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A cord blood multi-omic analysis of birthweight reveals new underlying mechanisms related to cholesterol metabolism [gene expression]

ABSTRACT: Birthweight reflects in utero exposures and later health evolution. Despite existing studies employing high-dimensional molecular measurements, the understanding of underlying mechanisms of birthweight remains limited. To investigate the systems biology of birthweight, we cross-sectionally integrated the methylome, the transcriptome, the metabolome and a set of inflammatory proteins measured in cord blood samples, collected from four birth-cohorts (n=489). We focused on two sets of 68 metabolites and 903 CpGs previously related to birthweight and investigated the correlation structures existing between these two sets and all other omic features via bipartite Pearson correlations. This dataset revealed that the set of metabolome and methylome signatures of birthweight have seven signals in common, including three metabolites [PC(34:2), plasmalogen PC(36:4)/PC(O-36:5), and a compound with m/z of 781.0545], two CpGs (on the DHCR24 and SC4MOL gene), and two proteins (periostin and CCL22). CCL22, a macrophage-derived chemokine has not been previously identified in relation to birthweight. Since the results of the omics integration indicated the central role of cholesterol metabolism, we explored the association of cholesterol levels in cord blood with birthweight in the ENVIRONAGE cohort (n=1,097), finding that higher birthweight was associated with increased high-density lipoprotein cholesterol and that high-density lipoprotein cholesterol was lower in small versus large for gestational age newborns. Our data suggests that an integration of different omic-layers in addition to single omics studies is a useful approach to generate new hypotheses regarding biological mechanisms. CCL22 and cholesterol metabolism in cord blood play a mechanistic role in birthweight.

ORGANISM(S): Homo sapiens

PROVIDER: GSE151373 | GEO | 2020/06/22

REPOSITORIES: GEO

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Project description:Morgan2016 - Dynamics of cholesterol metabolism and ageing This model is described in the article: Mathematically modelling the dynamics of cholesterol metabolism and ageing. Morgan AE, Mooney KM, Wilkinson SJ, Pickles NA, Mc Auley MT. BioSystems 2016 Jul; 145: 19-32 Abstract: Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in the UK. This condition becomes increasingly prevalent during ageing; 34.1% and 29.8% of males and females respectively, over 75 years of age have an underlying cardiovascular problem. The dysregulation of cholesterol metabolism is inextricably correlated with cardiovascular health and for this reason low density lipoprotein cholesterol (LDL-C) and high density lipoprotein cholesterol (HDL-C) are routinely used as biomarkers of CVD risk. The aim of this work was to use mathematical modelling to explore how cholesterol metabolism is affected by the ageing process. To do this we updated a previously published whole-body mathematical model of cholesterol metabolism to include an additional 96 mechanisms that are fundamental to this biological system. Additional mechanisms were added to cholesterol absorption, cholesterol synthesis, reverse cholesterol transport (RCT), bile acid synthesis, and their enterohepatic circulation. The sensitivity of the model was explored by the use of both local and global parameter scans. In addition, acute cholesterol feeding was used to explore the effectiveness of the regulatory mechanisms which are responsible for maintaining whole-body cholesterol balance. It was found that our model behaves as a hypo-responder to cholesterol feeding, while both the hepatic and intestinal pools of cholesterol increased significantly. The model was also used to explore the effects of ageing in tandem with three different cholesterol ester transfer protein (CETP) genotypes. Ageing in the presence of an atheroprotective CETP genotype, conferring low CETP activity, resulted in a 0.6% increase in LDL-C. In comparison, ageing with a genotype reflective of high CETP activity, resulted in a 1.6% increase in LDL-C. Thus, the model has illustrated the importance of CETP genotypes such as I405V, and their potential role in healthy ageing. This model is hosted on BioModels Database and identified by: MODEL1508170000. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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A cord blood multi-omic analysis of birthweight reveals new underlying mechanisms related to cholesterol metabolism [gene expression]

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