A new statistical workflow (R-packages based) to investigate associations between one variable of interest and the metabolome.

Introduction: In metabolomics, the investigation of associations between the metabolome and one trait of interest is a key research question. However, statistical analyses of such associations are often challenging. Statistical tools enabling resilient verification and clear presentation are therefore highly desired.

Acute effects of moderate vs. vigorous endurance exercise on urinary metabolites in healthy, young, physically active men-A multi-platform metabolomics approach.

Endurance exercise alters whole-body as well as skeletal muscle metabolism and physiology, leading to improvements in performance and health. However, biological mechanisms underlying the body's adaptations to different endurance exercise protocols are not entirely understood. We applied a multi-platform metabolomics approach to identify urinary metabolites and associated metabolic pathways that distinguish the acute metabolic response to two endurance exercise interventions at distinct intensities.

Gut Microbiome Analysis for Personalized Nutrition: The State of Science.

Whereas most concepts of personalized nutrition (PN) in the past, included genotyping, recent years have brought new approaches that include microbiome analysis to optimize recommendations for diet and lifestyle changes. The new approach, offered by companies, that microbiome analysis provides a real benefit to either more concise recommendations or for increased compliance to PN, is largely lacking scientific validation. Although the microbiome field shows enormous proliferation, it has some major flaws that make its use in the public health domain currently critical.

The role of baseline serum 25(OH)D concentration for a potential personalized vitamin D supplementation.

There are many examples in clinical nutrition with individuals responding differently to a dietary intervention. Here, personalized nutritional recommendations could be targeted, tailoring interventions to address plurality in response. For this, we reconsidered two randomized controlled trials investigating whether two different supplementation doses of cholecalciferol resulted in an increased serum 25(OH)D concentration.

What is the promise of personalised nutrition?

Personalised nutrition (PN) is an emerging field that bears great promise. Several definitions of PN have been proposed and different modelling approaches have been used to claim PN effects. We tentatively propose to group these approaches into two categories, which we term outcome-based and population reference approaches, respectively.

Exploring the Diversity of Sugar Compounds in Healthy, Prediabetic, and Diabetic Volunteers.

Scope: Diabetes is thought to primarily represent a disturbance of carbohydrate metabolism; however, population studies employing metabolomics have mainly identified plasma amino acids and lipids, or their products, as biomarkers. In this pilot study, the aim is to analyze a wide spectrum of sugar compounds in the fasting state and during an oral glucose tolerance test (OGTT) in healthy, prediabetic, and type 2 diabetic volunteers.

Methods And Results: The three volunteer groups underwent a standard OGTT.

The complex human urinary sugar profile: determinants revealed in the cross-sectional KarMeN study.

Background: Although sugars and sugar derivatives are an important class of metabolites involved in many physiologic processes, there is limited knowledge on their occurrence and pattern in biofluids.

Objective: Our aim was to obtain a comprehensive urinary sugar profile of healthy participants and to demonstrate the wide applicability and usefulness of this sugar profiling approach for nutritional as well as clinical studies.

Design: In the cross-sectional KarMeN study, the 24-h urine samples of 301 healthy participants on an unrestricted diet, assessed via a 24-h recall, were analyzed by a newly developed semitargeted gas chromatography-mass spectrometry (GC-MS) profiling method that enables the detection of known and unknown sugar compounds.

Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies.

The life sciences are currently being transformed by an unprecedented wave of developments in molecular analysis, which include important advances in instrumental analysis as well as biocomputing. In light of the central role played by metabolism in nutrition, metabolomics is rapidly being established as a key analytical tool in human nutritional studies. Consequently, an increasing number of nutritionists integrate metabolomics into their study designs.

Associations of current diet with plasma and urine TMAO in the KarMeN study: direct and indirect contributions.

Scope: Knowledge on the influence of current diet on trimethylamine-N-oxide (TMAO) levels in humans is still inconsistent. Thus, we aimed to investigate associations of current diet with urine and plasma TMAO levels and to determine the effect of different foods on TMAO variation.

Methods And Results: TMAO concentrations of 297 healthy individuals were assessed using H-NMR spectroscopy for 24 h urine collection and spot urine, and LC-MS for plasma.

Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease.

Background: Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits.

Objectives: This study sought to systematically test if genetic variants identified for non-CAD diseases/traits also associate with CAD and to undertake a comprehensive analysis of the extent of pleiotropy of all CAD loci.

Transferring entropy to the realm of GxG interactions.

Genome-wide association studies are moving to genome-wide interaction studies, as the genetic background of many diseases appears to be more complex than previously supposed. Thus, many statistical approaches have been proposed to detect gene-gene (GxG) interactions, among them numerous information theory-based methods, inspired by the concept of entropy. These are suggested as particularly powerful and, because of their nonlinearity, as better able to capture nonlinear relationships between genetic variants and/or variables.

Rheumatoid Arthritis and Coronary Artery Disease: Genetic Analyses Do Not Support a Causal Relation.

Objective: Inflammatory diseases, specifically rheumatoid arthritis (RA), are assumed to increase the risk of coronary artery disease (CAD). More recently, multiple single-nucleotide polymorphisms (SNP) associated with RA risk were identified. If causal mechanisms affecting risks of RA and CAD are overlapping, risk alleles for RA might also increase the risk of CAD.

Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease.

Background: The discovery of low-frequency coding variants affecting the risk of coronary artery disease has facilitated the identification of therapeutic targets.

Methods: Through DNA genotyping, we tested 54,003 coding-sequence variants covering 13,715 human genes in up to 72,868 patients with coronary artery disease and 120,770 controls who did not have coronary artery disease. Through DNA sequencing, we studied the effects of loss-of-function mutations in selected genes.

Genetic variants associated with celiac disease and the risk for coronary artery disease.

Epidemiological evidence suggests that patients with celiac disease are at increased risk for coronary artery disease (CAD). Genetic-epidemiological analyses identified many single nucleotide polymorphisms (SNPs) associated with celiac disease. If there is a causal relation between celiac disease and CAD, one might expect that risk alleles primarily associated with celiac disease also increase the risk of CAD.