Blood Metabolites Research Articles

Development of two ultra-sensitive UHPLC-QqQ-MS/MS methods for the simultaneous determination of hydroxyzine and its active metabolite (cetirizine) in human blood: applications to real cases of forensic toxicology.

Both postmortem toxicological and medical-forensic examinations are very important in the case of analyzing various types of chemical substances. Hydroxyzine (HZ) is a first-generation antihistamine drug with a sedative effect that disrupts cognitive function and affects the ability to drive motor vehicles. Enzymatic oxidation of the hydroxy-methyl group to the carboxyl group leads to the formation of its main metabolite-cetirizine (CZ). CZ is the active substance of antiallergic drugs. Because it does not cross the BBB (blood-brain barrier) easily, it is less likely to cause drowsiness or affect memory and impair cognitive function. Therefore, in criminal studies, it is often important what medication had been taken by a person involved, e.g., in a car accident, HZ or CZ. The analysis of both antihistamine drugs is challenging, as usually very low concentrations of the compound of interest need to be determined. Thus, an ultra-sensitive UHPLC-QqQ-MS/MS method was developed for simultaneous determination of HZ and CZ in biological fluid samples. The lower limit of quantification (LOQ) for HZ and CZ was calculated as 0.345 and 0.3696ng/mL, respectively. Together with a reduced sample volume to 200 μL, it makes the developed method suitable for a sensitive multidrug forensic toxicological analysis. Samples were extracted with simple and fast liquid-liquid extraction (ethyl acetate, pH 9). The present method for the determination of HZ and CZ in human blood proved to be simple, fast, selective, and sensitive. The quantification by LC-MS/MS was successfully applied to the samples coming from 28 authentic biological fluids (blood, urine, vitreous humor, bile and stomach content), both antemortem and postmortem. The performed studies confirm that the developed method is characterized by a high extraction efficiency. Its accuracy, reproducibility, simplicity, and selectivity suggest its application in clinical, toxicological, and forensic laboratories.

A stratified study of human blood metabolites and coronary artery diseases—A Mendelian randomization study

Background and aimsMetabolic dysregulation is closely associated with coronary artery diseases (CAD). Exploring the relationship between metabolites and CAD is helpful in identifying changes in energy metabolism during disease progression. Methods and resultsWe use Mendelian Randomization (MR) analysis to assess the relationships between 275 serum metabolites and CAD such as angina pectoris, post-myocardial infarction complications, coronary atherosclerosis, myocardial infarction (MI), and unstable angina pectoris (UA). The inverse variance-weighted method (IVW) served as the primary approach for causal analysis, with MR-Egger and weighted median (WM) as supplementary methods. Sensitivity analyses were conducted to assess heterogeneity and multiple effects. We also analyzed potentially related metabolic pathways.We identified causal relationships between 42 known metabolites and CAD. Among them, the genetic susceptibility to elevated levels of amino acid Isobutyrylcarnitine is associated with an increased risk of coronary artery atherosclerosis; but it provides protection against the development of MI. Genetic susceptibility to elevated levels of fatty acids Stearate, Caprylate is associated with higher risk of angina pectoris, while Threonate has a protective effect in the development of angina; Stearate is associated with an increased risk of UA, whereas higher levels of the lipids Choline, 1−arachidonoylglycerophosphoinositol∗, Hexadecanedioate, Tetradecanedioate play a protective role in UA.Metabolic pathway analysis identified 6 pathways that may be associated with CAD. ConclusionWe identified causal relationships between 42 serum metabolites and CAD. Specifically, changes in metabolites such as Isobutyrylcarnitine, Caprylate, and Stearate were associated with risks of CAD. These findings provide new insights into the metabolic mechanisms of CAD.

Development and validation of multiresidue analysis method for biomonitoring of pesticides and metabolites in human blood and urine by LC-QToF-MS

The widespread use of pesticides and their consequential presence in the environment is a growing concern due to the harmful health effects associated with pesticide exposure. For clinical and toxicology laboratories, a method for simultaneously determining these compounds and their metabolic products in body fluids, such as blood and urine, is important. In the present study, a rapid, sensitive and simultaneous LC-QToF-MS method for detecting multiclass pesticides and metabolites in blood and urine samples has been developed and validated. Four sample preparation procedures, protein precipitation and three different variants of QuEChERS-based extraction were evaluated to find a suitable, simple, and effective sample pretreatment technique. The final optimized sample preparation method (acetonitrile; 400 μl, MgSO4; 40 mg and NaCl; 10 mg) was validated for accuracy, precision, matrix effect, recovery, stability, carryover, and dilution integrity. Analyte recoveries ranged from 75.40 to 113.54 % while accuracy was evaluated in the range of 71.41–108.26 % and precision (%RSD) in the range of 0.01 %–16.85 %. The limit of quantification (LOQ) for all compounds was established in the range of 0.82–7.05 ng mL-1. The developed reliable, robust, and sensitive method was successfully applied for the quantification of target pesticides and metabolites in human blood and urine samples. Evaluated samples resulted in detection of eleven analytes (seven pesticides and four metabolites).

Buffer-free high pH mobile phase LC-MS/MS for determination of the alcohol biomarker phosphatidylethanol 16:0/18:1 and 20 drugs and metabolites in whole blood

BackgroundAcidic mobile phases are commonly used in reversed phase liquid chromatography tandem mass spectrometry (LC-MS/MS) bioanalysis. However, increased sensitivity, improved peak symmetry, and increased retention, especially for basic hydrophilic drugs have been observed using basic mobile phases. In our previous acidic mobile phase LC-MS/MS method we needed two injections (0.4 and 2.0 μL) of each sample for this task, which is inefficient. The aim of this study was to investigate if basic mobile phase LC-MS/MS could be used to determine phosphatidylethanol 16:0/18:1 and 20 other drugs and metabolites with satisfactory sensitivity in one single run. MethodsWhole blood was prepared by 96-well supported-liquid extraction using heptane/ethyl acetate/2-propanol (16:64:20, v:v:v). Chromatographic separation was achieved on an Acquity BEH C18 column (50 × 2.1 mm I.D.), using a mobile phase with 0.025 % ammonia, pH 10.7 (Solvent A) and methanol (Solvent B). All compounds had isotope-labelled internal standards. ResultsThe method was fully validated. Recovery was between 63 and 91 % for 20 compounds and 10 % for benzoylecgonine. Matrix effects were low, except for ion enhancement of buprenorphine and ion suppression for THC. However, internal standards compensated for these effects. Inter-assay precision and accuracy were < ± 20 % for all compounds at five tested concentrations, except for methamphetamine at the highest concentration. ConclusionAn LC-MS/MS method for simultaneous determination of PEth 16:0/18:1 and 20 drugs and metabolites in whole blood were for the first time developed and validated. Retention of PEth 16:0/18:1 was, in contrast to the other 20 compounds, largely affected by mobile phase buffer concentration. The buffer free basic mobile phase ensured that phosphatidylethanol 16:0/18:1 eluted before most of the unwanted phospholipids.

Rate of body weight gain during early gestation in F0 beef heifers has effects that extend multigenerationally to the F2 fetuses.

Our aim was to investigate the effects of maternal (F0) body weight (BW) gain during the first 84 d of gestation on body composition, ovarian reserve, and hormonal and metabolic parameters of breeding-age F1 heifers, as well as the body weight and morphometry of F2 fetuses. The study also evaluated the effect of maternal body weight gain (F0) on the mRNA relative abundance of the small intestine of both F1 heifers and F2 fetuses. Crossbred Angus heifers (F0; n = 100) were managed to gain 0.20kg/d (low gain [LG], n = 50) or 0.75kg/d (moderate gain [MG], n = 50) for the first 84 d of gestation. Subsequently, F0 dams were managed on a common forage-based diet for the rest of gestation until the weaning of the F1 offspring. At 15 months of age a subset of F1 heifers was randomly selected for the current experiment (n = 8 LG and n = 8 MG). Heifers were bred via artificial insemination (AI; d 0), then harvested on d 84 of gestation. On d -10, 42, and 84, BW was recorded, and blood was collected and analyzed for concentrations of glucose, non-esterified fatty acids, progesterone, insulin, and insulin-like growth factor-1. Weight of F1 carcasses, organs, gravid uteri, and F2 fetuses and organs were recorded at harvest. Visible follicles were counted on F1 ovaries at harvest, and histology was used to count microscopic follicles. Liver and jejunal samples from F1 heifers were collected to measure tissue oxygen consumption and jejunal samples from F1 heifers and F2 fetuses were collected for mRNA relative abundance analysis. Body weight of F1 heifers from MG dams tended to be 12kg greater (P = 0.06) than for F1 heifers from LG dams. Concentrations of glucose were greater (P = 0.03) in F1 heifers from the MG group, with no differences in other blood metabolites or follicular populations (P ≥ 0.16). Interestingly, mammary glands were heavier (P = 0.05) and placentas and body depth tended to be heavier and greater, respectively (P ≤ 0.10), for F2 fetuses from F0 LG heifers. Oxygen consumption in the liver and jejunum, as well as mRNA relative abundance in the jejunum of F1 heifers, were not affected by F0 rate of gain (P ≥ 0.16). However, the NDUFC1, SDHA, UQCR1, and PPARG genes were upregulated (P ≤ 0.05) in the jejunum of F2 fetuses from the LG group. In conclusion, BW gain of F0 heifers during early gestation exerts subtle effects on pre-breeding BW and blood metabolites in F1 offspring, with impacts present in F2 placenta, mammary gland, and intestine.

Parkinson's disease is characterized by vitamin B6-dependent inflammatory kynurenine pathway dysfunction.

Parkinson's disease (PD) is a complex multisystem disorder clinically characterized by motor, non-motor, and premotor manifestations. Pathologically, PD involves neuronal loss in the substantia nigra, striatal dopamine deficiency, and accumulation of intracellular inclusions containing aggregates of α-synuclein. Recent studies demonstrate that PD is associated with dysregulated metabolic flux through the kynurenine pathway (KP), in which tryptophan is converted to kynurenine (KYN), and KYN is subsequently metabolized to neuroactive compounds quinolinic acid (QA) and kynurenic acid (KA). This multicenter study used highly sensitive liquid chromatography-tandem mass-spectrometry to compare blood and cerebral spinal fluid (CSF) KP metabolites between 158 unimpaired older adults and 177 participants with PD. Results indicate that increased neuroexcitatory QA/KA ratio in both plasma and CSF of PD participants associated with peripheral and cerebral inflammation and vitamin B6 deficiency. Furthermore, increased QA tracked with CSF tau and severity of both motor and non-motor PD clinical dysfunction. Importantly, plasma and CSF kynurenine metabolites classified PD participants with a high degree of accuracy (AUC = 0.897). Finally, analysis of metabolite data revealed subgroups with distinct KP profiles, and these were subsequently found to display distinct PD clinical features. Together, these data further support the hypothesis that the KP serves as a site of brain and periphery crosstalk, integrating B-vitamin status, inflammation and metabolism to ultimately influence PD clinical manifestation.

Causality of genetically determined serum metabolites on lower back pain or/and sciatica: a comprehensive Mendelian randomized study.

There is an urgent need to confirm biomarkers reflecting the pathogenesis and targeted drugs of lower back pain or/and sciatica in clinical practice. This study aimed to conduct a two sample bidirectional Mendelian randomization (MR) analysis to explore the causal link between 486 serum metabolites and lower back pain or/and sciatica. All data come from two public shared databases of European ancestry and single nucleotide polymorphisms (SNPs) for lower back pain or/and sciatica acted as instrumental variables. The traditional inverse variance weighting (IVW) method, weighted-median method, MR-Egger methodand other methods were used to estimate causality. The horizontal pleiotropy, heterogeneities were also verified through the MR-Egger intercept test, Cochran's Q test, MR-PRESSO test and the leave-one-out sensitivity analysis. Reverse MR analysis was employed to evaluate the direct impact of metabolites on lower back pain or/and sciatica. Additionally, we conducted the colocalization analysis to reflect the causality deeply. Furthermore, metabolic pathway analysis was performed. 28 metabolites (18 known metabolites, 1 identified metabolites and 9 unknown metabolites) relevant to the risk of sciatica or/and lower back pain after using genetic variants as probes at PIVW < 0.05 were identifed. Among them, 8 serum metabolites decreased risk of sciatica or/and lower back pain significantly (P < 0.05), and 14 serum metabolites increased risk of sciatica or/and lower back pain significantly (P < 0.05). No reverse causal association was found between 28 metabolites and sciatica or/and lower back pain. Colocalization analysis results showed that the associations between sciatica or/and lower back pain and the 28 identified metabolites were not due to shared causal variant sites. Moreover, pathway enrichment analysis identifed 11 signifcant metabolic pathways, which are mainly involved in the pathological mechanism of sciatica or/and lower back pain (P < 0.05). There was no horizontal pleiotropy or heterogeneity in the other analyses. Our analyses provided robust evidence of causal associations between blood metabolites on sciatica or/and lower back pain. However, the underlying mechanisms remain to be further investigated.

Effects of chickpea grain feeding on the growth and carcass features of growing lambs.

An investigation was conducted to find out how diet formulation of chickpea grains (CHPE) rather than soybean meal and barely grain affected the performance, blood metabolites, carcass, and meat quality features of Awassi lambs. Thirty lambs, with an average age of 73 ± 0.85 days and an initial body weight of 21.0 ± 1.29kg, were randomly assigned into one of three diets, with 10 lambs per treatment diet. The diets were designed to replace a portion of the barley grain and soybean meal and included no CHPE (CON), 7.5% CHPE (CHPE7.5), and 15% CHPE (CHPE15). Lambs were individually housed, fed every day, and weighed every two weeks to measure performance characteristics over the 60-day study period. Four lambs per treatment were chosen at random on day 42 to participate in an N balance study and assess diet digestibility. All lambs were slaughtered at the termination of the trial period to measure the features of the carcass characteristics and meat quality. As the amount of CHPE included in the diets increased, the cost of diets reduced. As the amount of CHPE in the diets increased, so did the intake of ether extract (EE). The CON group's cost per kilogram of increase was higher (P = 0.017) than that of the CHPE7.5 and CHEP15 groups. The digestibility of EE was higher (P = 0.024) in the CHPE15 diet as opposed to the CHPE7.5 and CON diets. The various treatments did not impact blood metabolites, carcass features, or meat quality. Therefore, the present study suggested that chickpeas might be added to the diets of finishing lambs up to 15% of dry matter.

Regulatory effects of vitamin E nano-emulsion on blood metabolites, immunological variables, testicular architecture, and sperm ultrastructure of heat-stressed V-line rabbit bucks

The study investigated the beneficial effects of vitamin E-loaded nano-emulsion (NEVE) on hemato-biochemical changes, oxidative stress, inflammatory responses, immunological variables, and semen quality in heat-stressed rabbit bucks. Forty adult V-line rabbit bucks were randomly assigned to four groups and fed diets containing NEVE at 0 (NEVE0), 50 (NEVE50), 100 (NEVE100), and 200 (NEVE200) mg/kg for 12 weeks. The NEVE had a mean particle diameter of 32.6 nm, a polydispersity index of 0.6, and a zeta potential of −31.1 mV. The dietary NEVE significantly improved the hematological, blood protein, lipid profile, and liver functions of rabbit bucks (p < 0.05). The NEVE200 treated group showed higher levels of nitric oxide, TAC, and SOD in blood serum and seminal plasma compared to the control group (p < 0.05). Meanwhile, levels of MDA, IL-4, and TNF-α were significantly shrunken in response to the dietary treatment (p < 0.0001), while the IgA and IgG were improved in the NEVE100 and NEVE200 groups. The NEVE200 exhibited higher progressive motility, ejaculate volume, viability, and better libido (lower reaction time) than the untreated group (p < 0.05). TEM images illustrated that NEVE200 exhibited higher sperm cells with a normal structure, intact plasma membranes, and acrosomes than the other groups. Moreover, testicular architecture was improved with NEVE supplementation. Overall, the dietary addition of NEVE at 100 or 200 mg/kg could be an effective strategy to improve the health and semen quality of rabbit bucks during hot climates.

Stool and blood metabolomics in the metabolic syndrome: a cross-sectional study

Introduction/objectivesChanges in the stool metabolome have been poorly studied in the metabolic syndrome (MetS). Moreover, few studies have explored the relationship of stool metabolites with circulating metabolites. Here, we investigated the associations between stool and blood metabolites, the MetS and systemic inflammation.MethodsWe analyzed data from 1,370 participants of the KORA FF4 study (Germany). Metabolites were measured by Metabolon, Inc. (untargeted) in stool, and using the AbsoluteIDQ® p180 kit (targeted) in blood. Multiple linear regression models, adjusted for dietary pattern, age, sex, physical activity, smoking status and alcohol intake, were used to estimate the associations of metabolites with the MetS, its components and high-sensitivity C-reactive protein (hsCRP) levels. Partial correlation and Multi-Omics Factor Analysis (MOFA) were used to investigate the relationship between stool and blood metabolites.ResultsThe MetS was significantly associated with 170 stool and 82 blood metabolites. The MetS components with the highest number of associations were triglyceride levels (stool) and HDL levels (blood). Additionally, 107 and 27 MetS-associated metabolites (in stool and blood, respectively) showed significant associations with hsCRP levels. We found low partial correlation coefficients between stool and blood metabolites. MOFA did not detect shared variation across the two datasets.ConclusionsThe MetS, particularly dyslipidemia, is associated with multiple stool and blood metabolites that are also associated with systemic inflammation. Further studies are necessary to validate our findings and to characterize metabolic alterations in the MetS. Although our analyses point to weak correlations between stool and blood metabolites, additional studies using integrative approaches are warranted.

Causal association between blood metabolites and vertigo: A Mendelian randomization study.

Metabolic disorders have been identified as an important factor causing nervous system diseases. However, due to the interference of confounding factors, the causal relationship between them has not been clearly elucidated, so it is necessary to study the causal relationship between them. To explore the causal relationship between blood metabolites and vertigo by Mendelian randomization. To assess causality, the inverse variance weighting method was employed as the primary analytical approach, complemented by additional sensitivity analyses. Metabolic pathway enrichment analysis and genetic correlation analysis were employed to further assess the metabolites. All statistical analyses were conducted using the R software. The study employed metabolite Genome Wide Association Study and vertigo diseases summary data sets to examine the causal relationship between 486 blood metabolites and 3 types of vertigo. A total of 55 potential metabolites associated with the 3 types of vertigo were identified, with 22, 16, and 13 candidate metabolites showing relatively reliable MR Evidence for Vestibular Dysfunction, Peripheral Vertigo, and Central Vertigo, respectively. Enrichment analysis was conducted to investigate the biological significance of these candidate metabolites, resulting in the identification of 7 key metabolic pathways across the 3 diseases, the metabolic pathway known as "Valine, leucine, and isoleucine biosynthesis" was found to be associated with all 3 types of vertigo, suggesting its potential influence on the vestibular system. Genetic correlation analysis revealed a genetic correlation between X-10510 and dodecanedioate with Vestibular Dysfunction. This study offers novel perspectives on the causal impact of blood metabolites on vertigo through the integration of genomics and metabolomics. Identifying metabolites that contribute to vertigo could serve as potential biomarkers and contribute to a better understanding of the underlying biological mechanisms associated with vertigo.

Comparative Analysis of the Potential Adaptability of Tibetan Dzo and Yellow Cattle Based on Blood Indices, Metabolites, and Fecal Microbiota.

This study aimed to investigate the differences in environmental adaptability between dzo and Tibetan yellow cattle by using corresponding assay kits to analyze blood indices, utilizing mass spectrometry for blood metabolite profiling, and performing 16S rDNA sequencing of fecal microbiota. Forty female cattle were randomly divided into a dzomo (female dzo) group (MG, n = 20) and a Tibetan-yellow-cattle group (HG, n = 20). After 150 days of uniform feeding, six cattle from each group were randomly picked for jugular blood sampling and collection of fecal microorganisms. The results showed that the serum albumin, creatinine, total protein, superoxide dismutase, IgG, and IgM concentrations in the MG group were higher (p < 0.05), whereas the serum triglyceride concentration was lower, compared to the HG group (p < 0.05). The higher level of phospholipids containing long-chain polyunsaturated fatty acids (PUFAs) (PC (18:5e/2:0), PC (20:5e/2:0), LPC 18:2, LPC 20:5) observed in the serum of the dzo suggests that they have an advantage in adapting to the challenging conditions of the plateau environment. The fecal microbiota analysis showed that Akkermansia was significantly enriched in the MG group; this might be the key bacterial genus leading to the strong adaptability of dzo. Our findings indicated the dzo's superior adaptation to the Tibetan Plateau's harsh environment.

Genetically predicted blood metabolites mediate relationships between gut microbiota and ovarian cancer: a Mendelian randomization study.

While there is evidence that gut microbiota (GM) and blood metabolites are associated with ovarian cancer (OC), the precise mechanisms underlying this relationship are still unclear. This study used Mendelian randomization (MR) to elucidate the causal connections between GM, blood metabolite biomarkers, and OC. In this study, we leveraged summary data for GM (5,959 individuals with genotype-matched GM), blood metabolites (233 circulating metabolic traits with 136,016 participants), and OC (63,702 participants with 23,564 cases and 40,138 controls) from genome-wide association studies (GWASs). We performed MR analysis to explore the causal relationship between GM and OC. Further, we harnessed univariable MR (UVMR) analysis to evaluate the causal associations between GM and circulating metabolites. Finally, we employed a two-step approach based on multivariable MR (MVMR) to evaluate the total genetic prediction effect of metabolites mediating the GM on the risk of OC to discover a potential causal relationship. In the MR analysis, 24 gut bacteria were causally associated with the pathogenesis of OC, including 10 gut bacteria (Dorea phocaeense, Succinivibrionaceae, Raoultella, Phascolarctobacterium sp003150755, Paenibacillus J, NK4A144, K10, UCG-010 sp003150215, Pseudomonas aeruginosa, and Planococcaceae) that were risk factors, and 14 gut bacteria (CAG-177 sp002438685, GCA-900066135 sp900066135, Enorma massiliensis, Odoribacter laneus, Ruminococcus E sp003521625, Streptococcus sanguinis, Turicibacter sp001543345, Bacillus velezensis, CAG-977, CyanobacteriaStaphylococcus A fleurettii, Caloranaerobacteraceae, RUG472 sp900319345, and CAG-269 sp001915995) that were protective factors. The UVMR analysis showed that these 24 positive gut bacteria were causally related to lipoproteins, lipids, and amino acids. According to the MVMR analysis, Enorma massiliensis could reduce the risk of OC by raising the total cholesterol to total lipids ratio in large low-density lipoprotein (LDL) and cholesteryl esters to total lipids ratio in intermediate-density lipoprotein (IDL). Turicibacter sp001543345, however, could reduce the risk of OC by lowering free cholesterol in small high-density lipoprotein (HDL) and increasing the ratios of saturated fatty acids to total fatty acids, total cholesterol to total lipids ratio in very small very-low-density lipoprotein (VLDL), and cholesteryl esters to total lipids ratio in very small VLDL. The current MR study provides evidence that genetically predicted blood metabolites can mediate relationships between GM and OC.

Associations between human blood metabolome and vascular dementia

BackgroundEffective and specific biomarkers are warranted for the management of vascular dementia. We aimed to systematically screen the human blood metabolome to identify potential mediators of vascular dementia via a two-sample Mendelian randomization (MR) design. MethodsWe selected 93 unique blood metabolites from 3 metabolome genome-wide association studies (GWASs) with a total of 147,827 participants of European ancestry. Summary statistics for vascular dementia originated from a European-descent GWAS dataset released by the FinnGen Study, involving 859 cases and 211,300 controls. We applied the inverse-variance weighted MR method in the main analysis to examine the causal roles of blood metabolites in vascular dementia, followed by several sensitivity analyses for robustness validation. ResultsGenetically determined glycoproteins (OR per 1-SD increase, 0.75; 95 % CI, 0.68–0.83, P = 1.08 × 10−8) and O-methylascorbate (OR per 1-SD increase, 0.08; 95 % CI, 0.02–0.32; P = 3.74 × 10−4) levels had negative associations with the risk of vascular dementia, whereas genetically determined total cholesterol (OR per 1-SD increase, 1.77; 95 % CI, 1.32–2.38; P = 1.39 × 10−4) and low-density lipoprotein (LDL) cholesterol (OR per 1-SD increase, 1.94; 95 % CI, 1.48–2.55; P = 1.61 × 10−6) levels had positive associations with the risk of vascular dementia. MR-Egger regression suggested no directional pleiotropy for the identified associations, and sensitivity analyses with different MR models further confirmed these findings. ConclusionGlycoproteins, O-methylascorbate, total cholesterol, and LDL cholesterol might be promising blood markers of vascular dementia, which may provide novel insights into the prevention of vascular dementia. Further studies are warranted to replicate our findings and elucidate the potential mechanistic pathways.

Metabolic and Reproductive Parameters in Young Female Rats Subjected to Feed Restriction and/or Ginger Oil Administration

Background It is well known that the medicinal plant ginger (Zingiber officinale) has anti-oxidative properties that shield tissues and organs against oxidative damage. Aims Forty-eight, 9-week-old Sprague Dawley female rats (159±13 g) were used to evaluate the effects of feed restriction and/or ginger oil supplementation on growth, reproductive parameters, and blood metabolites. Methods Animals were randomly divided into 4 treatment groups (12 rats/treatment) in 2 × 2 factorial arrangements: ad libitum feed (CON), 25% feed restriction (G2), ad libitum feeding with 0.2 mL/rat ginger oil (G3), and 25% feed restriction plus 0.2 mL/rat ginger oil (G4). Animals in groups G2 and G4 received 75% of their pre-treatment feed intake (25% restriction). Six rats from each group were sacrificed at the end of treatments for blood and tissue collection, while the remaining rats were mated with mature males. Results No ginger-by-feed restriction interactions were detected in any of the tested parameters. Body size and BW increased as the experiment advanced (P &lt; 0.01). However, G2 had the lowest BW towards the end of the treatment. Glucose was greater (P &lt; 0.05) in feed-restricted animals, while urea nitrogen was greater in animals on ad libitum feeding. Combined ovarian weights and reproductive tract weights were greater in ginger-supplemented than non-supplemented animals. Similarly, rats on ad libitum feeding had greater ovarian weights than those on restricted feeding. Conclusion Ginger oil supplementation appears to have favorable effects on reproductive tract development and ovarian weight regardless of feed restriction.

Discovery of Hypoxanthine and Inosine as Robust Biomarkers for Predicting the Preanalytical Quality of Human Plasma and Serum for Metabolomics.

In cold human blood, the anomalous dynamics of adenosine triphosphate (ATP) result in the progressive accumulation of adenosine diphosphate (ADP), adenosine monophosphate (AMP), inosine monophosphate (IMP), inosine, and hypoxanthine. While the ATP, ADP, AMP, and IMP are confined to red blood cells (RBCs), inosine and hypoxanthine are excreted into plasma/serum. The plasma/serum levels of inosine and hypoxanthine depend on the temperature of blood and the plasma/serum contact time with the RBCs, and hence they represent robust biomarkers for evaluating the preanalytical quality of plasma/serum. These biomarkers are highly specific since they are generally absent or at very low levels in fresh plasma/serum and are highly sensitive since they are derived from ATP, one of the most abundant metabolites in blood. Further, whether blood was kept at room temperature or on ice could be predicted based on inosine levels. An analysis of >2000 plasma/serum samples processed for metabolomics-centric analyses showed alarmingly high levels of inosine and hypoxanthine. The results highlight the gravity of sample quality challenges with high risk of grossly inaccurate measurements and incorrect study outcomes. The discovery of these robust biomarkers provides new ways to address the longstanding and underappreciated preanalytical sample quality challenges in the blood metabolomics field.

Implementation of Machine Learning-Based System for Early Diagnosis of Feline Mammary Carcinomas through Blood Metabolite Profiling.

Background: Feline mammary carcinoma (FMC) is a prevalent and fatal carcinoma that predominantly affects unspayed female cats. FMC is the third most common carcinoma in cats but is still underrepresented in research. Current diagnosis methods include physical examinations, imaging tests, and fine-needle aspiration. The diagnosis through these methods is sometimes delayed and unreliable, leading to increased chances of mortality. Objectives: The objective of this study was to identify the biomarkers, including blood metabolites and genes, related to feline mammary carcinoma, study their relationships, and develop a machine learning (ML) model for the early diagnosis of the disease. Methods: We analyzed the blood metabolites of felines with mammary carcinoma using the pathway analysis feature in MetaboAnalyst software, v. 5.0. We utilized machine-learning (ML) methods to recognize FMC using the blood metabolites of sick patients. Results: The metabolic pathways that were elucidated to be associated with this disease include alanine, aspartate and glutamate metabolism, Glutamine and glutamate metabolism, Arginine biosynthesis, and Glycerophospholipid metabolism. Furthermore, we also elucidated several genes that play a significant role in the development of FMC, such as ERBB2, PDGFA, EGFR, FLT4, ERBB3, FIGF, PDGFC, PDGFB through STRINGdb, a database of known and predicted protein-protein interactions, and MetaboAnalyst 5.0. The best-performing ML model was able to predict metabolite class with an accuracy of 85.11%. Conclusion: Our findings demonstrate that the identification of the biomarkers associated with FMC and the affected metabolic pathways can aid in the early diagnosis of feline mammary carcinoma.

Blood metabolites, neurocognition and psychiatric disorders: a Mendelian randomization analysis to investigate causal pathways

BackgroundNeurocognitive dysfunction is observationally associated with the risk of psychiatric disorders. Blood metabolites, which are readily accessible, may become highly promising biomarkers for brain disorders. However, the causal role of blood metabolites in neurocognitive function, and the biological pathways underlying their association with psychiatric disorders remain unclear.MethodsTo explore their putative causalities, we conducted bidirectional two-sample Mendelian randomization (MR) using genetic variants associated with 317 human blood metabolites (nmax = 215,551), g-Factor (an integrated index of multiple neurocognitive tests with nmax = 332,050), and 10 different psychiatric disorders (n = 9,725 to 807,553) from the large-scale genome-wide association studies of European ancestry. Mediation analysis was used to assess the potential causal pathway among the candidate metabolite, neurocognitive trait and corresponding psychiatric disorder.ResultsMR evidence indicated that genetically predicted acetylornithine was positively associated with g-Factor (0.035 standard deviation units increase in g-Factor per one standard deviation increase in acetylornithine level; 95% confidence interval, 0.021 to 0.049; P = 1.15 × 10−6). Genetically predicted butyrylcarnitine was negatively associated with g-Factor (0.028 standard deviation units decrease in g-Factor per one standard deviation increase in genetically proxied butyrylcarnitine; 95% confidence interval, −0.041 to −0.015; P = 1.31 × 10−5). There was no evidence of associations between genetically proxied g-Factor and metabolites. Furthermore, the mediation analysis via two-step MR revealed that the causal pathway from acetylornithine to bipolar disorder was partly mediated by g-Factor, with a mediated proportion of 37.1%. Besides, g-Factor mediated the causal pathway from butyrylcarnitine to schizophrenia, with a mediated proportion of 37.5%. Other neurocognitive traits from different sources provided consistent findings.ConclusionOur results provide genetic evidence that acetylornithine protects against bipolar disorder through neurocognitive abilities, while butyrylcarnitine has an adverse effect on schizophrenia through neurocognition. These findings may provide insight into interventions at the metabolic level for risk of neurocognitive and related disorders.

3-epi-18β-Glycyrrhetinic Acid or Its Glucuronide, the Metabolites of Glycyrrhizinic Acid with Individual Differences, Correlated with Diagnostic Marker for Licorice-Induced Pseudoaldosteronism in Humans.

Licorice is a crude drug that is used in traditional Japanese Kampo medicine and is also used as a sweetener. Occasionally, it causes pseudoaldosteronism (PsA) as a side effect. The major symptoms include hypokalemia, hypertension, edema, and low plasma aldosterone levels. PsA might be caused by the metabolites of glycyrrhizinic acid (GL), a component of licorice. The development of PsA markedly varies among individuals; however, the factors that cause these individual differences remain unknown. In this study, 78 patients who consumed Kampo medicines containing licorice were enrolled, and their laboratory data, including serum potassium levels, plasma aldosterone concentrations (PAC), and the concentrations of GL metabolites in the residual blood and/or urine samples were evaluated. Of the 78 participants, 18β-glycyrrhetinic acid (GA), 3-epi-GA, 3-oxo-GA, 18β-glycyrrhetinyl-30-O-glucuronide (GA30G), and 3-epi-GA30G were detected in the serum samples of 65, 47, 63, 62, and three participants, respectively. Of the 29 urine samples collected, GA30G and 3-epi-GA30G were detected in 27 and 19 samples. 3-epi-GA30G is a newly found GL metabolite. Moreover, 3-epi-GA, 3-oxo-GA, and 3-epi-GA30G were identified in human samples for the first time. High individual differences were found in the appearances of 3-epi-GA in serum and 3-epi-GA30G in urine, and the concentrations of these metabolites were correlated with serum PsA markers. The inhibitory titers of 3-epi-GA, 3-oxo-GA, GA30G, and 3-epi-GA30G on human 11β-hydroxysteroid dehydrogenase type 2 were almost similar. These findings suggest that 3-epi-GA and/or 3-epi-GA30G are associated with individual differences in the development of PsA. SIGNIFICANCE STATEMENT: In this study, we detected 3-epi-18β-glycyrrhetinic acid (3-epi-GA) in human serum for the first time. We also identified 3-epi-18β-glycyrrhetinyl-30-O-glucuronide (3-epi-GA30G) as a novel glycyrrhizinic acid (GL) metabolite in human urine. These GL metabolite levels showed correlations with markers of PsA. Additionally, there are individual differences in whether they appear in the serum/urine. In conclusion, 3-epi-GA/3-epi-GA30G correlates with individual differences in the development of PsA.

Effects of Supplementing Different Quantities of Moringa stenopetala Leaves on Plasma Metabolite and Acylcarnitine Profile, Body Condition Score and Milk Yield Performance in Zebu (Bos indicus) Cattle.

The formulation of multi-nutrient blocks based on low-cost and locally available browse feed resources can be a valid feeding strategy in Sub-Saharan Africa, where inadequate feed supply, both in quality and quantity, is a major constraint. We evaluated the four different inclusion percentages (M-0%, M-25%, M-35% and M-45%) of Moringa stenopetala leaf powder to multi-nutrient blocks on their change on blood metabolite of dairy cows under practical, ranging conditions. Multi-nutrient blocks with four inclusion rates of M. stenopetala leaves were applied as complementary feed for free ranging dairy cows. The study was performed on 24 free ranging dairy cows reared around Arba Minch town in the Southern Ethiopian Rift Valley. Blood samples were collected from the jugular vein of dairy cows both before and after supplementation. Plasma glucose, beta hydroxy butyrate (BHB), urea, creatinine, triglycerides and nonesterified fatty acids (NEFA) concentration was quantified spectrophotometrically. Dried serum spots were subject to quantitative electrospray tandem mass spectrometry to estimate changes in nutrient metabolism based on selected carnitines. Based on these measurements, the milk yield and body condition score were increased during the period of multi-nutrient block supplementation. During the supplementation period, the cows got higher plasma glucose, triglyceride and urea concentrations and lower concentrations of BHB, NEFA and creatinine. From the metabolite profiles, a more efficient nutrient use could be concluded. Although no clear dose-response relationship was observed, the highest inclusion of the M. stenopetala leaves in the multi-nutrient blocks gave the best performance. This outcome supports the idea of implementing M. stenopetala based multi-nutrient blocks on tropical smallholder farms that are not easily accessible to conventional extension services.