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Title Incorporating family disease history in risk prediction models with large-scale genetic data substantially dissolves unexplained variability

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Abstract Motivation: Despite the many successes of genome-wide association studies (GWAS), the known susceptibility variants identified by GWAS have modest effect sizes, leading to notable scepticism about the effectiveness of building a risk prediction model from large-scale genetic data. However, in contrast to genetic variants, the family history of diseases has been largely accepted as an important risk factor in clinical diagnosis and risk prediction. Nevertheless, the complicated structures of the family history of diseases have limited their application in clinical practice.

Results: Here, we developed a new method that enables incorporation of the general family history of diseases with a liability threshold model, and propose a new analysis strategy for risk prediction with penalized regression analysis that incorporates both large numbers of genetic variants and clinical risk factors. Application of our model to type 2 diabetes (T2D) patients in the Korean population (1846 cases and 1846 controls) demonstrated that single nucleotide polymorphisms accounted for 32.5% of the variability of risk in T2D cases, and incorporation of family history led to an additional 6.3% improvement in prediction. Our results illustrate that the family medical history is valuable information on the variability of complex diseases and improves prediction performance.

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Career

2016/03- Associate Professor, Graduate School of Public Health, Seoul National University

2014-2016/02 Assistant Professor, Public Health Science, Seoul National University

2010-2014/03 Assistant Professor, Applied Statistics, Chung-Ang University

2009 Full-time Instructor, Chung-Ang University

2008-2009 Postdoctoral Fellow, Biostatistics, Harvard School of Public Health


Education

2004-2008 Ph.D, Biostatistics, Case Western Reserve University

2000-2004 MS, Statistics, Seoul National University

1996-2000 BS, Biology Education, Seoul National University

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Selected Publications

Won S, Christoph Lange. A general framework for robust and efficient association analysis in family-based designs: quantitative and dichotomous phenotypes. Stat in Med in press

Lasky-Su J et al. On genome-wide association studies for family-based designs: an integrative analysis approach combining ascertained family samples with unselected controls. Am J Hum Genet. 2010; 86(4):573-80

Cho MH, et al. Variants in FAM13A are associated with chronic obstructive pulmonary disease. Nat Genet 2010;42;200-202

Won S, Wilk JB, Mathias R, O¡¯Donnell C, Silverman EK, Barnes K, O¡¯Connor G, Weiss ST, Lange C. On the analysis of genome-wide association studies in family-based designs: A universal, robust analysis approach and an application to four genome-wide association studies. Plos Genet 2009; e1000741.

Won S, Morris N, Qing Lu, Elston RC. Choosing an optimal method to combine p-values. Stat in Med 2009;28(11);1537-1553

Won S, Elston RC. The power of independent types of genetic information to detect association in a case-control study design. Genet Epidemiol 2008;32(8);

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