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The study of age‐related biomarkers from different biofluids and tissues within the same individual might provide a more comprehensive understanding of age‐related changes within and between compartments as these changes are likely highly interconnected. Understanding age‐related differences by compartments may shed light on the mechanism of their reciprocal interactions, which may contribute to the phenotypic manifestations of aging. To study such possible interactions, we carried out a targeted metabolomic analysis of plasma, skeletal muscle, and urine collected from healthy participants, age 22–92 years, and identified 92, 34, and 35 age‐associated metabolites, respectively. The metabolic pathways that were identified across compartments included inflammation and cellular senescence, microbial metabolism, mitochondrial health, sphingolipid metabolism, lysosomal membrane permeabilization, vascular aging, and kidney function. A targeted metabolomic analysis of plasma, skeletal muscle, and urine from healthy participants was carried out to compare and contrast metabolite changes with aging across and within compartments. The metabolic pathways that were identified included inflammation and cellular senescence, microbial metabolism, mitochondrial health, sphingolipid metabolism, lysosomal membrane permeabilization, vascular aging, and kidney function.

Dietary biomarkers in urine remain elusive when evaluating diet-induced oxidative stress and inflammation. In our previous study, we conducted a randomized controlled crossover trial to compare the short-term (4-weeks) effects of the balanced Korean diet (BKD) with Western diets, including the 2010 dietary guidelines for Americans (2010 DGA) and typical American diet (TAD), on various metabolic indices in obese Korean adults. Building on this work, the current research focuses on the impact of these dietary interventions on oxidative stress (d-ROMs and BAP) and inflammation (CRP, TNF-α, IL-6, IL-1β, MCP-1) biomarkers in serum, and the concurrent urine metabolomes. Each dietary regimen was in silico and experimentally examined for their antioxidant levels using ABTS, DPPH, and FRAP assays, as well as total flavonoid (TFC) and total phenolic (TPC) contents. We assessed post-intervention variations in oxidative stress and inflammation biomarkers in serum, as well as the urine metabolite profiles for the participants ( n  = 48, average age: 41 years). Antioxidant contents and associated total antioxidant capacity (TAC) were significantly higher for the recommended diets (BKD and 2010 DGA) compared to TAD ( p  < 0.05). Butanol extracts from recommended diets (BKD and 2010 DGA) showed significantly higher antioxidant activity compared to TAD in ABTS ( p  < 0.01), DPPH, and FRAP ( p  < 0.05) assays. Consistent results were observed in total phenolic and flavonoid contents, mirroring their respective antioxidant activities. Following the intervention period, oxidative stress & inflammation markers in serum varied marginally, however, the urine metabolite profiles were clearly demarcated for the BKD and Western dietary groups (PC1 = 5.41%). For BKD group, the pre- and post-intervention urine metabolite profiles were clearly segregated (PLS2 = 2.93%). Compared to TAD, urine extracts from the recommended dietary group showed higher abundance of benzoic acid & phenolic derivatives (VIP > 0.7, p  < 0.05). Metabolites associated with oxidative stress were observed higher in the urine samples from Western dietary groups compared to BKD. Urine metabolomics data delineated the post-intervention effects of three dietary interventions which corroborates the respective findings for their effects on metabolic indices.

Aims/hypothesis Metabolomics has opened new avenues for studying metabolic alterations in type 2 diabetes. While many urine and blood metabolites have been associated individually with diabetes, a complete systems view analysis of metabolic dysregulations across multiple biofluids and over varying timescales of glycaemic control is still lacking. Methods Here we report a broad metabolomics study in a clinical setting, covering 2,178 metabolite measures in saliva, blood plasma and urine from 188 individuals with diabetes and 181 controls of Arab and Asian descent. Using multivariate linear regression we identified metabolites associated with diabetes and markers of acute, short-term and long-term glycaemic control. Results Ninety-four metabolite associations with diabetes were identified at a Bonferroni level of significance ( p <  2.3 × 10 −5 ), 16 of which have never been reported. Sixty-five of these diabetes-associated metabolites were associated with at least one marker of glycaemic control in the diabetes group. Using Gaussian graphical modelling, we constructed a metabolic network that links diabetes-associated metabolites from three biofluids across three different timescales of glycaemic control. Conclusions/interpretation Our study reveals a complex network of biochemical dysregulation involving metabolites from different pathways of diabetes pathology, and provides a reference framework for future diabetes studies with metabolic endpoints.

Background Epigenetic age is an estimator of biological age based on DNA methylation; its discrepancy from chronologic age warrants further investigation. We recently reported that greater polyphenol intake benefitted ectopic fats, brain function, and gut microbiota profile, corresponding with elevated urine polyphenols. The effect of polyphenol-rich dietary interventions on biological aging is yet to be determined. Methods We calculated different biological aging epigenetic clocks of different generations (Horvath2013, Hannum2013, Li2018, Horvath skin and blood2018, PhenoAge2018, PCGrimAge2022), their corresponding age and intrinsic age accelerations, and DunedinPACE, all based on DNA methylation (Illumina EPIC array; pre-specified secondary outcome) for 256 participants with abdominal obesity or dyslipidemia, before and after the 18-month DIRECT PLUS randomized controlled trial. Three interventions were assigned: healthy dietary guidelines, a Mediterranean (MED) diet, and a polyphenol-rich, low-red/processed meat Green-MED diet. Both MED groups consumed 28 g walnuts/day (+ 440 mg/day polyphenols). The Green-MED group consumed green tea (3–4 cups/day) and Mankai ( Wolffia globosa strain) 500-ml green shake (+ 800 mg/day polyphenols). Adherence to the Green-MED diet was assessed by questionnaire and urine polyphenols metabolomics (high-performance liquid chromatography quadrupole time of flight). Results Baseline chronological age (51.3 ± 10.6 years) was significantly correlated with all methylation age (mAge) clocks with correlations ranging from 0.83 to 0.95; p  < 2.2e − 16 for all. While all interventions did not differ in terms of changes between mAge clocks, greater Green-Med diet adherence was associated with a lower 18-month relative change (i.e., greater mAge attenuation) in Li and Hannum mAge (beta =  − 0.41, p  = 0.004 and beta =  − 0.38, p  = 0.03, respectively; multivariate models). Greater Li mAge attenuation (multivariate models adjusted for age, sex, baseline mAge, and weight loss) was mostly affected by higher intake of Mankai (beta =  − 1.8; p  = 0.061) and green tea (beta =  − 1.57; p  = 0.0016) and corresponded with elevated urine polyphenols: hydroxytyrosol , tyrosol , and urolithin C ( p  < 0.05 for all) and urolithin A ( p  = 0.08), highly common in green plants. Overall, participants undergoing either MED-style diet had ~ 8.9 months favorable difference between the observed and expected Li mAge at the end of the intervention ( p  = 0.02). Conclusions This study showed that MED and green-MED diets with increased polyphenols intake, such as green tea and Mankai, are inversely associated with biological aging. To the best of our knowledge, this is the first clinical trial to indicate a potential link between polyphenol intake, urine polyphenols, and biological aging. Trial registration ClinicalTrials.gov, NCT03020186.

Abstract Context Metabolites in the tricarboxylic acid (TCA) pathway have pleiotropic functions. Objective To study the association between urine TCA cycle metabolites and the risk for chronic kidney disease progression in individuals with type 2 diabetes. Design, setting and participants A prospective study in a discovery (n = 1826) and a validation (n = 1235) cohort of people with type 2 diabetes in a regional hospital and a primary care facility Exposure and Outcome Urine lactate, pyruvate, citrate, alpha-ketoglutarate, succinate, fumarate, and malate were measured by mass spectrometry. Chronic kidney disease progression was defined as a composite of sustained estimated glomerular filtration rate below 15 mL/min/1.73 m2, dialysis, renal death, or doubling of serum creatinine. Results During a median of 9.2 (interquartile range 8.1-9.7) and 4.0 (3.2-5.1) years of follow-up, 213 and 107 renal events were identified. Cox regression suggested that urine lactate, fumarate, and malate were associated with an increased risk (adjusted hazard ratio, [95% CI] 1.63 [1.16-2.28], 1.82 [1.17-2.82], and 1.49 [1.05-2.11], per SD), whereas citrate was associated with a low risk (aHR 0.83 [0.72-0.96] per SD) for the renal outcome after adjustment for cardiorenal risk factors. These findings were reproducible in the validation cohort. Noteworthy, fumarate and citrate were independently associated with the renal outcome after additional adjustment for other metabolites. Conclusion Urine fumarate and citrate predict the risk for progression to end-stage kidney disease independent of clinical risk factors and other urine metabolites. These 2 metabolites in TCA cycle pathway may play important roles in the pathophysiological network, underpinning progressive loss of kidney function in patients with type 2 diabetes.

Increasing evidence has shown that fecal microbiota transplantation (FMT) could be a promising treatment option for Crohn’s disease (CD). However, the frequency of FMT for CD treatment remains unclear. This study aimed to evaluate the optimal timing for administering the second course of FMT to maintain the long-term clinical effects from the first FMT for patients with CD. Sixty-nine patients with active CD who underwent FMT twice and benefited from the first FMT were enrolled in this study. Clinical response, stool microbiota, and urine metabolome of patients were assessed during the follow-up. The median time of maintaining clinical response to the first FMT in total 69 patients was 125 days (IQR, 82.5–225.5). The time of maintaining clinical response to the second FMT in 56 of 69 patients was 176.5 days (IQR, 98.5–280). The fecal microbiota composition of each patient post the first FMT was closer to that of his/her donor. Compared to that of the baseline, patients prior to the second course of FMT showed significant differences in urinary metabolic profiles characterized by increased indoxyl sulfate, 4-hydroxyphenylacetate, creatinine, dimethylamine, glycylproline, hippurate, and trimethylamine oxide (TMAO). This study demonstrated that patients with CD could be administered the second course of FMT less than 4 months after the first FMT for maintaining the clinical benefits from the first FMT. This was supported by the host–microbial metabolism changes in patients with active CD. Trial registration : ClinicalTrials.gov , NCT01793831. Registered 18 February 2013. https://clinicaltrials.gov/ct2/show/NCT01793831?term=NCT01793831&rank=1

Background The severity of thyroid cancer is judged on the basis of histologic and clinical features. A limited number of studies have considered urinary metabolite signatures for its diagnosis, and no reliable urinary metabolite biomarkers have been proposed. This diagnostic method would be particularly valuable because of its non-invasive nature. Method A nuclear magnetic resonance (NMR)-based metabolomics approach was used as the analytical platform to study the urine samples of patients with PTMC. Urine samples collected from 41 PTMC patients, 52 healthy subjects, and 13 patients with benign tumors were analyzed using 1H-NMR spectroscopy to identify metabolic changes. PLS-DA, or partial least squares discriminant analysis, was used to analyze the NMR spectra. A double cross-validation method and randomization tests were used to validate PLS-DA models. Results Clear discriminations between PTMC patients and healthy controls, as well as between PTMC patients and patients with benign tumors were obtained. Collectively, pi-methyhistidine, trimethylamine, myo-inositol, acetate, suberate, azelate, mannitol, tau-methylhistine, ascorbate, 3-aminoisobutyric acid, 2-oxoglutarate, and methanol contributed to the discrimination. Apart from myo-inositol and methanol, all of these metabolites exhibited increased levels in the urine samples of PTMC patients as compared to that of patients with benign tumors. Conclusions The application of this NMR-based metabolomics approach allowed the detection of anomalous metabolic traits directly connected PTMC, potentially yielding a more sensitive and comprehensive diagnostic results for PTMC.

Liver cirrhosis is one of the most prevalent chronic liver disorders with high mortality. We aimed to explore changed gut microbiome and urine metabolome in compensatory liver cirrhosis (CLC) patients, thus providing novel diagnostic biomarkers for CLC. Forty fecal samples from healthy volunteers (control: 19) and CLC patients (patient: 21) were undertaken 16S rDNA sequencing. Chromatography-mass spectrometry was performed on 40 urine samples (20 controls and 20 patients). Microbiome and metabolome data were separately analyzed using corresponding bioinformatics approaches. The diagnostic model was constructed using the least absolute shrinkage and selection operator regression. The optimal diagnostic model was determined by five-fold cross-validation. Pearson correlation analysis was applied to clarify the relations among the diagnostic markers. 16S rDNA sequencing analyses showed changed overall alpha diversity and beta diversity in patient samples compared with those of controls. Similarly, we identified 841 changed metabolites. Pathway analysis revealed that the differential metabolites were mainly associated with pathways, such as tryptophan metabolism, purine metabolism, and steroid hormone biosynthesis. A 9-maker diagnostic model for CLC was determined, including 7 microorganisms and 2 metabolites. In this model, there were multiple correlations between microorganisms and metabolites. Subdoligranulum , Agathobacter , norank_f_Eubacterium_coprostanoligenes_group , Butyricicoccus , Lachnospiraceae_UCG_004 , and L-2,3-Dihydrodipicolinate were elevated in CLC patients, whereas Blautia , Monoglobus , and 5-Acetamidovalerate were reduced. A novel diagnostic model for CLC was constructed and verified to be reliable, which provides new strategies for the diagnosis and treatment of CLC.

Antarctic expeditions have a high risk of participant depression owing to long stays and isolated environments. By quantifying the stress state and changes in biomolecules over time before the onset of depressive symptoms, predictive markers of depression can be explored. Here, we evaluated the psychological changes in 30 participants in the Japanese Antarctic Research Expedition using the Patient Health Questionnaire-9 (PHQ-9). Urinary samples were collected every three months for a year, and comprehensive urinary metabolomic profiles were quantified using liquid chromatography time-of-flight mass spectrometry. Five participants showed major depressive episodes (PHQ-9 ≥ 10) at 12 months. The urinary metabolites between these participants and the 25 unaffected participants were compared at individual metabolite and pathway levels. The individual comparisons showed the most significant differences at 12 months in 14 metabolites, including ornithine and beta-alanine. Data from shorter stays showed less significant differences. In contrast, pathway and enrichment analyses showed the most significant difference at three months and a less significant difference at longer stays. These time transitions of urinary metabolites could help in the development of urinary biomarkers to detect subjects with depressive episodes at an early stage.

Poncirin (PC) and its aglycone, isosakuranetin (IR), occur naturally in citrus fruits. This study aimed to explore the pathways behind the different health benefits of PC and IR by evaluating the effect of these two bioactive flavonoids on the gut microbial diversity and metabolomics of mice. The 16S rRNA gene sequencing was used to analyze the alteration of gut microbiota in mice after PC and IR intervention. The metabolic impact of PC and IR in mice were studied using a metabolomics approach based on LC-MS analysis. Results showed that, after 7 days intervention, PC and IR multiplied the abundance of Parabacteroides in mice’s intestinal tracts by 1.2 and 1.0 times, respectively. PC increased the abundance of Bacteroides by 2.4 times. IR reduced the Allobaculum abundance by 1.0 time and increased Alloprevotella abundance by 1.5 times. When mice were given PC, their fecal acetic acid level increased by 1.8 times, while their isobutyric and isovaleric acid content increased by 1.2 and 1.3 times, respectively. Supplementation with IR had no significant effect on the content of short-chain fatty acids (SCFAs) in the feces of mice. The potential urine biomarkers of mice in the PC group were involved in the digestion and absorption of protein and carbohydrate, as well as the metabolism of amino acids, such as glycine, serine, threonine, tryptophan, D-arginine, D-ornithine, etc. IR mainly affected the amino acid metabolic pathways in mice, including taurine and hypotaurine metabolism, glutathione metabolism, histidine metabolism, D-glutamate metabolism, etc. This study provided valuable clues for future research on the health promoting mechanisms of PC and IR.