Metabolome-wide association study on ABCA7 indicates a role of ceramide metabolism in Alzheimer's disease.

Genome-wide association studies (GWASs) have identified genetic loci associated with the risk of Alzheimer's disease (AD), but the molecular mechanisms by which they confer risk are largely unknown. We conducted a metabolome-wide association study (MWAS) of AD-associated loci from GWASs using untargeted metabolic profiling (metabolomics) by ultraperformance liquid chromatography-mass spectrometry (UPLC-MS). We identified an association of lactosylceramides (LacCer) with AD-related single-nucleotide polymorphisms (SNPs) in ABCA7 (P = 5.0 × 10-5 to 1.3 × 10-44). We showed that plasma LacCer concentrations are associated with cognitive performance and genetically modified levels of LacCer are associated with AD risk. We then showed that concentrations of sphingomyelins, ceramides, and hexosylceramides were altered in brain tissue from Abca7 knockout mice, compared with wild type (WT) (P = 0.049-1.4 × 10-5), but not in a mouse model of amyloidosis. Furthermore, activation of microglia increases intracellular concentrations of hexosylceramides in part through induction in the expression of sphingosine kinase, an enzyme with a high control coefficient for sphingolipid and ceramide synthesis. Our work suggests that the risk for AD arising from functional variations in ABCA7 is mediated at least in part through ceramides. Modulation of their metabolism or downstream signaling may offer new therapeutic opportunities for AD.

Chemometrics Methods and Strategies in Metabolomics.

Chemometrics has been a fundamental discipline for the development of metabolomics, while symbiotically growing with it. From design of experiments, through data processing, to data analysis, chemometrics tools are used to design, process, visualize, explore and analyse metabolomics data.In this chapter, the most commonly used chemometrics methods for data analysis and interpretation of metabolomics experiments will be presented, with focus on multivariate analysis. These are projection-based linear methods, like principal component analysis (PCA) and orthogonal projection to latent structures (OPLS), which facilitate interpretation of the causes behind the observed sample trends, correlation with outcomes or group discrimination analysis. Validation procedures for multivariate methods will be presented and discussed.Univariate analysis is briefly discussed in the context of correlation-based linear regression methods to find associations to outcomes or in analysis of variance-based and logistic regression methods for class discrimination. These methods rely on frequentist statistics, with the determination of p-values and corresponding multiple correction procedures.Several strategies of design-analysis of metabolomics experiments will be discussed, in order to guide the reader through different setups, adopted to better address some experimental issues and to better test the scientific hypotheses.

Metabolomics of Ramadan fasting and associated risk of chronic diseases.

BACKGROUND: The dramatic change in lifestyle associated with Ramadan fasting raises questions about its effect on metabolism and health. Metabolites, as the end product of metabolism, are excellent candidates to be studied in this regard. OBJECTIVE: This study aims to investigate the effect of Ramadan fasting on the metabolic profile and risk of chronic diseases. METHODS: The London Ramadan study (LORANS) is an observational study in which 2 blood samples were collected from 72 participants a few days before and after the fasting month of Ramadan. We conducted metabolomic profiling using nuclear magnetic resonance spectroscopy to assess the change in individual metabolites from before to after Ramadan. Also, we generated metabolic scores (scaled from 0 to 100) for 7 chronic diseases in the UK Biobank and assessed the association of Ramadan fasting with these scores in LORANS. RESULTS: Of the 72 participants, 35 were male (48.6%); the mean (± standard deviation) age was 45.7 (±16) y. Ramadan fasting was associated with changes in 14 metabolites (1 inflammation marker, 1 amino acid, 2 glycolysis-related metabolites, 2 ketone bodies, 2 triglyceride, and 6 lipoprotein subclasses), independent of changes in body composition. Using data from 117,981 participants in the UK Biobank, we generated metabolic scores for diabetes, hypertension, coronary artery disease, renal failure, colorectal cancer, breast cancer, and lung cancer. The metabolic scores for lung cancer, colorectal cancer, and breast cancer were lower after Ramadan in LORANS (-4.74, 9.6%, 95% confidence interval -6.56, -2.91, P < 0.001), (-1.09, -2.4%, -1.69, -0. 50, P < 0.001), and (-0.48, -1.1%, -0. 81, -0.15, P = 0.006), respectively. CONCLUSIONS: Ramadan fasting is associated with short-term favorable changes in the metabolic profile concerning risk of some chronic diseases. These findings should be further investigated in future, larger studies of longer follow-up with clinical outcomes.

Evidence for involvement of the alcohol consumption WDPCP gene in lipid metabolism, and liver cirrhosis.

Biological pathways between alcohol consumption and alcohol liver disease (ALD) are not fully understood. We selected genes with known effect on (1) alcohol consumption, (2) liver function, and (3) gene expression. Expression of the orthologs of these genes in Caenorhabditis elegans and Drosophila melanogaster was suppressed using mutations and/or RNA interference (RNAi). In humans, association analysis, pathway analysis, and Mendelian randomization analysis were performed to identify metabolic changes due to alcohol consumption. In C. elegans, we found a reduction in locomotion rate after exposure to ethanol for RNAi knockdown of ACTR1B and MAPT. In Drosophila, we observed (1) a change in sedative effect of ethanol for RNAi knockdown of WDPCP, TENM2, GPN1, ARPC1B, and SCN8A, (2) a reduction in ethanol consumption for RNAi knockdown of TENM2, (3) a reduction in triradylglycerols (TAG) levels for RNAi knockdown of WDPCP, TENM2, and GPN1. In human, we observed (1) a link between alcohol consumption and several metabolites including TAG, (2) an enrichment of the candidate (alcohol-associated) metabolites within the linoleic acid (LNA) and alpha-linolenic acid (ALA) metabolism pathways, (3) a causal link between gene expression of WDPCP to liver fibrosis and liver cirrhosis. Our results imply that WDPCP might be involved in ALD.

Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes.

Serum concentration of hepatic enzymes are linked to liver dysfunction, metabolic and cardiovascular diseases. We perform genetic analysis on serum levels of alanine transaminase (ALT), alkaline phosphatase (ALP) and gamma-glutamyl transferase (GGT) using data on 437,438 UK Biobank participants. Replication in 315,572 individuals from European descent from the Million Veteran Program, Rotterdam Study and Lifeline study confirms 517 liver enzyme SNPs. Genetic risk score analysis using the identified SNPs is strongly associated with serum activity of liver enzymes in two independent European descent studies (The Airwave Health Monitoring study and the Northern Finland Birth Cohort 1966). Gene-set enrichment analysis using the identified SNPs highlights involvement in liver development and function, lipid metabolism, insulin resistance, and vascular formation. Mendelian randomization analysis shows association of liver enzyme variants with coronary heart disease and ischemic stroke. Genetic risk score for elevated serum activity of liver enzymes is associated with higher fat percentage of body, trunk, and liver and body mass index. Our study highlights the role of molecular pathways regulated by the liver in metabolic disorders and cardiovascular disease.

GWAS for urinary sodium and potassium excretion highlights pathways shared with cardiovascular traits.

Urinary sodium and potassium excretion are associated with blood pressure (BP) and cardiovascular disease (CVD). The exact biological link between these traits is yet to be elucidated. Here, we identify 50 loci for sodium and 13 for potassium excretion in a large-scale genome-wide association study (GWAS) on urinary sodium and potassium excretion using data from 446,237 individuals of European descent from the UK Biobank study. We extensively interrogate the results using multiple analyses such as Mendelian randomization, functional assessment, co localization, genetic risk score, and pathway analyses. We identify a shared genetic component between urinary sodium and potassium expression and cardiovascular traits. Ingenuity pathway analysis shows that urinary sodium and potassium excretion loci are over-represented in behavioural response to stimuli. Our study highlights pathways that are shared between urinary sodium and potassium excretion and cardiovascular traits.

Dysregulated fatty acid metabolism in coronary ectasia: An extended lipidomic analysis.

BACKGROUND: Coronary artery ectasia (CAE) is not an uncommon clinical condition, which could be associated with adverse outcome. The exact pathophysiology of the disease is poorly understood and is commonly interpreted as a variant of atherosclerosis. In this study, we sought to undertake lipidomic profiling of a group of CAE patients in an attempt to achieve better understanding of its disturbed metabolism. METHODS: Untargeted lipid profiling and complementary modelling strategies were employed to compare serum samples from 16 patients with CAE (mean age 63.5±10.1years, 6 female) and 26 controls with normal smooth coronary arteries (mean age 59.2±6.6years and 7 female). Sample preparation, LC-MS analysis and metabolite identification were performed at the Swedish Metabolomics Centre, Umeå, Sweden. RESULTS: Phosphatidylcholine levels were significantly distorted in the CAE patients (p=0.001-0.04). Specifically, 16-carbon fatty acyl chain phosphatidylcholines (PC) were detected in lower levels. Similarly, 11 meioties of Sphyngomyelin (SM) species were detected at lower concentrations (p=0.000001-0.01) in the same group. However, only three metabolites were significantly higher in the pure CAE subgroup (6 patients) when compared with the 10 mixed CAE patients (two meioties of SM species and one of PC). Atherosclerosis risk factors were not different between groups. CONCLUSION: This is the first lipid profiling study reported in coronary artery ectasia. While the lower concentration and dysregulation of sphyngomyelin suggests an evidence for premature apoptosis, that of phosphatidylcholines suggests perturbed fatty acid elongation/desaturation, thus may be indicative of non-atherogenic process in CAE.

Metabolic profiles from two different breakfast meals characterized by 1H NMR-based metabolomics.

It is challenging to measure dietary exposure with techniques that are both accurate and applicable to free-living individuals. We performed a cross-over intervention, with 24 healthy individuals, to capture the acute metabolic response of a cereal breakfast (CB) and an egg and ham breakfast (EHB). Fasting and postprandial urine samples were analyzed using 1H nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis. Metabolic profiles were distinguished in relation to ingestion of either CB or EHB. Phosphocreatine/creatine and citrate were identified at higher concentrations after consumption of EHB. Beverage consumption (i.e., tea or coffee) could clearly be seen in the data. 2-furoylglycine and 5-hydroxymethyl-2-furoic acid - potential biomarkers for coffee consumption were identified at higher concentrations in coffee drinkers. Thus 1H NMR urine metabolomics is applicable in the characterization of acute metabolic fingerprints from meal consumption and in the identification of metabolites that may serve as potential biomarkers.

Design of experiments on 135 cloned poplar trees to map environmental influence in greenhouse.

To find and ascertain phenotypic differences, minimal variation between biological replicates is always desired. Variation between the replicates can originate from genetic transformation but also from environmental effects in the greenhouse. Design of experiments (DoE) has been used in field trials for many years and proven its value but is underused within functional genomics including greenhouse experiments. We propose a strategy to estimate the effect of environmental factors with the ultimate goal of minimizing variation between biological replicates, based on DoE. DoE can be analyzed in many ways. We present a graphical solution together with solutions based on classical statistics as well as the newly developed OPLS methodology. In this study, we used DoE to evaluate the influence of plant specific factors (plant size, shoot type, plant quality, and amount of fertilizer) and rotation of plant positions on height and section area of 135 cloned wild type poplar trees grown in the greenhouse. Statistical analysis revealed that plant position was the main contributor to variability among biological replicates and applying a plant rotation scheme could reduce this variation.