The American Journal of Clinical Nutrition

Undernutrition in early childhood causes stunted growth, cognitive delays, and anemia, with effects often magnified among children from the poorest households. Small-quantity lipid-based nutrient supplements (SQ-LNS) are effective in addressing undernutrition and improving child development. As momentum builds to scale up SQ-LNS for children aged 6-24 months in the Global South, a key concern is achieving equity in its distribution and outcomes. We performed equity analysis of individual participant data from 14 randomized controlled trials in nine countries (N=37,707 children) to assess SQ-LNS effects on child growth, development, and anemia across levels of an international wealth index. Benefits of SQ-LNS were consistent across the wealth spectrum, leading to similar improvements in child growth, development, and anemia regardless of wealth. However, such equal benefits of SQ-LNS did not erase large inequities in child growth and development between the poorest and wealthier households.

Background: Black adults bear a disproportionate burden of cardiometabolic dysfunction, yet most dietary trial evidence comes from predominantly White cohorts. Objective: To evaluate whether a personalized whole-food dietary intervention improves cardiometabolic outcomes more in Black than White young adults with overweight or obesity. Methods: In this 8-week randomized, controlled trial (ClinicalTrials.gov: NCT04635917), 112 Black and White adults (18-35 years; BMI 25-45 kg/m2) were block-randomized by race to a personalized dietary intervention providing whole foods (PD, n=57) or conventional dietary counseling at baseline (BL) using MyPlate guidelines (CD, n=55). Primary outcomes were Matsuda Index and fasting and OGTT-derived glucose, insulin, and non-esterified fatty acids. Other glucoregulatory, cardiovascular, anthropometric, appetite, and cognitive outcomes were also assessed. Outcomes were analyzed using baseline-adjusted linear models with sensitivity analyses adjusting for baseline BMI and food security score. Results: Compliance with study food consumption was 85-91%. Diet quality was higher in PD than CD (P < 0.05), with larger gains in vegetable-related outcomes among Black participants (group x race, P < 0.05). HOMA-{beta} was lower in PD than CD overall (P < 0.05). In sensitivity analyses, Black PD participants had greater fasting insulin reductions than White, especially in the latter half of intervention (week x group x race, P < 0.05), with a similar tendency for HOMA-IR. Glucose AUC 0-30 min was higher in White than Black PD participants (group x race, P < 0.05). Concentration performance was higher in PD than CD overall (P < 0.05), with larger gains in processing speed and accuracy among Black than White participants (group x race, P < 0.05). No effects were observed for cardiovascular or appetite outcomes. Conclusions: The personalized whole-food intervention produced differential effects in fasting insulin and early-phase glucose handling, and greater benefits in attention, in Black compared with White young adults with overweight or obesity during weight maintenance.

BackgroundGene-based nutrition recommendations have emerged as a strategy for weight management, but their effectiveness over standard advice remains uncertain. ObjectiveThis study evaluated MyGeneMyDiet(R) recommendations versus standard advice on anthropometry, biochemical markers, and dietary intake in overweight and obese Filipino adults over 12 months. MethodsIn this 12-month randomized controlled trial, participants received either MyGeneMyDiet(R) or standard advice. Both groups underwent regular nutrition counseling during the active phase (months 0-6) before transitioning to free-living conditions (months 6-12). Primary outcomes included weight, BMI, waist circumference, and body fat percentage; secondary outcomes were dietary intake and biochemical markers. Analyses followed an intention-to-treat approach, with paired t-tests for within-group comparisons and ANCOVA for between-group differences. Sensitivity analyses used Last Observation Carried Forward (LOCF) and Inverse Probability of Attrition Weighting (IPAW) to address loss-to-follow-up. ResultsOf 136 screened, 52 participants (19-59 years) were enrolled (MyGeneMyDiet(R), n = 29; standard recommendation, n = 23), with 27 completing the study (MyGeneMyDiet(R), n = 15; standard recommendation, n = 12). Weight changes over 12 months were minimal, with no substantial differences between groups. At month 6, baseline-adjusted analyses showed no meaningful differences in weight (-0.36 kg [95% CI: -1.77, 1.04]), BMI (0.11 kg/m{superscript 2} [-0.51, 0.73]), waist circumference (-0.27 cm [-2.23, 1.69]), or body fat percentage (0.92% [-0.86, 1.05]). These trends persisted on month 12. While both groups reduced dietary intake, the MyGeneMyDiet(R) group showed greater decreases in total calories (-461 kcal, P = 0.001), protein (-12 g, P = 0.007), carbohydrates (-46 g, P = 0.015), and fat (-22 g, P = 0.014), though between-group differences remained modest. ConclusionsGene-based and standard weight management advice led to comparable weight and metabolic outcomes over 12 months. While gene-based recommendations influenced dietary intake, these changes did not improve anthropometric or biochemical outcomes. This trial was registered at clinicaltrials.gov as NCT05098899.

The modern Western diet (MWD) provides high linoleic acid (LA) exposure, typically contributing 6-9% of total caloric intake. These high LA levels have fueled a longstanding debate regarding whether this dietary pattern confers benefit or risk. Importantly, LA intake is disproportionately elevated among lower socioeconomic populations due to greater reliance on industrial seed oils and ultra-processed foods. Despite decades of research, controlled dietary intervention studies directly evaluating the biological consequences of varying LA exposure remain limited. The current randomized, double-blind intervention compared the effects of a 12-week Low LA diet (2.5% energy) versus a High LA diet (10.0% energy) in healthy adults. Primary outcomes included plasma highly unsaturated fatty acid (HUFA) concentrations and ex vivo zymosan-stimulated whole-blood oxylipin generation. Fifty- two participants completed the intervention. High LA exposure resulted in a marked reduction in plasma n-3 eicosapentaenoic acid (EPA) concentrations compared with the LowLA arm. In contrast, levels of arachidonic acid (ARA), dihomo-gamma-linolenic acid (DGLA) and docosahexaenoic acid (DHA) did not differ by dietary LA exposure. Analysis of oxylipin species revealed that levels of EPA-derived relative to ARA-derived mediators were significantly reduced in the High LA arm. These findings reveal that higher dietary LA selectively suppresses EPA pools and EPA-derived oxylipins without altering ARA, shifting the lipid mediator balance toward a more n-6-dominant profile.

BACKGROUNDCrossover studies can induce order effects, especially when they lack a wash-out period. OBJECTIVETo explore diet order effects on energy balance and food intake between randomized diet order groups in two inpatient crossover studies originally designed to compare within-subject differences in ad libitum energy intake between either minimally processed low carbohydrate (LC) versus low fat (LF) diets or macronutrient-matched diets composed of mostly minimally processed food (MPF) or ultra-processed food (UPF). METHODSDiet order group comparisons of changes in body weight, body composition, and differences in energy expenditure, and food intake were assessed over four weeks in 20 adults randomized to either the LC followed immediately by the LF diet (LC[-&gt;]LF) or the opposite order (LF[-&gt;]LC) as well as 20 adults randomized to either the MPF followed by UPF (MPF[-&gt;]UPF) diets or the opposite order (UPF[-&gt;]MPF). RESULTSSubjects randomized to LC[-&gt;]LF lost 2.9 {+/-} 1.1 kg more body weight (p < 0.001) and 1.5 {+/-} 0.6 kg more body fat (p = 0.03) than the LF[-&gt;]LC group likely because the LC[-&gt;]LF group consumed 922 {+/-} 304 kcal/d less than the LFaLC group (p = 0.0024). Reduced energy intake in LC[-&gt;]LF vs LFaLC was driven by the last two weeks (-1610 {+/-} 306 kcal/d; p<0.00001) perhaps due to carryover effects of gut adaptations over the first two weeks arising from large differences in the mass of food (1295 {+/-} 209 g/d; p<0.00001) and fiber intake (58 {+/-} 5 g/d; p<0.00001). There were no diet order effects on ad libitum energy intake, body weight, or body composition change between UPF[-&gt;]MPF versus MPF[-&gt;]UPF groups. CONCLUSIONSDiet order influences daily ad libitum energy intake, body weight change, and fat change within the context of a 4-week crossover inpatient diet study varying in macronutrients, but not varying in extent and purpose of processing. Funding sourcesIntramural Research Program of the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health Clinical Trial RegistrationNCT03407053 and NCT03878108

1.Traditional nutrition science often proceeds under the assumption of a universal metabolic return to healthy eating, yet social environments may fundamentally modify these biological associations. This investigation utilized survey-weighted data from the National Health and Nutrition Examination Survey (NHANES 2017-2023) representing a weighted population of 286 million adults aged 20 years and older to test for association heterogeneity in the dietglycemia relationship. Dietary exposure was operationalized as energy-adjusted nutrient density scores derived via the residual method to measure the healthfulness of intake independent of total caloric volume. The primary outcome was HPLC-measured glycated hemoglobin (HbA1c) modeled as a continuous variable. Multivariable interaction models evaluated the Income-to-Poverty Ratio (PIR) as a formal effect modifier, adjusting for age, sex, race/ethnicity, body mass index, and smoking status. Analysis demonstrated that while quality-weighted nutrient intake levels remained statistically uniform across income tiers (p=0.207), multivariable interaction models identified significant modification of the diet-HbA1c association by socioeconomic position (p=0.028 for interaction). In the low-income reference group, higher quality nutrient intake was associated with a significant protective decline in HbA1c ({beta}=-6.11x10-5 percentage points per kilocalorie, p=0.017). Conversely, this protective association was attenuated to non-significance for the middle-income stratum ({beta}=3.31x10-6, p=0.849). Sensitivity analysis restricted to participants without clinical diabetes showed the interaction was non-significant (p=0.859), identifying an observed boundary condition where differential associations are most evident in pathological states. These findings suggest association heterogeneity where identical dietary behaviors relate to divergent glycemic patterning across socioeconomic groups. Socioeconomic position appears to function as an effect modifier of the diet-HbA1c relationship rather than a mere confounder. Such patterns suggest that the metabolic correlates of healthy eating are socially patterned, potentially due to structural factors that constrain the associations expected from improved nutrition.

BackgroundSeveral genetic variants have been identified to modify the effects of fish oil supplementation (FOS) on increasing circulating omega-3 fatty acids, but it remains unexplored whether polygenic predisposition to low circulating omega-3 fatty acids modifies these effects. ObjectiveTo test if polygenic scores (PGS) for circulating omega-3 fatty acids modify the associations of FOS with corresponding circulating concentrations. MethodsWe developed PGS models for absolute circulating concentrations of total omega-3 fatty acids (Omega-3), docosahexaenoic acid (DHA), and their relative percentages in total fatty acids (Omega-3% and DHA%), using a multi-ethnic genome-wide association study (N=136,016). PGS models were validated in 437,803 UK Biobank participants of European (EUR), Central/South Asian (CSA), African, and East Asian genetic ancestries. Linear models tested PGS-by-FOS interactions on corresponding observed circulating concentrations. Discovery analysis was performed separately in 237,380 EUR participants and each non-EUR group. Replication analyses were performed using oily fish intake and in another 178,935 EUR participants. ResultsIn EUR participants, PGS explained 5.3-11.1% of the phenotypic variance, and significant PGS-by-FOS interactions were detected across all four circulating omega-3 traits. Among participants in the bottom 5% of the PGS distribution, FOS was significantly associated with a 0.40 SD (95% CI: 0.39-0.44) increase in Omega-3. This association effect was 11.1% larger than the population average ({beta} = 0.36; 95% CI: 0.35-0.37; PInt = 0.016) and 42.8% larger than that in participants in the top 5% of the PGS distribution ({beta} = 0.28 SD; 95% CI: 0.25-0.32; PInt = 4.03X10-10). These interaction patterns were consistently observed in CSA ancestry and confirmed in replication and sensitivity analyses. ConclusionsPGS modify the associations of FOS with circulating omega-3 fatty acids in EUR and CSA populations, with larger FOS effects in participants with lower PGS. These findings support the development of genome-informed precision nutrition.

Colonic microorganisms have been linked to human health and disease, specifically metabolic disease states such as obesity, but causal relationships remain to be established. Previous work demonstrated that interactions between the hosts diet and intestinal microbiome were associated with human energy balance by affecting the humans energy absorption, quantified by metabolizable energy. We developed the Digestion, Absorption and Microbial Metabolism (DAMM) model, which explicitly accounts for the energy contributions of the colonic microbial community by: 1) breaking down the diet composition into the gross energy of the individual macronutrients, 2) calculating direct absorption in the upper gastrointestinal tract, 3) using microbial stoichiometry to estimate the consumption of the remaining unabsorbed nutrients by microbes in the large intestine, 4) quantifying predicted production of microbial products (short-chain fatty acids (SCFA) and methane) in the colon, and 5) estimating absorption from the colonic tract to the host. When used to predict the results from a clinical study that compared two distinctly different diets, the DAMM model captured the directionality and magnitude of change in measured metabolizable chemical oxygen demand (which can be converted to metabolizable energy), improved on the accuracy of predictions compared to the Atwater factors by reducing systematic bias on one of the diets, and estimated substrate availability within the colon and rate of production of microbially derived short-chain fatty acids. Measured methane concentrations, combined with findings from the DAMM model, support the hypothesis that methanogens accumulated in mucosal biofilms in participants harboring methanogens. Model outputs also support that colonic transit time directly influenced SCFA absorption rates. The DAMM model now can be linked to existing human models that predict changes in body energy stores to extend our understanding of how microbial metabolic processes affect macronutrient absorption and metabolizable energy.

It is unclear whether the effectiveness of weight loss interventions differs based on genetic predisposition to higher body mass index (BMI). Genome-wide polygenic scores (PS) for BMI are the strongest genetic predictors of elevated body weight, but no prospective trials have evaluated weight loss responses based on BMI PS. To assess whether adults with high or low genetic predisposition to higher BMI experience differential weight loss during a 6-month dietary intervention, we designed the GENEROOS study, a single-site, randomised controlled trial conducted in Finland from October 2023 to November 2024. Participants (N=223), aged 30-65 years, with a BMI of 23-36 kg/m{superscript 2} and no diabetes, were recruited from 38,621 genotyped individuals in the Finnish Clinical Biobank Tampere. They were selected from the top or bottom 5th percentile of the BMI PS distribution and randomized to either a six-month dietary coaching program aimed at a 500 kcal/day energy deficit or to a control group receiving no dietary intervention. The main outcome was change in body weight (%) from baseline to 6 months and the interaction between BMI PS and intervention status. At baseline, those in the top 5% of BMI PS weighed on average 8.4 kg (95% CI, 5.1 to 11.7 kg) more than those in the bottom 5%. In the intervention group, mean weight change at 2, 4, and 6 months was -3.89%, -5.32%, and -4.70%; in the control group it was -1.10%, -0.85%, and 0.14%, respectively. No significant interaction was found between BMI PS and intervention on weight change ({beta} = 0.06 [95% CI, -1.33 to 1.44]; P = .94). In this randomised trial, genetic predisposition as measured by BMI PS did not modify response to dietary intervention, indicating that leveraging polygenic scores may not enhance the effectiveness of personalized weight loss strategies. Trial RegistrationClinicalTrials.gov Identifier: NCT06092372

BackgroundCholine is an essential nutrient, and insufficient intake negatively affects organs such as the liver, brain, and muscles. In the United States, average choline intake remains below the Adequate Intake (AI) (550 mg/day men, 425 mg/day women). Although conventional dietary assessment tools can identify people who are eating diets low in choline, no metabolite biomarkers have been proven to reliably assess choline intake. ObjectiveWe tested whether plasma concentrations of choline and its metabolites could determine dietary choline intake. We also assessed whether liver elastography (Fibroscan) could detect diet-induced changes in liver fat. MethodsIn a double-blind, randomized, crossover feeding study, participants adhered to 3 distinct dietary patterns for 2-wk intervals, delivering approximately 100%, 50%, and 25% of the choline AI. On Day 12 of each dietary arm, in addition to the food supplied, subjects consumed a single bolus of 2.2 mmol trimethyl-d9-choline. Plasma concentrations of choline, betaine and phosphatidylcholine (PtdCho) were measured using mass spectrometry. Targeted assays quantified choline, betaine, phosphatidylcholine and total homocysteine concentrations. Liver fat content was evaluated non-invasively using Fibroscan. ResultsPlasma concentrations of d9-choline, betaine, and their isotopic enrichment ratio (IER) varied with dietary intake (q<0.0001), and PtdCho IER also differed significantly (q=0.001). In targeted analysis, choline and betaine concentrations were highly responsive to dietary choline intake, while PtdCho and tHcy were not. Receiver Operator Characteristic (ROC) analysis showed strong accuracy using plasma choline (AUC=0.81) and betaine (AUC=0.80), with improved accuracy when combined (AUC= 0.83). Fibroscan identified a subset of participants with increased liver fat in response to the 25% AI vs. 100% AI choline diet, though patterns varied among individuals. ConclusionPlasma choline and betaine concentrations are robust biomarkers of dietary choline intake under controlled feeding. These findings support targeted metabolite profiling to improve choline intake assessment and reveal induvial variability in liver response to low choline intake.

Time-restricted eating (TRE) is a promising strategy to improve metabolic outcomes. However, it remains unclear whether TRE has cardiometabolic benefits in an isocaloric setting and whether its effects depend on the eating timing. We conducted a randomized cross-over trial to directly compare the effects of a two-week early TRE (eTRE: eating between 8:00 and 16:00 hr) and a two-week late TRE (lTRE: eating between 13:00 and 21:00 hr) on insulin sensitivity, cardiometabolic risk factors, and the internal circadian phase. During the restricted 8-hour eating period, participants were asked to consume their habitual food quality and quantity. In 31 women with overweight or obesity, insulin sensitivity did not differ between (-0.07; 95% CI, -0.77 to 0.62, P = 0.60) and within (eTRE: 0.31; 95% CI, -0.14 to 0.76, P = 0.11; lTRE: 0.19; 95% CI, -0.22 to 0.60, P = 0.25) interventions. 24-hour glucose, lipid, inflammatory, and oxidative stress markers showed no clinically meaningful between- and within-intervention differences. Participants demonstrated high timely adherence (eTRE: 96.5%, lTRE: 97.7%), unchanged dietary composition and physical activity, minor daily calorie deficit (eTRE: -167 kcal/day) and weight loss (eTRE: -1.08 kg, lTRE: -0.44 kg). lTRE delayed the circadian phase in blood monocytes (24 min; 95% CI, -5 to 54 min, P = 0.10) and sleep midpoint (15 min; 95% CI, 7 to 22 min, P = 0.001) compared to eTRE. Overall, in an intended isocaloric setting, neither eTRE nor lTRE improve insulin sensitivity or other cardiometabolic traits despite a shift of internal circadian clocks. One sentence summaryNearly isocaloric time-restricted eating shifts circadian clocks but does not improve cardiometabolic health in women with overweight or obesity

BackgroundThe Dietary Guidelines for Americans (DGA) recommends consuming >1.75g/wk of long-chain omega-3 fatty acids to reduce the risk of cardiovascular disease (CVD) through triglyceride reduction, however individual responses to treatment vary. ObjectiveWe sought to determine if a DGA-conforming diet (DGAD) can increase the omega-3 index (OM3I), a diet-sensitive biomarker of omega-3 fatty acid status, into a health promoting range and reduce fasting triglycerides in 8 weeks. We further explored determinants of the basal OM3I and its response to treatment. DesignThis is a secondary analysis of a randomized, double-blind 8wk dietary intervention of overweight/obese women fed an 8d rotating DGAD (n =22) or typical American diet (TAD; n =20) registered at www.clinicaltrials.gov as NCT02298725. The DGAD and TAD provided individuals with 16 {+/-} 2 g/wk and 1.2 {+/-} 0.12 g/wk of eisocapentaenoic acid (EPA) + docosahexaenoic acid (DHA), respectively. Habitual diet and body composition were determined at baseline. OM3I, fasting triglycerides, glucose and insulin were measured at 0, 2 and 8wk. ResultsBaseline OM3I (5.8 {+/-} 1.3; n =42) was positively correlated to the dietary (EPA+DHA):dietary fat ratio (p =0.006), negatively correlated to the android fat mass (p =0.0007) and was not different between diet groups. At 8wk, while the TAD-group average OM3I was unchanged (5.8 {+/-} 0.76), the DGAD-group OM3I increased (7.33 {+/-} 1.36; p <0.001). In the DGAD-group 9 of 22 (i.e. 41%) participants achieving an OM3I >8%. Subgroup analyses of the DGAD-group revealed that body fat content and distribution influenced the baseline-dependent response to treatment. Fasting triglyceride and OM3I changes did not correlate. ConclusionsAn 8wk TAD stabilized the OM3I in a healthy range, while a DGAD increased the OM3I into a health-promoting range, but did not reduce fasting triglycerides. Fat distribution and basal omega-3 status are primary factors influencing omega-3 efficacy in overweight/obese women.

Fish oil supplements (FOS) are known to alter circulating levels of polyunsaturated fatty acids (PUFAs) among individuals but in a heterogeneous manner. These varied responses may result from unidentified gene-FOS interactions. To identify genetic factors that interact with FOS to alter the circulating levels of PUFAs, we performed a multi-level genome-wide interaction study (GWIS) of FOS on 14 plasma measurements in 200,060 unrelated European-ancestry individuals from the UK Biobank. From our single-variant tests, we identified genome-wide significant interacting SNPs (P < 5 x 10-8) in the FADS1-FADS2 gene cluster for total omega-3, omega-3%, docosapentaenoic acid (DHA), DHA% and the omega-6 to omega-3 ratio. Among the interaction signals for omega-3%, the lead SNP, rs35473591 (C>CT, CT allele frequency = 0.34), had a lower association effect size in the FOS-taking group ({beta} = 0.35 for allele C) than that in the group without FOS ({beta} = 0.42). Likewise, the effect sizes of associations between FOS and omega-3% varied across the three genotype groups ({beta} = 0.45, 0.50, and 0.59, respectively, in C/C, C/CT, and CT/CT). Our gene-level aggregate and transcriptome-wide interaction analyses identified significant signals at two loci, around FADS1-FADS2 and GRP12. The contribution of genome-wide gene-FOS interactions to phenotypic variance was statistically significant in omega-3-related traits. This systemic gene-FOS GWIS contributes to our understanding of the genetic architecture of circulating PUFAs underlying FOS response and informs personalized dietary recommendations.

Background: Diet is a modifiable risk factor for cardiometabolic disease, yet establishing causality remains challenging. Mendelian randomisation (MR) leverages genetic variants as instrumental variables (IVs) to enable causal inference. Method: Using two-sample MR, we assessed the causal effects of four principal component-derived dietary patterns (DPs) - Unhealthy, Healthy, Meat-based, Pescatarian - on twelve cardiometabolic outcomes: body mass index, coronary artery disease, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, total cholesterol, triglycerides, systolic blood pressure, diastolic blood pressure, type 2 diabetes, fasting glucose and insulin, and glycated haemoglobin. Two sets of IVs were employed: conventional genome-wide significant variants associated with each DP, rigorously filtered for pleiotropy and directionality; and biologically informed variants in chemosensory receptor genes, given the role of taste and smell perception in shaping food choices. Results: Using conventional IVs, the Pescatarian DP reduced fasting insulin ({beta}IVW = -0.10 pmolL-1 per SD increase in Pescatarian DP score, 95% Confidence interval [CI] [-0.15, -0.04]; P = 1.19x10-3), which survived multiple sensitivity analyses. Associations between the Unhealthy DP and elevated blood pressure and glycated haemoglobin were likely undermined by heterogeneity and pleiotropy, with insufficient IVs for robust sensitivity testing. Chemosensory receptors yielded null findings, reflecting insufficient power. Conclusion: Rigorously filtered conventional IVs supported the causal nature of well-established diet-disease relationships, demonstrating MR's utility in strengthening causal inference in nutritional epidemiology. Chemosensory IVs demonstrated limited utility for DPs, likely reflecting the heterogeneous and complex sensory profiles of overall diets. Future efforts should consider using guideline-based dietary scores to facilitate translation of findings.

BackgroundMendelian randomization (MR) uses genetic instruments (GI) to infer causality between exposures, like dietary intake, and health outcomes. Almost all MR of dietary intake use the full set of genome-wide significant (GWS) variants in the GI, and therefore, causal estimates are likely biased by variants that act indirectly on diet. ObjectiveFirst, we performed an assessment of the diet MR literature to evaluate the applications and approaches common in the field. Second, using conventional two-sample MR techniques with GWS variants, we evaluated whether MR could detect expected associations between six diet-health relationships supported by existing nutrition science literature. Third, we developed and tested methods for refining the GI using filtering and mediation-based approaches. MethodsStudies that performed MR of foods or beverages on any health outcome were identified in PubMed. We recorded how the GI was created, what dietary intake traits were studied, how the exclusion restriction assumption was evaluated, and what sensitivity tests were performed. We tested if conventional MR methods could detect established diet-health relationships by selecting a biomarker and disease outcome for each dietary trait (six positive controls total). This included oily fish intake on triglycerides (TG) and cardiovascular disease (CVD), alcohol intake on alanine aminotransferase (ALT) and liver cirrhosis, and white vs whole grain or brown bread on LDL cholesterol (LDL-C) and CVD. To refine the GI to better estimate the direct effect of diet by removing or accounting for the indirect effects of confounders, we tested two phenome-wide association study (PheWAS) based GI filtering approaches and a mediation approach via multivariable MR (MVMR). Causal inferences were estimated by the inverse variance weighted (IVW) and weighted median (WM) estimators and by MR-CAUSE. ResultsThere is a strong and rapidly expanding interest in applying MR to dietary intake exposures (178 studies identified with 76 published in 2024). Existing studies showed a wide range of methodological rigor, especially with respect to GI specificity, which raised concerns whether MR using GWS GIs can adequately evaluate diet-health relationships. In empirical testing, conventional two-sample MR methods on GWS GIs only identified the relationships between oily fish on TG and white vs whole grain or brown bread on LDL-C using the WM estimator, whereas no relationships were identified by the IVW estimator. Filtering the GI improved the ability to detect the expectation for diet-biomarker pairs (IVW, oily fish on TG: {beta}=-0.12 [95% CI -0.18 to -0.054]; IVW, white vs whole grain or brown bread on LDL-C: {beta} = 0.11 [95% CI 0.058 to 0.16]) but not diet-disease pairs. MR-CAUSE identified the only diet-disease association - white vs. whole grain or brown bread on CVD ({gamma}=0.17 [95% credible interval, 0.09 to 0.25]). Furthermore, MR-CAUSE found that many diet-health relationships were impacted by confounding. We evaluated which traits contributed to confounding via the PheWAS results and found that body composition traits were the most prevalent confounders. The PheWAS output was used to prioritize traits for MVMR and rescued the expected direct effect of alcohol on ALT ({beta}= 0.028 [95% CI 0.017 to 0.039]). ConclusionMR studies of diets causal role in health have flooded the literature; however, our inconsistent associations with positive and negative controls using multiple tests and filtering methods signal a need for caution. More thoughtful curation of the GI is critical to reduce confounding due to health and environmental factors when evaluating the causal effect of diet on health.

BackgroundCollege-attending young adults frequently experience declines in diet quality, physical activity, and psychological well-being during the transition to independent living, contributing to weight gain during the first year of college. Although multicomponent lifestyle interventions have been developed to address these behaviors, the responsiveness to such programs could differ across demographic factors associated with health behaviors, such as sex, race, and ethnicity. Hence, this secondary analysis of large-scale college health trials evaluated whether the effectiveness of such interventions differed by these demographic factors. MethodsData were combined from two multi-site randomized controlled trials: Young Adults Eating and Active for Health (YEAH) trial and the Get FRUVED trial. Both interventions used theory-based approaches to promote healthy weight management through improvements in diet quality, physical activity, and stress management. Baseline-adjusted linear regression models evaluated the effects of group (intervention, control) and its interactions with sex, race (White, Black, Other), or Hispanic ethnicity. Models were adjusted for baseline outcome values, baseline BMI, study (YEAH vs. FRUVED), and state of data collection. ResultsIntervention participants reported higher fruit and vegetable intake, lower processed meat intake, and longer sleep duration compared with controls. However, there was significant heterogeneity in these dietary outcomes by ethnicity, race, and sex. Non-Hispanic participants in the intervention group had higher fruit and vegetable intake compared to controls (p < 0.05). And, within the intervention group, Hispanic females had lower bacon/sausage intake than Hispanic males and non-Hispanic females (p < 0.05). With respect to race, Black participants reported higher total processed meat intake than White and Other race participants in the intervention group (p <0.05). These demographic factors did not moderate the interventions impact on physical activity, sleep duration, and perceived stress. Overall, the intervention appeared to be the least effective for Hispanic males who exhibited higher body weight and waist circumference compared with Hispanic females and non-Hispanic males (p < 0.05). ConclusionsMulticomponent lifestyle interventions can improve selected dietary outcomes among college students, but effectiveness may differ across demographic subgroups. Culturally and sex-tailored strategies that consider the intersecting influences of sex, race, and ethnicity may enhance intervention effectiveness during the transition to college.

BackgroundChronic malnutrition in early childhood is a multifactorial condition associated with long-term impairments, yet the physiological and gut microbial pathways underlying differential growth trajectories remain poorly understood. ObjectiveWe aimed to characterize phenotypic growth trajectories and identify the associated gut microbial and body composition signatures in infants during the first year of life. MethodsWe analyzed longitudinal data from birth to 12 months in a South African cohort (Soweto, n=45). Individual linear growth trajectories were modeled using the Jenss-Bayley equation, and children were clustered based on model parameters to identify phenotypic subgroups. Body composition (fat-free mass and fat mass) was measured via deuterium dilution at 6 and 12 months, and gut microbiome development was assessed using 16S rRNA gene amplicons at 4, 6, and 12 months. ResultsWe identified distinct phenotypic subgroups including healthy growth, catch-up growth, and growth faltering, that were obscured at the cohort level. These trajectories diverged most dynamically within the first 6 months of life. Integrated analysis revealed that in the growth faltering cluster, height-for-age and fat-free mass z-scores stabilized between 6 and 12 months, whereas fat mass z-scores (FMZ) declined. This trade-off is consistent with a catabolic state where energy reserves are prioritized for lean tissue and bone growth. Furthermore, at 6 months, the growth faltering cluster was enriched with opportunistic pathobionts (e.g., Paraclostridium). In contrast, the catch-up cluster exhibited a transient enrichment of facultative anaerobes (e.g., Enterobacter), supporting a hypothesis that these oxygen-tolerant taxa may help bridge a transitional microbial state in partially oxygenated or inflamed environments to enable physiological recovery. ConclusionsEarly childhood chronic malnutrition phenotypes in South African infants can be defined by distinct microbial and body composition signatures that diverge within six months of life. Integrated interventions should target both host anabolic state and microbiome transitions to support recovery.

The Goldberg method has been suggested for identifying energy intake (EI) under-reporting in nutritional epidemiology. Its implementation, however, is limited by challenges associated with estimating physical activity levels (PAL). We quantified the accuracy of the Sedentary Time and Activity Reporting Questionnaire (STAR-Q) derived PAL (PALSTAR-Q) combined with the Goldberg method (Goldberg-PALSTARQ) to identify EI misreporting as compared with doubly labeled water (DLW) derived total energy expenditure (TEEDLW). Between 2009 and 2011, 99 men and women completed a two-week DLW protocol, a food frequency questionnaire, and the STAR-Q. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of the Goldberg-PALSTAR-Q were determined. Fifty-eight percent of men and women were classified as under-reporters by Goldberg-PALSTAR-Q compared with 60% of men and 56% of women by TEEDLW. Among men, sensitivity, specificity, PPV, NPV and accuracy and 95% confidence intervals were 88% (68%-97%), 87% (61%-98%), 91% (72%-99%), 81% (56%-94%), and 87% (72%-95%), respectively; and among women 79% (62%-90%), 69% (50%-84%), 77% (60%-88%), 72% (52%-86%), and 75% (62%-84%), respectively. Validated individual level PALs used with the Goldberg method can be informative in sensitivity analyses to gain insight into EI misreporting in nutritional epidemiology studies lacking in objective EI measures.

BackgroundProbiotics may enhance host iron bioavailability, offering a strategy to address iron deficiency. Fecal iron may be a useful non-invasive biomarker of such effects in infants. ObjectiveTo examine the use of fecal iron quantification in a randomized placebo-controlled trial (RCT) of neonatal administration of Lactiplantibacillus plantarum ATCC 202195 (LP202195), with or without fructooligosaccharide (FOS), in Dhaka, Bangladesh. MethodsFecal iron quantification using atomic absorption spectrometry (AAS) was optimized using standards and reference materials, and pilot-tested using pooled stool aliquots (n=32) from an observational cohort of young infants in Bangladesh (aged 0-64 days). The optimized AAS assay was then applied to individual stool samples collected at 14 days of age (n=307) in a RCT in which newborns aged 0-4 days were randomly allocated to one of five groups: placebo, 1-or 7-day regimens of LP202195, with or without FOS. Serum ferritin was measured at 2 months postnatal age (n=251). Effects of the 1-and 7-day LP202195 regimens were estimated using linear regression and expressed as mean percent differences relative to placebo, with 95% confidence intervals (95%CI). ResultsThe optimized AAS fecal iron assay had acceptable accuracy (91-99%), precision (within-and between-run coefficients of variation <10%), and recovery (93-112%), with a reportable range of 0.2 to 80 mg Fe per 100 g dry stool. In pooled samples from the observational cohort, fecal iron varied with age and feeding status. In the RCT, fecal iron concentrations did not significantly differ following1-day (% difference=9.8%, 95%CI:-19%, 49%; P=0.54) or 7-days (% difference=-6.1%, 95%CI:-31%, 28%; P=0.69) of LP202195 administration, versus placebo (geometric mean concentration=4.3mg Fe/100g dry stool (95%CI:3.3, 5.6); n=53). Inferences were unchanged when groups were disaggregated by FOS co-administration (P>0.05 for all). Similarly, there were no effects of LP202195 on serum ferritin at 2 months of age (P>0.05 for all). ConclusionsFecal iron quantification by AAS was valid and feasibly implemented in a trial of neonatal administration of Lactiplantibacillus plantarum ATCC 202195. However, the assay is resource-intensive and may not be more informative than conventional measures of iron status when studying the effects of probiotics/synbiotics on iron bioavailability. Clinical Trial RegistryClinicalTrials.gov identifier: NCT05180201

BackgroundDiet is central to cardiovascular disease (CVD) prevention, yet free-living studies rarely capture what people eat at home or how closely they follow an assigned diet due to limitations in self-reporting. Short-term inpatient feeding studies, with all meals provided and supervised intake, allow direct assessment of the physiological effects of dietary patterns. Objectivesi) To compare the short-term effects of a UK-National Institute for Health and Care Excellence (NICE) aligned diet versus a Western-style diet on CVD risk factors, metabolic phenotypes and microbiome; ii) To evaluate whether urinary metabolic phenotyping can objectively classify dietary adherence in adults with increased CVD risk. MethodsIn a controlled inpatient randomized crossover trial, 18 adults at elevated CVD risk completed two 72 h isocaloric diets: NICE-compliant and Western-style. Repeated-measures MCCV-PLS-DA assessed NMR fasting serum and 24 h urine metabolomic phenotypes. Univariate analyses examined CVD markers, urinary metabolites, serum SCFAs, and gut microbial richness and -diversity. ResultsDiet modulated CVD risk markers, with the NICE compliant diet lowering systolic blood pressure and atherogenic lipid parameters, whereas the Western-style diet increased these measures (all q < 0.05). The Western-style diet reduced microbial richness and tended towards lower -diversity. Urinary metabolic phenotyping identified 27 discriminatory metabolites between the diets reflecting food intake. Most diet-linked metabolites diverged from baseline within 24 h; microbiome derived metabolites demonstrated early and sustained divergence across 72 h. The urinary MCCV-PLS-DA model extended from a previously published framework in healthy adults, robustly classified dietary adherence (Q2Y=0.96), and correctly predicted allocated dietary intervention at earlier timepoints (24-48 h). ConclusionsUrinary metabolic phenotyping offers a sensitive and non-invasive tool for objectively assessing dietary intake. Short-term adherence to contrasting dietary patterns produced rapid, diet-specific metabolic and microbial effect in individuals at elevated CVD risk and differentially impacted cardiovascular risk profiles. This trial was registered at the ISRCTN registry (https://www.isrctn.com/ISRCTN44705179).