Metabolic Changes Precede the Development of Pulmonary Hypertension in the Monocrotaline Exposed Rat Lung.

There is increasing interest in the potential for metabolic profiling to evaluate the progression of pulmonary hypertension (PH). However, a detailed analysis of the metabolic changes in lungs at the early stage of PH, characterized by increased pulmonary artery pressure but prior to the development of right ventricle hypertrophy and failure, is lacking in a preclinical animal model of PH. Thus, we undertook a study using rats 14 days after exposure to monocrotaline (MCT), to determine whether we could identify early stage metabolic changes prior to the manifestation of developed PH. We observed changes in multiple pathways associated with the development of PH, including activated glycolysis, increased markers of proliferation, disruptions in carnitine homeostasis, increased inflammatory and fibrosis biomarkers, and a reduction in glutathione biosynthesis. Further, our global metabolic profile data compare favorably with prior work carried out in humans with PH. We conclude that despite the MCT-model not recapitulating all the structural changes associated with humans with advanced PH, including endothelial cell proliferation and the formation of plexiform lesions, it is very similar at a metabolic level. Thus, we suggest that despite its limitations it can still serve as a useful preclinical model for the study of PH

Metabolites of milk intake: a metabolomic approach in UK twins with findings replicated in two European cohorts

Purpose: Milk provides a significant source of calcium, protein, vitamins and other minerals to Western populations throughout life. Due to its widespread use, the metabolic and health impact of milk consumption warrants further investigation and biomarkers would aid epidemiological studies.  Methods: Milk intake assessed by a validated food frequency questionnaire was analyzed against fasting blood metabolomic profiles from two metabolomic platforms in females from the TwinsUK cohort (n = 3559). The top metabolites were then replicated in two independent populations (EGCUT, n = 1109 and KORA, n = 1593), and the results from all cohorts were meta-analyzed.  Results: Four metabolites were significantly associated with milk intake in the TwinsUK cohort after adjustment for multiple testing (P < 8.08 × 10−5) and covariates (BMI, age, batch effects, family relatedness and dietary covariates) and replicated in the independent cohorts. Among the metabolites identified, the carnitine metabolite trimethyl-N-aminovalerate (β = 0.012, SE = 0.002, P = 2.98 × 10−12) and the nucleotide uridine (β = 0.004, SE = 0.001, P = 9.86 × 10−6) were the strongest novel predictive biomarkers from the non-targeted platform. Notably, the association between trimethyl-N-aminovalerate and milk intake was significant in a group of MZ twins discordant for milk intake (β = 0.050, SE = 0.015, P = 7.53 × 10−4) and validated in the urine of 236 UK twins (β = 0.091, SE = 0.032, P = 0.004). Two metabolites from the targeted platform, hydroxysphingomyelin C14:1 (β = 0.034, SE = 0.005, P = 9.75 × 10−14) and diacylphosphatidylcholine C28:1 (β = 0.034, SE = 0.004, P = 4.53 × 10−16), were also replicated.  Conclusions: We identified and replicated in independent populations four novel biomarkers of milk intake: trimethyl-N-aminovalerate, uridine, hydroxysphingomyelin C14:1 and diacylphosphatidylcholine C28:1. Together, these metabolites have potential to objectively examine and refine milk-disease associations

Untangling the relationship between diet and visceral fat mass through blood metabolomics and gut microbiome profiling

BACKGROUND/OBJECTIVES: Higher visceral fat mass (VFM) is associated with an increased risk for developing cardio-metabolic diseases. The mechanisms by which an unhealthy diet pattern may influence VF development has yet to be examined through cutting-edge multi-omic methods. Therefore, our objective was to examine the dietary influences on VFM and identify gut microbiome and metabolite profiles that link food intakes to VFM. SUBJECTS/METHODS: In 2218 twins with VFM, food intake and metabolomics data available we identified food intakes most strongly associated with VFM in 50% of the sample, then constructed and tested the ‘VFM diet score’ in the remainder of the sample. Using linear regression (adjusted for covariates, including BMI and total fat mass) we investigated associations between the VFM diet score, the blood metabolomics profile and the faecal microbiome (n=889), and confirmed these associations with VFM. We replicated top findings in monozygotic (MZ) twins discordant (greater than or equal to1 s.d. apart) for VFM, matched for age, sex and the baseline genetic sequence. RESULTS: Four metabolites were associated with the VFM diet score and VFM: hippurate, alpha-hydroxyisovalerate, bilirubin (Z,Z) and butyrylcarnitine. We replicated associations between VFM and the diet score (Beta[s.e.]: 0.281[0.091]; P=0.002), butyrylcarnitine (0.199[0.087]; P=0.023) and hippurate (−0.297[0.095]; P=0.002) in VFM-discordant MZ twins. We identified a single species, Eubacterium dolichum to be associated with the VFM diet score (0.042[0.011], P=8.47 × 10−5), VFM (0.057[0.019], P=2.73 × 10−3) and hippurate (−0.075[0.032], P=0.021). Moreover, higher blood hippurate was associated with elevated adipose tissue expression neuroglobin, with roles in cellular oxygen homeostasis (0.016[0.004], P=9.82 × 10−6). CONCLUSION: We linked a dietary VFM score and VFM to Eubacterium dolichum and four metabolites in the blood. In particular, the relationship between hippurate, a metabolite derived from microbial metabolism of dietary polyphenols, and reduced VFM, the microbiome and increased adipose tissue expression of neuroglobin provides potential mechanistic insight into the influence of diet on VFM

An Integrated Clinico-Metabolomic Model Improves Prediction of Death in Sepsis

Sepsis is a common cause of death, but outcomes in individual patients are difficult to predict. Elucidating the molecular processes that differ between sepsis patients who survive and those who die may permit more appropriate treatments to be deployed. We examined the clinical features, and the plasma metabolome and proteome of patients with and without community-acquired sepsis, upon their arrival at hospital emergency departments and 24 hours later. The metabolomes and proteomes of patients at hospital admittance who would die differed markedly from those who would survive. The different profiles of proteins and metabolites clustered into fatty acid transport and β-oxidation, gluconeogenesis and the citric acid cycle. They differed consistently among several sets of patients, and diverged more as death approached. In contrast, the metabolomes and proteomes of surviving patients with mild sepsis did not differ from survivors with severe sepsis or septic shock. An algorithm derived from clinical features together with measurements of seven metabolites predicted patient survival. This algorithm may help to guide the treatment of individual patients with sepsis