Genetic biomarkers for endometriosis

Hong Lee, Yadav Sapkota, Jenny Fung, Grant W. Montgomery

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Citations (Scopus)

Abstract

GWAS studies identified seven genomic regions with robust evidence for genome-wide significant association with endometriosis risk. One important question that arises is whether these genetic markers can be used to predict risk of developing endometriosis for individual women. As with most complex diseases, the effect sizes for genetic markers linked to endometriosis risk are small with odds ratios less than 1.3. If we combine information from all seven markers, we explain only 1.85% of the total phenotypic variance on the liability scale (assuming a population prevalence of endometriosis of 8%) with no predictive power for individual risk. To explore the ability of all common genetic markers to predict endometriosis risk in individuals, we conducted simulations to quantify how useful endometriosis risk prediction is given current parameters. Applying our estimate of heritability (h2 = 0.26) from all common SNPs and assuming data were available from ~30,000 endometriosis cases, the proportion of variance explained by the risk predictor is still only ~0.08. To improve this prediction would require a far greater sample size. Current data may be useful for population-based stratification into risk categories. This can have applications in some cases such as improved efficiency of screening in breast cancer. In the future, risk prediction for endometriosis might be improved through combining genetic risk scores with clinical data, estimates of environmental effects such as DNA methylation signals, and/or better understanding of disease subtypes.

LanguageEnglish
Title of host publicationBiomarkers for Endometriosis
Subtitle of host publicationState of the Art
PublisherSpringer International Publishing
Pages83-93
Number of pages11
ISBN (Electronic)9783319598567
ISBN (Print)9783319598543
DOIs
Publication statusPublished - 22 Sep 2017
Externally publishedYes

Keywords

  • Endometriosis
  • Genetic biomarkers
  • Prediction
  • Risk
  • Simulation

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)
  • Health Professions(all)

Cite this

Lee, H., Sapkota, Y., Fung, J., & Montgomery, G. W. (2017). Genetic biomarkers for endometriosis. In Biomarkers for Endometriosis: State of the Art (pp. 83-93). Springer International Publishing. https://doi.org/10.1007/978-3-319-59856-7_5
Lee, Hong ; Sapkota, Yadav ; Fung, Jenny ; Montgomery, Grant W. / Genetic biomarkers for endometriosis. Biomarkers for Endometriosis: State of the Art. Springer International Publishing, 2017. pp. 83-93
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Lee, H, Sapkota, Y, Fung, J & Montgomery, GW 2017, Genetic biomarkers for endometriosis. in Biomarkers for Endometriosis: State of the Art. Springer International Publishing, pp. 83-93. https://doi.org/10.1007/978-3-319-59856-7_5

Genetic biomarkers for endometriosis. / Lee, Hong; Sapkota, Yadav; Fung, Jenny; Montgomery, Grant W.

Biomarkers for Endometriosis: State of the Art. Springer International Publishing, 2017. p. 83-93.

Research output: Chapter in Book/Report/Conference proceedingChapter

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Lee H, Sapkota Y, Fung J, Montgomery GW. Genetic biomarkers for endometriosis. In Biomarkers for Endometriosis: State of the Art. Springer International Publishing. 2017. p. 83-93 https://doi.org/10.1007/978-3-319-59856-7_5