论文部分内容阅读
Over the past 10 years,through the use of large-scale genomic data,genome-wide association studies have discovered more than 7000 genetic loci associated with human diseases and other complex traits.In addition to genomics,other omic technologies have also been used increasingly in epidemiologic studies,providing tremendous opportunities to study causes of diseases,identify disease biomarkers,and understand biological mechanisms for disease development and progression.Over the years,in collaboration with investigators from many other institutions,we have initiated large studies and research consortia to interrogate the whole genome,transcriptome,metabolome,and epigenome to identify biomarkers for risk of cancer and other chronic diseases.In large genome-wide association studies that currently include approximately 180,000 participants of Asian descent recruited in nearly 50 studies conducted in mainland China,Hong Kong,Taiwan,Korea,Japan,Malaysia,Singapore,Thailand,and the USA,we have discovered more than 50 novel genetic susceptibility risk loci for breast and colorectal cancer,type 2 diabetes,and obesity.Using metabolomics tools,we have identified multiple new biomarkers for risk of colorectal and pancreatic cancers and type 2 diabetes.Recently,we conducted a series of studies integrating transcriptomic and genomic data to systematically search the transcriptome to uncover genes associated with the risk of breast,prostate,colorectal,and ovarian cancers,resulting in the identification of a large number of novel associations.For example,in a large breast cancer study including approximately 119,000 cases and 101,000 controls included in the Breast Cancer Association Consortium,by integrating genomic and transcriptomic data,we found nearly 100 genes showing a significant association with breast cancer risk after adjusting for multiple comparisons.This study demonstrated the potential of integrating multi-omics data to identify biomarkers for cancer risk.Proper use of multi-omic data will undoubtedly improve the understanding of the etiology of human diseases and accelerate the pace of discovery of the causes of diseases and identification of disease biomarkers,leading to the design of cost-efficient prevention strategies.