Effects of a neurodevelopmental genes based polygenic risk score for schizophrenia and single gene variants on brain structure in non-clinical subjects: A preliminary report

Psychosis Endophenotypes: A Gene-Set-Specific Polygenic Risk Score Analysis

BACKGROUND AND HYPOTHESIS

Endophenotypes can help to bridge the gap between psychosis and its genetic predispositions, but their underlying mechanisms remain largely unknown. This study aims to identify biological mechanisms that are relevant to the endophenotypes for psychosis, by partitioning polygenic risk scores into specific gene sets and testing their associations with endophenotypes.

STUDY DESIGN

We computed polygenic risk scores for schizophrenia and bipolar disorder restricted to brain-related gene sets retrieved from public databases and previous publications. Three hundred and seventy-eight gene-set-specific polygenic risk scores were generated for 4506 participants. Seven endophenotypes were also measured in the sample. Linear mixed-effects models were fitted to test associations between each endophenotype and each gene-set-specific polygenic risk score.

STUDY RESULTS

After correction for multiple testing, we found that a reduced P300 amplitude was associated with a higher schizophrenia polygenic risk score of the forebrain regionalization gene set (mean difference per SD increase in the polygenic risk score: -1.15 µV; 95% CI: -1.70 to -0.59 µV; P = 6 × 10-5). The schizophrenia polygenic risk score of forebrain regionalization also explained more variance of the P300 amplitude (R2 = 0.032) than other polygenic risk scores, including the genome-wide polygenic risk scores.

CONCLUSIONS

Our finding on reduced P300 amplitudes suggests that certain genetic variants alter early brain development thereby increasing schizophrenia risk years later. Gene-set-specific polygenic risk scores are a useful tool to elucidate biological mechanisms of psychosis and endophenotypes, offering leads for experimental validation in cellular and animal models.

Neurodevelopmental disturbances in schizophrenia: evidence from genetic and environmental factors

Since more than 3 decades, schizophrenia (SZ) has been regarded as a neurodevelopmental disorder. The neurodevelopmental hypothesis proposes that SZ is associated with genetic and environmental risk factors, which influence connectivity in neuronal circuits during vulnerable developmental periods. We carried out a non-systematic review of genetic/environmental factors that increase SZ risk in light of its neurodevelopmental hypothesis. We also reviewed the potential impact of SZ-related environmental and genetic risk factors on grey and white matter pathology and brain function based on magnetic resonance imaging and post-mortem studies. Finally, we reviewed studies that have used patient-derived neuronal models to gain knowledge of the role of genetic and environmental factors in early developmental stages. Taken together, these studies indicate that a variety of environmental factors may interact with genetic risk factors during the pre- or postnatal period and/or during adolescence to induce symptoms of SZ in early adulthood. These risk factors induce disturbances of macro- and microconnectivity in brain regions involving the prefrontal, temporal and parietal cortices and the hippocampus. On the molecular and cellular level, a disturbed synaptic plasticity, loss of oligodendrocytes and impaired myelination have been shown in brain regions of SZ patients. These cellular/histological phenotypes are related to environmental risk factors such as obstetric complications, maternal infections and childhood trauma and genetic risk factors identified in recent genome-wide association studies. SZ-related genetic risk may contribute to active processes interfering with synaptic plasticity in the adult brain. Advances in stem cell technologies are providing promising mechanistic insights into how SZ risk factors impact the developing brain. Further research is needed to understand the timing of the different complex biological processes taking place as a result of the interplay between genetic and environmental factors.

Specificity of Psychiatric Polygenic Risk Scores and their Effects on Associated Risk Phenotypes

Background

Polygenic risk scores (PRSs) are indices of genetic liability for illness, but their clinical utility for predicting risk for a specific psychiatric disorder is limited. Genetic overlap among disorders and their effects on allied phenotypes may be a possible explanation, but this has been difficult to quantify given focus on singular disorders and/or allied phenotypes.

Methods

We constructed PRSs for 5 psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder) and 3 nonpsychiatric control traits (height, type II diabetes, irritable bowel disease) in the UK Biobank (N = 31,616) and quantified associations between PRSs and phenotypes allied with mental illness: behavioral (symptoms, cognition, trauma) and brain measures from magnetic resonance imaging. We then evaluated the extent of specificity among PRSs and their effects on these allied phenotypes.

Results

Correlations among psychiatric PRSs replicated previous work, with overlap between schizophrenia and bipolar disorder, which was distinct from overlap between autism spectrum disorder and attention-deficit/hyperactivity disorder; overlap between psychiatric and control PRSs was minimal. There was, however, substantial overlap of PRS effects on allied phenotypes among psychiatric disorders and among psychiatric disorders and control traits, where the extent and pattern of overlap was phenotype specific.

Conclusions

Results show that genetic distinctions between psychiatric disorders and between psychiatric disorders and control traits exist, but this does not extend to their effects on allied phenotypes. Although overlap can be informative, work is needed to construct PRSs that will function at the level of specificity needed for clinical application.

Sex differences in schizophrenia: a longitudinal methylome analysis

DNA methylation analysis at the genome-wide level is a useful tool to explore potential sex differences in SCZ patients. The primary aim of the current study was to identify differentially methylated regions of DNA between males and females with schizophrenia. We collected DNA samples from 134 schizophrenia patients to measure genome-wide methylation at single-base resolution in 96 males and 38 females. We further repeated the analysis in 13 subjects (9 females, 4 males) to confirm the sex differences and to reduce the effect of potential confounders. The longitudinal methylation analysis found significant replication of several genes across the genome. These genes included RFTN1, TLE1, DAZL, PRR4, UTP14C, RNU12, and LOC644649. The overall results showed robust association between autosomal CpG sites and sex. Longitudinal methylation analysis can be used as internal replication to confirm epigenetic variants that are stable over time.

Cross-diagnostic evaluation of minor physical anomalies in psychiatric disorders

BACKGROUND

Minor physical anomalies (MPA) are markers of impaired neurodevelopment during the prenatal stage. Assessing MPA across psychiatric disorders may help understand their shared nature. In addition, MPA in family members would indicate a shared liability and endophenotype potential. We examined familial aggregation of MPA and their role as transdiagnostic and disorder-specific markers of 5 major psychiatric/neuropsychiatric conditions (schizophrenia, bipolar disorder, substance dependence, obsessive-compulsive disorder, and Alzheimer's dementia).

METHODS

Modified Waldrop's MPA scale was applied on 1321 individuals from 439 transdiagnostic multiplex families and 125 healthy population controls (HC). Stage of fetal development (morphogenetic/phenogenetic)- and anatomical location (craniofacial/peripheral)-based sub-scores were calculated. Familiality and endophenotypic potential of MPA were analyzed with serial negative binomial mixed-effect regression. Cross-diagnostic differences and the effect of family history density (FHD) of each diagnosis on MPA were assessed. Mixed-effects Cox models estimated the influence of MPA on age-at-onset of illness (AAO).

RESULTS

MPA were found to be heritable in families with psychiatric disorders, with a familiality of 0.52. MPA were higher in psychotic disorders after controlling for effects of sex and intrafamilial correlation. Morphogenetic variant MPA was noted to be lower in dementia in comparison to HC. FHD of schizophrenia and bipolar disorder predicted higher, and that of dementia and substance dependence predicted lower MPA. MPA brought forward the AAO [HR:1.07 (1.03-1.11)], and this was more apparent in psychotic disorders.

CONCLUSION

MPA are transmissible in families, are specifically related to the risk of developing psychoses, and predict an earlier age at onset. Neurodevelopmentally informed classification of MPA has the potential to enhance the etiopathogenic and translational understanding of psychiatric disorders.

Effects of polygenic risk for major mental disorders and cross-disorder on cortical complexity

BACKGROUND

MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood.

METHODS

We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness.

RESULTS

The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing.

CONCLUSIONS

Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.