Plasma Metabolites Research Articles

Causal relationships between immune cells, plasma metabolites and lung adenocarcinoma: a two-step, two-sample Mendelian randomization study

Causal relationships between immune cells, plasma metabolites and lung adenocarcinoma: a two-step, two-sample Mendelian randomization study

Multiomics Profiling of Plasma Reveals Molecular Alterations Prior to a Diagnosis with Stroke Among Chinese Hypertension Patients.

We aimed to investigate the correlation between plasma proteins and metabolites and the occurrence of future strokes using mass spectrometry and bioinformatics as well as to identify other biomarkers that could predict stroke risk in hypertensive patients. In a nested case-control study, baseline plasma samples were collected from 50 hypertensive subjects who developed stroke and 50 gender-, age- and body mass index-matched controls. Plasma untargeted metabolomics and data independent acquisition-based proteomics analysis were performed in hypertensive patients, and 19 metabolites and 111 proteins were found to be differentially expressed. Integrative analyses revealed that molecular changes in plasma indicated dysregulation of protein digestion and absorption, salivary secretion, and regulation of actin cytoskeleton, along with significant metabolic suppression. C4BPA, Caprolactam, Col15A1, and HBB were identified as predictors of stroke occurrence, and the Support Vector Machines (SVM) model was determined to be the optimal predictive model by integrating six machine-learning classification models. The SVM model showed strong performance in both the internal validation set (area under the curve [AUC]: 0.977, 95% confidence interval [CI]: 0.941-1.000) and the external independent validation set (AUC: 0.973, 95% CI: 0.921-0.999).

Metabolic profiling in new on-set non-ischemic dilated cardiomyopathy

Abstract Background Dilated cardiomyopathy is known as the most common cardiomyopathy with no therapy directly targeted the pathogenesis. The metabolic is a promising tool for better understanding of the difference in metabolites between health and disease and offering therapeutic targets, but the understanding of the specific metabolic processes distinguishing new on-set DCM from normal individuals remains insufficient. Aim To investigate the targeted blood metabolic profiling distinctions between new on-set Dilated Cardiomyopathy (DCM) and normal group. Methods We analyzed 231 plasma metabolites by liquid chromatography ⁄ mass spectroscopy and gas chromatography ⁄ mass spectroscopy in 48 patients with new on-set DCM(the duration of DCM diagnosis was less than 6 month before enrollment) and 48 age-, sex- and body mass index-matched normal controls. Results Twenty-four metabolites were significantly different between DCM and control individuals when adjusted by sex, age and smoking [false discovery rate (FDR) < 0.05]. Plasma levels of guanidinoacetate, hypoxanthin were reduced while levels of 6-methyladenosine, 1-methyladenosine and others were increased in patients with DCM when compared to controls (figure 1), while Taurine, L-kynurenine and Methylmalonate were the most significant metabolites between the two groups (figure 2) . Conclusions Metabolic processes were strongly enhanced in DCM and may be used to distinguish new on-set DCM from normal individuals. And it identififies biologically active metabolites that could serve as markers of New-onset DCM and impart protective or harmful effects on cardiac structure and function.

Novel metabolomic predictors of incident colorectal cancer in men and women.

Metabolomic profiles may influence colorectal cancer (CRC) development. Few studies have performed pre-diagnostic metabolome-wide analyses with CRC risk. We conducted a nested case-control study among women (Nurses' Health Study (NHS)) and men (Health Professionals Follow-up Study (HPFS)) who provided blood between 1989 and 1995. Over 22.9 years, 684 (409 NHS, 275 HPFS) incident CRC cases occurred and were matched 1:1 to controls. Liquid chromatography-mass spectrometry (LC-MS) identified 255 plasma metabolites after quality control. Cohort-specific and combined metabolite association analyses were performed using conditional logistic regression. Metabolite set enrichment analysis (MSEA) was used to identify differential abundance in metabolite classes. Weighted Correlation Network Analysis (WGCNA) provided modules of covarying metabolites, which were tested for CRC association. MSEA identified specific acylcarnitines associated with higher CRC risk and triacylglycerols with lower CRC risk among women and men. Further, phosphatidylcholines were associated with a higher risk of CRC among men. In an analysis restricted to CRC cases diagnosed two years after blood draw, myristoleic acid (OR = 1.37; 95%CI = 1.15-1.62; FDR = 0.072) and C60:12 triacylglycerol (OR = 0.75; 95%CI = 0.64-0.88; FDR = 0.072 were associated with CRC risk in women. WGCNA identified amino acids associated with CRC in men, fatty acid esters (carnitines) with distal CRC in men, and triradylcglycerols inversely associated with CRC in women. We identified pre-diagnostic CRC-associated metabolites with distinct sex-specific profiles. These results provide insight into CRC etiopathogenesis and have implications for risk prediction strategies.

Pharmacometabolomics Approach to Explore Pharmacokinetic Variation and Clinical Characteristics of a Single Dose of Desvenlafaxine in Healthy Volunteers

This study investigated the effects of a single dose of desvenlafaxine via oral administration on the pharmacokinetic parameters and clinical and laboratory characteristics in healthy volunteers using a pharmacometabolomics approach. In order to optimize desvenlafaxine’s therapeutic use and minimize potential adverse effects, this knowledge is essential. Methods: Thirty-five healthy volunteers were enrolled after a health trial and received a single dose of desvenlafaxine (Pristiq®, 100 mg). First, liquid chromatography coupled to tandem mass spectrometry was used to determine the main pharmacokinetic parameters. Next, ultra-performance liquid chromatography–quadrupole time-of-flight mass spectrometry was used to identify plasma metabolites with different relative abundances in the metabolome at pre-dose and when the desvenlafaxine peak plasma concentration was reached (pre-dose vs. post-dose). Results: Correlations were observed between metabolomic profiles, such as tyrosine, sphingosine 1-phosphate, and pharmacokinetic parameters, as well as acetoacetic acid and uridine diphosphate glucose associated with clinical characteristics. Our findings suggest that desvenlafaxine may have a broader effect than previously thought by acting on the proteins responsible for the transport of various molecules at the cellular level, such as the solute carrier SLC and adenosine triphosphate synthase binding cassette ABC transporters. Both of these molecules have been associated with PK parameters and adverse events in our study. Conclusions: This altered transporter activity may be related to the reported side effects of desvenlafaxine, such as changes in blood pressure and liver function. This finding may be part of the explanation as to why people respond differently to the drug.

Blood plasma metabolites and heart failure risk: insights from Mendelian randomization analysis

Abstract Background Heart failure remains a leading cause of mortality and disability worldwide. Blood plasma metabolites play a crucial role in influencing heart failure, yet they are subject to numerous confounding factors. Mendelian randomization analysis provides a powerful tool for assessing causal relationships between them. Methods We conducted a Mendelian randomization analysis using a meta-analysis comprising 115,150 heart failure cases (155,331 controls) and 1400 serum metabolites. Various methods including Inverse variance weighting (IVW), MR Egger, Weighted median, and Weighted mode were employed to estimate causal effects. Sensitivity analyses were conducted using Cochran’s Q test, MR Steiger test, leave-one-out analyses, funnel plot, and MR-PRESSO. Results Following rigorous selection, among the 1400 blood plasma metabolites, 71 metabolites including Sphingomyelin, Myristate, AMP to methionine ratio showed significant associations with increased risk of heart failure. Additionally, 40 metabolites including Glycine, octadecenedioylcarnitine (C18:1-DC), 1-palmitoyl-2-dihomo-linolenoyl-GPC (16:0/20:3n3 or 6) exhibited significant associations with decreased risk of heart failure. Conclusion Identified blood plasma metabolites provide crucial insights into screening and prevention strategies for heart failure. Further validation is warranted through animal models and large-scale cohorts.

Circulating metabolites associate with the QT interval in individuals without prevalent cardiovascular disease

Abstract Background Patients with metabolic syndrome have a higher prevalence of heart-rate corrected QT (QTc) interval prolongation. Despite this the effect of circulating metabolites on the QTc is largely unknown and limited to small studies. Purpose To test for association of circulating metabolites with the QTc interval in the UK Biobank study. Methods Participants were identified from the UK Biobank with same day plasma metabolite profiling and electrocardiograms. All 249 metabolites measured underwent quality control and log transformation to account for rightward skew and zero values. 149 metabolites with inter-correlations >0.7 were excluded. Participants taking QTc-prolonging medication or with a history of ischaemic heart disease or heart failure up to 6 months after the visit, were excluded. Participants were allocated to a training group (N=21,610) or an independent test group (N=5,304), if samples were obtained at recruitment or at a second visit, respectively. In the training group, each metabolite was tested separately for association with the QTc in linear regression analyses, adjusted for clinical covariates (age, sex, fasting time, body mass index (BMI), systolic blood pressure (SBP), smoking status, diabetes, lipid-lowering drug use and dietary factors). Significant metabolites (P<5x10-4) underwent validation in the test group. Sex-stratified analyses were also performed. In the training group, variables in two models underwent regularisation by LASSO regression (10-fold cross-validation) to reduce multicollinearity and downweigh less important variables; 1) clinical variables, 2) clinical variables and validated metabolites. Coefficients were used for QTc prediction in the test group. Significance between the models was evaluated by fisher’s transformation of R-squared statistics. Results In the per metabolite multivariate analysis, 56 metabolites were associated with the QTc interval. 19 metabolites validated in the test group. For 14 of these, absolute effect sizes were >5ms when comparing individuals in the top decile of the metabolite distribution verses the bottom (Figure 1), including the ketone body 3-hydroxybutyrate (9ms), and omega-6 fatty acid to total fatty acid ratio (7.2ms). For associations in males and females separately, significant effect size differences (P<0.05) were observed for 9 metabolites (Figure 2). In the training group, the combined LASSO model selected 17 (of 19) metabolites along with age, sex, SBP and BMI. In the test group, this model R-squared was 0.115 compared with 0.081 for clinical covariates alone, representing a significant 41.9% increase in QTc variation explained (P=0.002). Conclusions This study demonstrates clinically relevant metabolite associations with the QTc in individuals without cardiovascular disease and explain a significant proportion of QTc variation. Further investigation is warranted to test for direct effects on cardiac electrophysiology and proarrhythmic potential.Validated metabolitesSignificant sex differences

Plasma statin concentrations do not correlate with statin-induced myalgia

Abstract Aims Statins are essential in cardiovascular prevention. Although well-tolerated, patient adherence is often suboptimal due to experienced musculoskeletal symptoms ranging from mild myalgia to rare life-threatening rhabdomyolysis. This study aimed to investigate the relationship between plasma concentrations of statin metabolites in patients experiencing myalgia without rhabdomyolysis. Methods and results Plasma concentrations of statin metabolites were quantitatively assessed using mass spectrometry across three case-control cohorts evaluating statin-induced myalgia. The analysis included a total of 373 patients from the MILANO study (N=85 with self -reported myalgia), the MONTREAL study (N=248 with clinically verified myalgia) and the STOMP study (N=40 with rechallenge-verified statin-induced myalgia). STOMP found no significant difference in the plasma concentrations of statin metabolites between statin naïve patients with myalgia (N=12) taking atorvastatin 80 mg daily and asymptomatic controls (N=28), including upon subsequent statin rechallenge. Both the MILANO and MONTREAL studies showed lower plasma concentrations of statin metabolites in patients with myalgias compared to controls. MILANO showed a significant difference in rosuvastatin lactone concentration in patients with myalgias compared to asymptomatic controls (P = 0.025). Similarly, MONTREAL showed significantly lower mean atorvastatin metabolite concentrations in affected patients versus controls (P values ranging from 0.0073 to 0.037). Atorvastatin dosages in MONTREAL ranged from 5 to 80 mg daily, the most frequent regimens being 20 mg (27% in cases; 24% in controls) and 40 mg (33% in cases; 37% in controls). Creatine kinase levels were measured in all cohorts and were not different between cases and controls. Conclusion Development of myalgias in patients with normal creatine kinase levels is not associated with higher statin metabolite plasma concentrations. Myalgias during statin therapy are not caused by pharmacokinetic abnormalities.

A Simple HPLC-DAD Method for the Therapeutic Monitoring of Clozapine and Related Metabolites in Human Plasma and Urine Samples

Clozapine and its metabolites require close therapeutic monitoring (TDM) in patients due to poor correlation between the administrated doses and resulting plasma concentrations, the narrow therapeutic interval, high inter-individual variability, and the risk of serious side effects once toxic levels are exceeded. The aim of the study was to develop a simple (relatively cheap) LC-UV method for the quantification of clozapine and its metabolites in plasma and urine samples. For sample preparation, liquid-liquid extraction (LLE) in n-octanol was more efficient and less limiting in injection volumes compared to the in-situ formation of SUPRAS. When analyzing urine, an alkalinization step before extraction was required. The proposed method produced linear concentration responses with/without internal standard (IS) for the target analytes, with LLOQs within the targeted range of 50 ppb and %RSD within the acceptable 15% range. Furthermore, sample stability studies proved that pre-extracted samples were stable for the short term at room temperature and long-term when frozen.

Identification of metabolic biomarkers in idiopathic pulmonary arterial hypertension using targeted metabolomics and bioinformatics analysis

Pulmonary arterial hypertension (PAH) is a life-threatening disease with a poor prognosis, and metabolic abnormalities play a critical role in its development. This study used metabolomics, machine learning algorithms and bioinformatics to screen for potential metabolic biomarkers associated with the diagnosis of PAH. In this study, plasma samples were collected from 17 patients diagnosed with idiopathic pulmonary arterial hypertension (IPAH) and 20 healthy controls. Plasma metabolomic profiling was performed by high-performance liquid chromatography-mass spectrometry. Gene profiles of PAH patients were obtained from the GEO database. Key differentially expressed metabolites (DEMs) and metabolism-related genes were subsequently identified using machine learning algorithms. Twenty differential plasma metabolites associated with IPAH were identified (VIP score > 1 and p < 0 0.05), and enrichment analysis revealed the arginine biosynthesis pathway as the most altered pathway. Using machine learning models, including least absolute shrinkage and selection operator (LASSO), random forest (RF) and support vector machine (SVM), we extracted key metabolites that correlated with clinical phenotypes. Our results suggested that five metabolites, kynurenine, homoserine, tryptophan, AMP, and spermine, are potential biomarkers for IPAH. Bioinformatics analysis also identified 3 metabolism-related genes, MAPK6, SLC7A11 and CDC42BPA, that are strongly correlated with pulmonary hypertension, demonstrating strong predictive power and clinical relevance. Our findings revealed some key genes associated with metabolism in PH, and provided crucial information about complex metabolic reprogramming signals and may lead to the identification of useful metabolic biomarkers for the diagnosis of PAH.

Effects of ethanol extract from senna leaf (EESL) on inflammation and oxidative stress in mice: A non-targeted metabolomic study.

Senna leaf is a commonly used medication for treating constipation, and long-term use can cause damage to the intestinal mucosa and lead to drug dependence. But the exact mechanism remains unclear. Using non-targeted metabolomics technology to study the mechanism of senna leaf ethanol extract (EESL) inducing inflammation and oxidative stress in mice and causing side effects. EESL was administered to mice by gavage to detect inflammation and oxidative stressrelated factors in mice, and the EESL components and differential metabolites in mouse plasma were analyzed using non-targeted metabolome techniques. 23 anthraquinone compounds were identified in the EESL, including sennoside and their derivatives. Administration of EESL to mice resulted in a significant increase in pro-inflammatory factors, IL-1β, and IL-6 in the plasma, while the levels of IgA significantly decreased. The levels of oxidative stress significantly increased, and the intestinal mucosal integrity was impaired. 21 endogenous in plasma metabolites were identified as differential metabolites related with taurine and taurine metabolism, glycerophospholipid metabolism, arachidonic acid metabolism, tryptophan metabolism, and sphingolipid metabolism. These metabolic pathways are related to oxidative stress and inflammation. Senna leaf can inhibit the expression of tight junction proteins in the intestinal mucosa and disrupt intestinal mucosal barrier integrity, exacerbating oxidative stress and inflammation induced by bacterial LPS entering the bloodstream. In addition, the impact of Senna leaf on tryptophan metabolism may be linked to the occurrence of drug dependence.

Multiomic integration analysis identifies atherogenic metabolites mediating between novel immune genes and cardiovascular risk

BackgroundUnderstanding genetic-metabolite associations has translational implications for informing cardiovascular risk assessment. Interrogating functional genetic variants enhances our understanding of disease pathogenesis and the development and optimization of targeted interventions.MethodsIn this study, a total of 187 plasma metabolite levels were profiled in 4974 individuals of European ancestry of the GCAT| Genomes for Life cohort. Results of genetic analyses were meta-analysed with additional datasets, resulting in up to approximately 40,000 European individuals. Results of meta-analyses were integrated with reference gene expression panels from 58 tissues and cell types to identify predicted gene expression associated with metabolite levels. This approach was also performed for cardiovascular outcomes in three independent large European studies (N = 700,000) to identify predicted gene expression additionally associated with cardiovascular risk. Finally, genetically informed mediation analysis was performed to infer causal mediation in the relationship between gene expression, metabolite levels and cardiovascular risk.ResultsA total of 44 genetic loci were associated with 124 metabolites. Lead genetic variants included 11 non-synonymous variants. Predicted expression of 53 fine-mapped genes was associated with 108 metabolite levels; while predicted expression of 6 of these genes was also associated with cardiovascular outcomes, highlighting a new role for regulatory gene HCG27. Additionally, we found that atherogenic metabolite levels mediate the associations between gene expression and cardiovascular risk. Some of these genes showed stronger associations in immune tissues, providing further evidence of the role of immune cells in increasing cardiovascular risk.ConclusionsThese findings propose new gene targets that could be potential candidates for drug development aimed at lowering the risk of cardiovascular events through the modulation of blood atherogenic metabolite levels.

Retinol intake and PCOS management: a plasma metabolite and protein analysis via Mendelian randomization and NHANES 2011-2016.

Polycystic Ovary Syndrome (PCOS) represents a complex endocrine disorder characterized by a significant interplay with metabolic dysfunction and obesity. This research endeavors to elucidate the causal dynamics among plasma metabolites, proteins, and PCOS, alongside Body Mass Index (BMI), to pinpoint prospective therapeutic interventions. This investigation employed Mendelian randomization (MR) analyses combined with data derived from the National Health and Nutrition Examination Survey (NHANES) to explore the relationships between 1,400 plasma metabolites and PCOS, factoring in BMI adjustments. Additionally, the study examined the influence of plasma proteins and performed a retrospective cross-sectional analysis focusing on retinol consumption and testosterone levels. MR analyses showed metabolite Glycosyl-N-(2-hydroxynervonoyl)-sphingosine (GNS) and protein Keratin 19 (KRT19) were identified as significant markers in the context of PCOS and BMI adjustments. A Phenome-Wide Association Study (PheWAS) underscored the linkage between KRT19 and BMI, while gene-drug interaction findings demonstrated a connection between KRT19 and retinol. Analysis for NHANES data disclosed a negative correlation between retinol intake and testosterone levels, particularly within normal weight and obese cohorts, suggesting the feasibility of dietary interventions for PCOS management. The study sheds light on the intricate interactions between plasma metabolites, proteins, and PCOS, considering BMI variations, and highlights KRT19 protein as a promising therapeutic target. The outcomes support the integration of retinol consumption into dietary strategies to regulate testosterone levels and potentially alleviate PCOS symptoms, underscoring the necessity for personalized nutritional and therapeutic approaches in the effective management of PCOS.

Metabolic fate of the natural anticancer agent cucurbitacin B: an LC-MS/MS-enabled profiling of its major phase I and II conjugates in vivo.

Cucurbitacin B (CuB) is a natural triterpenoid with diverse pharmacological effects including potent anticancer activity. However, its oral bioavailability is hampered by limited metabolism in vivo. We characterized CuB's in vivo metabolism in rats to uncover bioactive metabolites retaining therapeutic potential, using a robust UHPLC-Q-TOF-MS/MS workflow. This workflow combined molecular networking, fragmentation filtering, and mass defect filtering to identify CuB metabolites in rat urine, plasma, and feces following oral administration. Thirteen metabolites were identified and seven were confirmed. Major phase I transformations involved hydrolysis, reduction, epoxidation, and amination. Phase II conjugation included cysteine, glutathione, glucuronide, and gluconic acid conjugates. Notably, one of the main metabolites formed was the cysteine conjugate CuB-Cys. CuB-Cys maintained similar in vitro antiproliferative activity to CuB on HepG2, MCF-7, and PANC-1 cancer cell lines. However, it demonstrated lower cytotoxicity towards non-cancerous L02 cells, highlighting improved therapeutic selectivity. Mechanistically, CuB-Cys induced greater apoptotic signaling in HepG2 cells than CuB via enhanced caspase activation and disrupted BAX-Bcl-2 balance. This represents the first systematic characterization of CuB's in vivo metabolic pathway. The identification and confirmation of CuB-Cys provide insight for drug development efforts aiming to maintain therapeutic efficacy while reducing toxicity, via metabolite-based approaches. Our findings shed light on strategies for improving CuB's clinical potential.

Simultaneous quantification of JWH-018, JWH-073, and their metabolites (4-OH JWH-018, 3-OH JWH-073) in human plasma and urine samples by LC-MS/MS

This study aims to develop and validate a method for the simultaneous quantification of JWH-073, JWH-018, and their two main metabolites 3-OH JWH-073 and 4-OH JWH-018 in human blood and urine samples by using liquid chromatography combined with a mass spectrometer (LC-MS/MS). The method was validated according to current FDA and EMA guidelines and was tested on 10 urine samples from suspected synthetic cannabinoid abusers and 10 plasma samples from drug-free volunteers. Experimental data showed that the limits of detection (LOD) for the analytes were very low at 0.01 ng/mL in plasma samples and 0.003 ng/mL in urine samples. The limits of quantification (LLOQ) were 0.03 ng/mL in plasma samples and 0.01 ng/mL in urine samples. The linear correlation coefficients (R 2) for these analytes ranged from 0.9914 to 0.9929 in plasma samples and 0.9820 to 0.9892 in urine samples. Among the 10 urine samples from suspected synthetic cannabinoid abusers, the parent JWH-073 and JWH-018 analytes were detected in six and three samples, with concentrations of 0.01 − 8.14 ng/mL and 7.16 − 17.50 ng/mL, respectively. At the same time, their two main metabolites, 3-OH JWH-073 and 4-OH JWH-018, were also found in the samples containing parent drugs, with concentrations of 32.13 − 84.24 ng/mL and 14.48–32.97 ng/mL, respectively. Three samples (T3, T5, and T6) contained only 4-OH JWH-018 metabolite (with concentrations of 25.69 − 51.87 ng/mL) and one sample (T10) contained only 3-OH JWH-073 metabolite (with concentration of 56.94 ng/mL) without the presence of their parent drugs. The plasma samples from drug-free volunteers were all negative for the analytes.

A systematic UHPLC-Q-TOF-MS/MS-based strategy for analysis of chemical constituents and related in vivo metabolites of Buyang Huanwu decoction

Ethnopharmacological relevanceBuyang Huanwu Decoction (BYHWD), a traditional Chinese medicine, is one of the classic prescriptions for the treatment of ischemic stroke in clinical practice. It has the effects of tonifying qi, activating blood circulation, and promoting meridian circulation. However, its chemical analysis has not been clarified, which greatly hinders its further clinical application. Therefore, it is necessary to clarify the chemical constituents and metabolites profile of BYHWD in vivo. Aim of the studyCharacterizing the chemical basis of BYHWD in vitro, and combing studies of related metabolism in vivo to screen out the potential active components of BYHWD with pharmacological effects in vivo. Materials and methodsTwelve male rats weighed 200 ± 20 each were selected for the experiments. According to the fragmentation of different structural types of components and diagnostic ions, UHPLC-Q-TOF-MS/MS was used to classify and clarify the unknown components of BYHWD and identify the material basis of BYHWD in vitro. Then, rat plasma, tissues, feces, and urine were collected for analysis. Based on the similarity of MS responses (accurate molecular weight and secondary fragmentation) and chromatographic behavior (retention time), the in vivo prototype and metabolites were analyzed. Through the phase I and phase II metabolism law, a metabolite library was established to analyze the prototype-matched metabolites. ResultsA total of 121 in vitro compounds and 55 in vivo prototypes of BYHWD were identified, corresponding to 123 matched prototypes. It was mainly composed of flavonoids, triterpene saponins, nucleosides and lactones both in vitro and in vivo. Quercetin, ligustilide, astragaloside IV, calycosin, paeoniflorin and ferulic acid were the main prototypes and metabolites in plasma and urine. ConclusionQuercetin, ligustilide, astragaloside IV, calycosin, paeoniflorin and ferulic acid were the main active ingredients of BYHWD.

Comorbidities confound metabolomics studies of human disease

The co-occurrence of multiple chronic conditions, termed multimorbidity, presents an expanding global health challenge, demanding effective diagnostics and treatment strategies. Chronic ailments such as obesity, diabetes, and cardiovascular diseases have been linked to metabolites interacting between the host and microbiota. In this study, we investigated the impact of co-existing conditions on risk estimations for 1375 plasma metabolites in 919 individuals from population-based Estonian Biobank cohort using liquid chromatography mass spectrometry (LC–MS) method. We leveraged annually linked national electronic health records (EHRs) data to delineate comorbidities in incident cases and controls for the 14 common chronic conditions. Among the 254 associations observed across 13 chronic conditions, we primarily identified disease-specific risk factors (92%, 217/235), with most predictors (93%, 219/235) found to be related to the gut microbiome upon cross-referencing recent literature data. Accounting for comorbidities led to a reduction of common metabolite predictors across various conditions. In conclusion, our study underscores the potential of utilizing biobank-linked retrospective and prospective EHRs for the disease-specific profiling of diverse multifactorial chronic conditions.

Integrating metabolomics and proteomics to identify novel drug targets for heart failure and atrial fibrillation

BackgroundAltered metabolism plays a role in the pathophysiology of cardiac diseases, such as atrial fibrillation (AF) and heart failure (HF). We aimed to identify novel plasma metabolites and proteins associating with cardiac disease.MethodsMendelian randomisation (MR) was used to assess the association of 174 metabolites measured in up to 86,507 participants with AF, HF, dilated cardiomyopathy (DCM), and non-ischemic cardiomyopathy (NICM). Subsequently, we sourced data on 1567 plasma proteins and performed cis MR to identify proteins affecting the identified metabolites as well as the cardiac diseases. Proteins were prioritised on cardiac expression and druggability, and mapped to biological pathways.ResultsWe identified 35 metabolites associating with cardiac disease. AF was affected by seventeen metabolites, HF by nineteen, DCM by four, and NCIM by taurine. HF was particularly enriched for phosphatidylcholines (p = 0.029) and DCM for acylcarnitines (p = 0.001). Metabolite involvement with AF was more uniform, spanning for example phosphatidylcholines, amino acids, and acylcarnitines. We identified 38 druggable proteins expressed in cardiac tissue, with a directionally concordant effect on metabolites and cardiac disease. We recapitulated known associations, for example between the drug target of digoxin (AT1B2), taurine and NICM risk. Additionally, we identified numerous novel findings, such as higher RET values associating with phosphatidylcholines and decreasing AF and HF. RET is targeted by drugs such as regorafenib which has known cardiotoxic side-effects. Pathway analysis implicated involvement of GDF15 signalling through RET, and ghrelin regulation of energy homeostasis in cardiac pathogenesis.ConclusionsThis study identified 35 plasma metabolites involved with cardiac diseases and linked these to 38 druggable proteins, providing actionable leads for drug development.

Effect of a Bacillus subtilis-based direct-fed microbial, on milk yield, milk components, feed intake and plasma hormones and metabolites in lactating Holstein cows

To investigate the effects of a Bacillus-based direct-fed microbial on milk production and related factors, a study was conducted on Holstein cows (n = 28) starting at 90 ± 11 DIM. The cows were divided into two dietary groups: a control group (CON) that received a total mixed ration (TMR), and a Bacillus-fed group (DFM) that received the same TMR along with a Bacillus subtilis product containing two strains (747 and 1781) in equal amounts. The study lasted for 25 wk and included both primiparous and multiparous cows. The cows were housed in a free-stall barn and were provided with ad libitum TMR, which was fed twice a day. Their daily meals and dry matter intake (DMI) were recorded during wk 1–4 and wk 19–25 using electronic feeders. Milk samples were collected weekly during morning and evening milkings and analyzed for milk fat, protein, lactose, and milk urea nitrogen (MUN). Blood samples were also collected weekly and analyzed for plasma glucose, insulin, cholesterol, insulin-like growth factor 1 (IGF1), and progesterone concentrations. Additionally, rumen fluid samples were collected and evaluated for various species of bacteria. One of the key findings was that daily 4 % fat-corrected milk production (FCM) was influenced by the interaction between treatment (DFM vs. CON) and parity (primiparous vs. multiparous), with multiparous DFM cows producing 11 % more FCM compared to CON. The DFM cows also had a higher milk fat percentage (4.41 % vs. 4.02 %) and MUN concentrations were 1.0 mg/dL higher in the DFM group. In terms of blood metabolites and hormones, multiparous DFM cows had lower plasma cholesterol, glucose, and insulin concentrations compared to CON multiparous cows. However, there were no significant differences between the groups in terms of plasma IGF1 concentrations, insulin-to-glucose ratios, and luteal phase plasma progesterone concentrations. The analysis of rumen fluid samples revealed that the abundance of Ruminococcus albus and Fibrobacter succinogenes group I was greater in the DFM cows compared to CON cows. Furthermore, during the periods when feed intake was measured, the DFM cows had a 9 % reduction in feed intake and a 14 % improvement in feed efficiency (FCM per DMI) compared to CON cows. In conclusion, the two-strain Bacillus product used in this study (Certillus) showed potential as an effective direct-fed microbial. It was found to increase feed efficiency and milk production by altering the composition of ruminal microbiota and metabolism in the cows.

Low blood S-methyl-5-thioadenosine is associated with postoperative delayed neurocognitive recovery

Elderly individuals display metabolite alterations that may contribute to development of cognitive impairment following surgery and anesthesia. However, these relationships remain largely unexplored. The study aims to assess the S-methyl-5-thioadenosine (MTA) is associated with postoperative delayed neurocognitive recovery (dNCR). We assess altered metabolites following anesthesia/surgery in both mice and patients to identify blood biomarkers of dNCR. Preoperative and postoperative plasma metabolites are determined by widely targeted metabolomics. The brains of mice with anesthesia/surgery show decreased MTA and activated MTA phosphorylase. Mice also show that preoperative administration of MTA can prevent inflammation and cognitive decline. In clinical patients, we detect lower preoperative serum MTA levels in those who developed dNCR. Both low preoperative and postoperative blood MTA levels are associated with increased risk of postoperative dNCR. These results suggest that anesthesia/surgery induces cognitive decline through methionine synthesis pathways and that MTA could be a perioperative predictor of dNCR.