BackgroundInflammation occurs as an immediate protective response of the immune system to a harmful stimulus, whether locally confined or systemic. In contrast, a persisting, i.e., chronic, inflammatory state, even at a low-grade, is a well-known risk factor in the development of common diseases like diabetes or atherosclerosis. In clinical practice, laboratory markers like high-sensitivity C-reactive protein (hsCRP), white blood cell count (WBC), and fibrinogen, are used to reveal inflammatory processes. In order to gain a deeper insight regarding inflammation-related changes in metabolism, the present study assessed the metabolic patterns associated with alterations in inflammatory markers.MethodsBased on mass spectrometry and nuclear magnetic resonance spectroscopy we determined a comprehensive panel of 613 plasma and 587 urine metabolites among 925 apparently healthy individuals. Associations between inflammatory markers, namely hsCRP, WBC, and fibrinogen, and metabolite levels were tested by linear regression analyses controlling for common confounders. Additionally, we tested for a discriminative signature of an advanced inflammatory state using random forest analysis.ResultsHsCRP, WBC, and fibrinogen were significantly associated with 71, 20, and 19 plasma and 22, 3, and 16 urine metabolites, respectively. Identified metabolites were related to the bradykinin system, involved in oxidative stress (e.g., glutamine or pipecolate) or linked to the urea cycle (e.g., ornithine or citrulline). In particular, urine 3’-sialyllactose was found as a novel metabolite related to inflammation. Prediction of an advanced inflammatory state based solely on 10 metabolites was well feasible (median AUC: 0.83).ConclusionsComprehensive metabolic profiling confirmed the far-reaching impact of inflammatory processes on human metabolism. The identified metabolites included not only those already described as immune-modulatory but also completely novel patterns. Moreover, the observed alterations provide molecular links to inflammation-associated diseases like diabetes or cardiovascular disorders.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-017-0974-6) contains supplementary material, which is available to authorized users.

Membrane envelopment and budding of negative strand RNA viruses (NSVs) is mainly driven by viral matrix proteins (M). In addition, several M proteins are also known to be involved in host cell manipulation. Knowledge about the cellular targets and detailed molecular mechanisms, however, is poor for many M proteins. For instance, Nipah Virus (NiV) M protein trafficking through the nucleus is essential for virus release, but nuclear targets of NiV M remain unknown. To identify cellular interactors of henipavirus M proteins, tagged Hendra Virus (HeV) M proteins were expressed and M-containing protein complexes were isolated and analysed. Presence of acidic leucine-rich nuclear phosphoprotein 32 family member B (ANP32B) in the complex suggested that this protein represents a direct or indirect interactor of the viral matrix protein. Over-expression of ANP32B led to specific nuclear accumulation of HeV M, providing a functional link between ANP32B and M protein. ANP32B-dependent nuclear accumulation was observed after plasmid-driven expression of HeV and NiV matrix proteins and also in NiV infected cells. The latter indicated that an interaction of henipavirus M protein with ANP32B also occurs in the context of virus replication. From these data we conclude that ANP32B is a nuclear target of henipavirus M that may contribute to virus replication. Potential effects of ANP32B on HeV nuclear shuttling and host cell manipulation by HeV M affecting ANP32B functions in host cell survival and gene expression regulation are discussed.

Comprehensive metabolic profiling allowed us to reveal molecular patterns accompanying hepatic steatosis independent of the known hallmarks. Novel biomarkers from urine (e.g., cortisol glucuronide) are worthwhile for follow-up in patients suffering from more severe liver impairment compared with our merely healthy population-based sample.

Background: White matter hyperintensities (WMH) are identified on T2-weighted magnetic resonance images of the human brain as areas of enhanced brightness; WMH are a major risk factor of stroke, dementia, and death. Currently, there are no large-scale studies testing associations between WMH and circulating metabolites. Methods: We studied up to 9,290 individuals (50.7% females, average age 61 years) from 15 populations of 8 community-based cohorts. WMH volume was quantified from T2-weighted or fluid-attenuated inversion-recovery images or as hypointensities on T1-weighted images. Circulating metabolomic measures were assessed with mass spectrometry and nuclear magnetic resonance spectroscopy. Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample, and in sex-stratified and statin treatment-stratified subsamples. Our basic models were adjusted for age, sex, age*sex, and technical covariates, and our fully adjusted models were additionally adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance-weighted method. Associations with false discovery rate (FDR)-adjusted p -values ( p FDR )<0.05 were considered significant. Results: In the meta-analysis of results from the basic models, we identified 30 metabolomic measures associated with WMH ( p FDR <0.05), 7 of which remained significant in the fully adjusted models. The most significant association was with higher level of hydroxyphenylpyruvate in males ( p FDR.full.adj =1.40×10 -7 ) and in both the pooled sample ( p FDR.full.adj =1.66×10 -4 ) and statin-nontreated ( p FDR.full.adj =1.65×10 -6 ) subsample. In males, HPP explained 3-14% of variance in WMH. In males and the pooled sample, WMH were also associated with lower levels of lysophosphatidylcholines and hydroxysphingomyelins, and a larger diameter of low-density lipoprotein particles, likely arising from higher triglyceride-to-total-lipids and lower cholesteryl ester-to-total-lipids ratios within these particles. In females, the only significant association was with higher level of glucuronate ( p FDR =0.047). Conclusions: Circulating metabolomic measures, including multiple lipid measures (e.g., lysophosphatidylcholines, hydroxysphingomyelins, low-density lipoprotein size and composition) and non-lipid metabolites (e.g., hydroxyphenylpyruvate, glucuronate) associate with WMH in a general population of middle-aged and older adults. Some metabolomic measures show marked sex specificities and explain sizable proportion of WMH variance.