Search

Introduction: Untargeted metabolomics is a powerful tool that provides strategies for gaining a systematic understanding of quantitative changes in the levels of metabolites, especially when combining different metabolomic platforms. Vanilla is one of the world's most popular flavors originating from cured pods of the orchid Vanilla planifolia. However, only a few studies have investigated the metabolome of V. planifolia, and no LC-MS or GC-MS metabolomics studies with respect to leaves have been performed., Objective: The aim of the study was to comprehensively characterize the metabolome of different organs (leaves, internodes, and aerial roots) of V. planifolia., Material and Methods: Characterization of the metabolome was achieved using two complementary platforms (GC × GC-MS, LC-QToF-MS), and metabolite identification was based on a comparison with in-house databases or curated external spectral libraries., Results: In total, 127 metabolites could be identified with high certainty (confidence level 1 or 2) including sugars, amino acids, fatty acids, organic acids, and amines/amides but also secondary metabolites such as vanillin-related metabolites, flavonoids, and terpenoids. Ninty-eight metabolites showed significantly different intensities between the plant organs. Most strikingly, aglycons of flavonoids and vanillin-related metabolites were elevated in aerial roots, whereas its O-glycoside forms tended to be higher in leaves and/or internodes. This suggests that the more bioactive aglycones may accumulate where preferably needed, e.g. for defense against pathogens., Conclusion: The results derived from the study substantially expand the knowledge regarding the vanilla metabolome forming a valuable basis for more targeted investigations in future studies, e.g. towards an optimization of vanilla plant cultivation., (© 2024 The Author(s). Phytochemical Analysis published by John Wiley & Sons Ltd.)

Background: Mammography screening programmes (MSP) aim to reduce breast cancer mortality by shifting diagnoses to earlier stages. However, it is difficult to evaluate the effectiveness of current MSP because analyses can only rely on observational data, comparing women who participate in screening with women who do not. These comparisons are subject to several biases: one of the most important is self-selection into the MSP, which introduces confounding and is difficult to control for. Here, we propose an approach to quantify confounding based on breast cancer survival analyses using readily available routine data sources., Methods: Using data from the Cancer Registry of North Rhine-Westphalia, Germany, we estimate the relative contribution of confounding to the observed survival benefit of participants of the German MSP. This is accomplished by comparing non-participants, participants with screen-detected and participants with interval breast cancers for the endpoints "death from breast cancer" and "death from all causes other than breast cancer" - the latter being assumed to be unrelated to any MSP effect. By using different contrasts, we eliminate the effects of stage shift, lead and length time bias. The association of breast cancer detection mode with survival is analysed using Cox models in 68,230 women, aged 50-69 years, with breast cancer diagnosed in 2006-2014 and followed up until 2018., Results: The hazard of dying from breast cancer was lower in participants with screen-detected cancer than in non-participants (HR = 0.21, 95% CI: 0.20-0.22), but biased by lead and length time bias, and confounding. When comparing participants with interval cancers and non-participants, the survival advantage was considerably smaller (HR = 0.62, 95% CI: 0.58-0.66), due to the elimination of stage shift and lead time bias. Finally, considering only mortality from causes other than breast cancer in the latter comparison, length time bias was minimised, but a survival advantage was still present (HR = 0.63, 95% CI: 0.56-0.70), which we attribute to confounding., Conclusions: This study shows that, in addition to stage shift, lead and length time bias, confounding is an essential component when comparing the survival of MSP participants and non-participants. We further show that the confounding effect can be quantified without explicit knowledge of potential confounders by using a negative control outcome., (© 2024. The Author(s).)

Introduction: In several claims-based studies, major depressive disorder (MDD) has been associated with increased risk of hospitalization due to acute infections. It remains unclear if this is a causal effect, and if it generalizes to an increased susceptibility to infections., Methods: We used data of the BiDirect (n = 925) and the HaBIDS (n = 1007) cohort studies to estimate the effect of MDD on self-reported infections, which were assessed with identical infection susceptibility questionnaires in both studies. We used the Center for Epidemiologic Studies Depression Scale (CES-D) to examine if there was a dose-response relationship between depressive symptom severity and self-reported infections., Results: BiDirect participants with MDD diagnosis (48%) had a higher risk of lower respiratory tract infections (incidence rate ratio 1.32, 95% confidence interval [1.00-1.75]), gastrointestinal infections (1.68 [1.30-2.16]) and fever (1.48 [1.11-1.98]) after adjusting for confounders identified by a directed acyclic graph approach. There was a dose-response relationship, i.e. individuals with higher CES-D scores reported more infections. Effect sizes were similar in HaBIDS (4% individuals with MDD)., Conclusion: We found increased risks of mild infections in patients with MDD diagnosis and a dose-response relationship between depressive symptom severity and infection frequency. While causal immunological pathways remain unclear, the results of our study might contribute to a change in prevention strategies, e.g. by recommending vaccination against influenza and S. pneumoniae to MDD patients because observed effect sizes in our study are similar to those of patients with cardiovascular and metabolic diseases for which the respective vaccinations are recommended., (© 2022. The Author(s).)

Neurofilament light is a constituent of the neuronal cytoskeleton and released into the blood following neuro-axonal damage. It has previously been reported that NfL measured in blood serum is inversely related to body mass index. However, no reports exist with regard to body composition assessed using bioelectrical impedance analysis or other indicators of obesity beyond BMI. We analyzed the relationship between sNfL and body composition according to the three compartment model. Additionally, associations between sNfL, body shape index, waist-to-height ratio, and BMI were examined. The sample consisted of 769 participants assessed during the baseline examination and 693 participants examined in the course of the follow-up of the BiDirect Study. Associations between sNfL, BMI, BSI, and WtHR were separately analyzed using linear mixed models. Body compartments operationalized as fat mass, extracellular cell mass, and body cell mass were derived using BIA and the relationship with sNfL was analyzed with a linear mixed model. Lastly, we also analyzed the association between total body water and sNfL. We found significant inverse associations of sNfL with BMI and WtHR. The analysis of the three compartment model yielded significant inverse associations between sNfL, body cell mass and body fat mass, but not extracellular mass. Furthermore, total body water was also inversely related to sNfL. A potential mechanism could involve body cell mass and body fat mass as highly adaptive body constituents that either directly absorb sNfL, or promote the formation of new vasculature and thereby increase blood volume., (© 2022. The Author(s).)

A wide range of secondary metabolites has been described for various Hydrangea species, including the sweet-tasting phenyldihydroisocoumarin phyllodulcin, which is found in the leaves of Hydrangea macrophylla ssp. serrata . This work aims at the development and validation of an analytical workflow for comprehensive semi-polar metabolite profiling using liquid chromatography coupled with electrospray ionization ion mobility quadrupole time-of-flight mass spectrometry (UPLC-ESI-IMS-QToF-MS) to complement existing analytical studies. The unsupervised analysis of this data set demonstrates the capability of this analytical workflow to distinguish different H. macrophylla ssp. serrata cultivars. In combination with supervised analysis, a list of metabolites responsible for the differentiation of the cultivars studied has been obtained. Suspect screening of phenyldihydroisocoumarins provides comprehensive information, which could help in the search for key enzymes related to the biosynthesis of phyllodulcin.

Aims: In patients with coronary heart disease (CHD), we investigated whether it is possible to accurately assess the probability of short-term control of risk factors (blood pressure, cholesterol, smoking) based on individual and large-area residential characteristics., Methods and Results: We merged individual data of participants from EUROASPIRE V who were hospitalized for CHD (2014-2017) and interviewed and examined for risk factor control (2016-2017), with large-area residential data provided by Eurostat for Nomenclature of Territorial Units for Statistics (NUTS) regions using postal codes. Data from 2562 CHD patients in 16 countries were linked to data from 60 NUTS 2 and 121 NUTS 3 regions. The median time between hospitalization and interview was 14 months. We developed prediction models to assess the probability of risk factor control at interview using data from the time of hospitalization: (i) baseline models including 35 variables on patients' demographic, clinical, and socio-economic characteristics and (ii) extended models additionally considering nine variables on large-area residential characteristics. We calculated and internally validated c-indices to assess the discriminative ability of prediction models. Baseline models showed good discrimination with c-indices of 0.69, 0.70, and 0.76 for blood pressure control, cholesterol control, and smoking cessation, respectively. Extended models for blood pressure, cholesterol, and smoking yielded improved c-indices of 0.72, 0.71, and 0.78, respectively., Conclusion: Our results indicate that the probability of risk factor control in CHD patients can be accurately assessed using individual and large-area residential characteristics, allowing for an identification of patients who are less likely to achieve risk factor targets., Competing Interests: Conflict of interest: K.K. had research grant support from the European Society of Cardiology (paid to the Imperial College London). K.S.M. had a doctoral fellowship from the German Heart Foundation. All other authors declare that there is no conflict of interest., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Previously, different Hydrangea macrophylla ssp. serrata cultivars were investigated by untargeted LC-MS analysis. From this, a list of tentatively identified and unknown compounds that differ significantly between these cultivars was obtained. Due to the lack of reference compounds, especially for dihydro-isocoumarins, we aimed to isolate and structurally characterise these compounds from the cultivar 'Yae-no-amacha' using NMR and LC-MS methods. For purification and isolation, counter-current chromatography was used in combination with reversed-phase preparative HPLC as an orthogonal and enhanced purification workflow. Thirteen dihydro-isocoumarins in combination with other metabolites could be isolated and structurally identified. Particularly interesting was the clarification of dihydrostilbenoid glycosides, which were described for the first time in H. macrophylla ssp. serrata . These results will help us in further studies on the biological interpretation of our data.