Epigenetic Clock at Birth and Childhood Blood Pressure Trajectory: A Prospective Birth Cohort Study.

BACKGROUND: The impact of methylation gestational age (GAmAge; a biomarker of fetal maturity) at birth on childhood blood pressure (BP) trajectories is unknown. METHODS: This cohort study included 500 boys and 440 girls with data on cord blood DNA methylation and BP at 3 to 15 years of age. Systolic BP (SBP) and diastolic BP percentiles were calculated based on clinical guidelines. Time-series K-means clustering identified 4 distinct SBP and diastolic BP percentile trajectories: high-steady, high-decrease, normal-increase, and normal-steady. GAmAge was estimated using an existing pediatric epigenetic clock. Extrinsic age acceleration was calculated as residuals of associations between GAmAge and chronological gestational age. Intrinsic age acceleration was calculated using the same method adjusting for cord blood cell compositions. RESULTS: Extrinsic age acceleration and intrinsic age acceleration were inversely associated with repeated measures of BP percentiles. Significant inverse associations were observed between extrinsic age acceleration and SBP percentiles in boys (ß=-2.02; P=0.02) but not in girls (ß=-0.49; P=0.58). Both extrinsic age acceleration and intrinsic age acceleration were inversely associated with SBP percentiles in girls born preterm (<37 weeks; ßEAA=-2.95; ßIAA=-3.00; P<0.05). Compared with the normal-steady SBP trajectory, significant inverse associations were observed between intrinsic age acceleration and high-steady, high-decrease, and normal-increase SBP trajectories in boys (odds ratio, 0.73-0.81; P<0.03), and significant positive associations were observed for high-decrease and normal-increase SBP trajectories in girls (odds ratio, 1.26-1.38; P<0.01). Significant sex differences were observed (Psex-interaction<2×10-16). CONCLUSIONS: GAmAge acceleration at birth was inversely associated with child BP, and such association was more pronounced in boys than in girls. Our findings may shed new light on the developmental origins of high BP and sex differences in cardiovascular risk.

Maternal arsenic exposure modifies associations between arsenic, folate and arsenic metabolism gene variants, and spina bifida risk: A case‒control study in Bangladesh.

BACKGROUND: Spina bifida is a type of neural tube defect (NTD); NTDs are developmental malformations of the spinal cord that result from failure of neural tube closure during embryogenesis and are likely caused by interactions between genetic and environmental factors. Arsenic induces NTDs in animal models, and studies demonstrate that mice with genetic defects related to folate metabolism are more susceptible to arsenic's effects. We sought to determine whether 25 single-nucleotide polymorphisms (SNPs) in genes involved in folate and arsenic metabolism modified the associations between maternal arsenic exposure and risk of spina bifida (a common NTD) among a hospital-based case-control study population in Bangladesh. METHODS: We used data from 262 mothers and 220 infants who participated in a case‒control study at the National Institutes of Neurosciences & Hospital and Dhaka Shishu Hospital in Dhaka, Bangladesh. Neurosurgeons assessed infants using physical examinations, review of imaging, and we collected histories using questionnaires. We assessed arsenic from mothers' toenails using inductively coupled plasma mass spectrometry (ICP-MS), and we genotyped participants using the Illumina Global Screening Array v1.0. We chose candidate genes and SNPs through a review of the literature. We assessed SNP-environment interactions using interaction terms and stratified models, and we assessed gene-environment interactions using interaction sequence/SNP-set kernel association tests (iSKAT). RESULTS: The median toenail arsenic concentration was 0.42 µg/g (interquartile range [IQR]: 0.27-0.86) among mothers of cases and 0.47 µg/g (IQR: 0.30-0.97) among mothers of controls. We found an two SNPs in the infants' AS3MT gene (rs11191454 and rs7085104) and one SNP in mothers' DNMT1 gene (rs2228611) were associated with increased odds of spina bifida in the setting of high arsenic exposure (rs11191454, OR 3.01, 95% CI: 1.28-7.09; rs7085104, OR 2.33, 95% CI: 1.20-4.and rs2228611, OR 2.11, 95% CI: 1.11-4.01), along with significant SNP-arsenic interactions. iSKAT analyses revealed significant interactions between mothers' toenail concentrations and infants' AS3MT and MTR genes (p = 0.02), and mothers' CBS gene (p = 0.05). CONCLUSIONS: Our results support the hypothesis that arsenic increases spina bifida risk via interactions with folate and arsenic metabolic pathways and suggests that individuals in the population who have certain genetic polymorphisms in genes involved with arsenic and folate metabolism may be more susceptible than others to the arsenic teratogenicity.

Integration of epidemiological and blood biomarker analysis links haem iron intake to increased type 2 diabetes risk.

Dietary haem iron intake is linked to an increased risk of type 2 diabetes (T2D), but the underlying plasma biomarkers are not well understood. We analysed data from 204,615 participants (79% females) in three large US cohorts over up to 36 years, examining the associations between iron intake and T2D risk. We also assessed plasma metabolic biomarkers and metabolomic profiles in subsets of 37,544 (82% females) and 9,024 (84% females) participants, respectively. Here we show that haem iron intake but not non-haem iron is associated with a higher T2D risk, with a multivariable-adjusted hazard ratio of 1.26 (95% confidence interval 1.20-1.33; P for trend <0.001) comparing the highest to the lowest quintiles. Haem iron accounts for significant proportions of the T2D risk linked to unprocessed red meat and specific dietary patterns. Increased haem iron intake correlates with unfavourable plasma profiles of insulinaemia, lipids, inflammation and T2D-linked metabolites. We also identify metabolites, including L-valine and uric acid, potentially mediating the haem iron-T2D relationship, highlighting their pivotal role in T2D pathogenesis.

Branched-Chain and Aromatic Amino Acids, Type 2 Diabetes, and Cardiometabolic Risk Factors among Puerto Rican Adults.

(1) Background: Branched-chain and aromatic amino acids (BCAAs/AAAs) have been considered as markers of type 2 diabetes (T2D); however, studies on associations between these metabolites and T2D and cardiometabolic traits in Hispanic populations are limited. The aim of this study was to examine the associations between baseline BCAAs (isoleucine, leucine, valine)/AAAs (phenylalanine, tyrosine) and prevalent and incident T2D, as well as baseline and longitudinal (2 year) changes in cardiometabolic traits (measures of glycemia, dyslipidemia, inflammation, and obesity) in two large cohorts of adults of Puerto Rican descent. (2) Methods: We included participants of the Boston Puerto Rican Health Study (BPRHS, n = 670) and San Juan Overweight Adult Longitudinal study (SOALS, n = 999) with available baseline metabolite and covariate data. T2D diagnosis was defined based on American Diabetes Association criteria. Multivariable logistic (for baseline T2D), Poisson (for incident T2D), and linear (for cardiometabolic traits) regression models were used; cohort-specific results were combined in the meta-analysis and adjusted for multiple comparisons. (3) Results: Higher baseline BCAAs were associated with higher odds of prevalent T2D (OR1SD BCAA score = 1.46, 95% CI: 1.34-1.59, p < 0.0001) and higher risk of incident T2D (IRR1SD BCAA score = 1.24, 95% CI: 1.13-1.37, p < 0.0001). In multivariable longitudinal analysis, higher leucine and valine concentrations were associated with 2-year increase in insulin (beta 1SD leucine = 0.37 mcU/mL, 95% CI: 0.11-0.63, p < 0.05; beta 1SD valine = 0.43 mcU/mL, 95% CI: 0.17-0.68, p < 0.01). Tyrosine was a significant predictor of incident T2D (IRR = 1.31, 95% CI: 1.09-1.58, p < 0.05), as well as 2 year increases in HOMA-IR (beta 1SD tyrosine = 0.13, 95% CI: 0.04-0.22, p < 0.05) and insulin concentrations (beta 1SD tyrosine = 0.37 mcU/mL, 95% CI: 0.12-0.61, p < 0.05). (4) Conclusions: Our results confirmed the associations between BCAAs and prevalent and incident T2D, as well as concurrent measures of glycemia, dyslipidemia, and obesity, previously reported in predominantly White and Asian populations. Baseline leucine, valine, and tyrosine were predictors of 2 year increases in insulin, whereas tyrosine was a significant predictor of deteriorating insulin resistance over time. Our study suggests that BCAAs and tyrosine could serve as early markers of future glycemic changes in Puerto Ricans.

The MIND diet, brain transcriptomic alterations, and dementia.

INTRODUCTION: Dietary patterns are associated with dementia risk, but the underlying molecular mechanisms are largely unknown. METHODS: We used RNA sequencing data from post mortem prefrontal cortex tissue and annual cognitive evaluations from 1204 participants in the Religious Orders Study and Memory and Aging Project. We identified a transcriptomic profile correlated with the MIND diet (Mediterranean-Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay) among 482 individuals who completed ante mortem food frequency questionnaires; and examined its associations with cognitive health in the remaining 722 participants. RESULTS: We identified a transcriptomic profile, consisting of 50 genes, correlated with the MIND diet score (p = 0.001). Each standard deviation increase in the transcriptomic profile score was associated with a slower annual rate of decline in global cognition (ß = 0.011, p = 0.003) and lower odds of dementia (odds ratio = 0.76, p = 0.0002). Expressions of several genes (including TCIM and IGSF5) appeared to mediate the association between MIND diet and dementia. DISCUSSION: A brain transcriptomic profile for healthy diets revealed novel genes potentially associated with cognitive health. HIGHLIGHTS: Why healthy dietary patterns are associated with lower dementia risk are unknown. We integrated dietary, brain transcriptomic, and cognitive data in older adults. Mediterranean-Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay (MIND) diet intake is correlated with a specific brain transcriptomic profile. This brain transcriptomic profile score is associated with better cognitive health. More data are needed to elucidate the causality and functionality of identified genes.

Saliva, Plasma, and Multifluid Metabolomic Signatures of Periodontal Disease, Type 2 Diabetes Progression, and Markers of Glycemia and Dyslipidemia Among Puerto Rican Adults With Overweight and Obesity.

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.

Exploring the association between type 2 diabetes and fecal incontinence in american adults: insights from a large cross-sectional study.

BACKGROUND: The relationship between fecal incontinence (FI) and type 2 diabetes (T2D) has been well recognized, but a comprehensive understanding of this relationship is lacking, taking into account demographic factors and lifestyle variables. METHODS: Using a cross-sectional approach, 13,510 adults aged 20 years and older were identified from the 2005-2010 National Health and Nutrition Examination Survey. Multivariate logistic regression models were used to calculate the adjusted odds ratios (ORs), and further subgroup analyses and propensity score analysis were performed to ensure stable results. RESULTS: Among 13,510 adults, 11.2% had T2D, and 8.8% had FI. We found a strong T2D-FI link (OR: 1.30; 95% CI: 1.09-1.54, P < 0.001), even after adjusting for covariates. Age > 45 was a critical factor, with a stronger T2D-FI association. Sedentary behavior (OR: 1.41; 95% CI: 1.15-1.73) in T2D patients were associated with FI. CONCLUSIONS: Our study highlights the significant T2D-FI link in US adults, especially in older T2D patients. Lifestyle changes may reduce FI risk. More research is needed for causality and mechanisms.

Metabolite Profiles of Plant-Based Diets and Cardiometabolic Risk in the Mediators of Atherosclerosis in South Asians Living in America Study.

BACKGROUND: Healthy plant-based diets have been associated with lower risk of type 2 diabetes (T2D). Metabolomics can be leveraged to identify potential pathways through which diet influences disease risk. OBJECTIVES: This study aimed to identify profiles of serum metabolites reflective of plant-based diets of varying quality and examine associations with cardiometabolic risk and T2D. METHODS: We included data from 687 participants of the Mediators of Atherosclerosis in South Asians Living in America (MASALA) cohort. An overall plant-based diet index (PDI), healthy PDI (hPDI), and unhealthy PDI (uPDI) were estimated from food frequency questionnaires. Serum metabolites were assayed using ultraperformance liquid chromatography mass spectrometry. Elastic net regression was used to identify sets of metabolites predictive of each diet index, and metabolite profile scores were calculated as the weighted sum of the selected metabolites. Cross-sectional associations between metabolite profile scores and cardiometabolic measures and prospective associations with incident T2D were evaluated with multivariable-adjusted linear and logistic regressions. RESULTS: Metabolite profiles for PDI, hPDI, and uPDI consisted of n = 51, 55, and 45 metabolites, respectively. Metabolites strongly positively correlated with diet indices included phosphatidylcholine (16:0/18:3) for PDI, phosphatidylethanolamine (20:1/20:4) and pantothenate for hPDI, and lysophosphatidylglycerol (18:2/0:0), proline, and lauric acid for uPDI. Higher metabolite profile scores for PDI and hPDI were associated with lower glycemia and lipids measures, whereas a higher uPDI metabolite score was associated with higher triglycerides and lower low density lipoprotein cholesterol and high density lipoprotein cholesterol. A higher metabolite score for hPDI was additionally associated with lower adiposity measures, higher liver fat attenuation, higher adiponectin, lower odds of overweight (odds ratio [OR]: 0.64; 95% confidence interval [CI]: 0.51, 0.81) and obesity (OR: 0.59; 95% CI: 0.48, 0.74), and lower odds of incident T2D (OR: 0.66; 95% CI: 0.45, 0.97). CONCLUSIONS: Metabolite profiles of different plant-based diets were identified. Metabolite profiles of overall and healthy plant-based diets were associated with favorable cardiometabolic risk profiles.

Arsenic modifies the effect of folic acid in spina bifida prevention, a large hospital-based case-control study in Bangladesh.

BACKGROUND: Spina bifida, a developmental malformation of the spinal cord, is associated with high rates of mortality and disability. Although folic acid-based preventive strategies have been successful in reducing rates of spina bifida, some areas continue to be at higher risk because of chemical exposures. Bangladesh has high arsenic exposures through contaminated drinking water and high rates of spina bifida. This study examines the relationships between mother's arsenic exposure, folic acid, and spina bifida risk in Bangladesh. METHODS: We conducted a hospital-based case-control study at the National Institute of Neurosciences & Hospital (NINS&H) in Dhaka, Bangladesh, between December 2016 and December 2022. Cases were infants under age one year with spina bifida and further classified by a neurosurgeon and imaging. Controls were drawn from children seen at NINS&H and nearby Dhaka Shishu Hospital. Mothers reported folic acid use during pregnancy, and we assessed folate status with serum assays. Arsenic exposure was estimated in drinking water using graphite furnace atomic absorption spectrophotometry (GF-AAS) and in toenails using inductively coupled plasma mass spectrometry (ICP-MS). We used logistic regression to examine the associations between arsenic and spina bifida. We used stratified models to examine the associations between folic acid and spina bifida at different levels of arsenic exposure. RESULTS: We evaluated data from 294 cases of spina bifida and 163 controls. We did not find a main effect of mother's arsenic exposure on spina bifida risk. However, in stratified analyses, folic acid use was associated with lower odds of spina bifida (adjusted odds ratio [OR]: 0.50, 95% confidence interval [CI]: 0.25-1.00, p = 0.05) among women with toenail arsenic concentrations below the median value of 0.46 µg/g, and no association was seen among mothers with toenail arsenic concentrations higher than 0.46 µg/g (adjusted OR: 1.09, 95% CI: 0.52-2.29, p = 0.82). CONCLUSIONS: Mother's arsenic exposure modified the protective association of folic acid with spina bifida. Increased surveillance and additional preventive strategies, such as folic acid fortification and reduction of arsenic, are needed in areas of high arsenic exposure.

Calibration of citrus intake assessed by food frequency questionnaires using urinary proline betaine in an observational study setting.

BACKGROUND: Whether observational study can be employed to establish calibration equations for self-reported dietary intake using food biomarkers is unknown. OBJECTIVES: This study aims to demonstrate the feasibility of obtaining calibration equations based on food biomarkers and 7-d diet records (7DDRs) to correct measurement errors of food frequency questionnaires (FFQs) in an observational study setting. METHODS: The study population consisted of 669 males and 749 females from the Women's and Men's Lifestyle Validation Studies. In the training set, the biomarker-predicted intake derived by regressing 7DDR-assessed intake on urinary proline betaine concentration was regressed on the FFQ-assessed intake to obtain the calibration equations. The regression coefficients were applied to the test set to calculate the calibrated FFQ intake. We examined total citrus as well as individual citrus fruits/beverages. RESULTS: Urinary proline betaine was moderately correlated with orange juice intake (Pearson correlation [r] = 0.53 for 7DDR and 0.48 for FFQ) but only weakly correlated with intakes of orange (r = 0.12 for 7DDR and 0.15 for FFQ) and grapefruit (r = 0.14 for 7DDR and 0.09 for FFQ). The FFQ-assessed citrus intake was systematically higher than the 7DDR-assessed intake, and after calibrations, the mean calibrated FFQ measurements were almost identical to 7DDR assessments. In the test set, the mean intake levels from 7DDRs, FFQs, and calibrated FFQs were 62.5, 75.3, and 63.2 g/d for total citrus; 41.6, 42.5, and 41.9 g/d for orange juice; 11.8, 24.3, and 12.3 g/d for oranges; and 8.3, 9.3, and 8.6 g/d for grapefruit, respectively. We observed larger differences between calibrated FFQ and 7DDR assessments at the extreme ends of intake, although, on average, good agreements were observed for all citrus except grapefruit. CONCLUSIONS: Our 2-step calibration approach has the potential to be adapted to correct systematic measurement error for other foods/nutrients with established food biomarkers in a cost effective way.

24-h urinary sodium and potassium excretions, plasma metabolomic profiles, and cardiometabolic biomarkers in the United States adults: a cross-sectional study.

BACKGROUND: High-sodium and low-potassium intakes are associated with a higher risk of hypertension and cardiovascular disease, but there are limited data on the circulating metabolomics profiles of 24-h urinary sodium and potassium excretions in free-living individuals. OBJECTIVES: We aimed to characterize the metabolomics signatures of a high-sodium and low-potassium diet in a cross-sectional study. METHODS: In 1028 healthy older adults from the Women's and Men's Lifestyle Validation Studies, we investigated the association of habitual sodium and potassium intakes measured by 2 to 4 24-h urine samples with plasma metabolites (quantified using liquid chromatography-tandem mass spectrometry) and metabolomic pathways. Our primary exposures were energy-adjusted 24-h urinary sodium excretion, potassium excretion, and sodium-to-potassium ratio, calculated based on energy expenditure derived from the doubly labeled water method. We then assessed the partial correlations of their metabolomics scores, derived from elastic net regressions, with cardiometabolic biomarkers. RESULTS: Higher sodium excretion was associated with 38 metabolites including higher piperine, phosphatidylethanolamine, and C5:1 carnitine. In pathway analysis, higher sodium excretion was associated with enhanced biotin and propanoate metabolism and enhanced degradation of lysine and branched-chain amino acids (BCAAs). Metabolites associated with higher potassium and lower sodium-to-potassium ratio included quinic acid and proline-betaine. After adjusting for confounding factors, the metabolomics score for sodium-to-potassium ratio positively correlated with fasting insulin (Spearman's rank correlation coefficient ρ = 0.27), C-peptide (ρ = 0.30), and triglyceride (ρ = 0.46), and negatively with adiponectin (ρ = -0.40), and high-density lipoprotein cholesterol (ρ = -0.42). CONCLUSIONS: We discovered metabolites and metabolomics pathways associated with a high-sodium diet, including metabolites related to biotin, propanoate, lysine, and BCAA pathways. The metabolomics signature for a higher sodium low-potassium diet is associated with multiple components of elevated cardiometabolic risk.

MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data.

Leveraging data from multiple ancestries can greatly improve fine-mapping power due to differences in linkage disequilibrium and allele frequencies. We propose MultiSuSiE, an extension of the sum of single effects model (SuSiE) to multiple ancestries that allows causal effect sizes to vary across ancestries based on a multivariate normal prior informed by empirical data. We evaluated MultiSuSiE via simulations and analyses of 14 quantitative traits leveraging whole-genome sequencing data in 47k African-ancestry and 94k European-ancestry individuals from All of Us. In simulations, MultiSuSiE applied to Afr47k+Eur47k was well-calibrated and attained higher power than SuSiE applied to Eur94k; interestingly, higher causal variant PIPs in Afr47k compared to Eur47k were entirely explained by differences in the extent of LD quantified by LD 4th moments. Compared to very recently proposed multi-ancestry fine-mapping methods, MultiSuSiE attained higher power and/or much lower computational costs, making the analysis of large-scale All of Us data feasible. In real trait analyses, MultiSuSiE applied to Afr47k+Eur94k identified 579 fine-mapped variants with PIP > 0.5, and MultiSuSiE applied to Afr47k+Eur47k identified 44% more fine-mapped variants with PIP > 0.5 than SuSiE applied to Eur94k. We validated MultiSuSiE results for real traits via functional enrichment of fine-mapped variants. We highlight several examples where MultiSuSiE implicates well-studied or biologically plausible fine-mapped variants that were not implicated by other methods.

Regulation of vascular remodeling by immune microenvironment after the establishment of autologous arteriovenous fistula in ESRD patients.

Autogenous arteriovenous fistula (AVF) is the preferred dialysis access for receiving hemodialysis treatment in end-stage renal disease patients. After AVF is established, vascular remodeling occurs in order to adapt to hemodynamic changes. Uremia toxins, surgical injury, blood flow changes and other factors can induce inflammatory response, immune microenvironment changes, and play an important role in the maintenance of AVF vascular remodeling. This process involves the infiltration of pro-inflammatory and anti-inflammatory immune cells and the secretion of cytokines. Pro-inflammatory and anti-inflammatory immune cells include neutrophil (NEUT), dendritic cell (DC), T lymphocyte, macrophage (Mφ), etc. This article reviews the latest research progress and focuses on the role of immune microenvironment changes in vascular remodeling of AVF, in order to provide a new theoretical basis for the prevention and treatment of AVF failure.

Metabolomic-derived endotypes of age-related macular degeneration (AMD): a step towards identification of disease subgroups.

Age-related macular degeneration (AMD) is a leading cause of blindness worldwide, with a complex pathophysiology and phenotypic diversity. Here, we apply Similarity Network Fusion (SNF) to cluster AMD patients into putative metabolomics-derived endotypes. Using a discovery cohort of 163 AMD patients from Boston, US, and a validation cohort of 214 patients from Coimbra, Portugal, we identified four distinct metabolomics-derived endotypes with varying retinal structural and functional characteristics, confirmed across both cohorts. Patients clustered into Endotype 1 exhibited a milder form of AMD and were characterized by low levels of amino acids in specific metabolic pathways. Meanwhile, patients clustered into both Endotype 3 and 4 were associated with more severe AMD and exhibited low levels of fatty acid metabolites and elevated levels of sphingomyelins and fatty acid metabolites, respectively. These preliminary findings indicate that metabolomics-derived endotyping may offer a refined strategy for categorizing AMD patients based on their specific pathophysiological underpinnings, rather than relying solely on traditional observational clinical indicators.

Discovery and validation of plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance and diabetes progression or regression among Puerto Rican adults.

AIMS/HYPOTHESIS: Many studies have examined the relationship between plasma metabolites and type 2 diabetes progression, but few have explored saliva and multi-fluid metabolites. METHODS: We used LC/MS to measure plasma (n=1051) and saliva (n=635) metabolites among Puerto Rican adults from the San Juan Overweight Adults Longitudinal Study. We used elastic net regression to identify plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting baseline HOMA-IR in a training set (n=509) and validated these scores in a testing set (n=340). We used multivariable Cox proportional hazards models to estimate HRs for the association of baseline metabolomic scores predicting insulin resistance with incident type 2 diabetes (n=54) and prediabetes (characterised by impaired glucose tolerance, impaired fasting glucose and/or high HbA1c) (n=130) at 3 years, along with regression from prediabetes to normoglycaemia (n=122), adjusting for traditional diabetes-related risk factors. RESULTS: Plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance included highly weighted metabolites from fructose, tyrosine, lipid and amino acid metabolism. Each SD increase in the plasma (HR 1.99 [95% CI 1.18, 3.38]; p=0.01) and multi-fluid (1.80 [1.06, 3.07]; p=0.03) metabolomic scores was associated with higher risk of type 2 diabetes. The saliva metabolomic score was associated with incident prediabetes (1.48 [1.17, 1.86]; p=0.001). All three metabolomic scores were significantly associated with lower likelihood of regressing from prediabetes to normoglycaemia in models adjusting for adiposity (HRs 0.72 for plasma, 0.78 for saliva and 0.72 for multi-fluid), but associations were attenuated when adjusting for lipid and glycaemic measures. CONCLUSIONS/INTERPRETATION: The plasma metabolomic score predicting insulin resistance was more strongly associated with incident type 2 diabetes than the saliva metabolomic score. Only the saliva metabolomic score was associated with incident prediabetes.

Association of Gut Microbiota-Related Metabolites and Type 2 Diabetes in Two Puerto Rican Cohorts.

(1) Aims: Gut microbiota metabolites may play integral roles in human metabolism and disease progression. However, evidence for associations between metabolites and cardiometabolic risk factors is sparse, especially in high-risk Hispanic populations. We aimed to evaluate the cross-sectional and longitudinal relationships between gut microbiota related metabolites and measures of glycemia, dyslipidemia, adiposity, and incident type 2 diabetes in two Hispanic observational cohorts. (2) Methods: We included data from 670 participants of the Boston Puerto Rican Health Study (BPRHS) and 999 participants of the San Juan Overweight Adult Longitudinal Study (SOALS). Questionnaires and clinical examinations were conducted over 3 years of follow-up for SOALS and 6 years of follow-up for BPRHS. Plasma metabolites, including L-carnitine, betaine, choline, and trimethylamine N-oxide (TMAO), were measured at baseline in both studies. We used multivariable linear models to evaluate the associations between metabolites and cardiometabolic risk factors and multivariable logistic and Poisson regressions to assess associations with prevalent and incident type 2 diabetes, adjusted for potential confounding factors. Cohort-specific analyses were combined using a fixed-effects meta-analysis. (3) Results: Higher plasma betaine was prospectively associated with lower fasting glucose [-0.97 mg/dL (95% CI: -1.59, -0.34), p = 0.002], lower HbA1c [-0.02% (95% CI: -0.04, -0.01), p = 0.01], lower HOMA-IR [-0.14 (95% CI: -0.23, -0.05), p = 0.003], and lower fasting insulin [-0.27 mcU/mL (95% CI: -0.51, -0.03), p = 0.02]. Betaine was also associated with a 22% lower incidence of type 2 diabetes (IRR: 0.78, 95% CI: 0.65, 0.95). L-carnitine was associated with lower fasting glucose [-0.68 mg/dL (95% CI: -1.29, -0.07), p = 0.03] and lower HbA1c at follow-up [-0.03% (95% CI: -0.05, -0.01), p < 0.001], while TMAO was associated with higher fasting glucose [0.83 mg/dL (95% CI: 0.22, 1.44), p = 0.01] and higher triglycerides [3.52 mg/dL (95% CI: 1.83, 5.20), p < 0.0001]. Neither choline nor TMAO were associated with incident type 2 diabetes. (4) Conclusions: Higher plasma betaine showed consistent associations with a lower risk of glycemia, insulinemia, and type 2 diabetes. However, TMAO, a metabolite of betaine, was associated with higher glucose and lipid concentrations. These observations demonstrate the importance of gut microbiota metabolites for human cardiometabolic health.

Effect of 1-year lifestyle intervention with energy-reduced Mediterranean diet and physical activity promotion on the gut metabolome and microbiota: a randomized clinical trial.

BACKGROUND: The health benefits of the Mediterranean diet (MedDiet) have been linked to the presence of beneficial gut microbes and related metabolites. However, its impact on the fecal metabolome remains poorly understood. OBJECTIVES: Our goal was to investigate the weight-loss effects of a 1-y lifestyle intervention based on an energy-reduced MedDiet coupled with physical activity (intervention group), compared with an ad libitum MedDiet (control group), on fecal metabolites, fecal microbiota, and their potential association with cardiovascular disease risk factors. METHODS: A total of 400 participants (200 from each study group), aged 55-75 y, and at high cardiovascular disease risk, were included. Dietary and lifestyle information, anthropometric measurements, blood biochemical parameters, and stool samples were collected at baseline and after 1 y of follow-up. Liquid chromatography-tandem mass spectrometry was used to profile endogenous fecal metabolites, and 16S amplicon sequencing was employed to profile the fecal microbiota. RESULTS: Compared with the control group, the intervention group exhibited greater weight loss and improvement in various cardiovascular disease risk factors. We identified intervention effects on 4 stool metabolites and subnetworks primarily composed of bile acids, ceramides, and sphingosines, fatty acids, carnitines, nucleotides, and metabolites of purine and the Krebs cycle. Some of these were associated with changes in several cardiovascular disease risk factors. In addition, we observed a reduction in the abundance of the genera Eubacterium hallii group and Dorea, and an increase in alpha diversity in the intervention group after 1 y of follow-up. Changes in the intervention-related microbiota profiles were also associated with alterations in different fecal metabolite subnetworks and some cardiovascular disease risk factors. CONCLUSIONS: An intervention based on an energy-reduced MedDiet and physical activity promotion, compared with an ad libitum MedDiet, was associated with improvements in cardiometabolic risk factors, potentially through modulation of the fecal microbiota and metabolome. This trial was registered at https://www.isrctn.com/ as ISRCTN89898870 (https://doi.org/10.1186/ISRCTN89898870).

Multidisciplinary approach combining food metabolomics and epidemiology identifies meglutol as an important bioactive metabolite in tempe, an Indonesian fermented food.

This study introduces a multidisciplinary approach to investigate bioactive food metabolites often overlooked due to their low concentrations. We integrated an in-house food metabolite library (n = 494), a human metabolite library (n = 891) from epidemiological studies, and metabolite pharmacological databases to screen for food metabolites with potential bioactivity. We identified six potential metabolites, including meglutol (3-hydroxy-3-methylglutarate), an understudied low-density lipoprotein (LDL)-lowering compound. We further focused on meglutol as a case study to showcase the range of characterizations achievable with this approach. Green pea tempe was identified to contain the highest meglutol concentration (21.8 ± 4.6 mg/100 g). Furthermore, we identified a significant cross-sectional association between plasma meglutol (per 1-standard deviation) and lower LDL cholesterol in two Hispanic adult cohorts (n = 1,628) (ß [standard error]: -5.5 (1.6) mg/dl, P = 0.0005). These findings highlight how multidisciplinary metabolomics can serve as a systematic tool for discovering and enhancing bioactive metabolites in food, such as meglutol, with potential applications in personalized dietary approaches for disease prevention.