2023
Measuring diet by metabolomics: a 14-d controlled feeding study of weighed food intake
Playdon M, Tinker L, Prentice R, Loftfield E, Hayden K, Van Horn L, Sampson J, Stolzenberg-Solomon R, Lampe J, Neuhouser M, Moore S. Measuring diet by metabolomics: a 14-d controlled feeding study of weighed food intake. American Journal Of Clinical Nutrition 2023, 119: 511-526. PMID: 38212160, PMCID: PMC10884612, DOI: 10.1016/j.ajcnut.2023.10.016.Peer-Reviewed Original ResearchConceptsWomen's Health InitiativeControlled feeding studyFood intakeAssociated with dietary intakeHabitually consumed foodsPotential of metabolomicsFasting serum samplesHealthy postmenopausal femalesHuman food intakeTandem mass spectrometryWeighed intakesEnd-of-studyLiquid chromatography tandem mass spectrometryHealth initiativesBeverage intakePostmenopausal femalesMetabolomics studiesDietary assessmentPartial Pearson correlationsHabitual dietMetabolite correlationsWeighing foodDietary intakeFood groupsMetabolomics
2017
Effects of dietary sodium on metabolites: the Dietary Approaches to Stop Hypertension (DASH)–Sodium Feeding Study
Derkach A, Sampson J, Joseph J, Playdon MC, Stolzenberg-Solomon RZ. Effects of dietary sodium on metabolites: the Dietary Approaches to Stop Hypertension (DASH)–Sodium Feeding Study. American Journal Of Clinical Nutrition 2017, 106: 1131-1141. PMID: 28855223, PMCID: PMC5611778, DOI: 10.3945/ajcn.116.150136.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAmino AcidsBlood PressureCross-Over StudiesDietDiet, Carbohydrate-RestrictedDiet, Fat-RestrictedDiet, Sodium-RestrictedFeeding BehaviorFemaleFruitGastrointestinal MicrobiomeHumansHypertensionMaleMetabolic Networks and PathwaysMetabolomeMiddle AgedPlant ExtractsSodium Chloride, DietarySodium, DietaryVegetablesYoung AdultConceptsSodium intakeBlood pressureDietary ApproachesDASH-Sodium trialHigh sodium intakeLow-sodium interventionAmino acid-related metabolitesDASH dietDiet armSodium trialLinear mixed-effects regressionDietary sodiumMixed-effects regressionEpidemiologic studiesSodium interventionBlood samplesGut microbialPlasma metabolitesControl dietIntakeRandom orderTrialsFeeding studyHypertensionIntervention
2016
Identifying biomarkers of dietary patterns by using metabolomics 1–3
Playdon MC, Moore SC, Derkach A, Reedy J, Subar AF, Sampson JN, Albanes D, Gu F, Kontto J, Lassale C, Liao LM, Männistö S, Mondul AM, Weinstein SJ, Irwin ML, Mayne ST, Stolzenberg-Solomon R. Identifying biomarkers of dietary patterns by using metabolomics 1–3. American Journal Of Clinical Nutrition 2016, 105: 450-465. PMID: 28031192, PMCID: PMC5267308, DOI: 10.3945/ajcn.116.144501.Peer-Reviewed Original ResearchMeSH KeywordsAgedAlpha-TocopherolAnimalsBeta CaroteneBiomarkersCase-Control StudiesCross-Sectional StudiesDietDiet, MediterraneanDietary FiberEdible GrainEnergy IntakeExerciseFastingFatty Acids, UnsaturatedFinlandFishesFruitHumansMetabolomicsMicronutrientsMiddle AgedRandomized Controlled Trials as TopicSeafoodSurveys and QuestionnairesVegetablesConceptsDiet Quality IndexDietary patternsDiet indexDiet qualitySerum metabolitesBeta-Carotene Cancer Prevention Study cohortHealthy Diet IndexMale Finnish smokersPrevention Study cohortChronic disease incidenceFood frequency questionnaireHealthy dietary patternBody mass indexCase-control studyNational dietary guidelinesDiet quality measurementsMass indexStudy cohortStudy randomizationFinnish smokersSpecific metabolite profilesDietary guidelinesPhysical activityEnergy intakeAlpha-tocopherol