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While it is known that air borne ultrafine particulate matter (PM) may pass through the pulmonary circulation of blood at the alveolar level between lung and heart and cross the air-blood barrier, the mechanism and effects are not completely clear. In this study the imaging method fluorescence lifetime imaging microscopy is adopted for visualization with high spatial resolution and quantification of ultrafine PM particles in mouse lung and heart tissues. The results showed that the median numbers of particles in lung of mice exposed to ultrafine particulate matter of diameter less than 2.5 µm was about 2.0 times more than that in the filtered air (FA)-treated mice, and about 1.3 times more in heart of ultrafine PM-treated mice than in FA-treated mice. Interestingly, ultrafine PM particles were more abundant in heart than lung, likely due to how ultrafine PM particles are cleared by phagocytosis and transport via circulation from lungs. Moreover, heart tissues showed inflammation and amyloid deposition. The component analysis of concentrated airborne ultrafine PM particles suggested traffic exhausts and industrial emissions as predominant sources. Our results suggest association of ultrafine PM exposure to chronic lung and heart tissue injuries. The current study supports the contention that industrial air pollution is one of the causative factors for rising levels of chronic pulmonary and cardiac diseases.

Although statins are widely prescribed medications, there remains considerable variability in therapeutic response. Genetics can explain only part of this variability. Metabolomics is a global biochemical approach that provides powerful tools for mapping pathways implicated in disease and in response to treatment. Metabolomics captures net interactions between genome, microbiome and the environment. In this study, we used a targeted GC-MS metabolomics platform to measure a panel of metabolites within cholesterol synthesis, dietary sterol absorption, and bile acid formation to determine metabolite signatures that may predict variation in statin LDL-C lowering efficacy. Measurements were performed in two subsets of the total study population in the Cholesterol and Pharmacogenetics (CAP) study: Full Range of Response (FR), and Good and Poor Responders (GPR) were 100 individuals randomly selected from across the entire range of LDL-C responses in CAP. GPR were 48 individuals, 24 each from the top and bottom 10% of the LDL-C response distribution matched for body mass index, race, and gender. We identified three secondary, bacterial-derived bile acids that contribute to predicting the magnitude of statin-induced LDL-C lowering in good responders. Bile acids and statins share transporters in the liver and intestine; we observed that increased plasma concentration of simvastatin positively correlates with higher levels of several secondary bile acids. Genetic analysis of these subjects identified associations between levels of seven bile acids and a single nucleotide polymorphism (SNP), rs4149056, in the gene encoding the organic anion transporter SLCO1B1. These findings, along with recently published results that the gut microbiome plays an important role in cardiovascular disease, indicate that interactions between genome, gut microbiome and environmental influences should be considered in the study and management of cardiovascular disease. Metabolic profiles could provide valuable information about treatment outcomes and could contribute to a more personalized approach to therapy.

Statins are widely prescribed for reducing LDL-cholesterol (C) and risk for cardiovascular disease (CVD), but there is considerable variation in therapeutic response. We used a gas chromatography-time-of-flight mass-spectrometry-based metabolomics platform to evaluate global effects of simvastatin on intermediary metabolism. Analyses were conducted in 148 participants in the Cholesterol and Pharmacogenetics study who were profiled pre and six weeks post treatment with 40 mg/day simvastatin: 100 randomly selected from the full range of the LDL-C response distribution and 24 each from the top and bottom 10% of this distribution (\"good\" and \"poor\" responders, respectively). The metabolic signature of drug exposure in the full range of responders included essential amino acids, lauric acid (p<0.0055, q<0.055), and alpha-tocopherol (p<0.0003, q<0.017). Using the HumanCyc database and pathway enrichment analysis, we observed that the metabolites of drug exposure were enriched for the pathway class amino acid degradation (p<0.0032). Metabolites whose change correlated with LDL-C lowering response to simvastatin in the full range responders included cystine, urea cycle intermediates, and the dibasic amino acids ornithine, citrulline and lysine. These dibasic amino acids share plasma membrane transporters with arginine, the rate-limiting substrate for nitric oxide synthase (NOS), a critical mediator of cardiovascular health. Baseline metabolic profiles of the good and poor responders were analyzed by orthogonal partial least square discriminant analysis so as to determine the metabolites that best separated the two response groups and could be predictive of LDL-C response. Among these were xanthine, 2-hydroxyvaleric acid, succinic acid, stearic acid, and fructose. Together, the findings from this study indicate that clusters of metabolites involved in multiple pathways not directly connected with cholesterol metabolism may play a role in modulating the response to simvastatin treatment. ClinicalTrials.gov NCT00451828.

Disordered cholesterol metabolism is linked to neurodegeneration. In this study we investigated the profile of cholesterol metabolites found in the cerebrospinal fluid (CSF) of Parkinson’s disease (PD) patients. When adjustments were made for confounding variables of age and sex, 7α,(25R)26-dihydroxycholesterol and a second oxysterol 7α,x,y-trihydroxycholest-4-en-3-one (7α,x,y-triHCO), whose exact structure is unknown, were found to be significantly elevated in PD CSF. The likely location of the additional hydroxy groups on the second oxysterol are on the sterol side-chain. We found that CSF 7α-hydroxycholesterol levels correlated positively with depression in PD patients, while two presumptively identified cholestenoic acids correlated negatively with depression.

GLIAL-CELL-LINE-DERIVED neurotrophic factor (GDNF) promotes the survival and phenotype of central dopaminergic 1,2 , noradrenergic 3 and motor neurons 4–6 , as well as various subpopulations of peripheral sensory and sympathetic neurons 7,8 . GDNF is structurally related to members of the transforming growth factor (TGF)-β superfamily 9 , several members of which have well-characterized receptor systems 10,11 ; however, GDNF receptors still remain undefined. Here we show that GDNF binds to, and induces tyrosine phosphorylation of, the product of the c- ret proto-oncogene, an orphan receptor tyrosine kinase, in a GDNF responsive motor-neuron cell line. Ret protein could also bind GDNF and mediate survival and growth responses to GDNF upon transfection into naive fibroblasts. Moreover, high levels of c- ret mRNA expression were found in dopaminergic neurons of the adult substantia nigra, where exogenous GDNF protected Ret-positive neurons from 6-hydroxydopamine-induced cell death. Thus the product of the c- ret proto-oncogene encodes a functional receptor for GDNF that may mediate its neurotrophic effects on motor and dopaminergic neurons.

The neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD) share some common molecular deficits including disruption of protein homeostasis leading to disease-specific protein aggregation. While insoluble protein aggregates are the defining pathological confirmation of diagnosis, patient stratification based on early molecular etiologies may identify distinct subgroups within a clinical diagnosis that would respond differently in therapeutic development programs. We are developing targeted multiple reaction monitoring (MRM) mass spectrometry methods to rigorously quantify CSF proteins from known disease genes involved in lysosomal, ubiquitin-proteasomal, and autophagy pathways. Analysis of CSF from 21 PD, 21 ALS, and 25 control patients, rigorously matched for gender, age, and age of sample, revealed significant changes in peptide levels between PD, ALS, and control. In patients with PD, levels of two peptides for chromogranin B (CHGB, secretogranin 1) were significantly reduced. In CSF of patients with ALS, levels of two peptides from ubiquitin carboxy-terminal hydrolase like protein 1 (UCHL1) and one peptide each for glycoprotein non-metastatic melanoma protein B (GPNMB) and cathepsin D (CTSD) were all increased. Analysis of patients with ALS separated into two groups based on length of survival after CSF sampling revealed that the increases in GPNMB and UCHL1 were specific for short-lived ALS patients. While analysis of additional cohorts is required to validate these candidate biomarkers, this study suggests methods for stratification of ALS patients for clinical trials and identifies targets for drug efficacy measurements during therapeutic development.

Polyunsaturated fatty acids (PUFAs) have been studied in relation to pregnancy. However, there is limited knowledge on PUFAs and their metabolites in relation to hyperemesis gravidarum (HG), a pregnancy complication associated with nutritional deficiencies and excessive vomiting. In order to survey the field, a systematic review of the literature was performed, which also included nausea and vomiting of pregnancy (NVP) due to its close relationship with HG. In the very few published studies found, the main subjects of the research concerned free fatty acids (four records), lipid profiles (three records), and bioactive lipids (one article about prostaglandin E2 and one about endocannabinoids). The authors of these studies concluded that, although no cause-and-effect relationship can be established, HG is linked to increased sympathetic responsiveness, thermogenic activity and metabolic rate. In addition, NVP is linked to a metabolic perturbance (which lasts throughout pregnancy). The low number of retrieved records underlines the need for more research in the area of PUFAs and HG, especially with regard to the underlying mechanism for the detected effects, potentially involving growth differentiation factor 15 (GDF15) since evidence for GDF15 regulation of lipid metabolism and the role for GDF15 and its receptor in nausea and vomiting is emerging.

Introduction Amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD) are two severe neurodegenerative disorders for which the disease mechanisms are poorly understood and reliable biomarkers are absent. Objectives To identify metabolite biomarkers for ALS and PD, and to gain insights into which metabolic pathways are involved in disease. Methods Nuclear magnetic resonance (NMR) metabolomics was utilized to characterize the metabolite profiles of cerebrospinal fluid (CSF) and plasma from individuals in three age, gender, and sampling-date matched groups, comprising 22 ALS, 22 PD and 28 control subjects. Results Multivariate analysis of NMR data generated robust discriminatory models for separation of ALS from control subjects. ALS patients showed increased concentrations of several metabolites in both CSF and plasma, these are alanine (CSF fold change = 1.22, p  = 0.005), creatine (CSF-fc = 1.17, p  = 0.001), glucose (CSF-fc = 1.11, p  = 0.036), isoleucine (CSF-fc = 1.24, p  = 0.002), and valine (CSF-fc = 1.17, p  = 0.014). Additional metabolites in CSF (creatinine, dimethylamine and lactic acid) and plasma (acetic acid, glutamic acid, histidine, leucine, pyruvate and tyrosine) were also important for this discrimination. Similarly, panels of CSF-metabolites that discriminate PD from ALS and control subjects were identified. Conclusions The results for the ALS patients suggest an affected creatine/creatinine pathway and an altered branched chain amino acid (BCAA) metabolism, and suggest links to glucose and energy metabolism. Putative metabolic markers specific for ALS (e.g. creatinine and lactic acid) and PD (e.g. 3-hydroxyisovaleric acid and mannose) were identified, while several (e.g. creatine and BCAAs) were shared between ALS and PD, suggesting some overlap in metabolic alterations in these disorders.

Background: Parkinson's disease is a progressive neurodegeneration that can begin in olfactory and vagal neurons and may spread via misfolded and aggregated alpha-synuclein in extracellular vesicles. The development of disease-modifying medications can be improved by the discovery of early biomarkers of disease and the characterization of the molecular mechanisms of transfer of aggregated proteins between neurons. We are attempting to identify molecular markers of toxic vesicles as candidate biomarkers for disease progression and therapeutic targets. Methods: We have isolated and characterized exosomes from neuronal and glial cells as well as from cerebrospinal fluid and blood. We have used electron and atomic force microscopy to analyse their physical properties, cell-based assays for functional studies and mass spectrometry-based proteomics to characterize their molecular composition. Results: In cell culture systems, pathological conditions such as mitochondrial stress can affect both physical properties and protein composition of exosomes. In particular, stress-induced exosomes appeared to be smaller and more homogeneous in size than those produced by the cells growing in normal conditions. We have identified proteins altered in exosomes from stressed neuronal and glial cells using mass spectrometry-based proteomic profiling. These candidate biomarkers for toxic exosomes are being used for targeted multiple reaction monitoring assays using extracellular vesicles isolated from cerebral spinal fluid and plasma from patients with Parkinson's disease. Summary/Conclusion: Our goal is to identify robust biomarkers for diagnosis of parkinsonian disorders based on isolation of exosomes from patient samples collected at Umeå University Hospital. These biobanks include longitudinal cerebral spinal fluid samples collected from patients during progression of Parkinson's disease and pre-symptomatic blood samples collected many years prior to diagnosis of disease. The fractionation of biofluids based on extracellular vesicle extraction increases the number of detectable proteins and allows the identification of additional candidate biomarkers for neurodegenerative diseases.

Sterol pathway map testing the association of pretreatment metabolites with change of LDL-C by statin treatment. Correlation matrix for testing the association of pretreatment metabolites with a change in LDL-C by statin treatment.