Effects of Preanalytical Sample Collection and Handling on Comprehensive Metabolite Measurements in Human Urine Biospecimens.

Epidemiology studies evaluate associations between the metabolome and disease risk. Urine is a common biospecimen used for such studies due to its wide availability and non-invasive collection. Evaluating the robustness of urinary metabolomic profiles under varying preanalytical conditions is thus of interest. Here we evaluate the impact of sample handling conditions on urine metabolome profiles relative to the gold standard condition (no preservative, no refrigeration storage, single freeze thaw). Conditions tested included the use of borate or chlorhexidine preservatives, various storage and freeze/thaw cycles. We demonstrate that sample handling conditions impact metabolite levels, with borate showing the largest impact with 125 of 1,048 altered metabolites (adjusted P < 0.05). When simulating a case-control study with expected inconsistencies in sample handling, we predicted the occurrence of false positive altered metabolites to be low (< 11). Predicted false positives increased substantially (³63) when cases were simulated to undergo alternate handling. Finally, we demonstrate that sample handling impacts on the urinary metabolome were markedly smaller than those in serum. While changes in urine metabolites incurred by sample handling are generally small, we recommend implementing consistent handling conditions and evaluating robustness of metabolite measurements for those showing significant associations with disease outcomes.

Fecal Metagenomics to Identify Biomarkers of Food Intake in Healthy Adults: Findings from Randomized, Controlled, Nutrition Trials.

BACKGROUND: Undigested components of the human diet affect the composition and function of the microorganisms present in the gastrointestinal tract. Techniques like metagenomic analyses allow researchers to study functional capacity, thus revealing the potential of using metagenomic data for developing objective biomarkers of food intake. OBJECTIVES: As a continuation of our previous work using 16S and metabolomic datasets, we aimed to utilize a computationally intensive, multivariate, machine-learning approach to identify fecal KEGG (Kyoto encyclopedia of genes and genomes) Orthology (KO) categories as biomarkers that accurately classify food intake. METHODS: Data were aggregated from 5 controlled feeding studies that studied the individual impact of almonds, avocados, broccoli, walnuts, barley, and oats on the adult gastrointestinal microbiota. Deoxyribonucleic acid from preintervention and postintervention fecal samples underwent shotgun genomic sequencing. After preprocessing, sequences were aligned and functionally annotated with Double Index AlignMent Of Next-generation sequencing Data v2.0.11.149 and MEtaGenome ANalyzer v6.12.2, respectively. After the count normalization, the log of the fold change ratio for resulting KOs between pre- and postintervention of the treatment group against its corresponding control was utilized to conduct differential abundance analysis. Differentially abundant KOs were used to train machine-learning models examining potential biomarkers in both single-food and multi-food models. RESULTS: We identified differentially abundant KOs in the almond (n = 54), broccoli (n = 2474), and walnut (n = 732) groups (q < 0.20), which demonstrated classification accuracies of 80%, 87%, and 86% for the almond, broccoli, and walnut groups using a random forest model to classify food intake into each food group's respective treatment and control arms, respectively. The mixed-food random forest achieved 81% accuracy. CONCLUSIONS: Our findings reveal promise in utilizing fecal metagenomics to objectively complement self-reported measures of food intake. Future research on various foods and dietary patterns will expand these exploratory analyses for eventual use in feeding study compliance and clinical settings.

Mixed Berry Juice and Cellulose Fiber Have Differential Effects on Peripheral Blood Mononuclear Cell Respiration in Overweight Adults.

Berries and other anthocyanin-rich foods have demonstrated anti-obesity effects in rodents and humans. However, the bioactive components of these foods and their mechanisms of action are unclear. We conducted an intervention study with overweight and obese adults to isolate the effects of different berry components on bioenergetics. Subjects consumed whole mixed berries (high anthocyanin, high fiber), pressed berry juice (high anthocyanin, low fiber), berry-flavored gelatin (low anthocyanin, low fiber), or fiber-enriched gelatin (low anthocyanin, high fiber) for one week prior to a meal challenge with the same treatment food as the pre-feed period. Peripheral blood mononuclear cells were collected 2 h after the meal challenge, and cellular respiration was assessed via high-resolution respirometry. The high-anthocyanin, low-fiber treatment (berry juice) and the low-anthocyanin, high-fiber treatment (fiber-enriched gelatin) had opposite effects on cellular respiration. In the fasted state, berry juice resulted in the highest oxygen-consumption rate (OCR), while fiber-enriched gelatin resulted in the highest OCR in the fed state. Differences were observed in multiple respiration states (basal, state 3, state 4, uncoupled), with the greatest differences being between the pressed berry juice and the fiber-enriched gelatin. Different components of berries, specifically anthocyanins/flavonoids and fiber, appear to have differential effects on cellular respiration.

Effect of Nuts on Gastrointestinal Health.

Nuts are high nutrient-dense foods containing healthy lipids, dietary fiber, and bioactive phytochemicals, including vitamins and minerals. Although the beneficial effect of nut consumption on different chronic diseases has been well documented, especially in relation to their cardiometabolic benefits, less scientific evidence is available on their possible beneficial effects on gastrointestinal health. In this narrative review, we summarize the most important findings and new research perspectives in relation to the importance of nut consumption on gastrointestinal health. The integrity of the cell wall structure, cell size and particle size after mastication are known to play a crucial role in energy, nutrient and bioactive release from nuts during digestion, therefore affecting bioaccessibility. Other mechanisms, such as cell wall composition, thickness and porosity, as well as stability of the membranes surrounding the oil bodies within the cell, are also important for energy extraction. As the undigested nutrients and phytochemicals are delivered to the colon, effects on gut microbiota composition are predicted. Although the overall effect of nut consumption on microbial alpha- and beta-diversity has been inconsistent, some scientific evidence suggests an increase in fecal butyrate after almond consumption, and a beneficial role of walnuts on the prevention of ulcerative colitis and protection against the development of gastric mucosal lesions.

Nuts, Energy Balance and Body Weight.

Over several decades, the health benefits of consuming nuts have been investigated, resulting in a large body of evidence that nuts can reduce the risk of chronic diseases. The consumption of nuts, being a higher-fat plant food, is restricted by some in order to minimize weight gain. In this review, we discuss several factors related to energy intake from nuts, including food matrix and its impact on digestibility, and the role of nuts in regulating appetite. We review the data from randomized controlled trials and observational studies conducted to examine the relationship between nut intake and body weight or body mass index. Consistently, the evidence from RCTs and observational cohorts indicates that higher nut consumption does not cause greater weight gain; rather, nuts may be beneficial for weight control and prevention of long-term weight gain. Multiple mechanisms likely contribute to these findings, including aspects of nut composition which affect nutrient and energy availability as well as satiety signaling.

Fecal Metabolites as Biomarkers for Predicting Food Intake by Healthy Adults.

BACKGROUND: The fecal metabolome is affected by diet and includes metabolites generated by human and microbial metabolism. Advances in -omics technologies and analytic approaches have allowed researchers to identify metabolites and better utilize large data sets to generate usable information. One promising aspect of these advancements is the ability to determine objective biomarkers of food intake. OBJECTIVES: We aimed to utilize a multivariate, machine learning approach to identify metabolite biomarkers that accurately predict food intake. METHODS: Data were aggregated from 5 controlled feeding studies in adults that tested the impact of specific foods (almonds, avocados, broccoli, walnuts, barley, and oats) on the gastrointestinal microbiota. Fecal samples underwent GC-MS metabolomic analysis; 344 metabolites were detected in preintervention samples, whereas 307 metabolites were detected postintervention. After removing metabolites that were only detected in either pre- or postintervention and those undetectable in ≥80% of samples in all study groups, changes in 96 metabolites relative concentrations (treatment postintervention minus preintervention) were utilized in random forest models to 1) examine the relation between food consumption and fecal metabolome changes and 2) rank the fecal metabolites by their predictive power (i.e., feature importance score). RESULTS: Using the change in relative concentration of 96 fecal metabolites, 6 single-food random forest models for almond, avocado, broccoli, walnuts, whole-grain barley, and whole-grain oats revealed prediction accuracies between 47% and 89%. When comparing foods with one another, almond intake was differentiated from walnut intake with 91% classification accuracy. CONCLUSIONS: Our findings reveal promise in utilizing fecal metabolites as objective complements to certain self-reported food intake estimates. Future research on other foods at different doses and dietary patterns is needed to identify biomarkers that can be applied in feeding study compliance and clinical settings.

Scoping Review and Evidence Map of the Relation between Exposure to Dietary Sweetness and Body Weight-Related Outcomes in Adults.

Numerous governmental and health organizations recommend reduced intake of added sugars due to the health risks associated with excess intake, including the risk of obesity. Some organizations further recommend avoiding dietary sweetness, regardless of the source. A scoping review and evidence map were completed to characterize the research that investigated associations between dietary sweetness and body weight. The aim was to identify and map published studies that have investigated total dietary sweetness, sweet food/beverages, sugar, or sweetener intake, and body weight-related outcomes and/or energy intake. Using preregistered search terms (osf.io/my7pb), 36,779 publications (duplicates removed) were identified from PubMed, Cochrane Library, and Scopus and screened for inclusion. Eligible studies were clinical trials, longitudinal cohorts, case-control studies, cross-sectional studies, and systematic reviews conducted among adults (age ≥18 y), which were performed to investigate associations between dietary sweetness, sweet foods/beverages, sugar, or sweetener (energetic or nonenergetic) intake and body weight, BMI, adiposity, and/or energy intake. A total of 833 eligible publications were identified, detailing 804 studies. Only 7 studies (0.9% of included studies; 2 clinical trials, 4 cross-sectional studies, and 1 with another design type) investigated associations between total dietary sweetness and body weight-related outcome and/or energy intake. An additional 608 (75.6%) studies investigated intakes of sweet foods/beverages, sugar, or sweetener, and body weight-related outcomes and/or energy intake, including 225 clinical trials, 81 longitudinal cohorts, 4 case-control studies, and 280 cross-sectional studies. Most studies (90.6%) did not measure the sweetness of the diet or individual foods consumed. Ninety-two (11.4%) publications reported data from studies on dietary patterns that included sweet foods/beverages alongside other dietary components and 97 (12.1%) systematic reviews addressed different but related research questions. Although there is a breadth of evidence from studies that have investigated associations between intakes of sweet foods and beverages, sugars, and sweeteners and body weight, there is a limited depth of evidence on the association between total dietary sweetness and body weight.

Intermittent calorie restriction alters T cell subsets and metabolic markers in people with multiple sclerosis.

BACKGROUND: Intermittent fasting or calorie restriction (CR) diets provide anti-inflammatory and neuroprotective advantages in models of multiple sclerosis (MS); data in humans are sparse. METHODS: We conducted a randomised-controlled feeding study of different CR diets in 36 people with MS over 8 weeks. Participants were randomised to 1 of 3 diets: 1) a control diet, in which the participant received 100% of his or her calorie needs 7 days per week, 2) a daily CR diet, in which the participant received 78% of his or her calorie needs 7 days per week, or 3) an intermittent CR diet, in which the participant received 100% of his or her calorie needs on 5 days per week and 25% of his or her calorie needs 2 days per week (i.e., a "5:2" style diet). Untargeted metabolomics was performed on plasma samples at weeks 0, 4 and 8 at Metabolon Inc (Durham, NC). Flow cytometry of cryopreserved peripheral blood mononuclear cells at weeks 0 and 8 were used to identify CD3+;CD4+ (CD4+) and CD3+;CD4- (as a proxy for CD8+) T cell subsets including effector memory, central memory, and naïve cells. FINDINGS: 31 (86%) completed the trial. Over time, individuals randomised to intermittent CR had significant reductions in effector memory (for CD4-EM: -3.82%; 95%CI: -7.44, -0.21; for CD4-: -6.96%; 95%CI: -11.96, -1.97) and Th1 subsets (-4.26%; 95% CI: -7.11, -1.40) and proportional increases in naïve subsets (for CD4-: 10.11%; 95%CI: 3.30, 16.92%). No changes were observed for daily CR or weight-stable diets. Larger within-person changes in lysophospholipid and lysoplasmalogen metabolites in intermittent CR were associated with larger reductions in memory T cell subsets and larger increases in naïve T cell subsets. INTERPRETATION: In people with MS, an intermittent CR diet was associated with reduction in memory T cell subsets and certain biologically-relevant lipid markers. FUNDING: National MS Society, NIH, Johns Hopkins Catalyst Award.

Measurement Error Affecting Web- and Paper-Based Dietary Assessment Instruments: Insights From the Multi-Cohort Eating and Activity Study for Understanding Reporting Error.

Few biomarker-based validation studies have examined error in online self-report dietary assessment instruments, and food records (FRs) have been considered less than food frequency questionnaires (FFQs) and 24-hour recalls (24HRs). We investigated measurement error in online and paper-based FFQs, online 24HRs, and paper-based FRs in 3 samples drawn primarily from 3 cohorts, comprising 1,393 women and 1,455 men aged 45-86 years. Data collection occurred from January 2011 to October 2013. Attenuation factors and correlation coefficients between reported and true usual intake for energy, protein, sodium, potassium, and respective densities were estimated using recovery biomarkers. Across studies, average attenuation factors for energy were 0.07, 0.07, and 0.19 for a single FFQ, 24HR, and FR, respectively. Correlation coefficients for energy were 0.24, 0.23, and 0.40, respectively. Excluding energy, the average attenuation factors across nutrients and studies were 0.22 for a single FFQ, 0.22 for a single 24HR, and 0.51 for a single FR. Corresponding correlation coefficients were 0.31, 0.34, and 0.53, respectively. For densities (nutrient expressed relative to energy), the average attenuation factors across studies were 0.37, 0.17, and 0.50, respectively. The findings support prior research suggesting different instruments have unique strengths that should be leveraged in epidemiologic research.

Targeting the Dietary Na:K Ratio-Considerations for Design of an Intervention Study to Impact Blood Pressure.

Despite medical, dietary, and lifestyle recommendations and drug advancements, hypertension persists as among the most prevalent noncommunicable diseases in the US population, and control remains elusive. Uncontrolled hypertension may increase the risk of serious illness from various other health challenges, including cardiovascular and renal responses. Adoption of a healthy diet is a consistent core element of lifestyle modifications that are recommended for mitigation of hypertension. The dietary sodium-to-potassium ratio is recognized as having promising potential in the regulation of blood pressure. In fact, the understanding of the relation between this ratio and blood pressure was documented as a key evidence gap in the 2019 National Academies of Sciences, Engineering, and Medicine report that revised recommended intake levels for both sodium and potassium. Although notable animal and human evidence supports this point, fundamental to developing a specific dietary recommendation for a sodium-to-potassium ratio is a well-designed human intervention trial. The successful translatability of such a trial will require careful consideration of study elements, including the study population, duration, blood pressure measurement, and dietary intervention, among other factors. This paper addresses these decision points and serves as supporting documentation for a research group or organization with the interest and means to address this important data gap, which will undoubtedly be foundational for advancing dietary guidance and would inform the next iteration of Dietary Reference Intakes for sodium and potassium.

Effect of varying quantities of lean beef as part of a Mediterranean-style dietary pattern on lipids and lipoproteins: a randomized crossover controlled feeding trial.

BACKGROUND: It remains unclear whether red meat consumption is causatively associated with cardiovascular disease (CVD) risk, and few randomized controlled studies have examined the effect of incorporating lean beef into a healthy dietary pattern. OBJECTIVES: To evaluate the effects of a Mediterranean (MED) diet (carbohydrate 42%, protein 17%, fat 41%, SFAs 8%, MUFAs 26%, PUFAs 8%) with 14 (MED0.5; 0.5 oz), 71 (MED2.5; 2.5 oz), and 156 (MED5.5; 5.5 oz) g/d/2000 kcal lean beef compared with an average American diet (AAD; carbohydrate 52%, protein 15%, fat 33%, SFAs 12%, MUFAs 13%, PUFAs 8%) on lipid and lipoprotein concentrations, particle number, and size. METHODS: This was a multicenter, 4-period controlled feeding, randomized crossover study. Fifty-nine generally healthy males and females (BMI 20-38 kg/m2; age 30-65 y) consumed each diet for 4 wk with a ≥1-wk washout between the diets. Fasting blood samples were collected at baseline and at the end of each 4-wk period. Lipid subfractions were measured by NMR. RESULTS: Compared with the AAD, all 3 MED diets decreased LDL cholesterol (MED0.5: -10.3 mg/dL; 95% CI: -5.4, -15.7 mg/dL; MED2.5: -9.1 mg/dL; 95% CI: -3.9, -14.3 mg/dL; MED5.5: -6.9 mg/dL; 95% CI: -1.7, -12.1 mg/dL; P < 0.0001). All MED diets elicited similar reductions in total LDL particle number compared with baseline (P < 0.005); however, significant decreases only occurred with MED0.5 (-91.2 nmol/L; 95% CI: -31.4, -151.0 nmol/L) and MED2.5 (-85.3 nmol/L; 95% CI: -25.4, -145.2 nmol/L) compared with AAD (P < 0.003). Compared with the AAD, non-HDL cholesterol (P < 0.01) and apoB (P < 0.01) were lower following the 3 MED diets; there were no differences between the MED diets. All diets reduced HDL-cholesterol and HDL particle number from baseline (P < 0.01). CONCLUSIONS: Lipid and lipoprotein lowering was not attenuated with the inclusion of lean beef in amounts ≤71 g (2.5 oz)/d as part of a healthy low-saturated-fat Mediterranean-style diet.This study is registered at clinicaltrials.gov as NCT02723617.

Common Genetic Variations Involved in the Inter-Individual Variability of Circulating Cholesterol Concentrations in Response to Diets: A Narrative Review of Recent Evidence.

The number of nutrigenetic studies dedicated to the identification of single nucleotide polymorphisms (SNPs) modulating blood lipid profiles in response to dietary interventions has increased considerably over the last decade. However, the robustness of the evidence-based science supporting the area remains to be evaluated. The objective of this review was to present recent findings concerning the effects of interactions between SNPs in genes involved in cholesterol metabolism and transport, and dietary intakes or interventions on circulating cholesterol concentrations, which are causally involved in cardiovascular diseases and established biomarkers of cardiovascular health. We identified recent studies (2014-2020) that reported significant SNP-diet interactions in 14 cholesterol-related genes (NPC1L1, ABCA1, ABCG5, ABCG8, APOA1, APOA2, APOA5, APOB, APOE, CETP, CYP7A1, DHCR7, LPL, and LIPC), and which replicated associations observed in previous studies. Some studies have also shown that combinations of SNPs could explain a higher proportion of variability in response to dietary interventions. Although some findings still need replication, including in larger and more diverse study populations, there is good evidence that some SNPs are consistently associated with differing circulating cholesterol concentrations in response to dietary interventions. These results could help clinicians provide patients with more personalized dietary recommendations, in order to lower their risk for cardiovascular disease.

Consumption of High-Oleic Soybean Oil Improves Lipid and Lipoprotein Profile in Humans Compared to a Palm Oil Blend: A Randomized Controlled Trial.

Partially hydrogenated oils (PHO) have been removed from the food supply due to adverse effects on risk for coronary heart disease (CHD). High-oleic soybean oils (HOSBO) are alternatives that provide functionality for different food applications. The objective of this study was to determine how consumption of diets containing HOSBO compared to other alternative oils, with similar functional properties, modifies LDL cholesterol (LDLc) and other risk factors and biomarkers of CHD. A triple-blind, crossover, randomized controlled trial was conducted in humans (n = 60) with four highly-controlled diets containing (1) HOSBO, (2) 80:20 blend of HOSBO and fully hydrogenated soybean oil (HOSBO+FHSBO), (3) soybean oil (SBO), and (4) 50:50 blend of palm oil and palm kernel oil (PO + PKO). Before and after 29 days of feeding, lipids/lipoproteins, blood pressure, body composition, and markers of inflammation, oxidation, and hemostasis were measured. LDLc, apolipoprotein B (apoB), NonHDL-cholesterol (HDLc), ratios of total cholesterol (TC)-to-HDLc and LDLc-to-HDL cholesterol, and LDL particle number and small LDL particles concentration were lower after HOSBO and HOSBO+FHSBO compared to PO (specific comparisons p < 0.05). Other than TC:HDL, there were no differences in lipid/lipoprotein markers when comparing HOSBO+FHSBO with HOSBO. LDLc and apoB were higher after HOSBO compared to SBO (p < 0.05). PO + PKO increased HDLc (p < 0.001) and apolipoprotein AI (p < 0.03) compared to HOSBO and HOSBO+FHSBO. With the exception of lipid hydroperoxides, dietary treatments did not affect other CHD markers. HOSBO, and blends thereof, is a PHO replacement that results in more favorable lipid/lipoprotein profiles compared to PO + PKO (an alternative fat with similar functional properties).

Perspective: Design and Conduct of Human Nutrition Randomized Controlled Trials.

In the field of human nutrition, randomized controlled trials (RCTs) are considered the gold standard for establishing causal relations between exposure to nutrients, foods, or dietary patterns and prespecified outcome measures, such as body composition, biomarkers, or event rates. Evidence-based dietary guidance is frequently derived from systematic reviews and meta-analyses of these RCTs. Each decision made during the design and conduct of human nutrition RCTs will affect the utility and generalizability of the study results. Within the context of limited resources, the goal is to maximize the generalizability of the findings while producing the highest quality data and maintaining the highest levels of ethics and scientific integrity. The aim of this document is to discuss critical aspects of conducting human nutrition RCTs, including considerations for study design (parallel, crossover, factorial, cluster), institutional ethics approval (institutional review boards), recruitment and screening, intervention implementation, adherence and retention assessment, and statistical analyses considerations. Additional topics include distinguishing between efficacy and effectiveness, defining the research question(s), monitoring biomarker and outcome measures, and collecting and archiving data. Addressed are specific aspects of planning and conducting human nutrition RCTs, including types of interventions, inclusion/exclusion criteria, participant burden, randomization and blinding, trial initiation and monitoring, and the analysis plan.

Preanalytical Sample Handling Conditions and Their Effects on the Human Serum Metabolome in Epidemiologic Studies.

Many epidemiologic studies use metabolomics for discovery-based research. The degree to which sample handling may influence findings, however, is poorly understood. In 2016, serum samples from 13 volunteers from the US Department of Agriculture's Beltsville Human Nutrition Research Center were subjected to different clotting (30 minutes/120 minutes) and refrigeration (0 minutes/24 hours) conditions, as well as different numbers (0/1/4) and temperatures (ice/refrigerator/room temperature) of thaws. The median absolute percent difference (APD) between metabolite levels and correlations between levels across conditions were estimated for 628 metabolites. The potential for handling artifacts to induce false-positive associations was estimated using variable hypothetical scenarios in which 1%-100% of case samples had different handling than control samples. All handling conditions influenced metabolite levels. Across metabolites, the median APD when extending clotting time was 9.08%. When increasing the number of thaws from 0 to 4, the median APD was 10.05% for ice and 5.54% for room temperature. Metabolite levels were correlated highly across conditions (all r's ≥ 0.84), indicating that relative ranks were preserved. However, if handling varied even modestly by case status, our hypotheticals showed that results can be biased and can result in false-positive findings. Sample handling affects levels of metabolites, and special care should be taken to minimize effects. Shorter room-temperature thaws should be preferred over longer ice thaws, and handling should be meticulously matched by case status.

Perspective: Measuring Sweetness in Foods, Beverages, and Diets: Toward Understanding the Role of Sweetness in Health.

Various global public health agencies recommend minimizing exposure to sweet-tasting foods or beverages. The underlying rationale is that reducing exposure to the perception of sweet tastes, without regard to the source of sweetness, may reduce preferences for sweetness, added sugar intake, caloric intake, and body weight. However, the veracity of this sequence of outcomes has yet to be documented, as revealed by findings from recent systematic reviews on the topic. Efforts to examine and document the effects of sweetness exposure are needed to support evidence-based recommendations. They require a generally agreed-upon methodology for measuring sweetness in foods, beverages, and the overall diet. Although well-established sensory evaluation techniques exist for individual foods in laboratory settings, they are expensive and time-consuming, and agreement on the optimal approach for measuring the sweetness of the total diet is lacking. If such a measure could be developed, it would permit researchers to combine data from different studies and populations and facilitate the design and conduct of new studies to address unresolved research questions about dietary sweetness. This narrative review includes an overview of available sensory techniques, their strengths and limitations, recent efforts to measure the sweetness of foods and diets across countries and cultures, and a proposed future direction for improving methods for measuring sweetness toward developing the data required to support evidence-based recommendations around dietary sweetness.

Fecal Bacteria as Biomarkers for Predicting Food Intake in Healthy Adults.

BACKGROUND: Diet affects the human gastrointestinal microbiota. Blood and urine samples have been used to determine nutritional biomarkers. However, there is a dearth of knowledge on the utility of fecal biomarkers, including microbes, as biomarkers of food intake. OBJECTIVES: This study aimed to identify a compact set of fecal microbial biomarkers of food intake with high predictive accuracy. METHODS: Data were aggregated from 5 controlled feeding studies in metabolically healthy adults (n = 285; 21-75 y; BMI 19-59 kg/m2; 340 data observations) that studied the impact of specific foods (almonds, avocados, broccoli, walnuts, and whole-grain barley and whole-grain oats) on the human gastrointestinal microbiota. Fecal DNA was sequenced using 16S ribosomal RNA gene sequencing. Marginal screening was performed on all species-level taxa to examine the differences between the 6 foods and their respective controls. The top 20 species were selected and pooled together to predict study food consumption using a random forest model and out-of-bag estimation. The number of taxa was further decreased based on variable importance scores to determine the most compact, yet accurate feature set. RESULTS: Using the change in relative abundance of the 22 taxa remaining after feature selection, the overall model classification accuracy of all 6 foods was 70%. Collapsing barley and oats into 1 grains category increased the model accuracy to 77% with 23 unique taxa. Overall model accuracy was 85% using 15 unique taxa when classifying almonds (76% accurate), avocados (88% accurate), walnuts (72% accurate), and whole grains (96% accurate). Additional statistical validation was conducted to confirm that the model was predictive of specific food intake and not the studies themselves. CONCLUSIONS: Food consumption by healthy adults can be predicted using fecal bacteria as biomarkers. The fecal microbiota may provide useful fidelity measures to ascertain nutrition study compliance.

Performance and Feasibility of Recalls Completed Using the Automated Self-Administered 24-Hour Dietary Assessment Tool in Relation to Other Self-Report Tools and Biomarkers in the Interactive Diet and Activity Tracking in AARP (IDATA) Study.

BACKGROUND: Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) is a self-administered web-based tool designed to collect detailed dietary data at low cost in observational studies. OBJECTIVE: The objectives of this study were to describe, overall and by demographic groups, the performance and feasibility of ASA24-2011 recalls and compare Healthy Eating Index-2015 (HEI-2015) total and component scores to 4-day food records (4DFRs) and food frequency questionnaires (FFQs). DESIGN: Over 12 months, participants completed up to 6 ASA24 recalls, 2 web-based FFQs, and 2 unweighed paper-and-pencil 4DFRs. Up to 3 attempts were made to obtain each ASA24 recall. Participants were administered doubly-labeled water to provide a measure of total energy expenditure and collected two 24-hour urine samples to assess concentrations of nitrogen, sodium, and potassium. PARTICIPANTS/SETTING: From January through September 2012, 1,110 adult members of AARP, 50 to 74 years of age, were recruited from the Pittsburgh, PA, area to participate in the Interactive Diet and Activity Tracking in AARP (IDATA) study. After excluding 33 participants who had not completed any dietary assessments, 531 men and 546 women remained. MAIN OUTCOME MEASURES: Response rates, nutrient intakes compared to recovery biomarkers across each ASA24 administration day, and HEI-2015 total and component scores were measured. STATISTICAL ANALYSES PERFORMED: Means, medians, standard deviations, interquartile ranges, and HEI-2015 total and component scores computed using a multivariate measurement error model are presented. RESULTS: Ninety-one percent of men and 86% of women completed 3 ASA24 recalls. Approximately three-quarters completed 5 or more, higher than the completion rates for 2 4DFRs and 2 FFQs. Approximately, three-quarters of men and 70% of women completed ASA24 on the first attempt; 1 in 5 completed it on the second. Completion rates varied slightly by age and body mass index. Median time to complete ASA24-2011 (current version: ASA24-2020) declined with subsequent recalls from 55 to 41 minutes in men and from 58 to 42 minutes in women and was lowest in those younger than 60 years. Mean nutrient intakes were similar across recalls. For each recording day, energy intakes estimated by ASA24 were lower than energy expenditure. Reported intakes for protein, potassium, and sodium were closer to recovery biomarkers for women, but not for men. Geometric means of reported intakes of these nutrients did not systematically vary across ASA24 administrations, but differences between reported intakes and biomarkers differed by nutrient. Of 100 possible points, HEI-2015 total scores were nearly identical for 4DFRs and ASA24 recalls and higher for FFQs (men: 61, 60, and 68; women: 64, 64, and 72, respectively). CONCLUSIONS: ASA24, a freely available dietary assessment tool for use in large-scale nutrition research, was found to be highly feasible. Similar to previously reported data for nutrient intakes, HEI-2015 total and component scores for ASA24 recalls were comparable to those for 4DFRs, but not FFQs. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03268577 (http://www.clinicaltrials.gov).

Conducting dietary intervention trials in people with multiple sclerosis: Lessons learned and a path forward.

Disease course in people with multiple sclerosis (MS) is heterogeneous. The impact of dietary and nutritional factors on MS prognosis is of interest to both patients and clinicians; differences in diet are hypothesized to contribute to disease evolution over time. However, studying diet, especially in people with MS, introduces methodologic complexity that should be recognized. In this review, we focus on methodological aspects relevant to the conduct of dietary interventions in people with MS, given our experience in leading such studies and the challenges we encountered in the realization of this work. We summarize key aspects of study design and important considerations, regardless of the specifics of the actual study (e.g. the particular diet of interest, target MS population, etc.). We discuss strategies for the design of the intervention as well as the selection of appropriate study endpoints. Finally, we provide an overview of strategies to improve the rigor of conducting dietary studies in people with MS.

An Anthocyanin-Rich Mixed-Berry Intervention May Improve Insulin Sensitivity in a Randomized Trial of Overweight and Obese Adults.

Evidence supports the beneficial effects of berries on glucoregulation, possibly related to flavonoid content, fiber content, or both. The purpose of this study was to assess the potential of mixed berries to improve insulin sensitivity and to identify the potential role of flavonoids and fiber. In a randomized cross-over trial with four treatment periods, overweight/obese men and women were fed a controlled 45% fat diet for one week prior to a meal-based glucose tolerance test. The same base diet was provided during each feeding period with the addition of one of four treatments: whole mixed berries, sugar matched mixed berry juice, sugar matched gelatin, and sugar/fiber matched gelatin. Subjects then completed a meal-based oral glucose tolerance test. Serum glucose, insulin and non-esterified fatty acids were not different between individual treatments. However, in a secondary analysis, the combined berry preparations resulted in a lower serum insulin area under the curve (difference of 0.15 ± 0.066 ln pmol min/mL, mean ± SE, p = 0.0228), compared to the combined gelatin treatments, while the difference for serum glucose did not quite meet statistical significance (difference of 0.17 ± 0.093 ln mg·min/dL, mean ± SE, p = 0.0738). These results suggest the potential for mixed berry preparations to improve post-prandial insulin response.