Sung Ho Won
Seoul National University · Medicine
About the Lab
Professor Sung Ho Won's research lab specializes in statistical genetics and bioinformatics, with a focus on identifying genetic factors underlying complex diseases such as hypertension, COPD, and type 2 diabetes, particularly in understudied populations like those of African ancestry. The lab develops advanced statistical and computational methods for genome-wide association studies, pan-genome analysis, and p-value combination techniques to improve the power and robustness of genetic association studies. A key emphasis is on integrating multi-omics data—especially microbiome and extracellular vesicle profiles—to uncover host-microbe interactions in metabolic and respiratory diseases. The lab also pioneers novel family-based and multi-trait analysis methods that enhance genetic discovery while maintaining resilience to population stratification.
Research Overview
Research Output Trend
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Selected Papers
15Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals
For more than a decade, pan-genome analysis has been applied as an effective method for explaining the genetic contents variation of prokaryotic species. However, genomic characteristics and detailed structures of gene pools have not been fully clarified, because most studies have used a small number of genomes. Here, we constructed pan-genomes of seven species in order to elucidate variations in the genetic contents of >27,000 genomes belonging to <i>Streptococcus pneumoniae</i>, <i>Staphylococ
Fisher (1925) was the first to suggest a method of combining the p-values obtained from several statistics and many other methods have been proposed since then. However, there is no agreement about what is the best method. Motivated by a situation that now often arises in genetic epidemiology, we consider the problem when it is possible to define a simple alternative hypothesis of interest for which the expected effect size of each test statistic is known and we determine the most powerful test
Abstract Progressive decline in lung function is the hallmark of chronic obstructive pulmonary disease (COPD). We aimed to assess the rate of decline in forced expiratory volume in 1 second (FEV 1 ) in patients from a community cohort database in Korea. 5,865 subjects aged 40–69 years from the Ansung-Ansan cohort database I–III (2001–2006) were included in this study. We assessed the annual rate of decline in FEV 1 over time in relation to smoking status, patient sex, and presence or absence of
For genome-wide association studies in family-based designs, we propose a new, universally applicable approach. The new test statistic exploits all available information about the association, while, by virtue of its design, it maintains the same robustness against population admixture as traditional family-based approaches that are based exclusively on the within-family information. The approach is suitable for the analysis of almost any trait type, e.g. binary, continuous, time-to-onset, multi
Recent investigations have revealed that the human microbiome plays an essential role in the occurrence of type 2 diabetes (T2D). However, despite the importance of understanding the involvement of the microbiota throughout the body in T2D, most studies have focused specifically on the intestinal microbiota. Extracellular vesicles (EVs) have been recently found to provide important evidence regarding the mechanisms of T2D pathogenesis, as they act as key messengers between intestinal microorgani
Motivation: Despite the need for separate tools to analyze family-based data, there are only a handful of tools optimized for family-based big data compared to the number of tools available for analyzing population-based data. Results: ONETOOL implements the properties of well-known existing family data analysis tools and recently developed methods in a computationally efficient manner, and so is suitable for analyzing the vast amount of variant data available from sequencing family members, pro
Multiple studies have demonstrated the effects of type 2 diabetes (T2D) on various human diseases; however, most of these were observational epidemiological studies that suffered from many potential biases including reported confounding and reverse causations. In this article, we investigated whether cancer and vascular disease can be affected by T2D-related traits, including fasting plasma glucose (FPG), 2-h postprandial glucose (2h-PG), and glycated hemoglobin A1c (HbA1c) levels, by using Mend
Abstract Cigarette smoke exposure is a major risk factor in chronic obstructive pulmonary disease (COPD) and its interactions with genetic variants could affect lung function. However, few gene-smoking interactions have been reported. In this report, we evaluated the effects of gene-smoking interactions on lung function using Korea Associated Resource (KARE) data with the spirometric variables—forced expiratory volume in 1 s (FEV 1 ). We found that variations in FEV 1 were different among smokin
MOTIVATION: Individuals in each family are genetically more homogeneous than unrelated individuals, and family-based designs are often recommended for the analysis of rare variants. However, despite the importance of family-based samples analysis, few statistical methods for rare variant association analysis are available. RESULTS: In this report, we propose a FAmily-based Rare Variant Association Test (FARVAT). FARVAT is based on the quasi-likelihood of whole families, and is statistically and
BACKGROUND: The quantification of asthma medication reduction and its relation to an aggravation of asthma during pregnancy at an individual level are unclear. METHODS: We conducted a nationwide retrospective cohort study of asthmatic pregnant women in South Korea. All of the asthma medications were ranked from 1 to 4 according to the guideline-based stepwise approach. We assessed the daily sums of the ranks of the asthma medications and their association with exacerbations during three phases b
For a family-based sample, the phenotypic variance-covariance matrix can be parameterized to include the variance of a polygenic effect that has then been estimated using a variance component analysis. However, with the advent of large-scale genomic data, the genetic relationship matrix (GRM) can be estimated and can be utilized to parameterize the variance of a polygenic effect for population-based samples. Therefore narrow sense heritability, which is both population and trait specific, can be
Research Areas
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