Metabolic homeostasis in chronic helminth infection is sustained by organ-specific metabolic rewiring

Opisthorchiasis, is a hepatobiliary disease caused by flukes of the trematode family Opisthorchiidae. A chronic form of the disease implies a prolonged coexistence of a host and the parasite. The pathological changes inflicted by the worm to the host’s hepatobiliary system are well documented. Yet, the response to the infection also triggers a deep remodeling of the host systemic metabolism reaching a new homeostasis and affecting the organs beyond the worm location. Understanding the metabolic alternation in chronic opisthorchiasis, could help us to pinpoint pathways that underlie infection opening possibilities for the development of more selective treatment strategies. Here, with this report we apply an integrative, multicompartment metabolomics analysis, using multiple biofluids, stool samples and tissue extracts to describe metabolic changes in Opisthorchis felineus infected animals at the chronic stage. We show that the shift in lipid metabolism in the serum, a depletion of the amino acids pool, an alteration of the ketogenic pathways in the jejunum and a suppressed metabolic activity of the spleen are the key features of the metabolic host adaptation at the chronic stage of O. felineus infection. We describe this combination of the metabolic changes as a “metabolically mediated immunosuppressive status of organism” which develops during a chronic infection. This status in combination with other factors (e.g., parasite-derived immunomodulators) might increase risk of infection-related malignancy

Genetics and Not Shared Environment Explains Familial Resemblance in Adult Metabolomics Data

Metabolites are small molecules involved in cellular metabolism where they act as reaction substrates or products. The term 'metabolomics' refers to the comprehensive study of these molecules. The concentrations of metabolites in biological tissues are under genetic control, but this is limited by environmental factors such as diet. In adult mono- and dizygotic twin pairs, we estimated the contribution of genetic and shared environmental influences on metabolite levels by structural equation modeling and tested whether the familial resemblance for metabolite levels is mainly explained by genetic or by environmental factors that are shared by family members. Metabolites were measured across three platforms: two based on proton nuclear magnetic resonance techniques and one employing mass spectrometry. These three platforms comprised 237 single metabolic traits of several chemical classes. For the three platforms, metabolites were assessed in 1407, 1037 and 1116 twin pairs, respectively. We carried out power calculations to establish what percentage of shared environmental variance could be detected given these sample sizes. Our study did not find evidence for a systematic contribution of shared environment, defined as the influence of growing up together in the same household, on metabolites assessed in adulthood. Significant heritability was observed for nearly all 237 metabolites; significant contribution of the shared environment was limited to 6 metabolites. The top quartile of the heritability distribution was populated by 5 of the 11 investigated chemical classes. In this quartile, metabolites of the class lipoprotein were significantly overrepresented, whereas metabolites of classes glycerophospholipids and glycerolipids were significantly underrepresented

Disruptions of Anaerobic Gut Bacteria Are Associated with Stroke and Post-stroke Infection : a Prospective Case-Control Study

In recent years, preclinical studies have illustrated the potential role of intestinal bacterial composition in the risk of stroke and post-stroke infections. The results of these studies suggest that bacteria capable of producing volatile metabolites, including trimethylamine-N-oxide (TMAO) and butyrate, play opposing, yet important roles in the cascade of events leading to stroke. However, no large-scale studies have been undertaken to determine the abundance of these bacterial communities in stroke patients and to assess the impact of disrupted compositions of the intestinal microbiota on patient outcomes. In this prospective case-control study, rectal swabs from 349 ischemic and hemorrhagic stroke patients (median age, 71 years; IQR: 67-75) were collected within 24 h of hospital admission. Samples were subjected to 16S rRNA amplicon sequencing and subsequently compared with samples obtained from 51 outpatient age- and sex-matched controls (median age, 72 years; IQR, 62-80) with similar cardiovascular risk profiles but without active signs of stroke. Plasma protein biomarkers were analyzed using a combination of nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS). Alpha and beta diversity analyses revealed higher disruption of intestinal communities during ischemic and hemorrhagic stroke compared with non-stroke matched control subjects. Additionally, we observed an enrichment of bacteria implicated in TMAO production and a loss of butyrate-producing bacteria. Stroke patients displayed two-fold lower plasma levels of TMAO than controls (median 1.97 vs 4.03 mu M, Wilcoxonp <0.0001). Finally, lower abundance of butyrate-producing bacteria within 24 h of hospital admission was an independent predictor of enhanced risk of post-stroke infection (odds ratio 0.77,p = 0.005), but not of mortality or functional patient outcome. In conclusion, aberrations in trimethylamine- and butyrate-producing gut bacteria are associated with stroke and stroke-associated infections.Peer reviewe

Insight in Genome-Wide Association of Metabolite Quantitative Traits by Exome Sequence Analyses

Metabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitative traits in serum, followed by exome sequence analysis to zoom in on putative causal variants in the associated genes. 1H Nuclear Magnetic Resonance (1H-NMR) spectroscopy experiments yielded successful quantification of 42 unique metabolites in 2,482 individuals from The Erasmus Rucphen Family (ERF) study. Heritability of metabolites were estimated by SOLAR. GWAS was performed by linear mixed models, using HapMap imputations. Based on physical vicinity and pathway analyses, candidate genes were screened for coding region variation using exome sequence data. Heritability estimates for metabolites ranged between 10% and 52%. GWAS replicated three known loci in the metabolome wide significance: CPS1 with glycine (P-value  = 1.27×10−32), PRODH with proline (P-value  = 1.11×10−19), SLC16A9 with carnitine level (P-value  = 4.81×10−14) and uncovered a novel association between DMGDH and dimethyl-glycine (P-value  = 1.65×10−19) level. In addition, we found three novel, suggestively significant loci: TNP1 with pyruvate (P-value  = 1.26×10−8), KCNJ16 with 3-hydroxybutyrate (P-value  = 1.65×10−8) and 2p12 locus with valine (P-value  = 3.49×10−8). Exome sequence analysis identified potentially causal coding and regulatory variants located in the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected by high-resolution 1H-NMR is a robust approach to uncover metabolite quantitative trait loci (mQTL), and the likely causative variants in these loci. It is anticipated that insight in the genetics of intermediate phenotypes will provide additional insight into the genetics of complex traits

Microbiota-derived short chain fatty acids modulate microglia and promote Aβ plaque deposition.

Previous studies have identified a crucial role of the gut microbiome in modifying Alzheimer's disease (AD) progression. However, the mechanisms of microbiome-brain interaction in AD were so far unknown. Here, we identify microbiota-derived short chain fatty acids (SCFA) as microbial metabolites which promote Aβ deposition. Germ-free (GF) AD mice exhibit a substantially reduced Aβ plaque load and markedly reduced SCFA plasma concentrations; conversely, SCFA supplementation to GF AD mice increased the Aβ plaque load to levels of conventionally colonized (specific pathogen-free [SPF]) animals and SCFA supplementation to SPF mice even further exacerbated plaque load. This was accompanied by the pronounced alterations in microglial transcriptomic profile, including upregulation of ApoE. Despite increased microglial recruitment to Aβ plaques upon SCFA supplementation, microglia contained less intracellular Aβ. Taken together, our results demonstrate that microbiota-derived SCFA are critical mediators along the gut-brain axis which promote Aβ deposition likely via modulation of the microglial phenotype

Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify >800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h2 total), and the proportion of heritability captured by known metabolite loci (h2 Metabolite-hits) for 309 lipids and 52 organic acids. Our study reveals significant differences in h2 Metabolite-hits among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h2 Metabolite-hits estimates than phosphatidylcholines with low degrees of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes

Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify >800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h2 total), and the proportion of heritability captured by known metabolite loci (h2 Metabolite-hits) for 309 lipids and

Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA

Genome-wide association studies have identified numerous loci linked with complex diseases, for which the molecular mechanisms remain largely unclear. Comprehensive molecular profiling of circulating metabolites captures highly heritable traits, which can help to uncover metabolic pathophysiology underlying established disease variants. We conduct an extended genome-wide association study of genetic influences on 123 circulating metabolic traits quantified by nuclear magnetic resonance metabolomics from up to 24,925 individuals and identify eight novel loci for amino acids, pyruvate and fatty acids. The LPA locus link with cardiovascular risk exemplifies how detailed metabolic profiling may inform underlying aetiology via extensive associations with very-low-density lipoprotein and triglyceride metabolism. Genetic fine mapping and Mendelian randomization uncover wide-spread causal effects of lipoprotein(a) on overall lipoprotein metabolism and we assess potential pleiotropic consequences of genetically elevated lipoprotein(a) on diverse morbidities via electronic health-care records. Our findings strengthen the argument for safe LPA-targeted intervention to reduce cardiovascular risk.Peer reviewe

Determination of internuclear distances in uniformly labeled molecules by rotational-resonance solid-state NMR.

Rotational-resonance magic-angle spinning NMR experiments are frequently used to measure dipolar couplings and to determine internuclear distances. So far most measurements were performed on samples containing isolated spin pairs. Thus, extensive structure elucidation, for example in biomolecules, requires the preparation of a whole set of doubly labeled samples. Here, we describe the analysis of the rotational-resonance polarization-exchange curves obtained from a single, uniformly labeled sample. It is shown experimentally that, at a magnetic field of 14.09 T, the rotational-resonance conditions in uniformly (13)C-labeled threonine are sufficiently narrow to permit the measurement of five distances between the four carbon spins with an accuracy of better than 10%. The polarization-exchange curves are analyzed using a modified two-spin model consisting of the two active spins. The modified model includes an additional offset in the final polarization, which comes from the coupling to the additional, passive, spins. The validity of this approach is experimentally verified for uniformly (13)C-labeled threonine. The broader applicability of such a model is demonstrated by numerical simulations which quantify the errors as a function of the most relevant parameters in the spin system