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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

Background First-degree relatives of patients with psychotic disorder have higher levels of polygenic risk (PRS) for schizophrenia and higher levels of intermediate phenotypes. Methods We conducted, using two different samples for discovery (n= 336 controls and 649 siblings of patients with psychotic disorder) and replication (n= 1208 controls and 1106 siblings), an analysis of association between PRS on the one hand and psychopathological and cognitive intermediate phenotypes of schizophrenia on the other in a sample at average genetic risk (healthy controls) and a sample at higher than average risk (healthy siblings of patients). Two subthreshold psychosis phenotypes, as well as a standardised measure of cognitive ability, based on a short version of the WAIS-III short form, were used. In addition, a measure of jumping to conclusion bias (replication sample only) was tested for association with PRS. Results In both discovery and replication sample, evidence for an association between PRS and subthreshold psychosis phenotypes was observed in the relatives of patients, whereas in the controls no association was observed. Jumping to conclusion bias was similarly only associated with PRS in the sibling group. Cognitive ability was weakly negatively and non-significantly associated with PRS in both the sibling and the control group. Conclusions The degree of endophenotypic expression of schizophrenia polygenic risk depends on having a sibling with psychotic disorder, suggestive of underlying gene-environment interaction. Cognitive biases may better index genetic risk of disorder than traditional measures of neurocognition, which instead may reflect the population distribution of cognitive ability impacting the prognosis of psychotic disorder.

Aims Psychosis spectrum disorder has a complex pathoetiology characterised by interacting environmental and genetic vulnerabilities. The present study aims to investigate the role of gene-environment interaction using aggregate scores of genetic (polygenic risk score for schizophrenia (PRS-SCZ)) and environment liability for schizophrenia (exposome score for schizophrenia (ES-SCZ)) across the psychosis continuum. Methods The sample consisted of 1699 patients, 1753 unaffected siblings, and 1542 healthy comparison participants. The Structured Interview for Schizotypy-Revised (SIS-R) was administered to analyse scores of total, positive, and negative schizotypy in siblings and healthy comparison participants. The PRS-SCZ was trained using the Psychiatric Genomics Consortiums results and the ES-SCZ was calculated guided by the approach validated in a previous report in the current data set. Regression models were applied to test the independent and joint effects of PRS-SCZ and ES-SCZ (adjusted for age, sex, and ancestry using 10 principal components). Results Both genetic and environmental vulnerability were associated with case-control status. Furthermore, there was evidence for additive interaction between binary modes of PRS-SCZ and ES-SCZ (above 75% of the control distribution) increasing the odds for schizophrenia spectrum diagnosis (relative excess risk due to interaction = 6.79, [95% confidential interval (CI) 3.32, 10.26], p < 0.001). Sensitivity analyses using continuous PRS-SCZ and ES-SCZ confirmed gene-environment interaction (relative excess risk due to interaction = 1.80 [95% CI 1.01, 3.32], p = 0.004). In siblings and healthy comparison participants, PRS-SCZ and ES-SCZ were associated with all SIS-R dimensions and evidence was found for an interaction between PRS-SCZ and ES-SCZ on the total (B = 0.006 [95% CI 0.003, 0.009], p < 0.001), positive (B = 0.006 [95% CI, 0.002, 0.009], p = 0.002), and negative (B = 0.006, [95% CI 0.004, 0.009], p < 0.001) schizotypy dimensions. Conclusions The interplay between exposome load and schizophrenia genetic liability contributing to psychosis across the spectrum of expression provide further empirical support to the notion of aetiological continuity underlying an extended psychosis phenotype.

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.

Getting an unbiased result is a remarkably long standing problem ofcollective observation/measurement. It is pointed out that quantum coin tossingcan generate unbiased result defeating dishonesty.

Getting an unbiased result is a remarkably long standing problem ofcollective observation/measurement. It is pointed out that quantum coin tossingcan generate unbiased result defeating dishonesty.

Objective: Every year, many people undergo cardiovasculary surgery in the world. Due to improvements in coronary artery bypass surgery (CABG) tecniques, patients in high risk also in advanced age groups, CABG cause many neurological complications like stroke, postoperative delirium, depression, cognitive decline etc. Because of these problems, the effect of CABG on the brain functions gain more importance with respect to effects on postoperative heart status last years. Material and method: In our study, 24 cases undergoing CABG and valve replacement were invastigated. Neuron-specific enolase released from neurons, protein S-100B released from glial cells and nitric oxide that known to have many functions in ischemia were studied in these cases to show cerebral effects of these operations. Also neuropsychological test using for assesment of cognitive functions were performed. We analysed protein S-100B, NSE, NO concentrations in serial venous blood samples taken preoperatively and 1, 6, 24 h and 3, 7 days postoperatively in 24 patients undergoing VR or CABG surgery. Neuropsychological tests were performed preoperatively, and 3. and 7 days after surgery. Results: After performing of neuropsychological tests, cognitive decline was seen in 8 cases. Protein S-100B levels at postoperative 1. and 6. hours and also the mean levels of age and perfusion times were significantly higher in these cases. NSE levels were significantly higher in VR group at postoperative7. days with respect to preoperative levels also. However there was no significant differance between preoperative and postoperative NO levels. Conclusions: Cognitive decline is seen in CABG patients with advanced age and with long perfusion time frequently. Increased protein S-100B levels in these patients are correlated with cerebral influence which cause distrubtion in cognitive functions., Amaç: Her yıl dünyada birçok insan kardiyovasküler cerrahi geçirmektedir. Koroner arterby-pass grafting ameliyatında cerrahi tekniklerdeki ilerleme sonucunda yüksek risk grubundaki hastalar da (hipertansiyon ve diyabet gibi) ameliyata alınabilmektedir. Yüksek riskgrubundaki ve ileri yaştaki hastalara CABG uygulanması beraberinde nörolojikkomplikasyonları da getirmiştir. Ortaya çıkan nörolojik sorunlar inme, ameliyat sonrasıdeliryum, bilişsel bozukluklar ve depresyondur. Bu nedenle ilgi son yıllarda kalbin ameliyatsonrası durumu yerine CABG’nin beyin üzerine de olan etkilerine kaymıştır.Gereç ve yöntem: Çalışmamıza CABG ve valf replasmanı geçiren 24 olgu alındı. Buolgularda serebral hasarı göstermek amacı ile gliadan salınan S-100B protein, nöronlardansalınan nöron spesifik enolaz ve iskemi patofizyolojisinde birçok fonksiyonu olan nitrik oksiddüzeyleri ölçüldü. Ayrıca hastaların bilişsel fonksiyonlarını ölçen nöropsikolojik testleruygulandı. Bu amaçla CABG ve VR ameliyatı geçiren 24 olgudan ameliyat öncesi veameliyattan sonra 1., 6. ve 24. saatler ve 3. ve 7. günlerde venöz kan alınarak S-100Bprotein, NSE ve NO düzeyleri ölçüldü. Nöropsikolojik testler ameliyattan önce ve ameliyatsonrası 3. ve 7. günlerde uygulandı.Bulgular: Nöropsikolojik testler sonucunda 8 olguda bilişsel fonksiyon kaybı saptandı. Buolgularda ameliyat sonrası 1. ve 6. saatteki S-100B protein düzeyleri, perfüzyon zamanı veolguların yaş ortalaması bilişsel kayıp saptanmayan grupla karşılaştırıldığında anlamlıyüksek bulundu. NSE, VR grubunda ameliyattan sonra 7.gün ameliyat öncesi değerleregöre anlamlı yüksek bulundu ancak bunun bilişsel fonksiyon kaybıyla bir bağlantısı saptanmadı. Ameliyat öncesi ve ameliyat sonrası NO düzeylerinde ise anlamlı fark bulunmadı.Sonuç: CABG hastaları içinde yaş ortalaması yüksek ve perfüzyon zamanı uzun olanlardabilişsel fonksiyon kaybı daha fazla görülmektedir. Artan serum S-100B protein düzeyleriserebral etkilenme ve buna bağlı bilişsel fonksiyon kaybı ile koreledir

Recent years have seen considerable progress in epidemiological and molecular genetic research into environmental and genetic factors in schizophrenia, but methodological uncertainties remain with regard to validating environmental exposures, and the population risk conferred by individual molecular genetic variants is small. There are now also a limited number of studies that have investigated molecular genetic candidate gene-environment interactions (G × E), however, so far, thorough replication of findings is rare and G × E research still faces several conceptual and methodological challenges. In this article, we aim to review these recent developments and illustrate how integrated, large-scale investigations may overcome contemporary challenges in G × E research, drawing on the example of a large, international, multi-center study into the identification and translational application of G × E in schizophrenia. While such investigations are now well underway, new challenges emerge for G × E research from late-breaking evidence that genetic variation and environmental exposures are, to a significant degree, shared across a range of psychiatric disorders, with potential overlap in phenotype. © 2014 The Author.

European Community Recent years have seen considerable progress in epidemiological and molecular genetic research into environmental and genetic factors in schizophrenia, but methodological uncertainties remain with regard to validating environmental exposures, and the population risk conferred by individual molecular genetic variants is small. There are now also a limited number of studies that have investigated molecular genetic candidate gene-environment interactions (G x E), however, so far, thorough replication of findings is rare and G x E research still faces several conceptual and methodological challenges. in this article, we aim to review these recent developments and illustrate how integrated, large-scale investigations may overcome contemporary challenges in G x E research, drawing on the example of a large, international, multi-center study into the identification and translational application of G x E in schizophrenia. While such investigations are now well underway, new challenges emerge for G x E research from late-breaking evidence that genetic variation and environmental exposures are, to a significant degree, shared across a range of psychiatric disorders, with potential overlap in phenotype. 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