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Background: We recently reported that Mediterranean (MED) and green-MED diets significantly attenuated age-related brain atrophy by ∼50% within 18 mo., Objective: The objective of this study was to explore the contribution of specific diet-induced parameters to brain-volume deviation from chronologic age., Methods: A post hoc analysis of the 18-mo DIRECT PLUS trial, where participants were randomly assigned to the following groups: 1) healthy dietary guidelines, 2) MED diet, or 3) green-MED diet, high in polyphenols, and low in red meat. Both MED groups consumed 28 g walnuts/d (+440 mg/d polyphenols). The green-MED group further consumed green tea (3-4 cups/d) and Mankai green shake (Wolffia globosa aquatic plant) (+800 mg/d polyphenols). We collected blood samples through the intervention and followed brain structure volumes by magnetic resonance imaging (MRI). We used hippocampal occupancy (HOC) score (hippocampal and inferior lateral-ventricle volumes ratio) as a neurodegeneration marker and brain-age proxy. We applied multivariate linear regression models., Results: Of 284 participants [88% male; age = 51.1 y; body mass index = 31.2 kg/m 2 ; hemoglobin A1c (HbA1c) = 5.48%; APOE-ε4 genotype = 15.7%], 224 completed the trial with eligible whole-brain MRIs. Individuals with higher HOC deviations (i.e., younger brain age) presented lower body weight [r = -0.204; 95% confidence interval (CI): -0.298, -0.101], waist circumference (r = -0.207; 95% CI: -0.310, -0.103), diastolic (r = -0.186; 95% CI: -0.304, -0.072), systolic blood pressure (r = -0.189; 95% CI: -0.308, -0.061), insulin (r = -0.099; 95% CI: -0.194, -0.004), and HbA1c (r = -0.164; 95% CI: -0.337, -0.006) levels. After 18 mo, greater changes in HOC deviations (i.e., brain-age decline attenuation) were independently associated with improved HbA1c (β = -0.254; 95% CI: -0.392, -0.117), HOMA-IR (β = -0.200; 95% CI: -0.346, -0.055), fasting glucose (β = -0.155; 95% CI: -0.293, -0.016), and c-reactive protein (β = -0.153; 95% CI: -0.296, -0.010). Improvement in diabetes status was associated with greater HOC deviation changes than either no change in diabetes status (0.010; 95% CI: 0.002, 0.019) or with an unfavorable change (0.012; 95% CI: 0.002, 0.023). A decline in HbA1c was further associated with greater deviation changes in the thalamus, caudate nucleus, and cerebellum (P < 0.05). Greater consumption of Mankai and green tea (green-MED diet components) were associated with greater HOC deviation changes beyond weight loss., Conclusions: Glycemic control contributes to the neuroprotective effects of the MED and green-MED diets on brain age. Polyphenols-rich diet components as Mankai and green tea may contribute to a more youthful brain age. This trial was registered at clinicaltrials.gov at clinicaltrials.gov as NCT03020186., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

The association of gut microbial features with type 2 diabetes (T2D) has been inconsistent due in part to the complexity of this disease and variation in study design. Even in cases in which individual microbial species have been associated with T2D, mechanisms have been unable to be attributed to these associations based on specific microbial strains. We conducted a comprehensive study of the T2D microbiome, analyzing 8,117 shotgun metagenomes from 10 cohorts of individuals with T2D, prediabetes, and normoglycemic status in the United States, Europe, Israel and China. Dysbiosis in 19 phylogenetically diverse species was associated with T2D (false discovery rate < 0.10), for example, enriched Clostridium bolteae and depleted Butyrivibrio crossotus. These microorganisms also contributed to community-level functional changes potentially underlying T2D pathogenesis, for example, perturbations in glucose metabolism. Our study identifies within-species phylogenetic diversity for strains of 27 species that explain inter-individual differences in T2D risk, such as Eubacterium rectale. In some cases, these were explained by strain-specific gene carriage, including loci involved in various mechanisms of horizontal gene transfer and novel biological processes underlying metabolic risk, for example, quorum sensing. In summary, our study provides robust cross-cohort microbial signatures in a strain-resolved manner and offers new mechanistic insights into T2D., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Objective: The objective of this study was to explore the effects of a green Mediterranean (green-MED) diet, which is high in dietary polyphenols and green plant-based protein and low in red/processed meat, on cardiovascular disease and inflammation-related circulating proteins and their associations with cardiometabolic risk parameters., Methods: In the 18-month weight loss trial Dietary Intervention Randomized Controlled Trial Polyphenols Unprocessed Study (DIRECT-PLUS), 294 participants with abdominal obesity were randomized to basic healthy dietary guidelines, Mediterranean (MED), or green-MED diets. Both isocaloric MED diet groups consumed walnuts (28 g/day), and the green-MED diet group also consumed green tea (3-4 cups/day) and green shakes (Mankai plant shake, 500 mL/day) and avoided red/processed meat. Proteome panels were measured at three time points using Olink CVDII., Results: At baseline, a dominant protein cluster was significantly related to higher phenotypic cardiometabolic risk parameters, with the strongest associations attributed to magnetic resonance imaging-assessed visceral adiposity (false discovery rate of 5%). Overall, after 6 months of intervention, both the MED and green-MED diets induced improvements in cardiovascular disease and proinflammatory risk proteins (p < 0.05, vs. healthy dietary guidelines), with the green-MED diet leading to more pronounced beneficial changes, largely driven by dominant proinflammatory proteins (IL-1 receptor antagonist protein, IL-16, IL-18, thrombospondin-2, leptin, prostasin, galectin-9, and fibroblast growth factor 21; adjusted for age, sex, and weight loss; p < 0.05). After 18 months, proteomics cluster changes presented the strongest correlations with visceral adiposity reduction., Conclusions: Proteomics clusters may enhance our understanding of the favorable effect of a green-MED diet that is enriched with polyphenols and low in red/processed meat on visceral adiposity and cardiometabolic risk., (© 2024 The Authors. Obesity published by Wiley Periodicals LLC on behalf of The Obesity Society.)

Background and Aims: We demonstrated in the randomized 18-month DIRECT PLUS trial (n = 294) that a Mediterranean (MED) diet, supplemented with polyphenol-rich Mankai duckweed, green tea, and walnuts and restricted in red/processed meat, caused substantial intrahepatic fat (IHF%) loss compared with 2 other healthy diets, reducing NAFLD by half, regardless of similar weight loss. Here, we investigated the baseline proteomic profile associated with IHF% and the changes in proteomics associated with IHF% changes induced by lifestyle intervention., Approach and Results: We calculated IHF% by proton magnetic resonance spectroscopy (normal IHF% <5% and abnormal IHF% ≥5%). We assayed baseline and 18-month samples for 95 proteomic biomarkers.Participants (age = 51.3 ± 10.8 y; 89% men; and body mass index = 31.3 ± 3.9 kg/m 2 ) had an 89.8% 18-month retention rate; 83% had eligible follow-up proteomics measurements, and 78% had follow-up proton magnetic resonance spectroscopy. At baseline, 39 candidate proteins were significantly associated with IHF% (false discovery rate <0.05), mostly related to immune function pathways (eg, hydroxyacid oxidase 1). An IHF% prediction based on the DIRECT PLUS by combined model ( R2 = 0.47, root mean square error = 1.05) successfully predicted IHF% ( R2 = 0.53) during testing and was stronger than separately inputting proteins/traditional markers ( R2 = 0.43/0.44). The 18-month lifestyle intervention induced changes in 18 of the 39 candidate proteins, which were significantly associated with IHF% change, with proteins related to metabolism, extracellular matrix remodeling, and immune function pathways. Thrombospondin-2 protein change was higher in the green-MED compared to the MED group, beyond weight and IHF% loss ( p = 0.01). Protein principal component analysis revealed differences in the third principal component time distinct interactions across abnormal/normal IHF% trajectory combinations; p < 0.05 for all)., Conclusions: Our findings suggest novel proteomic signatures that may indicate MRI-assessed IHF state and changes during lifestyle intervention. Specifically, carbonic anhydrase 5A, hydroxyacid oxidase 1, and thrombospondin-2 protein changes are independently associated with IHF% change, and thrombospondin-2 protein change is greater in the green-MED/high polyphenols diet., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Obesity is associated with negative effects on the brain. We exploit Artificial Intelligence (AI) tools to explore whether differences in clinical measurements following lifestyle interventions in overweight population could be reflected in brain morphology. In the DIRECT-PLUS clinical trial, participants with criterion for metabolic syndrome underwent an 18-month lifestyle intervention. Structural brain MRIs were acquired before and after the intervention. We utilized an ensemble learning framework to predict Body-Mass Index (BMI) scores, which correspond to adiposity-related clinical measurements from brain MRIs. We revealed that patient-specific reduction in BMI predictions was associated with actual weight loss and was significantly higher in active diet groups compared to a control group. Moreover, explainable AI (XAI) maps highlighted brain regions contributing to BMI predictions that were distinct from regions associated with age prediction. Our DIRECT-PLUS analysis results imply that predicted BMI and its reduction are unique neural biomarkers for obesity-related brain modifications and weight loss., (© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Background: The effect of microbes on their human host is often mediated through changes in metabolite concentrations. As such, multiple tools have been proposed to predict metabolite concentrations from microbial taxa frequencies. Such tools typically fail to capture the dependence of the microbiome-metabolite relation on the environment., Results: We propose to treat the microbiome-metabolome relation as the equilibrium of a complex interaction and to relate the host condition to a latent representation of the interaction between the log concentration of the metabolome and the log frequencies of the microbiome. We develop LOCATE (Latent variables Of miCrobiome And meTabolites rElations), a machine learning tool to predict the metabolite concentration from the microbiome composition and produce a latent representation of the interaction. This representation is then used to predict the host condition. LOCATE's accuracy in predicting the metabolome is higher than all current predictors. The metabolite concentration prediction accuracy significantly decreases cross datasets, and cross conditions, especially in 16S data. LOCATE's latent representation predicts the host condition better than either the microbiome or the metabolome. This representation is strongly correlated with host demographics. A significant improvement in accuracy (0.793 vs. 0.724 average accuracy) is obtained even with a small number of metabolite samples ([Formula: see text])., Conclusion: These results suggest that a latent representation of the microbiome-metabolome interaction leads to a better association with the host condition than any of the two separated or the simple combination of the two. Video Abstract., (© 2024. The Author(s).)

Bile acids (BAs) undergo extensive microbial metabolism in the gut and exert hormone-like functions on physiological processes underlying metabolic risk. However, the extent to which gut BA profiles predict cardiometabolic risk and explain individual responses to dietary interventions in humans is still unclear. In the DIRECT-PLUS Trial, we conducted a multi-omics analysis of 284 participants randomized into three groups: healthy dietary guidelines and two Mediterranean diet (MedDiet) groups. We longitudinally measured 44 fecal BAs using liquid chromatography-mass spectrometry, the gut microbiome through shotgun metagenomic sequencing, and body adiposity and serum lipids at baseline, 6, and 18 months. Fecal levels of 14 BAs, such as lithocholic acid and ursodeoxycholic acid, were prospectively associated with body mass index (BMI) and serum lipid profiles (false discovery rate [ q ]<0.05). Baseline fecal BA levels significantly modified the beneficial effects of the MedDiet; for example, BMI reduction induced by MedDiet interventions was more pronounced in individuals with lower 12-dehydrocholic acid levels ( q -interaction <0.001). We confirmed that the gut microbiome is a major modifier of the secondary BA pool in humans. Furthermore, the association of fecal BAs with body adiposity and serum lipids varied significantly in individuals with different abundances of gut microbes carrying BA metabolism enzymes, e.g. several Ruminococcus spp. In summary, our study identifies novel predictive biomarkers for cardiometabolic risk and offers new mechanistic insights to guide personalized dietary interventions.

To understand human longevity, inherent aging processes must be distinguished from known etiologies leading to age-related chronic diseases. Such deconvolution is difficult to achieve because it requires tracking patients throughout their entire lives. Here, we used machine learning to infer health trajectories over the entire adulthood age range using extrapolation from electronic medical records with partial longitudinal coverage. Using this approach, our model tracked the state of patients who were healthy and free from known chronic disease risk and distinguished individuals with higher or lower longevity potential using a multivariate score. We showed that the model and the markers it uses performed consistently on data from Israeli, British and US populations. For example, mildly low neutrophil counts and alkaline phosphatase levels serve as early indicators of healthy aging that are independent of risk for major chronic diseases. We characterize the heritability and genetic associations of our longevity score and demonstrate at least 1 year of extended lifespan for parents of high-scoring patients compared to matched controls. Longitudinal modeling of healthy individuals is thereby established as a tool for understanding healthy aging and longevity., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)