The ultimate goal of this study is to identify genetic factors controlling the accumulation of various lipids in human liver, using a system approach with integrated genomic and lipidomic (i.e. lipids family) data. Hepatic fat accumulation is a hallmark of nonalcoholic fatty liver disease (NAFLD) and various metabolic complications. Its mechanism, especially the genetic basis underlying the fat accumulation, is incompletely elucidated. This is largely attributed to insufficient understanding of the complexity of lipid metabolism and homeostasis. Since a wide range of lipids are involved in fat accumulation and the associated metabolic consequences, it is particularly necessary to investigate the lipid process at the system level. We hypothesize that the contents of various lipids and their metabolites in the livers of the general population are quantitative traits significantly controlled by genetic factors;and the discovery of these genetic loci could provide better insight on the hepatic fat accumulation and associated diseases. To accomplish this, we propose to perform a comprehensive genetic mapping for lipidome using a large collection of liver tissues (n=213) in which the total fat content is differentiated, and for which genome-wide genotypic and transcriptomic data have been previously collected. We will: 1) profile >400 different lipids in each of the 213 livers;2) perform genome-wide association study to identified polymorphisms and genes associated with variations in hepatic lipidome;and 3) validate the discovered associations in an independent liver sample set (n=70). We anticipate that this study will identify critical genes, alleles and pathways conferring susceptibility to imbalanced lipid accumulation in human liver, and will thus provide potential markers and targets for early diagnosis and intervention of NAFLD and related diseases.
This study will discover genes and DNA variants responsible for the accumulation of fat and fat fractions in human liver, a hallmark of nonalcoholic fatty liver disease and many other metabolic diseases, e.g. obesity and diabetes. This study will produce important information for attaining a better understanding of the development of these diseases. The study will also potentially identify molecular targets that could be used to develop better treatment.
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