Integration of Metabolomic and Other Omics Data in Population-Based Study Designs: An Epidemiological Perspective
Year: 2019
Type: article
Abstract: It is not controversial that study design considerations and challenges must be addressed when investigating the linkage between single omic measurements and human phenotypes. It follows that such considerations are just as critical, if not more so, in the context of multi-omic studies. In this review, we discuss (1) epidemiologic principles of study design, including selection of biospecimen source(s) and the implications of the timing of sample collection, in the context of a multi-omic investigation, and (2) the strengths and limitations of various techniques of data integration across multi-omic data types that may arise in population-based studies utilizing metabolomic data.
Source: Metabolites
Institutions: Brigham and Women's Hospital, Harvard University, Weill Cornell Medicine, The Ohio State University, Universidade de São Paulo, Wake Forest University Health Sciences, Wake Forest University, Karolinska Institutet, National Institutes of Health, Division of Cancer Epidemiology and Genetics
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $1,418
Awards: G1460097252, G3742232733, From metabolomics to treatment: novel approaches to understand heart failure, G4086346382, G4511766892, Novel Biomarkers and Prediction Models for Rheumatoid Arthritis, Genomic and Proteomic Architecture of Atherosclerosis, Multi-Omic Endotyping of Asthma, G784204608, G82491071, G984938634
OpenAlex ID: W2950697982