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The giant freshwater prawn (GFP; Macrobrachium rosenbergii), a tropical species cultured worldwide, has high market demand and economic value. Male GFP growth varies considerably; however, the mechanisms underlying these growth differences remain unclear. In this study, we collected gut and hemolymphatic samples of large (ML), medium (MM), and small (MS) male GFPs and used the 16S rRNA sequencing and liquid chromatography-mass spectrometry-based metabolomic methods to explore gut microbiota and metabolites associated with GFP growth. The dominant bacteria were Firmicutes and Proteobacteria; higher growth rates correlated with a higher Firmicutes/Bacteroides ratio. Serum metabolite levels significantly differed between the ML and MS groups. We also combined transcriptomics with integrative multiomic techniques to further elucidate systematic molecular mechanisms in the GFPs. The results revealed that Faecalibacterium and Roseburia may improve gut health in GFP through butyrate release, affecting physiological homeostasis and leading to metabolic variations related to GFP growth differences. Notably, our results provide novel, fundamental insights into the molecular networks connecting various genes, metabolites, microbes, and phenotypes in GFPs, facilitating the elucidation of differential growth mechanisms in GFPs.

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Objective To investigate the causal relationships between plasma metabolites and osteoporosis via Mendelian randomization (MR) analysis. Methods Bidirectional MR was used to analyze pooled data from different genome-wide association studies (GWAS) to investigate the causal relationships between plasma metabolites and osteoporosis. The causal effect of plasma metabolites on osteoporosis was estimated using the inverse variance weighted method, intersections of statistically significant metabolites obtained from different sources of osteoporosis-related GWAS aggregated data was determined, and then sensitivity analysis was performed on these metabolites. Heterogeneity between single nucleotide polymorphisms was evaluated by Cochran's Q test. Horizontal pleiotropy was assessed through the application of the MR-Egger intercept method and the MR-PRESSO method. The causal effect of osteoporosis on plasma metabolites was also evaluated using the inverse variance weighted method. Additionally, pathway analysis was conducted to identify potential metabolic pathways involved in the regulation of osteoporosis. Results After primary analysis and a series of sensitivity analyses, 77 and 61 plasma metabolites were identified as having a causal relationship with osteoporosis from the GWAS data in the GCST90038656 and GCST90044600 datasets , respectively. Five common metabolites were identified via intersection. X-13684 levels (GCST90038656: OR = 0.999, 95% CI, 0.998-1.000, P = 0.004; GCST90044600 (OR = 0.834, 95% CI, 0.700-0.993, P = 0.042), and the glucose-to-maltose ratio (GCST90038656: OR = 0.998, 95% CI, 0.997-1.000, P = 0.025; GCST90044600: OR = 0.752, 95% CI, 0.576-0.981, P = 0.036) were negatively associated with osteoporosis, whereas glycoursodeoxycholate levels (GCST90038656: OR = 1.002, 95% CI, 1.000-1.003, P = 0.032; GCST90044600: OR = 1.331, 95% CI, 1.036-1.709, P = 0.025) and arachidoylcarnitine (C20) levels (GCST90038656: OR = 1.001, 95% CI, 1.000-1.003, P = 0.039; GCST90044600: OR = 1.237; 95% CI, 1.008-1.518, P = 0.042) were positively associated with osteoporosis. The relationship between X-11299 levels and osteoporosis showed contradictory results (GCST90038656: OR= 0.998, 95% CI, 0.997-1.000, P = 0.026; GCST90044600: OR = 1.402, 95% CI, 1.071-1.834, P = 0.014). Pathway analysis indicated that glycine, serine, and threonine metabolism, valine, leucine, and isoleucine biosynthesis, galactose metabolism, arginine biosynthesis, and starch and sucrose metabolism pathways were participated in the development of osteoporosis. Conclusion We found a causal relationship between plasma metabolites and osteoporosis. These results offer novel perspectives that have implications for targeted interventions focused on metabolites in the management of osteoporosis.

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Background: Studies on the relationships between diseases of the urinary system and human plasma proteomes have identified several potential biomarkers. However, none of these studies have elucidated the causal relationships between plasma proteins and urolithiasis. Objective: The objective of the study was to investigate the potential risks of plasma metabolites in urolithiasis using a two-sample Mendelian randomization (MR) study. Methods: A total of 1,400 metabolites were identified in the most comprehensive genome-wide association study (GWAS) of plasma metabolomics in a European population to date, and single-nucleotide polymorphisms (SNPs) were used as the instrumental variables for the plasma metabolites. The European GWAS data for urinary calculi included 482,123 case samples and 6,223 control samples (ebi-a-GCST90018935). The associations between the plasma metabolites and risk of urolithiasis were evaluated by inverse variance weighting (IVW) and supplemented by sensitivity analyses of the MR-Egger and MR-PRESSO tests. Results: For the first time, we found a causal relationship between two plasma metabolites (p < 1.03 × 10-4) and urolithiasis (p < 0.05). The chemical 4-hydroxychlorothalonil, which is an intermediate product of the pesticide hydroxychlorothalonil, could promote urolithiasis (odds ratio (OR) = 1.12) as a risk factor. Moreover, 1-stearoyl-2-arachidonoyl-GPC, which is an important component of phospholipid metabolism in the human body, can inhibit urolithiasis (OR = 0.94). Conclusions: Our results suggest that blood metabolites can be used as blood markers and drug targets in the prevention, diagnosis, and treatment of urolithiasis; furthermore, our results can provide a basis for policy makers to formulate prevention and treatment policies for urolithiasis.

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Background: Increasing evidence indicates a close relationship between alterations in human immune cells and plasma metabolites with Rheumatoid Arthritis (RA). However, limited studies have left the causal relationships behind these links unclear. Methods: A bidirectional Mendelian Randomization (MR) study was conducted, combined with mediation analysis, using data from genome-wide association study database covering 731 immune cell phenotypes and 1,400 plasma metabolite traits to explore their causal relationships with RA and potential mediating effects. The primary method used for MR analysis was inverse-variance weighted and False Discovery Rate (FDR) correction was applied to verify the robustness of our results. Results: HLA DR on CD33- HLA DR+ (myeloid cell group) (OR, 1.422; 95% CI, 1.194-1.694; P < 0.001; PFDR = 0.012) increased the risk of developing RA. CD19 on IgD+ CD38- naive (B cell group) (OR, 0.969; 95% CI, 0.954-0.985; P < 0.001; PFDR = 0.021) reduced the risk of developing RA. RA was a risk factor for HLA DR on CD14- CD16+ monocytes (monocyte group) (OR, 1.242; 95% CI, 1.102-1.401; P < 0.001; PFDR = 0.047). RA was a protective factor for memory B cell %lymphocyte (B cell group) (OR, 0.861; 95% CI, 0.795-0.933; P < 0.001; PFDR = 0.050), CD4+ CD8dim T cell %lymphocyte (TBNK group) (OR, 0.802; 95% CI, 0.711-0.904; P < 0.001; PFDR = 0.043), CD4+ CD8dim T cell %leukocyte (TBNK group) (OR, 0.814; 95% CI, 0.726-0.913; P < 0.001; PFDR = 0.046), CD24 on IgD+ CD24+ B cells (B cell group) (OR, 0.857; 95% CI, 0.793-0.927; P < 0.001; PFDR = 0.038), and CD24 on unswitched memory B cells (B cell group) (OR, 0.867; 95% CI, 0.797-0.942; P < 0.001; PFDR = 0.050). Increasing levels of docosatrienoate (22:3n3) (OR, 0.886; 95% CI, 0.838-0.936; P < 0.001; PFDR = 0.023) significantly reduced the risk of developing RA. The mediating effect of plasma metabolites in this context was not established. Conclusion: This study provides genetic evidence for the intricate relationships between immune cells, plasma metabolites, and RA, highlighting the potential mechanisms involved. This will contribute to future directions in precision medicine and research.

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Artritis Reumatoide , Estudio de Asociación del Genoma Completo , Análisis de la Aleatorización Mendeliana , Humanos , Artritis Reumatoide/sangre , Artritis Reumatoide/inmunología , Artritis Reumatoide/genética , Monocitos/metabolismo , Monocitos/inmunología , Masculino , Femenino , Antígenos HLA-DR/genética , Linfocitos B/metabolismo , Linfocitos B/inmunología

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CONTEXT: Cardiometabolic multimorbidity (CM) is an increasing public health concern. Previous observational studies have suggested inverse associations between coffee, tea, and caffeine intake and risks of individual cardiometabolic diseases; however, their associations with CM and related biological markers are unknown. METHODS: This prospective study involved 172 315 (for caffeine analysis) and 188 091 (tea and coffee analysis) participants free of any cardiometabolic diseases at baseline from the UK Biobank; 168 metabolites were measured among 88 204 and 96 393 participants. CM was defined as the coexistence of at least 2 of the following conditions: type 2 diabetes, coronary heart disease, and stroke. RESULTS: Nonlinear inverse associations of coffee, tea, and caffeine intake with the risk of new-onset CM were observed. Compared with nonconsumers or consumers of less than 100 mg caffeine per day, consumers of moderate amount of coffee (3 drinks/d) or caffeine (200-300 mg/d) had the lowest risk for new-onset CM, with respective hazard ratios (95% CIs) of 0.519 (0.417-0.647) and 0.593 (0.499-0.704). Multistate models revealed that moderate coffee or caffeine intake was inversely associated with risks of almost all developmental stages of CM, including transitions from a disease-free state to single cardiometabolic diseases and subsequently to CM. A total of 80 to 97 metabolites, such as lipid components within very low-density lipoprotein, histidine, and glycoprotein acetyls, were identified to be associated with both coffee, tea, or caffeine intake and incident CM. CONCLUSION: Habitual coffee or caffeine intake, especially at a moderate level, was associated with a lower risk of new-onset CM and could play important roles in almost all transition phases of CM development. Future studies are warranted to validate the implicated metabolic biomarkers underlying the relation between coffee, tea, and caffeine intake and CM.

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Background: Emerging evidence indicates a correlation between imbalances in intestinal microbiota and changes in plasma metabolites in the progression of asthma. However, the causal link between these factors remains unclear. Methods: A two-sample Mendelian randomization (MR) study was employed to evaluate the potential causal connection between gut microbiota, plasma metabolites, and asthma susceptibility. Gut microbiota data from expansive genome-wide genotype studies and 16S fecal microbiome datasets were examined by the MiBioGen Alliance. Asthma data were procured from the FinnGen biobank analysis, while comprehensive Genome-Wide Association Studies (GWAS) summary statistics for plasma metabolites were derived from the NHGRI-EBI GWAS Catalog. Fluctuations in intestinal flora and plasma metabolites in asthma patients were evaluated using the weighted mode method. Additionally, pleiotropic and heterogeneity analyses were performed to ascertain the reliability of the findings. Results: Upon examining the gut microbiota through MR with the IVW method, alongside tests for heterogeneity and pleiotropy, findings reveal a negative association between the abundance of the Christensenellaceae R.7 group and asthma risk. In contrast, the Bifidobacterium and Prevotella 7 genera exhibit a positive association with asthma risk, indicating they may be potential risk factors (p < 0.05). Furthermore, MR analysis of 1,400 metabolites employing Weighted median, IVW, and Weighted mode methods resulted in p-values below 0.05. Subsequent tests for pleiotropy and heterogeneity showed that the levels of 3,5-dichloro-2,6-dihydroxybenzoic acid have a negative correlation with asthma, whereas the phenylalanine to phosphate ratio has a positive correlation, suggesting their potential as risk factors for asthma (p < 0.05). Conclusion: The current Mendelian randomization study provides evidence supporting a potential causal link between specific gut microbiota taxa, plasma metabolites, and asthma. These findings offer novel perspectives for future research and the development of treatment and prevention strategies for asthma.

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Introduction: The prevention and mitigation of intestinal immune challenge is crucial for poultry production. This study investigated the effects of dietary Macleaya cordata extract (MCE) supplementation on the prevention of intestinal injury in broiler chickens challenged with lipopolysaccharide (LPS). Methods: A total of 256 one-day-old male Arbor Acres broilers were randomly divided into 4 treatment groups using a 2×2 factorial design with 2 MCE supplemental levels (0 and 400 mg/kg) and 2 LPS challenge levels (0 and 1 mg/kg body weight). The experiment lasted for 21 d. Results and discussion: The results showed that MCE supplementation increased the average daily feed intake during days 0-14. MCE supplementation and LPS challenge have an interaction on the average daily gain during days 15-21. MCE supplementation significantly alleviated the decreased average daily gain of broiler chickens induced by LPS. MCE supplementation increased the total antioxidant capacity and the activity of catalase and reduced the level of malondialdehyde in jejunal mucosa. MCE addition elevated the villus height and the ratio of villus height to crypt depth of the ileum. MCE supplementation decreased the mRNA expression of pro-inflammatory cytokines interleukin (IL)-6 and IL-8 in the jejunum. MCE addition mitigated LPS-induced mRNA up-expression of pro-inflammatory factors IL-1ß and IL-17 in the jejunum. MCE supplementation increased the abundance of probiotic bacteria (such as Lactobacillus and Blautia) and reduced the abundance of pathogenic bacteria (such as Actinobacteriota, Peptostretococcaceae, and Rhodococcus), leading to alterations in gut microbiota composition. MCE addition altered several metabolic pathways such as Amino acid metabolism, Nucleotide metabolism, Energy metabolism, Carbohydrate metabolism, and Lipid metabolism in broilers. In these pathways, MCE supplementation increased the levels of L-aspartic acid, L-Glutamate, L-serine, etc., and reduced the levels of phosphatidylcholine, phosphatidylethanolamine, thromboxane B2, 13-(S)-HODPE, etc. In conclusion, dietary supplementation of 400 mg/kg MCE effectively improved the growth performance and intestinal function in LPS-challenged broiler chickens, probably due to the modulation of gut microbiota and plasma metabolites.

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Pollos , Suplementos Dietéticos , Microbioma Gastrointestinal , Lipopolisacáridos , Extractos Vegetales , Animales , Microbioma Gastrointestinal/efectos de los fármacos , Extractos Vegetales/farmacología , Extractos Vegetales/administración & dosificación , Masculino , Papaveraceae/química , Alimentación Animal , Enfermedades de las Aves de Corral/microbiología , Enfermedades de las Aves de Corral/inmunología , Citocinas/metabolismo , Citocinas/sangre , Intestinos/efectos de los fármacos , Intestinos/microbiología , Intestinos/inmunología

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The development of coronary artery disease (CAD) is significantly affected by impaired endocrine and metabolic status. Under this circumstance, improved prevention and treatment of CAD may result from knowing the connection between metabolites and CAD. This study aims to delve into the causal relationship between human metabolic biomarkers and CAD by using two-sample Mendelian randomization (MR). Utilizing two-sample bidirectional MR analysis, we assessed the correlation between 1400 blood metabolites and CAD, and the metabolites data from the CLSA, encompassing 8299 participants. Metabolite analysis identified 1091 plasma metabolites and 309 ratios as instrumental variables. To evaluate the causal link between metabolites and CAD, we analyzed three datasets: ebi-a-GCST005195 (547,261 European & East Asian samples), bbj-a-159 (29,319 East Asian CAD cases & 183,134 East Asian controls), and ebi-a-GCST005194 (296,525 European & East Asian samples). To estimate causal links, we utilized the IVW method. To conduct sensitivity analysis, we used MR-Egger, Weighted Median, and MR-PRESSO. Additionally, we employed MR-Egger interception and Cochran's Q statistic to assess potential heterogeneity and pleiotropy. What's more, replication and reverse analyses were performed to verify the reliability of the results and the causal order between metabolites and disease. Furthermore, we conducted a pathway analysis to identify potential metabolic pathways. 59 blood metabolites and 27 metabolite ratios nominally associated with CAD (P < 0.05) were identified by IVW analysis method. A total of four known blood metabolites, namely beta-hydroxyisovaleroylcarnitine (OR 1.06, 95% CI 1.027-1.094, FDR 0.07), 1-palmitoyl-2-arachidonoyl (OR 1.07, 95% CI 1.029-1.110, FDR 0.09), 1-stearoyl-2- docosahexaenoyl (OR 1.07, 95% CI 1.034-1.113, FDR 0.07) and Linoleoyl-arachidonoyl-glycerol, (OR 1.07, 95% CI 1.036-1.105, FDR 0.05), and two metabolite ratios, namely spermidine to N-acetylputrescine ratio (OR 0.94, 95% CI 0.903-0.972, FDR 0.09) and benzoate to linoleoyl-arachidonoyl-glycerol ratio (OR 0.87, 95% CI 0.879-0.962, FDR 0.07), were confirmed as having a significant causal relationship with CAD, after correcting for the FDR method (p < 0. 1). A causal relationship was found to be established between beta -hydroxyisovalerylcarnitine and CAD with the validation in other two datasets. Moreover, multiple metabolic pathways were discovered to be associated with CAD. Our study supports the hypothesis that metabolites have an impact on CAD by demonstrating a causal relationship between human metabolites and CAD. This study is important for new strategies for the prevention and treatment of CAD.

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Biomarcadores , Enfermedad de la Arteria Coronaria , Análisis de la Aleatorización Mendeliana , Femenino , Humanos , Masculino , Biomarcadores/sangre , Enfermedad de la Arteria Coronaria/sangre , Enfermedad de la Arteria Coronaria/genética , Enfermedad de la Arteria Coronaria/metabolismo , Metabolómica/métodos , Pueblos del Este de Asia , Pueblo Europeo

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OBJECTIVE: Gut dysbiosis and metabolic abnormalities have been implicated in HIV infection. However, the exact causal relationships among the gut microbiota, metabolites, and HIV infection remain poorly understood. Our study involving Mendelian randomization (MR) and mediation analysis aims to unveil these causalities. METHODS: Genetic instrumental variables for the gut microbiota were retrieved from MiBioGen consortium (n = 18,340). Metabolism-related genetic variants were sourced from the CLSA cohort (n = 8299). GWAS summary statistics for symptomatic HIV infection were derived from the FinnGen study (n = 309,154), and the UK Biobank (n = 208,808). We performed the bidirectional two-sample MR to assess causalities with the inverse-variance weighted (IVW) method as the primary analysis. Moreover, we executed a mediation analysis using two-step MR methods. RESULTS: Compared to the causal effects of HIV infection on gut microbiota (or metabolites), those of gut microbiota (or plasma metabolites) on the risk of HIV infection were more substantial. Phylum Proteobacteria (OR: 2.114, 95% CI 1.042-4.288, P = 0.038), and genus Ruminococcaceae UCG013 (OR: 2.127, 95% CI 1.080-4.191, P = 0.029) exhibited an adverse causal effect on HIV infection, whereas genus Clostridium sensu stricto 1(OR: 0.491, 95% CI 0.252-0.956, P = 0.036) and family Erysipelotrichaceae (OR: 0.399, 95% CI 0.193-0.827, P = 0.013) acted as significant protective factors for HIV. The salicyluric glucuronide level (OR = 2.233, 95% CI 1.120-4.453, P = 0.023) exhibited a considerably adverse causal effect on HIV infection. Conversely, the salicylate-to-citrate ratio (OR: 0.417, 95% CI 0.253-0.688, P = 0.001) was identified as a protective factor for HIV. We identified only one bidirectional causality between 1-palmitoyl-GPI and HIV infection. Mechanistically, genus Haemophilus mediated the causal effects of three phospholipids on HIV infection risk: 1-palmitoyl-GPI (mediation proportion = 33.7%, P = 0.018), 1-palmitoyl-2-arachidonoyl-GPI (mediation proportion = 18.3%, P = 0.019), and 1-linoleoyl-2-linolenoyl-GPC (mediation proportion = 20.3%, P = 0.0216). Additionally, 5-Dodecenoylcarnitine (C12:1) mediated the causal effect of genus Sellimonas on the risk of HIV infection (mediation proportion = 13.7%, P = 0.0348). CONCLUSION: Our study revealed that gut microbiota and metabolites causally influence HIV infection risk more substantially than the reverse. We identified the bidirectional causality between 1-palmitoyl-GPI (16:0) and HIV infection, and elucidated four mediation relationships. These findings provide genetic insights into prediction, prevention, and personalized medicine of HIV infection.

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Microbioma Gastrointestinal , Infecciones por VIH , Análisis de la Aleatorización Mendeliana , Humanos , Microbioma Gastrointestinal/genética , Infecciones por VIH/sangre , Análisis de Mediación , Disbiosis , Estudio de Asociación del Genoma Completo , Masculino , Femenino

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Background: Cellular and molecular biology, combined with research on the human microbiome and metabolome, have provided new insights into the pathogenesis of systemic sclerosis (SSc). However, most studies on gut microbiota (GM) and metabolome in SSc are observational studies. The impact of confounding factors and reverse causation leads to different insights. To shed light on this matter, we utilized Mendelian randomization (MR) to determine the causal effect of GM/metabolites on SSc. Methods: Based on summary-level data from genome-wide association studies, bidirectional Two-sample MR was conducted involving 196 GM, 1400 plasma metabolism, and 9,095 SSc. Inverse Variance Weighting (IVW) was mainly used for effect estimation. Results: Forward MR analysis found that three GM and two plasma metabolites are causally related to SSc. IVW results showed Victivallaceae (family) (OR, 1.469; 95%CI, 1.099-1.963; p = 0.009) and LachnospiraceaeUCG004 (genus) (OR, 1.548; 95%CI, 1.020-2.349; p = 0.04) were risk factor of SSc. Conversely, Prevotella7 (genus) (OR, 0.759; 95%CI, 0.578-0.997; p = 0.048)was a protective factor of SSc. The results on plasma metabolites indicated that Pregnenediol disulfate (C21H34O8S2) levels (OR, 1.164; 95%CI, 1.006-1.347; p = 0.041)was a risk factor of SSc, while Sphingomyelin (d18:1/19:0, d19:1/18:0) levels (OR, 0.821; 95%CI, 0.677-0.996; p = 0.045)was a protective factor of SSc. Reverse MR analysis did not find causally relationship between SSc and the above GM/plasma metabolites. Conclusion: Our results revealed the causally effect between GM/plasma metabolites and SSc. These findings provided new insights into the mechanism of SSc. In particular, we demonstrated Prevotella7 was a protective factor of SSc despite its controversial role in SSc in previous researches.

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Background: Despite the potential demonstrated by targeted plasma metabolite modulators in halting the progression of chronic kidney disease (CKD), a lingering uncertainty persists concerning the causal relationship between distinct plasma metabolites and the onset and progression of CKD. Methods: A genome-wide association study was conducted on 1,091 metabolites and 309 metabolite ratios derived from a cohort of 8,299 unrelated individuals of European descent. Employing a bidirectional two-sample Mendelian randomization (MR) analysis in conjunction with colocalization analysis, we systematically investigated the associations between these metabolites and three phenotypes: CKD, creatinine-estimated glomerular filtration rate (creatinine-eGFR), and urine albumin creatinine ratio (UACR). In the MR analysis, the primary analytical approach employed was inverse variance weighting (IVW), and sensitivity analysis was executed utilizing the MR-Egger method and MR-pleiotropy residual sum and outlier (MR-PRESSO). Heterogeneity was carefully evaluated through Cochrane's Q test. To ensure the robustness of our MR results, the leave-one-out method was implemented, and the strength of causal relationships was subjected to scrutiny via Bonferroni correction. Results: Our thorough MR analysis involving 1,400 plasma metabolites and three clinical phenotypes yielded a discerning identification of 21 plasma metabolites significantly associated with diverse outcomes. Specifically, in the forward MR analysis, 6 plasma metabolites were determined to be causally associated with CKD, 16 with creatinine-eGFR, and 7 with UACR. Substantiated by robust evidence from colocalization analysis, 6 plasma metabolites shared causal variants with CKD, 16 with creatinine-eGFR, and 7 with UACR. In the reverse analysis, a diminished creatinine-eGFR was linked to elevated levels of nine plasma metabolites. Notably, no discernible associations were observed between other plasma metabolites and CKD, creatinine-eGFR, and UACR. Importantly, our analysis detected no evidence of horizontal pleiotropy. Conclusion: This study elucidates specific plasma metabolites causally associated with CKD and renal functions, providing potential targets for intervention. These findings contribute to an enriched understanding of the genetic underpinnings of CKD and renal functions, paving the way for precision medicine applications and therapeutic strategies aimed at impeding disease progression.

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Estudio de Asociación del Genoma Completo , Tasa de Filtración Glomerular , Análisis de la Aleatorización Mendeliana , Insuficiencia Renal Crónica , Humanos , Insuficiencia Renal Crónica/sangre , Insuficiencia Renal Crónica/genética , Insuficiencia Renal Crónica/metabolismo , Femenino , Masculino , Creatinina/sangre , Polimorfismo de Nucleótido Simple , Biomarcadores/sangre , Estudios de Cohortes , Riñón/metabolismo , Persona de Mediana Edad

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BACKGROUND: Complex interconnections are evident among gut microbiota, circulating metabolites, inflammatory cytokines, and the pathogenesis of abdominal aortic aneurysms (AAA), with the causal dynamics yet to be comprehensively elucidated. The primary objective of this study was to elucidate the potential causal relationships involving gut microbiota-mediated plasma metabolites, inflammatory cytokines, and AAA. METHODS: We utilized data from genome-wide association studies predominantly comprising individuals of European ancestry, encompassing four major gut microbiota signatures, 233 plasma metabolite signatures (N = 136,016), 91 inflammatory cytokine signatures (N = 14,824), and AAA signatures (N = 1,458,875). Mendelian randomization (MR), employed in a two-sample format, was utilized as a tool to investigate the potential causal pathways from gut microbiota to the development of AAA. Additionally, a two-step MR approach was employed to dissect the impact of plasma metabolites and inflammatory cytokines on the relationship between gut microbiota and AAA and to ascertain the mediated fractions. RESULTS: Our findings indicate that five phylum or family-identical bacteria, 175 plasma metabolites, and seven inflammatory factors are causally associated with AAA. Among them, five bacterial species from the same phylum or family, identified from different GWAS data, were strongly associated with AAA. Of these, two exhibited negative causality and three exhibited positive causality. We found that the phylum Firmicutes and the families Oscillospiraceae might reduce the risk of AAA, whereas the families Prevotellaceae, Sutterellaceae, and Aminobacteriaceae might increase the risk of AAA. Further screening indicated that phylum Firmicutes id.1672 (GCST90017114) may confer a protective effect against AAA by reducing triglyceride levels in medium/small high-density lipoprotein (HDL). CONCLUSION: MR analysis has delineated a causal pathway from gut microbiota, through plasma circulating metabolites and inflammatory cytokines, to the pathogenesis of AAA. The role of intestinal flora and certain biomarkers may provide a reference for the diagnosis of AAA, and contribute to the prevention, diagnosis, and treatment of AAA disease.

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Aneurisma de la Aorta Abdominal , Citocinas , Microbioma Gastrointestinal , Estudio de Asociación del Genoma Completo , Análisis de la Aleatorización Mendeliana , Aneurisma de la Aorta Abdominal/microbiología , Aneurisma de la Aorta Abdominal/sangre , Aneurisma de la Aorta Abdominal/genética , Humanos , Microbioma Gastrointestinal/fisiología , Microbioma Gastrointestinal/genética , Citocinas/sangre , Masculino , Femenino , Inflamación/sangre , Inflamación/genética

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Changes in plasma and fecal metabolomes in colorectal cancer (CRC) progression (normal-adenoma-CRC) remain unclear. Here, plasma and fecal samples were collected from four independent cohorts of 1,251 individuals (422 CRC, 399 colorectal adenoma [CRA], and 430 normal controls [NC]). By metabolomic profiling, signature plasma and fecal metabolites with consistent shift across NC, CRA, and CRC are identified, including CRC-enriched oleic acid and CRC-depleted allocholic acid. Oleic acid exhibits pro-tumorigenic effects in CRC cells, patient-derived organoids, and two murine CRC models, whereas allocholic acid has opposing effects. By integrative analysis, we found that oleic acid or allocholic acid directly binds to α-enolase or farnesoid X receptor-1 in CRC cells, respectively, to modulate cancer-associated pathways. Clinically, we establish a panel of 17 plasma metabolites that accurately diagnoses CRC in a discovery and three validation cohorts (AUC = 0.848-0.987). Overall, we characterize metabolite signatures, mechanistic significance, and diagnostic potential of plasma and fecal metabolomes in CRC.

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Adenoma , Biomarcadores de Tumor , Neoplasias Colorrectales , Progresión de la Enfermedad , Heces , Metabolómica , Humanos , Neoplasias Colorrectales/diagnóstico , Neoplasias Colorrectales/metabolismo , Neoplasias Colorrectales/sangre , Neoplasias Colorrectales/patología , Heces/química , Adenoma/metabolismo , Adenoma/diagnóstico , Adenoma/patología , Adenoma/sangre , Metabolómica/métodos , Animales , Biomarcadores de Tumor/metabolismo , Biomarcadores de Tumor/sangre , Ratones , Masculino , Femenino , Detección Precoz del Cáncer/métodos , Metaboloma , Persona de Mediana Edad , Ácido Oléico/metabolismo , Ácido Oléico/sangre , Anciano

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Background: Numerous research studies have indicated a possible association between type 2 diabetes (T2DM) and gut microbiota. To explore specific metabolic pathways connecting gut microbiota and T2DM, we employed Mendelian randomization (MR) and linkage disequilibrium score regression (LDSC) techniques. Methods: This research utilized data from genome-wide association studies (GWAS) that are publicly accessible. We evaluated the genetic correlation between gut microbiota and T2DM using LDSC. Causality was primarily determined through the inverse variance weighted (IVW) method. To verify the robustness of our results, we conducted sensitivity analyses using several approaches, including the weighted median, MR-Egger, and MR-PRESSO. We integrated summary effect estimates from LDSC, along with forward and reverse MR, into a meta-analysis for T2DM using various data sources. Additionally, mediation analysis was performed to explore the impact of plasma metabolites on the relationship between gut microbiota and T2DM. Results: Our study indicated a significant genetic correlation between genus RuminococcaceaeUCG005 (Rg = -0.26, Rg_P = 2.07×10-4) and T2DM. Moreover, the forward MR analysis identified genus RuminococcaceaeUCG010 (OR = 0.857, 95% CI 0.795, 0.924; P = 6.33×10-5) and order Clostridiales (OR = 0.936, 95% CI 0.878, 0.997; P = 0.039) as being significantly associated with a decreased risk of T2DM. The analysis also highlighted several plasma metabolites as significant mediators in these relationships, with metabolites like octadecadienedioate (C18:2-DC) and branched chain 14:0 dicarboxylic acid being notably involved. Conclusion: The findings demonstrate a significant impact of gut microbiota on T2DM via plasma metabolites, suggesting potential metabolic pathways for therapeutic targeting. This study enhances our understanding of the microbiota's role in T2DM pathogenesis and supports the development of microbiota-based interventions.

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Diabetes Mellitus Tipo 2 , Microbioma Gastrointestinal , Estudio de Asociación del Genoma Completo , Análisis de la Aleatorización Mendeliana , Diabetes Mellitus Tipo 2/microbiología , Diabetes Mellitus Tipo 2/sangre , Diabetes Mellitus Tipo 2/genética , Humanos , Polimorfismo de Nucleótido Simple , Desequilibrio de Ligamiento , Predisposición Genética a la Enfermedad

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Animal health is affected during heat stress as a result of impaired immune responses, increased production of reactive oxygen species, and/or a deficiency of antioxidants. This leads to an imbalance between oxidants and antioxidants and results in oxidative stress. Heat stress is usually measured in dairy cattle via the temperature-humidity index (THI). In the present study, we aimed at assessing the influence of incremental THI on the balance between oxidative markers and the antioxidant defence system in the plasma of Modicana cows. Twenty-four multiparous, mid-lactating dairy cows were divided into two groups on the basis of different levels of mean THI reached in the period of the previous week up until the day of blood and milk sampling (April THI1:55, May THI2:68, June THI3:71, July THI4:80). The blood samples were collected to measure reactive oxygen metabolites (ROM) and antioxidant defense markers (ferric reducing ability of plasma (FRAP), paraoxonase (PON), advanced oxidation protein products (AOPP), plasma thiol groups (SHp), as well as lipid-soluble antioxidant pro-vitamin (ß-carotene) and vitamins (tocopherol and retinol). Milk characteristics, haematological values, and plasma biochemical metabolites were also evaluated. Results showed a significant increase in ROM (p < 0.05) and a significant decrease in PON (p < 0.05), AOPP (p < 0.05), and ß-carotene (p < 0.001). Incremental THI significantly decreased levels of milk fat content, red and white blood cells, plasma glucose, and non-esterified fatty acids, while significantly increasing monocytes and the concentrations of ß-hydroxybutyrate and creatinine, but not fructosamine. The results of the study show that heat stress significantly affects reactive oxygen species production and antioxidant parameters. Carotenoid supplementation should be considered to alleviate the impact of these effects.

RESUMEN

Objective: Osteoporosis, characterized by reduced bone density and heightened fracture risk, is influenced by genetic and environmental factors. This study investigates the interplay between gut microbiota, plasma metabolomics, and osteoporosis, identifying potential causal relationships mediated by plasma metabolites. Methods: Utilizing aggregated genome-wide association studies (GWAS) data, a comprehensive two-sample Mendelian Randomization (MR) analysis was performed involving 196 gut microbiota taxa, 1,400 plasma metabolites, and osteoporosis indicators. Causal relationships between gut microbiota, plasma metabolites, and osteoporosis were explored. Results: The MR analyses revealed ten gut microbiota taxa associated with osteoporosis, with five taxa positively linked to increased risk and five negatively associated. Additionally, 96 plasma metabolites exhibited potential causal relationships with osteoporosis, with 49 showing positive associations and 47 displaying negative associations. Mediation analyses identified six causal pathways connecting gut microbiota to osteoporosis through ten mediating relationships involving seven distinct plasma metabolites, two of which demonstrated suppression effects. Conclusion: This study provides suggestive evidence of genetic correlations and causal links between gut microbiota, plasma metabolites, and osteoporosis. The findings underscore the complex, multifactorial nature of osteoporosis and suggest the potential of gut microbiota and plasma metabolite profiles as biomarkers or therapeutic targets in the management of osteoporosis.

RESUMEN

BACKGROUND: Evidence from cohort studies indicates a bidirectional relationship between periodontal disease and type 2 diabetes (T2D), but the underlying mechanisms remain unknown. In this study, we aimed to (1) identify saliva, plasma, and multifluid metabolomic signatures associated with periodontal disease and (2) determine if these signatures predict T2D progression and cardiometabolic biomarkers at year 3. METHODS AND RESULTS: We included participants from the SOALS (San Juan Overweight Adult Longitudinal Study) (n=911). Metabolites from saliva (k=635) and plasma (k=1051) were quantified using liquid chromatography-mass spectrometry. We applied elastic net regression with 10-fold cross-validation to identify baseline metabolomic signatures of periodontal disease. Multivariable Cox proportional hazards regression and linear regression were used to evaluate the association with T2D progression and biomarker concentrations. Metabolomic profiles included highly weighted metabolites related to lysine and pyrimidine metabolism. Periodontal disease or its 3 metabolomic signatures were not associated with T2D progression in 3 years. Prospectively, 1-SD increments in the multifluid and saliva metabolomic signatures were associated with higher low-density lipoprotein (multifluid: 12.9±5.70, P=0.02; saliva: 13.3±5.11, P=0.009). A 1-SD increment in the plasma metabolomic signature was also associated with Homeostatic Model Assessment for Insulin Resistance (2.67±1.14, P=0.02) and triglyceride (0.52±0.18, P=0.002). CONCLUSIONS: Although metabolomic signatures of periodontal disease could not predict T2D progression, they were associated with low-density lipoprotein, triglyceride, and Homeostatic Model Assessment for Insulin Resistance levels at year 3.

Asunto(s)

Biomarcadores , Diabetes Mellitus Tipo 2 , Progresión de la Enfermedad , Dislipidemias , Metabolómica , Obesidad , Enfermedades Periodontales , Saliva , Humanos , Masculino , Saliva/metabolismo , Saliva/química , Diabetes Mellitus Tipo 2/sangre , Diabetes Mellitus Tipo 2/metabolismo , Diabetes Mellitus Tipo 2/diagnóstico , Femenino , Persona de Mediana Edad , Dislipidemias/sangre , Dislipidemias/epidemiología , Dislipidemias/metabolismo , Dislipidemias/diagnóstico , Biomarcadores/sangre , Enfermedades Periodontales/sangre , Enfermedades Periodontales/metabolismo , Enfermedades Periodontales/diagnóstico , Enfermedades Periodontales/epidemiología , Metabolómica/métodos , Obesidad/sangre , Obesidad/metabolismo , Obesidad/complicaciones , Sobrepeso/sangre , Sobrepeso/metabolismo , Sobrepeso/complicaciones , Glucemia/metabolismo , Glucemia/análisis , Adulto , Hispánicos o Latinos , Estudios Longitudinales , Anciano , Estudios Prospectivos

RESUMEN

Background: Heart failure with reduced ejection fraction (HFrEF) remains a significant public health issue, with the disease advancing despite neurohormonal antagonism. Energetic dysfunction is a likely contributor to residual disease progression, and we have previously reported a strong association of plasma metabolite profiles with survival among patients with HFrEF. However, the genetic and biologic mechanisms that underlie the metabolite-survival association in HFrEF were uncertain. Methods and results: We performed genetic mapping of the key metabolite parameters, followed by mediation analyses of metabolites and genotypes on survival, and genetic pathway analyses. Patients with HFrEF (n = 1,003) in the Henry Ford Pharmacogenomic Registry (HFPGR; 500 self-reported Black/African race patients [AA], 503 self-reported White/European race patients [EA], and 249 deaths over a median of 2.7 years) with genome-wide genotyping and targeted metabolomic profiling of plasma were included. We tested genome-wide association (GWA) of single nucleotide polymorphisms (SNPs) with the prognostic metabolite profile (PMP) and its components; first stratified by race, and then combined via meta-analysis for the entire cohort. Seven independent loci were identified as GWA significant hits in AA patients (3 for PMP and 4 for individual metabolites), one of which was also significant in the entire cohort (rs944469). No genome wide significant hits were found in White/EA patients. Among these SNPs, only rs35792152, (a hit for 3.HBA) tended to be associated with mortality in standard survival analysis (HR = 1.436, p = 0.052). The mediation analyses indicated several significant associations between SNPs, metabolites, and mortality in AA patients. Functional annotation mapping (FUMA) implicated inflammation, DNA metabolic, and mRNA splicing processes. Conclusions: GWAS of key metabolites and survival along with FUMA pathway analysis revealed new candidate genes which unveiled molecular pathways that contribute to HF disease progression via metabolic and energetic abnormalities.

RESUMEN

PURPOSE: As an important component of the microenvironment, the gastric microbiota and its metabolites are associated with tumour occurrence, progression, and metastasis. However, the relationship between the gastric microbiota and the development of gastric cancer is unclear. The present study investigated the role of the gastric mucosa microbiome and metabolites as aetiological factors in gastric carcinogenesis. METHODS: Gastric biopsies from different stomach microhabitats (n = 70) were subjected to 16S rRNA gene sequencing, and blood samples (n = 95) were subjected to untargeted metabolome (gas chromatography‒mass spectrometry, GC‒MS) analyses. The datasets were analysed using various bioinformatics approaches. RESULTS: The microbiota diversity and community composition markedly changed during gastric carcinogenesis. High Helicobacter. pylori colonization modified the overall diversity and composition of the microbiota associated with gastritis and cancer in the stomach. Most importantly, analysis of the functional features of the microbiota revealed that nitrate reductase genes were significantly enriched in the tumoral microbiota, while urease-producing genes were significantly enriched in the microbiota of H. pylori-positive patients. A panel of 81 metabolites was constructed to discriminate gastric cancer patients from gastritis patients, and a panel of 15 metabolites was constructed to discriminate H. pylori-positive patients from H. pylori-negative patients. receiver operator characteristic (ROC) curve analysis identified a series of gastric microbes and plasma metabolites as potential biomarkers of gastric cancer. CONCLUSION: The present study identified a series of signatures that may play important roles in gastric carcinogenesis and have the potential to be used as biomarkers for diagnosis and for the surveillance of gastric cancer patients with minimal invasiveness.

RESUMEN

Background: Recent studies have revealed changes in microbiota constitution and metabolites associated with tumor progression, however, no causal relation between microbiota or metabolites and diffuse large B-cell lymphoma (DLBCL) has yet been reported. Methods: We download a microbiota dataset from the MiBioGen study, a metabolites dataset from the Canadian Longitudinal Study on Aging (CLSA) study, and a DLBCL dataset from Integrative Epidemiology Unit Open genome-wide association study (GWAS) project. Mendelian randomization (MR) analysis was conducted using the R packages, TwoSampleMR and MR-PRESSO. Five MR methods were used: MR-Egger, inverse variance weighting (IVW), weighted median, simple mode, and weighted mode. Reverse MR analyses were also conducted to explore the causal effects of DLBCL on the microbiome, metabolites, and metabolite ratios. Pleiotropy was evaluated by MR Egger regression and MR-PRESSO global analyses, heterogeneity was assessed by Cochran's Q-test, and stability analyzed using the leave-one-out method. Results: 119 microorganisms, 1,091 plasma metabolite, and 309 metabolite ratios were analyzed. According to IVW analysis, five microorganisms were associated with risk of DLBCL. The genera Terrisporobacter (OR: 3.431, p = 0.049) andgenera Oscillibacter (OR: 2.406, p = 0.029) were associated with higher risk of DLBCL. Further, 27 plasma metabolites were identified as having a significant causal relationships with DLBCL, among which citrate levels had the most significant protective causal effect against DLBCL (p = 0.006), while glycosyl-N-tricosanoyl-sphingadienine levels was related to higher risk of DLBCL (p = 0.003). In addition, we identified 19 metabolite ratios with significant causal relationships to DLBCL, of which taurine/glutamate ratio had the most significant protective causal effect (p = 0.005), while the phosphoethanolamine/choline ratio was related to higher risk of DLBCL (p = 0.009). Reverse MR analysis did not reveal any significant causal influence of DLBCL on the above microbiota, metabolites, and metabolite ratios (p > 0.05). Sensitivity analyses revealed no significant heterogeneity or pleiotropy (p > 0.05). Conclusion: We present the first elucidation of the causal influence of microbiota and metabolites on DLBCL using MR methods, providing novel insights for potential targeting of specific microbiota or metabolites to prevent, assist in diagnosis, and treat DLBCL.