Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations.

Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well.

Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium.

Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.

Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study.

Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia's alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.

Neurexins in autism and schizophrenia-a review of patient mutations, mouse models and potential future directions.

Mutations in the family of neurexins (NRXN1, NRXN2 and NRXN3) have been repeatedly identified in patients with autism spectrum disorder (ASD) and schizophrenia (SCZ). However, it remains unclear how these DNA variants affect neurexin functions and thereby predispose to these neurodevelopmental disorders. Understanding both the wild-type and pathologic roles of these genes in the brain could help unveil biological mechanisms underlying mental disorders. In this regard, numerous studies have focused on generating relevant loss-of-function (LOF) mammalian models. Although this has increased our knowledge about their normal functions, the potential pathologic role(s) of these human variants remains elusive. Indeed, after reviewing the literature, it seems apparent that a traditional LOF-genetic approach based on complete LOF might not be sufficient to unveil the role of these human mutations. First, these genes present a very complex transcriptome and total-LOF of all isoforms may not be the cause of toxicity in patients, particularly given evidence that causative variants act through haploinsufficiency. Moreover, human DNA variants may not all lead to LOF but potentially to intricate transcriptome changes that could also include the generation of aberrant isoforms acting as a gain-of-function (GOF). Furthermore, their transcriptomic complexity most likely renders them prone to genetic compensation when one tries to manipulate them using traditional site-directed mutagenesis approaches, and this could act differently from model to model leading to heterogeneous and conflicting phenotypes. This review compiles the relevant literature on variants identified in human studies and on the mouse models currently deployed, and offers suggestions for future research.

Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA.

A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).

Wnt receptor gene FZD1 was associated with schizophrenia in genome-wide SNP analysis of the Australian Schizophrenia Research Bank cohort.

OBJECTIVES: Large-scale genetic analysis of common variation in schizophrenia has been a powerful approach to understanding this complex but highly heritable psychotic disorder. To further investigate loci, genes and pathways associated more specifically in the well-characterized Australian Schizophrenia Research Bank cohort, we applied genome-wide single-nucleotide polymorphism analysis in these three annotation categories. METHODS: We performed a case-control genome-wide association study in 429 schizophrenia samples and 255 controls. Post-genome-wide association study analyses were then integrated with genomic annotations to explore the enrichment of variation at the gene and pathway level. We also examine candidate single-nucleotide polymorphisms with potential function within expression quantitative trait loci and investigate overall enrichment of variation within tissue-specific functional regulatory domains of the genome. RESULTS: The strongest finding (p = 2.01 × 10-6, odds ratio = 1.82, 95% confidence interval = [1.42, 2.33]) in genome-wide association study was with rs10252923 at 7q21.13, downstream of FZD1 (frizzled class receptor 1). While this did not stand alone after correction, the involvement of FZD1 was supported by gene-based analysis, which exceeded the threshold for genome-wide significance (p = 2.78 × 10-6). CONCLUSION: The identification of FZD1, as an independent association signal at the gene level, supports the hypothesis that the Wnt signalling pathway is altered in the pathogenesis of schizophrenia and may be an important target for therapeutic development.

Stria terminalis, amygdala, and temporoparietal junction networks facilitate efficient emotion processing under expectations.

Rapid emotion processing is an ecologically essential ability for survival in social environments in which threatening or advantageous encounters dynamically and rapidly occur. Efficient emotion recognition is subserved by different processes, depending on one's expectations; however, the underlying functional and structural circuitry is still poorly understood. In this study, we delineate brain networks that subserve fast recognition of emotion in situations either congruent or incongruent with prior expectations. For this purpose, we used multimodal neuroimaging and investigated performance on a dynamic emotion perception task. We show that the extended amygdala structural and functional networks relate to speed of emotion processing under threatening conditions. Specifically, increased microstructure of the right stria terminalis, an amygdala white-matter pathway, was related to faster detection of emotion during actual presentation of anger or after cueing anger. Moreover, functional connectivity of right amygdala with limbic regions was related to faster detection of anger congruent with cue, suggesting selective attention to threat. On the contrary, we found that faster detection of anger incongruent with cue engaged the ventral attention "reorienting" network. Faster detection of happiness, in either expectancy context, engaged a widespread frontotemporal-subcortical functional network. These findings shed light on the functional and structural circuitries that facilitate speed of emotion recognition and, for the first time, elucidate a role for the stria terminalis in human emotion processing.

Is there a role for antibodies targeting muscarinic acetylcholine receptors in the pathogenesis of schizophrenia?

OBJECTIVE: Muscarinic receptor dysfunction has been suggested to play an important role in the pathophysiology of schizophrenia. Recently, it has also become clear that immune reactivity directed against neurotransmitter receptors may play a pathogenic role in some cases of schizophrenia. The aim of this review is to summarize the case for muscarinic receptor dysfunction in schizophrenia and the evidence supporting the hypothesis that this dysfunction is related to the development of muscarinic receptor-targeting antibodies. METHOD: The article reviews studies of muscarinic receptors and the presence and potential role(s) of anti-muscarinic acetylcholine receptor antibodies in people with schizophrenia. RESULTS: There is accumulating evidence that altered or deficient muscarinic signalling underlies some of the key clinical features of schizophrenia. Although the number of studies investigating anti-muscarinic acetylcholine receptor antibodies in schizophrenia is relatively small, they consistently demonstrate that such antibodies are present in a proportion of patients. This evidence suggests that these antibodies could have pathogenic effects or exist as a biomarker to an unknown pathophysiological process in schizophrenia. CONCLUSION: The presence of elevated levels of anti-muscarinic acetylcholine receptor antibodies may identify a subgroup of people with schizophrenia, potentially informing aetiopathogenesis, clinical presentation and treatment. To date, all studies have examined antibodies in participants with chronic schizophrenia, who have likely received antipsychotic medication for many years. As these medications modulate immune functions and regulate receptor densities, it is recommended that future studies screen for the presence of anti-muscarinic antibodies in people experiencing their first episode of psychosis.

No Reliable Association between Runs of Homozygosity and Schizophrenia in a Well-Powered Replication Study.

It is well known that inbreeding increases the risk of recessive monogenic diseases, but it is less certain whether it contributes to the etiology of complex diseases such as schizophrenia. One way to estimate the effects of inbreeding is to examine the association between disease diagnosis and genome-wide autozygosity estimated using runs of homozygosity (ROH) in genome-wide single nucleotide polymorphism arrays. Using data for schizophrenia from the Psychiatric Genomics Consortium (n = 21,868), Keller et al. (2012) estimated that the odds of developing schizophrenia increased by approximately 17% for every additional percent of the genome that is autozygous (ß = 16.1, CI(ß) = [6.93, 25.7], Z = 3.44, p = 0.0006). Here we describe replication results from 22 independent schizophrenia case-control datasets from the Psychiatric Genomics Consortium (n = 39,830). Using the same ROH calling thresholds and procedures as Keller et al. (2012), we were unable to replicate the significant association between ROH burden and schizophrenia in the independent PGC phase II data, although the effect was in the predicted direction, and the combined (original + replication) dataset yielded an attenuated but significant relationship between Froh and schizophrenia (ß = 4.86,CI(ß) = [0.90,8.83],Z = 2.40,p = 0.02). Since Keller et al. (2012), several studies reported inconsistent association of ROH burden with complex traits, particularly in case-control data. These conflicting results might suggest that the effects of autozygosity are confounded by various factors, such as socioeconomic status, education, urbanicity, and religiosity, which may be associated with both real inbreeding and the outcome measures of interest.

Identification of loci associated with schizophrenia by genome-wide association and follow-up.

We carried out a genome-wide association study of schizophrenia (479 cases, 2,937 controls) and tested loci with P < 10(-5) in up to 16,726 additional subjects. Of 12 loci followed up, 3 had strong independent support (P < 5 x 10(-4)), and the overall pattern of replication was unlikely to occur by chance (P = 9 x 10(-8)). Meta-analysis provided strongest evidence for association around ZNF804A (P = 1.61 x 10(-7)) and this strengthened when the affected phenotype included bipolar disorder (P = 9.96 x 10(-9)).

Additive genetic variation in schizophrenia risk is shared by populations of African and European descent.

To investigate the extent to which the proportion of schizophrenia's additive genetic variation tagged by SNPs is shared by populations of European and African descent, we analyzed the largest combined African descent (AD [n = 2,142]) and European descent (ED [n = 4,990]) schizophrenia case-control genome-wide association study (GWAS) data set available, the Molecular Genetics of Schizophrenia (MGS) data set. We show how a method that uses genomic similarities at measured SNPs to estimate the additive genetic correlation (SNP correlation [SNP-rg]) between traits can be extended to estimate SNP-rg for the same trait between ethnicities. We estimated SNP-rg for schizophrenia between the MGS ED and MGS AD samples to be 0.66 (SE = 0.23), which is significantly different from 0 (p(SNP-rg = 0) = 0.0003), but not 1 (p(SNP-rg = 1) = 0.26). We re-estimated SNP-rg between an independent ED data set (n = 6,665) and the MGS AD sample to be 0.61 (SE = 0.21, p(SNP-rg = 0) = 0.0003, p(SNP-rg = 1) = 0.16). These results suggest that many schizophrenia risk alleles are shared across ethnic groups and predate African-European divergence.

Verbal Initiation, Suppression, and Strategy Use and the Relationship with Clinical Symptoms in Schizophrenia.

OBJECTIVES: Individuals with schizophrenia have difficulties on measures of executive functioning such as initiation and suppression of responses and strategy development and implementation. The current study thoroughly examines performance on the Hayling Sentence Completion Test (HSCT) in individuals with schizophrenia, introducing novel analyses based on initiation errors and strategy use, and association with lifetime clinical symptoms. METHODS: The HSCT was administered to individuals with schizophrenia (N=77) and age- and sex-matched healthy controls (N=45), along with background cognitive tests. The standard HSCT clinical measures (initiation response time, suppression response time, suppression errors), composite initiation and suppression error scores, and strategy-based responses were calculated. Lifetime clinical symptoms [formal thought disorder (FTD), positive, negative] were calculated using the Lifetime Dimensions of Psychosis Scale. RESULTS: After controlling for baseline cognitive differences, individuals with schizophrenia were significantly impaired on the suppression response time and suppression error scales. For the novel analyses, individuals with schizophrenia produced a greater number of initiation errors and subtly wrong errors, and produced fewer responses indicative of developing an appropriate strategy. Strategy use was negatively correlated with FTD symptoms in individuals with schizophrenia. CONCLUSIONS: The current study provides further evidence for deficits in the initiation and suppression of verbal responses in individuals with schizophrenia. Moreover, an inability to attain a strategy at least partly contributes to increased semantically connected errors when attempting to suppress responses. The association between strategy use and FTD points to the involvement of executive deficits in disorganized speech in schizophrenia. (JINS, 2016, 22, 735-743).

Common variants on chromosome 6p22.1 are associated with schizophrenia.

Schizophrenia, a devastating psychiatric disorder, has a prevalence of 0.5-1%, with high heritability (80-85%) and complex transmission. Recent studies implicate rare, large, high-penetrance copy number variants in some cases, but the genes or biological mechanisms that underlie susceptibility are not known. Here we show that schizophrenia is significantly associated with single nucleotide polymorphisms (SNPs) in the extended major histocompatibility complex region on chromosome 6. We carried out a genome-wide association study of common SNPs in the Molecular Genetics of Schizophrenia (MGS) case-control sample, and then a meta-analysis of data from the MGS, International Schizophrenia Consortium and SGENE data sets. No MGS finding achieved genome-wide statistical significance. In the meta-analysis of European-ancestry subjects (8,008 cases, 19,077 controls), significant association with schizophrenia was observed in a region of linkage disequilibrium on chromosome 6p22.1 (P = 9.54 x 10(-9)). This region includes a histone gene cluster and several immunity-related genes--possibly implicating aetiological mechanisms involving chromatin modification, transcriptional regulation, autoimmunity and/or infection. These results demonstrate that common schizophrenia susceptibility alleles can be detected. The characterization of these signals will suggest important directions for research on susceptibility mechanisms.

Clinical and parental age characteristics of rare copy number variant burden in patients with schizophrenia.

Copy number variant (CNV) burden, especially for rare deletions, has been associated with risk for schizophrenia as well as phenotypic differences within cognitive and neuroimaging domains. The current study investigated clinical and parental age characteristics of rare CNV burden in patients with schizophrenia. Clinical data was collected for 629 patients with schizophrenia who formed part of a genomewide association study, which included CNV data. Parental age was available for 368 patients. Correlations were calculated between burden scores and positive, negative, and mood symptoms from the Lifetime Diagnostic Psychosis Scale as well as age at onset. Patients were grouped according to number of rare deletions, duplications, or total CNVs and MANOVAs used to investigate differences in clinical and parental age characteristics. Patients with the least number of CNVs had older fathers and larger parental age difference. Patients with no deletions had older mothers and those with five or more deletions had younger mothers. Total deletion, duplication, and CNV burden, as measured by number of base pairs, were not associated with clinical or parental age differences although total rare duplication burden had a negative correlation with positive symptoms that did not survive correction for multiple testing. Likewise, a positive correlation between age at onset and total CNV burden did not survive correction. Rare CNVs are associated with differences in parental age in patients with schizophrenia. No robust clinical differences were identified. However, duplication burden may have a small protective effect against positive symptoms and age at onset may be influenced by total CNV burden. No clinical differences were associated with deletion burden measures.

Hybridization-based reconstruction of small non-coding RNA transcripts from deep sequencing data.

Recent advances in RNA sequencing technology (RNA-Seq) enables comprehensive profiling of RNAs by producing millions of short sequence reads from size-fractionated RNA libraries. Although conventional tools for detecting and distinguishing non-coding RNAs (ncRNAs) from reference-genome data can be applied to sequence data, ncRNA detection can be improved by harnessing the full information content provided by this new technology. Here we present NorahDesk, the first unbiased and universally applicable method for small ncRNAs detection from RNA-Seq data. NorahDesk utilizes the coverage-distribution of small RNA sequence data as well as thermodynamic assessments of secondary structure to reliably predict and annotate ncRNA classes. Using publicly available mouse sequence data from brain, skeletal muscle, testis and ovary, we evaluated our method with an emphasis on the performance for microRNAs (miRNAs) and piwi-interacting small RNA (piRNA). We compared our method with Dario and mirDeep2 and found that NorahDesk produces longer transcripts with higher read coverage. This feature makes it the first method particularly suitable for the prediction of both known and novel piRNAs.

DSM-IV "criterion A" schizophrenia symptoms across ethnically different populations: evidence for differing psychotic symptom content or structural organization?

There is significant variation in the expression of schizophrenia across ethnically different populations, and the optimal structural and diagnostic representation of schizophrenia are contested. We contrasted both lifetime frequencies of DSM-IV criterion A (the core symptom criterion of the internationally recognized DSM classification system) symptoms and types/content of delusions and hallucinations in transethnic schizophrenia populations from Australia (n = 776), India (n = 504) and Sarawak, Malaysia (n = 259), to elucidate clinical heterogeneity. Differences in both criterion A symptom composition and symptom content were apparent. Indian individuals with schizophrenia reported negative symptoms more frequently than other sites, whereas individuals from Sarawak reported disorganized symptoms more frequently. Delusions of control and thought broadcast, insertion, or withdrawal were less frequent in Sarawak than Australia. Curiously, a subgroup of 20 Indian individuals with schizophrenia reported no lifetime delusions or hallucinations. These findings potentially challenge the long-held view in psychiatry that schizophrenia is fundamentally similar across cultural groups, with differences in only the content of psychotic symptoms, but equivalence in structural form.

Optimising the zebrafish Cre/Lox toolbox. Codon improved iCre, new gateway tools, Cre protein and guidelines.

We recently introduced the Cre/Lox technology in our laboratory for both transient (mRNA injections) and stable/transgenic experiments. We experienced significant issues such as silencing, mosaicism, and partial recombination using both approaches. Reviewing the literature gave us the impression that these issues are common among the zebrafish community using the Cre/Lox system. While some researchers took advantage of these problems for specific applications, such as cell and lineage tracing using the Zebrabow construct, we tried here to improve the efficiency and reliability of this system by constituting and testing a new set of tools for zebrafish genetics. First, we implemented a codon-improved Cre version (iCre) designed for rodent studies to counteract some of the aforementioned problems. This eukaryotic-like iCre version was engineered to i) reduce silencing, ii) increase mRNA stability, iii) enhance translational efficiency, and iv) improve nuclear translocation. Second, we established a new set of tol2-kit compatible vectors to facilitate the generation of either iCre-mRNA or iCre-transgenes for transient and transgenic experiments, respectively. We then validated the use of this material and are providing tips for users. Interestingly, during the validation steps, we found that maternal iCRE-mRNA and/or protein deposition from female transgenics systematically led to complete/homogeneous conversion of all tested Lox-responder-transgenes, as opposed to some residual imperfect conversion when using males-drivers or mRNA injections. Considering that we did not find any evidence of Cre-protein soaking and injections in the literature as it is usually conducted with cells, we tested these approaches. While soaking of cell-permeant CRE-protein did not lead to any detectable Lox-conversion, 1ng-10 ng protein injections led to robust and homogeneous Lox-recombination, suggesting that the use of protein could be a robust option for exogenous delivery. This approach may be particularly useful to manipulate housekeeping genes involved in development, sex determination and reproduction which are difficult to investigate with traditional knockout approaches. All in all, we are providing here a new set of tools that should be useful in the field.

Genetic interactions of schizophrenia using gene-based statistical epistasis exclusively identify nervous system-related pathways and key hub genes.

Background: The relationship between genotype and phenotype is governed by numerous genetic interactions (GIs), and the mapping of GI networks is of interest for two main reasons: 1) By modelling biological robustness, GIs provide a powerful opportunity to infer compensatory biological mechanisms via the identification of functional relationships between genes, which is of interest for biological discovery and translational research. Biological systems have evolved to compensate for genetic (i.e., variations and mutations) and environmental (i.e., drug efficacy) perturbations by exploiting compensatory relationships between genes, pathways and biological processes; 2) GI facilitates the identification of the direction (alleviating or aggravating interactions) and magnitude of epistatic interactions that influence the phenotypic outcome. The generation of GIs for human diseases is impossible using experimental biology approaches such as systematic deletion analysis. Moreover, the generation of disease-specific GIs has never been undertaken in humans. Methods: We used our Indian schizophrenia case-control (case-816, controls-900) genetic dataset to implement the workflow. Standard GWAS sample quality control procedure was followed. We used the imputed genetic data to increase the SNP coverage to analyse epistatic interactions across the genome comprehensively. Using the odds ratio (OR), we identified the GIs that increase or decrease the risk of a disease phenotype. The SNP-based epistatic results were transformed into gene-based epistatic results. Results: We have developed a novel approach by conducting gene-based statistical epistatic analysis using an Indian schizophrenia case-control genetic dataset and transforming these results to infer GIs that increase the risk of schizophrenia. There were ∼9.5 million GIs with a p-value ≤ 1 × 10-5. Approximately 4.8 million GIs showed an increased risk (OR > 1.0), while ∼4.75 million GIs had a decreased risk (OR <1.0) for schizophrenia. Conclusion: Unlike model organisms, this approach is specifically viable in humans due to the availability of abundant disease-specific genome-wide genotype datasets. The study exclusively identified brain/nervous system-related processes, affirming the findings. This computational approach fills a critical gap by generating practically non-existent heritable disease-specific human GIs from human genetic data. These novel datasets can train innovative deep-learning models, potentially surpassing the limitations of conventional GWAS.

Schizophrenia risk conferred by rare protein-truncating variants is conserved across diverse human populations.

Schizophrenia (SCZ) is a chronic mental illness and among the most debilitating conditions encountered in medical practice. A recent landmark SCZ study of the protein-coding regions of the genome identified a causal role for ten genes and a concentration of rare variant signals in evolutionarily constrained genes1. This recent study-and most other large-scale human genetics studies-was mainly composed of individuals of European (EUR) ancestry, and the generalizability of the findings in non-EUR populations remains unclear. To address this gap, we designed a custom sequencing panel of 161 genes selected based on the current knowledge of SCZ genetics and sequenced a new cohort of 11,580 SCZ cases and 10,555 controls of diverse ancestries. Replicating earlier work, we found that cases carried a significantly higher burden of rare protein-truncating variants (PTVs) among evolutionarily constrained genes (odds ratio = 1.48; P = 5.4 × 10-6). In meta-analyses with existing datasets totaling up to 35,828 cases and 107,877 controls, this excess burden was largely consistent across five ancestral populations. Two genes (SRRM2 and AKAP11) were newly implicated as SCZ risk genes, and one gene (PCLO) was identified as shared by individuals with SCZ and those with autism. Overall, our results lend robust support to the rare allelic spectrum of the genetic architecture of SCZ being conserved across diverse human populations.

Genetic influences on cost-efficient organization of human cortical functional networks.

The human cerebral cortex is a complex network of functionally specialized regions interconnected by axonal fibers, but the organizational principles underlying cortical connectivity remain unknown. Here, we report evidence that one such principle for functional cortical networks involves finding a balance between maximizing communication efficiency and minimizing connection cost, referred to as optimization of network cost-efficiency. We measured spontaneous fluctuations of the blood oxygenation level-dependent signal using functional magnetic resonance imaging in healthy monozygotic (16 pairs) and dizygotic (13 pairs) twins and characterized cost-efficient properties of brain network functional connectivity between 1041 distinct cortical regions. At the global network level, 60% of the interindividual variance in cost-efficiency of cortical functional networks was attributable to additive genetic effects. Regionally, significant genetic effects were observed throughout the cortex in a largely bilateral pattern, including bilateral posterior cingulate and medial prefrontal cortices, dorsolateral prefrontal and superior parietal cortices, and lateral temporal and inferomedial occipital regions. Genetic effects were stronger for cost-efficiency than for other metrics considered, and were more clearly significant in functional networks operating in the 0.09-0.18 Hz frequency interval than at higher or lower frequencies. These findings are consistent with the hypothesis that brain networks evolved to satisfy competitive selection criteria of maximizing efficiency and minimizing cost, and that optimization of network cost-efficiency represents an important principle for the brain's functional organization.