Glycemia and Gluconeogenesis With Metformin and Liraglutide: A Randomized Trial in Youth-onset Type 2 Diabetes

OBJECTIVE

Elevated rates of gluconeogenesis are an early pathogenic feature of youth-onset type 2 diabetes (Y-T2D), but targeted first-line therapies are suboptimal, especially in African American (AA) youth. We evaluated glucose-lowering mechanisms of metformin and liraglutide by measuring rates of gluconeogenesis and β-cell function after therapy in AA Y-T2D.

METHODS

In this parallel randomized clinical trial, 22 youth with Y-T2D-age 15.3 ± 2.1 years (mean ± SD), 68% female, body mass index (BMI) 40.1 ± 7.9 kg/m2, duration of diagnosis 1.8 ± 1.3 years-were randomized to metformin alone (Met) or metformin + liraglutide (Lira) (Met + Lira) and evaluated before and after 12 weeks. Stable isotope tracers were used to measure gluconeogenesis [2H2O] and glucose production [6,6-2H2]glucose after an overnight fast and during a continuous meal. β-cell function (sigma) and whole-body insulin sensitivity (mSI) were assessed during a frequently sampled 2-hour oral glucose tolerance test.

RESULTS

At baseline, gluconeogenesis, glucose production, and fasting and 2-hour glucose were comparable in both groups, though Met + Lira had higher hemoglobin A1C. Met + Lira had a greater decrease from baseline in fasting glucose (-2.0 ± 1.3 vs -0.6 ± 0.9 mmol/L, P = .008) and a greater increase in sigma (0.72 ± 0.68 vs -0.05 ± 0.71, P = .03). The change in fractional gluconeogenesis was similar between groups (Met + Lira: -0.36 ± 9.4 vs Met: 0.04 ± 12.3%, P = .9), and there were no changes in prandial gluconeogenesis or mSI. Increased glucose clearance in both groups was related to sigma (r = 0.63, P = .003) but not gluconeogenesis or mSI.

CONCLUSION

Among Y-T2D, metformin with or without liraglutide improved glycemia but did not suppress high rates of gluconeogenesis. Novel therapies that will enhance β-cell function and target the elevated rates of gluconeogenesis in Y-T2D are needed.

Striatal dopamine tone is positively associated with body mass index in humans as determined by PET using dual dopamine type-2 receptor antagonist tracers

The relationship between adiposity and dopamine type-2 receptor binding potential (D2BP) in the human brain has been repeatedly studied for >20 years with highly discrepant results, likely due to variable methodologies and differing study populations. We conducted a controlled inpatient feeding study to measure D2BP in the striatum using positron emission tomography with both [18F]fallypride and [11C]raclopride in pseudo-random order in 54 young adults with a wide range of body mass index (BMI 20-44 kg/m2). Within-subject D2BP measurements using the two tracers were moderately correlated (r=0.47, p<0.001). D2BP was negatively correlated with BMI as measured by [11C]raclopride (r= -0.51; p<0.0001) but not [18F]fallypride (r=-0.01; p=0.92) and these correlation coefficients were significantly different from each other (p<0.001). Given that [18F]fallypride has greater binding affinity to dopamine type-2 receptors than [11C]raclopride, which is more easily displaced by endogenous dopamine, our results suggest that adiposity is positively associated with increased striatal dopamine tone.

Metabolomic Profiling of an Ultraprocessed Dietary Pattern in a Domiciled Randomized Controlled Crossover Feeding Trial

BACKGROUND

Objective markers of ultraprocessed foods (UPF) may improve the assessment of UPF intake and provide insight into how UPF influences health.

OBJECTIVES

To identify metabolites that differed between dietary patterns (DPs) high in or void of UPF according to Nova classification.

METHODS

In a randomized, crossover, controlled-feeding trial (clinicaltrials.govNCT03407053), 20 domiciled healthy participants (mean ± standard deviation: age 31 ± 7 y, body mass index [kg/m2] 22 ± 11.6) consumed ad libitum a UPF-DP (80% UPF) and an unprocessed DP (UN-DP; 0% UPF) for 2 wk each. Metabolites were measured using liquid chromatography with tandem mass spectrometry in ethylenediaminetetraacetic acid plasma, collected at week 2 and 24-h, and spot urine, collected at weeks 1 and 2, of each DP. Linear mixed models, adjusted for energy intake, were used to identify metabolites that differed between DPs.

RESULTS

After multiple comparisons correction, 257 out of 993 plasma and 606 out of 1279 24-h urine metabolites differed between UPF-DP and UN-DP. Overall, 21 known and 9 unknown metabolites differed between DPs across all time points and biospecimen types. Six metabolites were higher (4-hydroxy-L-glutamic acid, N-acetylaminooctanoic acid, 2-methoxyhydroquinone sulfate, 4-ethylphenylsulfate, 4-vinylphenol sulfate, and acesulfame) and 14 were lower following the UPF-DP; pimelic acid, was lower in plasma but higher in urine following the UPF-DP.

CONCLUSIONS

Consuming a DP high in, compared with 1 void of, UPF has a measurable impact on the short-term human metabolome. Observed differential metabolites could serve as candidate biomarkers of UPF intake or metabolic response in larger samples with varying UPF-DPs. This trial was registered at clinicaltrials.gov as NCT03407053 and NCT03878108.

The effects of prebiotics on gastrointestinal side effects of metformin in youth: A pilot randomized control trial in youth-onset type 2 diabetes

Disclosure summary

Dr. Yadav is Chief Scientific Officer and Co-Founder of Postbiotics Inc and has no conflict of interest with this work. All other authors have no conflicts of interest to disclose.

Background

Metformin is the only approved first-line oral glucose lowering agent for youth with type 2 diabetes mellitus (Y-T2DM) but often causes gastrointestinal (GI) side effects, which may contribute to reduced treatment adherence and efficacy. Prebiotic intake may reduce metformin's side effects by shifting microbiota composition and activity.

Objective

The aims of this study were to determine the feasibility and tolerability of a prebiotic supplement to improve metformin-induced GI symptoms and explore the changes in glycemia and shifts in the microbiota diversity.

Methods

In a two-phase pilot clinical trial, we compared, stool frequency and stool form every 1-2 days, and composite lower GI symptoms (weekly) at initiation of daily metformin combined with either a daily prebiotic or a placebo shake in a 1-week randomized double-blind crossover design (Phase 1), followed by a 1-month open-labeled extension (Phase 2). Plasma glycemic markers and stool samples were collected before and after each phase.

Results

Six Y-T2DM (17.2 ± 1.7y (mean ± SD), 67% male, BMI (42 ± 9 kg/m2), HbA1c (6.4 ± 0.6%)) completed the intervention. Stool frequency, stool composition, and GI symptom scores did not differ by group or study phase. There were no serious or severe adverse events reported, and no differences in metabolic or glycemic markers. After one week Phase 1metformin/placebo Proteobacteria, Enterobacteriaceae, and Enterobacteriales were identified as candidate biomarkers of metformin effects. Principle coordinate analyses of beta diversity suggested that the metformin/prebiotic intervention was associated with distinct shifts in the microbiome signatures at one week and one month.

Conclusion

Administration of a prebiotic fiber supplement during short-term metformin therapy was well tolerated in Y-T2DM and associated with modest shifts in microbial composition. This study provides a proof-of-concept for feasibility exploring prebiotic-metformin-microbiome interactions as a basis for adjunctive metformin therapy.

Clinical trial registration

https://clinicaltrials.gov/, identifier NCT04209075.

Plasma and Urine Metabolomic Response to an Ultra-Processed Dietary Pattern: A Biomarker Discovery Analysis in a Domiciled Randomized Controlled Crossover Feeding Trial

Objectives

To identify metabolomic markers that differed between dietary patterns (DP) that are either high in or void of ultra-processed foods (UPFs) according to NOVA.

Methods

A secondary analysis of a randomized, crossover, controlled feeding trial in which 20 domiciled, healthy participants (mean ± SD: 31 ± 7 years, BMI 22 ± 11.6, 50% female) consumed a UPF-DP (80% UPFs) and an unprocessed DP (UN-DP; 0% UPFs) for two weeks with no washout. DPs were matched for energy, macronutrients, total fiber, total sugar, and sodium; presented at 200% of energy requirements; and consumed ad libitum. Metabolite levels were measured in EDTA plasma at the end of each DP (wk 2) and in 24-hr and spot urine at wk 1 and 2, using untargeted liquid chromatography with high resolution/tandem mass spectrometry and annotated using Metabolon's reference library and authentic standards. Metabolites (n = 1000 plasma, n = 1272 24-hr urine, and n = 1281 spot urine) with <80% missing data and coefficients of variation <30% were assigned minimum detected values, scaled to median of 1, and log2-transformed. Linear mixed models in SAS identified metabolites that differed between UPF-DP and UN-DP adjusted for trial, DP sequence, timepoint, and body weight changes, with a subject-specific random intercept and Benjamini-Hochberg multiple comparison correction.

Results

For plasma, 183 metabolites differed between UPF-DP and UN-DP at wk 2. For 24-hr urine, 461 metabolites differed between UPF-DP and UN-DP at wk 1 and 2, 68 of which also differed at wk 1 and 2 for spot urine. Twenty metabolites consistently differed between UPF-DP and UN-DP at each timepoint and for each sample type. The sub pathways for these 20 metabolites included glutamate metabolism (n = 1 metabolite); ascorbate and aldarate metabolism (n = 1); benzoate metabolism (n = 2); methionine, cysteine, SAM and taurine metabolism (n = 2); secondary bile acid metabolism (n = 2); fatty acid dicarboxylate (n = 1); and plant-food components (n = 2); 9 could not be annotated.

Conclusions

We identified exogenous and endogenous metabolites, representing a range of metabolic pathways, that consistently differed between a UPF-DP and UN-DP. These candidate biomarkers of UPF intake require investigation in larger samples with dietary data sufficient for NOVA classification.

Funding Sources

NCI, NIDDK.

Complex association of apolipoprotein E-containing HDL with coronary artery disease burden in cardiovascular disease

Background

Although traditional lipid parameters and coronary imaging techniques are valuable for cardiovascular disease (CVD) risk prediction, better diagnostic tests are still needed.

Methods

In a prospective, observational study, 795 individuals had extensive cardiometabolic profiling, including emerging biomarkers, such as apolipoprotein E–containing HDL-cholesterol (ApoE-HDL-C). Coronary artery calcium (CAC) score was assessed in the entire cohort, and quantitative coronary computed tomography angiography (CCTA) characterization of total burden, noncalcified burden (NCB), and fibrous plaque burden (FB) was performed in a subcohort (n = 300) of patients stratified by concentration of ApoE-HDL-C. Total and HDL-containing apolipoprotein C-III (ApoC-III) were also measured.

Results

Most patients had a clinical diagnosis of coronary artery disease (CAD) (n = 80.4% of 795), with mean age of 59 years, a majority being male (57%), and about half on statin treatment. The low ApoE-HDL-C group had more severe stenosis (11% vs. 2%, overall P < 0.001), with higher CAC as compared with high ApoE-HDL-C. On quantitative CCTA, the high ApoE-HDL-C group had lower NCB (β = –0.24, P = 0.0001), which tended to be significant in a fully adjusted model (β = –0.32, P = 0.001) and altered by ApoC-III in HDL levels. Low ApoE-HDL-C was significantly associated with LDL particle number (β = 0.31; P = 0.0001). Finally, when stratified by FB, ApoC-III in HDL showed a more robust predictive value of CAD over ApoE-HDL-C (AUC: 0.705, P = 0.0001) in a fully adjusted model.

Conclusion

ApoE-containing HDL-C showed a significant association with early coronary plaque characteristics and is affected by the presence of ApoC-III, indicating that low ApoE-HDL-C and high ApoC-III may be important markers of CVD severity.

Trial Registration

ClinicalTrials.gov: NCT01621594.

Funding

This work was supported by the NHLBI at the NIH Intramural Research Program.

Effect of a plant-based, low-fat diet versus an animal-based, ketogenic diet on ad libitum energy intake

The carbohydrate-insulin model of obesity posits that high-carbohydrate diets lead to excess insulin secretion, thereby promoting fat accumulation and increasing energy intake. Thus, low-carbohydrate diets are predicted to reduce ad libitum energy intake as compared to low-fat, high-carbohydrate diets. To test this hypothesis, 20 adults aged 29.9 ± 1.4 (mean ± s.e.m.) years with body mass index of 27.8 ± 1.3 kg m^-2 were admitted as inpatients to the National Institutes of Health Clinical Center and randomized to consume ad libitum either a minimally processed, plant-based, low-fat diet (10.3% fat, 75.2% carbohydrate) with high glycemic load (85 g 1,000 kcal^-1) or a minimally processed, animal-based, ketogenic, low-carbohydrate diet (75.8% fat, 10.0% carbohydrate) with low glycemic load (6 g 1,000 kcal^-1) for 2 weeks followed immediately by the alternate diet for 2 weeks. One participant withdrew due to hypoglycemia during the low-carbohydrate diet. The primary outcomes compared mean daily ad libitum energy intake between each 2-week diet period as well as between the final week of each diet. We found that the low-fat diet led to 689 ± 73 kcal d^-1 less energy intake than the low-carbohydrate diet over 2 weeks (P < 0.0001) and 544 ± 68 kcal d^-1 less over the final week (P < 0.0001). Therefore, the predictions of the carbohydrate-insulin model were inconsistent with our observations. This study was registered on ClinicalTrials.gov as NCT03878108 .

Effect of niacin monotherapy on high density lipoprotein composition and function

BACKGROUND

Niacin has modest but overall favorable effects on plasma lipids by increasing high density lipoprotein cholesterol (HDL-C) and lowering triglycerides. Clinical trials, however, evaluating niacin therapy for prevention of cardiovascular outcomes have returned mixed results. Recent evidence suggests that the HDL proteome may be a better indicator of HDL's cardioprotective function than HDL-C. The objective of this study was to evaluate the effect of niacin monotherapy on HDL protein composition and function.

METHODS

A 20-week investigational study was performed with 11 participants receiving extended-release niacin (target dose = 2 g/day) for 16-weeks followed by a 4-week washout period. HDL was isolated from participants at weeks: 0, 16, and 20. The HDL proteome was analyzed at each time point by mass spectrometry and relative protein quantification was performed by label-free precursor ion intensity measurement.

RESULTS

In this cohort, niacin therapy had typical effects on routine clinical lipids (HDL-C + 16%, q < 0.01; LDL-C - 20%, q < 0.01; and triglyceride - 15%, q = 0.1). HDL proteomics revealed significant effects of niacin on 5 proteins: serum amyloid A (SAA), angiotensinogen (AGT), apolipoprotein A-II (APOA2), clusterin (CLUS), and apolipoprotein L1 (APOL1). SAA was the most prominently affected protein, increasing 3-fold in response to niacin (q = 0.008). Cholesterol efflux capacity was not significantly affected by niacin compared to baseline, however, stopping niacin resulted in a 9% increase in efflux (q < 0.05). Niacin did not impact HDL's ability to influence endothelial function.

CONCLUSION

Extended-release niacin therapy, in the absence of other lipid-modifying medications, can increase HDL-associated SAA, an acute phase protein associated with HDL dysfunction.

Postprandial Responses to Isocaloric Low-Carbohydrate vs Low-Fat Meals After 2 Weeks of Inpatient Ad libitum Feeding

Objectives

To explore postprandial responses to isocaloric meals after ∼2 weeks on an ad libitum Low Carbohydrate (LC) diet vs. a Low Fat (LF) diet.

Methods

16 healthy volunteers without diabetes were admitted to the NIH Clinical Center and randomized to consume a LC or LF diet for 2 weeks immediately followed by 2 weeks of the alternate diet. The LC diet was composed of ∼75% fat, ∼10% carbohydrate, and ∼15% protein; the LF diet was ∼75% carbohydrate, ∼10% fat, and ∼15% protein. Daily meals and snacks were matched for presented calories and participants were instructed to consume as much or as little as desired. On day 13 of each diet after an 8 hour fast, participants consumed a liquid meal containing 30% of energy requirements with a macronutrient composition corresponding to the prevailing diet. Blood was drawn at 0, 10, 20, 30, 60, 90, 120, 180, 240, 300, 360 minutes post meal consumption. Plasma concentrations of glucose, lactate, insulin, c-peptide, free fatty acids, and triglycerides were measured.

Results

7 females and 9 males with an age of (mean ± SE) 28.7 ±1.7 y and BMI of 27.5 ± 1.5 kg/m2 completed the study. During the LC diet, baseline levels of triglycerides and lactate were significantly lower (−33.5 ± 9.1 mg/dl; P = 0.003, −0.18 ± 0.05 mM; P = 0.002, respectively) and glucose, insulin, and c-peptide also tended to be lower (−3.7 ± 2.0 mg/dl; P = 0.09, −2.2 ± 1.2 µU/ml; P = 0.08, −0.35 ± 0.17 ng/ml; P = 0.06, respectively) whereas free fatty acids were significantly higher (0.28 ± 0.06 mM; P = 0.0005) compared to the LF diet. Average postprandial levels of glucose, lactate, insulin, and c-peptide were significantly lower following the LC meal (−11 ± 3 mg/dl; P = 0.003, −0.88 ± 0.06 mM; P &lt; 0.0001, −35 ± 9 µU/ml; P = 0.002, −2.5 ± 0.3 ng/ml; P &lt; 0.0001, respectively) whereas free fatty acids and triglycerides were significantly higher (0.52 ± 0.03 mM; P &lt; 0.0001, 32 ± 12 mg/dl; P = 0.03, respectively) compared to the LF meal.

Conclusions

Following a ∼2 week adaptation period to ad libitum LC vs. LF diets, isocaloric meals resulted in substantial differences in postprandial glucose, lactate, insulin, c-peptide, free fatty acids, and triglycerides.

Funding Sources

Intramural Research Program of the NIDDK.

Ad Libitum Energy Intake Differences Between a Plant-Based, Low-Fat and an Animal-Based, Low-Carbohydrate Diet: An Inpatient Randomized Crossover Study

Objectives

To investigate differences in ad libitum energy intake when inpatient adults were exposed to diets with equal calories and protein but varied widely in the ratio of carbohydrate to fat.

Methods

16 adults without diabetes were admitted to the Metabolic Clinical Research Unit in the NIH Clinical Center for four continuous weeks and were randomized to receive either a plant-based, low-fat (LF) diet or an animal-based, low-carbohydrate (LC) diet for two weeks, followed by the alternate diet for two weeks. The LF diet was ∼75% carbohydrate and ∼10% fat, whereas the LC was ∼10% carbohydrate and ∼75% fat. The LF diet had ∼4-fold more fiber and was ∼60% of the energy density of the LC diet. Both diets were matched for protein and the presented calories were double each subject's maintenance energy requirements, as calculated from their measured resting energy expenditure multiplied by 1.6. Participants received three daily meals, had continuous access to snacks, and were instructed to eat as much or as little as they wanted. Leftovers were weighed to determine food intake. ProNutra software was used to calculate energy and nutrient intake.

Results

The study enrolled 9 men and 7 women with an age (mean ± SE) of 29 ± 1.7 years and body mass index (BMI) of 27.5 ± 1.5. During exposure to the LF diet, participants consumed 726 ± 84 kcal/d less than during the LC diet (P &lt; 0.0001). The composition of the food intake closely matched the presented diets, with the LF diet consumption of 75.2 ± 0.2% carbohydrate, 10.7 ± 0.2% fat, and 14.0 ± 0.3% protein whereas the LC diet consumption was 9.9 ± 0.1% carbohydrate, 74.5 ± 0.2% fat, and 15.6 ± 0.2% protein. During the second week of the LC diet, when ketosis had been fully established (capillary β-hydroxybutyrate = 1.4 ± 0.08 mM), intake decreased by 295 ± 52 kcal/d compared to the first week (P &lt; 0.0001) whereas during the second week of the LF diet intake was not significantly changed (−51 ± 52 kcal/d; P = 0.33). Nevertheless, energy intake remained 611 ± 68 kcal/d lower during the second week of the LF diet than the LC diet (P &lt; 0.0001).

Conclusions

Exposure to the LF diet resulted in significantly lower ad libitum energy intake compared to the LC diet, potentially due to its lower energy density and greater fiber content.

Funding Sources

Intramural Research Program of the National Institute of Diabetes and Digestive and Kidney Diseases.

Effects of Ad Libitum Low Carbohydrate Versus Low Fat Diets on Body Weight and Fat Mass

Objectives

To describe the effects of ad libitum low-fat (LF) and low-carbohydrate (LC) diets on body weight and fat mass.

Methods

Sixteen adults without diabetes spent 29 continuous days residing at the Metabolic Clinical Research Unit of the NIH Clinical Center where they were fed ad libitum either an animal-based, LC diet (75% fat, 10% carbohydrates, 15% protein) or a plant-based, LF diet (75% carbohydrates, 10% fat, 15% protein). Participants were randomly assigned to one diet for the first phase of the study (14 days), after which they were switched to the other diet for the remainder of the study. Participants were given three meals daily and were provided with additional snacks amounting to 200% of their daily energy requirements as determined by their resting energy expenditure multiplied by 1.6. Subjects were told that this was not a weight loss study and were not informed about the primary study aim. They were instructed to eat as much or as little as they desired. Total body weight and fat mass were measured using a calibrated scale and dual-energy X-ray absorptiometry, respectively. Subjects were blinded to their data and wore loose-fitting scrubs to avoid any feedback regarding changes in the fit of their clothing.

Results

Subjects included 7 women and 9 men, with an age of (mean ± SE) 29 ± 1.7 years and BMI of 27.5 ± 1.5 at baseline. Participants lost weight on both diets, with the LC diet resulting in 1.34 ± 0.31 kg of weight loss (P = 0.0006) and the LF diet resulting in 1.09 ± 0.31 kg of weight loss (P = 0.003) which was not significantly different from the LC diet (P = 0.58). However, participants lost 0.6 ± 0.17 kg of body fat on the LF diet (P = 0.002) but the LC diet did not result in significant body fat loss (0.04 ± 0.17 kg; P = 0.8) and the difference in body fat loss between the diets was statistically significant (P = 0.03).

Conclusions

While participants lost similar amounts of weight on both diets, only the LF diet led to significant body fat loss. Early weight loss with a LC diet does not necessarily reflect a similar state of negative energy balance as compared with a LF diet.

Funding Sources

Intramural Research Program of the National Institutes of Diabetes and Digestive and Kidney Diseases.

Supplementation with saury oil, a fish oil high in omega-11 monounsaturated fatty acids, improves plasma lipids in healthy subjects

BACKGROUND

Fish oil enriched in omega-11 long-chain monounsaturated fatty acids (LCMUFAs; C20:1 and C22:1 isomers combined) have shown lipid-lowering and atheroprotective effects in animal models.

OBJECTIVE

To perform a first-in-human trial of LCMUFA-rich saury fish oil supplementation to test its safety and possible effect on plasma lipids.

METHODS

A double-blind, randomized, crossover clinical trial was carried out in 30 healthy normolipidemic adults (BMI <25 kg/m2; mean TG, 84 mg/dL). Treatment periods of 8 weeks were separated by an 8-week washout period. Subjects were randomized to receive either 12 g of saury oil (3.5 g of LCMUFA and 3.4 g of omega-3 FAs) or identical capsules with control oil (a mixture of sardine and olive oil; 4.9 g of shorter-chain MUFA oleate and 3 g of omega-3 FAs).

RESULTS

Saury oil supplementation was safe and resulted in LDL particle counts 12% lower than control oil (P < .001). Saury oil also had a minor effect on increasing HDL particle size (9.8 nm vs 9.7 nm; P < .05) based on a linear mixed effect model. In contrast, control oil, but not saury oil, increased LDL-C by 7.5% compared with baseline (P < .05). Saury oil had similar effects compared with control oil on lowering plasma TG levels, VLDL, and TG-rich lipoprotein particle counts (by ∼16%, 25%, and 35%, respectively; P < .05), and increasing HDL-C and cholesterol efflux capacity (by ∼6% and 8%, respectively; P < .05) compared with baseline.

CONCLUSION

Saury oil supplementation is well tolerated and has beneficial effects on several cardiovascular parameters, such as LDL particle counts, HDL particle size, and plasma TG levels.

Ultra-Processed Diets Cause Excess Calorie Intake and Weight Gain: An Inpatient Randomized Controlled Trial of Ad Libitum Food Intake

We investigated whether ultra-processed foods affect energy intake in 20 weight-stable adults, aged (mean ± SE) 31.2 ± 1.6 years and BMI = 27 ± 1.5 kg/m². Subjects were admitted to the NIH Clinical Center and randomized to receive either ultra-processed or unprocessed diets for 2 weeks immediately followed by the alternate diet for 2 weeks. Meals were designed to be matched for presented calories, energy density, macronutrients, sugar, sodium, and fiber. Subjects were instructed to consume as much or as little as desired. Energy intake was greater during the ultra-processed diet (508 ± 106 kcal/day; p = 0.0001), with increased consumption of carbohydrate (280 ± 54 kcal/day; p < 0.0001) and fat (230 ± 53 kcal/day; p = 0.0004), but not protein (-2 ± 12 kcal/day; p = 0.85). Weight changes were highly correlated with energy intake (r = 0.8, p < 0.0001), with participants gaining 0.9 ± 0.3 kg (p = 0.009) during the ultra-processed diet and losing 0.9 ± 0.3 kg (p = 0.007) during the unprocessed diet. Limiting consumption of ultra-processed foods may be an effective strategy for obesity prevention and treatment.