Polygenic risk score increases schizophrenia liability through cognition-relevant pathways

Single-cell multi-cohort dissection of the schizophrenia transcriptome

The complexity and heterogeneity of schizophrenia have hindered mechanistic elucidation and the development of more effective therapies. Here, we performed single-cell dissection of schizophrenia-associated transcriptomic changes in the human prefrontal cortex across 140 individuals in two independent cohorts. Excitatory neurons were the most affected cell group, with transcriptional changes converging on neurodevelopment and synapse-related molecular pathways. Transcriptional alterations included known genetic risk factors, suggesting convergence of rare and common genomic variants on neuronal population-specific alterations in schizophrenia. Based on the magnitude of schizophrenia-associated transcriptional change, we identified two populations of individuals with schizophrenia marked by expression of specific excitatory and inhibitory neuronal cell states. This single-cell atlas links transcriptomic changes to etiological genetic risk factors, contextualizing established knowledge within the human cortical cytoarchitecture and facilitating mechanistic understanding of schizophrenia pathophysiology and heterogeneity.

Polygenic risk scores mediating functioning outcomes through cognitive and clinical features in youth at family risk and controls

Schizophrenia and bipolar disorder exhibit substantial clinical overlap, particularly in individuals at familial high risk, who frequently present sub-threshold symptoms before the onset of illness. Severe mental disorders are highly polygenic traits, but their impact on the stages preceding the manifestation of mental disorders remains relatively unexplored. Our study aimed to examine the influence of polygenic risk scores (PRS) on sub-clinical outcomes over a 2-year period in youth at familial high risk for schizophrenia and bipolar disorder and controls. The sample included 222 children and adolescents, comprising offspring of parents with schizophrenia (n = 38), bipolar disorder (n = 80), and community controls (n = 104). We calculated PRS for psychiatric disorders, neuroticism and cognition using the PRS-CS method. Linear mixed-effects models were employed to investigate the association between PRS and cognition, symptom severity and functioning. Mediation analyses were conducted to explore whether clinical features acted as intermediaries in the impact of PRS on functioning outcomes. SZoff exhibited elevated PRS for schizophrenia. In the entire sample, PRS for depression, neuroticism, and cognitive traits showed associations with sub-clinical features. The effect of PRS for neuroticism and general intelligence on functioning outcomes were mediated by cognition and symptoms severity, respectively. This study delves into the interplay among genetics, the emergence of sub-clinical symptoms and functioning outcomes, providing novel evidence on mechanisms underpinning the continuum from sub-threshold features to the onset of mental disorders. The findings underscore the interplay of genetics, cognition, and clinical features, providing insights for personalized early interventions.

Clinical Application of Polygenic Risk Score in IgA Nephropathy

Genome-wide association studies (GWASs) have identified 30 independent genetic variants associated with IgA nephropathy (IgAN). A genetic risk score (GRS) represents the number of risk alleles carried and thus captures an individual's genetic risk. However, whether and which polygenic risk score crucial for the evaluation of any potential personal or clinical utility on risk and prognosis are still obscure. We constructed different GRS models based on different sets of variants, which were top single nucleotide polymorphisms (SNPs) reported in the previous GWASs. The case-control GRS analysis included 3365 IgAN patients and 8842 healthy individuals. The association between GRS and clinical variability, including age at diagnosis, clinical parameters, Oxford pathology classification, and kidney prognosis was further evaluated in a prospective cohort of 1747 patients. Three GRS models (15 SNPs, 21 SNPs, and 55 SNPs) were constructed after quality control. The patients with the top 20% GRS had 2.42-(15 SNPs, p = 8.12 × 10-40), 3.89-(21 SNPs, p = 3.40 × 10-80) and 3.73-(55 SNPs, p = 6.86 × 10-81) fold of risk to develop IgAN compared to the patients with the bottom 20% GRS, with area under the receiver operating characteristic curve (AUC) of 0.59, 0.63, and 0.63 in group discriminations, respectively. A positive correlation between GRS and microhematuria, mesangial hypercellularity, segmental glomerulosclerosis and a negative correlation on the age at diagnosis, body mass index (BMI), mean arterial pressure (MAP), serum C3, triglycerides can be observed. Patients with the top 20% GRS also showed a higher risk of worse prognosis for all three models (1.36, 1.42, and 1.36 fold of risk) compared to the remaining 80%, whereas 21 SNPs model seemed to show a slightly better fit in prediction. Collectively, a higher burden of risk variants is associated with earlier disease onset and a higher risk of a worse prognosis. This may be informational in translating knowledge on IgAN genetics into disease risk prediction and patient stratification.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-023-00138-6.

Genome-wide DNA methylation risk scores for schizophrenia derived from blood and brain tissues further explain the genetic risk in patients stratified by polygenic risk scores for schizophrenia and bipolar disorder

BACKGROUND

Genetic and environmental factors contribute to the pathogenesis of schizophrenia (SZ) and bipolar disorder (BD). Among genetic risk groups stratified by combinations of Polygenic Risk Score (PRS) deciles for SZ, BD and SZ versus BD, genetic SZ risk groups had high SZ risk and prominent cognitive impairments. Furthermore, epigenetic alterations are implicated in these disorders. However, it was unclear whether DNA Methylation Risk Scores (MRSs) for SZ risk derived from blood and brain tissues were associated with SZ risk, particularly the PRS-stratified genetic SZ risk group.

METHODS

Epigenome-wide association studies (EWASs) of SZ risk in whole blood were preliminarily conducted between 66 SZ patients and 30 healthy controls (HCs) and among genetic risk groups (individuals with low genetic risk for SZ and BD in HCs (n=30) and in SZ patients (n=11), genetic BD risk in SZ patients (n=25) and genetic SZ risk in SZ patients (n=30)) stratified by combinations of PRSs for SZ, BD and SZ versus BD. Next, differences in MRSs based on independent EWASs of SZ risk in whole blood, postmortem frontal cortex (FC) and superior temporal gyrus (STG) were investigated among our case‒control and PRS-stratified genetic risk status groups.

RESULTS

Among case‒control and genetic risk status groups, 33 and 351 genome-wide significant differentially methylated positions (DMPs) associated with SZ were identified, respectively, many of which were hypermethylated. Compared with the low genetic risk in HCs group, the genetic SZ risk in SZ group had 39 genome-wide significant DMPs, while the genetic BD risk in SZ group had only six genome-wide significant DMPs. The MRSs for SZ risk derived from whole blood, FC and STG were higher in our SZ patients than in HCs in whole blood and were particularly higher in the genetic SZ risk in SZ group than in the low genetic risk in HCs and genetic BD risk in SZ groups. Conversely, the MRSs for SZ risk based on our whole-blood EWASs among genetic risk groups were also associated with SZ in the FC and STG. There were no correlations between the MRSs and PRSs.

CONCLUSIONS

These findings suggest that the MRS is a potential genetic marker in understanding SZ, particularly in patients with a genetic SZ risk.

Dissecting Schizotypy and Its Association With Cognition and Polygenic Risk for Schizophrenia in a Nonclinical Sample

Schizotypy is a multidimensional construct that captures a continuum of risk for developing schizophrenia-spectrum psychopathology. Existing 3-factor models of schizotypy, consisting of positive, negative, and disorganized dimensions have yielded mixed evidence of genetic continuity with schizophrenia using polygenic risk scores. Here, we propose an approach that involves splitting positive and negative schizotypy into more specific subdimensions that are phenotypically continuous with distinct positive symptoms and negative symptoms recognized in clinical schizophrenia. We used item response theory to derive high-precision estimates of psychometric schizotypy using 251 self-report items obtained from a non-clinical sample of 727 (424 females) adults. These subdimensions were organized hierarchically using structural equation modeling into 3 empirically independent higher-order dimensions enabling associations with polygenic risk for schizophrenia to be examined at different levels of phenotypic generality and specificity. Results revealed that polygenic risk for schizophrenia was associated with variance specific to delusional experiences (γ = 0.093, P = .001) and reduced social interest and engagement (γ = 0.076, P = .020), and these effects were not mediated via the higher-order general, positive, or negative schizotypy factors. We further fractionated general intellectual functioning into fluid and crystallized intelligence in 446 (246 females) participants that underwent onsite cognitive assessment. Polygenic risk scores explained 3.6% of the variance in crystallized intelligence. Our precision phenotyping approach could be used to enhance the etiologic signal in future genetic association studies and improve the detection and prevention of schizophrenia-spectrum psychopathology.

Cognitive performances across individuals at high genetic risk for schizophrenia, high genetic risk for bipolar disorder, and low genetic risks: a combined polygenic risk score approach

BACKGROUND

Individuals with schizophrenia (SCZ) and bipolar disorder (BD) display cognitive impairments, but the impairments in those with SCZ are more prominent, supported by genetic overlap between SCZ and cognitive impairments. However, it remains unclear whether cognitive performances differ between individuals at high and low genetic risks for SCZ or BD.

METHODS

Using the latest Psychiatric Genomics Consortium (PGC) data, we calculated PGC3 SCZ-, PGC3 BD-, and SCZ v. BD polygenic risk scores (PRSs) in 173 SCZ patients, 70 unaffected first-degree relatives (FRs) and 196 healthy controls (HCs). Based on combinations of three PRS deciles, individuals in the genetic SCZ, genetic BD and low genetic risk groups were extracted. Cognitive performance was assessed by the Brief Assessment of Cognition in Schizophrenia.

RESULTS

SCZ-, BD-, SCZ v. BD-PRSs were associated with case-control status (R2 = 0.020-0.061), and SCZ-PRS was associated with relative-control status (R2 = 0.023). Furthermore, individuals in the highest decile for SCZ PRSs had elevated BD-PRSs [odds ratio (OR) = 6.33] and SCZ v. BD-PRSs (OR = 1.86) compared with those in the lowest decile. Of the three genetic risk groups, the low genetic risk group contained more HCs, whereas the genetic BD and SCZ groups contained more SCZ patients (p < 0.05). SCZ patients had widespread cognitive impairments, and FRs had cognitive impairments that were between those of SCZ patients and HCs (p < 0.05). Cognitive differences between HCs in the low genetic risk group and SCZ patients in the genetic BD or genetic SCZ groups were more prominent (Cohen's d > -0.20) than those between HCs and SCZ patients in the no genetic risk group. Furthermore, SCZ patients in the genetic SCZ group displayed lower scores in verbal fluency and attention than those in the genetic BD group (d > -0.20).

CONCLUSIONS

Our findings suggest that cognitive impairments in SCZ are partially mediated through genetic loadings for SCZ but not BD.

Link between cognitive polygenic risk scores and clinical progression after a first-psychotic episode

BACKGROUND

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.

METHODS

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.

RESULTS

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).

CONCLUSIONS

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.

Cognitive impairment in schizophrenia: aetiology, pathophysiology, and treatment

Cognitive deficits are a core feature of schizophrenia, account for much of the impaired functioning associated with the disorder and are not responsive to existing treatments. In this review, we first describe the clinical presentation and natural history of these deficits. We then consider aetiological factors, highlighting how a range of similar genetic and environmental factors are associated with both cognitive function and schizophrenia. We then review the pathophysiological mechanisms thought to underlie cognitive symptoms, including the role of dopamine, cholinergic signalling and the balance between GABAergic interneurons and glutamatergic pyramidal cells. Finally, we review the clinical management of cognitive impairments and candidate novel treatments.

Cerebellar Functional Dysconnectivity in Drug-Naïve Patients With First-Episode Schizophrenia

BACKGROUND

Cerebellar functional dysconnectivity has long been implicated in schizophrenia. However, the detailed dysconnectivity pattern and its underlying biological mechanisms have not been well-charted. This study aimed to conduct an in-depth characterization of cerebellar dysconnectivity maps in early schizophrenia.

STUDY DESIGN

Resting-state fMRI data were processed from 196 drug-naïve patients with first-episode schizophrenia and 167 demographically matched healthy controls. The cerebellum was parcellated into nine functional systems based on a state-of-the-art atlas, and seed-based connectivity for each cerebellar system was examined. The observed connectivity alterations were further associated with schizophrenia risk gene expressions using data from the Allen Human Brain Atlas.

STUDY RESULTS

Overall, we observed significantly increased cerebellar connectivity with the sensorimotor cortex, default-mode regions, ventral part of visual cortex, insula, and striatum. In contrast, decreased connectivity was shown chiefly within the cerebellum, and between the cerebellum and the lateral prefrontal cortex, temporal lobe, and dorsal visual areas. Such dysconnectivity pattern was statistically similar across seeds, with no significant group by seed interactions identified. Moreover, connectivity strengths of hypoconnected but not hyperconnected regions were significantly correlated with schizophrenia risk gene expressions, suggesting potential genetic underpinnings for the observed hypoconnectivity.

CONCLUSIONS

These findings suggest a common bidirectional dysconnectivity pattern across different cerebellar subsystems, and imply that such bidirectional alterations may relate to different biological mechanisms.

Polygenic risk scores for schizophrenia are associated with oculomotor endophenotypes

BACKGROUND

Schizophrenia is a heterogeneous disorder with substantial heritability. The use of endophenotypes may help clarify its aetiology. Measures from the smooth pursuit and antisaccade eye movement tasks have been identified as endophenotypes for schizophrenia in twin and family studies. However, the genetic basis of the overlap between schizophrenia and these oculomotor markers is largely unknown. Here, we tested whether schizophrenia polygenic risk scores (PRS) were associated with oculomotor performance in the general population.

METHODS

Analyses were based on the data of 2956 participants (aged 30-95) of the Rhineland Study, a community-based cohort study in Bonn, Germany. Genotyping was performed on Omni-2.5 exome arrays. Using summary statistics from a recent meta-analysis based on the two largest schizophrenia genome-wide association studies to date, we quantified genetic risk for schizophrenia by creating PRS at different p value thresholds for genetic markers. We examined associations between PRS and oculomotor performance using multivariable regression models.

RESULTS

Higher PRS were associated with higher antisaccade error rate and latency, and lower antisaccade amplitude gain. PRS showed inconsistent patterns of association with smooth pursuit velocity gain and were not associated with saccade rate during smooth pursuit or performance on a prosaccade control task.

CONCLUSIONS

There is an overlap between genetic determinants of schizophrenia and oculomotor endophenotypes. Our findings suggest that the mechanisms that underlie schizophrenia also affect oculomotor function in the general population.

Third-generation genome sequencing implicates medium-sized structural variants in chronic schizophrenia

Background

Schizophrenia (SCZ) is a heterogeneous psychiatric disorder, with significant contribution from genetic factors particularly for chronic cases with negative symptoms and cognitive deficits. To date, Genome Wide Association Studies (GWAS) and exome sequencing have associated SCZ with a number of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs), but there is still missing heritability. Medium-sized structural variants (SVs) are difficult to detect using SNP arrays or second generation sequencing, and may account for part of the missing heritability of SCZ.

Aims and objectives

To identify SVs associated with severe chronic SCZ across the whole genome.

Study design

10 multiplex families with probands suffering from chronic SCZ with negative symptoms and cognitive deficits were recruited, with all their affected members demonstrating uni-lineal inheritance. Control subjects comprised one affected member from the affected lineage, and unaffected members from each paternal and maternal lineage.

Methods

Third generation sequencing was applied to peripheral blood samples from 10 probands and 5 unaffected controls. Bioinformatic tools were used to identify SVs from the long sequencing reads, with confirmation of findings in probands by short-read Illumina sequencing, Sanger sequencing and visual manual validation with Integrated Genome Browser.

Results

In the 10 probands, we identified and validated 88 SVs (mostly in introns and medium-sized), within 79 genes, which were absent in the 5 unaffected control subjects. These 79 genes were enriched in 20 biological pathways which were related to brain development, neuronal migration, neurogenesis, neuronal/synaptic function, learning/memory, and hearing. These identified SVs also showed evidence for enrichment of genes that are highly expressed in the adolescent striatum.

Conclusion

A substantial part of the missing heritability in SCZ may be explained by medium-sized SVs detectable only by third generation sequencing. We have identified a number of such SVs potentially conferring risk for SCZ, which implicate multiple brain-related genes and pathways. In addition to previously-identified pathways involved in SCZ such as neurodevelopment and neuronal/synaptic functioning, we also found novel evidence for enrichment in hearing-related pathways and genes expressed in the adolescent striatum.

Genetic and Structural Brain Correlates of Cognitive Subtypes Across Youth at Family Risk for Schizophrenia and Bipolar Disorder

OBJECTIVE

Cognitive impairment is an important feature of schizophrenia (SZ) and bipolar disorder (BP) with severity across the two disorders characterized by significant heterogeneity. Youth at family risk for SZ and BP were clustered based on cognitive function and examined in terms of the clinical, genetic, and brain imaging correlates of cluster membership.

METHOD

One hundred sixty participants, 32 offspring of patients with SZ, 59 offspring of patients with BP and 69 offspring of healthy control parents underwent clinical and cognitive assessments, genotyping and structural MRI. K-means clustering was used to group family risk participants based on cognitive measures. Clusters were compared in terms of cortical and subcortical brain measures as well as polygenic risk scores.

RESULTS

Participants were grouped in 3 clusters with intact, intermediate, and impaired cognitive performance. The intermediate and impaired clusters had lower total brain surface area compared with the intact cluster, with prominent localization in frontal and temporal cortices. No between-cluster differences were identified in cortical thickness and subcortical brain volumes. The impaired cluster also had poorer psychosocial functioning and worse PRS-COG compared with the other 2 clusters and with offspring of healthy control parents, while there was no significant between-cluster difference in terms of PRS-SZ and PRS-BP. PRS-COG predicted psychosocial functioning, yet this effect did not appear to be mediated by an effect of PRS-COG on brain area.

CONCLUSION

Stratification based on cognition may help to elucidate the biological underpinnings of cognitive heterogeneity across SZ and BP risk.

Brain-wide versus genome-wide vulnerability biomarkers for severe mental illnesses

Severe mental illnesses (SMI), including major depressive (MDD), bipolar (BD), and schizophrenia spectrum (SSD) disorders have multifactorial risk factors and capturing their complex etiopathophysiology in an individual remains challenging. Regional vulnerability index (RVI) was used to measure individual's brain-wide similarity to the expected SMI patterns derived from meta-analytical studies. It is analogous to polygenic risk scores (PRS) that measure individual's similarity to genome-wide patterns in SMI. We hypothesized that RVI is an intermediary phenotype between genome and symptoms and is sensitive to both genetic and environmental risks for SMI. UK Biobank sample of N = 17,053/19,265 M/F (age = 64.8 ± 7.4 years) and an independent sample of SSD patients and controls (N = 115/111 M/F, age = 35.2 ± 13.4) were used to test this hypothesis. UKBB participants with MDD had significantly higher RVI-MDD (Cohen's d = 0.20, p = 1 × 10-23 ) and PRS-MDD (d = 0.17, p = 1 × 10-15 ) than nonpsychiatric controls. UKBB participants with BD and SSD showed significant elevation in the respective RVIs (d = 0.65 and 0.60; p = 3 × 10-5 and .009, respectively) and PRS (d = 0.57 and 1.34; p = .002 and .002, respectively). Elevated RVI-SSD were replicated in an independent sample (d = 0.53, p = 5 × 10-5 ). RVI-MDD and RVI-SSD but not RVI-BD were associated with childhood adversity (p < .01). In nonpsychiatric controls, elevation in RVI and PRS were associated with lower cognitive performance (p < 10-5 ) in six out of seven domains and showed specificity with disorder-associated deficits. In summary, the RVI is a novel brain index for SMI and shows similar or better specificity for SMI than PRS, and together they may complement each other in the efforts to characterize the genomic to brain level risks for SMI.

Striatal dopamine D2/3 receptors in medication-naïve schizophrenia: an [123I] IBZM SPECT study

BACKGROUND

The hyper-function of the striatal dopamine system has been suggested to underlie key pathophysiological mechanisms in schizophrenia. Moreover, patients have been observed to present a significant elevation of dopamine receptor availability compared to healthy controls. Although it is difficult to measure dopamine levels directly in humans, neurochemical imaging techniques such as single-photon emission computed tomography (SPECT) provide indirect indices of in vivo dopamine synthesis and release, and putative synaptic levels.

METHODS

We focused on the role of dopamine postsynaptic regulation using [¹²³I] iodobenzamide (IBZM) SPECT. We compared D_2/3 receptor availability between 53 healthy controls and 21 medication-naive patients with recent-onset schizophrenia.

RESULT

The mean specific striatal binding showed no significant difference between patients and controls (estimated difference = 0.001; 95% CI -0.11 to 0.11; F = 0.00, df = 1, 69; p = 0.99). There was a highly significant effect of age whereby IBZM binding declined with advancing age [estimated change per decade of age = -0.01(binding ratio); 95% CI -0.01 to -0.004; F = 11.5, df = 1, 69; p = 0.001]. No significant correlations were found between the mean specific striatal binding and psychopathological or cognitive rating scores.

CONCLUSIONS

Medication-naïve patients with recent-onset schizophrenia have similar D_2/3 receptor availability to healthy controls. We suggest that, rather than focusing exclusively on postsynaptic receptors, future treatments should target the presynaptic control of dopamine synthesis and release.

Within-family influences on dimensional neurobehavioral traits in a high-risk genetic model

BACKGROUND

Genotype-first and within-family studies can elucidate factors that contribute to psychiatric illness. Combining these approaches, we investigated the patterns of influence of parental scores, a high-impact variant, and schizophrenia on dimensional neurobehavioral phenotypes implicated in major psychiatric disorders.

METHODS

We quantitatively assessed cognitive (FSIQ, VIQ, PIQ), social, and motor functioning in 82 adult individuals with a de novo 22q11.2 deletion (22 with schizophrenia), and 148 of their unaffected parents. We calculated within-family correlations and effect sizes of the 22q11.2 deletion and schizophrenia, and used linear regressions to assess contributions to neurobehavioral measures.

RESULTS

Proband-parent intra-class correlations (ICC) were significant for cognitive measures (e.g. FSIQ ICC = 0.549, p < 0.0001), but not for social or motor measures. Compared to biparental scores, the 22q11.2 deletion conferred significant impairments for all phenotypes assessed (effect sizes -1.39 to -2.07 s.d.), strongest for PIQ. There were further decrements in those with schizophrenia. Regression models explained up to 37.7% of the variance in IQ and indicated that for proband IQ, parental IQ had larger effects than schizophrenia.

CONCLUSIONS

This study, for the first time, disentangles the impact of a high-impact variant from the modifying effects of parental scores and schizophrenia on relevant neurobehavioral phenotypes. The robust proband-parent correlations for cognitive measures, independent of the impact of the 22q11.2 deletion and of schizophrenia, suggest that, for certain phenotypes, shared genetic variation plays a significant role in expression. Molecular genetic and predictor studies are needed to elucidate shared factors and their contribution to psychiatric illness in this and other high-risk groups.

Cognitive Dysfunction as a Risk Factor for Psychosis

The current chapter summarizes recent evidence for cognition as a risk factor for the development of psychosis, including the range of cognitive impairments that exist across the spectrum of psychosis risk symptoms. The chapter examines several possible theories linking cognitive deficits with the development of psychotic symptoms, including evidence that cognitive deficits may be an intermediate risk factor linking genetic and/or neural metrics to psychosis spectrum symptoms. Although there is not strong evidence for unique cognitive markers associated specifically with psychosis compared to other forms of psychopathology, psychotic disorders are generally associated with the greatest severity of cognitive deficits. Cognitive deficits precede the development of psychotic symptoms and may be detectable as early as childhood. Across the psychosis spectrum, both the presence and severity of psychotic symptoms are associated with mild to moderate impairments across cognitive domains, perhaps most consistently for language, cognitive control, and working memory domains. Research generally indicates the size of these cognitive impairments worsens as psychosis symptom severity increases. The chapter points out areas of unclarity and unanswered questions in each of these areas, including regarding the mechanisms contributing to the association between cognition and psychosis, the timing of deficits, and whether any cognitive systems can be identified that function as specific predictors of psychosis risk symptoms.

First-Episode Psychosis Patients Who Deteriorated in the Premorbid Period Do Not Have Higher Polygenic Risk Scores Than Others: A Cluster Analysis of EU-GEI Data

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.

Contribution of brain network connectivity in predicting effects of polygenic risk and childhood trauma on state-trait anxiety

BACKGROUND

Anxiety is usually attributed to adverse environmental factors, but it is known as a polygenic inheritance disease. Gene-environment interactions on the occurrence and severity of anxiety are still unclear. The role of brain network connectivity in the gene-environment effects on anxiety has not been explored and may be key to understanding neuropathogenesis and guiding treatment.

METHODS

This study recruited 177 young adults from the community that completed functional magnetic resonance imaging, Childhood Trauma Questionnaire (CTQ), state-trait anxiety scores, and whole exome sequencing. We calculated polygenic risk score (PRS) for anxiety and the sum score of CTQ, which are genetic and environmental factors that may affect anxiety, respectively. Abnormal brain network connectivity determined by the gene-environment effects and its associations with anxiety scores were then explored.

RESULTS

Except for the main effect of PRS or CTQ on intra-network connectivity, significant interactions were found in intra-network connectivity of visual network, default mode network, self-reference network, and sensorimotor network. Moreover, altered network connectivity was related to anxious tendency. In particular, the effect of CTQ on trait anxiety was mediated by the disrupted sensorimotor network, accompanied by a significant direct effect. However, the PRS influence on anxiety was mainly mediated through sensorimotor network paths, which exceeded the direct influence and was moderated by childhood trauma levels.

CONCLUSIONS

These network-specific functional changes related to individual gene-environment risks advance our understanding of psychiatric pathogenesis of anxiety and provide new insights for clinical intervention.

Heritability of specific cognitive functions and associations with schizophrenia spectrum disorders using CANTAB: a nation-wide twin study

BACKGROUND

Many cognitive functions are under strong genetic control and twin studies have demonstrated genetic overlap between some aspects of cognition and schizophrenia. How the genetic relationship between specific cognitive functions and schizophrenia is influenced by IQ is currently unknown.

METHODS

We applied selected tests from the Cambridge Neuropsychological Test Automated Battery (CANTAB) to examine the heritability of specific cognitive functions and associations with schizophrenia liability. Verbal and performance IQ were estimated using The Wechsler Adult Intelligence Scale-III and the Danish Adult Reading Test. In total, 214 twins including monozygotic (MZ = 32) and dizygotic (DZ = 22) pairs concordant or discordant for a schizophrenia spectrum disorder, and healthy control pairs (MZ = 29, DZ = 20) were recruited through the Danish national registers. Additionally, eight twins from affected pairs participated without their sibling.

RESULTS

Significant heritability was observed for planning/spatial span (h² = 25%), self-ordered spatial working memory (h² = 64%), sustained attention (h² = 56%), and movement time (h² = 47%), whereas only unique environmental factors contributed to set-shifting, reflection impulsivity, and thinking time. Schizophrenia liability was associated with planning/spatial span (r_ph = -0.34), self-ordered spatial working memory (r_ph = -0.24), sustained attention (r_ph = -0.23), and set-shifting (r_ph = -0.21). The association with planning/spatial span was not driven by either performance or verbal IQ. The remaining associations were shared with performance, but not verbal IQ.

CONCLUSIONS

This study provides further evidence that some cognitive functions are heritable and associated with schizophrenia, suggesting a partially shared genetic etiology. These functions may constitute endophenotypes for the disorder and provide a basis to explore genes common to cognition and schizophrenia.

Contribution of schizophrenia polygenic burden to longitudinal phenotypic variance in 22q11.2 deletion syndrome

While the recurrent 22q11.2 deletion is one of the strongest genetic risk factors for schizophrenia (SCZ), variability of its associated neuropsychiatric endophenotypes reflects its incomplete penetrance for psychosis development. To assess whether this phenotypic variability is linked to common variants associated with SCZ, we studied the association between SCZ polygenic risk score (PRS) and longitudinally acquired phenotypic information of the Swiss 22q11.2DS cohort (n = 97, 50% females, mean age 17.7 yr, mean visit interval 3.8 yr). The SCZ PRS with the best predictive performance was ascertained in the Estonian Biobank (n = 201,146) with LDpred. The infinitesimal SCZ PRS model showed the strongest capacity in discriminating SCZ cases from controls with one SD difference in SCZ PRS corresponding to an odds ratio (OR) of 1.73 (95% CI 1.57-1.90, P = 1.47 × 10^-29). In 22q11.2 patients, random-effects ordinal regression modelling using longitudinal data showed SCZ PRS to have the strongest effect on social anhedonia (OR = 2.09, P = 0.0002), and occupational functioning (OR = 1.82, P = 0.0003) within the negative symptoms course, and dysphoric mood (OR = 2.00, P = 0.002) and stress intolerance (OR = 1.76, P = 0.0002) within the general symptoms course. Genetic liability for SCZ was additionally associated with full scale cognitive decline (β = -0.25, P = 0.02) and with longitudinal volumetric reduction of the right and left hippocampi (β = -0.28, P = 0.005; β = -0.23, P = 0.02, respectively). Our results indicate that the polygenic contribution to SCZ acts upon the threshold-lowering first hit (i.e., the deletion). It modifies the endophenotypes of 22q11.2DS and augments the derailment of developmental trajectories of negative and general symptoms, cognition, and hippocampal volume.

Cerebellar gray matter volume changes in patients with schizophrenia: A voxel-based meta-analysis

BACKGROUND

In schizophrenia, the structural changes in the cerebellum are associated with patients' cognition and motor deficits. However, the findings are inconsistent owing to the heterogeneity in sample size, magnetic resonance imaging (MRI) scanners, and other factors among them. In this study, we conducted a meta-analysis to characterize the anatomical changes in cerebellar subfields in patients with schizophrenia.

METHODS

Systematic research was conducted to identify studies that compare the gray matter volume (GMV) differences in the cerebellum between patients with schizophrenia and healthy controls with a voxel-based morphometry (VBM) method. A coordinate-based meta-analysis was adopted based on seed-based d mapping (SDM) software. An exploratory meta-regression analysis was conducted to associate clinical and demographic features with cerebellar changes.

RESULTS

Of note, 25 studies comprising 996 patients with schizophrenia and 1,109 healthy controls were included in the present meta-analysis. In patients with schizophrenia, decreased GMVs were demonstrated in the left Crus II, right lobule VI, and right lobule VIII, while no increased GMV was identified. In the meta-regression analysis, the mean age and illness duration were negatively associated with the GMV in the left Crus II in patients with schizophrenia.

CONCLUSION

The most significant structural changes in the cerebellum are mainly located in the posterior cerebellar hemisphere in patients with schizophrenia. The decreased GMVs of these regions might partly explain the cognitive deficits and motor symptoms in patients with schizophrenia.

Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction

Schizophrenia (SCZ) is a debilitating neuropsychiatric disorder with high heritability and complex inheritance. In the past decade, successful identification of numerous susceptibility loci has provided useful insights into the molecular etiology of SCZ. However, applications of these findings to clinical classification and diagnosis, risk prediction, or intervention for SCZ have been limited, and elucidating the underlying genomic and molecular mechanisms of SCZ is still challenging. More recently, multiple Omics technologies - genomics, transcriptomics, epigenomics, proteomics, metabolomics, connectomics, and gut microbiomics - have all been applied to examine different aspects of SCZ pathogenesis. Integration of multi-Omics data has thus emerged as an approach to provide a more comprehensive view of biological complexity, which is vital to enable translation into assessments and interventions of clinical benefit to individuals with SCZ. In this review, we provide a broad survey of the single-omics studies of SCZ, summarize the advantages and challenges of different Omics technologies, and then focus on studies in which multiple omics data are integrated to unravel the complex pathophysiology of SCZ. We believe that integration of multi-Omics technologies would provide a roadmap to create a more comprehensive picture of interactions involved in the complex pathogenesis of SCZ, constitute a rich resource for elucidating the potential molecular mechanisms of the illness, and eventually improve clinical assessments and interventions of SCZ to address clinical translational questions from bench to bedside.

Evidence for the Association between the Intronic Haplotypes of Ionotropic Glutamate Receptors and First-Episode Schizophrenia

The heritable component of schizophrenia (SCH) as a polygenic trait is represented by numerous variants from a heterogeneous group of genes each contributing a relatively small effect. Various SNPs have already been found and analyzed in genes encoding the NMDAR subunits. However, less is known about genetic variations of genes encoding the AMPA and kainate receptor subunits. We analyzed sixteen iGluR genes in full length to determine the sequence variability of iGluR genes. Our aim was to describe the rate of genetic variability, its distribution, and the co-occurrence of variants and to identify new candidate risk variants or haplotypes. The cumulative effect of genetic risk was then estimated using a simple scoring model. GRIN2A-B, GRIN3A-B, and GRIK4 genes showed significantly increased genetic variation in SCH patients. The fixation index statistic revealed eight intronic haplotypes and an additional four intronic SNPs within the sequences of iGluR genes associated with SCH (p < 0.05). The haplotypes were used in the proposed simple scoring model and moreover as a test for genetic predisposition to schizophrenia. The positive likelihood ratio for the scoring model test reached 7.11. We also observed 41 protein-altering variants (38 missense variants, four frameshifts, and one nonsense variant) that were not significantly associated with SCH. Our data suggest that some intronic regulatory regions of iGluR genes and their common variability are among the components from which the genetic predisposition to SCH is composed.

Causal associations of intelligence with schizophrenia and bipolar disorder: A Mendelian randomization analysis

Background

Intelligence is inversely associated with schizophrenia (SCZ) and bipolar disorder (BD); it remains unclear whether low intelligence is a cause or consequence. We investigated causal associations of intelligence with SCZ or BD risk and a shared risk between SCZ and BD and SCZ-specific risk.

Methods

To estimate putative causal associations, we performed multi-single nucleotide polymorphism (SNP) Mendelian randomization (MR) using generalized summary-data-based MR (GSMR). Summary-level datasets from five GWASs (intelligence, SCZ vs. control [CON], BD vs. CON, SCZ + BD vs. CON, and SCZ vs. BD; sample sizes of up to 269,867) were utilized.

Results

A strong bidirectional association between risks for SCZ and BD was observed (odds ratio; OR_SCZ → BD = 1.47, p = 2.89 × 10⁻⁴¹, OR_BD → SCZ = 1.44, p = 1.85 × 10⁻⁵²). Low intelligence was bidirectionally associated with a high risk for SCZ, with a stronger effect of intelligence on SCZ risk (OR_{lower intelligence → SCZ} = 1.62, p = 3.23 × 10⁻¹⁴) than the reverse (OR_{SCZ → lower intelligence} = 1.06, p = 3.70 × 10⁻²³). Furthermore, low intelligence affected a shared risk between SCZ and BD (OR _{lower intelligence → SCZ + BD} = 1.23, p = 3.41 × 10⁻⁵) and SCZ-specific risk (OR_{lower intelligence → SCZvsBD} = 1.64, p = 9.72 × 10⁻¹⁰); the shared risk (OR_{SCZ + BD → lower intelligence} = 1.04, p = 3.09 × 10⁻¹⁴) but not SCZ-specific risk (OR_{SCZvsBD → lower intelligence} = 1.00, p = 0.88) weakly affected low intelligence. Conversely, there was no significant causal association between intelligence and BD risk (p > 0.05).

Conclusions

These findings support observational studies showing that patients with SCZ display impairment in premorbid intelligence and intelligence decline. Moreover, a shared factor between SCZ and BD might contribute to impairment in premorbid intelligence and intelligence decline but SCZ-specific factors might be affected by impairment in premorbid intelligence. We suggest that patients with these genetic factors should be categorized as having a cognitive disorder SCZ or BD subtype.

The Role of Electronic Health Records in Advancing Genomic Medicine

Recent advances in genomic technology and widespread adoption of electronic health records (EHRs) have accelerated the development of genomic medicine, bringing promising research findings from genome science into clinical practice. Genomic and phenomic data, accrued across large populations through biobanks linked to EHRs, have enabled the study of genetic variation at a phenome-wide scale. Through new quantitative techniques, pleiotropy can be explored with phenome-wide association studies, the occurrence of common complex diseases can be predicted using the cumulative influence of many genetic variants (polygenic risk scores), and undiagnosed Mendelian syndromes can be identified using EHR-based phenotypic signatures (phenotype risk scores). In this review, we trace the role of EHRs from the development of genome-wide analytic techniques to translational efforts to test these new interventions to the clinic. Throughout, we describe the challenges that remain when combining EHRs with genetics to improve clinical care.

Development and validation of a novel survival model for acute myeloid leukemia based on autophagy-related genes

Background

Acute myeloid leukemia (AML) is one of the most common blood cancers, and is characterized by impaired hematopoietic function and bone marrow (BM) failure. Under normal circumstances, autophagy may suppress tumorigenesis, however under the stressful conditions of late stage tumor growth autophagy actually protects tumor cells, so inhibiting autophagy in these cases also inhibits tumor growth and promotes tumor cell death.

Methods

AML gene expression profile data and corresponding clinical data were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, from which prognostic-related genes were screened to construct a risk score model through LASSO and univariate and multivariate Cox analyses. Then the model was verified in the TCGA cohort and GEO cohorts. In addition, we also analyzed the relationship between autophagy genes and immune infiltrating cells and therapeutic drugs.

Results

We built a model containing 10 autophagy-related genes to predict the survival of AML patients by dividing them into high- or low-risk subgroups. The high-risk subgroup was prone to a poorer prognosis in both the training TCGA-LAML cohort and the validation GSE37642 cohort. Univariate and multivariate Cox analysis revealed that the risk score of the autophagy model can be used as an independent prognostic factor. The high-risk subgroup had not only higher fractions of CD4 naïve T cell, NK cell activated, and resting mast cells but also higher expression of immune checkpoint genes CTLA4 and CD274. Last, we screened drug sensitivity between high- and low-risk subgroups.

Conclusion

The risk score model based on 10 autophagy-related genes can serve as an effective prognostic predictor for AML patients and may guide for patient stratification for immunotherapies and drugs.

Early magnetic resonance imaging biomarkers of schizophrenia spectrum disorders: Toward a fetal imaging perspective

There is mounting evidence to implicate the intrauterine environment as the initial pathogenic stage for neuropsychiatric disease. Recent developments in magnetic resonance imaging technology are making a multimodal analysis of the fetal central nervous system a reality, allowing analysis of structural and functional parameters. Exposures to a range of pertinent risk factors whether preconception or in utero can now be indexed using imaging techniques within the fetus' physiological environment. This approach may determine the first "hit" required for diseases that do not become clinically manifest until adulthood, and which only have subtle clinical markers during childhood and adolescence. A robust characterization of a "multi-hit" hypothesis may necessitate a longitudinal birth cohort; within this investigative paradigm, the full range of genetic and environmental risk factors can be assessed for their impact on the early developing brain. This will lay the foundation for the identification of novel biomarkers and the ability to devise methods for early risk stratification and disease prevention. However, these early markers must be followed over time: first, to account for neural plasticity, and second, to assess the effects of postnatal exposures that continue to drive the individual toward disease. We explore these issues using the schizophrenia spectrum disorders as an illustrative paradigm. However, given the potential richness of fetal magnetic resonance imaging, and the likely overlap of biomarkers, these concepts may extend to a range of neuropsychiatric conditions.

Polygenic Risk Scores Differentiating Schizophrenia From Bipolar Disorder Are Associated With Premorbid Intelligence in Schizophrenia Patients and Healthy Subjects

BACKGROUND

Impairments in intelligence are more severe in patients with schizophrenia (SCZ) than in patients with bipolar disorder (BD) despite clinical and genetic similarities between the disorders. Genetic loci differentiating SCZ from BD, that is, SCZ-specific risk, have been identified. Polygenetic [risk] scores (PGSs) for SCZ-specific risk are higher in SCZ patients than in healthy controls (HCs). However, the influence of genetic risk on impaired intelligence is poorly understood. Here, we investigated whether SCZ-specific risk could predict impairments in intelligence in SCZ patients and HCs.

METHODS

Large-scale genome-wide association study datasets related to SCZ vs BD, childhood intelligence (CHI), and adulthood intelligence (n = 12 441-282 014) were utilized to compute PGSs. PGSs derived from the genome-wide association studies were calculated for 130 patients with SCZ and 146 HCs. Premorbid and current intelligence and the decline were measured in SCZ patients and HCs. Correlations between PGSs and intelligence functions were investigated.

RESULTS

High PGSs for SCZ-specific risk were correlated with low premorbid intelligence in SCZ patients and HCs (β = -0.17, P = 4.12 × 10-3). The correlation was still significant after adjusting for diagnostic status (β = -0.13, P = .024). There were no significant correlations between PGSs for SCZ-specific risk and current intelligence or intelligence decline (P > .05). PGSs for CHI were lower in SCZ patients than in HCs (R2 = 0.025, P = .025), while the PGSs for CHI were not significantly correlated with premorbid and current intelligence, the decline, or the PGSs for SCZ-specific risk (P > .05).

CONCLUSIONS

These findings suggest that genetic factors differentiating SCZ from BD might affect the pathogenesis of SCZ and/or pathological differences between SCZ and BD via the impairment of premorbid intelligence, that is, crystallized intelligence, while genetic factors for CHI might affect the pathogenesis of SCZ but not via impairments in intelligence.

Jumping to conclusions, general intelligence, and psychosis liability: findings from the multi-centre EU-GEI case-control study

BACKGROUND

The 'jumping to conclusions' (JTC) bias is associated with both psychosis and general cognition but their relationship is unclear. In this study, we set out to clarify the relationship between the JTC bias, IQ, psychosis and polygenic liability to schizophrenia and IQ.

METHODS

A total of 817 first episode psychosis patients and 1294 population-based controls completed assessments of general intelligence (IQ), and JTC, and provided blood or saliva samples from which we extracted DNA and computed polygenic risk scores for IQ and schizophrenia.

RESULTS

The estimated proportion of the total effect of case/control differences on JTC mediated by IQ was 79%. Schizophrenia polygenic risk score was non-significantly associated with a higher number of beads drawn (B = 0.47, 95% CI -0.21 to 1.16, p = 0.17); whereas IQ PRS (B = 0.51, 95% CI 0.25-0.76, p < 0.001) significantly predicted the number of beads drawn, and was thus associated with reduced JTC bias. The JTC was more strongly associated with the higher level of psychotic-like experiences (PLEs) in controls, including after controlling for IQ (B = -1.7, 95% CI -2.8 to -0.5, p = 0.006), but did not relate to delusions in patients.

CONCLUSIONS

Our findings suggest that the JTC reasoning bias in psychosis might not be a specific cognitive deficit but rather a manifestation or consequence, of general cognitive impairment. Whereas, in the general population, the JTC bias is related to PLEs, independent of IQ. The work has the potential to inform interventions targeting cognitive biases in early psychosis.

Epigenetic Modifications in Schizophrenia and Related Disorders: Molecular Scars of Environmental Exposures and Source of Phenotypic Variability

Epigenetic modifications are increasingly recognized to play a role in the etiology and pathophysiology of schizophrenia and other psychiatric disorders with developmental origins. Here, we summarize clinical and preclinical findings of epigenetic alterations in schizophrenia and relevant disease models and discuss their putative origin. Recent findings suggest that certain schizophrenia risk loci can influence stochastic variation in gene expression through epigenetic processes, highlighting the intricate interaction between genetic and epigenetic control of neurodevelopmental trajectories. In addition, a substantial portion of epigenetic alterations in schizophrenia and related disorders may be acquired through environmental factors and may be manifested as molecular "scars." Some of these scars can influence brain functions throughout the entire lifespan and may even be transmitted across generations via epigenetic germline inheritance. Epigenetic modifications, whether caused by genetic or environmental factors, are plausible molecular sources of phenotypic heterogeneity and offer a target for therapeutic interventions. The further elucidation of epigenetic modifications thus may increase our knowledge regarding schizophrenia's heterogeneous etiology and pathophysiology and, in the long term, may advance personalized treatments through the use of biomarker-guided epigenetic interventions.

Predicting Complex Traits and Exposures From Polygenic Scores and Blood and Buccal DNA Methylation Profiles

We examined the performance of methylation scores (MS) and polygenic scores (PGS) for birth weight, BMI, prenatal maternal smoking exposure, and smoking status to assess the extent to which MS could predict these traits and exposures over and above the PGS in a multi-omics prediction model. MS may be seen as the epigenetic equivalent of PGS, but because of their dynamic nature and sensitivity of non-genetic exposures may add to complex trait prediction independently of PGS. MS and PGS were calculated based on genotype data and DNA-methylation data in blood samples from adults (Illumina 450 K; N = 2,431; mean age 35.6) and in buccal samples from children (Illumina EPIC; N = 1,128; mean age 9.6) from the Netherlands Twin Register. Weights to construct the scores were obtained from results of large epigenome-wide association studies (EWASs) based on whole blood or cord blood methylation data and genome-wide association studies (GWASs). In adults, MSs in blood predicted independently from PGSs, and outperformed PGSs for BMI, prenatal maternal smoking, and smoking status, but not for birth weight. The largest amount of variance explained by the multi-omics prediction model was for current vs. never smoking (54.6%) of which 54.4% was captured by the MS. The two predictors captured 16% of former vs. never smoking initiation variance (MS:15.5%, PGS: 0.5%), 17.7% of prenatal maternal smoking variance (MS:16.9%, PGS: 0.8%), 11.9% of BMI variance (MS: 6.4%, PGS 5.5%), and 1.9% of birth weight variance (MS: 0.4%, PGS: 1.5%). In children, MSs in buccal samples did not show independent predictive value. The largest amount of variance explained by the two predictors was for prenatal maternal smoking (2.6%), where the MSs contributed 1.5%. These results demonstrate that blood DNA MS in adults explain substantial variance in current smoking, large variance in former smoking, prenatal smoking, and BMI, but not in birth weight. Buccal cell DNA methylation scores have lower predictive value, which could be due to different tissues in the EWAS discovery studies and target sample, as well as to different ages. This study illustrates the value of combining polygenic scores with information from methylation data for complex traits and exposure prediction.

Cortical Gyrification, Psychotic-Like Experiences, and Cognitive Performance in Nonclinical Subjects

BACKGROUND

Psychotic-like experiences (PLE) are present in nonclinical populations, yet their association with brain structural variation, especially markers of early neurodevelopment, is poorly understood. We tested the hypothesis that cortical surface gyrification, a putative marker of early brain development, is associated with PLE in healthy subjects.

METHODS

We analyzed gyrification from 3 Tesla MRI scans (using CAT12 software) and PLE (positive, negative, and depressive symptom dimensions derived from the Community Assessment of Psychic Experiences, CAPE) in 103 healthy participants (49 females, mean age 29.13 ± 9.37 years). A subsample of 63 individuals completed tasks from the Wechsler Adult Intelligence Scale and Controlled Oral Word Association Test. Estimated IQ and a composite neuropsychological score were used to explore mediation pathways via cognition.

RESULTS

Positive PLE distress was negatively associated with gyrification of the left precuneus. PLE depression dimension showed a negative association with gyrification in the right supramarginal and temporal region. There was no significant mediating effect of cognition on these associations.

CONCLUSION

Our results support a neurobiological psychosis spectrum, for the first time linking an early developmental imaging marker (rather than volume) to dimensional subclinical psychotic symptoms. While schizophrenia risk, neurodevelopment, and cognitive function might share genetic risk factors, additional mediation analyses did not confirm a mediating effect of cognition on the gyrification-psychopathology correlation.

Polygenic scores for schizophrenia and general cognitive ability: associations with six cognitive domains, premorbid intelligence, and cognitive composite score in individuals with a psychotic disorder and in healthy controls

Cognitive impairments are considered core features in schizophrenia and other psychotic disorders. Cognitive impairments are, to a lesser degree, also documented in healthy first-degree relatives. Although recent studies have shown (negative) genetic correlations between schizophrenia and general cognitive ability, the association between polygenic risk for schizophrenia and individual cognitive phenotypes remains unclear. We here investigated the association between a polygenic score for schizophrenia (SCZ_PGS) and six well-defined cognitive domains, in addition to a composite measure of cognitive ability and a measure of premorbid intellectual ability in 731 participants with a psychotic disorder and 851 healthy controls. We also investigated the association between a PGS for general cognitive ability (COG_PGS) and the same cognitive domains in the same sample. We found no significant associations between the SCZ_PGS and any cognitive phenotypes, in either patients with a psychotic disorder or healthy controls. For COG_PGS we observed stronger associations with cognitive phenotypes in healthy controls than in participants with psychotic disorders. In healthy controls, the association between COG_PGS (at the p value threshold of ≥0.01) and working memory remained significant after Bonferroni correction (β = 0.12, p = 8.6 × 10^-5). Altogether, the lack of associations between SCZ_PGS and COG_PGS with cognitive performance in participants with psychotic disorders suggests that either environmental factors or unassessed genetic factors play a role in the development of cognitive impairments in psychotic disorders. Working memory should be further studied as an important cognitive phenotype.

Polygenic risk scores for late smoking initiation associated with the risk of schizophrenia

Patients with schizophrenia display characteristic smoking-related behaviors and genetic correlations between smoking behaviors and schizophrenia have been identified in European individuals. However, the genetic etiology of the association remains to be clarified. The present study investigated transethnic genetic overlaps between European-based smoking behaviors and the risk of Japanese schizophrenia by conducting polygenic risk score (PRS) analyses. Large-scale European genome-wide association study (GWAS) datasets (n = 24,114-74,035) related to four smoking-related intermediate phenotypes [(i) smoking initiation, (ii) age at smoking initiation, (iii) smoking quantity, and (iv) smoking cessation] were utilized as discovery samples. PRSs derived from these discovery GWASs were calculated for 332 Japanese subjects [schizophrenia patients, their unaffected first-degree relatives (FRs), and healthy controls (HCs)] as a target sample. Based on GWASs of European smoking phenotypes, we investigated the effects of PRSs on smoking phenotypes and the risk of schizophrenia in the Japanese population. Of the four smoking-related behaviors, the PRSs for age at smoking initiation in Europeans significantly predicted the age at smoking initiation (R² = 0.049, p = 0.026) and the PRSs for smoking cessation significantly predicted the smoking cessation (R² = 0.092, p = 0.027) in Japanese ever-smokers. Furthermore, the PRSs related to age at smoking initiation in Europeans were higher in Japanese schizophrenia patients than in the HCs and those of the FRs were intermediate between those of patients with schizophrenia and those of the HCs (R² = 0.015, p = 0.015). In our target subjects, patients with schizophrenia had a higher mean age at smoking initiation (p = 0.018) and rate of daily smoking initiation after age 20 years (p = 0.023) compared with the HCs. A total of 60.6% of the patients started to smoke before the onset of schizophrenia. These findings suggest that genetic factors affecting late smoking initiation are associated with the risk of schizophrenia.

Polygenic risk for autism spectrum disorder affects left amygdala activity and negative emotion in schizophrenia

Although the diagnoses based on phenomenology have many practical advantages, accumulating evidence shows that schizophrenia and autism spectrum disorder (ASD) share some overlap in genetics and clinical presentation. It remains largely unknown how ASD-associated polygenetic risk contributes to the pathogenesis of schizophrenia. In the present study, we calculated high-resolution ASD polygenic risk scores (ASD PRSs) and selected optimal ten ASD PRS with minimal P values in the association analysis of PRSs, with schizophrenia to assess the effect of ASD PRS on brain neural activity in schizophrenia cases and controls. We found that amplitude of low-frequency fluctuation in left amygdala was positively associated with ASD PRSs in our cohort. Correlation analysis of ASD PRSs with facial emotion recognition test identified the negative correlation of ASD PRSs with negative emotions in schizophrenia cases and controls. Finally, functional enrichment analysis of PRS genes revealed that neural system function and development, as well as signal transduction, were mainly enriched in PRS genes. Our results provide empirical evidence that polygenic risk for ASD contributes to schizophrenia by the intermediate phenotypes of left amygdala function and emotion recognition. It provides a promising strategy to understand the relationship between phenotypes and genotypes shared in mental disorders.

Reinforcement learning as an intermediate phenotype in psychosis? Deficits sensitive to illness stage but not associated with polygenic risk of schizophrenia in the general population

BACKGROUND

Schizophrenia is a complex disorder in which the causal relations between risk genes and observed clinical symptoms are not well understood and the explanatory gap is too wide to be clarified without considering an intermediary level. Thus, we aimed to test the hypothesis of a pathway from molecular polygenic influence to clinical presentation occurring via deficits in reinforcement learning.

METHODS

We administered a reinforcement learning task (Go/NoGo) that measures reinforcement learning and the effect of Pavlovian bias on decision making. We modelled the behavioural data with a hierarchical Bayesian approach (hBayesDM) to decompose task performance into its underlying learning mechanisms. Study 1 included controls (n = 29, F|M = 0.81), At Risk Mental State for psychosis (ARMS, n = 23, F|M = 0.35) and FEP (First-episode psychosis, n = 26, F|M = 0.18). Study 2 included healthy adolescents (n = 735, F|M = 1.06), 390 of whom had their polygenic risk scores for schizophrenia (PRSs) calculated.

RESULTS

Patients with FEP showed significant impairments in overriding Pavlovian conflict, a lower learning rate and a lower sensitivity to both reward and punishment. Less widespread deficits were observed in ARMS. PRSs did not significantly predict performance on the task in the general population, which only partially correlated with measures of psychopathology.

CONCLUSIONS

Reinforcement learning deficits are observed in first episode psychosis and, to some extent, in those at clinical risk for psychosis, and were not predicted by molecular genetic risk for schizophrenia in healthy individuals. The study does not support the role of reinforcement learning as an intermediate phenotype in psychosis.

Accurate and Scalable Construction of Polygenic Scores in Large Biobank Data Sets

Accurate construction of polygenic scores (PGS) can enable early diagnosis of diseases and facilitate the development of personalized medicine. Accurate PGS construction requires prediction models that are both adaptive to different genetic architectures and scalable to biobank scale datasets with millions of individuals and tens of millions of genetic variants. Here, we develop such a method called Deterministic Bayesian Sparse Linear Mixed Model (DBSLMM). DBSLMM relies on a flexible modeling assumption on the effect size distribution to achieve robust and accurate prediction performance across a range of genetic architectures. DBSLMM also relies on a simple deterministic search algorithm to yield an approximate analytic estimation solution using summary statistics only. The deterministic search algorithm, when paired with further algebraic innovations, results in substantial computational savings. With simulations, we show that DBSLMM achieves scalable and accurate prediction performance across a range of realistic genetic architectures. We then apply DBSLMM to analyze 25 traits in UK Biobank. For these traits, compared to existing approaches, DBSLMM achieves an average of 2.03%-101.09% accuracy gain in internal cross-validations. In external validations on two separate datasets, including one from BioBank Japan, DBSLMM achieves an average of 14.74%-522.74% accuracy gain. In these real data applications, DBSLMM is 1.03-28.11 times faster and uses only 7.4%-24.8% of physical memory as compared to other multiple regression-based PGS methods. Overall, DBSLMM represents an accurate and scalable method for constructing PGS in biobank scale datasets.

Polygenetic Risk Scores for Major Psychiatric Disorders Among Schizophrenia Patients, Their First-Degree Relatives, and Healthy Participants

BACKGROUND

The genetic etiology of schizophrenia (SCZ) overlaps with that of other major psychiatric disorders in samples of European ancestry. The present study investigated transethnic polygenetic features shared between Japanese SCZ or their unaffected first-degree relatives and European patients with major psychiatric disorders by conducting polygenic risk score (PRS) analyses.

METHODS

To calculate PRSs for 5 psychiatric disorders (SCZ, bipolar disorder [BIP], major depressive disorder, autism spectrum disorder, and attention-deficit/hyperactivity disorder) and PRSs differentiating SCZ from BIP, we utilized large-scale European genome-wide association study (GWAS) datasets as discovery samples. PRSs derived from these GWASs were calculated for 335 Japanese target participants [SCZ patients, FRs, and healthy controls (HCs)]. We took these PRSs based on GWASs of European psychiatric disorders and investigated their effect on risk in Japanese SCZ patients and unaffected first-degree relatives.

RESULTS

The PRSs obtained from European SCZ and BIP patients were higher in Japanese SCZ patients than in HCs. Furthermore, PRSs differentiating SCZ patients from European BIP patients were higher in Japanese SCZ patients than in HCs. Interestingly, PRSs related to European autism spectrum disorder were lower in Japanese first-degree relatives than in HCs or SCZ patients. The PRSs of autism spectrum disorder were positively correlated with a young onset age of SCZ.

CONCLUSIONS

These findings suggest that polygenic factors related to European SCZ and BIP and the polygenic components differentiating SCZ from BIP can transethnically contribute to SCZ risk in Japanese people. Furthermore, we suggest that reduced levels of an ASD-related genetic factor in unaffected first-degree relatives may help protect against SCZ development.

Schizophrenia polygenic risk score influence on white matter microstructure

Schizophrenia (SZ) and bipolar disorder (BD) are highly heritable, share symptomatology, and have a polygenic architecture. The impact of recent polygenic risk scores (PRS) for psychosis, which combine multiple genome-wide associated risk variations, should be assessed on heritable brain phenotypes also previously associated with the illnesses, for a better understanding of the pathways to disease. We have recently reported on the current SZ PRS's ability to predict 1st episode of psychosis case-control status and general cognition. Herein, we test its penetrance on white matter microstructure, which is known to be impaired in SZ, in BD and their relatives, using 141 participants (including SZ, BP, relatives of SZ or BP patients, and healthy volunteers), and two white matter integrity indexes: fractional anisotropy (FA) and mean diffusivity (MD). No significant correlation between the SZ PRS and FA or MD was found, thus it remains unclear whether white matter changes are primarily associated with SZ genetic risk profiles.

Developmental Genes and Regulatory Proteins, Domains of Cognitive Impairment in Schizophrenia Spectrum Psychosis and Implications for Antipsychotic Drug Discovery: The Example of Dysbindin-1 Isoforms and Beyond

Alongside positive and negative symptomatology, deficits in working memory, attention, selective learning processes, and executive function have been widely documented in schizophrenia spectrum psychosis. These cognitive abnormalities are strongly associated with impairment across multiple function domains and are generally treatment-resistant. The DTNBP1 (dystrobrevin-binding protein-1) gene, encoding dysbindin, is considered a risk factor for schizophrenia and is associated with variation in cognitive function in both clinical and nonclinical samples. Downregulation of DTNBP1 expression in dorsolateral prefrontal cortex and hippocampal formation of patients with schizophrenia has been suggested to serve as a primary pathophysiological process. Described as a "hub," dysbindin is an important regulatory protein that is linked with multiple complexes in the brain and is involved in a wide variety of functions implicated in neurodevelopment and neuroplasticity. The expression pattern of the various dysbindin isoforms (-1A, -1B, -1C) changes depending upon stage of brain development, tissue areas and subcellular localizations, and can involve interaction with different protein partners. We review evidence describing how sequence variation in DTNBP1 isoforms has been differentially associated with schizophrenia-associated symptoms. We discuss results linking these isoform proteins, and their interacting molecular partners, with cognitive dysfunction in schizophrenia, including evidence from drosophila through to genetic mouse models of dysbindin function. Finally, we discuss preclinical evidence investigating the antipsychotic potential of molecules that influence dysbindin expression and functionality. These studies, and other recent work that has extended this approach to other developmental regulators, may facilitate identification of novel molecular pathways leading to improved antipsychotic treatments.

Polygenic Risk Scores Shed Light on the Relationship between Schizophrenia and Cognitive Functioning: Review and Meta-Analysis

Schizophrenia is a multifactorial disease associated with widespread cognitive impairment. Although cognitive deficits are one of the factors most strongly associated with functional impairment in schizophrenia (SZ), current treatment strategies hardly tackle these impairments. To develop more efficient treatment strategies in patients, a better understanding of their pathogenesis is needed. Recent progress in genetics, driven by large genome-wide association studies (GWAS) and the use of polygenic risk scores (PRS), has provided new insights about the genetic architecture of complex human traits, including cognition and SZ. Here, we review the recent findings examining the genetic links between SZ and cognitive functions in population-based samples as well as in participants with SZ. The performed meta-analysis showed a negative correlation between the polygenetic risk score of schizophrenia and global cognition (p < 0.001) when the samples rely on general and healthy participants, while no significant correlation was detected when the three studies devoted to schizophrenia patients were meta-analysed (p > 0.05). Our review and meta-analysis therefore argues against universal pleiotropy for schizophrenia alleles and cognition, since cognition in SZ patients would be underpinned by the same genetic factors than in the general population, and substantially independent of common variant liability to the disorder.

Evidence of association of the DISC1 interactome gene set with schizophrenia from GWAS

DISC1 was discovered as a gene disrupted by a balanced translocation in a large pedigree that segregated with major mental disorders, including schizophrenia. Further attempts to find genetic association with schizophrenia were inconclusive. Most of the biology of DISC1 was inferred from the functionality of its protein partners. Recently, a gene set constituted by DISC1 and several of its partners has been associated with cognitive performance during development, a well-known schizophrenia endophenotype, by means of burden test of rare disruptive variants. Here, we performed a gene set analysis using common variants from the largest schizophrenia genome-wide association study of the Psychiatric Genomics Consortium to test if this gene set is associated with schizophrenia. The main test was based on the MAGMA software. Several additional tests were performed to analyze the robustness of the main findings. The DISC1 interactome gene set was associated with schizophrenia (P = .0056), confirmed by an additional method (INRICH). This association was robust to removal of the major histocompatibility complex region, different definitions of gene boundaries, or different statistical gene models. Conditional analysis revealed that the association was not solely explained by higher expression in brain. Three genes from the gene set, CLIC1, DST, and PDE4B, were associated with schizophrenia at the gene level. Consideration of other DISC1 interactome gene sets revealed the importance of gene set definition. Therefore, we present the first evidence from genome-wide association studies of the role of DISC1 and interacting partners in schizophrenia susceptibility, reconciling genetic and molecular biology data.

Polygenic Risk Scores for Psychiatric Disorders Reveal Novel Clues About the Genetics of Disordered Gambling

Disordered gambling (DG) is a rare but serious condition that results in considerable financial and interpersonal harms. Twin studies indicate that DG is heritable but are silent with respect to specific genes or pathways involved. Existing genomewide association studies (GWAS) of DG have been substantially underpowered. Larger GWAS of other psychiatric disorders now permit calculation of polygenic risk scores (PRSs) that reflect the aggregated effects of common genetic variants contributing risk for the target condition. The current study investigated whether gambling and DG are associated with PRSs for four psychiatric conditions found to be comorbid with DG in epidemiologic surveys: major depressive disorder (MDD), attention-deficit hyperactivity disorder (ADHD), bipolar disorder (BD) and schizophrenia (SCZ). Genotype data and survey responses were analyzed from the Wave IV assessment (conducted in 2008) of the National Longitudinal Study of Adolescent to Adult Health, a representative sample of adolescents recruited in 1994-1995 and followed into adulthood. Among participants classified as having European ancestry based on genetic analysis (N = 5215), 78.4% reported ever having gambled, and 1.3% reported lifetime DG. Polygenic risk for BD was associated with decreased odds of lifetime gambling, OR = 0.93 [0.87, 0.99], p = .045, pseudo-R2(%) = .12. The SCZ PRS was associated with increased odds of DG, OR = 1.54 [1.07, 2.21], p = .02, pseudo-R2(%) = .85. Polygenic risk scores for MDD and ADHD were not related to either gambling outcome. Investigating features common to both SCZ and DG might generate valuable clues about the genetically influenced liabilities to DG.