Intelligence decline between present and premorbid IQ in schizophrenia: Schizophrenia Non-Affected Relative Project (SNARP)

Implications of altered pyramidal cell morphology on clinical symptoms of neurodevelopmental disorders

The prevalence of pyramidal cells (PCs) in the mammalian cerebral cortex underscore their value as they play a crucial role in various brain functions, ranging from cognition, sensory processing, to motor output. PC morphology significantly influences brain connectivity and plays a critical role in maintaining normal brain function. Pathological alterations to PC morphology are thought to contribute to the aetiology of neurodevelopmental disorders such as autism spectrum disorder (ASD) and schizophrenia. This review explores the relationship between abnormalities in PC morphology in key cortical areas and the clinical manifestations in schizophrenia and ASD. We focus largely on human postmortem studies and provide evidence that dendritic segment length, complexity and spine density are differentially affected in these disorders. These morphological alterations can lead to disruptions in cortical connectivity, potentially contributing to the cognitive and behavioural deficits observed in these disorders. Furthermore, we highlight the importance of investigating the functional and structural characteristics of PCs in these disorders to illuminate the underlying pathogenesis and stimulate further research in this area.

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.

Olfactory identification ability among schizophrenia patients, their first-degree relatives and healthy subjects

OBJECTIVE

Olfactory impairments, including identification, have been reported in patients with schizophrenia, while few studies have examined the olfactory function of unaffected first-degree relatives of patients with schizophrenia, and the sample sizes of first-degree relatives were relatively small. Here, we investigated olfactory identification ability among patients with schizophrenia, first-degree relatives and healthy controls (HCs) using relatively large sample sizes at a single institute.

METHODS

To assess olfactory identification ability, the open essence odorant identification test was administered to 172 schizophrenia patients, 75 first-degree relatives and 158 healthy controls. Differences in olfactory identification and correlations between olfactory ability and clinical variables were examined among these participants.

RESULTS

We found a significant difference in olfactory identification ability among the diagnostic groups (p = 7.65 × 10-16). Schizophrenia patients displayed lower olfactory identification ability than first-degree relatives (Cohen's d = -0.57, p = 3.13 × 10-6) and healthy controls (d = -1.00, p = 2.19 × 10-16). Furthermore, first-degree relatives had lower olfactory identification ability than healthy controls (d = -0.29, p = 0.039). Olfactory identification ability moderately and negatively correlated with the duration of illness (r = -0.41, p = 1.88 × 10-8) and negative symptoms (r = -0.28, p = 1.99 × 10-4) in schizophrenia patients, although the correlation with the duration of illness was affected by aging (r = -0.24).

CONCLUSIONS

Our results demonstrated that schizophrenia patients have impaired olfactory identification ability compared with first-degree relatives and healthy controls, and the impaired olfactory identification ability of first-degree relatives was intermediate between those in schizophrenia patients and healthy controls. Olfactory identification ability was relatively independent of clinical variables. Therefore, olfactory identification ability might be an intermediate phenotype for schizophrenia.

The Risk for Schizophrenia-Bipolar Spectrum: Does the Apple Fall Close to the Tree? A Narrative Review

Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric disorders that share clinical features and several risk genes. Important information about their genetic underpinnings arises from intermediate phenotypes (IPs), quantifiable biological traits that are more prevalent in unaffected relatives (RELs) of patients compared to the general population and co-segregate with the disorders. Within IPs, neuropsychological functions and neuroimaging measures have the potential to provide useful insight into the pathophysiology of SCZ and BD. In this context, the present narrative review provides a comprehensive overview of the available evidence on deficits in neuropsychological functions and neuroimaging alterations in unaffected relatives of SCZ (SCZ-RELs) and BD (BD-RELs). Overall, deficits in cognitive functions including intelligence, memory, attention, executive functions, and social cognition could be considered IPs for SCZ. Although the picture for cognitive alterations in BD-RELs is less defined, BD-RELs seem to present worse performances compared to controls in executive functioning, including adaptable thinking, planning, self-monitoring, self-control, and working memory. Among neuroimaging markers, SCZ-RELs appear to be characterized by structural and functional alterations in the cortico-striatal-thalamic network, while BD risk seems to be associated with abnormalities in the prefrontal, temporal, thalamic, and limbic regions. In conclusion, SCZ-RELs and BD-RELs present a pattern of cognitive and neuroimaging alterations that lie between patients and healthy individuals. Similar abnormalities in SCZ-RELs and BD-RELs may be the phenotypic expression of the shared genetic mechanisms underlying both disorders, while the specificities in neuropsychological and neuroimaging profiles may be associated with the differential symptom expression in the two disorders.

Mitochondrial genetic variants associated with bipolar disorder and Schizophrenia in a Japanese population

BACKGROUND

Bipolar disorder (BD) and schizophrenia (SZ) are complex psychotic disorders (PSY), with both environmental and genetic factors including possible maternal inheritance playing a role. Some studies have investigated whether genetic variants in the mitochondrial chromosome are associated with BD and SZ. However, the genetic variants identified as being associated are not identical among studies, and the participants were limited to individuals of European ancestry. Here, we investigate associations of genome-wide genetic variants in the mitochondrial chromosome with BD, SZ, and PSY in a Japanese population.

METHODS

After performing quality control for individuals and genetic variants, we investigated whether mitochondrial genetic variants [minor allele frequency (MAF) > 0.01, n = 45 variants) are associated with BD, SZ, and PSY in 420 Japanese individuals consisting of patients with BD (n = 51), patients with SZ (n = 172), and healthy controls (HCs, n = 197).

RESULTS

Of mitochondrial genetic variants, three (rs200478835, rs200044200 and rs28359178 on or near NADH dehydrogenase) and one (rs200478835) were significantly associated with BD and PSY, respectively, even after correcting for multiple comparisons (PGC=0.045-4.9 × 10- 3). In particular, individuals with the minor G-allele of rs200044200, a missense variant, were only observed among patients with BD (MAF = 0.059) but not HCs (MAF = 0) (odds ratio=∞). Three patients commonly had neuropsychiatric family histories.

CONCLUSIONS

We suggest that mitochondrial genetic variants in NADH dehydrogenase-related genes may contribute to the pathogenesis of BD and PSY in the Japanese population through dysfunction of energy production.

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.

Higher polygenic risk scores for anxiety disorders are associated with reduced area in the anterior cingulate gyrus

Anxiety disorders are heterogeneous, show a moderate genetic contribution and are associated with inconsistent cortical structure alterations. Here, we investigated whether genetic factors for anxiety disorders contribute to cortical alterations by conducting polygenic risk score (PRS) analyses. We calculated PRSs for anxiety disorders at several P value thresholds (from P_T ≤ 5.0 × 10^-8 to P_T ≤ 1.0) based on the latest large-scale genome-wide association study of anxiety disorders from the UK biobank (25,453 cases; 58,113 controls) in an independent sample of psychiatrically and physically healthy subjects (n = 174). Using regression after adjusting for confounding factors, we tested whether these PRSs were associated with the surface area and cortical thickness in 34 bilateral brain regions extracted using FreeSurfer. A higher PRS for anxiety disorders at P_T ≤ 1.0 was significantly associated with a reduced right caudal anterior cingulate area (beta = -0.25, p_uncorrected = 9.51 × 10^-4, p_corrected = 0.032). PRSs based on more common SNPs, especially from P_T ≤ 0.01 to P_T ≤ 1.0, were associated with the right caudal anterior cingulate area (a maximum at P_T ≤ 0.5: R² = 0.066, beta = -0.27, p_uncorr = 3.81 × 10^-4, p_corr = 0.013). Furthermore, individuals in the highest quartile for anxiety disorder PRS had lower surface area and volume in the right anterior cingulate gyrus than those in the lowest quartile. We suggest a shared genetic etiology between anxiety disorders and structural features of the anterior cingulate gyrus, possibly contributing to the pathogenesis of anxiety disorders via emotional dysregulations. Our findings suggest the potential usefulness of PRS to reduce pathological heterogeneity among anxiety disorders.

Differences in subcortical brain volumes among patients with schizophrenia and bipolar disorder and healthy controls

BACKGROUND

Patients with schizophrenia and bipolar disorder have an overlapping polygenic architecture and clinical similarities, although the 2 disorders are distinct diagnoses with clinical dissimilarities. It remains unclear whether there are specific differences in subcortical volumes between schizophrenia and bipolar disorder, and whether the subcortical differences are affected by any clinical characteristics. We investigated differences in subcortical volumes bilaterally among patients with schizophrenia, patients with bipolar disorder and healthy controls. We also investigated the influences of clinical characteristics on specific subcortical volumes in these patient groups.

METHODS

We collected 3 T T ₁-weighted MRI brain scans from 413 participants (157 with schizophrenia, 51 with bipolar disorder and 205 controls) with a single scanner at a single institute. We used FreeSurfer version 6.0 for processing the T ₁-weighted images to segment the following subcortical brain volumes: thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala and nucleus accumbens. Differences in the 7 subcortical volumes were investigated among the groups. We also evaluated correlations between subcortical volumes and clinical variables in these patient groups.

RESULTS

Of 7 subcortical regions, patients with schizophrenia had significantly smaller volumes in the left thalamus (Cohen d = -0.29, p = 5.83 × 10^-3), bilateral hippocampi (left, d = -0.36, p = 8.85 × 10^-4; right, d = -0.41, p = 1.15 × 10^-4) and left amygdala (d = -0.31, p = 4.02 × 10^-3) than controls. Compared with controls, patients with bipolar disorder had bilateral reductions only in the hippocampal volumes (left, d = -0.52, p = 1.12 × 10^-3; right, d = -0.58, p = 0.30 × 10^-4). We also found that patients with schizophrenia had significantly smaller volumes in the bilateral amygdalae (left, d = -0.43, p = 4.22 × 10^-3; right, d = -0.45, p = 4.56 × 10^-3) than patients with bipolar disorder. We did not find any significant volumetric differences in the other 6 subcortical structures between patient groups (p > 0.05). Smaller left amygdalar volumes were significantly correlated with younger onset age only in patients with schizophrenia (r = 0.22, p = 5.78 × 10^-3).

LIMITATIONS

We did not evaluate the differences in subcortical volumes between patients stratified based on clinical bipolar disorder subtype and a history of psychotic episodes because our sample size of patients with bipolar disorder was limited.

CONCLUSION

Our findings suggest that volumetric differences in the amygdala between patients with schizophrenia and those with bipolar disorder may be a putative biomarker for distinguishing 2 clinically similar diagnoses.

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.

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.

Effects of genome-wide neuroticism-associated variants on five-factor model personality traits in schizophrenia

Patients with schizophrenia (SCZ) have characteristic personality traits compared with healthy subjects. Genome-wide significant variants for neuroticism have been reported in healthy subjects. However, the associations of these genome-wide neuroticism-associated variants with five-factor personality traits in patients with SCZ are less clear. We investigated the influences of nine independent genome-wide significant variants for neuroticism on five-factor personality traits (neuroticism, extraversion, openness, agreeableness, and conscientiousness) assessed by the NEO Five-Factor Inventory (NEO-FFI) in 107 patients with SCZ and 119 healthy controls (HCs). As expected, patients with SCZ scored significantly higher for neuroticism and lower for extraversion, openness, agreeableness and conscientiousness than HCs (p < 0.05). Of nine neuroticism-associated variants, the T allele at rs4653663 related to lower neuroticism was only significantly associated with lower neuroticism in patients with SCZ (β = -0.27, p = 3.88 × 10^-3) and in combined subjects (β = -0.15, p = 0.026). Furthermore, of other personality traits, the genetic variant was significantly associated with higher agreeableness in combined subjects (β = 0.17, p = 9.41×10^-3), higher conscientiousness in patients with SCZ (β = 0.21, p = 0.031) and lower conscientiousness in HCs (β = -0.20, p = 0.034), and nominally associated with higher extraversion in patients with SCZ (β = 0.18, p = 0.056) and in combined subjects (β = 0.13, p = 0.051). These outcomes were not affected by clinical variables. We suggest that genome-wide neuroticism-associated variant could be associated with neuroticism as well as other personality traits in schizophrenia.

Intelligence decline across major depressive disorder, bipolar disorder, and schizophrenia

BACKGROUND

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are associated with impaired intelligence that predicts poor functional outcomes. However, little is known regarding the extent and severity of intelligence decline, that is, decreased present intelligence quotient (IQ) relative to premorbid levels, across psychiatric disorders and which clinical characteristics affect the decline.

METHODS

Premorbid IQ, present IQ, and intelligence decline were compared across patients with MDD (n = 45), BD (n = 30), and SCZ (n = 139), and healthy controls (HCs; n = 135). Furthermore, we investigated which factors contribute to the intelligence decline in each diagnostic group.

RESULTS

Significant differences were observed in premorbid IQ, present IQ, and intelligence decline across the diagnostic groups. Patients with each psychiatric disorder displayed lower premorbid and present IQ and more intelligence decline than HCs. Patients with SCZ displayed lower premorbid and present IQ and more intelligence decline than patients with MDD and BD, while there were no significant differences between patients with MDD and BD. When patients with BD were divided based on bipolar I disorder (BD-I) and bipolar II disorder (BD-II), degrees of intelligence decline were similar between MDD and BD-II and between BD-I and SCZ. Lower educational attainment was correlated with a greater degree of intelligence decline in patients with SCZ and BD but not MDD.

CONCLUSIONS

These findings confirm that although all psychiatric disorders display intelligence decline, the severity of intelligence decline differs across psychiatric disorders (SCZ, BD-I > BD-II, MDD > HCs). Higher educational attainment as cognitive reserve contributes to protection against intelligence decline in BD and SCZ.

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.

Differences in executive function among patients with schizophrenia, their unaffected first-degree relatives and healthy participants

BACKGROUND

Patients with schizophrenia (SCZ) display impaired executive functions compared with healthy controls (HCs). Furthermore, unaffected first-degree relatives (FRs) of patients with SCZ independently perform worse executive functions than do HCs. However, few studies have investigated the differences in executive functions assessed among patients with SCZ, FRs, and HCs, and the findings are inconsistent.

METHODS

We investigated diagnostic differences in executive functions, namely, (i) numbers of categories achieved (CA), (ii) total errors (TE) and (iii) %perseverative errors of Nelson types (%PEN), using the Wisconsin card sorting test (WCST) among patients with SCZ (n=116), unaffected FRs (n=62) and HCs (n=146) at a single institute. Correlations between these executive functions and clinical variables were investigated.

RESULTS

Significant differences existed in all executive functions among diagnostic groups (CA, F2,319=15.5, p=3.71×10-7; TE, F2,319=16.2, p=2.06×10-7; and %PEN, F2,319=21.3, p=2.15×10-9). Patients with SCZ had fewer CA and more TE and %PEN than those of HCs (CA, Cohen's d=-0.70, p=5.49×10-8; TE, d=0.70, p=5.62×10-8; and %PEN, d=0.82, p=2.85×10-10) and FRs (TE, d=0.46, p=3.73×10-3 and %PEN, d=0.38, p=0.017). Of the three executive functions, CA and %PEN of FRs were intermediately impaired between patients with SCZ and HCs (CA, d=-0.41, p=0.011 and %PEN, d=0.41, p=0.012). In contrast, no significant difference in TE existed between FRs and HCs (d=0.22, p=0.18). Although CA and TE were affected by the duration of illness (p<0.017), %PEN was not affected by any clinical variable in patients with SCZ (p>0.017).

CONCLUSIONS

Executive function, particularly %PEN, could be a useful intermediate phenotype for understanding the genetic mechanisms implicated in SCZ pathophysiology.

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.