2024
Young adults, particularly young women, account for an increasingly large share of Dutch mental healthcare expenditure over the period between 2015 and 2021
Dijkstra L, Gülöksüz S, Batalla A, van Os J. Young adults, particularly young women, account for an increasingly large share of Dutch mental healthcare expenditure over the period between 2015 and 2021. Epidemiology And Psychiatric Sciences 2024, 33: e48. PMID: 39390846, PMCID: PMC11561524, DOI: 10.1017/s2045796024000404.Peer-Reviewed Original ResearchConceptsMental healthcare expenditureMental healthcare costsHealthcare expendituresGeneral practitionersMental distressHealthcare costsPublic mental health approachYounger ageYoung adultsMental healthcare utilisationMental health approachPostal code levelYoung womenHealthcare utilisationOlder adultsSpecialist costsHealth approachMedical specialistsHealth insuranceMedical systemAge groupsTime pointsAdultsYoung peopleLinear regression
2021
Genetic Risk for Smoking: Disentangling Interplay Between Genes and Socioeconomic Status
Pasman J, Demange P, Guloksuz S, Willemsen A, Abdellaoui A, ten Have M, Hottenga J, Boomsma D, de Geus E, Bartels M, de Graaf R, Verweij K, Smit D, Nivard M, Vink J. Genetic Risk for Smoking: Disentangling Interplay Between Genes and Socioeconomic Status. Behavior Genetics 2021, 52: 92-107. PMID: 34855049, PMCID: PMC8860781, DOI: 10.1007/s10519-021-10094-4.Peer-Reviewed Original ResearchMeSH KeywordsGenome-Wide Association StudyHumansMultifactorial InheritanceNetherlandsSmokingSocial ClassConceptsLifetime smokingSocioeconomic statusNetherlands Mental Health SurveyMental healthIncidence Study-2Mental Health SurveyNeighborhood socioeconomic statusGenome-wide association studiesGenetic liabilityHealth SurveySmokingGene-environment interactionsEducational attainmentEA effectNetherlands Twin RegisterSmoking traitsGenetic riskPolygenic scoresEtiology of smokingPredictive profilesTwin RegisterSES characteristicsUK BiobankReliable predictorHealthSchizophrenia and the Environment: Within-Person Analyses May be Required to Yield Evidence of Unconfounded and Causal Association—The Example of Cannabis and Psychosis
van Os J, Pries L, Have M, de Graaf R, van Dorsselaer S, Bak M, Wittchen H, Rutten B, Guloksuz S. Schizophrenia and the Environment: Within-Person Analyses May be Required to Yield Evidence of Unconfounded and Causal Association—The Example of Cannabis and Psychosis. Schizophrenia Bulletin 2021, 47: 594-603. PMID: 33693921, PMCID: PMC8084443, DOI: 10.1093/schbul/sbab019.Peer-Reviewed Original ResearchConceptsFixed-effects modelCannabis usePsychotic experiencesGeneral population cohortRandom-effects modelMental health outcomesRisk factorsTime-varying confoundersProspective associationsPopulation cohortHealth outcomesOwn controlCausal associationPsychosisCannabisLongitudinal studyAssociationBetween-person levelConfoundersCohortIncidenceSchizophreniaStudy protocol of a randomized, double-blind, placebo-controlled, multi-center trial to treat antipsychotic-induced weight gain: the Metformin-Lifestyle in antipsychotic users (MELIA) trial
de Boer N, Guloksuz S, van Baal C, Willebrands L, Deenik J, Vinkers C, Rossum I, Zinkstok J, Wilting I, Zantvoord J, Backx F, Swildens W, Schouw M, Bogers J, Hulshof F, de Knijff R, Duindam P, Veereschild M, Bak M, Frederix G, de Haan L, van Os J, Cahn W, Luykx J. Study protocol of a randomized, double-blind, placebo-controlled, multi-center trial to treat antipsychotic-induced weight gain: the Metformin-Lifestyle in antipsychotic users (MELIA) trial. BMC Psychiatry 2021, 21: 4. PMID: 33402159, PMCID: PMC7783702, DOI: 10.1186/s12888-020-02992-4.Peer-Reviewed Original ResearchConceptsNetherlands Trial RegisterLifestyle interventionQuality of lifeTreatment inceptionOutcome measuresWeight gainAntipsychotic-induced weight gainSafety of metforminUse of metforminCommon adverse effectsSecondary outcome measuresPrimary outcome measureWeeks of treatmentBody weight lossMulti-center trialType 2 diabetesMajor health problemYears of ageSchizophrenia spectrum disordersTrials RegisterMetabolic syndromeOptimal management strategyExercise programMetformin treatmentDietary consultation
2020
Association of Recent Stressful Life Events With Mental and Physical Health in the Context of Genomic and Exposomic Liability for Schizophrenia
Pries L, van Os J, Have M, de Graaf R, van Dorsselaer S, Bak M, Lin B, van Eijk K, Kenis G, Richards A, O’Donovan M, Luykx J, Rutten B, Guloksuz S. Association of Recent Stressful Life Events With Mental and Physical Health in the Context of Genomic and Exposomic Liability for Schizophrenia. JAMA Psychiatry 2020, 77: 1296-1304. PMID: 32805017, PMCID: PMC7711318, DOI: 10.1001/jamapsychiatry.2020.2304.Peer-Reviewed Original ResearchConceptsRecent stressful life eventsStressful life eventsAssociations of SLEsPoor physical healthMental health outcomesHealth outcomesPhysical healthGeneral populationPopulation-based prospective cohort studyPRS-SCZNetherlands Mental Health SurveyES-SCZMental healthProspective cohort studyIncidence Study-2Modifiable environmental factorsAdulthood stressful life eventsMental Health SurveyDutch general populationPoor mental healthPopulation-based health outcomesLife eventsCohort studyMean ageHealth SurveyPredictive Performance of Exposome Score for Schizophrenia in the General Population
Pries L, Erzin G, van Os J, Have M, de Graaf R, van Dorsselaer S, Bak M, Rutten B, Guloksuz S. Predictive Performance of Exposome Score for Schizophrenia in the General Population. Schizophrenia Bulletin 2020, 47: 277-283. PMID: 33215211, PMCID: PMC7965069, DOI: 10.1093/schbul/sbaa170.Peer-Reviewed Original ResearchConceptsES-SCZOptimal cut pointGeneral populationPopulation cohortGeneral population cohortCut pointsExposome scoreSchizophrenia spectrum disordersMeta-analytical estimatesClinical outcomesRisk strataRisk stratificationMulticausal etiologyMedical outcomesPsychiatric diagnosisBipolar disorderSchizophrenia diagnosisExposure scoreSuicide planSum scoreGene-environment interaction studiesSchizophreniaRisk predictionCharacteristic curveScoresDo Current Measures of Polygenic Risk for Mental Disorders Contribute to Population Variance in Mental Health?
Marsman A, Pries L, Have M, de Graaf R, van Dorsselaer S, Bak M, Kenis G, Lin B, Luykx J, Rutten B, Guloksuz S, van Os J. Do Current Measures of Polygenic Risk for Mental Disorders Contribute to Population Variance in Mental Health? Schizophrenia Bulletin 2020, 46: 1353-1362. PMID: 33259628, PMCID: PMC7707067, DOI: 10.1093/schbul/sbaa086.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAdverse Childhood ExperiencesAgedFamilyFemaleGenetic Predisposition to DiseaseHealth SurveysHumansLife Change EventsLongitudinal StudiesMaleMarijuana UseMiddle AgedMultifactorial InheritanceNetherlandsPsychotic DisordersSchizophreniaSocioeconomic FactorsUrban PopulationYoung AdultConceptsPolygenic risk scoresSchizophrenia polygenic risk scoresMental healthFamily historyNetherlands Mental Health SurveyPopulation-based studyPolygenic riskChildhood traumaMental Health SurveyMental health changesEnvironmental risk factorsGeneral mental healthPopulation mental healthGeneral population sampleSomatic painRisk factorsHealth SurveyRisk scorePRS-SZBipolar disorderEpidemiological settingsMental disordersHealth changesAttributable variationPainThe jumping to conclusions reasoning bias as a cognitive factor contributing to psychosis progression and persistence: findings from NEMESIS-2
Rauschenberg C, Reininghaus U, Have M, de Graaf R, van Dorsselaer S, Simons C, Gunther N, Henquet C, Pries L, Guloksuz S, Bak M, van Os J. The jumping to conclusions reasoning bias as a cognitive factor contributing to psychosis progression and persistence: findings from NEMESIS-2. Psychological Medicine 2020, 51: 1696-1703. PMID: 32174291, PMCID: PMC8327623, DOI: 10.1017/s0033291720000446.Peer-Reviewed Original Research
2018
Reasoning bias, working memory performance and a transdiagnostic phenotype of affective disturbances and psychotic experiences in the general population
Reininghaus U, Rauschenberg C, Have M, de Graaf R, van Dorsselaer S, Simons CJP, Gunther N, Pries LK, Guloksuz S, Radhakrishnan R, Bak M, van Os J. Reasoning bias, working memory performance and a transdiagnostic phenotype of affective disturbances and psychotic experiences in the general population. Psychological Medicine 2018, 49: 1799-1809. PMID: 30160228, DOI: 10.1017/s0033291718002209.Peer-Reviewed Original ResearchConceptsComposite International Diagnostic InterviewAffective disturbancesPsychotic experiencesNetherlands Mental Health SurveySecond Netherlands Mental Health SurveyTransdiagnostic phenotypeJTC biasMental Health SurveyDose-response relationshipGeneral population sampleHealth SurveyGeneral populationIncidence studyHelp-seeking behaviorDiagnostic InterviewTime pointsMemory performanceConclusions reasoning biasPopulation sampleRecent findingsPhenotypeDigit span taskIndividualsFindingsPsychosisThe Complexities of Evaluating the Exposome in Psychiatry: A Data-Driven Illustration of Challenges and Some Propositions for Amendments
Guloksuz S, Rutten B, Pries L, Have M, de Graaf R, van Dorsselaer S, Klingenberg B, van Os J, Ioannidis J, Group T. The Complexities of Evaluating the Exposome in Psychiatry: A Data-Driven Illustration of Challenges and Some Propositions for Amendments. Schizophrenia Bulletin 2018, 44: 1175-1179. PMID: 30169883, PMCID: PMC6192470, DOI: 10.1093/schbul/sby118.Peer-Reviewed Original ResearchConceptsMental health outcomesHealth outcomesNetherlands Mental Health SurveyMental Health SurveyPre-specified analysis planFalsification endpointsModifiable factorsSources of heterogeneityHealth SurveyIntervention effectsSelective reportingAnalysis planP-valueOutcomesEffect sizeVibration of effectsAnalytical planSame outcomeDifferent studiesExploratory analysisExposureStudy 2 dataP-value threshold
2016
Exposure to environmental factors increases connectivity between symptom domains in the psychopathology network
Guloksuz S, van Nierop M, Bak M, de Graaf R, ten Have M, van Dorsselaer S, Gunther N, Lieb R, van Winkel R, Wittchen H, van Os J. Exposure to environmental factors increases connectivity between symptom domains in the psychopathology network. BMC Psychiatry 2016, 16: 223. PMID: 27391407, PMCID: PMC4939022, DOI: 10.1186/s12888-016-0935-1.Peer-Reviewed Original ResearchConceptsMental disordersSymptom dimensionsNetherlands Mental Health SurveyNEMESIS-1Symptom connectivityContinuous symptom dimensionsEnvironmental exposuresSelf-report Symptom Checklist-90Mental Health SurveySymptom Checklist-90Health SurveyPsychotic symptomsIncidence studyPopulation cohortSelf-reported psychopathologyConclusionsOur findingsDiagnostic categoriesSymptom domainsIndependent population cohortsRisk loadPsychopathology StudyDisordersRegression analysisCohortSymptoms