Plant-Forward Diets Lower Circulating TMAO in Adults: A Systematic Review and Meta-Analysis

Plant-Forward Diets Lower Circulating TMAO in Adults: A Systematic Review and Meta-Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Plant-Forward Diets Lower Circulating TMAO in Adults: A Systematic Review and Meta-Analysis Roberta Zupo, Fabio Castellana, Feliciana Catino, Luisa Lampignano, and 14 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9382739/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Diet modulates circulating trimethylamine N-oxide (TMAO), a gut microbiota-derived metabolite linked to cardiovascular risk; whether plant-forward versus animal-based dietary patterns consistently influence TMAO concentrations in adults remains unclear. A PRISMA-2020-compliant systematic review and meta-analysis (PROSPERO: CRD420261326106) was conducted through February 2026 across multiple databases; eligible studies assessed dietary patterns, food groups, or diet-related interventions in relation to circulating TMAO in adults. Random-effects meta-analyses were performed where data were combinable. Thirty-four studies were included; 11 contributed to quantitative synthesis. Eight RCTs showed significantly lower TMAO with plant-forward versus animal-based exposures (pooled MD −1.08 µM, 95% CI −1.52 to −0.65; I² [a measure of between-study heterogeneity] = 0%), consistent across dietary-pattern (−0.85 µM) and food-group subgroups (−1.24 µM). Three cross-sectional studies linking higher meat intake to higher TMAO showed substantial heterogeneity (I² = 75%). Plant-forward diets are associated with lower circulating TMAO in adults, with the strongest evidence from RCTs. Nutrition & Dietetics Epidemiology trimethylamine N-oxide TMAO dietary patterns plant-based diet animal-based diet gut microbiota cardiovascular risk meta-analysis systematic review food groups Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Cardiovascular disease (CVD) rank as leading cause of morbidity and mortality worldwide 1 , and diet is one of its most important modifiable determinants 2,3 . Contemporary evidence indicates that the global burden of CVD attributable to diet risk is still substantial and is driven not only by excessive intake of sodium, processed foods, and red meat, but also by insufficient consumption of whole grains, fruits, vegetables, legumes, nuts, and other plant foods 2 . While traditional nutritional epidemiology has often focused on single nutrients, this approach does not fully capture the complexity of human diets or the biological pathways through which diet exposures may influence cardiometabolic health. Increasingly, research has shifted toward dietary patterns and toward mechanistic intermediates that may help explain why certain ways of eating are associated with either higher or lower cardiovascular risk. Among these mechanistic intermediates, gut microbiota–derived metabolites have attracted growing attention as candidate biomarkers—and, in some cases, possible mediators—of cardiometabolic risk . Trimethylamine N-oxide (TMAO) is the most extensively studied example 4–6 . TMAO is generated when diet precursors such as choline, phosphatidylcholine, and L-carnitine are metabolized by gut microbes into trimethylamine (TMA), which is then oxidized in the liver by flavin monooxygenases. Experimental and human evidence has linked TMAO to several pathways relevant to atherosclerosis and CVD, including altered cholesterol handling 7 , vascular inflammation, impaired endothelial function 8 , thrombosis potential, and interactions with renal function. In observational settings, higher circulating concentrations of TMAO and related metabolites have also been associated with major adverse cardiovascular events and mortality 9 , supporting their relevance as intermediate cardiometabolic risk signals. Because TMAO is strongly influenced by the availability of diet precursors and by the composition and metabolic capacity of the gut microbiota, it represents a plausible mechanistic link between habitual diet and cardiometabolic risk 5 . This makes dietary pattern analysis particularly relevant, as whole diets may shape TMAO production not only through specific nutrients or foods, but also through broader host–microbe interactions. In this context, comparing plant-forward and animal-based dietary exposures may help clarify whether differences in overall diet quality translate into distinct TMAO profiles 4 . Within this framework, the contrast between plant-forward and animal-based dietary exposures has become relevant. Plant-forward diets, characterized by higher intakes of vegetables, fruits, legumes, nuts, and whole grains and by lower intakes of red and processed meat, are aligned not only with cardiometabolic prevention strategies 10 but also with sustainable dietary models such as the EAT-Lancet planetary health diet 11 . This predominantly plant-based dietary framework has been proposed to support both human and planetary health, and recent evidence suggests that greater adherence is generally associated with lower risk of all-cause mortality, cardiovascular disease, and type 2 diabetes 11 . Despite growing literature, the evidence remains inconsistent. Studies have examined both specific food-group contrasts and broader dietary patterns, while findings vary according to biospecimen matrix, study design, and the potential contribution of preformed TMAO from seafood 6,12 . Moreover, not all plant-based diets appear equally beneficial, with healthier plant-based patterns showing more favorable microbiome features and lower TMAO than less healthy ones. Against this background, a systematic synthesis of the available human evidence is warranted. We therefore conducted a systematic review and meta-analysis to evaluate whether plant-forward dietary exposures are associated with lower circulating TMAO concentrations compared with animal-based exposures in adults, distinguishing between food-group and dietary-pattern comparisons, and assessing consistency of findings across intervention and observational study designs. METHODS Study Design and Registration This systematic review was conducted in accordance with the PRISMA 2020 guidelines 13 . The protocol was prospectively registered in the International Prospective Register of Systematic Reviews (PROSPERO; registration number CRD420261326106). Literature Search Strategy A systematic literature search was conducted in PubMed, MEDLINE (via Ovid), Embase (via Ovid), and Web of Science Core Collection from inception to February 2026, with no language restrictions. The search strategy combined controlled vocabulary — MeSH terms in PubMed/MEDLINE and Emtree in Embase — with free-text terms, structured around four conceptual domains: trimethylamine N-oxide (TMAO), the gut milieu and microbiome, metabolites and metabolomics, and dietary exposures. The core query followed the structure: ("trimethylamine n-oxide" OR "TMAO") AND ("gut" OR "intestinal" OR "gut-derived" OR "gut-related") AND ("metabolit*" OR "microbiot*" OR "microbiom*" OR "metabolom*") AND ("association*" OR "relation*" OR "correlation*"). This was expanded with dietary and nutritional keywords to capture both food-group and dietary-pattern exposures, including: diet*, dietary, nutrition*, food*, "dietary pattern*", plant-based, vegetarian*, vegan*, Mediterranean, DASH, animal-based, omnivor*, red meat, processed meat, poultry, egg*, dairy, fish, seafood, whole grain*, fiber, and resistant starch. Database-specific syntax, Boolean operators, truncation symbols, field tags, and proximity operators were applied as appropriate, and search strings were translated across all databases. To maximize sensitivity, no study-design filters were applied at the search stage. Records were limited to human research using database-appropriate limits, and non-eligible publication types were excluded using publication type filters and/or free-text terms as appropriate, including reviews, meta-analyses, editorials, commentaries, letters, consensus statements, and books or book chapters. Animal-only studies were excluded using validated database limits and exclusion logic to avoid inadvertently removing human studies that might include terms such as “animal-based diet.” Reference lists of included articles and relevant reviews were hand-searched, and forward citation tracking was conducted to identify additional eligible studies. Duplicate records were removed prior to screening. The complete search strategy is reported in Table 1 , and the study selection process is summarized in Fig. 1 (PRISMA flow diagram). Study Selection Two reviewers (FC and RZ) independently screened titles and abstracts for relevance. The full texts of potentially eligible articles were then retrieved and assessed against the predefined inclusion and exclusion criteria. Any disagreements were resolved through discussion, and when consensus could not be reached, a third reviewer (RS) was consulted. The study selection process was conducted in accordance with the PRISMA 2020 framework. Eligibility Criteria (PICO Framework) Eligibility criteria were defined according to the PICO framework ( Table 1 ). Population (P): Human participants aged 18 years or older, of either sex, were eligible for inclusion. Studies conducted in healthy adults, as well as in adults with overweight, obesity, cardiometabolic risk factors, or stable chronic conditions, were considered eligible provided that TMAO was assessed in plasma/serum or urine. Animal studies, in vitro studies, pediatric populations, and studies conducted exclusively in pregnant women were excluded. Intervention/Exposure (I): Eligible studies investigated dietary exposures potentially associated with TMAO and other gut-derived metabolites. These included plant-forward dietary patterns, vegetarian or vegan diets, Mediterranean- or DASH-style diets, plant-based substitutions, animal-based dietary patterns, and specific food-group exposures such as red or processed meat, poultry, eggs, dairy products, fish, seafood, fiber-rich foods, whole grains, resistant starch, legumes, and nuts. Both controlled dietary interventions and observational assessments of habitual dietary intake were considered. Comparator (C): Comparators included alternative dietary patterns, different levels of intake of the same food group, plant-forward versus animal-based dietary exposures, omnivorous or usual diets, or, in observational studies, lower versus higher adherence or intake categories. Studies without a formal comparator were also considered if they reported quantitative associations between dietary exposure and TMAO. Outcomes (O): The primary outcome was trimethylamine N-oxide (TMAO), measured in plasma/serum or urine. Studies were eligible if they reported absolute TMAO concentrations, changes in TMAO over time, or quantitative associations between dietary exposures and TMAO. Secondary outcomes, when available, included TMAO-related and other gut-derived metabolites, such as choline, carnitine, betaine, trimethylamine, phenylacetylglutamine (PAGln/PAG), indoxyl sulfate, p-cresyl sulfate (including p-cresol sulfate), and imidazole propionate, as well as inflammatory and cardiometabolic biomarkers. Eligible study designs included randomized controlled trials, non-randomized dietary interventions, crossover feeding studies, prospective and retrospective cohort studies, case-control studies, and cross-sectional studies. Reviews, meta-analyses, editorials, commentaries, letters, conference abstracts without sufficient data, book chapters, and consensus papers were excluded. For the quantitative synthesis, only studies providing sufficiently comparable numerical data were considered for meta-analysis, whereas all eligible studies were included in the qualitative synthesis. Table 1 . Search strategy structured according to the PICO framework. PICO domain Concept Search terms / keywords P Population Human adult populations adults OR humans OR men OR women OR participants OR patients OR "aged 18 and over" OR "18 years and older" OR "adult population" OR "working age" OR "middle aged" OR "older adults" OR "elderly" I/E Intervention / Exposure Dietary exposures, food groups, and dietary patterns potentially associated with TMAO and other gut-derived metabolites diet* OR dietary OR nutrition* OR food* OR "dietary pattern*" OR "plant-based" OR vegetarian* OR vegan* OR Mediterranean OR DASH OR "animal-based" OR omnivor* OR "red meat" OR "processed meat" OR poultry OR egg* OR dairy OR fish OR seafood OR "whole grain*" OR fiber OR "resistant starch" OR legumes OR nuts C Comparator Alternative dietary exposures, lower versus higher intake categories, plant-forward versus animal-based patterns, or usual diet — Comparator terms were not explicitly required in the search string in order to maximize sensitivity; comparators were addressed during study selection and eligibility assessment. O Outcomes Primary metabolite outcome "trimethylamine n-oxide" OR TMAO Excl. Exclusion block Non-eligible publication types and animal-only studies NOT (review OR "meta-analysis" OR editorial OR commentary OR letter OR consensus OR "book chapter" OR book OR animal OR pig OR pigs OR rat OR rats OR mice) Quality Assessment The methodological quality and risk of bias of the included studies were assessed according to study design. Randomized controlled trials, including parallel-group, crossover, and controlled-feeding randomized studies, were evaluated using the Cochrane Risk of Bias 2 (RoB-2) tool, which assesses bias across five domains: the randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported result. For crossover trials, the crossover-specific RoB-2 version was applied to account for potential carryover effects, period effects, and washout adequacy 14 . Prospective and longitudinal cohort studies were assessed using the Newcastle–Ottawa Scale (NOS), which evaluates study quality according to the selection of participants, comparability of study groups, and ascertainment of exposure or outcomes. The NOS was applied using the original Ottawa Hospital Research Institute guidance 15 . Analytical cross-sectional studies were appraised using the JBI Critical Appraisal Checklist for Analytical Cross-Sectional Studies, which focuses on the appropriateness of inclusion criteria, validity and reliability of exposure and outcome measurement, identification and management of confounding, and adequacy of statistical analysis 16 . Uncontrolled pre–post intervention studies and before–after feeding studies without a comparator group were evaluated using the National Institutes of Health (NIH) Quality Assessment Tool for Before–After (Pre–Post) Studies With No Control Group, which examines clarity of study objectives, eligibility criteria, participant representativeness, intervention description, outcome assessment, follow-up, and statistical analysis (https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools). Meta-analysis The meta-analysis was performed using a random-effects model, with between-study variance (τ²) estimated by Restricted Maximum Likelihood (REML) 17,18 . Effect sizes were expressed as mean differences (MD) in circulating TMAO concentrations between dietary exposure and comparator groups, with corresponding standard errors. Separate analyses were conducted by study design — randomized controlled trials and cross-sectional studies — and further stratified by exposure type. The variable Type distinguished studies evaluating the effect of specific food group substitutions (e.g., animal- versus plant-based foods) from those assessing adherence to broader dietary patterns. This two-level stratification allowed simultaneous accounting for within- and between-study heterogeneity 19 , yielding both overall and subgroup-specific pooled estimates. RESULTS Study selection and characteristics A total of 34 studies 3–6,12,20–48 met the inclusion criteria. Characteristics of all included studies are summarized in Table 2 . No time restrictions were set, and the selected publications spanned the period from 2006 to 2024, with a median publication year of 2019 (IQR 2018–2022), indicating a marked increase in interest in this topic in recent years. The included studies were conducted across 11 countries, predominantly in the United States (17/34; 50.0%), followed by the United Kingdom (4/34; 11.8%), and Italy and Norway (3/34; 8.8% each), with additional contributions from Spain, Sweden, Poland, Australia, Denmark, New Zealand, and China. Based on the sample sizes reported in each study, the overall summed study population comprised 8,045 participants. Most included studies were randomized dietary intervention or controlled feeding trials (24/34; 70.6%), including parallel, crossover, and crossover-feeding designs. The remaining studies consisted of 6 cross-sectional studies (17.6%), 2 cohort studies (5.9%), and 2 uncontrolled intervention/pre–post studies (5.9%). The populations were heterogeneous and included healthy adults (16 studies) as well as adults with overweight/obesity, cardiometabolic risk factors, or established clinical conditions (18 studies). Reported mean or median age ranged from approximately 22 to 74 years. Regarding the biological matrix used for TMAO assessment, 25 studies measured TMAO in blood (plasma or serum), 6 studies in urine, and 3 studies in both blood and urine. To facilitate synthesis of the evidence, exposures were grouped a priori into two broad categories: food group (n = 15) and dietary pattern (n = 19). This classification was adopted pragmatically to improve the interpretability of findings, given the wide variability in how dietary exposures were defined across studies. Food group exposures included comparisons focused on specific foods or substitutions, such as meat, plant-based meat alternatives, seafood, or protein sources. Dietary pattern exposures included broader eating patterns or dietary prescriptions, such as Mediterranean, DASH, vegan or vegetarian, Paleolithic, among the others. For the quantitative synthesis, we extracted or derived, whenever possible, the mean difference (MD) between plant-forward and animal-based dietary exposures, together with the corresponding standard deviation (SD), standard error (SE), 95% confidence intervals (95% CI), and p values. Only 11 study-level comparisons provided sufficiently comparable numerical data for meta-analysis 3,20,22,24–26,35,36,38,43 . These included 8 RCTs and 3 cross-sectional comparisons. Seafood-focused studies were retained in the qualitative synthesis but were not pooled because fish and seafood contain preformed TMAO, which could confound the interpretation of circulating TMAO differences. Likewise, studies reporting only urinary TMAO or non-combinable association measures were not included in the quantitative synthesis. Because of methodological heterogeneity, separate forest plots were generated for RCTs and observational cross-sectional studies. Table 2. Characteristics of included studies (n=34). Study design, population characteristics, dietary exposure, TMAO biospecimen matrix, and key findings, stratified by exposure category (FG: food group; DP: dietary pattern). First author, year Country Category Study design Population N Age Dietary exposure TMAO matrix Key finding Crimarco, 2020 USA FG RCT crossover Healthy omnivorous adults 36 50 ± 14 y Plant-based meat vs animal meat (8 wk each) Plasma or serum Plant-based meat: 2.7 µM vs animal meat: 4.7 µM; MD −2.0 µM (p=0.012) Farsi, 2023 UK FG RCT crossover Healthy male adults 20 30.4 ± 7.9 y Mycoprotein vs red+processed meat (14 d) Urine Urinary TMAO not significantly different between phases (p=0.06) Tate, 2023 USA FG RCT parallel Obese older adults 28 65–84 y DASH + 3 oz vs 6 oz lean beef/day (12 wk) Plasma or serum TMAO increased overall (+26.5%, p<0.001); greater with 6 oz beef (p=0.033) Vázquez-Fresno, 2015 Spain FG RCT parallel Adults at high CVD risk 98 55–80 y Mediterranean diet (PREDIMED; 1- and 3-year) Urine Urinary TMAO lower with higher MD adherence (ANCOVA; p=0.003–9.56×10⁻⁵) Barrea, 2019 Italy FG Cross-sectional Healthy normal-weight adults 144 31.6 ± 6.2 y Mediterranean diet adherence; food groups Plasma or serum Higher MD adherence inversely associated with TMAO (r≈−0.50, p<0.001) Krishnan, 2022a USA FG RCT crossover Overweight/obese adults 39 30–69 y Mediterranean-style diet: low vs moderate lean red meat (5 wk) Plasma or serum Low red meat: 3.1 µM vs moderate: 5.0 µM (p<0.001) Krishnan, 2022b USA FG RCT parallel Overweight/obese women at cardiometabolic risk 44 20–65 y Dietary Guidelines for Americans vs Typical American Diet (8 wk) Plasma or serum No significant difference in TMAO between diet groups Park JE, 2019 USA FG RCT crossover Healthy normolipidemic adults 14 30.6 ± 9.6 y Atkins vs Ornish vs South Beach diets (4 wk each) Plasma or serum Atkins vs Ornish: 3.3 vs 1.8 µM (p=0.01); Atkins vs South Beach NS Shen X, 2024 USA FG Cross-sectional Aging adults (BLSA) 705 (TMAO n=425) 71.0 ± 12.8 y Plant-based diet index (hPDI); food groups Plasma or serum Higher hPDI inversely associated with TMAO (q<0.05); fish/seafood positively correlated (ρ=0.12) Costabile, 2021 Italy FG RCT parallel Adults with metabolic syndrome 78 / 48 53–57 y Marine LCn3/whole-grain vs refined cereals (8–12 wk) Plasma or serum Marine LCn3 and whole-grain diets increased TMAO (p=0.007; p=0.037) Schmedes, 2016 Norway FG RCT crossover Healthy adults 20 ~50 y Lean-seafood vs non-seafood diet Plasma or serum + urine Lean-seafood significantly increased TMAO vs non-seafood (plasma and urine) Schmedes, 2018 Norway FG RCT crossover Healthy adults 20 50.6 ± 3.4 y Lean-seafood vs non-seafood diet (4 wk each) Plasma or serum Lean-seafood increased postprandial TMAO (diet×time p=0.008) Wang Z, 2019 USA FG RCT crossover Healthy omnivorous adults 113 21–65 y (median 45) Red meat vs white meat vs non-meat protein (4 wk each) Plasma or serum + urine Red meat: ~3-fold higher plasma TMAO vs non-meat (p<0.0001); median diff −5.9 µM Dhakal, 2022 USA FG RCT crossover Healthy older adults 36 66 y (mean) Lean pork vs chicken within DGA-based diet Plasma or serum TMAO fold change non-inferior pork vs chicken; p=0.07 (NS) Li J, 2022 USA FG Longitudinal cohort Healthy free-living men (MLVS/HPFS) 307 ~71.4 y Red meat intake Plasma or serum Red meat intake positively associated with circulating TMAO Wang, 2022 USA FG Prospective cohort Community-dwelling adults ≥65 y (CHS) 3,931 ≥65 y Meat, poultry, fish, processed meat, egg intake Plasma or serum Total meat (ρ=0.047) and unprocessed red meat (ρ=0.060) weakly correlated with TMAO (p<0.01) Huang Y, 2024 China FG Cross-sectional Chinese adults 754 (TMAO n=333) NR Red meat intake Plasma or serum Higher red meat intake associated with higher serum TMAO García-Pérez I, 2017 UK DP RCT crossover Healthy adults (inpatient) 19 55.8 ± 12.6 y High vs low DASH-score diet (72h inpatient; 4 phases) Urine Urinary TMAO higher after high-DASH diet vs low-DASH diet (p<0.0001); driven by fish content De Filippis, 2016 Italy DP Cross-sectional Healthy adults (omnivore, vegetarian, vegan) 153 NR Mediterranean diet adherence; dietary pattern (omnivore vs veg*n) Urine Higher MD adherence and veg*n diet associated with lower urinary TMAO (p<0.0001) Griffin, 2019 USA DP RCT parallel Adults at risk for colon cancer 115 (90 completers) 52 ± 12 y Mediterranean vs Healthy Eating diet (6 months) Plasma or serum No significant change in plasma TMAO after 6-month Mediterranean diet intervention Malinowska AM, 2016 Poland DP Cross-sectional Elderly women (free-living) 122 68.5 ± 7.4 y Western vs prudent dietary pattern Plasma or serum Western-style pattern associated with higher plasma TMAO across tertiles Argyridou, 2021 UK DP Pre–post (single-arm) Adults with dysglycemia/obesity 23 57.8 ± 10.0 y 8-week vegan diet (Plant Your Health trial) Plasma or serum TMAO decreased at wk1 and wk8 vs baseline (p=0.004); rebound after unrestricted diet Landry, 2023 USA DP RCT parallel (twin) Healthy identical twin pairs 44 (22 pairs) 39.6 ± 12.7 y Healthy vegan vs healthy omnivorous diet (8 wk) Plasma or serum Vegan: 2.9 µM vs omnivorous: 4.9 µM; MD −2.1 µM (95% CI −7.7 to 3.6; NS) Djekic, 2020 Sweden DP RCT crossover Patients with ischemic heart disease 31 (27 completers) Median 67 y Vegetarian vs meat diet (4 wk each) Plasma or serum TMAO decreased after vegetarian diet (−1.90 µM vs baseline, p<0.001); between-diet diff NS Heianza Y, 2018 USA DP RCT parallel Overweight/obese adults (POUNDS Lost) 504 NR Energy-reduced diets varying fat/protein (4 arms) Plasma or serum No significant differences in ΔTMAO across macronutrient-varying diet groups Erickson, 2019 USA DP RCT parallel Obese insulin-resistant older adults 16 66.1 ± 4.4 y Exercise + hypocaloric vs eucaloric diet (12 wk) Plasma or serum Caloric restriction + exercise: TMAO −31% vs +32% with eucaloric (p=0.04) Zhou, 2019 USA DP RCT parallel Overweight/obese adults (POUNDS Lost) 264 52.3 ± 8.9 y Energy-reduced diets varying fat/protein (4 arms) Plasma or serum Median ΔTMAO = 0.0 µmol/L; no significant differences across diet groups (p=0.70) Schmedes, 2019 Norway DP RCT crossover Healthy adults 20 ~50 y Lean-seafood vs non-seafood diet (~4 wk each) Plasma or serum Lean-seafood significantly increased circulating TMAO vs non-seafood Boutagy, 2015 USA DP Pre–post (single-arm) Healthy nonobese young men 10 22.1 ± 0.5 y High-fat diet (5 d) vs eucaloric control Plasma or serum Postprandial TMAO increased after high-fat diet; fasting TMAO unchanged Genoni A, 2020 Australia DP Cross-sectional Paleolithic followers vs controls 91 39–45 y (mean) Long-term Paleolithic diet Plasma or serum Strict Paleo: 9.53 µM vs controls: 3.93 µM (p=0.008); red meat positively associated (r=0.357) Rasmussen LG, 2012 Denmark DP RCT parallel Overweight non-diabetic adults 77 42–44 y High-protein vs low-protein diet (6 months) Urine Tendency toward higher urinary TMAO with high-protein diet (NMR metabolomics) Mitchell, 2019 New Zealand DP RCT parallel Healthy older men 29 74.2 ± 3.6 y Protein at 2×RDA vs RDA (10 wk) Plasma or serum + urine Plasma TMAO increased with 2×RDA protein (p=0.004; time×diet p=0.002) Starr KNP, 2019 USA DP RCT parallel Obese middle-aged/older adults 80 ~64 ± 8 y Higher-protein + lean red meat vs RDA protein (6 months) Plasma or serum No significant increase in plasma TMAO with higher-protein lean red meat diet Stella C, 2006 UK DP RCT crossover Healthy male adults 12 25–74 y High-meat vs low-meat vs vegetarian diet (15 d each) Urine Urinary TMAO elevated during high-meat vs low-meat and vegetarian periods (NMR) Abbreviations: FG, food group; DP, dietary pattern; RCT, randomized controlled trial; TMAO, trimethylamine N-oxide; MD, mean difference; NMR, nuclear magnetic resonance; DGA, Dietary Guidelines for Americans; DASH, Dietary Approaches to Stop Hypertension; hPDI, healthful plant-based diet index; LCn3, long-chain omega-3 fatty acids; NS, not significant; NR, not reported Quality assessment Among the 24 RCTs, 23 were judged as having some concerns and 1 as high risk of bias ( Fig. 2 ). Concerns were mainly related to the randomization process, deviations from intended interventions, and selection of the reported result, whereas outcome measurement was consistently rated at low risk across all studies. Fig. 3 summarizes the quality assessment of non-randomized studies. Both cohort studies (panel A) were rated as good quality using the NOS. Among the six cross-sectional studies (panel B), five were judged as low risk/high quality, whereas De Filippis 34 showed some concerns related mainly to confounding. The two before–after studies without controls (panel C) were rated as fair 37 and poor 42 , reflecting the limitations inherent to uncontrolled pre–post designs. Meta-analysis The quantitative synthesis included 11 study-level comparisons, comprising 8 randomized controlled trials and 3 observational cross-sectional studies. In the RCT meta-analysis ( Fig. 4 ), plant-forward dietary exposures were associated with significantly lower serum TMAO concentrations than animal-based exposures, with a pooled random-effects mean difference of −1.08 µM (95% CI −1.52 to −0.65; I²=0%). Subgroup analyses showed consistent results for both dietary-pattern interventions (−0.85 µM, 95% CI −1.52 to −0.17; I²=0%) and food-group interventions (−1.24 µM, 95% CI −1.86 to −0.62; I²=10%), with no significant subgroup differences. In contrast, the meta-analysis of cross-sectional studies ( Fig. 5 ), comparing high versus low meat intake, showed substantial heterogeneity (I²=75%). The pooled random-effects estimate was 2.35 (95% CI −0.20 to 4.90), whereas the fixed-effect estimate was 1.30 (95% CI 0.54 to 2.05). Because this comparison was defined as higher versus lower meat intake, the positive effect estimate indicates higher serum TMAO concentrations among participants with greater meat consumption. Overall, the meta-analysis supports a consistent TMAO-lowering effect of plant-forward dietary exposures in intervention studies, while observational findings point in the same direction but are less precise because of between-study heterogeneity. DISCUSSION The aim of this systematic review and meta-analysis was to evaluate whether plant-forward diet exposure is associated with lower circulating TMAO concentrations than animal-based diet in adults, while distinguishing between food-group and dietary-pattern. Across 34 studies included in the qualitative synthesis, the overall evidence suggested a consistent directional pattern: plant-forward exposures tended to be associated with lower TMAO, whereas animal-based exposures—particularly higher meat intake—tended to be associated with higher TMAO. In the quantitative synthesis, 11 study-level comparisons were meta-analyzed. Among the 8 RCTs, plant-forward interventions were associated with significantly lower serum/plasma TMAO concentrations than animal-based interventions, with a pooled mean difference of −1.08 µM (95% CI −1.52 to −0.65). This pattern remained consistent in subgroup analyses of both dietary-pattern interventions and food-group interventions. In contrast, the 3 cross-sectional studies comparing high versus low meat intake suggested higher TMAO with greater meat consumption, but with substantial heterogeneity, indicating that observational evidence was directionally supportive but methodologically less stable. From a clinical perspective, these findings are relevant because TMAO is well-acknowledged as a gut microbiota–related marker linked to cardiometabolic risk, atherosclerotic disease, and adverse cardiovascular outcomes, although causal role remains debated 5,6 . The present results suggest that diets emphasizing plant foods and reducing animal source—especially red and processed meat—may shift the circulating TMAO profile in a more favorable direction. Importantly, the consistency of the pooled RCT estimate strengthens the interpretation that this association is not purely observational but is at least partly diet-responsive under controlled conditions. This interpretation is biologically plausible. Plant-forward diets generally reduce exposure to dietary precursors of TMAO, including L-carnitine and choline-rich animal foods, while at the same time providing more fiber and plant substrates that may favourably shape gut microbial ecology. Several intervention studies included in this review support this framework. In the SWAP-MEAT trial, replacing animal meat with plant-based meat alternatives significantly lowered circulating TMAO 20 . Similarly, an 8-week randomized trial in identical twins found lower TMAO under a healthy vegan diet compared with a healthy omnivorous diet 3 . In overweight or obese adults, a Mediterranean-style dietary pattern with lowered meat intake reduced fasting TMAO, whereas a similar pattern with moderate red meat intake did not, suggesting that the overall healthfulness of the diet may not fully offset the effect of animal-source precursor load 24 . Likewise, chronic red meat intake has been shown to increase plasma and urinary TMAO compared with non-meat protein sources under controlled feeding conditions 30 . The observational findings were directionally concordant with the intervention evidence. Higher meat intake was associated with higher TMAO, although heterogeneity was substantial, likely reflecting differences in study populations, exposure assessment, background diets, renal function, microbiome composition, and biospecimen handling. This variability is not surprising, because TMAO is not merely a readout of food intake; it reflects a dynamic interaction between dietary precursors, gut microbial metabolic capacity, and host metabolism 5 . For this reason, the clinical significance of a given TMAO concentration should be interpreted in context, rather than as a stand-alone nutritional target. Another clinically important point is that not all animal-source foods behave similarly. Seafood-focused studies were deliberately excluded from the pooled meta-analysis because fish and seafood contain preformed TMAO, which may elevate circulating concentrations through a mechanism distinct from endogenous microbial generation from meat-derived precursors. Controlled studies have shown that lean-seafood diets can increase fasting or postprandial TMAO despite otherwise favorable cardiometabolic features 29 . This reinforces the idea that TMAO should not be interpreted simplistically as a universal marker of “healthy” or “unhealthy” eating, but rather as a context-dependent metabolite whose meaning depends on food source, microbiome function, and cardiometabolic background. Taken together, the present findings may have practical implications for dietary counseling, particularly in individuals with overweight, obesity, insulin resistance, dyslipidemia, or established cardiovascular disease. While TMAO should not replace established clinical outcomes, it may provide a useful intermediate biomarker through which plant-forward dietary strategies could exert cardiometabolic benefit. In this sense, our results are consistent with a broader movement toward dietary models that combine metabolic and environmental relevance, including Mediterranean-style and other plant-forward eating patterns. Strengths and limitations This study has several strengths. First, to our knowledge, it provides one of the most focused syntheses of the literature comparing plant-forward versus animal-based dietary exposures in relation to circulating TMAO. Second, we separated food-group and dietary-pattern comparisons, which improved interpretability and allowed us to show that the overall direction of effect was consistent across both exposure types. Third, we analyzed RCTs and observational cross-sectional studies separately, thereby avoiding inappropriate pooling across fundamentally different study designs. Fourth, we deliberately excluded seafood-focused studies from the quantitative synthesis to minimize confounding by preformed TMAO, which strengthens the internal coherence of the pooled estimates. This study has also several limitations. The total number of studies that could be quantitatively pooled was relatively small, especially for the observational meta-analysis. Reporting formats were highly heterogeneous: some studies presented means and standard deviations, whereas others reported medians, relative intensities, p-value contrasts, or graphical data only. Several crossover trials required careful handling because paired variance estimates were not always fully available. In addition, exposures were diverse, ranging from whole dietary patterns to single food substitutions, which may limit direct comparability. TMAO was measured in different biological matrices, although the meta-analysis was restricted to serum/plasma studies whenever possible. Another important limitation is that the gut microbiota was not systematically incorporated into the quantitative synthesis, despite its central role in TMAO generation. Although several studies acknowledged or explored microbiome-related mechanisms, the available data were still too limited, heterogeneous, and inconsistently reported to allow a methodologically robust synthesis of microbiota-related findings. As a result, the present review could not adequately address how inter-individual differences in microbial composition or function may modify the association between diet and circulating TMAO. Finally, because TMAO is an intermediate biomarker rather than a hard clinical endpoint, its interpretation should remain cautious and embedded within the broader cardiometabolic, dietary, and host–microbiome context. Conclusion This systematic review and meta-analysis demonstrate that plant-forward dietary exposures are associated with lower circulating TMAO concentrations compared with animal-based exposures in adults, with the most consistent evidence derived from RCTs. Observational data were directionally concordant, linking greater meat intake to higher TMAO concentrations, albeit with substantial between-study heterogeneity. Collectively, the available evidence suggests that shifting toward plant-forward dietary strategies may beneficially modulate circulating TMAO; however, larger, well-standardized human studies with harmonized exposure definitions, standardized biospecimen protocols, and consistent outcome reporting are needed to establish the clinical relevance of these findings and their translation into dietary recommendations. Declarations Ethical approval: Not required. Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Declaration of Competing Interest: None of the authors has a financial or other interest to declare. Acknowledgements: The authors thank the research teams behind all primary studies included in this systematic review and meta-analysis for making their data available. C.M. acknowledges the Chronic Disease Research Foundation (CDRF), by the Italian Ministry of Education and Research: Dipartimenti di Eccellenza Program 2023–2027, and by the Italian Ministry of Health – Bando Ricerca Corrente. Author Contributions: R.Z.: Conceptualization, Methodology, Formal analysis, Investigation, Writing – original draft, Writing – review & editing. F.Ca.: Conceptualization, Methodology, Investigation, Writing – review & editing. F.Cat.: Investigation, Data curation, Writing – review & editing. L.L.: Investigation, Data curation, Writing – review & editing. Y.Z.: Methodology, Writing – review & editing. G.L.: Writing – review & editing, Supervision. A.Ma.: Writing – review & editing. M.A.I.: Writing – review & editing. A.R.-M.: Writing – review & editing. 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Red meat intake, faecal microbiome, serum trimethylamine N-oxide and hepatic steatosis among Chinese adults. Liver Int 44 , 1142–1153 (2024). Garcia-Perez, I. et al. Objective assessment of dietary patterns by use of metabolic phenotyping: a randomised, controlled, crossover trial. Lancet Diabetes Endocrinol 5 , 184–195 (2017). De Filippis, F. et al. High-level adherence to a Mediterranean diet beneficially impacts the gut microbiota and associated metabolome. Gut 65 , 1812–1821 (2016). Griffin, L. E. et al. A Mediterranean diet does not alter plasma trimethylamine N-oxide concentrations in healthy adults at risk for colon cancer. Food Funct 10 , 2138–2147 (2019). Malinowska, A. M., Szwengiel, A. & Chmurzynska, A. Dietary, anthropometric, and biochemical factors influencing plasma choline, carnitine, trimethylamine, and trimethylamine-N-oxide concentrations. Int J Food Sci Nutr 68 , 488–495 (2017). Argyridou, S. et al. Evaluation of an 8-Week Vegan Diet on Plasma Trimethylamine-N-Oxide and Postchallenge Glucose in Adults with Dysglycemia or Obesity. J Nutr 151 , 1844–1853 (2021). Djekic, D. et al. Effects of a Vegetarian Diet on Cardiometabolic Risk Factors, Gut Microbiota, and Plasma Metabolome in Subjects With Ischemic Heart Disease: A Randomized, Crossover Study. J Am Heart Assoc 9 , e016518 (2020). Heianza, Y. et al. Gut microbiota metabolites, amino acid metabolites and improvements in insulin sensitivity and glucose metabolism: the POUNDS Lost trial. Gut 68 , 263–270 (2019). Erickson, M. L. et al. Effects of Lifestyle Intervention on Plasma Trimethylamine N-Oxide in Obese Adults. Nutrients 11 , (2019). Zhou, T. et al. Circulating Gut Microbiota Metabolite Trimethylamine N-Oxide (TMAO) and Changes in Bone Density in Response to Weight Loss Diets: The POUNDS Lost Trial. Diabetes Care 42 , 1365–1371 (2019). Boutagy, N. E. et al. Short-term high-fat diet increases postprandial trimethylamine-N-oxide in humans. Nutr Res 35 , 858–864 (2015). Genoni, A. et al. Long-term Paleolithic diet is associated with lower resistant starch intake, different gut microbiota composition and increased serum TMAO concentrations. Eur J Nutr 59 , 1845–1858 (2020). Rasmussen, L. G. et al. Assessment of the effect of high or low protein diet on the human urine metabolome as measured by NMR. Nutrients 4 , 112–131 (2012). Mitchell, S. M. et al. Protein Intake at Twice the RDA in Older Men Increases Circulatory Concentrations of the Microbiome Metabolite Trimethylamine-N-Oxide (TMAO). Nutrients 11 , (2019). Porter Starr, K. N. et al. Impact on cardiometabolic risk of a weight loss intervention with higher protein from lean red meat: Combined results of 2 randomized controlled trials in obese middle-aged and older adults. J Clin Lipidol 13 , 920–931 (2019). Stella, C. et al. Susceptibility of human metabolic phenotypes to dietary modulation. J Proteome Res 5 , 2780–2788 (2006). Barrea, L. et al. Trimethylamine N-oxide, Mediterranean diet, and nutrition in healthy, normal-weight adults: also a matter of sex? Nutrition 62 , 7–17 (2019). Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9382739","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":621171346,"identity":"ec81beec-b330-4017-9d13-c07bbe94cf98","order_by":0,"name":"Roberta Zupo","email":"","orcid":"","institution":"Department of Interdisciplinary Medicine (DIM), University of Bari Aldo Moro, Bari, Italy","correspondingAuthor":false,"prefix":"","firstName":"Roberta","middleName":"","lastName":"Zupo","suffix":""},{"id":621171347,"identity":"ec9ae2bf-a1a2-4622-9f81-0a0fc43c250f","order_by":1,"name":"Fabio Castellana","email":"","orcid":"","institution":"Department of Interdisciplinary Medicine (DIM), University of Bari Aldo Moro, Bari, Italy","correspondingAuthor":false,"prefix":"","firstName":"Fabio","middleName":"","lastName":"Castellana","suffix":""},{"id":621171348,"identity":"1181117b-39b9-47c8-8c45-d70a3bddf257","order_by":2,"name":"Feliciana Catino","email":"","orcid":"","institution":"Department of Research, Innovation, and Technology Transfer, Health Directorate, Taranto Local Health Authority, Taranto, Italy","correspondingAuthor":false,"prefix":"","firstName":"Feliciana","middleName":"","lastName":"Catino","suffix":""},{"id":621171349,"identity":"d4d00541-4c4d-488f-aea1-de9049716e0d","order_by":3,"name":"Luisa Lampignano","email":"","orcid":"","institution":"Department of Research, Innovation, and Technology Transfer, Health Directorate, Taranto Local Health Authority, Taranto, Italy","correspondingAuthor":false,"prefix":"","firstName":"Luisa","middleName":"","lastName":"Lampignano","suffix":""},{"id":621171350,"identity":"2d3c5638-e192-49a8-9e5b-d2a1d7b15428","order_by":4,"name":"Yalin Zheng","email":"","orcid":"","institution":"Department of Eye and Vision Science, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK","correspondingAuthor":false,"prefix":"","firstName":"Yalin","middleName":"","lastName":"Zheng","suffix":""},{"id":621171351,"identity":"8f3ea4fa-b89c-4961-b348-76882adbfcb3","order_by":5,"name":"Gregory Lip","email":"","orcid":"","institution":"Liverpool Centre for Cardiovascular Sciences, University of Liverpool, Liverpool John Moores University and Liverpool Heart \u0026 Chest Hospital, Liverpool, UK; 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Liverpool Centre for Cardiovascular Sciences, Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK","correspondingAuthor":false,"prefix":"","firstName":"Masoud","middleName":"","lastName":"Isanejad","suffix":""},{"id":621171363,"identity":"98fe7bdb-f130-4578-962a-e4ae5cbfe1cc","order_by":17,"name":"Rodolfo Sardone","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYLACHiDmZ2dsgPDYIZQBQS2SzTAtzMRqMTgM4xHSYt5/+NmHNxV35IwPM7dJfNxzR46fmYHxww+Gw8a4tMjcSDOeOefMM2Ozw4xtkjOePTOWbGZgluxhOGyGS4uEBIMxM2/b4cRthxmbjXkOHE7cAHShNAPDYRucWviPfwZpqd/cDNTyB6KF+TdeLQw5YFsSDJgZGx8zQLSwgWzB47CcYsY5Zw4bzjjM2Piw5wDIL4xtlj0G6Ti9D3TYZoY3FYfl+dvbHxz4cQAYYuzNh2/8qLA2bMClBw0cAGJQnOKPSAwto2AUjIJRMApQAQCuAFP6FccqgwAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Research, Innovation, and Technology Transfer, Health Directorate, Taranto Local Health Authority, Taranto, Italy","correspondingAuthor":true,"prefix":"","firstName":"Rodolfo","middleName":"","lastName":"Sardone","suffix":""}],"badges":[],"createdAt":"2026-04-10 19:42:21","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9382739/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9382739/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106960757,"identity":"711ede43-3c80-4f75-b2a0-b3ae3ddc4344","added_by":"auto","created_at":"2026-04-15 09:22:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":359031,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA 2020 flow diagram of study selection. Records identified through database searching (PubMed, MEDLINE, Embase, and Web of Science) and additional sources are shown in the top boxes. Numbers of records excluded at each stage, with reasons, are indicated in the right-hand boxes. The bottom box shows the total number of studies included in qualitative synthesis (n = 34) and quantitative synthesis (n = 11).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9382739/v1/17366b024174a348a78d0503.png"},{"id":106884463,"identity":"7885eb06-ecf2-448a-a6fe-1993d5ca8efa","added_by":"auto","created_at":"2026-04-14 12:13:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":342769,"visible":true,"origin":"","legend":"\u003cp\u003eRisk of bias assessment of randomized controlled trials (n = 24) using the Cochrane Risk of Bias 2 (RoB 2) tool. Each row represents one RCT; columns correspond to the five RoB 2 domains: D1, randomization process; D2, deviations from intended interventions; D3, missing outcome data; D4, measurement of the outcome; D5, selection of the reported result. Colours indicate the risk-of-bias judgement: green, low risk; yellow, some concerns; red, high risk. The rightmost column shows the overall risk-of-bias judgement for each study.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9382739/v1/b74f0d31857bda762b1150d7.png"},{"id":106961503,"identity":"49bec892-cdd5-442c-aa79-e0eb3f0d5b3e","added_by":"auto","created_at":"2026-04-15 09:25:49","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":228470,"visible":true,"origin":"","legend":"\u003cp\u003eQuality assessment of non-randomized studies (n = 10) using design-specific appraisal tools. Panel A: cohort studies (n = 2) assessed with the Newcastle–Ottawa Scale (NOS). Panel B: cross-sectional studies (n = 6) assessed with the JBI critical appraisal checklist. Panel C: uncontrolled before–after studies (n = 2) assessed with the NIH Quality Assessment Tool for Before–After (Pre–Post) Studies With No Control Group. Green, low risk or high quality; yellow, some concerns or fair quality; red, high risk or poor quality.\u003c/p\u003e","description":"","filename":"3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9382739/v1/59654aea27fa281a0ef31def.jpeg"},{"id":106884464,"identity":"bfcb8906-23e2-42dd-a291-002499f5cf21","added_by":"auto","created_at":"2026-04-14 12:13:47","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":256015,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of randomized controlled trials (n = 8 studies; 8 comparisons; total n = 477 participants) comparing circulating TMAO concentrations between plant-forward and animal-based dietary exposures. Effect sizes are expressed as mean differences (MD) in serum or plasma TMAO (µM); horizontal bars represent 95% confidence intervals. The overall pooled estimate (random-effects model, REML) is shown as a filled diamond; individual study estimates are shown as filled squares sized proportionally to study weight. Subgroup analyses are stratified by exposure type (dietary-pattern interventions and food-group interventions). I² = 0% for the overall analysis and dietary-pattern subgroup; I² = 10% for the food-group subgroup, indicating negligible between-study heterogeneity.\u003c/p\u003e","description":"","filename":"4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9382739/v1/eccfabbba1302b1aab2617af.jpeg"},{"id":106884466,"identity":"39071bbc-dc99-4b02-95a2-f916d83a747d","added_by":"auto","created_at":"2026-04-14 12:13:47","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":278523,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of observational cross-sectional studies (n = 3 studies; 3 comparisons; total n = 891 participants) comparing circulating TMAO concentrations between high and low meat intake groups. Effect sizes are expressed as mean differences in serum or plasma TMAO (µM); horizontal bars represent 95% confidence intervals. Individual study estimates are shown as filled squares sized proportionally to study weight. The random-effects pooled estimate is shown as a filled diamond (MD 2.35 µM, 95% CI −0.20 to 4.90); the fixed-effect estimate is shown as an open diamond (MD 1.30 µM, 95% CI 0.54 to 2.05). I² = 75%, indicating substantial between-study heterogeneity.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9382739/v1/bbcb32ad53870933858ca011.png"},{"id":106963355,"identity":"7baec289-829b-4f49-aa63-7e6b444d6193","added_by":"auto","created_at":"2026-04-15 09:43:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2423524,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9382739/v1/81f8367e-26d3-4ed7-b1f5-131823f1d928.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003ePlant-Forward Diets Lower Circulating TMAO in Adults: A Systematic Review and Meta-Analysis\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eCardiovascular disease (CVD) rank as leading cause of morbidity and mortality worldwide \u003csup\u003e1\u003c/sup\u003e, and diet is one of its most important modifiable determinants \u003csup\u003e2,3\u003c/sup\u003e. Contemporary evidence indicates that the global burden of CVD attributable to diet risk is still substantial and is driven not only by excessive intake of sodium, processed foods, and red meat, but also by insufficient consumption of whole grains, fruits, vegetables, legumes, nuts, and other plant foods \u003csup\u003e2\u003c/sup\u003e. While traditional nutritional epidemiology has often focused on single nutrients, this approach does not fully capture the complexity of human diets or the biological pathways through which diet exposures may influence cardiometabolic health. Increasingly, research has shifted toward dietary patterns and toward mechanistic intermediates that may help explain why certain ways of eating are associated with either higher or lower cardiovascular risk.\u003c/p\u003e\n\u003cp\u003eAmong these mechanistic intermediates, gut microbiota\u0026ndash;derived metabolites have attracted growing attention as candidate biomarkers\u0026mdash;and, in some cases, possible mediators\u0026mdash;of cardiometabolic risk . Trimethylamine N-oxide (TMAO) is the most extensively studied example \u003csup\u003e4\u0026ndash;6\u003c/sup\u003e. TMAO is generated when diet precursors such as choline, phosphatidylcholine, and L-carnitine are metabolized by gut microbes into trimethylamine (TMA), which is then oxidized in the liver by flavin monooxygenases. Experimental and human evidence has linked TMAO to several pathways relevant to atherosclerosis and CVD, including altered cholesterol handling \u003csup\u003e7\u003c/sup\u003e, vascular inflammation, impaired endothelial function\u003csup\u003e8\u003c/sup\u003e, thrombosis potential, and interactions with renal function. In observational settings, higher circulating concentrations of TMAO and related metabolites have also been associated with major adverse cardiovascular events and mortality \u003csup\u003e9\u003c/sup\u003e, supporting their relevance as intermediate cardiometabolic risk signals.\u003c/p\u003e\n\u003cp\u003eBecause TMAO is strongly influenced by the availability of diet precursors and by the composition and metabolic capacity of the gut microbiota, it represents a plausible mechanistic link between habitual diet and cardiometabolic risk \u003csup\u003e5\u003c/sup\u003e. This makes dietary pattern analysis particularly relevant, as whole diets may shape TMAO production not only through specific nutrients or foods, but also through broader host\u0026ndash;microbe interactions. In this context, comparing plant-forward and animal-based dietary exposures may help clarify whether differences in overall diet quality translate into distinct TMAO profiles\u003csup\u003e4\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWithin this framework, the contrast between plant-forward and animal-based dietary exposures has become relevant. Plant-forward diets, characterized by higher intakes of vegetables, fruits, legumes, nuts, and whole grains and by lower intakes of red and processed meat, are aligned not only with cardiometabolic prevention strategies \u003csup\u003e10\u003c/sup\u003e but also with sustainable dietary models such as the EAT-Lancet planetary health diet \u003csup\u003e11\u003c/sup\u003e. This predominantly plant-based dietary framework has been proposed to support both human and planetary health, and recent evidence suggests that greater adherence is generally associated with lower risk of all-cause mortality, cardiovascular disease, and type 2 diabetes\u003csup\u003e11\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eDespite growing literature, the evidence remains inconsistent. Studies have examined both specific food-group contrasts and broader dietary patterns, while findings vary according to biospecimen matrix, study design, and the potential contribution of preformed TMAO from seafood \u003csup\u003e6,12\u003c/sup\u003e. Moreover, not all plant-based diets appear equally beneficial, with healthier plant-based patterns showing more favorable microbiome features and lower TMAO than less healthy ones. \u003c/p\u003e\n\u003cp\u003eAgainst this background, a systematic synthesis of the available human evidence is warranted. We therefore conducted a systematic review and meta-analysis to evaluate whether plant-forward dietary exposures are associated with lower circulating TMAO concentrations compared with animal-based exposures in adults, distinguishing between food-group and dietary-pattern comparisons, and assessing consistency of findings across intervention and observational study designs.\u003c/p\u003e"},{"header":"METHODS","content":"\u003ch3\u003e\u003cstrong\u003eStudy Design and Registration\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThis systematic review was conducted in accordance with the PRISMA 2020 guidelines \u003csup\u003e13\u003c/sup\u003e. The protocol was prospectively registered in the International Prospective Register of Systematic Reviews (PROSPERO; registration number CRD420261326106).\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eLiterature Search Strategy\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eA systematic literature search was conducted in PubMed, MEDLINE (via Ovid), Embase (via Ovid), and Web of Science Core Collection from inception to February 2026, with no language restrictions. The search strategy combined controlled vocabulary \u0026mdash; MeSH terms in PubMed/MEDLINE and Emtree in Embase \u0026mdash; with free-text terms, structured around four conceptual domains: trimethylamine N-oxide (TMAO), the gut milieu and microbiome, metabolites and metabolomics, and dietary exposures. The core query followed the structure: (\u0026quot;trimethylamine n-oxide\u0026quot; OR \u0026quot;TMAO\u0026quot;) AND (\u0026quot;gut\u0026quot; OR \u0026quot;intestinal\u0026quot; OR \u0026quot;gut-derived\u0026quot; OR \u0026quot;gut-related\u0026quot;) AND (\u0026quot;metabolit*\u0026quot; OR \u0026quot;microbiot*\u0026quot; OR \u0026quot;microbiom*\u0026quot; OR \u0026quot;metabolom*\u0026quot;) AND (\u0026quot;association*\u0026quot; OR \u0026quot;relation*\u0026quot; OR \u0026quot;correlation*\u0026quot;). This was expanded with dietary and nutritional keywords to capture both food-group and dietary-pattern exposures, including: diet*, dietary, nutrition*, food*, \u0026quot;dietary pattern*\u0026quot;, plant-based, vegetarian*, vegan*, Mediterranean, DASH, animal-based, omnivor*, red meat, processed meat, poultry, egg*, dairy, fish, seafood, whole grain*, fiber, and resistant starch. Database-specific syntax, Boolean operators, truncation symbols, field tags, and proximity operators were applied as appropriate, and search strings were translated across all databases.\u003c/p\u003e\n\u003cp\u003eTo maximize sensitivity, no study-design filters were applied at the search stage. Records were limited to human research using database-appropriate limits, and non-eligible publication types were excluded using publication type filters and/or free-text terms as appropriate, including reviews, meta-analyses, editorials, commentaries, letters, consensus statements, and books or book chapters. Animal-only studies were excluded using validated database limits and exclusion logic to avoid inadvertently removing human studies that might include terms such as \u0026ldquo;animal-based diet.\u0026rdquo; Reference lists of included articles and relevant reviews were hand-searched, and forward citation tracking was conducted to identify additional eligible studies. Duplicate records were removed prior to screening. The complete search strategy is reported in \u003cstrong\u003eTable 1\u003c/strong\u003e, and the study selection process is summarized in \u003cstrong\u003eFig. 1\u003c/strong\u003e (PRISMA flow diagram).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo reviewers (FC and RZ) independently screened titles and abstracts for relevance. The full texts of potentially eligible articles were then retrieved and assessed against the predefined inclusion and exclusion criteria. Any disagreements were resolved through discussion, and when consensus could not be reached, a third reviewer (RS) was consulted. The study selection process was conducted in accordance with the PRISMA 2020 framework.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eEligibility Criteria (PICO Framework)\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eEligibility criteria were defined according to the PICO framework (\u003cstrong\u003eTable 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePopulation (P):\u003c/strong\u003e Human participants aged 18 years or older, of either sex, were eligible for inclusion. Studies conducted in healthy adults, as well as in adults with overweight, obesity, cardiometabolic risk factors, or stable chronic conditions, were considered eligible provided that TMAO was assessed in plasma/serum or urine. Animal studies, in vitro studies, pediatric populations, and studies conducted exclusively in pregnant women were excluded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIntervention/Exposure (I):\u003c/strong\u003e Eligible studies investigated dietary exposures potentially associated with TMAO and other gut-derived metabolites. These included plant-forward dietary patterns, vegetarian or vegan diets, Mediterranean- or DASH-style diets, plant-based substitutions, animal-based dietary patterns, and specific food-group exposures such as red or processed meat, poultry, eggs, dairy products, fish, seafood, fiber-rich foods, whole grains, resistant starch, legumes, and nuts. Both controlled dietary interventions and observational assessments of habitual dietary intake were considered.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparator (C):\u003c/strong\u003e Comparators included alternative dietary patterns, different levels of intake of the same food group, plant-forward versus animal-based dietary exposures, omnivorous or usual diets, or, in observational studies, lower versus higher adherence or intake categories. Studies without a formal comparator were also considered if they reported quantitative associations between dietary exposure and TMAO.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcomes (O):\u003c/strong\u003e The primary outcome was trimethylamine N-oxide (TMAO), measured in plasma/serum or urine. Studies were eligible if they reported absolute TMAO concentrations, changes in TMAO over time, or quantitative associations between dietary exposures and TMAO. Secondary outcomes, when available, included TMAO-related and other gut-derived metabolites, such as choline, carnitine, betaine, trimethylamine, phenylacetylglutamine (PAGln/PAG), indoxyl sulfate, p-cresyl sulfate (including p-cresol sulfate), and imidazole propionate, as well as inflammatory and cardiometabolic biomarkers.\u003c/p\u003e\n\u003cp\u003eEligible study designs included randomized controlled trials, non-randomized dietary interventions, crossover feeding studies, prospective and retrospective cohort studies, case-control studies, and cross-sectional studies. Reviews, meta-analyses, editorials, commentaries, letters, conference abstracts without sufficient data, book chapters, and consensus papers were excluded. For the quantitative synthesis, only studies providing sufficiently comparable numerical data were considered for meta-analysis, whereas all eligible studies were included in the qualitative synthesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e. Search strategy structured according to the PICO framework.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"602\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.113%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePICO domain\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 30.0664%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConcept\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53.8206%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSearch terms / keywords\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.113%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePopulation\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 30.0664%;\"\u003e\n \u003cp\u003eHuman adult populations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53.8206%;\"\u003e\n \u003cp\u003eadults OR humans OR men OR women OR participants OR patients OR \u0026quot;aged 18 and over\u0026quot; OR \u0026quot;18 years and older\u0026quot; OR \u0026quot;adult population\u0026quot; OR \u0026quot;working age\u0026quot; OR \u0026quot;middle aged\u0026quot; OR \u0026quot;older adults\u0026quot; OR \u0026quot;elderly\u0026quot;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.113%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eI/E\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eIntervention / Exposure\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 30.0664%;\"\u003e\n \u003cp\u003eDietary exposures, food groups, and dietary patterns potentially associated with TMAO and other gut-derived metabolites\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53.8206%;\"\u003e\n \u003cp\u003ediet* OR dietary OR nutrition* OR food* OR \u0026quot;dietary pattern*\u0026quot; OR \u0026quot;plant-based\u0026quot; OR vegetarian* OR vegan* OR Mediterranean OR DASH OR \u0026quot;animal-based\u0026quot; OR omnivor* OR \u0026quot;red meat\u0026quot; OR \u0026quot;processed meat\u0026quot; OR poultry OR egg* OR dairy OR fish OR seafood OR \u0026quot;whole grain*\u0026quot; OR fiber OR \u0026quot;resistant starch\u0026quot; OR legumes OR nuts\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.113%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eComparator\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 30.0664%;\"\u003e\n \u003cp\u003eAlternative dietary exposures, lower versus higher intake categories, plant-forward versus animal-based patterns, or usual diet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53.8206%;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eComparator terms were not explicitly required in the search string in order to maximize sensitivity; comparators were addressed during study selection and eligibility assessment.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.113%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eO\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eOutcomes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 30.0664%;\"\u003e\n \u003cp\u003ePrimary metabolite outcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53.8206%;\"\u003e\n \u003cp\u003e\u0026quot;trimethylamine n-oxide\u0026quot; OR TMAO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.113%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExcl.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eExclusion block\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 30.0664%;\"\u003e\n \u003cp\u003eNon-eligible publication types and animal-only studies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53.8206%;\"\u003e\n \u003cp\u003eNOT (review OR \u0026quot;meta-analysis\u0026quot; OR editorial OR commentary OR letter OR consensus OR \u0026quot;book chapter\u0026quot; OR book OR animal OR pig OR pigs OR rat OR rats OR mice)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch3\u003e\u003cstrong\u003eQuality Assessment\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThe methodological quality and risk of bias of the included studies were assessed according to study design. Randomized controlled trials, including parallel-group, crossover, and controlled-feeding randomized studies, were evaluated using the Cochrane Risk of Bias 2 (RoB-2) tool, which assesses bias across five domains: the randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported result. For crossover trials, the crossover-specific RoB-2 version was applied to account for potential carryover effects, period effects, and washout adequacy \u003csup\u003e14\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eProspective and longitudinal cohort studies were assessed using the Newcastle\u0026ndash;Ottawa Scale (NOS), which evaluates study quality according to the selection of participants, comparability of study groups, and ascertainment of exposure or outcomes. The NOS was applied using the original Ottawa Hospital Research Institute guidance \u003csup\u003e15\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAnalytical cross-sectional studies were appraised using the JBI Critical Appraisal Checklist for Analytical Cross-Sectional Studies, which focuses on the appropriateness of inclusion criteria, validity and reliability of exposure and outcome measurement, identification and management of confounding, and adequacy of statistical analysis \u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eUncontrolled pre\u0026ndash;post intervention studies and before\u0026ndash;after feeding studies without a comparator group were evaluated using the National Institutes of Health (NIH) Quality Assessment Tool for Before\u0026ndash;After (Pre\u0026ndash;Post) Studies With No Control Group, which examines clarity of study objectives, eligibility criteria, participant representativeness, intervention description, outcome assessment, follow-up, and statistical analysis (https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeta-analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe meta-analysis was performed using a random-effects model, with between-study variance (\u0026tau;\u0026sup2;) estimated by Restricted Maximum Likelihood (REML) \u003csup\u003e17,18\u003c/sup\u003e. Effect sizes were expressed as mean differences (MD) in circulating TMAO concentrations between dietary exposure and comparator groups, with corresponding standard errors. Separate analyses were conducted by study design \u0026mdash; randomized controlled trials and cross-sectional studies \u0026mdash; and further stratified by exposure type. The variable \u003cem\u003eType\u003c/em\u003e distinguished studies evaluating the effect of specific food group substitutions (e.g., animal- versus plant-based foods) from those assessing adherence to broader dietary patterns. This two-level stratification allowed simultaneous accounting for within- and between-study heterogeneity \u003csup\u003e19\u003c/sup\u003e, yielding both overall and subgroup-specific pooled estimates.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eStudy selection and characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 34 studies \u003csup\u003e3\u0026ndash;6,12,20\u0026ndash;48\u003c/sup\u003emet the inclusion criteria. Characteristics of all included studies are summarized in \u003cstrong\u003eTable 2\u003c/strong\u003e. No time restrictions were set, and the selected publications spanned the period from 2006 to 2024, with a median publication year of 2019 (IQR 2018\u0026ndash;2022), indicating a marked increase in interest in this topic in recent years. The included studies were conducted across 11 countries, predominantly in the United States (17/34; 50.0%), followed by the United Kingdom (4/34; 11.8%), and Italy and Norway (3/34; 8.8% each), with additional contributions from Spain, Sweden, Poland, Australia, Denmark, New Zealand, and China. Based on the sample sizes reported in each study, the overall summed study population comprised 8,045 participants. Most included studies were randomized dietary intervention or controlled feeding trials (24/34; 70.6%), including parallel, crossover, and crossover-feeding designs. The remaining studies consisted of 6 cross-sectional studies (17.6%), 2 cohort studies (5.9%), and 2 uncontrolled intervention/pre\u0026ndash;post studies (5.9%). The populations were heterogeneous and included healthy adults (16 studies) as well as adults with overweight/obesity, cardiometabolic risk factors, or established clinical conditions (18 studies). Reported mean or median age ranged from approximately 22 to 74 years. Regarding the biological matrix used for TMAO assessment, 25 studies measured TMAO in blood (plasma or serum), 6 studies in urine, and 3 studies in both blood and urine.\u003c/p\u003e\n\u003cp\u003eTo facilitate synthesis of the evidence, exposures were grouped \u003cem\u003ea priori\u003c/em\u003e into two broad categories: food group (n = 15) and dietary pattern (n = 19). This classification was adopted pragmatically to improve the interpretability of findings, given the wide variability in how dietary exposures were defined across studies. Food group exposures included comparisons focused on specific foods or substitutions, such as meat, plant-based meat alternatives, seafood, or protein sources. Dietary pattern exposures included broader eating patterns or dietary prescriptions, such as Mediterranean, DASH, vegan or vegetarian, Paleolithic, among the others.\u003c/p\u003e\n\u003cp\u003eFor the quantitative synthesis, we extracted or derived, whenever possible, the mean difference (MD) between plant-forward and animal-based dietary exposures, together with the corresponding standard deviation (SD), standard error (SE), 95% confidence intervals (95% CI), and p values. Only 11 study-level comparisons provided sufficiently comparable numerical data for meta-analysis \u003csup\u003e3,20,22,24\u0026ndash;26,35,36,38,43\u003c/sup\u003e. These included 8 RCTs and 3 cross-sectional comparisons. Seafood-focused studies were retained in the qualitative synthesis but were not pooled because fish and seafood contain preformed TMAO, which could confound the interpretation of circulating TMAO differences. Likewise, studies reporting only urinary TMAO or non-combinable association measures were not included in the quantitative synthesis. Because of methodological heterogeneity, separate forest plots were generated for RCTs and observational cross-sectional studies. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. \u003c/strong\u003eCharacteristics of included studies (n=34). Study design, population characteristics, dietary exposure, TMAO biospecimen matrix, and key findings, stratified by exposure category (FG: food group; DP: dietary pattern).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"979\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst author, year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePopulation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDietary exposure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTMAO matrix\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 372px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKey finding\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eCrimarco, 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT crossover\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy omnivorous adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e50 \u0026plusmn; 14 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePlant-based meat vs animal meat (8 wk each)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003ePlant-based meat: 2.7 \u0026micro;M vs animal meat: 4.7 \u0026micro;M; MD \u0026minus;2.0 \u0026micro;M (p=0.012)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eFarsi, 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT crossover\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy male adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e30.4 \u0026plusmn; 7.9 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMycoprotein vs red+processed meat (14 d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eUrine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eUrinary TMAO not significantly different between phases (p=0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eTate, 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT parallel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eObese older adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e65\u0026ndash;84 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eDASH + 3 oz vs 6 oz lean beef/day (12 wk)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eTMAO increased overall (+26.5%, p\u0026lt;0.001); greater with 6 oz beef (p=0.033)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eV\u0026aacute;zquez-Fresno, 2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eSpain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT parallel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eAdults at high CVD risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e55\u0026ndash;80 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMediterranean diet (PREDIMED; 1- and 3-year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eUrine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eUrinary TMAO lower with higher MD adherence (ANCOVA; p=0.003\u0026ndash;9.56\u0026times;10⁻⁵)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eBarrea, 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eItaly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy normal-weight adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e31.6 \u0026plusmn; 6.2 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMediterranean diet adherence; food groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eHigher MD adherence inversely associated with TMAO (r\u0026asymp;\u0026minus;0.50, p\u0026lt;0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eKrishnan, 2022a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT crossover\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eOverweight/obese adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e30\u0026ndash;69 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMediterranean-style diet: low vs moderate lean red meat (5 wk)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eLow red meat: 3.1 \u0026micro;M vs moderate: 5.0 \u0026micro;M (p\u0026lt;0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eKrishnan, 2022b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT parallel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eOverweight/obese women at cardiometabolic risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e20\u0026ndash;65 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eDietary Guidelines for Americans vs Typical American Diet (8 wk)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eNo significant difference in TMAO between diet groups\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003ePark JE, 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT crossover\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy normolipidemic adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e30.6 \u0026plusmn; 9.6 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eAtkins vs Ornish vs South Beach diets (4 wk each)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eAtkins vs Ornish: 3.3 vs 1.8 \u0026micro;M (p=0.01); Atkins vs South Beach NS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eShen X, 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eAging adults (BLSA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e705 (TMAO n=425)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e71.0 \u0026plusmn; 12.8 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePlant-based diet index (hPDI); food groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eHigher hPDI inversely associated with TMAO (q\u0026lt;0.05); fish/seafood positively correlated (\u0026rho;=0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eCostabile, 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eItaly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT parallel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eAdults with metabolic syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e78 / 48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e53\u0026ndash;57 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMarine LCn3/whole-grain vs refined cereals (8\u0026ndash;12 wk)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eMarine LCn3 and whole-grain diets increased TMAO (p=0.007; p=0.037)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eSchmedes, 2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eNorway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT crossover\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e~50 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eLean-seafood vs non-seafood diet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum + urine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eLean-seafood significantly increased TMAO vs non-seafood (plasma and urine)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eSchmedes, 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eNorway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT crossover\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e50.6 \u0026plusmn; 3.4 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eLean-seafood vs non-seafood diet (4 wk each)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eLean-seafood increased postprandial TMAO (diet\u0026times;time p=0.008)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eWang Z, 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT crossover\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy omnivorous adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e21\u0026ndash;65 y (median 45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eRed meat vs white meat vs non-meat protein (4 wk each)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum + urine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eRed meat: ~3-fold higher plasma TMAO vs non-meat (p\u0026lt;0.0001); median diff \u0026minus;5.9 \u0026micro;M\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eDhakal, 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT crossover\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy older adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e66 y (mean)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eLean pork vs chicken within DGA-based diet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eTMAO fold change non-inferior pork vs chicken; p=0.07 (NS)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eLi J, 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eLongitudinal cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy free-living men (MLVS/HPFS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e~71.4 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eRed meat intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eRed meat intake positively associated with circulating TMAO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eWang, 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eProspective cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eCommunity-dwelling adults \u0026ge;65 y (CHS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e3,931\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026ge;65 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMeat, poultry, fish, processed meat, egg intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eTotal meat (\u0026rho;=0.047) and unprocessed red meat (\u0026rho;=0.060) weakly correlated with TMAO (p\u0026lt;0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eHuang Y, 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eChinese adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e754 (TMAO n=333)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eRed meat intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eHigher red meat intake associated with higher serum TMAO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eGarc\u0026iacute;a-P\u0026eacute;rez I, 2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT crossover\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy adults (inpatient)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e55.8 \u0026plusmn; 12.6 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eHigh vs low DASH-score diet (72h inpatient; 4 phases)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eUrine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eUrinary TMAO higher after high-DASH diet vs low-DASH diet (p\u0026lt;0.0001); driven by fish content\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eDe Filippis, 2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eItaly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy adults (omnivore, vegetarian, vegan)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMediterranean diet adherence; dietary pattern (omnivore vs veg*n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eUrine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eHigher MD adherence and veg*n diet associated with lower urinary TMAO (p\u0026lt;0.0001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eGriffin, 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT parallel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eAdults at risk for colon cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e115 (90 completers)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e52 \u0026plusmn; 12 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMediterranean vs Healthy Eating diet (6 months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eNo significant change in plasma TMAO after 6-month Mediterranean diet intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eMalinowska AM, 2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003ePoland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eElderly women (free-living)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e68.5 \u0026plusmn; 7.4 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eWestern vs prudent dietary pattern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eWestern-style pattern associated with higher plasma TMAO across tertiles\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eArgyridou, 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ePre\u0026ndash;post (single-arm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eAdults with dysglycemia/obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e57.8 \u0026plusmn; 10.0 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e8-week vegan diet (Plant Your Health trial)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eTMAO decreased at wk1 and wk8 vs baseline (p=0.004); rebound after unrestricted diet\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eLandry, 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT parallel (twin)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy identical twin pairs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e44 (22 pairs)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e39.6 \u0026plusmn; 12.7 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eHealthy vegan vs healthy omnivorous diet (8 wk)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eVegan: 2.9 \u0026micro;M vs omnivorous: 4.9 \u0026micro;M; MD \u0026minus;2.1 \u0026micro;M (95% CI \u0026minus;7.7 to 3.6; NS)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eDjekic, 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eSweden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT crossover\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ePatients with ischemic heart disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e31 (27 completers)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eMedian 67 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eVegetarian vs meat diet (4 wk each)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eTMAO decreased after vegetarian diet (\u0026minus;1.90 \u0026micro;M vs baseline, p\u0026lt;0.001); between-diet diff NS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eHeianza Y, 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT parallel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eOverweight/obese adults (POUNDS Lost)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eEnergy-reduced diets varying fat/protein (4 arms)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eNo significant differences in \u0026Delta;TMAO across macronutrient-varying diet groups\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eErickson, 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT parallel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eObese insulin-resistant older adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e66.1 \u0026plusmn; 4.4 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eExercise + hypocaloric vs eucaloric diet (12 wk)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eCaloric restriction + exercise: TMAO \u0026minus;31% vs +32% with eucaloric (p=0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eZhou, 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT parallel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eOverweight/obese adults (POUNDS Lost)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e52.3 \u0026plusmn; 8.9 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eEnergy-reduced diets varying fat/protein (4 arms)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eMedian \u0026Delta;TMAO = 0.0 \u0026micro;mol/L; no significant differences across diet groups (p=0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eSchmedes, 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eNorway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT crossover\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e~50 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eLean-seafood vs non-seafood diet (~4 wk each)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eLean-seafood significantly increased circulating TMAO vs non-seafood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eBoutagy, 2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ePre\u0026ndash;post (single-arm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy nonobese young men\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e22.1 \u0026plusmn; 0.5 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eHigh-fat diet (5 d) vs eucaloric control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003ePostprandial TMAO increased after high-fat diet; fasting TMAO unchanged\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eGenoni A, 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eAustralia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ePaleolithic followers vs controls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e39\u0026ndash;45 y (mean)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eLong-term Paleolithic diet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eStrict Paleo: 9.53 \u0026micro;M vs controls: 3.93 \u0026micro;M (p=0.008); red meat positively associated (r=0.357)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eRasmussen LG, 2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eDenmark\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT parallel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eOverweight non-diabetic adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e42\u0026ndash;44 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eHigh-protein vs low-protein diet (6 months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eUrine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eTendency toward higher urinary TMAO with high-protein diet (NMR metabolomics)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eMitchell, 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eNew Zealand\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT parallel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy older men\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e74.2 \u0026plusmn; 3.6 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eProtein at 2\u0026times;RDA vs RDA (10 wk)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum + urine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003ePlasma TMAO increased with 2\u0026times;RDA protein (p=0.004; time\u0026times;diet p=0.002)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eStarr KNP, 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT parallel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eObese middle-aged/older adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e~64 \u0026plusmn; 8 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eHigher-protein + lean red meat vs RDA protein (6 months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePlasma or serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eNo significant increase in plasma TMAO with higher-protein lean red meat diet\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eStella C, 2006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eUK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRCT crossover\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHealthy male adults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e25\u0026ndash;74 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eHigh-meat vs low-meat vs vegetarian diet (15 d each)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eUrine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 372px;\"\u003e\n \u003cp\u003eUrinary TMAO elevated during high-meat vs low-meat and vegetarian periods (NMR)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations: FG, food group; DP, dietary pattern; RCT, randomized controlled trial; TMAO, trimethylamine N-oxide; MD, mean difference; NMR, nuclear magnetic resonance; DGA, Dietary Guidelines for Americans; DASH, Dietary Approaches to Stop Hypertension; hPDI, healthful plant-based diet index; LCn3, long-chain omega-3 fatty acids; NS, not significant; NR, not reported\u003c/em\u003e\u003cem\u003e\u003cbr clear=\"all\"\u003e \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuality assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the 24 RCTs, 23 were judged as having some concerns and 1 as high risk of bias (\u003cstrong\u003eFig. 2\u003c/strong\u003e). Concerns were mainly related to the randomization process, deviations from intended interventions, and selection of the reported result, whereas outcome measurement was consistently rated at low risk across all studies. \u003cstrong\u003eFig. 3\u003c/strong\u003e summarizes the quality assessment of non-randomized studies. Both cohort studies (panel A) were rated as good quality using the NOS. Among the six cross-sectional studies (panel B), five were judged as low risk/high quality, whereas De Filippis \u003csup\u003e34\u003c/sup\u003e showed some concerns related mainly to confounding. The two before\u0026ndash;after studies without controls (panel C) were rated as fair \u003csup\u003e37\u003c/sup\u003e and poor \u003csup\u003e42\u003c/sup\u003e, reflecting the limitations inherent to uncontrolled pre\u0026ndash;post designs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeta-analysis \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe quantitative synthesis included 11 study-level comparisons, comprising 8 randomized controlled trials and 3 observational cross-sectional studies. In the RCT meta-analysis (\u003cstrong\u003eFig. 4\u003c/strong\u003e), plant-forward dietary exposures were associated with significantly lower serum TMAO concentrations than animal-based exposures, with a pooled random-effects mean difference of \u0026minus;1.08 \u0026micro;M (95% CI \u0026minus;1.52 to \u0026minus;0.65; I\u0026sup2;=0%). Subgroup analyses showed consistent results for both dietary-pattern interventions (\u0026minus;0.85 \u0026micro;M, 95% CI \u0026minus;1.52 to \u0026minus;0.17; I\u0026sup2;=0%) and food-group interventions (\u0026minus;1.24 \u0026micro;M, 95% CI \u0026minus;1.86 to \u0026minus;0.62; I\u0026sup2;=10%), with no significant subgroup differences. In contrast, the meta-analysis of cross-sectional studies (\u003cstrong\u003eFig. 5\u003c/strong\u003e), comparing high versus low meat intake, showed substantial heterogeneity (I\u0026sup2;=75%). The pooled random-effects estimate was 2.35 (95% CI \u0026minus;0.20 to 4.90), whereas the fixed-effect estimate was 1.30 (95% CI 0.54 to 2.05). Because this comparison was defined as higher versus lower meat intake, the positive effect estimate indicates higher serum TMAO concentrations among participants with greater meat consumption. Overall, the meta-analysis supports a consistent TMAO-lowering effect of plant-forward dietary exposures in intervention studies, while observational findings point in the same direction but are less precise because of between-study heterogeneity.\u003cstrong\u003e\u003c/strong\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe aim of this systematic review and meta-analysis was to evaluate whether plant-forward diet exposure is associated with lower circulating TMAO concentrations than animal-based diet in adults, while distinguishing between food-group and dietary-pattern. Across 34 studies included in the qualitative synthesis, the overall evidence suggested a consistent directional pattern: plant-forward exposures tended to be associated with lower TMAO, whereas animal-based exposures\u0026mdash;particularly higher meat intake\u0026mdash;tended to be associated with higher TMAO. In the quantitative synthesis, 11 study-level comparisons were meta-analyzed. Among the 8 RCTs, plant-forward interventions were associated with significantly lower serum/plasma TMAO concentrations than animal-based interventions, with a pooled mean difference of \u0026minus;1.08 \u0026micro;M (95% CI \u0026minus;1.52 to \u0026minus;0.65). This pattern remained consistent in subgroup analyses of both dietary-pattern interventions and food-group interventions. In contrast, the 3 cross-sectional studies comparing high versus low meat intake suggested higher TMAO with greater meat consumption, but with substantial heterogeneity, indicating that observational evidence was directionally supportive but methodologically less stable.\u003c/p\u003e\n\u003cp\u003eFrom a clinical perspective, these findings are relevant because TMAO is well-acknowledged as a gut microbiota\u0026ndash;related marker linked to cardiometabolic risk, atherosclerotic disease, and adverse cardiovascular outcomes, although causal role remains debated \u003csup\u003e5,6\u003c/sup\u003e. The present results suggest that diets emphasizing plant foods and reducing animal source\u0026mdash;especially red and processed meat\u0026mdash;may shift the circulating TMAO profile in a more favorable direction. Importantly, the consistency of the pooled RCT estimate strengthens the interpretation that this association is not purely observational but is at least partly diet-responsive under controlled conditions.\u003c/p\u003e\n\u003cp\u003eThis interpretation is biologically plausible. Plant-forward diets generally reduce exposure to dietary precursors of TMAO, including L-carnitine and choline-rich animal foods, while at the same time providing more fiber and plant substrates that may favourably shape gut microbial ecology. Several intervention studies included in this review support this framework. In the SWAP-MEAT trial, replacing animal meat with plant-based meat alternatives significantly lowered circulating TMAO \u003csup\u003e20\u003c/sup\u003e. Similarly, an 8-week randomized trial in identical twins found lower TMAO under a healthy vegan diet compared with a healthy omnivorous diet \u003csup\u003e3\u003c/sup\u003e. In overweight or obese adults, a Mediterranean-style dietary pattern with lowered meat intake reduced fasting TMAO, whereas a similar pattern with moderate red meat intake did not, suggesting that the overall healthfulness of the diet may not fully offset the effect of animal-source precursor load \u003csup\u003e24\u003c/sup\u003e. Likewise, chronic red meat intake has been shown to increase plasma and urinary TMAO compared with non-meat protein sources under controlled feeding conditions \u003csup\u003e30\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe observational findings were directionally concordant with the intervention evidence. Higher meat intake was associated with higher TMAO, although heterogeneity was substantial, likely reflecting differences in study populations, exposure assessment, background diets, renal function, microbiome composition, and biospecimen handling. This variability is not surprising, because TMAO is not merely a readout of food intake; it reflects a dynamic interaction between dietary precursors, gut microbial metabolic capacity, and host metabolism \u003csup\u003e5\u003c/sup\u003e. For this reason, the clinical significance of a given TMAO concentration should be interpreted in context, rather than as a stand-alone nutritional target.\u003c/p\u003e\n\u003cp\u003eAnother clinically important point is that not all animal-source foods behave similarly. Seafood-focused studies were deliberately excluded from the pooled meta-analysis because fish and seafood contain preformed TMAO, which may elevate circulating concentrations through a mechanism distinct from endogenous microbial generation from meat-derived precursors. Controlled studies have shown that lean-seafood diets can increase fasting or postprandial TMAO despite otherwise favorable cardiometabolic features \u003csup\u003e29\u003c/sup\u003e. This reinforces the idea that TMAO should not be interpreted simplistically as a universal marker of \u0026ldquo;healthy\u0026rdquo; or \u0026ldquo;unhealthy\u0026rdquo; eating, but rather as a context-dependent metabolite whose meaning depends on food source, microbiome function, and cardiometabolic background.\u003c/p\u003e\n\u003cp\u003eTaken together, the present findings may have practical implications for dietary counseling, particularly in individuals with overweight, obesity, insulin resistance, dyslipidemia, or established cardiovascular disease. While TMAO should not replace established clinical outcomes, it may provide a useful intermediate biomarker through which plant-forward dietary strategies could exert cardiometabolic benefit. In this sense, our results are consistent with a broader movement toward dietary models that combine metabolic and environmental relevance, including Mediterranean-style and other plant-forward eating patterns.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eStrengths and limitations\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThis study has several strengths. First, to our knowledge, it provides one of the most focused syntheses of the literature comparing plant-forward versus animal-based dietary exposures in relation to circulating TMAO. Second, we separated food-group and dietary-pattern comparisons, which improved interpretability and allowed us to show that the overall direction of effect was consistent across both exposure types. Third, we analyzed RCTs and observational cross-sectional studies separately, thereby avoiding inappropriate pooling across fundamentally different study designs. Fourth, we deliberately excluded seafood-focused studies from the quantitative synthesis to minimize confounding by preformed TMAO, which strengthens the internal coherence of the pooled estimates.\u003c/p\u003e\n\u003cp\u003eThis study has also several limitations. The total number of studies that could be quantitatively pooled was relatively small, especially for the observational meta-analysis. Reporting formats were highly heterogeneous: some studies presented means and standard deviations, whereas others reported medians, relative intensities, p-value contrasts, or graphical data only. Several crossover trials required careful handling because paired variance estimates were not always fully available. In addition, exposures were diverse, ranging from whole dietary patterns to single food substitutions, which may limit direct comparability. TMAO was measured in different biological matrices, although the meta-analysis was restricted to serum/plasma studies whenever possible. Another important limitation is that the gut microbiota was not systematically incorporated into the quantitative synthesis, despite its central role in TMAO generation. Although several studies acknowledged or explored microbiome-related mechanisms, the available data were still too limited, heterogeneous, and inconsistently reported to allow a methodologically robust synthesis of microbiota-related findings. As a result, the present review could not adequately address how inter-individual differences in microbial composition or function may modify the association between diet and circulating TMAO. Finally, because TMAO is an intermediate biomarker rather than a hard clinical endpoint, its interpretation should remain cautious and embedded within the broader cardiometabolic, dietary, and host\u0026ndash;microbiome context.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis systematic review and meta-analysis demonstrate that plant-forward dietary exposures are associated with lower circulating TMAO concentrations compared with animal-based exposures in adults, with the most consistent evidence derived from RCTs. Observational data were directionally concordant, linking greater meat intake to higher TMAO concentrations, albeit with substantial between-study heterogeneity. Collectively, the available evidence suggests that shifting toward plant-forward dietary strategies may beneficially modulate circulating TMAO; however, larger, well-standardized human studies with harmonized exposure definitions, standardized biospecimen protocols, and consistent outcome reporting are needed to establish the clinical relevance of these findings and their translation into dietary recommendations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval:\u0026nbsp;\u003c/strong\u003eNot required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest:\u0026nbsp;\u003c/strong\u003eNone of the authors has a financial or other interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eThe authors thank the research teams behind all primary studies included in this systematic review and meta-analysis for making their data available. C.M. acknowledges\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ethe Chronic Disease Research Foundation (CDRF), by the Italian Ministry of Education and Research: Dipartimenti di Eccellenza Program 2023\u0026ndash;2027, and by the Italian Ministry of Health \u0026ndash; Bando Ricerca Corrente.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eR.Z.: Conceptualization, Methodology, Formal analysis, Investigation, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing. F.Ca.: Conceptualization, Methodology, Investigation, Writing \u0026ndash; review \u0026amp; editing. F.Cat.: Investigation, Data curation, Writing \u0026ndash; review \u0026amp; editing. L.L.: Investigation, Data curation, Writing \u0026ndash; review \u0026amp; editing. Y.Z.: Methodology, Writing \u0026ndash; review \u0026amp; editing. G.L.: Writing \u0026ndash; review \u0026amp; editing, Supervision. A.Ma.: Writing \u0026ndash; review \u0026amp; editing. M.A.I.: Writing \u0026ndash; review \u0026amp; editing. A.R.-M.: Writing \u0026ndash; review \u0026amp; editing. C.M.: Funding acquisition, Writing \u0026ndash; review \u0026amp; editing. D.J.C.: Writing \u0026ndash; review \u0026amp; editing. T.P.: Writing \u0026ndash; review \u0026amp; editing. K.N.: Writing \u0026ndash; review \u0026amp; editing. F.R.: Writing \u0026ndash; review \u0026amp; editing. H.M.: Writing \u0026ndash; review \u0026amp; editing. I.A.P.: Writing \u0026ndash; review \u0026amp; editing. M.I.: Methodology, Formal analysis, Writing \u0026ndash; review \u0026amp; editing, Supervision. R.S.: Conceptualization, Methodology, Formal analysis, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing, Supervision, Project administration. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u0026nbsp;\u003c/strong\u003eAll data analysed in this study are included in the published articles referenced.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChong, B. \u003cem\u003eet al.\u003c/em\u003e Global burden of cardiovascular diseases: projections from 2025 to 2050. \u003cem\u003eEur J Prev Cardiol\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 1001\u0026ndash;1015 (2025).\u003c/li\u003e\n\u003cli\u003eFang, Y. \u003cem\u003eet al.\u003c/em\u003e The burden of cardiovascular disease attributable to dietary risk factors in the provinces of China, 2002-2018: a nationwide population-based study. \u003cem\u003eLancet Reg Health West Pac\u003c/em\u003e \u003cstrong\u003e37\u003c/strong\u003e, 100784 (2023).\u003c/li\u003e\n\u003cli\u003eLandry, M. 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N. \u003cem\u003eet al.\u003c/em\u003e Impact on cardiometabolic risk of a weight loss intervention with higher protein from lean red meat: Combined results of 2 randomized controlled trials in obese middle-aged and older adults. \u003cem\u003eJ Clin Lipidol\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 920\u0026ndash;931 (2019).\u003c/li\u003e\n\u003cli\u003eStella, C. \u003cem\u003eet al.\u003c/em\u003e Susceptibility of human metabolic phenotypes to dietary modulation. \u003cem\u003eJ Proteome Res\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 2780\u0026ndash;2788 (2006).\u003c/li\u003e\n\u003cli\u003eBarrea, L. \u003cem\u003eet al.\u003c/em\u003e Trimethylamine N-oxide, Mediterranean diet, and nutrition in healthy, normal-weight adults: also a matter of sex? \u003cem\u003eNutrition\u003c/em\u003e \u003cstrong\u003e62\u003c/strong\u003e, 7\u0026ndash;17 (2019).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Department of Research, Innovation, and Technology Transfer, Health Directorate, Taranto Local Health Authority, Taranto, Italy","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"trimethylamine N-oxide, TMAO, dietary patterns, plant-based diet, animal-based diet, gut microbiota, cardiovascular risk, meta-analysis, systematic review, food groups","lastPublishedDoi":"10.21203/rs.3.rs-9382739/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9382739/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDiet modulates circulating trimethylamine N-oxide (TMAO), a gut microbiota-derived metabolite linked to cardiovascular risk; whether plant-forward versus animal-based dietary patterns consistently influence TMAO concentrations in adults remains unclear. A PRISMA-2020-compliant systematic review and meta-analysis (PROSPERO: CRD420261326106) was conducted through February 2026 across multiple databases; eligible studies assessed dietary patterns, food groups, or diet-related interventions in relation to circulating TMAO in adults. Random-effects meta-analyses were performed where data were combinable. Thirty-four studies were included; 11 contributed to quantitative synthesis. Eight RCTs showed significantly lower TMAO with plant-forward versus animal-based exposures (pooled MD −1.08 µM, 95% CI −1.52 to −0.65; I² [a measure of between-study heterogeneity] = 0%), consistent across dietary-pattern (−0.85 µM) and food-group subgroups (−1.24 µM). Three cross-sectional studies linking higher meat intake to higher TMAO showed substantial heterogeneity (I² = 75%). Plant-forward diets are associated with lower circulating TMAO in adults, with the strongest evidence from RCTs.\u003c/p\u003e","manuscriptTitle":"Plant-Forward Diets Lower Circulating TMAO in Adults: A Systematic Review and Meta-Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-14 12:13:43","doi":"10.21203/rs.3.rs-9382739/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eb212692-b1d5-4ec5-8c53-d711717f8773","owner":[],"postedDate":"April 14th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":66112919,"name":"Nutrition \u0026 Dietetics"},{"id":66112920,"name":"Epidemiology"}],"tags":[],"updatedAt":"2026-04-14T12:13:43+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-14 12:13:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9382739","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9382739","identity":"rs-9382739","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}