Differential Effects of Obesity, Hyperlipidaemia, Dietary Intake and Physical Inactivity on Type I versus Type IV Allergies.

BACKGROUND: Alongside metabolic diseases (esp. obesity), allergic disorders are becoming increasingly prevalent. Since both obesity and allergies are highly impacted by environmental determinants, with this study we assessed the potential link between metabolic implications and two distinct types of allergies. METHODS: Using cross-sectional data from the German FoCus cohort, n = 385 allergy cases, either hay fever (=type I allergy, n = 183) or contact allergy (=type IV allergy, n = 202) were compared to age- and sex-matched healthy control subjects (1:1 ratio, in total n = 770) regarding their metabolic phenotype, diet, physical activity, sleep, gut microbial composition, and serum metabolite profile using suitable BMI-adjusted models. RESULTS: Obesity and metabolic alterations were found significantly more prevalent in subjects with allergies. In fact, this relation was more pronounced in contact allergy than hay fever. Subsequent BMI-adjusted analysis reveals particular importance of co-occurring hyperlipidaemia for both allergy types. For contact allergy, we revealed a strong association to the dietary intake of poly-unsaturated fatty acids, particularly α-linolenic acid, as well as the enrichment of the corresponding metabolic pathway. For hay fever, there were no major associations to the diet but to a lower physical activity level, shorter duration of sleep, and an altered gut microbial composition. Finally, genetic predisposition for hyperlipidaemia was associated to both contact allergy and hay fever. CONCLUSIONS: Reflected by higher allergy prevalence, our findings indicate an impaired immune response in obesity and hyperlipidaemia, which is differentially regulated in type I and type IV allergies by an unfavourable lifestyle constellation and subsequent microbial and metabolic dysfunctions.

Vitamin C and Omega-3 Fatty Acid Intake Is Associated with Human Periodontitis-A Nested Case-Control Study.

Vitamins and omega-3 fatty acids (Ω3FA) modulate periodontitis-associated inflammatory processes. The aim of the current investigation was to evaluate associations of oral nutrient intake and corresponding serum metabolites with clinical severity of human periodontitis. Within the Food Chain Plus cohort, 373 periodontitis patients­245 without (POL) and 128 with tooth loss (PWL)­were matched to 373 controls based on sex, smoking habit, age and body mass index in a nested case-control design. The amount of oral intake of vitamins and Ω3FAs was assessed from nutritional data using a Food Frequency Questionnaire. Oral intake and circulatory bioavailability of vitamins and Ω3FA serum metabolomics were compared, using ultra-high-resolution mass spectrometry. Periodontitis patients exhibited a significantly higher oral intake of vitamin C and Ω3FA Docosapentaenoic acid (p < 0.05) compared to controls. Nutritional intake of vitamin C was higher in PWL, while the intake of Docosapentaenoic acid was increased in POL (p < 0.05) compared to controls. In accordance, serum levels of Docosapentaenoic acid were also increased in POL (p < 0.01) compared to controls. Vitamin C and the Ω3FA Docosapentaenoic acid might play a role in the pathophysiology of human periodontitis. Further studies on individualized nutritional intake and periodontitis progression and therapy are necessary.

Precision Nutrition in Chronic Inflammation.

The molecular foundation of chronic inflammatory diseases (CIDs) can differ markedly between individuals. As our understanding of the biochemical mechanisms underlying individual disease manifestations and progressions expands, new strategies to adjust treatments to the patient's characteristics will continue to profoundly transform clinical practice. Nutrition has long been recognized as an important determinant of inflammatory disease phenotypes and treatment response. Yet empirical work demonstrating the therapeutic effectiveness of patient-tailored nutrition remains scarce. This is mainly due to the challenges presented by long-term effects of nutrition, variations in inter-individual gastrointestinal microbiota, the multiplicity of human metabolic pathways potentially affected by food ingredients, nutrition behavior, and the complexity of food composition. Historically, these challenges have been addressed in both human studies and experimental model laboratory studies primarily by using individual nutrition data collection in tandem with large-scale biomolecular data acquisition (e.g. genomics, metabolomics, etc.). This review highlights recent findings in the field of precision nutrition and their potential implications for the development of personalized treatment strategies for CIDs. It emphasizes the importance of computational approaches to integrate nutritional information into multi-omics data analysis and to predict which molecular mechanisms may explain how nutrients intersect with disease pathways. We conclude that recent findings point towards the unexhausted potential of nutrition as part of personalized medicine in chronic inflammation.

A fungal pathogen induces systemic susceptibility and systemic shifts in wheat metabolome and microbiome composition.

Yield losses caused by fungal pathogens represent a major threat to global food production. One of the most devastating fungal wheat pathogens is Zymoseptoria tritici. Despite the importance of this fungus, the underlying mechanisms of plant-pathogen interactions are poorly understood. Here we present a conceptual framework based on coinfection assays, comparative metabolomics, and microbiome profiling to study the interaction of Z. tritici in susceptible and resistant wheat. We demonstrate that Z. tritici suppresses the production of immune-related metabolites in a susceptible cultivar. Remarkably, this fungus-induced immune suppression spreads within the leaf and even to other leaves, a phenomenon that we term "systemic induced susceptibility". Using a comparative metabolomics approach, we identify defense-related biosynthetic pathways that are suppressed and induced in susceptible and resistant cultivars, respectively. We show that these fungus-induced changes correlate with changes in the wheat leaf microbiome. Our findings suggest that immune suppression by this hemibiotrophic pathogen impacts specialized plant metabolism, alters its associated microbial communities, and renders wheat vulnerable to further infections.

Variability of Pyrrolizidine Alkaloid Occurrence in Species of the Grass Subfamily Pooideae (Poaceae).

Pyrrolizidine alkaloids (PAs) are a class of secondary metabolites found in various unrelated angiosperm lineages including cool-season grasses (Poaceae, subfamily Pooideae). Thesinine conjugates, saturated forms of PA that are regarded as non-toxic, have been described to occur in the two grass species Lolium perenne and Festuca arundinacea (Poaceae, subfamily Pooideae). In a wider screen, we tested various species of the Pooideae lineage, grown under controlled conditions, for their ability to produce thesinine conjugates or related structures. Using an LC-MS based targeted metabolomics approach we were able to show that PA biosynthesis in grasses is limited to a group of very closely related Pooideae species that produce a limited diversity of PA structures. High variability in PA levels was observed even between individuals of the same species. These individual accumulation patterns are discussed with respect to a possible function and evolution of this type of alkaloid.

Validation of a two-step quality control approach for a large-scale human urine metabolomic study conducted in seven experimental batches with LC/QTOF-MS.

After his study of food science at the Rheinische Friedrich-Wilhelms University of Bonn, Tobias J Demetrowitsch obtained his doctoral degree in the research field of metabolomics at the Christian-Albrechts-University of Kiel. The present paper is part of his doctoral thesis and describes an extended strategy to evaluate and verify complex or large-scale experiments and data sets. Large-scale studies result in high sample numbers, requiring the analysis of samples in different batches. So far, the verification of such LC-MS-based metabolomics studies is difficult. Common approaches have not provided a reliable validation procedure to date. This article shows a novel verification process for a large-scale human urine study (analyzed by a LC/QToF-MS system) using a two-step validation procedure. The first step comprises a targeted approach that aims to examine and exclude statistical outliers. The second step consists of a principle component analysis, with the aim of a tight cluster of all quality controls and a second for all volunteer samples. The applied study design provides a reliable two-step validation procedure for large-scale studies and additionally contains an inhouse verification procedure.