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 groupsMetabolomicsAssociation of hormonal and reproductive factors with differentiated thyroid cancer risk in women: a pooled prospective cohort analysis
O’Grady T, Rinaldi S, Michels K, Adami H, Buring J, Chen Y, Clendenen T, D’Aloisio A, DeHart J, Franceschi S, Freedman N, Gierach G, Giles G, Lacey J, Lee I, Liao L, Linet M, McCullough M, Patel A, Prizment A, Robien K, Sandler D, Stolzenberg-Solomon R, Weiderpass E, White E, Wolk A, Zheng W, de Gonzalez A, Kitahara C. Association of hormonal and reproductive factors with differentiated thyroid cancer risk in women: a pooled prospective cohort analysis. International Journal Of Epidemiology 2023, 53: dyad172. PMID: 38110618, PMCID: PMC10859160, DOI: 10.1093/ije/dyad172.Peer-Reviewed Original ResearchConceptsThyroid cancer riskRisk of DTCDTC riskCancer riskMultivariable-adjusted Cox proportional hazards modelsMenopausal hormone therapy useHazard ratioFactors associated with higher riskEstimate hazard ratiosHormonal factorsOral contraceptivesHormone therapy useFactor associated with lower riskCox proportional hazards modelsProspective cohort analysisIncidence of differentiated thyroid cancerPost-menopausal statusMenopausal hormone therapyProportional hazards modelExposure misclassificationReproductive factorsPre-diagnosticTherapy useEvaluate associationsSex steroid hormones
2018
Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer
Klein AP, Wolpin BM, Risch HA, Stolzenberg-Solomon RZ, Mocci E, Zhang M, Canzian F, Childs EJ, Hoskins JW, Jermusyk A, Zhong J, Chen F, Albanes D, Andreotti G, Arslan AA, Babic A, Bamlet WR, Beane-Freeman L, Berndt SI, Blackford A, Borges M, Borgida A, Bracci PM, Brais L, Brennan P, Brenner H, Bueno-de-Mesquita B, Buring J, Campa D, Capurso G, Cavestro GM, Chaffee KG, Chung CC, Cleary S, Cotterchio M, Dijk F, Duell EJ, Foretova L, Fuchs C, Funel N, Gallinger S, M. Gaziano JM, Gazouli M, Giles GG, Giovannucci E, Goggins M, Goodman GE, Goodman PJ, Hackert T, Haiman C, Hartge P, Hasan M, Hegyi P, Helzlsouer KJ, Herman J, Holcatova I, Holly EA, Hoover R, Hung RJ, Jacobs EJ, Jamroziak K, Janout V, Kaaks R, Khaw KT, Klein EA, Kogevinas M, Kooperberg C, Kulke MH, Kupcinskas J, Kurtz RJ, Laheru D, Landi S, Lawlor RT, Lee I, LeMarchand L, Lu L, Malats N, Mambrini A, Mannisto S, Milne RL, Mohelníková-Duchoňová B, Neale RE, Neoptolemos JP, Oberg AL, Olson SH, Orlow I, Pasquali C, Patel AV, Peters U, Pezzilli R, Porta M, Real FX, Rothman N, Scelo G, Sesso HD, Severi G, Shu XO, Silverman D, Smith JP, Soucek P, Sund M, Talar-Wojnarowska R, Tavano F, Thornquist MD, Tobias GS, Van Den Eeden SK, Vashist Y, Visvanathan K, Vodicka P, Wactawski-Wende J, Wang Z, Wentzensen N, White E, Yu H, Yu K, Zeleniuch-Jacquotte A, Zheng W, Kraft P, Li D, Chanock S, Obazee O, Petersen GM, Amundadottir LT. Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer. Nature Communications 2018, 9: 556. PMID: 29422604, PMCID: PMC5805680, DOI: 10.1038/s41467-018-02942-5.Peer-Reviewed Original ResearchMeSH KeywordsCarcinoma, Pancreatic DuctalDatabases, GeneticGenetic Predisposition to DiseaseGenome-Wide Association StudyHepatocyte Nuclear Factor 1-betaHepatocyte Nuclear Factor 4HumansIntercellular Signaling Peptides and ProteinsIntracellular Signaling Peptides and ProteinsPancreatic NeoplasmsPolymorphism, Single NucleotideProteinsRepressor ProteinsTensinsConceptsNew genome-wide significant lociGenome-wide significant lociExpression quantitative trait loci (eQTL) analysisQuantitative trait locus (QTL) analysisPANcreatic Disease ReseArch (PANDoRA) consortiumNew susceptibility lociPancreatic cancer susceptibility genesCommon susceptibility allelesCancer susceptibility genesSignificant lociPancreatic Cancer Case-Control ConsortiumMolecular supportPancreatic Cancer Cohort ConsortiumLocus analysisSusceptibility lociSusceptibility genesSusceptibility allelesEuropean ancestryNovel associationsLociPancreatic cancerConsortiumGWASGenesAlleles
2017
Pancreatic cancer incidence trends: evidence from the Surveillance, Epidemiology and End Results (SEER) population-based data
Gordon-Dseagu VL, Devesa SS, Goggins M, Stolzenberg-Solomon R. Pancreatic cancer incidence trends: evidence from the Surveillance, Epidemiology and End Results (SEER) population-based data. International Journal Of Epidemiology 2017, 47: 427-439. PMID: 29149259, PMCID: PMC5913617, DOI: 10.1093/ije/dyx232.Peer-Reviewed Original ResearchConceptsPancreatic cancer incidence ratesCancer incidence ratesHistologic typeAnnual percent changeIncidence ratePancreatic cancerEnd Results (SEER) population-based dataLifestyle risk factorsEnd Results registryPopulation-based dataPancreatic cancer ratesCancer incidence trendsMucinous adenocarcinomaHistologic subgroupsPancreatic adenocarcinomaRisk factorsDuctal adenocarcinomaIncidence trendsCancer ratesEndocrine cancersCystic carcinomaAdenocarcinomaPercent changeYounger ageHispanic malesEffects 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
2013
The Healthy Eating Index 2005 and Risk for Pancreatic Cancer in the NIH–AARP Study
Arem H, Reedy J, Sampson J, Jiao L, Hollenbeck AR, Risch H, Mayne ST, Stolzenberg-Solomon RZ. The Healthy Eating Index 2005 and Risk for Pancreatic Cancer in the NIH–AARP Study. Journal Of The National Cancer Institute 2013, 105: 1298-1305. PMID: 23949329, PMCID: PMC3760780, DOI: 10.1093/jnci/djt185.Peer-Reviewed Original ResearchConceptsHealthy Eating Index 2005Pancreatic cancer riskPancreatic cancerHazard ratioDietary guidelinesCancer riskExocrine pancreatic cancer casesOverweight/obese menCox proportional hazards regressionHealth-American AssociationP-interaction valuesRetired Persons DietFood frequency questionnaireNormal-weight menDietary pattern analysisBody mass indexProportional hazards regressionConfidence intervalsPancreatic cancer casesNIH-AARP studyFrequency questionnaireObese menMass indexHazards regressionWeight men