Blood Metabolites Research Articles

Blood metabolomic profile in patients with type 2 diabetes mellitus with diabetic peripheral neuropathic pain.

This study aimed to identify metabolic markers for diabetic peripheral neuropathic pain (DPNP) in patients with type 2 diabetes mellitus (T2DM). Blood metabolite levels in the amino acid, biogenic amine, sphingomyelin, phosphatidylcholine (PC), carnitines, and hexose classes were analyzed in nondiabetic control (n = 27), T2DM without DPNP (n = 58), and T2DM with DPNP (n = 29) using liquid chromatography tandem mass spectrometry. Variable importance projection (VIP) evaluation by partial least squares discriminant analysis was performed on clinical parameters and metabolites. Sixteen variables with VIP > 1.0 (P < 0.05) were identified across all patient groups, and 5 variables were identified to discriminate between the two T2DM groups. DPNP patients showed elevated fasting blood glucose, glutamate, PC aa C36:1, lysoPC a C18:1, and lysoPC a C18:2, while low-density lipoprotein cholesterol, phenylalanine, and tryptophan were reduced. Glutamate, lysoPC a C18:1, and lysoPC a C18:2 discriminated T2DM with DPNP from those without DPNP with an AUC of 0.671. The AUC was improved to 0.765 when ratios of metabolite pairs were considered. Blood metabolites include glutamate, and phospholipid-related metabolites implicated in neuropathic pain may have the potential as biomarkers for DPNP. Further investigation is required to understand the mechanism of action of these altered metabolites in DPNP.

Causal links of human serum metabolites on the risk of prostate cancer: insights from genome-wide Mendelian randomization, single-cell RNA sequencing, and metabolic pathway analysis

BackgroundRecently, serum metabolites have shown potential in predicting survival outcomes and may be related to the pathogenesis of prostate cancer. Nevertheless, the precise impact concerning the genetic effect of metabolites on prostate cancer risk remains obscure. In this context, we conducted a Mendelian randomization (MR) study aiming to explore the causality between genetically determined metabolites and the risk of prostate cancer.MethodsWe conducted a two-sample MR analysis aiming to identify the underlying metabolites associated with prostate cancer. Exposure information was obtained from the largest metabolome-based genome-wide association (GWAS) data containing 7,824 Europeans. Genome-wide association analysis was utilized to detect instrumental variables (IVs) for metabolites. We applied the inverse-variance weighted (IVW) approach as the primary method, and to augment the reliability and robustness of our findings, additional analysis methods encompassing weighted median, MR-Egger, and leave-one-out analysis were utilized. MR-Egger intercept test was implemented to explore the pleiotropy. Cochran’s Q test was utilized to quantify the degree of heterogeneity. Additionally, we performed metabolic pathway analysis and single-cell RNA sequencing analysis.ResultsWe found that three serum metabolites were causally associated with prostate cancer after utilizing rigorous screening standards. Utilizing single nucleotide polymorphisms as IVs, a 1-SD increase in fructose was associated with 77% higher risk of prostate cancer (OR:1.77, 95%CI: 1.05-2.97, PIVW=0.031), a 1-SD increase in N1-methyl-3-pyridone-4-carboxamide was associated with 29% higher risk of prostate cancer (OR:1.29, 95%CI: 1.05-1.58, PIVW=0.017), and a 1-SD increase in 12-hydroxyeicosatetraenoate (12-HETE) was associated with 18% higher risk of prostate cancer (OR:1.18, 95%CI: 1.07-1.31, PIVW=0.0008). Metabolites that were causally linked to the risk of prostate cancer were mainly enriched in the valine, leucine and isoleucine biosynthesis pathway (P=0.026) and the nicotinate and nicotinamide metabolism pathway (P=0.048).ConclusionsOur MR analysis provided suggestive evidence supporting the causal relationships between three identified serum metabolites and prostate cancer, necessitating further investigation to elucidate the underlying mechanisms through which these blood metabolites and metabolic pathways may impact the initiation and progression of prostate cancer.

Genetic architecture of cerebrospinal fluid and brain metabolite levels and the genetic colocalization of metabolites with human traits.

Brain metabolism perturbation can contribute to traits and diseases. We conducted a genome-wide association study for cerebrospinal fluid (CSF) and brain metabolite levels, identifying 205 independent associations (47.3% new signals, containing 11 new loci) for 139 CSF metabolites, and 32 independent associations (43.8% new signals, containing 4 new loci) for 31 brain metabolites. Of these, 96.9% (CSF) and 71.4% (brain) of the new signals belonged to previously analyzed metabolites in blood or urine. We integrated the metabolite quantitative trait loci (MQTLs) with 23 neurological, psychiatric and common human traits and diseases through colocalization to identify metabolites and biological processes implicated in these phenotypes. Combining CSF and brain, we identified 71 metabolite-trait associations, such as glycerophosphocholines with Alzheimer's disease, O-sulfo-L-tyrosine with Parkinson's disease, glycine, xanthine with waist-to-hip ratio and ergothioneine with inflammatory bowel disease. Our study expanded the knowledge of MQTLs in the central nervous system, providing insights into human traits.

Ketamine attenuates kidney damage and depression-like behaviors in mice with cisplatin-induced acute kidney injury

Acute kidney injury (AKI) is a serious condition characterized by decreased urine output, often accompanied by psychiatric symptoms like depression. However, there are limited pharmacological treatments available for AKI and its associated depressive symptoms. In this study, we investigated whether cisplatin-induced AKI in mice leads to depression-like behaviors and whether ketamine could alleviate both the kidney injury and these behaviors. Mice with cisplatin-induced AKI exhibited elevated levels of creatinine and urea, kidney damage, increased kidney injury molecule-1 protein, and pathological changes in the liver, colon, and spleen. They also showed depression-like behaviors and reduced expression of synaptic proteins in the prefrontal cortex. Remarkably, a single dose of ketamine significantly reduced these symptoms and pathological changes. Interestingly, the beneficial effects of ketamine on the kidneys, other organs, and depression-like behaviors, were reversed by the tropomyosin receptor kinase B (TrkB) inhibitor ANA-12. Western blot analysis revealed the involvement of the TrkB and ERK (extracellular signal-regulated kinase)-CREB (cAMP response element binding protein) signaling pathway. Additionally, metabolomics analysis indicated that blood metabolites, such as C16-ceramide, may contribute to the effects of ketamine in this model. These findings suggest that cisplatin-induced nephrotoxicity in AKI mice contributes to depression-like behaviors, and ketamine can alleviate both kidney damage and depression-like symptoms by modulating the TrkB and ERK-CREB signaling pathways, as well as altering blood metabolites. However, the role of the kidney-brain axis in these depression-like behaviors remains unclear. Furthermore, ketamine may have therapeutic potential for treating kidney diseases such as AKI, along with associated depressive symptoms.

Effect of L-Carnitine Level on the Risk of Neuromyelitis Optica Spectrum Disorders: A Two-Sample Mendelian Randomization Study.

Previous research has often focused on studying the CNS damage in neuromyelitis optica spectrum disorders (NMOSD), while the role of the peripheral blood in the development of NMOSD is also of significant importance. The relationship between metabolites in blood and cerebrospinal fluid (CSF) with neuroimmune is receiving increasing attention. L-carnitine, whose astrocytic accumulation is associated with neuroinflammation and demyelination, may participate in the pathogenesis of NMOSD. However, whether circulating L-carnitine level has a causal effect on NMOSD risk needs elucidation. With large data sets now available, we used two-sample Mendelian randomization (MR) to determine whether circulating L-carnitine level is causally associated with the risk of NMOSD. Genetic variants associated with circulating L-carnitine levels were derived from a genome-wide association study (GWAS) of 7797 individuals from TwinsUK and KORA F4 cohorts. NMOSD summary statistics, including 215 cases and 1244 controls, were obtained from a separate GWAS. Subgroup analyses included aquaporin-4 (AQP4)-IgG-seropositive NMOSD (132 cases) and AQP4-IgG-seronegative NMOSD (83 cases). We used two-sample MR to explore associations between circulating L-carnitine levels and NMOSD risk, as well as its seropositive and seronegative subtypes. 16 SNPs (single nucleotide polymorphisms) were significantly associated with circulating L-carnitine level (P < 5 × 10-8), all of which were independent and available in the NMOSD dataset, after 1 SNP removed for being palindromic with intermediate allele frequencies in harmonization. Finally, a high circulating L-carnitine level conferred a protective effect against combined NMOSD (OR = 2.216 × 10-4, 95% confidence interval [CI] = 2.335 × 10-7-2.104 × 10-1, P = 0.0161) as well as AQP4-IgG-seronegative NMOSD (OR = 7.678 × 10-7, 95% CI = 2.233 × 10-11-2.640 × 10-2, P = 0.0082). There is no causal effect on AQP4-IgG-seropositive NMOSD risk (OR = 5.471 × 10-3, CI = 1.090 × 10-6-27.465, P = 0.2798) by circulating L-carnitine. Results remained positive and robust after the horizontal pleiotropy test, heterogeneity test, and Bonferroni test. In the reverse MR analysis, there was no causal effect of NMOSD and its subtypes on circulating L-carnitine levels. Our findings suggest that higher circulating L-carnitine levels may reduce the risk of NMOSD, particularly in AQP4-IgG-seronegative patients. L-carnitine could serve as a valuable biomarker and potential therapeutic target for NMOSD, especially in cases without AQP4-IgG. The genetic evidence from this study supports further exploration of L-carnitine's role in managing NMOSD.

Association between gut microbiota, plasma metabolites, and ovarian cancer: A Mendelian randomization study.

Numerous studies have demonstrated a correlation between alterations in gut microbiota (GM) and levels of body metabolites in ovarian cancer (OC). However, the specific causal relationships underlying these associations remain unclear. This study utilized summary statistics of GM from the MiBioGen consortium, along with an unprecedented dataset comprising 1091 blood metabolites and 309 metabolite ratios from the UK Biobank, in conjunction with OC data from the FinnGen Consortium R9 release. We conducted bidirectional Mendelian randomization (MR) analyses to investigate the causal relationships between GM and OC. Additionally, a two-step MR approach was employed to identify potential mediating metabolites. Our analysis revealed significant associations between 6 specific microbiota taxa and OC. Furthermore, we identified several plasma metabolites that act as mediators of the association between GM and OC. In the two-step MR analysis, we observed a negative correlation between 4-methoxyphenol sulfate and pregnenetriol disulfate levels with OC. The genus Lachnospiraceae UCG008 potentially increases the risk of OC by decreasing 4-methoxyphenol sulfate levels, while the genus Howardella may elevate the risk of OC by reducing pregnenetriol disulfate levels, with mediation proportions of 22.35% and 4.23%, respectively. Additionally, levels of dilinoleoyl-GPE (18:2/18:2) and N-acetylkynurenine (2) were positively correlated with OC. The inhibitory effect of the genus Ruminococcus 1 on OC may be mediated through 1,2-dilinoleoyl-GPE (18:2/18:2) and N-acetylkynurenine (2), with mediation proportions of 10.15% and 11.32%, respectively. Our findings highlight the complex relationship among GM, plasma metabolites, and OC. The identified associations and mediation effects offer valuable insights into potential therapeutic approaches targeting GM for the management of OC.

Associations between milk infrared-predicted plasma biomarkers of stress resilience and fertility in dairy cattle: insights for enhancing breeding programs and herd management

Fertility is a crucial aspect of dairy herd efficiency and sustainability. Among factors influencing fertility in dairy cattle, metabolic stress and systemic inflammation of animals are of main relevance, especially in the postpartum stage when ovarian activity begins and cows are inseminated. Our study aimed to infer the associations between milk infrared-predicted blood biomarkers of stress resilience and fertility traits, namely the interval from calving to first service (iCF), days open (DO), and the pregnancy rate at first service (PRF) in a multi-breed population of 89,097 dairy cows. The blood metabolites (15 blood biomarkers related to hepatic damage and function, oxidative stress, and inflammation/innate immunity) were predicted using milk Fourier-transform mid-infrared (MIR) spectroscopy. A gradient boosting machine (GBM) approach with leave-one-batch-out cross-validation (R2 range from 0.45 to 0.82) was implemented to an independent calibration database of 1,367 lactating cows reared in 5 herds. Calibration equations were then applied to a population database of 1,799,186 MIR milk spectral data, that were then merged with fertility data collected by the Breeders Federation of Alto Adige (Bolzano province, Italy) generating a final database of 285,145 records. The 2 databases were merged according to the milk test day (and thus the MIR spectrum) closest to the date of insemination. The interval fertility traits were fitted as the hazard of either receiving the first service after calving at time t for iCF or becoming pregnant after calving at time t for DO in a Cox proportional-hazards model. Statistical analyses were performed including in the model the number of lactations, year of calving, and herd as fixed effects. The independent effect of the MIR-based predictions of metabolites was also included with each metabolite evaluated separately and discretized into 7 levels based on percentiles. Pregnancy rate at first service, on the other hand, was analyzed using logistic regression and the same explanatory variables. The metabolites linked to liver function and damage, such as aspartate aminotransferase, total bilirubin, and alkaline phosphatase, had a relevant influence on iCF and DO in terms of the hazard ratio (HR). Relevant results were also obtained for the biomarkers related to oxidative stress and inflammation/innate immunity. Specifically, increasing levels of ceruloplasmin, total reactive oxygen metabolites, and advanced oxidation protein products resulted in a relevant decrease in the HR of cows becoming pregnant. The logistic regression analysis did not reveal any significant effect of the aforementioned biomarkers on PRF, indicating that the effects of the stress response mainly concern the resumption of the ovarian cycle after calving. The results for the associations of the predicted biomarkers of the stress response with iCF and DO were consistent with expected physiological patterns. In conclusion, the predicted biomarkers investigated revealed to be promising novel phenotypes for assessing animal health and welfare, in the view of enhancing fertility in dairy cattle also through selective breeding, thus improving the overall efficiency of dairy herds.

Causal association of gut microbes and blood metabolites with acne identified through systematic mendelian randomization

Acne is a prevalent inflammatory disease in dermatology, and its pathogenesis may be associated with inflammation, immunity, and other mechanisms. It commonly manifests in young individuals and frequently imposes a heavy economic, physical, and psychological burden on patients. Gut microbes and blood metabolites, as significant immune and inflammatory regulators in the body, have been hypothesized to form the “neurocutaneous axis.” Nonetheless, the precise causal relationships among the gut microbes, circulating blood metabolites, and acne development have yet to be elucidated. This study employed bidirectional two-sample Mendelian randomization (MR) to probe the causal impacts of 412 distinct gut microbes and 249 blood metabolites on acne. Single nucleotide polymorphisms (SNPs), which are closely associated with gut microbes and blood metabolites, were utilized as instrumental variables. This approach was taken to discern whether these elements serve as pathogenic or protective factors in relation to acne. Furthermore, a mediation analysis encompassing gut microbes, blood metabolites, and acne was conducted to explore potential correlations between gut microbes and blood metabolites, as well as their cumulative effects on acne. This was done to substantiate the notion of causality. Bidirectional two-sample MR analysis revealed 8 gut bacteria, 6 bacterial metabolic abundance pathways determined by birdshot, and 8 blood metabolites significantly associated with acne. The mediation MR analysis revealed 2 potential causal relationships, namely, Bifidobacterium-DHA-Acne and Bifidobacterium-Degree of Unsaturation-Acne. This study identified gut microbes and blood metabolites that are causally associated with acne. A potential causal relationship between gut microbes and blood metabolites was obtained via mediation analysis. These insights pave the way for the identification of new targets and the formulation of innovative approaches for the prevention and treatment of acne.

Genetic Association Between Blood Metabolites and Craniosynostosis: A Mendelian Randomization Study.

Craniosynostosis is a congenital disorder characterized by the premature fusion of cranial sutures, leading to abnormal skull development and potential neurodevelopmental complications. The role of metabolic influences in craniosynostosis remains underexplored. This study investigates the causal relationship between specific blood metabolites and the risk of craniosynostosis using a 2-sample Mendelian randomization (MR) approach. Genetic instruments were selected from a genome-wide association study on blood metabolites and craniosynostosis data from the FinnGen database. The MR analysis was conducted using inverse variance weighted regression as the primary method, with MR-Egger and weighted median methods as sensitivity analyses. Additional tests for pleiotropy and heterogeneity were performed to validate the robustness of the findings. The analysis identified significant associations between elevated levels of gamma-glutamylglycine [odds ratio (OR) = 2.379, 95% CI = 1.261-4.488, P = 0.007], N6-acetyllysine (OR = 2.731, 95% CI = 1.081-6.901, P = 0.034), phosphocholine (OR = 2.205, 95% CI = 1.226-3.658, P = 0.038) and glycine (OR = 2.118, 95% CI = 1.226-3.658, P = 0.007) with an increased risk of craniosynostosis. Conversely, higher levels of 3-hydroxy-2-methylpyridine sulfate (OR = 0.411, 95% CI = 0.1717-0.988, P = 0.047) and 5,6-dihydrothymine (OR = 0.293, 95% CI = 0.098-0.876, P = 0.028) were associated with reduced risk. Sensitivity analyses confirmed the robustness of these findings, with no significant evidence of pleiotropy or heterogeneity detected. This study provides evidence that specific blood metabolites may causally influence the risk of craniosynostosis, suggesting potential metabolic pathways that could be targeted for therapeutic intervention. These findings help to develop metabolite-based strategies for the prevention and treatment of craniosynostosis.

Associations of human blood metabolome with optic neurodegenerative diseases: a bi-directionally systematic mendelian randomization study

BackgroundMetabolic disruptions were observed in patients with optic neurodegenerative diseases (OND). However, evidence for the causal association between metabolites and OND is limited.MethodsTwo-sample Mendelian randomization (MR). Summary data for 128 blood metabolites was selected from three genome-wide association study (GWASs) involving 147,827 participants of European descent. GWASs Data for glaucoma (20906 cases and 391275 controls) and age-related macular degeneration (AMD, 9721 cases and 381339 controls) came from FinnGen consortium. A bi-directional MR was conducted to assess causality, and a Mediation MR was further applied to explore the indirect effect, a phenome-wide MR analysis was then performed to identify possible side-effects of the therapies.ResultsAll the results underwent correction for multiple testing and rigorous sensitivity analyses. We identified N-acetyl glycine, serine, uridine were linked to an elevated risk of glaucoma. 1-arachidonic-glycerol-phosphate-ethanolamine, 4-acetamido butanoate, o-methylascorbate, saturated fatty acids, monounsaturated fatty acids, VLDL cholesterol, serum total cholesterol, X-11,529 were linked to reduced risk of glaucoma. There were 4 metabolites linked to a reduced risk of AMD, including tryptophan betaine, 4-androsten-3beta-17beta-diol disulfate, apolipoprotein B, VLDL cholesterol. We discovered IOP, AS, T2D as glaucoma risk factors, while BMI, AS, GCIPL as AMD factors. And 6 metabolites showed associations with risk factors in the same direction as their associations with glaucoma/AMD. Phenome-wide MR indicated that selected metabolites had protective/adverse effects on other diseases.ConclusionsBy integrating genomics and metabolomics, this study supports new insights into the intricate mechanisms, and helps prevent and screen glaucoma and AMD.

From metabolomics to therapeutics: identifying causal metabolites and potential drugs for the treatment of osteoarthritis.

Osteoarthritis (OA) is a common age-related disease that causes pain and impaired mobility. Various blood metabolites are reportedly associated with bone health; however, their impact on OA remains unclear. Therefore, we conducted a metabolome-wide Mendelian randomization (MR) study to identify causal metabolites and therapeutic targets in OA. Genetic associations of metabolites were derived from the largest genome-wide association study (GWAS) of the blood metabolome, which provided summary-level data on 1091 blood metabolites. Genetic associations with OA were obtained from four large-scale GWAS: McDonald's study (140,025 cases, 344,349 controls), Zengini's study (12,658 cases, 50,898 controls), Dönertaş's study (39,515 cases, 445,083 controls), and Tachmazidou's study (39,427 cases, 378,169 controls). MR and colocalization analyses were performed to validate the causal roles of the candidate metabolites. Further analyses were conducted using expression quantitative trait locus-based MR, single-cell sequencing data, protein-protein interaction networks, and druggability assessments. These analyses aimed to identify the differentially expressed genes and prioritize them as potential therapeutic targets. The genetically predicted levels of 10 metabolites were associated with OA. Elevated levels of five metabolites and reduced levels of another five metabolites were associated with an increased OA risk. Among these, five metabolites were prioritized based on the most compelling evidence. Seven genes were identified as potentially involved and could serve as novel therapeutic targets for OA. Several blood metabolites were associated with OA, providing new insights into the etiology of OA and highlighting promising therapeutic targets.

Association between human blood metabolome and risk of myocarditis: a mendelian randomization study

Myocarditis is a common disease of the cardiovascular and immune systems, but the relationship between relevant blood metabolites and the risk of myocarditis has not been well-established. To identify potential biometabolic markers associated with myocarditis, we conducted a two-sample Mendelian randomization (MR) study. We performed preliminary MR analysis using the inverse variance weighted (IVW) method, supplemented by MR-Egger, weighted median, and weighted mode methods to adjust for false discovery rate (FDR). Confounders were screened using the GWAS Catalog website. Sensitivity analyses included Cochrane Q-test, Egger regression, Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO), scatterplots, funnel plots, and forest plots. For genetic and directional analysis, we employed co-localization analysis and the Steiger test. MR analysis was performed using the FinnGen database and meta-analysis was performed using the IEU database. MR analysis identified significant correlations for five metabolic biomarkers after FDR correction. These included four known metabolites: kynurenine, 1-stearoyl-GPE (18:0), deoxycarnitine, and 5-acetylamino-6-formylamino-3-methyluracil, as well as one unknown metabolite, X-25,422. Among these, kynurenine (OR = 1.441, 95%CI = 1.089–1.906, p-value = 0.018) and 1-stearoyl-GPE (18:0) (OR = 1.263, 95%CI = 1.029–1.550, p-value = 0.029) were identified as risk factors for myocarditis, while deoxycarnitine (OR = 0.813, 95%CI = 0.676–0.979, p-value = 0.029), 5-acetylamino-6-formylamino-3-methyluracil (OR = 0.864, 95% CI = 0.775–0.962, p-value = 0.018), and X-25,422 (OR = 0.721, 95%CI = 0.587–0.886, p-value = 0.009) were found to be protective factors. No evidence of heterogeneity, horizontal pleiotropy, or sensitivity issues was observed, and no shared genetic factors between exposure and outcome were detected. The causality was in the correct direction. Meta-analysis further confirmed the causal relationship between the five metabolites and myocarditis. This study identifies a causal relationship between five circulating metabolites and myocarditis. Kynurenine, 1-stearoyl-GPE (18:0), deoxycarnitine, X-25,422, and 5-acetylamino-6-formylamino-3-methyluracil may serve as potential drug targets for myocarditis, providing a theoretical basis for the prevention, diagnosis, and treatment of the condition.

Effects of dietary digestible lysine levels in breeding Japanese quails on productive and reproductive performance, egg quality, blood metabolites and immune responses.

The vegetable-based diet alone does not provide the lysine (Lys) needed to maximize poultry productive performance. This experiment aimed to evaluate the effects of dietary digestible Lys (dLys) level on productive and reproductive performance, egg quality, blood metabolites and immune responses in breeding Japanese quails (Coturnix japonica). The experiment was conducted in a completely randomized design with 6 treatments, 5 replicates and 15 (12 females and 3 meals) 10-week-old breeding Japanese quails each. A basal diet was formulated to meet nutritional requirements of breeding quails except dLys. The basal diet was supplemented with graded (+0.82g/kg) levels of l-Lys-HCl, corresponding to dietary dLys levels of 0.690%, 0.755%, 0.820%, 0.885%, 0.950% and 1.015%. The experiment lasted for 12 weeks, which was divided into 3-4-week periods. Significant differences were observed for egg production (EP), egg mass (EM) and feed efficiency (FE) in response to increasing dietary dLys concentration with quadratic trends. The highest traits were observed in the birds fed with a diet containing 0.885% dLys. However, feed intake, egg quality, reproductive performance, blood metabolites and immune responses against sheep red blood cell inoculation were not significantly affected by increasing dietary dLys concentrations. The dLys requirements during 11-14, 15-18, 19-22 and 11-22 (overall) weeks of age for optimal EP, EM and FE, based on the quadratic broken-line regression analysis, were estimated 272, 265, 250 and 266; 293, 285, 264 and 279; and 303, 294, 281 and 293mg/bird/day, respectively. The dLys requirements vary depending on the EP phase and the trait being optimized. The estimated dLys requirement for FE was higher than those for EP and EM. During the peak stage of the first laying cycle, the dietary dLys level of 0.932% and a daily intake of 303mg dLys/bird are sufficient for optimal performance.

Discovery of novel metabolic biomarkers in blood serum for diagnosis of Alzheimer's disease.

Blood metabolites have emerged as promising candidates in the search for biomarkers for Alzheimer's disease (AD), as evidence shows that various metabolic derangements contribute to neurodegeneration in AD. We aim to identify metabolic biomarkers for AD diagnosis. We conducted an in-depth analysis of the serum metabolome of AD patients and age, sex-matched cognitively unimpaired older adults using ultra-high-performance liquid chromatography-high resolution mass spectrometry. The biomarkers associated with AD were identified using machine learning algorithms. Using the discovery dataset and support vector machine (SVM) algorithm, we identified a panel of 14 metabolites predicting AD with a 1.00 area under the curve (AUC) of receiver operating characteristic (ROC). The SVM model was tested against the verification dataset using an independent cohort and retained high predictive accuracy with a 0.97 AUC. Using the random forest (RF) algorithm, we identified a panel of 13 metabolites that predicted AD with a 0.96 AUC when tested against the verification dataset. These findings pave the way for an efficient, blood-based diagnostic test for AD, holding promise for clinical screenings and diagnostic procedures.

Impact of live yeast and selenium supplementation on blood metabolites and rumen pH of young bulls after long-transport to the fattening unit

Impact of live yeast and selenium supplementation on blood metabolites and rumen pH of young bulls after long-transport to the fattening unit

P030 Sex hormones and blood metabolites mediating the causal associations between gut microbiota and prostate cancer: Evidences from mendelian randomization study

P030 Sex hormones and blood metabolites mediating the causal associations between gut microbiota and prostate cancer: Evidences from mendelian randomization study

Genetic aspects of major blood metabolites in the Italian Simmental cattle population

The Simmental breed is widely known for its resilience, robustness, and resistance to disease and therefore the incidence of ketosis in this breed is generally lower compared with Holsteins. Blood concentrations of nonesterified fatty acids (NEFA), BHB, and urea provide valuable information about the metabolic, health, and nutritional status of lactating animals. In the present study we estimated h2 of BHB, NEFA, and urea in blood predicted from milk mid-infrared spectra and assessed their genetic correlation with milk yield and composition traits in the Italian Simmental cattle breed using phenotypes of 3,549 cows in 207 herds. Two sets were considered: early (1,920 records - 1 per cow - between 5 and 35 DIM) and whole (14,378 records - at least 3 per cow - between 5 and 305 d in milk) lactation. In early lactation, h2 were 0.06 for blood BHB as is, 0.06 for log-transformed BHB, 0.18 for NEFA, 0.14 for log-transformed NEFA, and 0.05 for blood urea. In whole lactation, the h2 were 0.09 for blood BHB as is, 0.16 for log-transformed BHB, 0.03 for NEFA, 0.04 for log-transformed NEFA, and 0.04 for blood urea. As far as the genetic correlations were concerned, blood BHB was positively correlated with NEFA and blood urea. Blood BHB and NEFA were generally positively correlated with milk fat-to-protein ratio and milk BHB; blood BHB was negatively correlated with lactose content and positively with SCS. Sires' estimated breeding values for BHB (accuracy ≥0.60) were extrapolated for a-posteriori evaluation of the daughters' observed performance. The progeny of the top 5% of sires exhibited, on average, lower blood BHB, NEFA, and urea compared with the daughters of the bottom 5%. Overall, it is highly recommended to monitor the genetic variability of the metabolic traits in the dual-purpose Italian Simmental breed to monitor the metabolic diseases incidence in future generations.

Exploring genetic links between blood metabolites and gout susceptibility.

Gout, a prevalent form of inflammatory arthritis, has a complex etiology where the causal relationship between metabolites and the disease remains underexplored. This study aims to elucidate the impact of genetically determined blood metabolites on gout. Employing a two-sample bidirectional Mendelian randomization analysis, we examined the association between 1400 blood metabolites and gout. Causal associations were determined using the inverse variance weighted (IVW) method with false discovery rate (FDR) correction. Sensitivity analyses encompassed weighted models, MR-Egger, weighted median, and MR-PRESSO approaches. MR-pleiotropy and Cochran's Q statistic were utilized to evaluate potential heterogeneity and pleiotropy. Additionally, metabolic pathway analyses were conducted to pinpoint relevant pathways. Of the initial 4 serum metabolites identified, 3 known metabolites-hexanoylglutamine levels, mannose content, and the phosphate to mannose ratio-were found to be causally associated with gout, along with 55 serum metabolites identified as potential predictors of gout (PIVW < 0.05). Furthermore, we discovered 3 metabolic pathways implicated in gouty attacks. Our findings, derived from Mendelian randomization, indicate that the identified metabolites and pathways may serve as biomarkers for clinical screening and prevention of gout. Additionally, they offer novel insights into the mechanisms of the disease and potential drug targets. Key points • Conducted a comprehensive Mendelian randomization study involving 1400 blood metabolites to explore their genetic impact on gout development and progression • Identified three key metabolites-hexanoylglutamine, mannose, and the phosphate-to-mannose ratio-with causal associations to gout, highlighting their potential use as biomarkers for early detection and risk stratification • Discovered 55 additional serum metabolites as potential predictors of gout, offering new insights into the pathophysiology of the disease and identifying high-risk individuals • Revealed three novel metabolic pathways involved in gout attacks, providing new therapeutic targets for precision medicine in gout treatment.

Effects of dietary phytase supplementation on growth performance, nutrient digestibility, and blood metabolites of weaned piglets

Context Phytase plays a crucial role in the nutrition of piglets. Incorporating phytase into weaner pigs’ diet may alleviate the anti-nutritional effect by catalyzing the hydrolysis of phytic acid. As a result, bounded phosphorus and other minerals become more available for absorption, thereby enhancing nutrient utilization growth performance. Aims This study evaluated the efficacy of dietary phytase supplementation on the performance of weaned piglets. Methods Two hundred and forty cross-bred piglets (Yorkshire × Landrace × Duroc), of initial average bodyweight (BW) of 5.57 ± 1 kg at weaning, were assigned to five dietary treatments in a complete randomized block design. The study was conducted in the following three phases: Phase 1 (Days 1–7), Phase 2 (Days 8–21), and Phase 3 (Days 22–35). The treatments included basal diet containing 0.15% lower concentration of both total calcium and total phosphorus (NC), a standard basal diet (PC), NC + 500 phytase units per kilogram of feed (NC500), NC + 1000 phytase units per kilogram of feed (NC1000), and NC + 1500 phytase units per kilogram of feed (NC1500). Key results In Phase 1, the final BW was higher (P &lt; 0.01) in PC and the phytase-supplemented diets than in the NC treatment. In Phase 2, Phase 3, and the overall days the average daily gain (ADG) and gain-to-feed ratio (G:F) were greater (P &lt; 0.05) in the PC and the phytase-supplemented diets than in the NC treatments. The ADG and G:F were also higher (P &lt; 0.01) in the phytase-supplemented diets than in the NC treatment. The digestibility of calcium, phosphorus, and blood myo-inositol was higher (P &lt; 0.05) in the phytase-supplemented diets than in the NC treatment in Phase 2. In Phase 3, the level of blood myo-inositol was higher (P &lt; 0.01) in the phytase-supplemented diets than in NC. Fecal inositol hexakisphosphate was lower (P &lt; 0.01) in the phytase-supplemented diets than in NC in both Phases 1 and 2. Conclusion Dietary supplementation of phytase increased the digestibility of phytate by releasing phosphorus, calcium, and myo-inositol concentration, leading to improved growth performance. Implications Inclusion of phytase in pig diets can help farmers save money on feed additives such as phosphorus, improve environmental sustainability, and promote better growth performance.

The Protein/Carbohydrate Ratio in the Diet Affects Zootechnical Performance and the Regulation of Intermediary Metabolism in Juveniles Tambaqui (Colossoma macropomum).

The use of carbohydrates in animal feed is a way to save protein in the diet. This study evaluated the effect of protein/starch ratio on the performance, hepatic metabolism, and body composition of juvenile tambaqui (Colossoma macropomum). Six isoenergetic experimental diets were formulated containing three levels of digestible protein (P: 230, 260 and 290 g kg- 1) and two levels of starch (S: 180 and 280 g kg- 1): P23S18, P23S28, P26S18, P26S28, P29S18 and P29S28. Juveniles tambaqui (N = 288; initial weight = 30.0 ± 3.8 g) were fed experimental diets for 90 days and the zootechnical performance was evaluated. Nine fish from each treatment group were sampled to determine somatic indices, blood metabolites, tissue energy reserves, body composition and activity of key hepatic enzymes. Blood triglycerides, hepatosomatic index, liver and muscle lipids, and hepatic glycogen increased significantly with starch while blood glucose, triglycerides and cholesterol, muscle lipids were significantly impacted by protein levels. Fish-fed S28 had increased feed intake (1714-1829 g; p < 0.0001) and fish-fed diet P26S18 had a higher protein efficiency rate (23.62%; p = 0.0356). Fish fed P23 had lower crude protein retention in the carcass (p = 0.0018) and high lipogenesis and lipid deposition in the muscle (p = 0.0069). These results suggest that dietary carbohydrates have a protein-sparing effect. Tambaqui adapted well to diets containing starch, even at higher levels, resulting in an overall increase in lipogenesis from S18 to S28. Thus, we recommend P26S18 as a cost-effective feed that ensures both zootechnical performance and quality of the final product.