Background The gut-derived metabolite Trimethylamine N-oxide (TMAO) and its precursors - betaine, carnitine, choline, and deoxycarnitine – have been associated with an increased risk of... Show moreBackground The gut-derived metabolite Trimethylamine N-oxide (TMAO) and its precursors - betaine, carnitine, choline, and deoxycarnitine – have been associated with an increased risk of cardiovascular disease, but their relation to cognition, neuroimaging markers, and dementia remains uncertain. Methods In the population-based Rotterdam Study, we used multivariable regression models to study the associations between plasma TMAO, its precursors, and cognition in 3,143 participants. Subsequently, we examined their link to structural brain MRI markers in 2,047 participants, with a partial validation in the Leiden Longevity Study (n=318). Among 2,517 participants, we assessed the risk of incident dementia using multivariable Cox proportional hazard models. Following this, we stratified the longitudinal associations by medication use and sex, after which we conducted a sensitivity analysis for individuals with impaired renal function. Results Overall, plasma TMAO was not associated with cognition, neuroimaging markers or incident dementia. Instead, higher plasma choline was significantly associated with poor cognition (adjusted mean difference: -0.170 [95% confidence interval (CI) -0.297;-0.043]), brain atrophy and more markers of cerebral small vessel disease, such as white matter hyperintensity volume (0.237 [95% CI: 0.076;0.397]). By contrast, higher carnitine concurred with lower white matter hyperintensity volume (-0.177 [95% CI: -0.343;-0.010]). Only among individuals with impaired renal function, TMAO appeared to increase risk of dementia (hazard ratio (HR): 1.73 [95% CI: 1.16;2.60]). No notable differences were observed in stratified analyses. Conclusions Plasma choline, as opposed to TMAO, was found to be associated with cognitive decline, brain atrophy, and markers of cerebral small vessel disease. These findings illustrate the complexity of relationships between TMAO and its precursors, and emphasize the need for concurrent study to elucidate gut-brain mechanisms. Show less
De uitkomsten beschreven in dit proefschrift dragen bij aan de bestaande overtuiging dat een verfijndere classificatie voor depressie, op basis van symptoomprofielen en hun mogelijke biologische... Show moreDe uitkomsten beschreven in dit proefschrift dragen bij aan de bestaande overtuiging dat een verfijndere classificatie voor depressie, op basis van symptoomprofielen en hun mogelijke biologische onderbouwing, overwogen dient te worden. Inmiddels wordt adipositas in de dagelijkse praktijk op meer dan alleen het BMI beoordeeld, namelijk ook de tailleomtrek en het lipidenprofiel. Echter, dergelijke aandacht bestaat nog niet voor de heterogeniteit van depressie. Een grotere bewustwording van de verschillende manifestaties van depressie-symptomatologie, die het gevolg kunnen zijn van uiteenlopende pathofysiologische mechanismen, is van essentieel belang. Wanneer een patiënt met depressie een atypisch energie-gerelateerd symptoomprofiel heeft, kan het nuttig zijn om diens metabole biomarkers te controleren om mogelijke ontwikkeling van cardiometabole ziekten te voorkomen. In de klinische praktijk moeten wij ons bij de behandeling van patiënten met depressie ook meer bewust worden van de correlatie tussen symptoomprofielen van depressie en afzonderlijke biologische en klinische manifestaties. Het is cruciaal om goed te kijken naar de symptomen die bij elke patiënt tot uiting komen. De resultaten van dit proefschrift tonen aan dat patiënten met een depressie die atypische energie-gerelateerde depressieve symptomen vertonen, genetisch en klinisch kwetsbaar zijn voor aan insulineresistentie gerelateerde ziekten (namelijk adipositas, metabole ontregelingen en diabetes mellitus type 2). Een gepersonaliseerde aanpak kan behulpzaam zijn in preventie van deze chronische en complexe ziekten. Hierbij dient er rekening gehouden worden met de heterogeniteit van depressie en de associatie tussen atypische energie-gerelateerde symptomen van depressie en deze ziekten. Show less
Although ketamine can be considered to be an “old” drug, a definitive model explainingketamine pharmacokinetics for a wide range of patient populations, dosing regimens and ketamine administrations... Show moreAlthough ketamine can be considered to be an “old” drug, a definitive model explainingketamine pharmacokinetics for a wide range of patient populations, dosing regimens and ketamine administrations forms is lacking. Currently, a large number of ketamine population pharmacokinetic models is published. However, the large number of ketamine pharmacokinetic models based on data from all types of study populations,ketamine dosing regimens and administration forms, can prove to become a serious challenge for clinical decision makers, since it may not always be easy to pick the model that best suits their patient population. In this thesis, we focus on unraveling the complex pharmacokinetics and pharmacodynamics that characterize ketamine, in order to get a step closer to a final “all encompassing” pharmacokinetic-pharmacodynamic model. For the pharmacodynamic outcomes, we especially focus on the effects of ketamine on neuropathic pain, nociceptive pain (pressure pain) and psychedelic outcomes. Show less
BACKGROUND: Depression has been associated with metabolic alterations, which adversely impact cardiometabolic health. Here, a comprehensive set of metabolic markers, predominantly lipids, was... Show moreBACKGROUND: Depression has been associated with metabolic alterations, which adversely impact cardiometabolic health. Here, a comprehensive set of metabolic markers, predominantly lipids, was compared between depressed and nondepressed persons.METHODS: Nine Dutch cohorts were included, comprising 10,145 control subjects and 5283 persons with depression, established with diagnostic interviews or questionnaires. A proton nuclear magnetic resonance metabolomics platform provided 230 metabolite measures: 51 lipids, fatty acids, and low-molecular-weight metabolites; 98 lipid composition and particle concentration measures of lipoprotein subclasses; and 81 lipid and fatty acids ratios. For each metabolite measure, logistic regression analyses adjusted for gender, age, smoking, fasting status, and lipid-modifying medication were performed within cohort, followed by random-effects meta-analyses.RESULTS: Of the 51 lipids, fatty acids, and low-molecular-weight metabolites, 21 were significantly related to depression (false discovery rate q < .05). Higher levels of apolipoprotein B, very-low-density lipoprotein cholesterol, triglycerides, diglycerides, total and monounsaturated fatty acids, fatty acid chain length, glycoprotein acetyls, tyrosine, and isoleucine and lower levels of high-density lipoprotein cholesterol, acetate, and apolipoprotein Al were associated with increased odds of depression. Analyses of lipid composition indicators confirmed a shift toward less high-density lipoprotein and more very-low-density lipoprotein and triglyceride particles in depression. Associations appeared generally consistent across gender, age, and body mass index strata and across cohorts with depressive diagnoses versus symptoms.CONCLUSIONS: This large-scale meta-analysis indicates a clear distinctive profile of circulating lipid metabolites associated with depression, potentially opening new prevention or treatment avenues for depression and its associated cardiometabolic comorbidity. Show less
The detailed description of the chemical compounds present in organisms, organs/tissues, biofluids and cells is the key to understand the complexity of biological systems. The small molecules ... Show moreThe detailed description of the chemical compounds present in organisms, organs/tissues, biofluids and cells is the key to understand the complexity of biological systems. The small molecules (metabolites) are known to be very diverse in structure and function. However, the identification of the chemical structure of metabolites is one of the major bottlenecks in metabolomics research. Hence, the annotation and the structure elucidation of the metabolites are essential to understand the biological system under study. Actually, no single analytical platform exists that can measure and identify all existing metabolites. Multistage mass spectrometry (MSn) is a powerful analytical technique that helps identifying all these metabolites. This technique provides detailed structural information of the unknown metabolite by fragmenting the metabolite and its fragments recursively. However, only computational tools can provide a fast and straightforward analysis of the large amount of complex data that is generated by using MSn spectrometry. The aim of this thesis was to develop a novel semi-automatic approach for the identification of metabolites using MS n data. Furthermore, these tools were to be integrated into a pipeline to assign identities to unknown metabolites present in databases but especially to unknown metabolites not present in a database Show less
The prediction of coronary heart disease (CHD) risk is currently based on traditional risk factors (TRFs) like age, sex, lipid levels, blood pressure. Here we investigated, using the CAREMA cohort,... Show moreThe prediction of coronary heart disease (CHD) risk is currently based on traditional risk factors (TRFs) like age, sex, lipid levels, blood pressure. Here we investigated, using the CAREMA cohort, whether this prediction can potentially be improved by applying a metabolomics approach and by including information on single nucleotide polymorphisms (SNPs) previously reported to be relevant for cardiovascular disease risk. Based on the results described in this thesis it can be concluded that a metabolomics profile generated by 1H-NMR spectroscopy when combined with age and sex could mark individuals at high risk for cardiovascular disease. The performance of that method was comparable to a score based on TRFs. It was also found that a weighted genetic risk score based 29 SNPs associated with CHD marginally improved CHD risk prediction. In the Leiden Longevity Study it was examined if comprehensive lipid profiles could mark metabolic health in middle-aged individuals. We found that male metabolic health was characterized by LDL particle size and female metabolic health was characterized by triglyceride levels. Finally it was observed that an increased delta-5 desaturase activity was protective against CHD. This effect was mainly observed in AA carriers of a SNP located in FADS1 Show less
Erp, N.P. van; Wit, D. de; Guchelaar, H.J.; Gelderblom, H.; Hessing, T.J.; Hartigh, J. den 2013
