scholarly journals Fecal Bacteria as Biomarkers for Predicting Food Intake in Healthy Adults

2020 ◽  
Author(s):  
Leila M Shinn ◽  
Yutong Li ◽  
Aditya Mansharamani ◽  
Loretta S Auvil ◽  
Michael E Welge ◽  
...  
Keyword(s):  
Food Intake ◽  
Food Consumption ◽  
Healthy Adults ◽  
Compact Set ◽  
Fecal Bacteria ◽  
Whole Grain ◽  
Gastrointestinal Microbiota ◽  
Model Accuracy ◽  
Microbial Biomarkers ◽  
The Impact

ABSTRACT 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.

scholarly journals Effects of Protein Source and Quantity on Appetite Control, Satiety and Subsequent Food Intake in Healthy Adults

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 409-409
Author(s):  
Charlotte Griffith ◽  
Kamille Piacquadio ◽  
Morgan Braden ◽  
Heather Leidy
Keyword(s):  
Food Intake ◽  
Energy Intake ◽  
Food Consumption ◽  
Repeated Measures ◽  
Healthy Adults ◽  
Protein Source ◽  
Pea Protein ◽  
Desire To Eat ◽  
Main Effects ◽  
Eating Initiation

Abstract Objectives To examine whether consumption of breakfast preloads varying in protein source and quantity affect measures of appetite, satiety and subsequent energy intake in healthy adults. Methods Thirty-seven healthy adults (Age: 26 ± 4; BMI: 23 ± 2) participated in this randomized crossover design study. On 3 consecutive days, participants consumed 325 kcal preload breakfast yogurts, varying in protein quality (Whey vs. Pea) and quantity (20, 30, 40 g) vs. an isocaloric carbohydrate preload (Control). On day 4, participants completed a 5-hr in clinic testing day. At baseline time -15 min, questionnaires assessing hunger, fullness, desire to eat, prospective food consumption, and eating initiation, were completed. At time 0 min, the respective preload was provided, and palatability assessed. At time 15 min, after consumption, similar questionnaires were completed every 30 min during the 4-h postprandial period followed by an ad libitum pizza lunch. There was a 3–7 day washout period between testing days. To assess main effects of protein source, paired sample t-tests of incremental area under the curve (iAUC) were computed for 20g Pea vs. 20g Whey preloads on 4-h hunger, fullness, desire to eat, prospective food consumption, eating initiation and lunch energy intake. To assess main effects of protein quantity, repeated measures ANOVA was computed between control and pea protein preloads of 20g, 30g, and 40g on 4-h hunger, fullness, desire to eat, and prospective food consumption niAUC, eating initiation, and lunch energy intake. P < 0.05 was considered statistically significant. Statistical analyses were performed using The R Foundation (R; version 4.0.3). Results No main effects of protein source or quantities were detected for 4-h postprandial hunger, fullness, desire to eat, and prospective food consumption niAUC. On average, participants requested to eat again 2-h after breakfast (134 ± 12 min) and consumed on average 830 ± 10 kcals at lunch with no differences between protein sources or quantities. Conclusions In the context of an acute feeding study, no differences in postprandial appetite, satiety, and subsequent food intake were detected when comparing protein preloads varying in source and quantity. These data suggest that 20 g pea protein is sufficient to elicit satiety effects and can be used as a plant-based alternative for whey protein. Funding Sources Roquette.

scholarly journals Comparison of Knowledge and Behavior of High-Iodine Food Consumption Among Patients With Graves’ Disease and Healthy Adults in Iodine-Sufficient Area

2021 ◽  
Vol 44 (2) ◽  
pp. 1-10
Author(s):  
Juthathip Posuwan ◽  
Yuvadee Rodjarkpai ◽  
Pajaree Abdullakasim ◽  
Sathapakorn Siriwong ◽  
Teeradej Aticharoenkul ◽  
...  
Keyword(s):  
Food Consumption ◽  
Fermented Food ◽  
Healthy Adults ◽  
Control Group ◽  
Graves Disease ◽  
High Iodine ◽  
Chi Square ◽  
Chi Square Test ◽  
The Impact ◽  
Healthy Participants

Background: Iodine is a required dietary supplement to solve iodine deficiencies; however, many food products may now have an excessive amount of iodine. This excess may be causing unexpected iodine-induced Graves’ disease. Objective: To investigate the impact of high-iodine diets on adults diagnosed with Graves’ disease and healthy adults. Methods: A case-control study was performed among 200 patients with Graves’ disease and 200 healthy participants in Chon Buri, Thailand, using cluster random sampling from November 2019 to March 2020. Data on iodine-rich food consumption were collected using a questionnaire. Data were analyzed using a chi-square test and multiple logistic regression. Results: Patients with Graves’ disease significantly less knew of high-iodine food than the control group (P < .05), particularly in eggs, processed foods, ready-to-eat food, cod liver oil, and high-iodine vegetables. A frequent consumption of high-iodine food items, including fermented food (OR, 2.20; 95% CI, 1.20 - 4.02), ready-to-eat food (OR, 2.08; 95% CI, 1.02 - 4.22), high-iodine vegetables (OR, 1.72; 95% CI, 1.13 - 2.61), bakery (OR, 1.99; 95% CI, 1.10 - 3.64), iodine-supplemented sauces (OR, 1.79; 95% CI, 1.18 - 2.72), and iodized salts (OR, 1.62; 95% CI, 1.02 - 2.56) was higher in Graves’ disease patients. Conclusions: In iodine sufficiency area, patients with Graves’ disease less knew and more frequently consumed high-iodine foods than healthy participants.  

scholarly journals An Intervention With Michigan-Grown Wheat in Healthy Adult Humans to Determine Effect on Gut Microbiota: Protocol for a Crossover Trial (Preprint)

2021 ◽  
Author(s):  
Gigi A Kinney ◽  
Eliot N Haddad ◽  
Linda S Garrow ◽  
Perry K W Ng ◽  
Sarah S Comstock
Keyword(s):  
Gut Microbiota ◽  
Wheat Flour ◽  
Intestinal Inflammation ◽  
Production Capacity ◽  
Whole Grain ◽  
Gastrointestinal Microbiota ◽  
White Wheat ◽  
Whole Wheat ◽  
The Impact ◽  
Butyrate Production

BACKGROUND Daily fiber intake can increase the diversity of the human gut microbiota as well as the abundance of beneficial microbes and their metabolites. Whole-grain wheat is high in fiber. OBJECTIVE This manuscript presents a study protocol designed to understand the effects of different types of wheat on gastrointestinal tract microbes. METHODS Human adults will consume crackers made from three types of wheat flour (refined soft white wheat, whole-grain soft white wheat, and whole-grain soft red wheat). In this study, participants will alternate between crackers made from refined soft white wheat flour to those made from whole-grain soft white wheat and whole-grain soft red wheat flour. Survey and stool sample collection will occur after 7-day treatment periods. We will assess how wheat consumption affects gastrointestinal bacteria by sequencing the V4 region of 16S rRNA gene amplicons and the inflammatory state of participants’ intestines using enzyme-linked immunosorbent assays. The butyrate production capacity of the gut microbiota will be determined by targeted quantitative real-time polymerase chain reaction. RESULTS We will report the treatment effects on alpha and beta diversity of the microbiota and taxa-specific differences. Microbiota results will be analyzed using the vegan package in R. Butyrate production capacity and biomarkers of intestinal inflammation will be analyzed using parametric statistical methods such as analysis of variance or linear regression. We expect whole wheat intake to increase butyrate production capacity, bacterial alpha diversity, and abundance of bacterial taxa responsive to phenolic compounds. Soft red wheat is also expected to decrease the concentration of inflammatory biomarkers in the stool of participants. CONCLUSIONS This protocol describes the methods to be used in a study on the impact of wheat types on the human gastrointestinal microbiota and biomarkers of intestinal inflammation. The analysis of intestinal responses to the consumption of two types of whole wheat will expand our understanding of how specific foods affect health-associated outcomes. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/29046

scholarly journals An Intervention With Michigan-Grown Wheat in Healthy Adult Humans to Determine Effect on Gut Microbiota: Protocol for a Crossover Trial

10.2196/29046 ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. e29046
Author(s):  
Gigi A Kinney ◽  
Eliot N Haddad ◽  
Linda S Garrow ◽  
Perry K W Ng ◽  
Sarah S Comstock
Keyword(s):  
Gut Microbiota ◽  
Wheat Flour ◽  
Intestinal Inflammation ◽  
Production Capacity ◽  
Whole Grain ◽  
Gastrointestinal Microbiota ◽  
White Wheat ◽  
Whole Wheat ◽  
The Impact ◽  
Butyrate Production

Background Daily fiber intake can increase the diversity of the human gut microbiota as well as the abundance of beneficial microbes and their metabolites. Whole-grain wheat is high in fiber. Objective This manuscript presents a study protocol designed to understand the effects of different types of wheat on gastrointestinal tract microbes. Methods Human adults will consume crackers made from three types of wheat flour (refined soft white wheat, whole-grain soft white wheat, and whole-grain soft red wheat). In this study, participants will alternate between crackers made from refined soft white wheat flour to those made from whole-grain soft white wheat and whole-grain soft red wheat flour. Survey and stool sample collection will occur after 7-day treatment periods. We will assess how wheat consumption affects gastrointestinal bacteria by sequencing the V4 region of 16S rRNA gene amplicons and the inflammatory state of participants’ intestines using enzyme-linked immunosorbent assays. The butyrate production capacity of the gut microbiota will be determined by targeted quantitative real-time polymerase chain reaction. Results We will report the treatment effects on alpha and beta diversity of the microbiota and taxa-specific differences. Microbiota results will be analyzed using the vegan package in R. Butyrate production capacity and biomarkers of intestinal inflammation will be analyzed using parametric statistical methods such as analysis of variance or linear regression. We expect whole wheat intake to increase butyrate production capacity, bacterial alpha diversity, and abundance of bacterial taxa responsive to phenolic compounds. Soft red wheat is also expected to decrease the concentration of inflammatory biomarkers in the stool of participants. Conclusions This protocol describes the methods to be used in a study on the impact of wheat types on the human gastrointestinal microbiota and biomarkers of intestinal inflammation. The analysis of intestinal responses to the consumption of two types of whole wheat will expand our understanding of how specific foods affect health-associated outcomes. International Registered Report Identifier (IRRID) DERR1-10.2196/29046

scholarly journals Effects of Whole Grain, Compared to Refined Grain, Intake on Subjective Measures of Appetite: A Systematic Review and Meta-Analysis

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 657-657
Author(s):  
Lisa Sanders ◽  
Yong Zhu ◽  
Meredith Wilcox ◽  
Orsolya Palacios ◽  
Katie Koecher ◽  
...  
Keyword(s):  
Systematic Review ◽  
Weight Gain ◽  
Food Intake ◽  
Meta Analysis ◽  
Sensitivity Analyses ◽  
Whole Grain ◽  
Subjective Measures ◽  
Meta Analyses ◽  
The Impact ◽  
Grain Foods

Abstract Objectives Results from observational studies indicate that whole grain intake is inversely associated with BMI and risk of weight gain.  Whole grain intake may influence energy balance and body composition through effects on appetite and thus, energy intake.  To evaluate the impact of whole grain food consumption on appetite, we performed a systematic review and meta-analysis of randomized controlled trials (RCTs) assessing whole grain food intake and subjective measures of appetite in adults. Methods A search of PubMed, Scopus and Food Science and Technology abstracts yielded 34 RCTs measuring hunger ratings after consuming whole grain foods compared to refined grain controls.  Seventeen of these studies (598 subjects), with a total of 33 unique whole grain treatments, reported areas under the curve (AUC) for subjective hunger and were included in the meta-analysis.  Pooled estimates from meta-analyses are expressed as standardized mean differences (SMD). Results Intake of whole grain foods resulted in significantly lower subjective hunger AUC (range for AUC times ranged from 120 to 270 min) compared to refined grain foods [SMD −0.36, P &lt; 0.001, 95% CI (−0.48, −0.24)]. Sensitivity analyses were also completed in which studies with AUC values for &lt; and ≥ 180 min were evaluated separately, as well as hunger ratings at the 180 min timepoint alone, and the results were similar to those for the main analysis (SMDs −0.33 to −0.54, all P ≤ 0.03). Conclusions These results support the view that consumption of whole grain foods, compared to refined grain controls, significantly reduces subjective hunger, and this may provide at least part of the explanation for the inverse associations between whole grain food intake and risks for overweight, obesity and weight gain over time. Funding Sources This study was funded by the Bell Institute of Health and Nutrition, General Mills, Minneapolis, MN and registered with PROSPERO.

043 Sleep Restriction Affects Memory in Healthy Adults: Preliminary Findings

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A18-A19
Author(s):  
Molly Zimmerman ◽  
Christiane Hale ◽  
Adam Brickman ◽  
Lok-Kin Yeung ◽  
Justin Cochran ◽  
...  
Keyword(s):  
Working Memory ◽  
Negative Impact ◽  
Positive Impact ◽  
Healthy Adults ◽  
Task Demands ◽  
Sleep Restriction ◽  
Neuropsychological Function ◽  
Wake Time ◽  
Sleep Condition ◽  
The Impact

Abstract Introduction Sleep loss has a range of detrimental effects on cognitive ability. However, few studies have examined the impact of sleep restriction on neuropsychological function using an experimental design. The goal of this study was to examine the extent to which maintained insufficient sleep affects cognition in healthy adults compared to habitual adequate sleep. Methods This study used a randomized, crossover, outpatient sleep restriction design. Adults who regularly slept at least 7 h/night, verified by 2 weeks of screening with actigraphy, completed 2 phases of 6 weeks each: habitual sleep (&gt;7 h of sleep/night) or sleep restriction (habitual sleep minus 1.5 h) separated by a 6-week washout period. During the sleep restriction phase, participants were asked to delay their bedtime by 1.5 hours/night while maintaining their habitual wake time. Neuropsychological function was evaluated with the NIH Toolbox Cognition Battery at baseline (week 0) and endpoint (week 6) of each intervention phase. The NIH Toolbox evaluates a range of cognitive abilities, including attention, executive functioning, and working memory. General linear models with post hoc paired t-tests were used to assess demographically-adjusted test scores prior to and following each sleep condition. Results At the time of analyses, 16 participants were enrolled (age 34.5□14.5 years, 9 women), 10 of whom had completed study procedures. An interaction between sleep condition and testing session revealed that individuals performed worse on List Sorting, a working memory test, after sleep restriction but improved slightly after habitual sleep (p&lt;0.001). While not statistically reliable, the pattern of test results was similar on the other tests of processing speed, executive function, and attention. Conclusion In these preliminary results from this randomized experimental study, we demonstrated that sleep restriction has a negative impact while stable habitual adequate sleep has a positive impact on working memory, or the ability to temporarily hold information in mind while executing task demands. This finding contributes to our understanding of the complex interplay between different aspects of sleep quality (i.e., both sleep restriction as well as the maintenance of stable sleep patterns) on cognition and underscores the importance of routine sleep screening as part of medical evaluations. Support (if any):

scholarly journals Effect of ultraprocessed food intake on cardiometabolic risk is mediated by diet quality: a cross-sectional study

2021 ◽  
pp. bmjnph-2020-000225
Author(s):  
Jennifer Griffin ◽  
Anwar Albaloul ◽  
Alexandra Kopytek ◽  
Paul Elliott ◽  
Gary Frost
Keyword(s):  
Food Intake ◽  
Energy Intake ◽  
Food Consumption ◽  
Outcome Measures ◽  
Diet Quality ◽  
Cardiometabolic Risk ◽  
Saturated Fat ◽  
Secondary Outcome ◽  
Cross Sectional ◽  
Occupational Cohort

ObjectiveTo examine the effect of the consumption of ultraprocessed food on diet quality, and cardiometabolic risk (CMR) in an occupational cohort.DesignCross-sectional.SettingOccupational cohort.Participants53 163 British police force employees enrolled (2004–2012) into the Airwave Health Monitoring Study. A total of 28 forces across the UK agreed to participate. 9009 participants with available 7-day diet record data and complete co-variate data are reported in this study.Main outcome measuresA CMR and Dietary Approaches to Stop Hypertension score were treated as continuous variables and used to generate measures of cardiometabolic health and diet quality. Secondary outcome measures include percentage of energy from fat, saturated fat, carbohydrate, protein and non-milk extrinsic sugars (NMES) and fibre grams per 1000 kcal of energy intake.ResultsIn this cohort, 58.3%±11.6 of total energy intake was derived from ultraprocessed (NOVA 4) foods. Ultraprocessed food intake was negatively correlated with diet quality (r=−0.32, p<0.001), fibre (r=−0.20, p<0.001) and protein (r = −0.40, p<0.001) and positively correlated with fat (r=0.18, p<0.001), saturated fat (r=0.14, p<0.001) and nmes (r=0.10, p<0.001) intake . Multivariable analysis suggests a positive association between ultraprocessed food (NOVA 4) consumption and CMR. However, this main effect was no longer observed after adjustment for diet quality (p=0.209). Findings from mediation analysis indicate that the effect of ultraprocessed food (NOVA 4) intake on CMR is mediated by diet quality (p<0.001).ConclusionsUltraprocessed food consumption is associated with a deterioration in diet quality and positively associated with CMR, although this association is mediated by and dependent on the quality of the diet. The negative impact of ultraprocessed food consumption on diet quality needs to be addressed and controlled studies are needed to fully comprehend whether the relationship between ultraprocessed food consumption and health is independent to its relationship with poor diet quality.

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