham Julie M., Vachon Celine M., Vierkant Robert A., Iversen Edwin S., Berchuck Andrew, Goode Ellen L., Sellers Thomas A., Kelemen Linda E.
Hypothesis
Inherited variation in DCN and LUM may influence the risk of serous epithelial ovarian cancer.
Conclusion
Variants in DCN and LUM are not directly associated with serous epithelial ovarian cancer, and further confirmation of possible effect modification by non-genetic factors is needed.
Supporting Evidence
- Decreased risks of serous epithelial ovarian cancer were associated with four genetic variants in the discovery set.
- Statistically significant increased risks were observed in a larger sample of cases in the OCAC replication set 2.
- Heterogeneity in associations across studies was statistically significant.
- Interactions were observed between genetic variants and recruitment period, age at diagnosis, and year of diagnosis.
Takeaway
The study looked at genes that might affect the risk of a type of ovarian cancer, but found that these genes don't seem to be linked to the disease.
Methodology
The study used a multi-stage replication approach across 18 independent study populations to estimate associations between genetic variants and ovarian cancer risk.
Potential Biases
Potential population structure influences on associations due to varying minor allele frequencies across studies.
Limitations
The absence of epidemiological information for most studies limited the ability to confirm associations and explore gene-environment interactions.
Participant Demographics
Caucasian subjects from multiple studies, including both cases and controls.
Statistical Information
P-Value
p<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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