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Cluster studies identified a subgroup of patients with psychosis whose premorbid adjustment deteriorates before the onset, which may reflect variation in genetic influence. However, other studies reported a complex relationship between distinctive patterns of cannabis use and cognitive and premorbid impairment that is worthy of consideration. We examined whether: (1) premorbid social functioning (PSF) and premorbid academic functioning (PAF) in childhood and adolescence and current intellectual quotient (IQ) define different clusters in 802 first-episode of psychosis (FEP) patients; resulting clusters vary in (2) polygenic risk scores (PRSs) for schizophrenia (SCZ_PRS), bipolar disorder (BD_PRS), major depression (MD_PRS), and IQ (IQ_PRS), and (3) patterns of cannabis use, compared to 1,263 population-based controls. Four transdiagnostic clusters emerged (BIC = 2268.5): (1) high-cognitive-functioning (n  = 205), with the highest IQ (Mean = 106.1, 95% CI: 104.3, 107.9) and PAF, but low PSF. (2) Low-cognitive-functioning (n  = 223), with the lowest IQ (Mean = 73.9, 95% CI: 72.2, 75.7) and PAF, but normal PSF. (3) Intermediate (n  = 224) (Mean_IQ = 80.8, 95% CI: 79.1, 82.5) with low-improving PAF and PSF. 4) Deteriorating (n  = 150) (Mean_IQ = 80.6, 95% CI: 78.5, 82.7), with normal-deteriorating PAF and PSF. The PRSs explained 7.9% of between-group membership. FEP had higher SCZ_PRS than controls [ F (4,1319) = 20.4, P  < .001]. Among the clusters, the deteriorating group had lower SCZ_PRS and was likelier to have used high-potency cannabis daily. Patients with FEP clustered according to their premorbid and cognitive abilities. Pronounced premorbid deterioration was not typical of most FEP, including those more strongly predisposed to schizophrenia, but appeared in a cluster with a history of high-potency cannabis use. [ABSTRACT FROM AUTHOR]

Background and Hypothesis Facial Emotion Recognition is a key domain of social cognition associated with psychotic disorders as a candidate intermediate phenotype. In this study, we set out to investigate global and specific facial emotion recognition deficits in first-episode psychosis, and whether polygenic liability to psychotic disorders is associated with facial emotion recognition. Study Design 828 First Episode Psychosis (FEP) patients and 1308 population-based controls completed assessments of the Degraded Facial Affect Recognition Task (DFAR) and a subsample of 524 FEP and 899 controls provided blood or saliva samples from which we extracted DNA, performed genotyping and computed polygenic risk scores for schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MD). Study Results A worse ability to globally recognize facial emotion expressions was found in patients compared with controls [ B = −1.5 (0.6), 95% CI −2.7 to −0.3], with evidence for stronger effects on negative emotions (fear [ B = −3.3 (1.1), 95% CI −5.3 to −1.2] and anger [ B = −2.3 (1.1), 95% CI −4.6 to −0.1]) than on happiness [ B = 0.3 (0.7), 95% CI −1 to 1.7]. Pooling all participants, and controlling for confounds including case/control status, facial anger recognition was associated significantly with Schizophrenia Polygenic Risk Score (SZ PRS) [ B = −3.5 (1.7), 95% CI −6.9 to −0.2]. Conclusions Psychosis is associated with impaired recognition of fear and anger, and higher SZ PRS is associated with worse facial anger recognition. Our findings provide evidence that facial emotion recognition of anger might play a role as an intermediate phenotype for psychosis. [ABSTRACT FROM AUTHOR]

Background: There is increasing evidence that smoking is a risk factor for severe mental illness, including bipolar disorder. Conversely, patients with bipolar disorder might smoke more (often) as a result of the psychiatric disorder.Aims: We conducted a bidirectional Mendelian randomisation (MR) study to investigate the direction and evidence for a causal nature of the relationship between smoking and bipolar disorder.Method: We used publicly available summary statistics from genome-wide association studies on bipolar disorder, smoking initiation, smoking heaviness, smoking cessation and lifetime smoking (i.e. a compound measure of heaviness, duration and cessation). We applied analytical methods with different, orthogonal assumptions to triangulate results, including inverse-variance weighted (IVW), MR-Egger, MR-Egger SIMEX, weighted-median, weighted-mode and Steiger-filtered analyses.Results: Across different methods of MR, consistent evidence was found for a positive effect of smoking on the odds of bipolar disorder (smoking initiation ORIVW = 1.46, 95% CI 1.28-1.66, P = 1.44 × 10-8, lifetime smoking ORIVW = 1.72, 95% CI 1.29-2.28, P = 1.8 × 10-4). The MR analyses of the effect of liability to bipolar disorder on smoking provided no clear evidence of a strong causal effect (smoking heaviness betaIVW = 0.028, 95% CI 0.003-0.053, P = 2.9 × 10-2).Conclusions: These findings suggest that smoking initiation and lifetime smoking are likely to be a causal risk factor for developing bipolar disorder. We found some evidence that liability to bipolar disorder increased smoking heaviness. Given that smoking is a modifiable risk factor, these findings further support investment into smoking prevention and treatment in order to reduce mental health problems in future generations. [ABSTRACT FROM AUTHOR]