Establishing multiple omics baselines for three Southeast Asian populations in the Singapore Integrative Omics Study

• Published in: Nature communications Vol. 8; no. 1; pp. 653 - 11
• Main Authors: Saw, Woei-Yuh, Tantoso, Erwin, Begum, Husna, Zhou, Lihan, Zou, Ruiyang, He, Cheng, Chan, Sze Ling, Tan, Linda Wei-Lin, Wong, Lai-Ping, Xu, Wenting, Moong, Don Kyin Nwe, Lim, Yenly, Li, Bowen, Pillai, Nisha Esakimuthu, Peterson, Trevor A, Bielawny, Tomasz, Meikle, Peter J, Mundra, Piyushkumar A, Lim, Wei-Yen, Luo, Ma, Chia, Kee-Seng, Ong, Rick Twee-Hee, Brunham, Liam R, Khor, Chiea-Chuen, Too, Heng Phon, Soong, Richie, Wenk, Markus R, Little, Peter, Teo, Yik-Ying
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 21.09.2017; Nature Publishing Group UK; Nature Portfolio
• Subjects: Biomarkers; Diet; Gene expression; Genetic diversity; Genetics; Genomes; Lipids; Minority & ethnic groups; Population genetics; Populations; Singapore
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-017-00413-x

The Singapore Integrative Omics Study provides valuable insights on establishing population reference measurement in 364 Chinese, Malay, and Indian individuals. These measurements include > 2.5 millions genetic variants, 21,649 transcripts expression, 282 lipid species quantification, and 284 clinical, lifestyle, and dietary variables. This concept paper introduces the depth of the data resource, and investigates the extent of ethnic variation at these omics and non-omics biomarkers. It is evident that there are specific biomarkers in each of these platforms to differentiate between the ethnicities, and intra-population analyses suggest that Chinese and Indians are the most biologically homogeneous and heterogeneous, respectively, of the three groups. Consistent patterns of correlations between lipid species also suggest the possibility of lipid tagging to simplify future lipidomics assays. The Singapore Integrative Omics Study is expected to allow the characterization of intra-omic and inter-omic correlations within and across all three ethnic groups through a systems biology approach.The Singapore Genome Variation projects characterized the genetics of Singapore's Chinese, Malay, and Indian populations. The Singapore Integrative Omics Study introduced here goes further in providing multi-omic measurements in individuals from these populations, including genetic, transcriptome, lipidome, and lifestyle data, and will facilitate the study of common diseases in Asian communities.