Lipidomic analyses in epidemiology
Author(s) -
Piyushkumar A. Mundra,
Jonathan E. Shaw,
Peter J. Meikle
Publication year - 2016
Publication title -
international journal of epidemiology
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 3.406
H-Index - 208
eISSN - 1464-3685
pISSN - 0300-5771
DOI - 10.1093/ije/dyw112
Subject(s) - lipidome , epidemiology , lipidomics , disease , framingham heart study , data science , medicine , bioinformatics , computational biology , biology , framingham risk score , computer science , pathology
Clinical lipid measurements have been the mainstay of risk assessment for chronic disease since the Framingham study commenced over 60 years ago. Thousands of subsequent epidemiological studies have provided much insight into the relationship between plasma lipid profiles, health and disease. However, the human lipidome consists of thousands of individual lipid species, and current lipidomic technology presents us with an unprecedented opportunity to measure lipid phenotypes, representing genomic, metabolic, diet and lifestyle-related exposures, in large epidemiological studies. The number of epidemiological studies using lipidomic profiling is increasing and has the potential to provide improved biological and clinical insight into human disease. In this review, we discuss current lipidomic technologies, epidemiological studies using these technologies and the statistical approaches used in the analysis of the resulting data. We highlight the potential of integrating genomic and lipidomic datasets and discuss the future opportunities and challenges in this emerging field.
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