Your browser doesn't support javascript.
loading
Integrative multi-omics database (iMOMdb) of Asian pregnant women.
Pan, Hong; Tan, Pei Fang; Lim, Ives Y; Huan, Jason; Teh, Ai Ling; Chen, Li; Gong, Min; Tin, Felicia; Mir, Sartaj Ahmad; Narasimhan, Kothandaraman; Chan, Jerry K Y; Tan, Kok Hian; Kobor, Michael S; Meikle, Peter J; Wenk, Markus R; Chong, Yap Seng; Eriksson, Johan G; Gluckman, Peter D; Karnani, Neerja.
Afiliación
  • Pan H; Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore.
  • Tan PF; Bioinformatics Institute, Agency for Science, Technology and Research, Singapore.
  • Lim IY; Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore.
  • Huan J; Bioinformatics Institute, Agency for Science, Technology and Research, Singapore.
  • Teh AL; Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore.
  • Chen L; Bioinformatics Institute, Agency for Science, Technology and Research, Singapore.
  • Gong M; Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore.
  • Tin F; Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore.
  • Mir SA; Bioinformatics Institute, Agency for Science, Technology and Research, Singapore.
  • Narasimhan K; Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore.
  • Chan JKY; Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore.
  • Tan KH; Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore.
  • Kobor MS; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Meikle PJ; Singapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore.
  • Wenk MR; Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore.
  • Chong YS; Department of Reproductive Medicine, KK Women's and Children's Hospital, Singapore.
  • Eriksson JG; Academic Clinical Program in Obstetrics and Gynaecology, Duke-NUS Medical School, Singapore.
  • Gluckman PD; Academic Clinical Program in Obstetrics and Gynaecology, Duke-NUS Medical School, Singapore.
  • Karnani N; Department of Maternal Fetal Medicine, KK Women's and Children's Hospital, Singapore.
Hum Mol Genet ; 31(18): 3051-3067, 2022 09 10.
Article en En | MEDLINE | ID: mdl-35445712
ABSTRACT
Asians are underrepresented across many omics databases, thereby limiting the potential of precision medicine in nearly 60% of the global population. As such, there is a pressing need for multi-omics derived quantitative trait loci (QTLs) to fill the knowledge gap of complex traits in populations of Asian ancestry. Here, we provide the first blood-based multi-omics analysis of Asian pregnant women, constituting high-resolution genotyping (N = 1079), DNA methylation (N = 915) and transcriptome profiling (N = 238). Integrative omics analysis identified 219 154 CpGs associated with cis-DNA methylation QTLs (meQTLs) and 3703 RNAs associated with cis-RNA expression QTLs (eQTLs). Ethnicity was the largest contributor of inter-individual variation across all omics datasets, with 2561 genes identified as hotspots of this variation; 395 of these hotspot genes also contained both ethnicity-specific eQTLs and meQTLs. Gene set enrichment analysis of these ethnicity QTL hotspots showed pathways involved in lipid metabolism, adaptive immune system and carbohydrate metabolism. Pathway validation by profiling the lipidome (~480 lipids) of antenatal plasma (N = 752) and placenta (N = 1042) in the same cohort showed significant lipid differences among Chinese, Malay and Indian women, validating ethnicity-QTL gene effects across different tissue types. To develop deeper insights into the complex traits and benefit future precision medicine research in Asian pregnant women, we developed iMOMdb, an open-access database.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Sitios de Carácter Cuantitativo / Mujeres Embarazadas Tipo de estudio: Prognostic_studies Límite: Female / Humans / Pregnancy Idioma: En Revista: Hum Mol Genet Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Singapur

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Sitios de Carácter Cuantitativo / Mujeres Embarazadas Tipo de estudio: Prognostic_studies Límite: Female / Humans / Pregnancy Idioma: En Revista: Hum Mol Genet Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Singapur