원성호 교수
Sung Ho Won
서울대학교 · 의학
연구실 소개
원성호 교수의 연구실은 유전체학과 생물정보학을 기반으로 한 대규모 유전적 분석을 통해 고혈압, 당뇨병 등 만성질환의 유전적 기반을 규명하고 있습니다. 특히 아프리카계 인구의 고혈압 유전적 소인을 탐색하고, 마이크로바이옴 및 외소체를 통한 질병 메커니즘 규명에 주력하고 있습니다. 또한 가족 기반 유전자 연관 연구와 다변량 분석 기법 개발을 통해 복잡한 유전적 특성의 분석 정확도를 높이는 데 기여하고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
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
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
Supplementary data are available at Bioinformatics online.
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
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
Asthmatic pregnant women tended to reduce their asthma medication use during pregnancy. This led to a greater number of exacerbations in a small part of the study population.
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
There have been many single nucleotide polymorphism-based tests suggested for association analysis in a case-control design. The possible evidence for association comprises three types of information: differences between cases and controls in allele frequencies, in parameters for Hardy Weinberg disequilibrium (HWD) and in parameters for linkage disequilibrium (LD). Here, first we find the pairwise covariances between statistics that measure these three types of information and show that the stat
Supplementary data are available at Bioinformatics online.
Heterogeneity of lung function levels and risk for developing chronic obstructive pulmonary disease (COPD) among people exposed to the same environmental risk factors, such as cigarette smoking, suggest an important role of genetic factors in COPD susceptibility. To investigate the possible role of different genetic factors in COPD susceptibility across ethnicities. We used a population-stratified analysis for: (i) identifying ethnic-specific genetic susceptibility loci, (ii) developing ethnic-s
Comparison with existing toolsets showed that WISARD is computationally suitable for integrated analysis of related subjects, and demonstrated that WISARD outperforms existing toolsets. WISARD has also been successfully utilized to analyze the large-scale massive sequencing dataset of chronic obstructive pulmonary disease data (COPD), and we identified multiple genes associated with COPD, which demonstrates its practical value.
We concluded that there was no fundamental difference between the rating scores of experienced psychologists and those of our AI scoring system. We expect that our AI psychologist will be able to contribute to screen the early stages of Alzheimer's disease pathology in medical checkup centers or large-scale community-based research institutes in a faster and cost-effective way.
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