CAS Key Lab of Computational Biology Seminar
Lining Guo, Ph.D. Management, Metabolon
2018-04-23
Speaker: Lining Guo, Ph.D.
Vice President of Project
Management, Metabolon
Vice President of Project
Management, Metabolon
Host: Prof. Zefeng Wang
CAS Key Lab of Computational Biology,
CAS-MPG Partner Institute for Computational Biology,
Shanghai Institute of Nutrition and Health, CAS
CAS Key Lab of Computational Biology,
CAS-MPG Partner Institute for Computational Biology,
Shanghai Institute of Nutrition and Health, CAS
Title: Metabolomics in Precision Medicine: From big data to individual genetic risk assessment and disease management
Time: Apr. 23, 11:00 am（Monday), 2018
Venue: Room 315, SIBS Main Building
320 Yueyang Road, Shanghai
320 Yueyang Road, Shanghai
Abstract:
The human metabolome represents a high resolution intermediate phenotype that bridges the impact of genetics, non-genetic factors, and health/disease end points. Genetic factors modifying the blood metabolome have been investigated through GWAS of common, low frequency, and rare genetic variants. Population analysis has further provided insights on the natural variation and regulation of human plasma metabolome. Based on the knowledge we have learnt from large cohort studies, we combined metabolomics and whole genome/exome sequencing in individual clinical cases and provided novel insights to:
The human metabolome represents a high resolution intermediate phenotype that bridges the impact of genetics, non-genetic factors, and health/disease end points. Genetic factors modifying the blood metabolome have been investigated through GWAS of common, low frequency, and rare genetic variants. Population analysis has further provided insights on the natural variation and regulation of human plasma metabolome. Based on the knowledge we have learnt from large cohort studies, we combined metabolomics and whole genome/exome sequencing in individual clinical cases and provided novel insights to:
1). Clarifying sequence variants of unknown significance (VUS).
2). Identifying metabolic defects in undiagnosed disease cases leading to clinical intervention, and
3). Identifying drug toxicity and responsiveness. Metabolomics in Precision Medicine: From big data to individual genetic risk assessment and disease management.