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Yip, V.

Publications and source records attributed to Yip, V..

2 recordsLinked to original sources

A multi-variant recall-by-genotype study of the metabolomic signature of body mass index

ObjectiveWe estimated the effect of body mass index (BMI) on circulating metabolites in young adults using a recall-by-genotype (RbG) study design. MethodsAn RbG study was implemented in the Avon Longitudinal Study of Parents and Children. Samples from 756 participants were selected for untargeted metabolomics analysis based on low/high genetic liability for higher BMI defined by a genetic score (GS). Regression analyses were performed to investigate the association between BMI GS groups and relative abundance of 973 metabolites. ResultsAfter correction for multiple testing, 29 metabolites were associated with BMI GS group. Bilirubin was amongst the most strongly associated metabolites with reduced levels measured in individuals with the highest BMI GS (beta=-0.32, 95% confidence interval (CI): -0.46, -0.18, Benjamini-Hochberg (BH) adjusted p=0.005). We observed associations between BMI GS group and levels of several potentially diet-related metabolites including hippurate which had lower mean abundance in individuals in the high BMI GS group (beta=-0.29, 95% CI: -0.44, -0.15, BH adjusted p=0.008). ConclusionsTogether with existing literature our results suggest a genetic predisposition to higher BMI captures differences in metabolism leading to adiposity gain. In the absence of prospective data, separating these effects from the downstream consequences of weight gain is challenging. Study Importance questionsO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LIMetabolomics, defined as the measurement and study of circulating small molecules that are the substrates and products of cellular metabolism, is increasingly used by epidemiologists to provide a functional read-out of bulk cellular activity and a proxy to individual current health. This approach also provides insight into biological pathways linking exposures and disease. C_LIO_LIIn observational studies, elevated body mass index (BMI) has been associated with a wide range of circulating metabolites. Researchers are now looking to genetic epidemiological methods, such as Mendelian randomization, to offer insight into potential causal relationships. C_LI What are the new findings in your manuscript?O_LIWe identified 29 metabolites whose relative abundance varies with a genetic predisposition to higher BMI. C_LIO_LIBilirubin, a key component of the heme catabolic pathway and a potent antioxidant, showed the strongest association with BMI score group. C_LI How might your results change the direction of research or the focus of clinical practice?O_LIResults of both Mendelian randomization and recall-by-genotype studies need to be combined with alternative study designs to distinguish between biomarkers that are intermediates on the pathway to BMI from those reflective of metabolic changes that result from increased adiposity. C_LIO_LISeparating causal biomarkers from non-causative biomarkers of adiposity is important since only the former are relevant to treatment and prevention, whilst both could be informative with respect to prediction and the downstream consequences of high BMI. C_LI

genetics↗

The effect of pre-analytical conditions on blood metabolomics in epidemiological studies

BackgroundSerum and plasma are commonly used biofluids for large-scale metabolomic-epidemiology studies. Their metabolomic profile is susceptible to changes due to variability in pre-analytical conditions and the impact of this is unclear.\n\nMethodsParticipant-matched EDTA-plasma and serum samples were collected from 37 non-fasting volunteers and profiled using a targeted nuclear magnetic resonance (NMR) metabolomics platform (N=151 traits). Metabolic concentrations were compared between reference (pre-storage: 4{degrees}C, 1.5h; post-storage: no sample preparation or NMR-analysis delays) and four, pre-storage, blood processing conditions, where samples were incubated at (i) 4{degrees}C, 24h; (ii) 4{degrees}C, 48h; (iii) 21{degrees}C, 24h; (iv) 21{degrees}C, 48h, before centrifugation; and two, post-storage, sample processing conditions in which samples (i) thawed overnight, then left for 24h before addition of sodium buffer followed by immediate NMR analysis; (ii) thawed overnight, addition of sodium buffer, then left for 24h before profiling. Linear regression models with random-intercepts were used to assess the impact of these six pre-analytical conditions on EDTA-plasma/serum metabolome.\n\nResultsFatty acids, beta-hydroxybutyrate, glycoprotein-acetyls and most lipid-related traits, in serum and plasma, were robust to the tested pre and post-storage conditions. Pre-storage conditions impacted concentrations of glycolysis metabolites, acetate, albumin and amino-acids by levels that could potentially bias research results (up to 1.4SD difference compared with reference). Post-storage conditions affected histidine, phenylalanine and LDL-particle-size, with differences up to 1.4SD.\n\nConclusionsMost metabolic traits are robust to the pre- and post-storage conditions tested here and that may commonly occur in large-scale cohorts. However, concentrations of glycolysis metabolites, and amino-acids may be compromised.\n\nKey messagesO_LIIn large scale epidemiological studies, blood processing delays, incubation at high temperature prior to long term storage, and NMR profiling delays after long term storage, may occur.\nC_LIO_LIConcentrations of fatty acids, beta-hydroxybutyrate, glycoprotein acetyls and most lipid-related traits are robust to variations in pre-storage temperature and duration of incubation (4{degrees}C or 21{degrees}C for up to 48h prior to centrifugation) and post-storage sample handling (24h delay in sample preparation or NMR profiling).\nC_LIO_LIGlycolytic metabolite concentrations are altered by pre-storage conditions and amino-acids, particularly histidine and phenylalanine, by both, pre and post-storage conditions.\nC_LI

epidemiology↗