The ChinaMAP analytics of deep whole genome sequences in 10,588 individuals.
Yanan CaoLin LiYanan HouZhimin FengXiaohui SunJieli LuYu XuPeina DuTiange WangRuying HuZhen YeLixin ShiXulei TangLi YanZhengnan GaoGang ChenYinfei ZhangLulu ChenGuang NingYufang BiWeiqing Wangnull nullPublished in: Cell research (2020)
Metabolic diseases are the most common and rapidly growing health issues worldwide. The massive population-based human genetics is crucial for the precise prevention and intervention of metabolic disorders. The China Metabolic Analytics Project (ChinaMAP) is based on cohort studies across diverse regions and ethnic groups with metabolic phenotypic data in China. Here, we describe the centralized analysis of the deep whole genome sequencing data and the genetic bases of metabolic traits in 10,588 individuals from the ChinaMAP. The frequency spectrum of variants, population structure, pathogenic variants and novel genomic characteristics were analyzed. The individual genetic evaluations of Mendelian diseases, nutrition and drug metabolism, and traits of blood glucose and BMI were integrated. Our study establishes a large-scale and deep resource for the genetics of East Asians and provides opportunities for novel genetic discoveries of metabolic characteristics and disorders.
Keyphrases
- copy number
- genome wide
- blood glucose
- big data
- randomized controlled trial
- endothelial cells
- healthcare
- public health
- machine learning
- electronic health record
- body mass index
- physical activity
- metabolic syndrome
- gene expression
- type diabetes
- deep learning
- risk assessment
- health information
- adipose tissue
- insulin resistance
- social media
- human health
- pluripotent stem cells