Genome-wide association study results for educational attainment aid in identifying genetic heterogeneity of schizophrenia

Transcriptomic changes in oligodendrocytes and precursor cells associate with clinical outcomes of Parkinson's disease

Several prior studies have proposed the involvement of various brain regions and cell types in Parkinson's disease (PD) pathology. Here, we performed snRNA-seq on the prefrontal cortex and anterior cingulate regions from a small cohort of post-mortem control and PD brain tissue. We found a significant association of oligodendrocytes (ODCs) and oligodendrocyte precursor cells (OPCs) with PD-linked risk loci and report several dysregulated genes and pathways, including regulation of tau-protein kinase activity, regulation of inclusion body assembly and protein processing involved in protein targeting to mitochondria. In an independent PD cohort with clinical measures (681 cases and 549 controls), polygenic risk scores derived from the dysregulated genes significantly predicted Montreal Cognitive Assessment (MoCA)-, and Beck Depression Inventory-II (BDI-II)-scores but not motor impairment (UPDRS-III). We extended our analysis of clinical outcome prediction by incorporating differentially expressed genes from three separate datasets that were previously published by different laboratories. In the first dataset from the anterior cingulate cortex, we identified an association between ODCs and BDI-II. In the second dataset obtained from the substantia nigra (SN), OPCs displayed an association with UPDRS-III. In the third dataset from the SN region, a distinct subtype of OPCs, labeled OPC_ADM, exhibited an association with UPDRS-III. Intriguingly, the OPC_ADM cluster also demonstrated a significant increase in PD samples. These results suggest that by expanding our focus to glial cells, we can uncover region-specific molecular pathways associated with PD symptoms.

Polygenic Risk of Mental Disorders and Subject-Specific School Grades

BACKGROUND

Education is essential for socioeconomic security and long-term mental health; however, mental disorders are often detrimental to the educational trajectory. Genetic correlations between mental disorders and educational attainment do not always align with corresponding phenotypic associations, implying heterogeneity in the genetic overlap.

METHODS

We unraveled this heterogeneity by investigating associations between polygenic risk scores for 6 mental disorders and fine-grained school outcomes: school grades in language and mathematics in ninth grade and high school, as well as educational attainment by age 25, using nationwide-representative data from established cohorts (N = 79,489).

RESULTS

High polygenic liability of attention-deficit/hyperactivity disorder was associated with lower grades in language and mathematics, whereas high polygenic risk of anorexia nervosa or bipolar disorder was associated with higher grades in language and mathematics. Associations between polygenic risk and school grades were mixed for schizophrenia and major depressive disorder and neutral for autism spectrum disorder.

CONCLUSIONS

Polygenic risk scores for mental disorders are differentially associated with language and mathematics school grades.

Early cognitive development and psychopathology in children at familial high risk for schizophrenia

Schizophrenia is a neurodevelopmental disorder associated with deficits in cognitive development and childhood psychopathology. Previous studies have focused on older children and the few studies of early childhood have yielded inconsistent findings. We studied cognitive development and psychopathology in children at familial high risk (FHR) of schizophrenia and matched controls from 1 to 6 years and hypothesized that FHR children would show consistent deficits across cognitive and behavioral measures in early childhood.

STUDY DESIGN

Cognitive development in children at high familial risk for schizophrenia or schizoaffective disorder (n = 33) and matched healthy controls (n = 66) was assessed at 1 and 2 years with the Mullen Scales of Early Learning, and at 4 and 6 years with the Stanford Binet Intelligence Scales, BRIEF-P/BRIEF and CANTAB. Psychopathology was assessed at 4 and 6 years with the BASC-2. General linear models were used to examine differences on outcome scores, and chi-square analyses were used to explore differences in the proportion of "at risk" or "below average" score profiles.

STUDY RESULTS

FHR children scored significantly lower than controls on Mullen Composite at age 2, and demonstrated broad deficits in IQ, executive function and working memory and 4 and 6 years. FHR children were also rated as significantly worse on most items of the BASC-2 at ages 4 and 6.

CONCLUSIONS

Children at FHR for schizophrenia demonstrate abnormal cognitive development and psychopathology at younger ages than previously detected, suggesting that early detection and intervention needs to be targeted to very early childhood.

Hub genes, a diagnostic model, and immune infiltration based on ferroptosis-linked genes in schizophrenia

Background

Schizophrenia (SCZ) is a prevalent and serious mental disorder, and the exact pathophysiology of this condition is not fully understood. In previous studies, it has been proven that ferroprotein levels are high in SCZ. It has also been shown that this inflammatory response may modify fibromodulin. Accumulating evidence indicates a strong link between metabolism and ferroptosis. Therefore, the present study aims to identify ferroptosis-linked hub genes to further investigate the role that ferroptosis plays in the development of SCZ.

Material and methods

From the GEO database, four microarray data sets on SCZ (GSE53987, GSE38481, GSE18312, and GSE38484) and ferroptosis-linked genes were extracted. Using the prefrontal cortex expression matrix of SCZ patients and healthy individuals as the control group from GSE53987, weighted gene co-expression network analysis (WGCNA) was performed to discover SCZ-linked module genes. From the feed, genes associated with ferroptosis were retrieved. The intersection of the module and ferroptosis-linked genes was done to obtain the hub genes. Then, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and Gene Set Enrichment Analysis (GSEA) were conducted. The SCZ diagnostic model was established using logistic regression, and the GSE38481, GSE18312, and GSE38484 data sets were used to validate the model. Finally, hub genes linked to immune infiltration were examined.

Results

A total of 13 SCZ module genes and 7 hub genes linked to ferroptosis were obtained: DECR1, GJA1, EFN2L2, PSAT1, SLC7A11, SOX2, and YAP1. The GO/KEGG/GSEA study indicated that these hub genes were predominantly enriched in mitochondria and lipid metabolism, oxidative stress, immunological inflammation, ferroptosis, Hippo signaling pathway, AMP-activated protein kinase pathway, and other associated biological processes. The diagnostic model created using these hub genes was further confirmed using the data sets of three blood samples from patients with SCZ. The immune infiltration data showed that immune cell dysfunction enhanced ferroptosis and triggered SCZ.

Conclusion

In this study, seven critical genes that are strongly associated with ferroptosis in patients with SCZ were discovered, a valid clinical diagnostic model was built, and a novel therapeutic target for the treatment of SCZ was identified by the investigation of immune infiltration.

Genetic regulation of cell type-specific chromatin accessibility shapes brain disease etiology

Nucleotide variants in cell type-specific gene regulatory elements in the human brain are risk factors for human disease. We measured chromatin accessibility in 1932 aliquots of sorted neurons and non-neurons from 616 human postmortem brains and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTLs). Only 10.4% of caQTLs are shared between neurons and non-neurons, which supports cell type-specific genetic regulation of the brain regulome. Incorporating allele-specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms that underlie disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs and identified the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides insights into disease etiology.

Dissecting the polygenic contribution of attention-deficit/hyperactivity disorder and autism spectrum disorder on school performance by their relationship with educational attainment

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorders (ASD) are strongly associated with educational attainment (EA), but little is known about their genetic relationship with school performance and whether these links are explained, in part, by the genetic liability of EA. Here, we aim to dissect the polygenic contribution of ADHD and ASD to school performance, early manifestation of psychopathology and other psychiatric disorders and related traits by their relationship with EA. To do so, we tested the association of polygenic scores for EA, ADHD and ASD with school performance, assessed whether the contribution of the genetic liability of ADHD and ASD to school performance is influenced by the genetic liability of EA, and evaluated the role of EA in the genetic overlap between ADHD and ASD with early manifestation of psychopathology and other psychiatric disorders and related traits in a sample of 4,278 school-age children. The genetic liability for ADHD and ASD dissected by their relationship with EA show differences in their association with school performance and early manifestation of psychopathology, partly mediated by ADHD and ASD symptoms. Genetic variation with concordant effects in ASD and EA contributes to better school performance, while the genetic variation with discordant effects in ADHD or ASD and EA is associated with poor school performance and higher rates of emotional and behavioral problems. Our results strongly support the usage of the genetic load for EA to dissect the genetic and phenotypic heterogeneity of ADHD and ASD, which could help to fill the gap of knowledge of mechanisms underlying educational outcomes.

Dissecting Schizophrenia Biology Using Pleiotropy with Cognitive Genomics

Given the increasingly large number of loci discovered by psychiatric GWAS, specification of the key biological pathways underlying these loci has become a priority for the field. We have previously leveraged the pleiotropic genetic relationships between schizophrenia and two cognitive phenotypes (educational attainment and cognitive task performance) to differentiate two subsets of illness-relevant SNPs: (1) those with "concordant" alleles, which are associated with reduced cognitive ability/education and increased schizophrenia risk; and (2) those with "discordant" alleles linked to reduced educational and/or cognitive levels but lower schizophrenia susceptibility. In the present study, we extend our prior work, utilizing larger input GWAS datasets and a more powerful statistical approach to pleiotropic meta-analysis, the Pleiotropic Locus Exploration and Interpretation using Optimal test (PLEIO). Our pleiotropic meta-analysis of schizophrenia and the two cognitive phenotypes revealed 768 significant loci (159 novel). Among these, 347 loci harbored concordant SNPs, 270 encompassed discordant SNPs, and 151 "dual" loci contained concordant and discordant SNPs. Competitive gene-set analysis using MAGMA related concordant SNP loci with neurodevelopmental pathways (e.g., neurogenesis), whereas discordant loci were associated with mature neuronal synaptic functions. These distinctions were also observed in BrainSpan analysis of temporal enrichment patterns across developmental periods, with concordant loci containing more prenatally expressed genes than discordant loci. Dual loci were enriched for genes related to mRNA translation initiation, representing a novel finding in the schizophrenia literature.

Exploring the influences of education, intelligence and income on mental disorders

Background

Previous studies have shown that educational attainment (EA), intelligence and income are key factors associated with mental disorders. However, the direct effects of each factor on major mental disorders are unclear.

Aims

We aimed to evaluate the overall and independent causal effects of the three psychosocial factors on common mental disorders.

Methods

Using genome-wide association study summary datasets, we performed Mendelian randomisation (MR) and multivariable MR (MVMR) analyses to assess potential associations between the 3 factors (EA, N=766 345; household income, N=392 422; intelligence, N=146 808) and 13 common mental disorders, with sample sizes ranging from 9907 to 807 553. Inverse-variance weighting was employed as the main method in the MR analysis.

Results

Our MR analysis showed that (1) higher EA was a protective factor for eight mental disorders but contributed to anorexia nervosa, obsessive-compulsive disorder (OCD), bipolar disorder (BD) and autism spectrum disorder (ASD); (2) higher intelligence was a protective factor for five mental disorders but a risk factor for OCD and ASD; (3) higher household income protected against 10 mental disorders but confers risk for anorexia nervosa. Our MVMR analysis showed that (1) higher EA was a direct protective factor for attention-deficit/hyperactivity disorder (ADHD) and insomnia but a direct risk factor for schizophrenia, BD and ASD; (2) higher intelligence was a direct protective factor for schizophrenia but a direct risk factor for major depressive disorder (MDD) and ASD; (3) higher income was a direct protective factor for seven mental disorders, including schizophrenia, BD, MDD, ASD, post-traumatic stress disorder, ADHD and anxiety disorder.

Conclusions

Our study reveals that education, intelligence and income intertwine with each other. For each factor, its independent effects on mental disorders present a more complex picture than its overall effects.

Unraveling shared susceptibility loci and Mendelian genetic associations linking educational attainment with multiple neuropsychiatric disorders

Background

Empirical studies have demonstrated that educational attainment (EA) is associated with neuropsychiatric disorders (NPDs), suggesting a shared etiological basis between them. However, little is known about the shared genetic mechanisms and causality behind such associations.

Methods

This study explored the shared genetic basis and causal relationships between EA and NPDs using the high-definition likelihood (HDL) method, cross phenotype association study (CPASSOC), transcriptome-wide association study (TWAS), and bidirectional Mendelian randomization (MR) with summary-level data for EA (N = 293,723) and NPDs (N range = 9,725 to 455,258).

Results

Significant genetic correlations between EA and 12 NPDs (rg range - 0.49 to 0.35; all p < 3.85 × 10-3) were observed. CPASSOC identified 37 independent loci shared between EA and NPDs, one of which was novel (rs71351952, mapped gene: ARFGEF2). Functional analyses and TWAS found shared genes were enriched in brain tissue, especially in the cerebellum and highlighted the regulatory role of neuronal signaling, purine nucleotide metabolic process, and cAMP-mediated signaling pathways. CPASSOC and TWAS supported the role of three regions of 6q16.1, 3p21.31, and 17q21.31 might account for the shared causes between EA and NPDs. MR confirmed higher genetically predicted EA lower the risk of ADHD (ORIVW: 0.50; 95% CI: 0.39 to 0.63) and genetically predicted ADHD decreased the risk of EA (Causal effect: -2.8 months; 95% CI: -3.9 to -1.8).

Conclusion

These findings provided evidence of shared genetics and causation between EA and NPDs, advanced our understanding of EA, and implicated potential biological pathways that might underlie both EA and NPDs.

Genetic regulation of cell-type specific chromatin accessibility shapes the etiology of brain diseases

Nucleotide variants in cell type-specific gene regulatory elements in the human brain are major risk factors of human disease. We measured chromatin accessibility in sorted neurons and glia from 1,932 samples of human postmortem brain and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTL). Only 10.4% of caQTL are shared between neurons and glia, supporting the cell type specificity of genetic regulation of the brain regulome. Incorporating allele specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms underlying disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs, identifying the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides novel insights into brain disease etiology.

Wrestling with Social and Behavioral Genomics: Risks, Potential Benefits, and Ethical Responsibility

In this consensus report by a diverse group of academics who conduct and/or are concerned about social and behavioral genomics (SBG) research, the authors recount the often-ugly history of scientific attempts to understand the genetic contributions to human behaviors and social outcomes. They then describe what the current science-including genomewide association studies and polygenic indexes-can and cannot tell us, as well as its risks and potential benefits. They conclude with a discussion of responsible behavior in the context of SBG research. SBG research that compares individuals within a group according to a "sensitive" phenotype requires extra attention to responsible conduct and to responsible communication about the research and its findings. SBG research (1) on sensitive phenotypes that (2) compares two or more groups defined by (a) race, (b) ethnicity, or (c) genetic ancestry (where genetic ancestry could easily be misunderstood as race or ethnicity) requires a compelling justification to be conducted, funded, or published. All authors agree that this justification at least requires a convincing argument that a study's design could yield scientifically valid results; some authors would additionally require the study to have a socially favorable risk-benefit profile.

Pathways from developmental vulnerabilities in early childhood to schizotypy in middle childhood

OBJECTIVES

Childhood disturbances in social, emotional, language, motor and cognitive functioning, and schizotypy have each been implicated as precursors of schizophrenia-spectrum disorders. We investigated whether relationships between early childhood developmental vulnerabilities and childhood schizotypy are mediated by educational underachievement in middle childhood.

METHODS

Participants were members of a large Australian (n = 19,216) population cohort followed longitudinally. Path analyses were used to model relationships between developmental vulnerabilities at age ~5 years, educational underachievement from ages ~8 to 10 years and three distinct profiles of schizotypy at age ~11 years (true, introverted and affective schizotypy).

RESULTS

Early childhood developmental vulnerabilities on five broad domains (related to physical, emotional, social, cognitive and communication development) were associated with schizotypy profiles in middle childhood. Educational underachievement in middle childhood was associated with all schizotypy profiles, but most strongly with the true schizotypy profile (OR = 3.92, 95% CI = 3.12, 4.91). The relationships between schizotypy profiles and early childhood developmental vulnerabilities in 'language and cognitive skills (school-based)' and 'communication skills and general knowledge' domains were fully mediated by educational underachievement in middle childhood, and the relationships with early childhood 'physical health and well-being' and 'emotional maturity' domains were partially mediated.

CONCLUSION

Developmental continuity from early childhood developmental vulnerabilities to schizotypy in middle childhood is mediated by educational underachievement in middle childhood. While some domains of early developmental functioning showed differential relationships with distinct schizotypy profiles, these findings support a developmental pathway to schizotypy in which cognitive vulnerability operates from early childhood through to middle childhood.

Genome-wide association study of school grades identifies genetic overlap between language ability, psychopathology and creativity

Cognitive functions of individuals with psychiatric disorders differ from that of the general population. Such cognitive differences often manifest early in life as differential school performance and have a strong genetic basis. Here we measured genetic predictors of school performance in 30,982 individuals in English, Danish and mathematics via a genome-wide association study (GWAS) and studied their relationship with risk for six major psychiatric disorders. When decomposing the school performance into math and language-specific performances, we observed phenotypically and genetically a strong negative correlation between math performance and risk for most psychiatric disorders. But language performance correlated positively with risk for certain disorders, especially schizophrenia, which we replicate in an independent sample (n = 4547). We also found that the genetic variants relating to increased risk for schizophrenia and better language performance are overrepresented in individuals involved in creative professions (n = 2953) compared to the general population (n = 164,622). The findings together suggest that language ability, creativity and psychopathology might stem from overlapping genetic roots.

Developmental control of noradrenergic system by SLITRK1 and its implications in the pathophysiology of neuropsychiatric disorders

SLITRK1 is a neuronal transmembrane protein with neurite development-and synaptic formation-controlling abilities. Several rare variants of SLITRK1 have been identified and implicated in the pathogenesis of Tourette's syndrome, trichotillomania, and obsessive-compulsive disorder, which can be collectively referred to as obsessive-compulsive-spectrum disorders. Recent studies have reported a possible association between bipolar disorder and schizophrenia, including a revertant of modern human-specific amino acid residues. Although the mechanisms underlying SLITRK1-associated neuropsychiatric disorders are yet to be fully clarified, rodent studies may provide some noteworthy clues. Slitrk1-deficient mice show neonatal dysregulation of the noradrenergic system, and later, anxiety-like behaviors that can be attenuated by an alpha 2 noradrenergic receptor agonist. The noradrenergic abnormality is characterized by the excessive growth of noradrenergic fibers and increased noradrenaline content in the medial prefrontal cortex, concomitant with enlarged serotonergic varicosities. Slitrk1 has both cell-autonomous and cell-non-autonomous functions in controlling noradrenergic fiber development, and partly alters Sema3a-mediated neurite control. These findings suggest that transiently enhanced noradrenergic signaling during the neonatal stage could cause neuroplasticity associated with neuropsychiatric disorders. Studies adopting noradrenergic signal perturbation via pharmacological or genetic means support this hypothesis. Thus, Slitrk1 is a potential candidate genetic linkage between the neonatal noradrenergic signaling and the pathophysiology of neuropsychiatric disorders involving anxiety-like or depression-like behaviors.

Collective genomic segments with differential pleiotropic patterns between cognitive dimensions and psychopathology

Cognitive deficits are known to be related to most forms of psychopathology. Here, we perform local genetic correlation analysis as a means of identifying independent segments of the genome that show biologically interpretable pleiotropic associations between cognitive dimensions and psychopathology. We identify collective segments of the genome, which we call "meta-loci", showing differential pleiotropic patterns for psychopathology relative to either cognitive task performance (CTP) or performance on a non-cognitive factor (NCF) derived from educational attainment. We observe that neurodevelopmental gene sets expressed during the prenatal-early childhood period predominate in CTP-relevant meta-loci, while post-natal gene sets are more involved in NCF-relevant meta-loci. Further, we demonstrate that neurodevelopmental gene sets are dissociable across CTP meta-loci with respect to their spatial distribution across the brain. Additionally, we find that GABA-ergic, cholinergic, and glutamatergic genes drive pleiotropic relationships within dissociable meta-loci.

Cultural evolution may influence heritability by shaping assortative mating

Uchiyama et al. productively discuss how culture can influence genetic heritability and, by modifying environmental conditions, limit the generalizability of genome-wide association studies (GWASs). Here, we supplement their account by highlighting how recent changes in culture and institutions in industrialized, westernized societies - such as increased female workforce participation - may have increased assortative mating. This alters the distribution of genotypes themselves, increasing heritability and phenotypic variance, and may be detectable using the latest methods.

SLITRK1-mediated noradrenergic projection suppression in the neonatal prefrontal cortex

SLITRK1 is an obsessive-compulsive disorder spectrum-disorders-associated gene that encodes a neuronal transmembrane protein. Here we show that SLITRK1 suppresses noradrenergic projections in the neonatal prefrontal cortex, and SLITRK1 functions are impaired by SLITRK1 mutations in patients with schizophrenia (S330A, a revertant of Homo sapiens-specific residue) and bipolar disorder (A444S). Slitrk1-KO newborns exhibit abnormal vocalizations, and their prefrontal cortices show excessive noradrenergic neurites and reduced Semaphorin3A expression, which suppresses noradrenergic neurite outgrowth in vitro. Slitrk1 can bind Dynamin1 and L1 family proteins (Neurofascin and L1CAM), as well as suppress Semaphorin3A-induced endocytosis. Neurofascin-binding kinetics is altered in S330A and A444S mutations. Consistent with the increased obsessive-compulsive disorder prevalence in males in childhood, the prefrontal cortex of male Slitrk1-KO newborns show increased noradrenaline levels, and serotonergic varicosity size. This study further elucidates the role of noradrenaline in controlling the development of the obsessive-compulsive disorder-related neural circuit.

A Novel Gene Controls a New Structure: PiggyBac Transposable Element-Derived 1, Unique to Mammals, Controls Mammal-Specific Neuronal Paraspeckles

Although new genes can arrive from modes other than duplication, few examples are well characterized. Given high expression in some human brain subregions and a putative link to psychological disorders [e.g., schizophrenia (SCZ)], suggestive of brain functionality, here we characterize piggyBac transposable element-derived 1 (PGBD1). PGBD1 is nonmonotreme mammal-specific and under purifying selection, consistent with functionality. The gene body of human PGBD1 retains much of the original DNA transposon but has additionally captured SCAN and KRAB domains. Despite gene body retention, PGBD1 has lost transposition abilities, thus transposase functionality is absent. PGBD1 no longer recognizes piggyBac transposon-like inverted repeats, nonetheless PGBD1 has DNA binding activity. Genome scale analysis identifies enrichment of binding sites in and around genes involved in neuronal development, with association with both histone activating and repressing marks. We focus on one of the repressed genes, the long noncoding RNA NEAT1, also dysregulated in SCZ, the core structural RNA of paraspeckles. DNA binding assays confirm specific binding of PGBD1 both in the NEAT1 promoter and in the gene body. Depletion of PGBD1 in neuronal progenitor cells (NPCs) results in increased NEAT1/paraspeckles and differentiation. We conclude that PGBD1 has evolved core regulatory functionality for the maintenance of NPCs. As paraspeckles are a mammal-specific structure, the results presented here show a rare example of the evolution of a novel gene coupled to the evolution of a contemporaneous new structure.

A Large-Scale Genome-Wide Gene-Gene Interaction Study of Lung Cancer Susceptibility in Europeans With a Trans-Ethnic Validation in Asians

INTRODUCTION

Although genome-wide association studies have been conducted to investigate genetic variation of lung tumorigenesis, little is known about gene-gene (G × G) interactions that may influence the risk of non-small cell lung cancer (NSCLC).

METHODS

Leveraging a total of 445,221 European-descent participants from the International Lung Cancer Consortium OncoArray project, Transdisciplinary Research in Cancer of the Lung and UK Biobank, we performed a large-scale genome-wide G × G interaction study on European NSCLC risk by a series of analyses. First, we used BiForce to evaluate and rank more than 58 billion G × G interactions from 340,958 single-nucleotide polymorphisms (SNPs). Then, the top interactions were further tested by demographically adjusted logistic regression models. Finally, we used the selected interactions to build lung cancer screening models of NSCLC, separately, for never and ever smokers.

RESULTS

With the Bonferroni correction, we identified eight statistically significant pairs of SNPs, which predominantly appeared in the 6p21.32 and 5p15.33 regions (e.g., rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.17, p = 6.57 × 10-13; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.17, p = 2.43 × 10-13; rs2858859HLA-DQA1 and rs9275572HLA-DQA2, ORinteraction = 1.15, p = 2.84 × 10-13; rs2853668TERT and rs62329694CLPTM1L, ORinteraction = 0.73, p = 2.70 × 10-13). Notably, even with much genetic heterogeneity across ethnicities, three pairs of SNPs in the 6p21.32 region identified from the European-ancestry population remained significant among an Asian population from the Nanjing Medical University Global Screening Array project (rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.13, p = 0.008; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.11, p = 5.23 × 10-4; rs3135369BTNL2 and rs9271300HLA-DQA1, ORinteraction = 0.89, p = 0.006). The interaction-empowered polygenetic risk score that integrated classical polygenetic risk score and G × G information score was remarkable in lung cancer risk stratification.

CONCLUSIONS

Important G × G interactions were identified and enriched in the 5p15.33 and 6p21.32 regions, which may enhance lung cancer screening models.

The impact of educational attainment, intelligence and intellectual disability on schizophrenia: a Swedish population-based register and genetic study

Schizophrenia (SCZ) is highly heterogenous and no subtypes characterizing treatment response or longitudinal course well. Cognitive impairment is a core clinical feature of SCZ and a determinant of poorer outcome. Genetic overlap between SCZ and cognitive traits is complex, with limited studies of comprehensive epidemiological and genomic evidence. To examine the relation between SCZ and three cognitive traits, educational attainment (EDU), premorbid cognitive ability, and intellectual disability (ID), we used two Swedish samples: a national cohort (14,230 SCZ cases and 3,816,264 controls) and a subsample with comprehensive genetic data (4992 cases and 6009 controls). Population-based analyses confirmed worse cognition as a risk factor for SCZ, and the pedigree and SNP-based genetic correlations were comparable. In the genotyped cases, those with high EDU and premorbid cognitive ability tended to have higher polygenetic risk scores (PRS) of EDU and intelligence and fewer rare exonic variants. Finally, by applying an empirical clustering method, we dissected SCZ cases into four replicable subgroups characterized by EDU and ID. In particular, the subgroup with higher EDU in the national cohort had fewer adverse outcomes including long hospitalization and death. In the genotyped subsample, this subgroup had higher PRS of EDU and no excess of rare genetic burdens than controls. In conclusion, we found extensive evidence of a robust relation between cognitive traits and SCZ, underscoring the importance of cognition in dissecting the heterogeneity of SCZ.

Educational attainment and mortality in schizophrenia

BACKGROUND

Individuals suffering from schizophrenia have a reduced life expectancy with cardiovascular disease (CVD) as a major contributor. Low educational attainment is associated with schizophrenia, as well as with all-cause and CVD mortality. However, it is unknown to what extent low educational attainment can explain the increased mortality in individuals with schizophrenia.

AIM

Here, we quantify associations between educational attainment and all-cause and CVD mortality in individuals with schizophrenia, and compare them with the corresponding associations in the general population.

METHOD

All Norwegian citizens born between January 1, 1925, and December 31, 1959, were followed up from January 1, 1990, to December 31, 2014. The total sample included 1,852,113 individuals, of which 6548 were registered with schizophrenia. We estimated hazard ratios (HR) for all-cause and CVD mortality with Cox models, in addition to life years lost. Educational attainment for index persons and their parents were included in the models.

RESULTS

In the general population individuals with low educational attainment had higher risk of all-cause (HR: 1.48 [95% CI: 1.47-1.49]) and CVD (HR: 1.59 [95% CI: 1.57-1.61]) mortality. In individuals with schizophrenia these estimates were substantially lower (all-cause: HR: 1.13 [95% CI: 1.05-1.21] and CVD: HR: 1.12 [95% CI: 0.98-1.27]). Low educational attainment accounted for 3.28 (3.21-3.35) life years lost in males and 2.48 (2.42-2.55) years in females in the general population, but was not significantly associated with life years lost in individuals with schizophrenia. Results were similar for parental educational attainment.

CONCLUSIONS

Our results indicate that while individuals with schizophrenia in general have lower educational attainment and higher mortality rates compared with the general population, the association between educational attainment and mortality is smaller in schizophrenia subjects than in the general population.

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57.

Neurocognitive heterogeneity in 7-year-old children at familial high risk of schizophrenia or bipolar disorder: The Danish high risk and resilience study - VIA 7

BACKGROUND

Studies of neurocognitive heterogeneity in young children at familial high-risk of bipolar disorder (FHR-BP) or schizophrenia (FHR-SZ) are important to investigate inter-individual neurocognitive differences. We aimed to identify neurocognitive subgroups, describe prevalence of FHR-BP or FHR-SZ children herein, and examine risk ratios (RR) compared with controls.

METHODS

In a population-based cohort of 514 7-year-old children (197 FHR-SZ, 118 FHR-BP, and 199 matched controls) we used hierarchical cluster analyses to identify subgroups across 14 neurocognitive indices.

RESULTS

Three neurocognitive subgroups were derived: A Mildly Impaired (30%), Typical (51%), and Above Average subgroup (19%). The Mildly Impaired subgroup significantly underperformed controls (Cohen d = 0.11-1.45; Ps < 0.001) except in set-shifting (P = .84). FHR-SZ children were significantly more prevalent in the Mildly Impaired subgroup; FHR-BP children were more so in the Above Average subgroup (X² (2, N = 315) = 9.64, P < .01). 79.7% FHR-BP and 64.6% FHR-SZ children demonstrated typical or above average neurocognitive functions. Neurocognitive heterogeneity related significantly to concurrent functioning, psychopathology severity, home environment adequacy, and polygenic scores for schizophrenia (Ps <. 01). Compared with controls, FHR-SZ and FHR-BP children had a 93% (RR, 1.93; 95% CI, 1.40-2.64) and 8% (RR, 1.08; 95% CI, 0.71-1.66) increased risk of Mildly Impaired subgroup membership.

LIMITATIONS

Limitations include the cross-sectional design and smaller FHR-BP sample size.

CONCLUSIONS

Identification of neurocognitive heterogeneity in preadolescent children at FHR-BP or FHR-SZ may ease stigma and enable pre-emptive interventions to enhance neurocognitive functioning and resilience to mental illness in the impaired sub-population.

Investigating genetic overlaps of the genetic factor differentiating schizophrenia from bipolar disorder with cognitive function and hippocampal volume

Schizophrenia and bipolar disorder display clinical similarities and dissimilarities. We investigated whether the genetic factor differentiating schizophrenia from bipolar disorder is genetically associated with cognitive phenotypes and hippocampal volumes. We revealed genetic overlaps of the genetic differentiating factor with low general cognitive ability, low childhood IQ, low educational attainment and reduced hippocampal volumes. The genetic correlations with low general cognitive ability and reduced hippocampal volumes were associated with risk of schizophrenia, whereas the genetic correlations with high childhood IQ and educational attainment were associated with risks of bipolar disorder. These findings suggest these disorders have disorder-specific genetic factors related to clinical phenotypes.

Association of polygenic risk for schizophrenia with fast sleep spindle density depends on pro-cognitive variants

Cognitive impairment is a common feature in schizophrenia and the strongest prognostic factor for long-term outcome. Identifying a trait associated with the genetic background for cognitive outcome in schizophrenia may aid in a deeper understanding of clinical disease subtypes. Fast sleep spindles may represent such a biomarker as they are strongly genetically determined, associated with cognitive functioning and impaired in schizophrenia and unaffected relatives. We measured fast sleep spindle density in 150 healthy adults and investigated its association with a genome-wide polygenic score for schizophrenia (SCZ-PGS). The association between SCZ-PGS and fast spindle density was further characterized by stratifying it to the genetic background of intelligence. SCZ-PGS was positively associated with fast spindle density. This association mainly depended on pro-cognitive genetic variants. Our results strengthen the evidence for a genetic background of spindle abnormalities in schizophrenia. Spindle density might represent an easily accessible marker for a favourable cognitive outcome which should be further investigated in clinical samples.

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.

Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning

Psychiatric disorders show heterogeneous symptoms and trajectories, with current nosology not accurately reflecting their molecular etiology and the variability and symptomatic overlap within and between diagnostic classes. This heterogeneity impedes timely and targeted treatment. Our study aimed to identify psychiatric patient clusters that share clinical and genetic features and may profit from similar therapies. We used high-dimensional data clustering on deep clinical data to identify transdiagnostic groups in a discovery sample (N = 1250) of healthy controls and patients diagnosed with depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other psychiatric disorders. We observed five diagnostically mixed clusters and ordered them based on severity. The least impaired cluster 0, containing most healthy controls, showed general well-being. Clusters 1-3 differed predominantly regarding levels of maltreatment, depression, daily functioning, and parental bonding. Cluster 4 contained most patients diagnosed with psychotic disorders and exhibited the highest severity in many dimensions, including medication load. Depressed patients were present in all clusters, indicating that we captured different disease stages or subtypes. We replicated all but the smallest cluster 1 in an independent sample (N = 622). Next, we analyzed genetic differences between clusters using polygenic scores (PGS) and the psychiatric family history. These genetic variables differed mainly between clusters 0 and 4 (prediction area under the receiver operating characteristic curve (AUC) = 81%; significant PGS: cross-disorder psychiatric risk, schizophrenia, and educational attainment). Our results confirm that psychiatric disorders consist of heterogeneous subtypes sharing molecular factors and symptoms. The identification of transdiagnostic clusters advances our understanding of the heterogeneity of psychiatric disorders and may support the development of personalized treatments.

Reconstructing Sociogenomics Research: Dismantling Biological Race and Genetic Essentialism Narratives

We detail the implications of sociogenomics for social determinants research. We focus on education and race because of how early twentieth-century scientific eugenic thinking facilitated a range of racist and eugenic policies, most of which helped justify and pattern racial and educational morbidity and mortality disparities that remain today, and are central to sociological research. Consequently, we detail the implications of sociogenomics research by unpacking key controversies and opportunities in sociogenomics as they pertain to the understanding of racial and educational inequalities. We clarify why race is not a valid biological or genetic construct, the ways that environments powerfully shape genetic influence, and risks linked to this field of research. We argue that sociologists can usefully engage in genetics research, a domain dominated by psychologists and behaviorists who, given their focus on individuals, have mostly not examined the role of history and social structure in shaping genetic influence.

Identification of genetic overlap and novel risk loci for attention-deficit/hyperactivity disorder and bipolar disorder

Differential diagnosis between childhood onset attention-deficit/hyperactivity disorder (ADHD) and bipolar disorder (BD) remains a challenge, mainly due to overlapping symptoms and high rates of comorbidity. Despite this, genetic correlation reported for these disorders is low and non-significant. Here we aimed to better characterize the genetic architecture of these disorders utilizing recent large genome-wide association studies (GWAS). We analyzed independent GWAS summary statistics for ADHD (19,099 cases and 34,194 controls) and BD (20,352 cases and 31,358 controls) applying the conditional/conjunctional false discovery rate (condFDR/conjFDR) statistical framework that increases the power to detect novel phenotype-specific and shared loci by leveraging the combined power of two GWAS. We observed cross-trait polygenic enrichment for ADHD conditioned on associations with BD, and vice versa. Leveraging this enrichment, we identified 19 novel ADHD risk loci and 40 novel BD risk loci at condFDR <0.05. Further, we identified five loci jointly associated with ADHD and BD (conjFDR < 0.05). Interestingly, these five loci show concordant directions of effect for ADHD and BD. These results highlight a shared underlying genetic risk for ADHD and BD which may help to explain the high comorbidity rates and difficulties in differentiating between ADHD and BD in the clinic. Improving our understanding of the underlying genetic architecture of these disorders may aid in the development of novel stratification tools to help reduce these diagnostic difficulties.

Genetic Influences on Disease Subtypes

Disease classification, or nosology, was historically driven by careful examination of clinical features of patients. As technologies to measure and understand human phenotypes advanced, so too did classifications of disease, and the advent of genetic data has led to a surge in genetic subtyping in the past decades. Although the fundamental process of refining disease definitions and subtypes is shared across diverse fields, each field is driven by its own goals and technological expertise, leading to inconsistent and conflicting definitions of disease subtypes. Here, we review several classical and recent subtypes and subtyping approaches and provide concrete definitions to delineate subtypes. In particular, we focus on subtypes with distinct causal disease biology, which are of primary interest to scientists, and subtypes with pragmatic medical benefits, which are of primary interest to physicians. We propose genetic heterogeneity as a gold standard for establishing biologically distinct subtypes of complex polygenic disease. We focus especially on methods to find and validate genetic subtypes, emphasizing common pitfalls and how to avoid them.

Phenotypically independent profiles relevant to mental health are genetically correlated

Genome-wide association studies (GWAS) and family-based studies have revealed partly overlapping genetic architectures between various psychiatric disorders. Given clinical overlap between disorders, our knowledge of the genetic architectures underlying specific symptom profiles and risk factors is limited. Here, we aimed to derive distinct profiles relevant to mental health in healthy individuals and to study how these genetically relate to each other and to common psychiatric disorders. Using independent component analysis, we decomposed self-report mental health questionnaires from 136,678 healthy individuals of the UK Biobank, excluding data from individuals with a diagnosed neurological or psychiatric disorder, into 13 distinct profiles relevant to mental health, capturing different symptoms as well as social and risk factors underlying reduced mental health. Utilizing genotypes from 117,611 of those individuals with White British ancestry, we performed GWAS for each mental health profile and assessed genetic correlations between these profiles, and between the profiles and common psychiatric disorders and cognitive traits. We found that mental health profiles were genetically correlated with a wide range of psychiatric disorders and cognitive traits, with strongest effects typically observed between a given mental health profile and a disorder for which the profile is common (e.g. depression symptoms and major depressive disorder, or psychosis and schizophrenia). Strikingly, although the profiles were phenotypically uncorrelated, many of them were genetically correlated with each other. This study provides evidence that statistically independent mental health profiles partly share genetic underpinnings and show genetic overlap with psychiatric disorders, suggesting that shared genetics across psychiatric disorders cannot be exclusively attributed to the known overlapping symptomatology between the disorders.

Genome-wide Association Analysis of Parkinson's Disease and Schizophrenia Reveals Shared Genetic Architecture and Identifies Novel Risk Loci

BACKGROUND

Parkinson's disease (PD) and schizophrenia (SCZ) are heritable brain disorders that involve dysregulation of the dopaminergic system. Epidemiological studies have reported potential comorbidity between the disorders, and movement disturbances are common in patients with SCZ before treatment with antipsychotic drugs. Despite this, little is known about shared genetic etiology between the disorders.

METHODS

We analyzed recent large genome-wide association studies on patients with SCZ (N = 77,096) and PD (N = 417,508) using a conditional/conjunctional false discovery rate (FDR) approach to evaluate overlap in common genetic variants and improve statistical power for genetic discovery. Using a variety of biological resources, we functionally characterized the identified genomic loci.

RESULTS

We observed genetic enrichment in PD conditional on associations with SCZ and vice versa, indicating polygenic overlap. We then leveraged this cross-trait enrichment using conditional FDR analysis and identified 9 novel PD risk loci and 1 novel SCZ locus at conditional FDR < .01. Furthermore, we identified 9 genomic loci jointly associated with PD and SCZ at conjunctional FDR < .05. There was an even distribution of antagonistic and agonistic effect directions among the shared loci, in line with the insignificant genetic correlation between the disorders. Of 67 genes mapped to the shared loci, 65 are expressed in the human brain and show cell type-specific expression profiles.

CONCLUSIONS

Altogether, the study increases understanding of the genetic architectures underlying SCZ and PD, indicating that common molecular genetic mechanisms may contribute to overlapping pathophysiological and clinical features between the disorders.

Pharmacotherapy of schizophrenia: Mechanisms of antipsychotic accumulation, therapeutic action and failure

Schizophrenia is a multi-dimensional disorder with a complex and mostly unknown etiology, leading to a severe decline in life quality. Antipsychotic drugs (APDs) remain beneficial interventions in the treatment of the disorder, but vary significantly in binding profile, clinical effects and adverse reactions. The present review summarizes the main principles of APD mechanisms of action with a particular focus on recent findings in APD accumulation and its role in the therapeutic efficacy and treatment failure. High and low doses of APDs were shown to be effective in different dimensions of antipsychotic-like behaviour in rodent models. Efficacy of the APDs correlates with high dopamine D2 receptor occupancy, which occurs quickly after drug administration. However, onset and peak of action are delayed up to several days or weeks. APD accumulation via acidic trapping in synaptic vesicles is considered to underlie the time course of APD action. Use-dependent exocytosis, co-release with dopamine and serotonin and inhibition of ion channels impact on the neuronal transmission and determine effects of APDs. Disruption in accumulating properties leads to diminished APD effects. In addition, long-term APD administration at therapeutic doses leads to treatment failure both in animal models and in humans. APD failure was associated with treatment induced neuroadaptations, including a decline in extracellular dopamine levels, dopamine transporter upregulation, and altered neuronal firing. However, enhanced synaptic vesicle release has also been reported. APD loss of efficacy may be reversed through inhibition of the dopamine transporter or switching the administration regimen from continuous to intermittent. Thus, manipulating the accumulation properties of APDs, changes in the administration regimen and doses, or co-administration with dopamine transporter inhibitors may be considered to yield benefits in the development of new effective strategies in the treatment of schizophrenia.

Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction

Little is known about the genetic architecture of traits affecting educational attainment other than cognitive ability. We used genomic structural equation modeling and prior genome-wide association studies (GWASs) of educational attainment (n = 1,131,881) and cognitive test performance (n = 257,841) to estimate SNP associations with educational attainment variation that is independent of cognitive ability. We identified 157 genome-wide-significant loci and a polygenic architecture accounting for 57% of genetic variance in educational attainment. Noncognitive genetics were enriched in the same brain tissues and cell types as cognitive performance, but showed different associations with gray-matter brain volumes. Noncognitive genetics were further distinguished by associations with personality traits, less risky behavior and increased risk for certain psychiatric disorders. For socioeconomic success and longevity, noncognitive and cognitive-performance genetics demonstrated associations of similar magnitude. By conducting a GWAS of a phenotype that was not directly measured, we offer a view of genetic architecture of noncognitive skills influencing educational success.

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.

Interactome overlap between schizophrenia and cognition

Cognitive impairments constitute a core feature of schizophrenia, and a genetic overlap between schizophrenia and cognitive functioning in healthy individuals has been identified. However, due to the high polygenicity and complex genetic architecture of both traits, overlapping biological pathways have not yet been identified between schizophrenia and normal cognitive ability. Network medicine offers a framework to study underlying biological pathways through protein-protein interactions among risk genes. Here, established network-based methods were used to characterize the biological relatedness of schizophrenia and cognition by examining the genetic link between schizophrenia risk genes and genes associated with cognitive performance in healthy individuals, through the protein interactome. First, network separation showed a profound interactome overlap between schizophrenia risk genes and genes associated with cognitive performance (S_AB = -0.22, z-score = -6.80, p = 5.38e-12). To characterize this overlap, network propagation was thereafter used to identify schizophrenia risk genes that are close to cognition-associated genes in the interactome network space (n = 140, of which 54 were part of the direct genetic overlap). Schizophrenia risk genes close to cognition were enriched for pathways including long-term potentiation and Alzheimer's disease, and included genes with a role in neurotransmitter systems important for cognitive functioning, such as glutamate and dopamine. These results pinpoint a subset of schizophrenia risk genes that are of particular interest for further examination in schizophrenia patient groups, of which some are druggable genes with potential as candidate targets for cognitive enhancing drugs.

Genome-wide association study of cognitive function in diverse Hispanics/Latinos: results from the Hispanic Community Health Study/Study of Latinos

Cognitive function such as reasoning, attention, memory, and language is strongly correlated with brain aging. Compared to non-Hispanic whites, Hispanics/Latinos have a higher risk of cognitive impairment and dementia. The genetic determinants of cognitive function have not been widely explored in this diverse and admixed population. We conducted a genome-wide association analysis of cognitive function in up to 7600 middle aged and older Hispanics/Latinos (mean = 55 years) from the Hispanic Community Health Study / Study of Latinos (HCHS/SOL). Four cognitive measures were examined: the Brief Spanish English Verbal Learning Test (B-SEVLT), the Word Fluency Test (WFT), the Digit Symbol Substitution Test (DSST), the Six-Item Screener (SIS). Four novel loci were identified: one for B-SEVLT at 4p14, two for WFT at 3p14.1 and 6p21.32, and one for DSST at 10p13. These loci implicate genes highly expressed in brain and previously connected to neurological diseases (UBE2K, FRMD4B, the HLA gene complex). By applying tissue-specific gene expression prediction models to our genotype data, additional genes highly expressed in brain showed suggestive associations with cognitive measures possibly indicating novel biological mechanisms, including IFT122 in the hippocampus for SIS, SNX31 in the basal ganglia for B-SEVLT, RPS6KB2 in the frontal cortex for WFT, and CSPG5 in the hypothalamus for DSST. These findings provide new information about the genetic determinants of cognitive function in this unique population. In addition, we derived a measure of general cognitive function based on these cognitive tests and generated genome-wide association summary results, providing a resource to the research community for comparison, replication, and meta-analysis in future genetic studies in Hispanics/Latinos.

Quantifying the Polygenic Architecture of the Human Cerebral Cortex: Extensive Genetic Overlap between Cortical Thickness and Surface Area

The thickness of the cerebral cortical sheet and its surface area are highly heritable traits thought to have largely distinct polygenic architectures. Despite large-scale efforts, the majority of their genetic determinants remain unknown. Our ability to identify causal genetic variants can be improved by employing brain measures that better map onto the biology we seek to understand. Such measures may have fewer variants but with larger effects, that is, lower polygenicity and higher discoverability. Using Gaussian mixture modeling, we estimated the number of causal variants shared between mean cortical thickness and total surface area, as well as the polygenicity and discoverability of regional measures. We made use of UK Biobank data from 30 880 healthy White European individuals (mean age 64.3, standard deviation 7.5, 52.1% female). We found large genetic overlap between total surface area and mean thickness, sharing 4016 out of 7941 causal variants. Regional surface area was more discoverable (P = 2.6 × 10⁻⁶) and less polygenic (P = 0.004) than regional thickness measures. These findings may serve as a roadmap for improved future GWAS studies; knowledge of which measures are most discoverable may be used to boost identification of genetic predictors and thereby gain a better understanding of brain morphology.

Using genetics for social science

Social science genetics is concerned with understanding whether, how and why genetic differences between human beings are linked to differences in behaviours and socioeconomic outcomes. Our review discusses the goals, methods, challenges and implications of this research endeavour. We survey how the recent developments in genetics are beginning to provide social scientists with a powerful new toolbox they can use to better understand environmental effects, and we illustrate this with several substantive examples. Furthermore, we examine how medical research can benefit from genetic insights into social-scientific outcomes and vice versa. Finally, we discuss the ethical challenges of this work and clarify several common misunderstandings and misinterpretations of genetic research on individual differences.

Heterogeneity and Polygenicity in Psychiatric Disorders: A Genome-Wide Perspective

Genome-wide association studies (GWAS) have been performed for many psychiatric disorders and revealed a complex polygenic architecture linking mental and physical health phenotypes. Psychiatric diagnoses are often heterogeneous, and several layers of trait heterogeneity may contribute to detection of genetic risks per disorder or across multiple disorders. In this review, we discuss these heterogeneities and their consequences on the discovery of risk loci using large-scale genetic data. We primarily highlight the ways in which sex and diagnostic complexity contribute to risk locus discovery in schizophrenia, bipolar disorder, attention deficit hyperactivity disorder, autism spectrum disorder, posttraumatic stress disorder, major depressive disorder, obsessive-compulsive disorder, Tourette’s syndrome and chronic tic disorder, anxiety disorders, suicidality, feeding and eating disorders, and substance use disorders. Genetic data also have facilitated discovery of clinically relevant subphenotypes also described here. Collectively, GWAS of psychiatric disorders revealed that the understanding of heterogeneity, polygenicity, and pleiotropy is critical to translate genetic findings into treatment strategies.

An Investigation of Psychosis Subgroups With Prognostic Validation and Exploration of Genetic Underpinnings: The PsyCourse Study

IMPORTANCE

Identifying psychosis subgroups could improve clinical and research precision. Research has focused on symptom subgroups, but there is a need to consider a broader clinical spectrum, disentangle illness trajectories, and investigate genetic associations.

OBJECTIVE

To detect psychosis subgroups using data-driven methods and examine their illness courses over 1.5 years and polygenic scores for schizophrenia, bipolar disorder, major depression disorder, and educational achievement.

DESIGN, SETTING, AND PARTICIPANTS

This ongoing multisite, naturalistic, longitudinal (6-month intervals) cohort study began in January 2012 across 18 sites. Data from a referred sample of 1223 individuals (765 in the discovery sample and 458 in the validation sample) with DSM-IV diagnoses of schizophrenia, bipolar affective disorder (I/II), schizoaffective disorder, schizophreniform disorder, and brief psychotic disorder were collected from secondary and tertiary care sites. Discovery data were extracted in September 2016 and analyzed from November 2016 to January 2018, and prospective validation data were extracted in October 2018 and analyzed from January to May 2019.

MAIN OUTCOMES AND MEASURES

A clinical battery of 188 variables measuring demographic characteristics, clinical history, symptoms, functioning, and cognition was decomposed using nonnegative matrix factorization clustering. Subtype-specific illness courses were compared with mixed models and polygenic scores with analysis of covariance. Supervised learning was used to replicate results in validation data with the most reliably discriminative 45 variables.

RESULTS

Of the 765 individuals in the discovery sample, 341 (44.6%) were women, and the mean (SD) age was 42.7 (12.9) years. Five subgroups were found and labeled as affective psychosis (n = 252), suicidal psychosis (n = 44), depressive psychosis (n = 131), high-functioning psychosis (n = 252), and severe psychosis (n = 86). Illness courses with significant quadratic interaction terms were found for psychosis symptoms (R2 = 0.41; 95% CI, 0.38-0.44), depression symptoms (R2 = 0.28; 95% CI, 0.25-0.32), global functioning (R2 = 0.16; 95% CI, 0.14-0.20), and quality of life (R2 = 0.20; 95% CI, 0.17-0.23). The depressive and severe psychosis subgroups exhibited the lowest functioning and quadratic illness courses with partial recovery followed by reoccurrence of severe illness. Differences were found for educational attainment polygenic scores (mean [SD] partial η2 = 0.014 [0.003]) but not for diagnostic polygenic risk. Results were largely replicated in the validation cohort.

CONCLUSIONS AND RELEVANCE

Psychosis subgroups were detected with distinctive clinical signatures and illness courses and specificity for a nondiagnostic genetic marker. New data-driven clinical approaches are important for future psychosis taxonomies. The findings suggest a need to consider short-term to medium-term service provision to restore functioning in patients stratified into the depressive and severe psychosis subgroups.

A multivariable Mendelian randomization to appraise the pleiotropy between intelligence, education, and bipolar disorder in relation to schizophrenia

Education and intelligence are highly correlated and inversely associated with schizophrenia. Counterintuitively, education genetically associates with an increased risk for the disease. To investigate why, this study applies a multivariable Mendelian randomization of intelligence and education. For those without college degrees, older age of finishing school associates with a decreased likelihood of schizophrenia-independent of intelligence-and, hence, may be entangled with the health inequalities reflecting differences in education. A different picture is observed for schooling years inclusive of college: more years of schooling increases the likelihood of schizophrenia, whereas higher intelligence distinctly and independently decreases it. This implies the pleiotropy between years of schooling and schizophrenia is horizontal and likely confounded by a third trait influencing education. A multivariable Mendelian randomization of schooling years and bipolar disorder reveals that the increased risk of schizophrenia conferred by more schooling years is an artefact of bipolar disorder - not education.

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.

On the origin of schizophrenia: Testing evolutionary theories in the post-genomic era

Considering the relatively high heritability of schizophrenia and the fact that it significantly reduces the reproductive fitness of affected individuals, it is not clear how the disorder is still maintained in human populations at a disproportionally high prevalence. Many theories propose that the disorder is a result of a trade-off between costs and benefits of the evolution of exclusively human adaptations. There have also been suggestions that schizophrenia risk alleles are accompanied with increase in fitness of affected persons or their relatives in both past and current social contexts. The discoveries of novel schizophrenia-related genes and the advancements in comparative genomics (especially comparisons of the human genome and the genomes of related species, such as chimpanzees and extinct hominids) have finally made certain evolutionary theories testable. In this paper, we review the current understanding of the genetics of schizophrenia, the basic principles of evolution that complement our understanding of the subject, and the latest genetic studies that examine long-standing evolutionary theories of schizophrenia using novel methodologies and data. We find that the origin of schizophrenia is complex and likely governed by different evolutionary mechanisms that are not mutually exclusive. Furthermore, the most recent evidence implies that schizophrenia cannot be comprehended as a trait that has elevated fitness in human evolutionary lineage, but has been a mildly deleterious by-product of specific patterns of the evolution of the human brain. In other words, novel findings do not support previous hypotheses stating that schizophrenia risk genes have an evolutionary advantage.

Neuropeptides and oligopeptidases in schizophrenia

Schizophrenia (SCZ) is a complex psychiatric disorder with severe impact on patient's livelihood. In the last years, the importance of neuropeptides in SCZ and other CNS disorders has been recognized, mainly due to their ability to modulate the signaling of classical monoaminergic neurotransmitters as dopamine. In addition, a class of enzymes coined as oligopeptidases are able to cleave several of these neuropeptides, and their potential implication in SCZ was also demonstrated. Interestingly, these enzymes are able to play roles as modulators of neuropeptidergic systems, and they were also implicated in neurogenesis, neurite outgrowth, neuron migration, and therefore, in neurodevelopment and brain formation. Altered activity of oligopeptidases in SCZ was described only more recently, suggesting their possible utility as biomarkers for mental disorders diagnosis or treatment response. We provide here an updated and comprehensive review on neuropeptides and oligopeptidases involved in mental disorders, aiming to attract the attention of physicians to the potential of targeting this system for improving the therapy and for understanding the neurobiology underlying mental disorders as SCZ.

The emerging pattern of shared polygenic architecture of psychiatric disorders, conceptual and methodological challenges

Genome-wide association studies have transformed psychiatric genetics and provided novel insights into the genetic etiology of psychiatric disorders. Two major discoveries have emerged; the disorders are polygenic, with a large number of common variants each with a small effect and many genetic variants influence more than one phenotype, suggesting shared genetic etiology. These concepts have the potential to revolutionize the current classification system with diagnostic categories and facilitate development of better treatments. However, to reach clinical impact, we need larger samples and better analytical tools, as most polygenic factors remain undetected. We here present statistical approaches designed to improve the yield of existing genome-wide association studies for polygenic phenotypes. We review how these tools have informed the current knowledge on the genetic architecture of psychiatric disorders, focusing on schizophrenia, bipolar disorder and major depression, and overlap with psychological and cognitive traits. We discuss application of statistical tools for stratification and prediction.

Common brain disorders are associated with heritable patterns of apparent aging of the brain

Common risk factors for psychiatric and other brain disorders are likely to converge on biological pathways influencing the development and maintenance of brain structure and function across life. Using structural MRI data from 45,615 individuals aged 3-96 years, we demonstrate distinct patterns of apparent brain aging in several brain disorders and reveal genetic pleiotropy between apparent brain aging in healthy individuals and common brain disorders.