Preparing glycomics data for robust statistical analysis with GlyCompareCT.

GlyCompareCT is a portable command-line tool to facilitate downstream glycomic data analyses, by addressing data inherent sparsity and non-independence. Inputting glycan abundances, users can run GlyCompareCT with one line of code to obtain the abundances of a minimal substructure set, named glycomotif, thereby quantifying hidden biosynthetic relationships between measured glycans. Optional parameters tuning and annotation are supported for personal preference. For complete details on the use and execution of this protocol, please refer to Bao et al. (2021).1.

Anti-Mullerian Hormone-Based Phenotyping Identifies Subgroups of Women with Polycystic Ovary Syndrome with Differing Clinical and Biochemical Characteristics.

Even though polycystic ovary syndrome (PCOS) was originally defined as "amenorrhea associated with bilateral polycystic ovaries", women without PCO morphology can be included in this diagnosis. This may contribute to the clinical heterogeneity seen in PCOS. Serum anti-Mullerian hormone (AMH) correlates with the number of ovarian cysts. We investigated whether phenotyping based on serum AMH can distinguish subgroups of PCOS with different clinical and biochemical characteristics. The electronic medical records of 108 women with PCOS (Rotterdam criteria) were reviewed. The serum AMH value correlated inversely (0.03 < p < 0.0001) with age, weight, and BMI values and directly with serum total testosterone (T), free T, and bioavailable T values. When divided into quartiles based on serum AMH values, the women in the highest quartile (AMH: 18.5 ± 9.9 ng/mL; n = 27) had lower BMI (29.4 ± 6.9 vs. 34.0 ± 10.6-36.7 ± 7.2 kg/m2) but higher total T (51.3 ± 27.2 vs. 26.5 ± 10.4-35.1 ± 16.3 ng/dL), free T (7.7 ± 6.0 vs. 4.4 ± 2.3-5.7 ± 3.2 ng/dL), and bioavailable T (22.1 ± 17.0 vs. 12.2 ± 6.6-16.5 ± 8.7 ng/dL) values. The combination of high AMH and high testosterone values may point to the ovaries and reproductive etiology for PCOS in this subgroup. Thus, AMH-based phenotyping may provide a practical and cost-effective tool to explore the heterogeneity in PCOS.

Effect of a diet based on the dietary guidelines for americans on inflammation markers in women at risk for cardiometabolic disease: results of a randomized, controlled trial.

OBJECTIVE: To evaluate the effect of a diet pattern based on Dietary Guidelines for Americans (DGA), in a controlled feeding setting, on plasma markers of inflammation and on cytokine production by peripheral blood mononuclear cells (PBMC). DESIGN: Women (n = 44) with one or more risk factors of metabolic syndrome (and BMI: 25.2-39.8 kg/m2) completed an 8-wk controlled feeding study. They were randomized to either a group following a diet based on DGA 2010 (DGA), or a group given a 'typical American diet' (TAD), based largely on a Western diet pattern. By design, women maintained their body weight. Fasting plasma and PBMC were collected at wk. 0 (baseline) and at wk. 8 (post-intervention). Sixteen plasma markers of inflammation and eight PBMC cytokines were measured at both time points, to evaluate if the diet had a significant effect on concentrations of these inflammatory markers. Data were analyzed using ANCOVA, followed by multiple-comparison adjustment using Benjamini-Hochberg method. RESULTS: Significant changes observed in Serum Amyloid A (SAA) and Matrix Metalloproteinase 3 (MMP3) in plasma did not retain significance upon multiple comparison adjustment. SAA: p = 0.044, adj p = 0.450; DGA mean change [95% CI] = - 12.6[- 32.3 to 7.04]; TAD mean change [95% CI] = - 2.24 [- 9.99 to 5.51]. MMP3: p = 0.014, adj p = 0.35; DGA mean change [95% CI] = 2.72[- 4.16 to 9.59]; TAD mean change [95% CI] = - 0.98[- 16.7 to 14.7]). Other inflammation markers were not differently altered by DGA relative to TAD. Effect size of change (Cohens d) indicated a large/medium-large effect of intervention on MMP3 and CRP, and medium effect on IL-6. CONCLUSIONS: No statistically significant changes were observed in the immune markers examined in this study. The biological roles and magnitude of the non-significant differences seen with two variables, CRP and MMP3, suggest that they be examined in future studies. TRIAL REGISTRATION: Clinicaltrials.gov identifier NCT02298725.

Assessing Insulin Sensitivity and Postprandial Triglyceridemic Response Phenotypes With a Mixed Macronutrient Tolerance Test.

The use of meal challenge tests to assess postprandial responses in carbohydrate and fat metabolism is well established in clinical nutrition research. However, challenge meal compositions and protocols remain a variable. Here, we validated a mixed macronutrient tolerance test (MMTT), containing 56-g palm oil, 59-g sucrose, and 26-g egg white protein for the parallel determination of insulin sensitivity and postprandial triglyceridemia in clinically healthy subjects. The MMTT was administered in two study populations. In one, women with overweight/obese BMIs (n = 43) involved in an 8-week dietary intervention were administered oral glucose tolerance tests (OGTTs) and MMTTs within 2 days of each other after 0, 2, and 8 weeks of the dietary intervention. In the other, 340 men and women between 18 and 64 years of age, with BMI from 18-40 kg/m2, completed the MMTT as part of a broad nutritional phenotyping effort. Postprandial blood collected at 0, 0.5, 3, and 6 h was used to measure glucose, insulin, and clinical lipid panels. The MMTT postprandial insulin-dependent glucose disposal was evaluated by using the Matsuda Index algorithm and the 0- and 3 h blood insulin and glucose measures. The resulting MMTT insulin sensitivity index (ISIMMTT) was strongly correlated (r = 0.77, p < 0.001) with the OGTT-dependent 2 h composite Matsuda index (ISIComposite), being related by the following equation: Log (ISIComposite) = [0.8751 x Log(ISIMMTT)] -0.2115. An area under the triglyceride excursion curve >11.15 mg/mL h-1 calculated from the 0, 3, and 6 h blood draws established mild-to-moderate triglyceridemia in agreement with ∼20% greater prevalence of hypertriglyceridemia than fasting indications. We also demonstrated that the product of the 0 to 3 h and 3 to 6 h triglyceride rate of change as a function of the triglyceride incremental area under the curve optimally stratified subjects by postprandial response patterns. Notably, ∼2% of the population showed minimal triglyceride appearance by 6 h, while ∼25% had increasing triglycerides through 6 h. Ultimately, using three blood draws, the MMTT allowed for the simultaneous determination of insulin sensitivity and postprandial triglyceridemia in individuals without clinically diagnosed disease. Clinical Trial Registration: [https://clinicaltrials.gov/], identifier [NCT02298725; NCT02367287].

Satiety Associated with Calorie Restriction and Time-Restricted Feeding: Peripheral Hormones.

Calorie restriction (CR) is a common approach to inducing negative energy balance. Recently, time-restricted feeding (TRF), which involves consuming food within specific time windows during a 24-h day, has become popular owing to its relative ease of practice and potential to aid in achieving and maintaining a negative energy balance. TRF can be implemented intentionally with CR, or TRF might induce CR simply because of the time restriction. This review focuses on summarizing our current knowledge on how TRF and continuous CR affect gut peptides that influence satiety. Based on peer-reviewed studies, in response to CR there is an increase in the orexigenic hormone ghrelin and a reduction in fasting leptin and insulin. There is likely a reduction in glucagon-like peptide-1 (GLP-1), peptide YY (PYY), and cholecystokinin (CCK), albeit the evidence for this is weak. After TRF, unlike CR, fasting ghrelin decreased in some TRF studies, whereas it showed no change in several others. Further, a reduction in fasting leptin, insulin, and GLP-1 has been observed. In conclusion, when other determinants of food intake are held equal, the peripheral satiety systems appear to be somewhat similarly affected by CR and TRF with regard to leptin, insulin, and GLP-1. But unlike CR, TRF did not appear to robustly increase ghrelin, suggesting different influences on appetite with a potential decrease of hunger after TRF when compared with CR. However, there are several established and novel gut peptides that have not been measured within the context of CR and TRF, and studies that have evaluated effects of TRF are often short-term, with nonuniform study designs and highly varying temporal eating patterns. More evidence and studies addressing these aspects are needed to draw definitive conclusions.

The Omega-3 Index Response to an 8 Week Randomized Intervention Containing Three Fatty Fish Meals Per Week Is Influenced by Adiposity in Overweight to Obese Women.

BACKGROUND: The Dietary Guidelines for Americans (DGA) recommends consuming ~225 g/wk of a variety of seafood providing >1.75 g/wk of long-chain omega-3 fatty acids to reduce cardiovascular disease risk, however individual responses to treatment vary. OBJECTIVE: This study had three main objectives. First, to determine if a DGA-conforming diet (DGAD), in comparison to a typical American diet (TAD), can increase the omega-3 index (OM3I), i.e., the red blood cell mol% of eicosapentaenoic acid (EPA) + docosahexaenoic acid (DHA). Second, to identify factors explaining variability in the OM3I response to dietary treatment. Third to identify factors associated with the baseline OM3I. DESIGN: This is a secondary analysis of a randomized, double-blind 8 wk dietary intervention of overweight/obese women fed an 8d rotating TAD (n = 20) or DGAD (n = 22) registered at www.clinicaltrials.gov as NCT02298725. The DGAD-group consumed 240 g/wk of Atlantic farmed salmon and albacore tuna in three meals with an estimated EPA + DHA of 3.7 ± 0.6 g/wk. The TAD-group consumed ~160 g/wk of farmed white shrimp and a seafood salad containing imitation crab in three meal with an estimated EPA + DHA of 0.45 ± 0.05 g/wk. Habitual diet was determined at baseline, and body composition was determined at 0 and 8wks. Red blood cell fatty acids were measured at 0, 2 and 8 wk. RESULTS: At 8 wk, the TAD-group OM3I was unchanged (5.90 ± 1.35-5.80 ± 0.76%), while the DGAD-group OM3I increased (5.63 ± 1.27-7.33 ± 1.36%; p < 0.001). In the DGAD-group 9 of 22 participants achieved an OM3I >8%. Together, body composition and the baseline OM3I explained 83% of the response to treatment variability. Baseline OM3I (5.8 ± 1.3%; n = 42) was negatively correlated to the android fat mass (p = 0.0007) and positively correlated to the FFQ estimated habitual (EPA+DHA) when expressed as a ratio to total dietary fat (p = 0.006). CONCLUSIONS: An 8 wk TAD did not change the OM3I of ~6%, while a DGAD with 240 g/wk of salmon and albacore tuna increased the OM3I. Body fat distribution and basal omega-3 status are primary factors influencing the OM3I response to dietary intake in overweight/obese women.

Satiety Associated with Calorie Restriction and Time-Restricted Feeding: Central Neuroendocrine Integration.

This review focuses on summarizing current knowledge on how time-restricted feeding (TRF) and continuous caloric restriction (CR) affect central neuroendocrine systems involved in regulating satiety. Several interconnected regions of the hypothalamus, brainstem, and cortical areas of the brain are involved in the regulation of satiety. Following CR and TRF, the increase in hunger and reduction in satiety signals of the melanocortin system [neuropeptide Y (NPY), proopiomelanocortin (POMC), and agouti-related peptide (AgRP)] appear similar between CR and TRF protocols, as do the dopaminergic responses in the mesocorticolimbic circuit. However, ghrelin and leptin signaling via the melanocortin system appears to improve energy balance signals and reduce hyperphagia following TRF, which has not been reported in CR. In addition to satiety systems, CR and TRF also influence circadian rhythms. CR influences the suprachiasmatic nucleus (SCN) or the primary circadian clock as seen by increased clock gene expression. In contrast, TRF appears to affect both the SCN and the peripheral clocks, as seen by phasic changes in the non-SCN (potentially the elusive food entrainable oscillator) and metabolic clocks. The peripheral clocks are influenced by the primary circadian clock but are also entrained by food timing, sleep timing, and other lifestyle parameters, which can supersede the metabolic processes that are regulated by the primary circadian clock. Taken together, TRF influences hunger/satiety, energy balance systems, and circadian rhythms, suggesting a role for adherence to CR in the long run if implemented using the TRF approach. However, these suggestions are based on only a few studies, and future investigations that use standardized protocols for the evaluation of the effect of these diet patterns (time, duration, meal composition, sufficiently powered) are necessary to verify these preliminary observations.

Effects of a diet based on the Dietary Guidelines on vascular health and TMAO in women with cardiometabolic risk factors.

BACKGROUND AND AIMS: Recent evidence links trimethylamine oxide (TMAO) to endothelial dysfunction, an early indicator of cardiovascular disease. We aimed to determine whether short-term consumption of a diet patterned after the 2010 Dietary Guidelines for Americans (DGA) would affect endothelial function, plasma TMAO concentrations, and cardiovascular disease risk, differently than a typical American Diet (TAD). METHODS AND RESULTS: An 8-wk controlled feeding trial was conducted in overweight/obese women pre-screened for insulin resistance and/or dyslipidemia. Women were randomized to a DGA or TAD group (n = 22/group). At wk0 (pre-intervention) and wk8 (post-intervention) vascular age was calculated; endothelial function (reactive hyperemia index (RHI)) and augmentation index (AI@75) were measured using EndoPAT, and plasma TMAO was measured by LC-MS/MS. Vascular age was reduced in DGA at wk8 compared to wk0 but TAD wk8 was not different from wk0 (DGA wk0: 54.2 ± 4.0 vs. wk8: 50.5 ± 3.1 (p = 0.05), vs. TAD wk8: 47.7 ± 2.3). Plasma TMAO concentrations, RHI, and AI@75 were not different between groups or weeks. CONCLUSION: Consumption of a diet based on the 2010 Dietary Guidelines for Americans for 8 weeks did not improve endothelial function or reduce plasma TMAO. CLINICALTRIALS.GOV: NCT02298725.

Adopting a Mediterranean-style eating pattern with low, but not moderate, unprocessed, lean red meat intake reduces fasting serum trimethylamine N-oxide (TMAO) in adults who are overweight or obese.

A Mediterranean-style eating pattern (MED-EP) may include moderate red meat intake. However, it is unknown if the pro-atherogenic metabolite trimethylamine N-oxide (TMAO) is affected by the amount of red meat consumed with a MED-EP. The results presented are from a secondary, retrospective objective of an investigator-blinded, randomized, crossover, controlled feeding trial (two 5-wk interventions separated by a 4-wk washout) to determine if a MED-EP with 200g unprocessed lean red meat/wk (MED-CONTROL) reduces circulating TMAO concentrations compared to a MED-EP with 500g unprocessed lean red meat/wk (MED-RED). Participants were 27 women and 12 men (n=39 total) who were either overweight or obese (BMI: 30.5 ± 0.3 kg/m2 mean ± SEM). Serum samples were obtained following an overnight fast both before (pre) and after (post) each intervention. Fasting serum TMAO, choline, carnitine, and betaine concentrations were measured using a targeted Liquid chromatography-mass spectrometry. Data were analyzed to assess if (a) TMAO and related metabolites differed by intervention, and (b) if changes in TMAO were associated with changes in Framingham 10-year risk score. Serum TMAO was lower post-intervention following MED-CONTROL compared to MED-RED intervention (post-MED-CONTROL 3.1 ± 0.2 µM vs. post-MED-RED 5.0 ± 0.5 µM, p<0.001), and decreased following MED-CONTROL (pre- vs post-MED-CONTROL, p = 0.025). Exploratory analysis using mixed model analysis of covariance identified a positive association between changes in TMAO and changes in HOMA-IR (p = 0.036). These results suggest that lower amounts of red meat intake leads to lower TMAO concentrations in the context of a MED-EP.

Healthy eating index patterns in adults by sex and age predict cardiometabolic risk factors in a cross-sectional study.

BACKGROUND: Associations between diet and cardiometabolic disease (CMD) risk may vary in men and women owing to sex differences in eating habits and physiology. The current secondary analysis sought to determine the ability of sex differences in dietary patterns to discriminate groups with or without CMD risk factors (CMDrf) in the adult population and if this was influenced by age. METHODS: Diet patterns and quality were evaluated using 24 h recall-based Healthy Eating Index (HEI-2015) in free-living apparently healthy men (n = 184) and women (n = 209) 18-65 y of age with BMIs of 18-44 kg/m2. Participants were stratified into low- and high-CMDrf groups based on the presence/absence of at least one CMDrf: BMI > 25 kg/m2; fasting triglycerides > 150 mg/dL; HDL cholesterol < 50 mg/dL-women or < 40 mg/dL-men; HOMA > 2; HbA1c > 5.7. Sex by age dietary patterns were stratified by multivariate analyses, with metabolic variable associations established by stepwise discriminant analysis. RESULTS: Diet quality increased with age in both sexes (P < 0.01), while women showed higher fruit, vegetable and saturated fat intake as a percentage of total energy (P < 0.05). The total-HEI score (i.e. diet quality) was lower in the high-CMDrf group (P = 0.01), however, diet quality parameters predicted CMDrf presence more accurately when separated by sex. Lower 'total vegetable' intake in the high-CMDrf group in both sexes, while high-CMDrf men also had lower 'total vegetables', 'greens and beans' intake, and high-CMDrf women had lower 'total fruits', 'whole-fruits', 'total vegetables', 'seafood and plant-proteins', 'fatty acids', and 'saturated fats' intakes (P < 0.05). Moreover, 'dairy' intake was higher in high-CMDrf women but not in men (sex by 'dairy' interaction P = 0.01). Sex by age diet pattern models predicted CMDrf with a 93 and 89% sensitivity and 84 and 92% specificity in women and men, respectively. CONCLUSIONS: Sex and age differences in dietary patterns classified participants with and without accepted CMDrfs, supporting an association between specific diet components and CMD risk that differs by sex. Including sex specific dietary patterns into health assessments may provide targeted nutritional guidance to reduce the burden of cardiovascular disease. TRIAL REGISTRATION: ClinicalTrials.gov : NCT02367287 . ClinicalTrials.gov : NCT02298725 .

Diet affects glycosylation of serum proteins in women at risk for cardiometabolic disease.

BACKGROUND: Glycoproteomics deals with glycoproteins that are formed by post-translational modification when sugars (like fucose and sialic acid) are attached to protein. Glycosylation of proteins influences function, but whether glycosylation is altered by diet is unknown. OBJECTIVE: To evaluate the effect of consuming a diet based on the Dietary Guidelines for Americans on circulating glycoproteins that have previously been associated with cardiometabolic diseases. DESIGN: Forty-four women, with one or more metabolic syndrome characteristics, completed an 8-week randomized controlled feeding intervention (n = 22) consuming a diet based on the Dietary Guidelines for Americans (DGA 2010); the remaining consumed a 'typical American diet' (TAD, n = 22). Fasting serum samples were obtained at week0 (baseline) and week8 (post-intervention); 17 serum proteins were chosen for targeted analyses. Protein standards and serum samples were analyzed in a UHPLC-MS protocol to determine peptide concentration and their glycan (fucosylation or sialylation) profiles. Data at baseline were used in correlational analyses; change in proteins and glycans following intervention were used in non-parametric analyses. RESULTS: At baseline, women with more metabolic syndrome characteristics had more fucosylation (total di-fucosylated proteins: p = 0.045) compared to women with a lesser number of metabolic syndrome characteristics. Dietary refined grain intake was associated with increased total fucosylation (ρ = - 0.530, p < 0.001) and reduced total sialylation (ρ = 0.311, p = 0.042). After the 8-week intervention, there was higher sialylation following the DGA diet (Total di-sialylated protein p = 0.018, poly-sialylated orosomucoid p = 0.012) compared to the TAD diet. CONCLUSIONS: Based on this study, glycosylation of proteins is likely affected by dietary patterns; higher sialylation was associated with a healthier diet pattern. Altered glycosylation is associated with several diseases, particularly cancer and type 2 diabetes, and this study raises the possibility that diet may influence disease state by altering glycosylation. CLINICAL TRIAL REGISTRATION: NCT02298725 at clinicaltrials.gov; https://clinicaltrials.gov/ct2/show/NCT02298725 .

N-Glycosylation Network Construction and Analysis to Modify Glycans on the Spike (S) Glycoprotein of SARS-CoV-2.

Background: The N-glycan structure and composition of the spike (S) protein of SARS-CoV-2 are pertinent to vaccine development and efficacy. Methods: We reconstructed the glycosylation network based on previously published mass spectrometry data using GNAT, a glycosylation network analysis tool. Our compilation of the network tool had 26 glycosyltransferase and glucosidase enzymes and could infer the pathway of glycosylation machinery based on glycans in the virus spike protein. Once the glycan biosynthesis pathway was generated, we simulated the effect of blocking specific enzymes-swainsonine or deoxynojirimycin for blocking mannosidase-II and indolizidine for blocking alpha-1,6-fucosyltransferase-to see how they would affect the biosynthesis network and the glycans that were synthesized. Results: The N-glycan biosynthesis network of SARS-CoV-2 spike protein shows an elaborate enzymatic pathway with several intermediate glycans, along with the ones identified by mass spectrometric studies. Of the 26 enzymes, the following were involved-Man-Ia, MGAT1, MGAT2, MGAT4, MGAT5, B3GalT, B4GalT, Man-II, SiaT, ST3GalI, ST3GalVI, and FucT8. Blocking specific enzymes resulted in a substantially modified glycan profile of SARS-CoV-2. Conclusion: Variations in the final N-glycan profile of the virus, given its site-specific microheterogeneity, are factors in the host response to the infection, vaccines, and antibodies. Heterogeneity in the N-glycan profile of the spike (S) protein and its potential effect on vaccine efficacy or adverse reactions to the vaccines remain unexplored. Here, we provide all the resources we generated-the glycans in the glycoCT xml format and the biosynthesis network for future work.

Weight Loss, but Not Dairy Composition of Diet, Moderately Affects Satiety and Postprandial Gut Hormone Patterns in Adults.

BACKGROUND: Inclusion of dairy in diet patterns has been shown to have mixed effects on weight loss. A prevailing hypothesis is that dairy improves weight loss by influencing endocrine systems associated with satiety and food intake regulation. OBJECTIVES: The objective of the current study was to evaluate the effect of weight loss with or without adequate dietary dairy on subjective and objective appetitive measures. METHODS: Men and women who were habitual low dairy consumers (n = 65, 20-50 y) participated in a 12-wk randomized controlled feeding weight loss trial. During the 12-wk intervention, a low-dairy (<1 serving dairy/d) was compared with an adequate-dairy (3-4 servings dairy/d) diet, both with a 500-kcal deficit/d. Test days, before and at the end of the intervention, began with 2 fasting blood draws and visual analog scale (VAS) measures, followed by a standard breakfast (25% of prescribed restricted calories), 5 postbreakfast blood draws and VASs, a standard lunch (40% of restricted energy amount), and 12 postlunch blood draws and VASs. Blood samples were used for satiety hormone measurements. On a separate day when matching standard meals were consumed, an ad libitum buffet meal was provided as dinner, at a self-selected time. Meal duration and intermeal interval were recorded. RESULTS: Weight loss (-6.1 kg), irrespective of dairy, resulted in reduced fasting insulin (-20%) and leptin (-25%), and increased fasting acylated ghrelin (+25%) and VAS desire to eat (+18%) (P < 0.05). There were no effects of dairy on objective or subjective satiety measures. Weight loss marginally reduced the intermeal interval (289 min compared with 276 min, P = 0.059) between lunch and the ad libitum buffet. CONCLUSIONS: These results do not support the hypothesis that inclusion of dairy in long-term dietary patterns influences appetite during weight loss. Weight loss per se has a modest impact on select systems that regulate hunger and satiety.This trial was registered at clinicaltrials.gov as NCT00858312.

Challenges in Designing and Delivering Diets and Assessing Adherence: A Randomized Controlled Trial Evaluating the 2010 Dietary Guidelines for Americans.

BACKGROUND: Controlled-feeding trials are challenging to design and administer in a free-living setting. There is a need to share methods and best practices for diet design, delivery, and standard adherence metrics. OBJECTIVES: This report describes menu planning, implementing, and monitoring of controlled diets for an 8-wk free-living trial comparing a diet pattern based on the Dietary Guidelines for Americans (DGA) and a more typical American diet (TAD) pattern based on NHANES 2009-2010. The objectives were to 1) provide meals that were acceptable, portable, and simple to assemble at home; 2) blind the intervention diets to the greatest extent possible; and 3) use tools measuring adherence to determine the success of the planned and implemented menu. METHODS: Menus were blinded by placing similar dishes on the 2 intervention diets but changing recipes. Adherence was monitored using daily food checklists, a real-time dashboard of scores from daily checklists, weigh-backs of containers returned, and 24-h urinary nitrogen recoveries. Proximate analyses of diet composites were used to compare the macronutrient composition of the composite and planned menu. RESULTS: Meeting nutrient intake recommendations while scaling menus for individual energy intake amounts and food portions was most challenging for vitamins D and E, the sodium-to-potassium ratio, dietary fiber, and fatty acid composition. Dietary adherence for provided foods was >95%, with no differences between groups. Urinary nitrogen recoveries were ∼80% relative to nitrogen intake and not different between groups. Composite proximate analysis matched the plan for dietary fat, protein, and carbohydrates. Dietary fiber was ∼2.5 g higher in the TAD composite compared with the planned menu, but ∼7.4 g lower than the DGA composite. CONCLUSIONS: Both DGA and TAD diets were acceptable to most participants. This conclusion was supported by self-reported consumption, quantitative weigh-backs of provided food, and urinary nitrogen recovery. Dietary adherence measures in controlled-feeding trials would benefit from standard protocols to promote uniformity across studies. The trial is registered at clinicaltrials.gov as NCT02298725.

Phenotyping Women Based on Dietary Macronutrients, Physical Activity, and Body Weight Using Machine Learning Tools.

Nutritional phenotyping can help achieve personalized nutrition, and machine learning tools may offer novel means to achieve phenotyping. The primary aim of this study was to use energy balance components, namely input (dietary energy intake and macronutrient composition) and output (physical activity) to predict energy stores (body weight) as a way to evaluate their ability to identify potential phenotypes based on these parameters. From the Women's Health Initiative Observational Study (WHI OS), carbohydrates, proteins, fats, fibers, sugars, and physical activity variables, namely energy expended from mild, moderate, and vigorous intensity activity, were used to predict current body weight (both as body weight in kilograms and as a body mass index (BMI) category). Several machine learning tools were used for this prediction. Finally, cluster analysis was used to identify putative phenotypes. For the numerical predictions, the support vector machine (SVM), neural network, and k-nearest neighbor (kNN) algorithms performed modestly, with mean approximate errors (MAEs) of 6.70 kg, 6.98 kg, and 6.90 kg, respectively. For categorical prediction, SVM performed the best (54.5% accuracy), followed closely by the bagged tree ensemble and kNN algorithms. K-means cluster analysis improved prediction using numerical data, identified 10 clusters suggestive of phenotypes, with a minimum MAE of ~1.1 kg. A classifier was used to phenotype subjects into the identified clusters, with MAEs <5 kg for 15% of the test set (n = ~2000). This study highlights the challenges, limitations, and successes in using machine learning tools on self-reported data to identify determinants of energy balance.

A randomized controlled-feeding trial based on the Dietary Guidelines for Americans on cardiometabolic health indexes.

Background: The 2010 Dietary Guidelines for Americans (DGA) recommend nutrient needs be met by increasing fruit, vegetable, and whole-grain intake with the use of low-fat or fat-free dairy products and by reducing sodium, solid fats, and added sugars. However, the DGA, as a dietary pattern, have not been tested in an intervention trial. Objective: The aim of this study was to evaluate the impact of a DGA-based diet compared with a representative typical American diet (TAD) on glucose homeostasis and fasting lipids in individuals at risk of cardiometabolic disease. Design: A randomized, double-blind, controlled 8-wk intervention was conducted in overweight and obese women selected according to indexes of insulin resistance or dyslipidemia. Women were randomly assigned to the DGA or TAD group (n = 28 DGA and 24 TAD). The TAD diet was based on average adult intake from the NHANES 2009-2010. The DGA and TAD diets had respective Healthy Eating Index scores of 98 and 62. All foods and beverages were provided during the intervention. Oral-glucose tolerance and fasting lipids were evaluated at 0, 2, and 8 wk of the intervention. Insulin resistance and sensitivity were estimated with the use of surrogates (e.g., homeostasis model assessment of insulin resistance). Results: By design, volunteers maintained their weight during the intervention. Fasting insulin, glucose, triglycerides, oral-glucose tolerance, and indexes of insulin resistance were not affected by either of the diets. Systolic blood pressure decreased in the DGA group (∼-9 mm Hg; P < 0.05). Total and HDL cholesterol also decreased in both groups (P < 0.05). Exploratory analysis comparing volunteers entering the study with insulin resistance and dyslipidemia with those with only dyslipidemia did not show an effect of pre-existing conditions on glucose tolerance or fasting lipid outcomes. Conclusions: The consumption of a DGA dietary pattern for 8 wk without weight loss reduced systolic blood pressure. There were no differences between the DGA and TAD diets in fasting insulin, glucose, indexes of insulin resistance, or fasting lipids. This trial was registered at www.clinicaltrials.gov as NCT02298725.

A Clear Difference Emerges in Hormone Patterns Following a Standard Midday Meal in Young Women Who Regularly Eat or Skip Breakfast.

BACKGROUND: Multiple hormones are involved in the regulation of food intake and glucose metabolism. Past intervention studies showed a benefit of eating breakfast on satiety, but this was possibly confounded by the disruption of habitual meal patterns. OBJECTIVE: The objective of this study was to compare hormonal responses, including insulin, leptin, glucagon-like peptide-1, ghrelin, peptide YY (PYY3-36), and cholecystokinin (CCK), between habitual breakfast eaters (Br-Es) and habitual skippers (Br-Ss) to a standard midday meal. METHODS: Thirty-two women [mean ± SD age: 22.6 ± 3.3 y; body mass index (in kg/m2): 21.8 ± 2.0] participated in a cross-sectional study that consisted of a 3-h test protocol that included a standard test meal served at 1230 with pre- and postmeal blood sampling. The protocol required that Br-Es eat a typical breakfast between 0700 and 1000, whereas Br-Ss had no breakfast meal and had fasted for 12 h. Blood was drawn 35 and 5 min prelunch and 5, 20, 35, 50, and 110 min postlunch. RESULTS: Repeated-measures ANOVA revealed a group difference for PYY3-36 (P = 0.001), with the Br-E group exhibiting 50-90% higher concentrations throughout the test period. Leptin tended to be different (P = 0.08) between groups, with higher mean ± SD values for the Br-S group (27.6 ± 29.6 ng/mL) compared with the Br-E group (11.5 ± 9.8 ng/mL). Partial least squares regression analysis confirmed that these 2 hormones were important contributors to the patterns of the hormones, anthropometric, clinical, and behavioral variables that differed between groups; insulin and CCK were important as well. CONCLUSION: We found differences between the Br-E and Br-S groups in circulating gut and adipose-derived hormones measured midday, indicating that the breakfast habit is associated with the hormonal milieu before and after a midday meal. The different patterns may be short-lived or may impact metabolism later in the day. This report is a secondary analysis of a trial registered at clinicaltrials.gov as NCT01427556.

SELF BLOOD GLUCOSE MONITORING UNDERESTIMATES HYPERGLYCEMIA AND HYPOGLYCEMIA AS COMPARED TO CONTINUOUS GLUCOSE MONITORING IN TYPE 1 AND TYPE 2 DIABETES.

OBJECTIVE: When glucose records from self blood glucose monitoring (SBGM) do not reflect estimated average glucose from glycosylated hemoglobin (HgBA1) or when patients' clinical symptoms are not explained by their SBGM records, clinical management of diabetes becomes a challenge. Our objective was to determine the magnitude of differences in glucose values reported by SBGM versus those documented by continuous glucose monitoring (CGM). METHODS: The CGM was conducted by a clinical diabetes educator (CDE)/registered nurse by the clinic protocol, using the Medtronic iPRO2™ system. Patients continued SBGM and managed their diabetes without any change. Data from 4 full days were obtained, and relevant clinical information was recorded. De-identified data sets were provided to the investigators. RESULTS: Data from 61 patients, 27 with type 1 diabetes (T1DM) and 34 with T2DM were analyzed. The lowest, highest, and average glucose recorded by SBGM were compared to the corresponding values from CGM. The lowest glucose values reported by SBGM were approximately 25 mg/dL higher in both T1DM ( P = .0232) and T2DM ( P = .0003). The highest glucose values by SBGM were approximately 30 mg/dL lower in T1DM ( P = .0005) and 55 mg/dL lower in T2DM ( P<.0001). HgBA1c correlated with the highest and average glucose by SBGM and CGM. The lowest glucose values were seen most frequently during sleep and before breakfast; the highest were seen during the evening and postprandially. CONCLUSION: SBGM accurately estimates the average glucose but underestimates glucose excursions. CGM uncovers glucose patterns that common SBGM patterns cannot. ABBREVIATIONS: CDE = certified diabetes educator; CGM = continuous glucose monitoring; HgBA1c = glycosylated hemoglobin; MAD = mean absolute difference; SBGM = self blood glucose monitoring; T1DM = type 1 diabetes; T2DM = type 2 diabetes.