ISSN / EISSN : 0924-9338 / 1778-3585
Published by: Cambridge University Press (10.1192)
Total articles ≅ 28,386
Latest articles in this journal
European Psychiatry, Volume 64; https://doi.org/10.1192/j.eurpsy.2021.2237
Background Intelligence is inversely associated with schizophrenia (SCZ) and bipolar disorder (BD); it remains unclear whether low intelligence is a cause or consequence. We investigated causal associations of intelligence with SCZ or BD risk and a shared risk between SCZ and BD and SCZ-specific risk. Methods To estimate putative causal associations, we performed multi-single nucleotide polymorphism (SNP) Mendelian randomization (MR) using generalized summary-data-based MR (GSMR). Summary-level datasets from five GWASs (intelligence, SCZ vs. control [CON], BD vs. CON, SCZ + BD vs. CON, and SCZ vs. BD; sample sizes of up to 269,867) were utilized. Results A strong bidirectional association between risks for SCZ and BD was observed (odds ratio; ORSCZ → BD = 1.47, p = 2.89 × 10−41, ORBD → SCZ = 1.44, p = 1.85 × 10−52). Low intelligence was bidirectionally associated with a high risk for SCZ, with a stronger effect of intelligence on SCZ risk (ORlower intelligence → SCZ = 1.62, p = 3.23 × 10−14) than the reverse (ORSCZ → lower intelligence = 1.06, p = 3.70 × 10−23). Furthermore, low intelligence affected a shared risk between SCZ and BD (OR lower intelligence → SCZ + BD = 1.23, p = 3.41 × 10−5) and SCZ-specific risk (ORlower intelligence → SCZvsBD = 1.64, p = 9.72 × 10−10); the shared risk (ORSCZ + BD → lower intelligence = 1.04, p = 3.09 × 10−14) but not SCZ-specific risk (ORSCZvsBD → lower intelligence = 1.00, p = 0.88) weakly affected low intelligence. Conversely, there was no significant causal association between intelligence and BD risk (p > 0.05). Conclusions These findings support observational studies showing that patients with SCZ display impairment in premorbid intelligence and intelligence decline. Moreover, a shared factor between SCZ and BD might contribute to impairment in premorbid intelligence and intelligence decline but SCZ-specific factors might be affected by impairment in premorbid intelligence. We suggest that patients with these genetic factors should be categorized as having a cognitive disorder SCZ or BD subtype.
European Psychiatry pp 1-27; https://doi.org/10.1192/j.eurpsy.2021.2241
European Psychiatry pp 1-30; https://doi.org/10.1192/j.eurpsy.2021.2235
European Psychiatry pp 1-41; https://doi.org/10.1192/j.eurpsy.2021.2236
European Psychiatry, Volume 64; https://doi.org/10.1192/j.eurpsy.2021.2238
European Psychiatry pp 1-29; https://doi.org/10.1192/j.eurpsy.2021.2239
European Psychiatry pp 1-5; https://doi.org/10.1192/j.eurpsy.2021.2240
European Psychiatry, Volume 64, pp 1-28; https://doi.org/10.1192/j.eurpsy.2021.2234
Background Reality-monitoring process enables to discriminate memories of internally generated information from memories of externally derived information. Studies have reported impaired reality-monitoring abilities in schizophrenia patients with auditory hallucinations (AHs), specifically with an exacerbated externalization bias, as well as alterations in neural activity within frontotemporoparietal areas. In healthy subjects, impaired reality-monitoring abilities have been associated with reduction of the paracingulate sulcus (PCS). The current study aimed to identify neuroanatomical correlates of reality monitoring in patients with schizophrenia. Methods Thirty-five patients with schizophrenia and AHs underwent a reality-monitoring task and a 3D anatomical MRI scan at 1.5 T. PCS lengths were measured separately for each hemisphere, and whole-brain voxel-based morphometry analyses were performed using the Computational Anatomy Toolbox (version 12.6) to evaluate the gray-matter volume (GMV). Partial correlation analyses were used to investigate the relationship between reality-monitoring and neuroanatomical outcomes (PCS length and GMV), with age and intracranial volume as covariates. Results The right PCS length was positively correlated with reality-monitoring accuracy (Spearman’s ρ = 0.431, p = 0.012) and negatively with the externalization bias (Spearman’s ρ = −0.379, p = 0.029). Reality-monitoring accuracy was positively correlated with GMV in the right angular gyrus, whereas externalization bias was negatively correlated with GMV in the left supramarginal gyrus/superior temporal gyrus, in the right lingual gyrus and in the bilateral inferior temporal/fusiform gyri (voxel-level p < 0.001 and cluster-level p < 0.05, FDR-corrected). Conclusions Reduced reality-monitoring abilities were significantly associated with shorter right PCS and reduced GMV in temporal and parietal regions of the reality-monitoring network in schizophrenia patients with AHs.
European Psychiatry pp 1-21; https://doi.org/10.1192/j.eurpsy.2021.2232
European Psychiatry, Volume 64, pp 1-20; https://doi.org/10.1192/j.eurpsy.2021.2233
Background The high prevalence of smoking in individuals who are at ultra-high risk (UHR) for psychosis is well known and moderate cognitive deficits have also been found in UHR. However, the association between smoking and cognition in UHR is unknown and longitudinal studies are lacking. Method A cohort study with 330 UHR individuals and 66 controls was conducted, as part of the European network of national schizophrenia networks studying gene–environment interactions (EU-GEI). At baseline and after 6, 12, and 24 months, smoking behavior was assessed with the Composite International Diagnostic Interview and cognitive functioning with a comprehensive test battery. Linear mixed-effects analyses were used to examine the multicross-sectional and prospective associations between (change in) smoking behavior and cognitive functioning, accounting for confounding variables. Results At baseline, 53% of UHR and 27% of controls smoked tobacco. Smoking UHR and controls did not significantly differ from nonsmoking counterparts on the tested cognitive domains (speed of processing, attention/vigilance, working memory, verbal learning, or reasoning/problem solving) across different assessment times. Neither smoking cessation nor initiation was associated with a significant change in cognitive functioning in UHR. Conclusions No associations were found between smoking and cognitive impairment in UHR nor in controls. However, the fact that one in every two UHR individuals report daily use of tobacco is alarming. Our data suggest that UHR have fewer cognitive impairments and higher smoking cessation rates compared to patients with first-episode psychosis found in literature. Implications to promote smoking cessation in the UHR stage need further investigation.