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Title: Genetic Biomarkers for Endometriosis
Contributor(s): Lee, Sang Hong  (author); Sapkota, Yadav (author); Fung, Jenny (author); Montgomery, Grant W (author)
Publication Date: 2017
DOI: 10.1007/978-3-319-59856-7_5
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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.
Publication Type: Book Chapter
Grant Details: NHMRC/1080157
Source of Publication: Biomarkers for Endometriosis: State of the Art, p. 83-93
Publisher: Springer
Place of Publication: Cham, Switzerland
ISBN: 9783319598567
Fields of Research (FoR) 2008: 060411 Population, Ecological and Evolutionary Genetics
060412 Quantitative Genetics (incl. Disease and Trait Mapping Genetics)
060408 Genomics
Fields of Research (FoR) 2020: 310506 Gene mapping
310509 Genomics
Socio-Economic Objective (SEO) 2008: 970111 Expanding Knowledge in the Medical and Health Sciences
970106 Expanding Knowledge in the Biological Sciences
Socio-Economic Objective (SEO) 2020: 280112 Expanding knowledge in the health sciences
HERDC Category Description: B1 Chapter in a Scholarly Book
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Editor: Editor(s): Thomas D'Hooghe
Appears in Collections:Book Chapter
School of Environmental and Rural Science

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