세미나/행사

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제목 2022년 11월 3일 생물정보학 세미나
작성자 관리자 작성일 2022-10-26

서울대학교 생물정보학 협동과정 주최로 세미나를 아래와 같이 열고자 하오니 많은 참여 바랍니다.

세미나는 Zoom을 통한 온라인 강의로 예정되어 있으며 강의에 참여하고자 하시는 분께서는 아래의 링크로 참여 부탁드리겠습니다.



*줌으로 참석하기 위해서는 "참석자로 회의 참가" --> 이름, 성, 이메일 주소, 이메일 주소 확인을 입력하시고 등록하시면 회의 참석이 가능합니다.



일시: 2022년 11월 3일 목요일 오전 11시

연사: 원홍희 교수님 (성균관대학교)

Zoom link:　https://snu-ac-kr.zoom.us/j/95800656704?pwd=d1FNREZscWdNSEJtL1JqS0YwTkpRdz09



Mendelian randomization and GWAS in medicine

Hong-Hee Won, Ph.D.
SAIHST, Sungkyunkwan University
Samsung Medical Center

Observational studies are useful to identify associations between risk factors and diseases, but often　show inconsistent results due to heterogeneity among studies such as metrics, race, and cohort　characteristics. In addition, many associated factors have a bidirectional interaction with the disease.
For example, although the risk of disease is increased by an associated factor, it can also be　increased due to the occurrence of the disease. In the case of such a complex epidemiologic　relationship, it is difficult to confirm the exact causality or direction of interaction only by observational　studies.
The concept of causality is important in medicine because it enables proper and effective　treatments. Randomized controlled trials (RCTs) are considered a gold standard to confirm a causal　relationship between risk factors and disease. For example, in interventional studies such as drug　studies, causality can be confirmed through RCT. In many cases such as smoking and lung cancer,
however, RCTs are not feasible because it is unethical to induce risk factors through intervention.
Mendelian randomization (MR) is a method of using genetic variants as instrumental
variables to examine the causal effect of a modifiable exposure on disease based on the fact that　genetic variants which increase or decrease the risk of a factor are randomly assigned during meiosis.
Comparing the difference in the risk of disease for two groups that have high or low genetic risk for　the factor can evaluate whether the factor induces the disease without intervention. In this　presentation, I will talk about genome-wide association studies that identify genetic variants　associated with traits such as risk factors and diseases. Also, I will explain MR analyses,　assumptions, interpretation as well as several examples from the literature.