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Oxytocin has been proposed to mediate amygdala dysfunction associated with altered emotion processing in schizophrenia, but the contribution of oxytocin pathway genes is yet to be investigated.
To identify potential different contributions of three oxytocin receptor polymorphisms (rs53576, rs237902 and rs2254298) between patients with schizophrenia spectrum disorders (SCZ), affective spectrum disorders (AD) and healthy controls (HC).
In a total of 346 participants (104 with SCZ, 100 with AD, and 142 HC) underwent genotyping and functional magnetic resonance imaging (fMRI) during an emotional faces matching paradigm. Genetic association analyses were performed to test the possible effects on task-induced BOLD amygdala response to fearful/angry faces.
In participants with SCZ, the rs237902 G allele was associated with low amygdala activation (left hemisphere: b= −4.99, Bonferroni corrected P=0.04) and interaction analyses showed that this association was disorder specific (left hemisphere: Bonferroni corrected P=0.003; right hemisphere: Bonferroni corrected P=0.03). There were no associations between oxytocin polymorphisms and amygdala activation in the total sample, among AD patients or HC.
Rs237902 was associated with amygdala activation in response to fearful/angry faces only in patients with SCZ. Our findings indicate that the endogenous oxytocin system could serve as a contributing factor in biological underpinnings of emotion processing and that this contribution is disorder specific.
Schizophrenia (SZ) and bipolar disorder (BD) are heritable, polygenic disorders with shared clinical and genetic components, suggesting a psychosis continuum. Cannabis use is a well-documented environmental risk factor in psychotic disorders. In the current study, we investigated the relationship between SZ genetic load and cannabis use before illness onset in SZ and BD spectrums. Since frequent early cannabis use (age <18 years) is believed to increase the risk of developing psychosis more than later use, follow-up analyses were conducted comparing early use to later use and no use.
We assigned a SZ-polygenic risk score (PGRS) to each individual in our independent sample (N = 381 SZ spectrum cases, 220 BD spectrum cases and 415 healthy controls), calculated from the results of the Psychiatric Genomics Consortium (PGC) SZ case–control study (N = 81 535). SZ-PGRS in patients who used cannabis weekly to daily in the period before first illness episode was compared with that of those who never or infrequently used cannabis.
Patients with weekly to daily cannabis use before illness onset had the highest SZ-PGRS (p = 0.02, Cohen's d = 0.33). The largest difference was found between patients with daily or weekly cannabis use before illness onset <18 years of age and patients with no or infrequent use of cannabis (p = 0.003, Cohen's d = 0.42).
Our study supports an association between high SZ-PGRS and frequent cannabis use before illness onset in psychosis continuum disorders.
Many studies have shown associations between a history of childhood trauma and more severe or complex clinical features of bipolar disorders (BD), including suicide attempts and earlier illness onset. However, the psychopathological mechanisms underlying these associations are still unknown. Here, we investigated whether affective lability mediates the relationship between childhood trauma and the severe clinical features of BD.
A total of 342 participants with BD were recruited from France and Norway. Diagnosis and clinical characteristics were assessed using the Diagnostic Interview for Genetic Studies (DIGS) or the Structured Clinical Interview for DSM-IV Axis I disorders (SCID-I). Affective lability was measured using the short form of the Affective Lability Scale (ALS-SF). A history of childhood trauma was assessed using the Childhood Trauma Questionnaire (CTQ). Mediation analyses were performed using the SPSS process macro.
Using the mediation model and covariation for the lifetime number of major mood episodes, affective lability was found to statistically mediate the relationship between childhood trauma experiences and several clinical variables, including suicide attempts, mixed episodes and anxiety disorders. No significant mediation effects were found for rapid cycling or age at onset.
Our data suggest that affective lability may represent a psychological dimension that mediates the association between childhood traumatic experiences and the risk of a more severe or complex clinical expression of BD.
Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database.
The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared.
There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups.
These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.
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