Search

The European Community’s Seventh Framework Programme under grant agreement No. HEALTH-F2-2010-241909 (EUGEI); The Spanish sample was supported by the Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012, PI19/024) (...), Velthorst, E., Mollon, J., Murray, R.M., de Haan, L., Germeys, I.M., Glahn, D.C., Arango, C., van der Ven, E., Di Forti, M., Bernardo, M., Guloksuz, S., Delespaul, P., Mezquida, G., Amoretti, S., Bobes, J., Saiz, P.A., García-Portilla, M.P., Santos, J.L., Jiménez-López, E., Sanjuan, J., Aguilar, E.J., Arrojo, M., Carracedo, A., López, G., González-Peñas, J., Parellada, M., Atbaşoğlu, C., Saka, M.C., Üçok, A., Alptekin, K., Akdede, B., Binbay, T., Altınyazar, V., Ulaş, H., Yalınçetin, B., Gümüş-Akay, G., Beyaz, B.C., Soygür, H., Cankurtaran, E.Ş., Kaymak, S.U., Maric, N.P., Mihaljevic, M.M., Petrovic, S.A., Mirjanic, T., Del-Ben, C.M., Ferraro, L., Gayer-Anderson, C., Jones, P.B., Jongsma, H.E., Kirkbride, J.B., La Cascia, C., Lasalvia, A., Tosato, S., Llorca, P.-M., Menezes, P.R., Morgan, C., Quattrone, D., Menchetti, M., Selten, J.-P., Szöke, A., Tarricone, I., Tortelli, A., McGuire, P., Valmaggia, L., Kempton, M.J., van der Gaag, M., Riecher-Rössler, A., Bressan, R.A., Barrantes-Vidal, N., Nelson, B., McGorry, P., Pantelis, C., Krebs, M.-O., Ruhrmann, S., Sachs, G., Rutten, B.P.F., van Os, J., Alizadeh, B.Z., van Amelsvoort, T., Bartels-Velthuis, A.A., Bruggeman, R., van Beveren, N.J., Luykx, J.J., Cahn, W., Simons, C.J.P., Kahn, R.S., Schirmbeck, F., van Winkel, R., Calem, M., Tognin, S., Modinos, G., Pisani, S., Kraan, T.C., van Dam, D.S., Burger, N., Amminger, G.P., Politis, A., Goodall, J., Borgwardt, S., Studerus, E., Gadelha, A., Brietzke, E., Asevedo, G., Asevedo, E., Zugman, A., Domínguez-Martínez, T., Monsonet, M., Cristóbal-Narváez, P., Racioppi, A., Kwapil, T.R., Kazes, M., Daban, C., Bourgin, J., Gay, O., Mam-Lam-Fook, C., Nordholm, D., Rander, L., Krakauer, K., Glenthøj, L.B., Glenthøj, B., Gebhard, D., Arnhold, J., Klosterkötter, J., Lasser, I., Winklbaur, B., Reichenberg, A., EU-GEI High Risk Study

Achtergrond: Ecological momentary assessment (EMA) is een veelbelovende methode om meer inzicht te krijgen in het dagelijks leven van mensen met psychische problemen. Met EMA houden patiënten meermaals per dag hun symptomen, emoties, (sociale) activiteiten en gebeurtenissen bij. Door statistische methodieken, zoals netwerkanalyse, zou EMA-feedback nieuwe inzichten kunnen opleveren in de psychiatrische zorg. Doel: De belofte, valkuilen en mogelijkheden van EMA en netwerkanalyse voor de psychiatrische zorg onderzoeken. Methode: We gebruikten empirische netwerkstudies, reviews en kwalitatief onderzoek om de stand van onderzoek en de perspectieven van patiënten en behandelaars op EMA en netwerkanalyse in kaart te brengen. Daarnaast bespreken we een studie waarbij 20 patiënten met een bipolaire stoornis 4 maanden lang 5 maal per dag EMA-dagboeken invulden binnen hun behandeling. Resultaten: Studies naar netwerkanalyse lieten inconsistente bevindingen zien. Kwalitatief onderzoek wees uit dat patiënten met bipolaire stoornis en hun behandelaars de meerwaarde van EMA voor de zorg zien, met name in het versterken van inzicht en eigen regie. Tegelijkertijd vonden sommigen EMA belastend. Integratie van EMA in de zorg vereist personalisatie en goede aansluiting met bestaande behandelmethoden. Conclusie: EMA heeft toegevoegde waarde voor de psychiatrische zorg, mits het zorgvuldig ingezet wordt.

Clozapine is the most effective antipsychotic for patients with treatment-resistant schizophrenia. However, response is highly variable and possible genetic underpinnings of this variability remain unknown. Here, we performed polygenic risk score (PRS) analyses to estimate the amount of variance in symptom severity among clozapine-treated patients explained by PRSs (R2) and examined the association between symptom severity and genotype-predicted CYP1A2, CYP2D6, and CYP2C19 enzyme activity. Genome-wide association (GWA) analyses were performed to explore loci associated with symptom severity. A multicenter cohort of 804 patients (after quality control N = 684) with schizophrenia spectrum disorder treated with clozapine were cross-sectionally assessed using the Positive and Negative Syndrome Scale and/or the Clinical Global Impression-Severity (CGI-S) scale. GWA and PRS regression analyses were conducted. Genotype-predicted CYP1A2, CYP2D6, and CYP2C19 enzyme activities were calculated. Schizophrenia-PRS was most significantly and positively associated with low symptom severity (p = 1.03 × 10−3; R2 = 1.85). Cross-disorder-PRS was also positively associated with lower CGI-S score (p = 0.01; R2 = 0.81). Compared to the lowest tertile, patients in the highest schizophrenia-PRS tertile had 1.94 times (p = 6.84×10−4) increased probability of low symptom severity. Higher genotype-predicted CYP2C19 enzyme activity was independently associated with lower symptom severity (p = 8.44×10−3). While no locus surpassed the genome-wide significance threshold, rs1923778 within NFIB showed a suggestive association (p = 3.78×10−7) with symptom severity. We show that high schizophrenia-PRS and genotype-predicted CYP2C19 enzyme activity are independently associated with lower symptom severity among individuals treated with clozapine. Our findings open avenues for future pharmacogenomic projects investigating the potential of PRS and genotype-predicted CYP-activity in schizophrenia.

ACHTERGROND Er is consensus over het belang van het betrekken van naasten in de zorg voor mensen met ernstige psychiatrische problematiek. Vanuit de naasten, hulpverlening en cliënten is er de vraag hoe dit op een goede manier vorm te geven. DOEL Vaststellen of de Triadekaart, een gespreksinstrument ontwikkeld om de rol van naasten in het contact te versterken, leidt tot betere samenwerking. METHODE Quasi-experimenteel onderzoek bij 12 woonzorgteams en 3 FACT-teams die met de Triadekaart gingen werken en 8 vergelijkbare woonzorgteams en 2 FACT-teams. Met dossieronderzoek en enquêtes verzamelden we informatie over gebruik van de kaart en de samenwerking bij invoering en een jaar daarna. RESULTATEN De Triadekaart bleek spaarzaam te worden ingezet. Bij gebruik ervan, werd een breder scala aan onderwerpen besproken waaronder de behoeften van naasten zelf. Ook kregen cliënten een grotere rol bij de verdeling van taken. In teams waar aandacht was geweest voor de Triadekaart kwam bij meer cliënten het netwerk in beeld en sprak men elkaar ook vaker face-to-face. CONCLUSIE Aandacht voor de Triadekaart leidt tot beter bereik van naasten en, indien ingezet, tot inhoudsvoller contact. Daadwerkelijke implementatie van de Triadekaart blijkt echter problematisch en de beoogde positieve invloed op samenwerking en zorg daarmee nog gering.

Mensen met een ernstige psychische aandoening (EPA) die langdurig afhankelijk zijn van intensieve psychiatrische zorg, hebben vaak cognitieve problemen die het dagelijks functioneren be- perken. Cognitieve Adaptatietraining (CAT) beoogt dagelijks functione- ren te verbeteren door cognitieve beperkingen te ondervangen met eenvoudige, praktische hulpmiddelen. In deze studie werd CAT ingezet als verpleegkundige interventie. Twaalf verpleegkundige teams en hun cliënten werden willekeurig toe- gewezen aan CAT (n = 42) of gebruikelijke zorg (n = 47). Gedurende een jaar werden dagelijks functioneren, kwaliteit van leven, empower- ment, negatieve symptomen en cognitief funtioneren (onder andere executief functioneren, visuele perceptie) gemeten. De CAT-groep werd een jaar extra gevolgd. Dagelijks functioneren, executief functioneren en visuele perceptie verbeterden bij de CAT-groep vergeleken met deelnemers die gebruike- lijke zorg ontvingen. De groepen verschilden niet op andere uitkomst- maten. Verbeteringen in het dagelijks functioneren in de CAT-groep bleven behouden bij follow-up. CAT lijkt hiermee een waardevolle aanvulling voor de ondersteuning van mensen met een EPA in langdurige klinische psychiatrische zorg.

OBJECTIVE: This study aimed to assess the heterogeneity and stability of cognition in patients with a non-affective psychotic disorder and their unaffected siblings. In addition, we aimed to predict the cognitive subtypes of siblings by their probands. METHOD: Assessments were conducted at baseline, 3 and 6 years in 1119 patients, 1059 siblings and 586 controls from the Genetic Risk and Outcome of Psychosis (GROUP) study. Group-based trajectory modeling was applied to identify trajectories and clustered multinomial logistic regression analysis was used for prediction modeling. A composite score of eight neurocognitive tests was used to measure cognitive performance. RESULTS: Five stable cognitive trajectories ranging from severely altered to high cognitive performance were identified in patients. Likewise, four stable trajectories ranging from moderately altered to high performance were found in siblings. Siblings had a higher risk of cognitive alteration when patients' alteration was mild (OR = 2.21), moderate (OR = 5.70), and severe (OR = 10.07) compared with patients with intact cognitive function. The familial correlation coefficient between pairs of index patients and their siblings was 0.27 (P = 0.003). CONCLUSIONS: The cognitive profiles identified in the current study might be suitable as endophenotypes and could be used in future genetic studies and predicting functional and clinical outcomes. ispartof: Acta Psychiatrica Scandinavica vol:138 issue:6 pages:591-604 ispartof: location:United States status: published

Background: Schizophrenia Spectrum Disorder (SSD) patients have repeated symptomatic relapses during their life course. A clear definition of such episodes is required to enable building patient level models describing episode patterns. In current literature, the definitions of relapse and episodes in SSD are mostly based on hospitalisation and occasionally on symptom scales. Hospitalisation rates are affected by deinstitutionalization, hence definitions of episodes should rather depend on healthcare intensity. We present a method for grouping healthcare consumption trajectories into episodes based on individual patterns of healthcare use. Methods: Administrative data describing the daily healthcare consumption of 13155 SSD patients in the Northern Netherlands is available for research. Data was collected between the years 2000 and 2012. Healthcare use costs are calculated using unit costs from a costing manual. We use Exponentially Weighted Moving Average (EWMA) control charts to distinguish two states of healthcare consumption based on intensity. Daily healthcare use weighted by cost is used as healthcare intensity. State transitions are determined on a patient level. The chart is restarted after a detected structural change. The approach is validated by determining the association between the Global Assessment of Functioning (GAF) scale and the episode state. Results: The mean number of episodes was 0.63 per patient per year. For the subsample without hospitalisations this was also 0.63. Average episode durations were similar with 235 and 245 days for the full- and subsample respectively. GAF scores have an inverse relationship with the episode state indicator. Conclusions: The Repeated Exponentially Weighted Moving Average Control Chart (REWMACC), using a daily healthcare intensity signal, is a feasible and promising tool in quantifying patient level SSD healthcare episodes, useful in health economic models to support prevention based healthcare. The results in the subgroup without hospitalizations show that the method is robust towards changes in health care policy.

BACKGROUND: Sequencing studies have pointed to the involvement in schizophrenia of rare coding variants in neuronally expressed genes, including activity-regulated cytoskeleton-associated protein (ARC) and N-methyl-D-aspartate receptor (NMDAR) complexes; however, larger samples are required to reveal novel genes and specific biological mechanisms. METHODS: We sequenced 187 genes, selected for prior evidence of association with schizophrenia, in a new dataset of 5207 cases and 4991 controls. Included among these genes were members of ARC and NMDAR postsynaptic protein complexes, as well as voltage-gated sodium and calcium channels. We performed a rare variant meta-analysis with published sequencing data for a total of 11,319 cases, 15,854 controls, and 1136 trios. RESULTS: While no individual gene was significantly associated with schizophrenia after genome-wide correction for multiple testing, we strengthen the evidence that rare exonic variants in the ARC (p = 4.0 × 10-4) and NMDAR (p = 1.7 × 10-5) synaptic complexes are risk factors for schizophrenia. In addition, we found that loss-of-function variants and missense variants at paralog-conserved sites were enriched in voltage-gated sodium channels, particularly the alpha subunits (p = 8.6 × 10-4). CONCLUSIONS: In one of the largest sequencing studies of schizophrenia to date, we provide novel evidence that multiple voltage-gated sodium channels are involved in schizophrenia pathogenesis and confirm the involvement of ARC and NMDAR postsynaptic complexes. ispartof: BIOLOGICAL PSYCHIATRY vol:85 issue:7 pages:554-562 ispartof: location:United States status: published

Obsessive–compulsive symptoms (OCS) are frequently reported in patients with schizophrenia and have been associated with subjective distress and higher impairment. Recent studies suggest fluctuation in co-occurring OCS and associations with the course of psychotic symptoms. Current evidence is limited by few studies with long assessments intervals and a sole focus on between-subject comparisons. The aim of this study was to specifically investigate co-variation of symptom domains over time within individuals. Patients with a psychotic disorder (n = 56) and un-affected siblings (n = 49) completed monthly assessments of clinical and subclinical symptoms over 6 months. Mixed-model multilevel analyses examined the variability and relationship between OCS and positive, negative, and depressive symptoms on the between- and within-subject level. Symptom domains were associated across subjects and assessment times, in patients and siblings, with the strongest association between OCS and (subclinical) positive symptoms. Within-subjects, substantial variability and co-variation of all symptom domains was found. Particularly, between-subject differences in positive symptoms and within-subject change in depressive symptoms predicted subsequent OCS in patients 1 months later. This is the first prospective study disaggregating between and within-subject associations between co-occurring OCS and symptom cluster of psychosis. Differences on these two levels suggest different underlying mechanisms. The association between depressive symptoms and subsequent increase/decrease of OCS within patients may have important treatment implications. Electronic supplementary material The online version of this article (10.1007/s00406-018-0884-4) contains supplementary material, which is available to authorized users.

Exposures constitute a dense network of the environment: exposome. Here, we argue for embracing the exposome paradigm to investigate the sum of nongenetic "risk" and show how predictive modeling approaches can be used to construct an exposome score (ES; an aggregated score of exposures) for schizophrenia. The training dataset consisted of patients with schizophrenia and controls, whereas the independent validation dataset consisted of patients, their unaffected siblings, and controls. Binary exposures were cannabis use, hearing impairment, winter birth, bullying, and emotional, physical, and sexual abuse along with physical and emotional neglect. We applied logistic regression (LR), Gaussian Naive Bayes (GNB), the least absolute shrinkage and selection operator (LASSO), and Ridge penalized classification models to the training dataset. ESs, the sum of weighted exposures based on coefficients from each model, were calculated in the validation dataset. In addition, we estimated ES based on meta-analyses and a simple sum score of exposures. Accuracy, sensitivity, specificity, area under the receiver operating characteristic, and Nagelkerke's R-2 were compared. The ESMeta-analyses performed the worst, whereas the sum score and the ESGNB were worse than the ESLR that performed similar to the ESLASSO and ESRIDGE. The ESLR distinguished patients from controls (odds ratio [OR] = 1.94, P < .001), patients from siblings (OR = 1.58, P < .001), and siblings from controls (OR = 1.21, P= .001). An increase in ESLR was associated with a gradient increase of schizophrenia risk. In reference to the remaining fractions, the ESLR at top 30%, 20%, and 10% of the control distribution yielded ORs of 3.72, 3.74, and 4.77, respectively. Our findings demonstrate that predictive modeling approaches can be harnessed to evaluate the exposome.

BACKGROUND: Use of decision aids in mental health care is increasing and will also be introduced in the Dutch mental healthcare system. We describe the context of this development and discuss how decision aids could facilitate evidence-based psychiatry. AIM: To describe the development of the decision aid TReatment E-Assist (TREAT) in the Dutch mental healthcare system that aims to optimize treatment of people with a psychotic illness. METHOD: We describe how the TREAT application works and discuss its potential contribution to the treatment of people with a psychotic illness. RESULTS: In a pilot study TREAT was judged as user friendly and useful. TREAT seemed to increase the integration of ROM-results in treatment and the advice offered new view points for practioners. CONCLUSION: TREAT is a novel application which combines routine outcome monitoring results with current treatment guidelines and standards of care in order to generate personalised treatment recommendations in the context of a psychiatric treatment trajectory. A multicentre study is being conducted in different provinces in the Netherlands to investigate the effectiveness of TREAT.

BackgroundLittle is known about visual hallucinations (VH) in psychosis. We investigated the prevalence and the role of bottom-up and top-down processing in VH. The prevailing view is that VH are probably related to altered top-down processing, rather than to distorted bottom-up processing. Conversely, VH in Parkinson's disease are associated with impaired visual perception and attention, as proposed by the Perception and Attention Deficit (PAD) model. Auditory hallucinations (AH) in psychosis, however, are thought to be related to increased attention.MethodOur retrospective database study included 1119 patients with non-affective psychosis and 586 controls. The Community Assessment of Psychic Experiences established the VH rate. Scores on visual perception tests [Degraded Facial Affect Recognition (DFAR), Benton Facial Recognition Task] and attention tests [Response Set-shifting Task, Continuous Performance Test-HQ (CPT-HQ)] were compared between 75 VH patients, 706 non-VH patients and 485 non-VH controls.ResultsThe lifetime VH rate was 37%. The patient groups performed similarly on cognitive tasks; both groups showed worse perception (DFAR) than controls. Non-VH patients showed worse attention (CPT-HQ) than controls, whereas VH patients did not perform differently.ConclusionsWe did not find significant VH-related impairments in bottom-up processing or direct top-down alterations. However, the results suggest a relatively spared attentional performance in VH patients, whereas face perception and processing speed were equally impaired in both patient groups relative to controls. This would match better with the increased attention hypothesis than with the PAD model. Our finding that VH frequently co-occur with AH may support an increased attention-induced ‘hallucination proneness’.

Genome-wide association studies (GWAS) of schizophrenia have yielded more than 100 common susceptibility variants, and strongly support a substantial polygenic contribution of a large number of small allelic effects. It has been hypothesized that familial schizophrenia is largely a consequence of inherited rather than environmental factors. We investigated the extent to which familiality of schizophrenia is associated with enrichment for common risk variants detectable in a large GWAS. We analyzed single nucleotide polymorphism (SNP) data for cases reporting a family history of psychotic illness (N=978), cases reporting no such family history (N=4,503), and unscreened controls (N=8,285) from the Psychiatric Genomics Consortium (PGC1) study of schizophrenia. We used a multinomial logistic regression approach with model-fitting to detect allelic effects specific to either family history subgroup. We also considered a polygenic model, in which we tested whether family history positive subjects carried more schizophrenia risk alleles than family history negative subjects, on average. Several individual SNPs attained suggestive but not genome-wide significant association with either family history subgroup. Comparison of genome-wide polygenic risk scores based on GWAS summary statistics indicated a significant enrichment for SNP effects among family history positive compared to family history negative cases (Nagelkerke's R-2=0.0021; P=0.00331; P-value threshold

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7% for height to 47% for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait., Genetic prediction of complex traits so far has limited accuracy because of insufficient understanding of the genetic risk. Here, Maier et al. develop an improved method for trait prediction that makes use of genetic correlations between traits and apply it to summary statistics of psychiatric diseases.

Regulatory and coding variants are known to be enriched with associations identified by genome-wide association studies (GWASs) of complex disease, but their contributions to trait heritability are currently unknown. We applied variance-component methods to imputed genotype data for 11 common diseases to partition the heritability explained by genotyped SNPs (h(g)(2)) across functional categories (while accounting for shared variance due to linkage disequilibrium). Extensive simulations showed that in contrast to current estimates from GWAS summary statistics, the variance-component approach partitions heritability accurately under a wide range of complex-disease architectures. Across the 11 diseases DNaseI hypersensitivity sites (DHSs) from 217 cell types spanned 16% of imputed SNPs (and 24% of genotyped SNPs) but explained an average of 79% (SE = 8%) of h(g)(2) from imputed SNPs (5.1 x enrichment; p = 3.7 x 10(-17)) and 38% (SE = 4%) of h(g)(2) from genotyped SNPs (1.6 x enrichment, p = 1.0 x 10(-4)). Further enrichment was observed at enhancer DHSs and cell-type-specific DHSs. In contrast, coding variants, which span 1% of the genome, explained