Biology subjects

Sebert, S.

Publications and source records attributed to Sebert, S..

6 recordsLinked to original sources

bioRxiv2018

DNA methylation links prenatal smoking exposure to later life health outcomes in offspring.

Maternal smoking during pregnancy is associated with adverse offspring health outcomes across their life course. We hypothesize that DNA methylation is a potential mediator of this relationship. To test this, we examined the association of prenatal maternal smoking with DNA methylation in 2,821 individuals (age 16 to 48 years) from five prospective birth cohort studies and perform Mendelian randomization and mediation analyses to assess, whether methylation markers have causal effects on disease outcomes in the offspring. We identify 69 differentially methylated CpGs in 36 genomic regions (P < 1x10-7), and show that DNA methylation may represent a biological mechanism through which maternal smoking is associated with increased risk of psychiatric morbidity in the exposed offspring.

epidemiology↗

bioRxiv2018

Machine Learning in Multi-Omics Data to Assess Longitudinal Predictors of Glycaemic Trait Levels

Type 2 diabetes (T2D) is a global health burden that will benefit from personalised risk prediction and targeted prevention programmes. Omics data have enabled more detailed risk prediction; however, most studies have focussed on directly on the ability of DNA variants predicting T2D onset with less attention given to epigenetic regulation and glycaemic trait variability. By applying machine learning to the longitudinal Northern Finland Birth Cohort 1966 (NFBC 1966) at 31 (T1) and 46 (T2) years old, we predicted fasting glucose (FG) and insulin (FI), glycated haemoglobin (HbA1c) and 2-hour glucose and insulin from oral glucose tolerance test (2hGlu, 2hIns) at T2 in 513 individuals from 1,001 variables at T1 and T2, including anthropometric, metabolic, metabolomic and epigenetic variables. We further tested whether the information obtained by the machine learning models in NFBC could be used to predict glycaemic traits in the independent French study with 48 matching predictors (DESIR, N=769, age range 30-65 years at recruitment, interval between data collections: 9 years). In this study, FG and FI were best predicted, with average R2 values of 0.38 and 0.53. Sex, branched-chain and aromatic amino acids, HDL-cholesterol, glycerol, ketone bodies, blood pressure at T2 and measurements of adiposity at T1, as well as multiple methylation marks at both time points were amongst the top predictors. In the validation analysis, we reached R2 values of 0.41/0.55 for FG/FI when trained and tested in NFBC1966 and 0.17/0.30 when trained in NFBC1966 and tested in DESIR. We identified clinically relevant sets of predictors from a large multi-omics dataset and highlighted the potential of methylation markers and longitudinal changes in prediction.

genomics↗

bioRxiv2018

Metabolomic consequences of genetic inhibition of PCSK9 compared with statin treatment

BackgroundBoth statins and PCSK9 inhibitors lower blood low-density lipoprotein cholesterol (LDL-C) levels to reduce risk of cardiovascular events. To assess potential differences between metabolic effects of these two lipid-lowering therapies, we performed detailed lipid and metabolite profiling of a large randomized statin trial, and compared the results with the effects of genetic inhibition of PCSK9, acting as a naturally occurring trial.\n\nMethods228 circulating metabolic measures were quantified by nuclear magnetic resonance spectroscopy, including lipoprotein subclass concentrations and their lipid composition, fatty acids, and amino acids, for 5,359 individuals (2,659 on treatment) in the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial at 6-months post-randomization. The corresponding metabolic measures were analyzed in eight population cohorts (N=72,185) using PCSK9 rs11591147 as an unconfounded proxy to mimic the therapeutic effects of PCSK9 inhibitors.\n\nResultsScaled to an equivalent lowering of LDL-C, the effects of genetic inhibition of PCSK9 on 228 metabolic markers were generally consistent with those of statin therapy (R2=0.88). Alterations in lipoprotein lipid composition and fatty acid balance were similar. However, discrepancies were observed for very-low-density lipoprotein (VLDL) lipid measures. For instance, genetic inhibition of PCSK9 showed weaker effects on lowering of VLDL-cholesterol compared with statin therapy (54% vs. 77% reduction, relative to the lowering effect on LDL-C; P=2 x 10-7 for heterogeneity). Genetic inhibition of PCSK9 showed no robust effects on amino acids, ketones, and a marker of inflammation (GlycA); in contrast, statin treatment lowered GlycA levels.\n\nConclusionsGenetic inhibition of PCSK9 results in similar metabolic effects as statin therapy across a detailed lipid and metabolite profile. However, for the same lowering of LDL-C, PCSK9 inhibitors are predicted to be less efficacious than statins at lowering VLDL lipids, which could potentially translate into subtle differences in cardiovascular risk reduction.

epidemiology↗

bioRxiv2017

Variants at the ADAMTS13, BGALT5, SSBP2 and TKT Loci are associated with Post-term birth.

Gestation is a crucial timepoint in human development. Deviation from a term gestational age correlates with both acute and long-term adverse health effects for the child. Both being born pre and post-term, i.e. having short and long gestational ages, are heritable and influenced by the pre- and perinatal environment. Despite the obvious heritable component, specific genetic influences underlying differences in gestational age are poorly understood. Here we identify one globally significant intronic genetic variant within the ADAMTS13 gene that is associated with prolonged gestation in 9,141 white European individuals from the 1966 and 1986 Northern Finland birth cohorts. Additional variants that reached suggestive levels of significance were identified within introns at the TKT, and ARGHAP42 genes, and in the upstream (5) intergenic regions of the B3GALT5 and SSBP2 genes. The variants near the ADAMTS13, B3GALT5, SSBP2 and TKT loci are linked to alterations in gene expression levels (cis-eQTLs). Luciferase assays confirmed the allele specific enhancer activity for the BGALT5 and TKT loci. Our findings provide the first evidence of a specific genetic influence associated with prolonged gestation.

genetics↗

bioRxiv2017

Genetic architecture of early childhood growth phenotypes gives insights into their link with later obesity

Early childhood growth patterns are associated with adult metabolic health, but the underlying mechanisms are unclear. We performed genome-wide meta-analyses and follow-up in up to 22,769 European children for six early growth phenotypes derived from longitudinal data: peak height and weight velocities, age and body mass index (BMI) at adiposity peak (AP ~9 months) and rebound (AR ~5-6 years). We identified four associated loci (P< 5x10-8): LEPR/LEPROT with BMI at AP, FTO and TFAP2B with Age at AR and GNPDA2 with BMI at AR. The observed AR-associated SNPs at FTO, TFAP2B and GNPDA2 represent known adult BMI-associated variants. The common BMI at AP associated variant at LEPR/LEPROT was not associated with adult BMI but was associated with LEPROT gene expression levels, especially in subcutaneous fat (P<2x10-51). We identify strong positive genetic correlations between early growth and later adiposity traits, and analysis of the full discovery stage results for Age at AR revealed enrichment for insulin-like growth factor 1 (IGF-1) signaling and apolipoprotein pathways. This genome-wide association study suggests mechanistic links between early childhood growth and adiposity in later childhood and adulthood, highlighting these early growth phenotypes as potential targets for the prevention of obesity.

genomics↗

bioRxiv2017

Metabolic Effects Of Risk Alleles In PNPLA3, TM6SF2, GCKR, And LYPLAL1 Inform About Heterogeneity Of Non-Alcoholic Fatty Liver Disease

Fatty liver has been associated with unfavourable metabolic changes in circulation and is considered as a risk factor for cardiometabolic complications such as type 2 diabetes and cardiovascular disease. We aimed to provide insights in fatty liver related metabolic deviations by studying the resemblance between the metabolic profile associated with fatty liver observationally and metabolic profiles of non-alcoholic fatty liver disease (NAFLD) risk increasing genotypes. We determined cross-sectional associations of ultrasound-ascertained fatty liver status with 123 metabolic traits in 1,810 individuals aged 34-49 years from The Cardiovascular Risk in Young Finns Study. The cross-sectional associations were compared with the association profiles of NAFLD risk alleles in PNPLA3, TM6SF2, GCKR, and LYPLAL1 with the corresponding metabolic traits obtained from a publicly available genome-wide association study including up to 24,925 European individuals. The analysis revealed substantially different metabolic effects of the risk alleles. PNPLA3 rs738409-G, the strongest genetic risk factor to NAFLD, did not associate with metabolic changes. GCKR rs1260326-T resulted in an association profile similar to the observational fatty liver associations. Metabolic effects of LYPLAL1 rs12137855-C were similar, but statistically less robust, to the effects of GCKR rs1260326-T. In contrast, NAFLD risk allele TM6SF2 rs58542926-T displayed opposite metabolic associations when compared with the observational association pattern.\n\nConclusionThe divergent effects of the risk alleles on circulating lipids and metabolites underline involvement of several metabolic pathways in NAFLD and suggest that there are pathogenically different subtypes of NAFLD with alternate metabolic consequences. NAFLD risk alleles may have neutral or even cardioprotective effect on circulating lipids and metabolites providing evidence that hepatic lipid accumulation by itself would not necessarily cause the metabolic deviations associated observationally with fatty liver.

epidemiology↗