Treated Incidence of Psychotic Disorders in the Multinational EU-GEI Study

Jongsma, Hannah E; Gayer‐Anderson, Charlotte; Lasalvia, Antonio; Quattrone, Diego; Mulè, Alice; Szöke, Andreı̈; Selten, Jean‐Paul; Turner, Caitlin; Arango, Celso; Tarricone, Ilaria; Berardi, Domenico; Tortelli, Andrea; Llorca, Pierre‐Michel; Haan, Lieuwe de; Bobes, Julio; Bernardo, Miquel; Sanjuán, Julio; Santos, José Luís; Arrojo, Manuel; Del-Ben, Cristina Marta; Menezes, Paulo Rossi; Murray, Robin M.; Rutten, Bart P. F.; Jones, Peter M.; Os, Jim van; Morgan, Craig; Kirkbride, James

doi:10.1001/jamapsychiatry.2017.3554

Cited by 281 publications

(309 citation statements)

References 42 publications

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“…Finally, an important strength of our study lies in our control samples, which were recruited to represent the population at risk of each of the study sites catchment area 7,18 . This was achieved by setting quotas based on the main socio-demographics of the populations at risk.…”

Section: Discussionmentioning

confidence: 99%

The independent and combined influence of schizophrenia polygenic risk score and heavy cannabis use on risk for psychotic disorder: A case-control analysis from the EUGEI study.

M¹,

Wu-Choi

Quattrone³

et al. 2019

Preprint

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Background Some recent studies have challenged the direction of causality for the association between cannabis use and psychotic disorder, suggesting that cannabis use initiation is explained by common genetic variants associated with risk of schizophrenia.We used data from the European Union Gene-Environment Interaction consortium (EUGEI) case-control study to test for the independent and combined effect of heavy cannabis use, and of Schizophrenia Polygenic risk score (SZ PRS), on risk for psychotic disorder.Methods Genome-wide data were obtained from 492 first episode psychosis patients (FEPp) and from 787 controls of European Ancestry, and used to generate SZ PRS from the summary results of an independent meta-analysis. Information on pattern of cannabis use was used to build a 7-level frequency-type composite cannabis use measure that we previously found was a strong predictor of psychotic disorder. Results: SZ PRS did not predict cannabis initiation (b=0.027; p=0.51) or how frequently controls (b=0.027; p=0.06) or FEPp (b=0.006; p=0.91) used it, or the type of cannabis they used (Controls: b = 0.032; p=0.31); FEPp: b= 0.005; p=0.89). The frequency-type composite cannabis use measure (OR=1.32; 95% CI 1.22-1.44) and SZ PRS (OR=2.29; 95%CI 1.71-3.05) showed independent effects from each other on the OR for psychotic disorder.Conclusion SZ PRS does not predict an individual's propensity to try cannabis, frequency of use, or the potency of the cannabis used. Our findings provide the first evidence that SZ PRS and heavy cannabis use exert effects independent from each other on the risk for psychotic disorder.

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Section: Discussionmentioning

confidence: 99%

The independent and combined influence of schizophrenia polygenic risk score and heavy cannabis use on risk for psychotic disorder: A case-control analysis from the EUGEI study.

M¹,

Wu-Choi

Quattrone³

et al. 2019

Preprint

Self Cite

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“…Often the data types used to build these models (eg, English indices of deprivation) do not map easily to available US data. Plus, there is known heterogeneity in psychosis incidence between sites in different countries (Jongsma, Gayer‐Anderson, Lasalvia, et al, ) which undermine the idea that covariates affecting incidence in non‐US cohorts should be assumed to have the same effect in a US one.…”

Section: Discussionmentioning

confidence: 99%

Blind Spots: Spatial analytics can identify nonrandom geographic variation in first episode psychosis program enrollments

Mathis

Woods

Srihari

2018

Early Intervention Psych

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Findings of nonrandom spatial variation in program enrollment is valuable data for those evaluating the impact of and implementing improvements for recruitment to specialty clinics serving geographically-defined catchments. Positive findings from this preliminary study warrant further development of the predictive model as well as measurement of the impact on enrollment from recruitment interventions driven by these findings.

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“…Briefly, S3 is a population-based cohort of individuals born in Sweden including 4,936 SCZ cases and 6,321 healthy controls recruited between 2004 and 2010. SCZ cases were identified from the Sweden Hospital Discharge Register [32,33] with ≥2 hospitalizations with an ICD discharge diagnosis of SCZ or schizoaffective disorder (SAD) [34]. This operational definition of SCZ was validated in clinical, epidemiological, genetic epidemiological, and genetic studies [31].…”

Section: Ioppn Samplesmentioning

confidence: 99%

Large-scale analysis of DNA methylation identifies cellular alterations in blood from psychosis patients and molecular biomarkers of treatment-resistant schizophrenia

Hannon

Dempster

Mansell

et al. 2020

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Objective:Psychosis -a complex and heterogeneous neuropsychiatric condition characterized by hallucinations and delusions -is a common feature of schizophrenia. There is evidence for altered DNA methylation (DNAm) associated with schizophrenia in both brain and peripheral tissues. We aimed to undertake a systematic analysis of variable DNAm associated with psychosis, schizophrenia, and treatmentresistant schizophrenia, also exploring measures of biological ageing, smoking, and blood cell composition derived from DNAm data to identify molecular biomarkers of disease. Methods:We quantified DNAm across the genome in blood samples from 4,483 participants from seven casecontrol cohorts including patients with schizophrenia or first-episode psychosis. Measures of biological age, cellular composition and smoking status were derived from DNAm data using established algorithms. DNAm and derived measures were analyzed within each cohort and the results combined by meta-analysis. Results:Psychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNAm data, with the largest differences seen in treatment-resistant schizophrenia patients. DNAm at 95 CpG sites was significantly different between psychosis cases and controls, with 1,048 differentially methylated positions (DMPs) identified between schizophrenia cases and controls. Schizophrenia-associated DMPs colocalize to regions identified in genetic association studies, with genes annotated to these sites enriched for pathways relevant to disease. Finally, a number of the schizophrenia associated differences were only present in the treatment-resistant schizophrenia subgroup. Conclusions:We show that DNAm data can be leveraged to derive measures of blood cell counts and smoking that are strongly associated with psychosis. Our DNAm meta-analysis identified multiple DMPs associated with both psychosis and a more refined diagnosis of schizophrenia, with evidence for differential methylation associated with treatment-resistant schizophrenia that potentially reflects exposure to clozapine.

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Treated Incidence of Psychotic Disorders in the Multinational EU-GEI Study

Abstract: This study confirmed marked heterogeneity in risk for psychotic disorders by person and place, including higher rates in younger men, racial/ethnic minorities, and areas characterized by a lower percentage of owner-occupied houses.

Cited by 281 publications

References 42 publications

The independent and combined influence of schizophrenia polygenic risk score and heavy cannabis use on risk for psychotic disorder: A case-control analysis from the EUGEI study.

The independent and combined influence of schizophrenia polygenic risk score and heavy cannabis use on risk for psychotic disorder: A case-control analysis from the EUGEI study.

Blind Spots: Spatial analytics can identify nonrandom geographic variation in first episode psychosis program enrollments

Large-scale analysis of DNA methylation identifies cellular alterations in blood from psychosis patients and molecular biomarkers of treatment-resistant schizophrenia

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