The association between cannabis and psychosis is established, but the role of underlying genetics is unclear. We used data from the EU-GEI case-control study and UK Biobank to examine the independent and combined effect of heavy cannabis use and schizophrenia polygenic risk score (PRS) on risk for psychosis.

Genome-wide association study summary statistics from the Psychiatric Genomics Consortium and the Genomic Psychiatry Cohort were used to calculate schizophrenia and cannabis use disorder (CUD) PRS for 1098 participants from the EU-GEI study and 143600 from the UK Biobank. Both datasets had information on cannabis use.

In both samples, schizophrenia PRS and cannabis use independently increased risk of psychosis. Schizophrenia PRS was not associated with patterns of cannabis use in the EU-GEI cases or controls or UK Biobank cases. It was associated with lifetime and daily cannabis use among UK Biobank participants without psychosis, but the effect was substantially reduced when CUD PRS was included in the model. In the EU-GEI sample, regular users of high-potency cannabis had the highest odds of being a case independently of schizophrenia PRS (OR daily use high-potency cannabis adjusted for PRS = 5.09, 95% CI 3.08–8.43, p = 3.21 × 10−10). We found no evidence of interaction between schizophrenia PRS and patterns of cannabis use.

Regular use of high-potency cannabis remains a strong predictor of psychotic disorder independently of schizophrenia PRS, which does not seem to be associated with heavy cannabis use. These are important findings at a time of increasing use and potency of cannabis worldwide.

Cognitive impairment constitutes a prevailing issue in the schizophrenia spectrum, severely impacting patients' functional outcomes. A global cognitive score, sensitive to the stages of the spectrum, would benefit the exploration of potential factors involved in the cognitive decline.

First, we performed principal component analysis on cognitive scores from 768 individuals across the schizophrenia spectrum, including first-degree relatives of patients, individuals at ultra-high risk, who had a first-episode psychosis, and chronic schizophrenia patients, alongside 124 healthy controls. The analysis provided 10 g-factors as global cognitive scores, validated through correlations with intelligence quotient and assessed for their sensitivity to the stages on the spectrum using analyses of variance. Second, using the g-factors, we explored potential mechanisms underlying cognitive impairment in the schizophrenia spectrum using correlations with sociodemographic, clinical, and developmental data, and linear regressions with genotypic data, pooled through meta-analyses.

The g-factors were highly correlated with intelligence quotient and with each other, confirming their validity. They presented significant differences between subgroups along the schizophrenia spectrum. They were positively correlated with educational attainment and the polygenic risk score (PRS) for cognitive performance, and negatively correlated with general psychopathology of schizophrenia, neurodevelopmental load, and the PRS for schizophrenia.

The g-factors appeared as valid estimators of global cognition, enabling discerning cognitive states within the schizophrenia spectrum. Educational attainment and genetics related to cognitive performance may have a positive influence on cognitive functioning, while general psychopathology of schizophrenia, neurodevelopmental load, and genetic liability to schizophrenia may have an adverse impact.

Genetic vulnerability to mental disorders has been associated with coronavirus disease-19 (COVID-19) outcomes. We explored whether polygenic risk scores (PRSs) for several mental disorders predicted poorer clinical and psychological COVID-19 outcomes in people with pre-existing depression.

Data from three assessments of the Australian Genetics of Depression Study (N = 4405; 52.2 years ± 14.9; 76.2% females) were analyzed. Outcomes included COVID-19 clinical outcomes (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] infection and long COVID, noting the low incidence of COVID-19 cases in Australia at that time) and COVID-19 psychological outcomes (COVID-related stress and COVID-19 burnout). Predictors included PRS for depression, bipolar disorder, schizophrenia, and anxiety. The associations between these PRSs and the outcomes were assessed with adjusted linear/logistic/multinomial regressions. Mediation (N = 4338) and moderation (N = 3326) analyses were performed to explore the potential influence of anxiety symptoms and resilience on the identified associations between the PRSs and COVID-19 psychological outcomes.

None of the selected PRS predicted SARS-CoV-2 infection or long COVID. In contrast, the depression PRS predicted higher levels of COVID-19 burnout. Anxiety symptoms fully mediated the association between the depression PRS and COVID-19 burnout. Resilience did not moderate this association.

A higher genetic risk for depression predicted higher COVID-19 burnout and this association was fully mediated by anxiety symptoms. Interventions targeting anxiety symptoms may be effective in mitigating the psychological effects of a pandemic among people with depression.

It is well established that there is a substantial genetic component to eating disorders (EDs). Polygenic risk scores (PRSs) can be used to quantify cumulative genetic risk for a trait at an individual level. Recent studies suggest PRSs for anorexia nervosa (AN) may also predict risk for other disordered eating behaviors, but no study has examined if PRS for AN can predict disordered eating as a global continuous measure. This study aimed to investigate whether PRS for AN predicted overall levels of disordered eating, or specific lifetime disordered eating behaviors, in an Australian adolescent female population.

PRSs were calculated based on summary statistics from the largest Psychiatric Genomics Consortium AN genome-wide association study to date. Analyses were performed using genome-wide complex trait analysis to test the associations between AN PRS and disordered eating global scores, avoidance of eating, objective bulimic episodes, self-induced vomiting, and driven exercise in a sample of Australian adolescent female twins recruited from the Australian Twin Registry (N = 383).

After applying the false-discovery rate correction, the AN PRS was significantly associated with all disordered eating outcomes.

Findings suggest shared genetic etiology across disordered eating presentations and provide insight into the utility of AN PRS for predicting disordered eating behaviors in the general population. In the future, PRSs for EDs may have clinical utility in early disordered eating risk identification, prevention, and intervention.

Bipolar disorder (BD) shows heterogeneous illness presentation both cross-sectionally and longitudinally. This phenotypic heterogeneity might reflect underlying genetic heterogeneity. At the same time, overlapping characteristics between BD and other psychiatric illnesses are observed at clinical and biomarker levels, which implies a shared biological mechanism between them. Incorporating these two issues in a single study design, this study investigated whether phenotypically heterogeneous subtypes of BD have a distinct polygenic basis shared with other psychiatric illnesses.

Six lifetime phenotype dimensions of BD identified in our previous study were used as target phenotypes. Associations between these phenotype dimensions and polygenic risk scores (PRSs) of major psychiatric illnesses from East Asian (EA) and other available populations were analyzed.

Each phenotype dimension showed a different association pattern with PRSs of mental illnesses. PRS for EA schizophrenia showed a significant negative association with the cyclicity dimension (p = 0.044) but a significant positive association with the psychotic/irritable mania dimension (p = 0.001). PRS of EA major depressive disorder demonstrated a significant negative association with the elation dimension (p = 0.003) but a significant positive association with the comorbidity dimension (p = 0.028).

This study demonstrates that well-defined phenotype dimensions of lifetime-basis in BD have distinct genetic risks shared with other major mental illnesses. This finding supports genetic heterogeneity in BD and suggests a pleiotropy among BD subtypes and other psychiatric disorders beyond BD. Further genomic analyses adopting deep phenotyping across mental illnesses in ancestrally diverse populations are warranted to clarify intra-diagnosis heterogeneity and inter-diagnoses commonality issues in psychiatry.

The intelligence quotient (IQ) of patients with first-episode psychosis (FEP) and their unaffected relatives may be related to the genetic burden of schizophrenia (SCZ). The polygenic score approach can be useful for testing this question.

To assess the contribution of the polygenic risk scores for SCZ (PGS-SCZ) and polygenic scores for IQ (PGS-IQ) to the individual IQ and its difference from the mean IQ of the family (named family-IQ) through a family-based design in an FEP sample.

The PAFIP-FAMILIES sample (Spain) consists of 122 FEP patients, 131 parents, 94 siblings, and 176 controls. They all completed the WAIS Vocabulary subtest for IQ estimation and provided a DNA sample. We calculated PGS-SCZ and PGS-IQ using the continuous shrinkage method. To account for relatedness in our sample, we performed linear mixed models. We controlled for covariates potentially related to IQ, including age, years of education, sex, and ancestry principal components.

FEP patients significantly deviated from their family-IQ. FEP patients had higher PGS-SCZ than other groups, whereas the relatives had intermediate scores between patients and controls. PGS-IQ did not differ between groups. PGS-SCZ significantly predicted the deviation from family-IQ, whereas PGS-IQ significantly predicted individual IQ.

PGS-SCZ discriminated between different levels of genetic risk for the disorder and was specifically related to patients’ lower IQ in relation to family-IQ. The genetic background of the disorder may affect neurocognition through complex pathological processes interacting with environmental factors that prevent the individual from reaching their familial cognitive potential.

It remains unclear whether cognitive reserve can attenuate dementia risk among people with different genetic predispositions.

We aimed to examine the association between cognitive reserve and dementia, and further to explore whether and to what extent cognitive reserve may modify the risk effect of genetic factors on dementia.

Within the UK Biobank, 210 631 dementia-free participants aged ≥60 years were followed to detect incident dementia. Dementia was ascertained through medical and death records. A composite cognitive reserve indicator encompassing education, occupation and multiple cognitively loaded activities was created using latent class analysis, categorised as low, moderate and high level. Polygenic risk scores for Alzheimer's disease were constructed to evaluate genetic risk for dementia, categorised by tertiles (high, moderate and low). Data were analysed using Cox models and Laplace regression.

In multi-adjusted Cox models, the hazard ratio (HR) of dementia was 0.66 (95% confidence interval (CI) 0.61–0.70) for high cognitive reserve compared with low cognitive reserve. In Laplace regression, participants with high cognitive reserve developed dementia 1.62 (95% CI 1.35–1.88) years later than those with low cognitive reserve. In stratified analysis by genetic risk, high cognitive reserve was related to more than 30% lower dementia risk compared with low cognitive reserve in each stratum. There was an additive interaction between low cognitive reserve and high genetic risk on dementia (attributable proportion 0.24, 95% CI 0.17–0.31).

High cognitive reserve is associated with reduced risk of dementia and may delay dementia onset. Genetic risk for dementia may be mitigated by high cognitive reserve. Our findings underscore the importance of enhancing cognitive reserve in dementia prevention.

Previous evidence suggests that early life complications (ELCs) interact with polygenic risk for schizophrenia (SCZ) in increasing risk for the disease. However, no studies have investigated this interaction on neurobiological phenotypes. Among those, anomalous emotion-related brain activity has been reported in SCZ, even if evidence of its link with SCZ-related genetic risk is not solid. Indeed, it is possible this relationship is influenced by non-genetic risk factors. Thus, this study investigated the interaction between SCZ-related polygenic risk and ELCs on emotion-related brain activity.

169 healthy participants (HP) in a discovery and 113 HP in a replication sample underwent functional magnetic resonance imaging (fMRI) during emotion processing, were categorized for history of ELCs and genome-wide genotyped. Polygenic risk scores (PRSs) were computed using SCZ-associated variants considering the most recent genome-wide association study. Furthermore, 75 patients with SCZ also underwent fMRI during emotion processing to verify consistency of their brain activity patterns with those associated with risk factors for SCZ in HP.

Results in the discovery and replication samples indicated no effect of PRSs, but an interaction between PRS and ELCs in left ventrolateral prefrontal cortex (VLPFC), where the greater the activity, the greater PRS only in presence of ELCs. Moreover, SCZ had greater VLPFC response than HP.

These results suggest that emotion-related VLPFC response lies in the path from genetic and non-genetic risk factors to the clinical presentation of SCZ, and may implicate an updated concept of intermediate phenotype considering early non-genetic factors of risk for SCZ.

Smoking contributes to a variety of neurodegenerative diseases and neurobiological abnormalities, suggesting that smoking is associated with accelerated brain aging. However, the neurobiological mechanisms affected by smoking, and whether they are genetically influenced, remain to be investigated.

Using structural magnetic resonance imaging data from the UK Biobank (n = 33 293), a brain age predictor was trained on non-smoking healthy groups and tested on smokers to obtain the BrainAge Gap (BAG). The cumulative effect of multiple common genetic variants associated with smoking was then calculated to acquire a polygenic risk score (PRS). The relationship between PRS, BAG, total gray matter volume (tGMV), and smoking parameters was explored and further genes included in the PRS were annotated to identify potential molecular mechanisms affected by smoking.

The BrainAge in smokers was predicted with very high accuracy (r = 0.725, MAE = 4.16). Smokers had a greater BAG (Cohen's d = 0.074, p < 0.0001) and higher PRS (Cohen's d = 0.63, p < 0.0001) than non-smokers. A higher PRS was associated with increased amount of smoking, mediated by BAG and tGMV. Several neurotransmitters and ion channel pathways were enriched in the group of smoking-related genes involved in addiction, brain synaptic plasticity, and some neurological disorders.

By using a simplified single indicator of the entire brain (BAG) in combination with the PRS, this study highlights the greater BAG in smokers and its linkage with genes and smoking behavior, providing insight into the neurobiological underpinnings and potential features of smoking-related aging.

Hospital-based biobanks are being increasingly considered as a resource for translating polygenic risk scores (PRS) into clinical practice. However, since these biobanks originate from patient populations, there is a possibility of bias in polygenic risk estimation due to overrepresentation of patients with higher frequency of healthcare interactions.

PRS for schizophrenia, bipolar disorder, and depression were calculated using summary statistics from the largest available genomic studies for a sample of 24 153 European ancestry participants in the Mass General Brigham (MGB) Biobank. To correct for selection bias, we fitted logistic regression models with inverse probability (IP) weights, which were estimated using 1839 sociodemographic, clinical, and healthcare utilization features extracted from electronic health records of 1 546 440 non-Hispanic White patients eligible to participate in the Biobank study at their first visit to the MGB-affiliated hospitals.

Case prevalence of bipolar disorder among participants in the top decile of bipolar disorder PRS was 10.0% (95% CI 8.8–11.2%) in the unweighted analysis but only 6.2% (5.0–7.5%) when selection bias was accounted for using IP weights. Similarly, case prevalence of depression among those in the top decile of depression PRS was reduced from 33.5% (31.7–35.4%) to 28.9% (25.8–31.9%) after IP weighting.

Non-random selection of participants into volunteer biobanks may induce clinically relevant selection bias that could impact implementation of PRS in research and clinical settings. As efforts to integrate PRS in medical practice expand, recognition and mitigation of these biases should be considered and may need to be optimized in a context-specific manner.

Social cognition refers to a complex set of mental abilities that support the construction of adequate social competence and adaptation. Impairments in social cognition can be found in several psychiatric disorders, particularly in psychoses. Polygenic Risk Scores (PRSs) represent single metrics of molecular genetic risk and are a predictor of the genetic susceptibility to diseases, although they explain only a small part of the risk.

To explore the association between PRS for psychiatric disorders and social cognition.

We conducted a systematic search in PubMed and Scopus according to the PRISMA guidelines up to August 2021. We included papers evaluating PRS and social cognition with psychometric scales. Articles concerning single-nucleotide polymorphisms and biological measures of social cognition (e.g., neuroimaging, peripheral biomarkers) were excluded.

We initially retrieved 150 articles. After removing duplicates, we screened 133 titles and abstracts and preliminary selected 19 papers. Participants recruited in the papers of interest were either people with schizophrenia, ASD or ADHD, their family members or healthy subjects. Articles evaluated the association between different psychometrical measures of social cognition and PRS for schizophrenia, Autism Spectrum Disorder and ADHD.

Literature regarding the association between PRS for psychiatric disorders and social cognition is heterogeneous in terms of populations, genetic risk evaluation, and outcome tools. Given the critical role played by social cognition in the onset and progression of mental disorders and its association with real-world functioning, future research should try to disentangle the complex genetic basis of this domain.

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Clinical intervention in early stages of psychotic disorders is crucial for the prevention of severe symptomatology trajectories and poor outcomes. Genetic variability is studied as a promising modulator of prognosis, thus novel approaches considering the polygenic nature of these complex phenotypes are required to unravel the mechanisms underlying the early progression of the disorder.

The sample comprised of 233 first-episode psychosis (FEP) subjects with clinical and cognitive data assessed periodically for a 2-year period and 150 matched controls. Polygenic risk scores (PRSs) for schizophrenia, bipolar disorder, depression, education attainment and cognitive performance were used to assess the genetic risk of FEP and to characterize their association with premorbid, baseline and progression of clinical and cognitive status.

Schizophrenia, bipolar disorder and cognitive performance PRSs were associated with an increased risk of FEP [false discovery rate (FDR) ⩽ 0.027]. In FEP patients, increased cognitive PRSs were found for FEP patients with more cognitive reserve (FDR ⩽ 0.037). PRSs reflecting a genetic liability for improved cognition were associated with a better course of symptoms, functionality and working memory (FDR ⩽ 0.039). Moreover, the PRS of depression was associated with a worse trajectory of the executive function and the general cognitive status (FDR ⩽ 0.001).

Our study provides novel evidence of the polygenic bases of psychosis and its clinical manifestation in its first stage. The consistent effect of cognitive PRSs on the early clinical progression suggests that the mechanisms underlying the psychotic episode and its severity could be partially independent.