Schizophrenia polygenic risk scores, clinical variables and genetic pathways as predictors of phenotypic traits of bipolar I disorder.

AIM: We investigated the predictive value of polygenic risk scores (PRS) derived from the schizophrenia GWAS (Trubetskoy et al., 2022) (SCZ3) for phenotypic traits of bipolar disorder type-I (BP-I) in 1878 BP-I cases and 2751 controls from Romania and UK. METHODS: We used PRSice-v2.3.3 and PRS-CS for computing SCZ3-PRS for testing the predictive power of SCZ3-PRS alone and in combination with clinical variables for several BP-I subphenotypes and for pathway analysis. Non-linear predictive models were also used. RESULTS: SCZ3-PRS significantly predicted psychosis, incongruent and congruent psychosis, general age-of-onset (AO) of BP-I, AO-depression, AO-Mania, rapid cycling in univariate regressions. A negative correlation between the number of depressive episodes and psychosis, mainly incongruent and an inverse relationship between increased SCZ3-SNP loading and BP-I-rapid cycling were observed. In random forest models comparing the predictive power of SCZ3-PRS alone and in combination with nine clinical variables, the best predictions were provided by combinations of SCZ3-PRS-CS and clinical variables closely followed by models containing only clinical variables. SCZ3-PRS performed worst. Twenty-two significant pathways underlying psychosis were identified. LIMITATIONS: The combined RO-UK sample had a certain degree of heterogeneity of the BP-I severity: only the RO sample and partially the UK sample included hospitalized BP-I cases. The hospitalization is an indicator of illness severity. Not all UK subjects had complete subphenotype information. CONCLUSION: Our study shows that the SCZ3-PRS have a modest clinical value for predicting phenotypic traits of BP-I. For clinical use their best performance is in combination with clinical variables.

Predicting ADHD in alcohol dependence using polygenic risk scores for ADHD.

Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder with a high degree of comorbidity, including substance misuse. We aimed to assess whether ADHD polygenic risk scores (PRS) could predict ADHD diagnosis in alcohol dependence (AD). ADHD PRS were generated for 1223 AD subjects with ADHD diagnosis information and 1818 healthy controls. ADHD PRS distributions were compared to evaluate the differences between healthy controls and AD cases with and without ADHD. We found increased ADHD PRS means in the AD cohort with ADHD (mean 0.30, standard deviation (SD) 0.92; p = 3.9 × 10-6 ); and without ADHD (mean - 0.00, SD 1.00; p = 5.2 × 10-5 ) compared to the healthy control subjects (mean - 0.17, SD 0.99). The ADHD PRS means differed within the AD group with a higher ADHD PRS mean in those with ADHD, odds ratio (OR) 1.34, confidence interval (CI) 1.10 to 1.65; p = 0.002. This study showed a positive relationship between ADHD PRS and risk of ADHD in individuals with co-occurring AD indicating that ADHD PRS may have utility in identifying individuals that are at a higher or lower risk of ADHD. Further larger studies need to be conducted to confirm the reliability of the results before ADHD PRS can be considered as a robust biomarker for diagnosis.

Multiple psychiatric polygenic risk scores predict associations between childhood adversity and bipolar disorder.

BACKGROUND: It remains unclear how adverse childhood experiences (ACE) and increased genetic risk for bipolar disorder (BD) interact to influence BD symptom outcomes. Here we calculated multiple psychiatric polygenic risk scores (PRS) and used the measures of ACE to understand these gene-environment interactions. METHOD: 885 BD subjects were included for analyses. BD, ADHD, MDD and SCZ PRSs were calculated using the PRS-CS-auto method. ACEs were evaluated using the Children Life Event Questionnaire (CLEQ). Participants were divided into groups based on the presence of ACE and the total number of ACEs. The associations between total ACE number, PRSs and their interactions were evaluated using multiple linear and logistic regressions. Secondary analyses were performed to evaluate the influence of ACE and PRS on sub-phenotypes of BD. RESULTS: The number of ACEs increased with the ADHD PRS. BD participants who had ACEs showed an earlier age of BD onset and higher odds of having rapid cycling. Increased BD PRS was associated with increased odds of developing psychotic symptoms. Higher ADHD PRS was associated with increased odds of having rapid cycling. No prediction effect was observed from MDD and SCZ PRS. And, we found no significant interaction between ACE numbers and any of the PRSs in predicting any selected BD sub-phenotypes. LIMITATIONS: The study was limited by sample size, ACE definition, and cross-sectional data collection method. CONCLUSIONS: The findings consolidate the importance of considering multiple psychiatric PRSs in predicting symptom outcomes among BD patients.

The Attentional Blink is Related to the Microsaccade Rate Signature.

The reduced detectability of a target T2 following discrimination of a preceding target T1 in the attentional blink (AB) paradigm is classically interpreted as a consequence of reduced attention to T2 due to attentional allocation to T1. Here, we investigated whether AB was related to changes in microsaccade rate (MSR). We found a pronounced MSR signature following T1 onset, characterized by MSR suppression from 200 to 328 ms and enhancement from 380 to 568 ms. Across participants, the magnitude of the MSR suppression correlated with the AB effect such that low T2 detectability corresponded to reduced MSR. However, in the same task, T1 error trials coincided with the presence of microsaccades. We discuss this apparent paradox in terms of known neurophysiological correlates of MS whereby cortical excitability is suppressed both during the microsaccade and MSR suppression, in accordance to poor T1 performance with microsaccade occurrence and poor T2 performance with microsaccade absence. Our data suggest a novel low-level mechanism contributing to AB characterized by reduced MSR, thought to cause suppressed visual cortex excitability. This opens the question of whether attention mediates T2 performance suppression independently from MSR, and if not, how attention interacts with MSR to produce the T2 performance suppression.