Nearly two decades of genome-wide association studies (GWAS) have identify thousands of disease-associated genetic variants, but very few genes with evidence of causality. Recent methodological advances demonstrate that Mendelian randomization (MR) using expression quantitative loci (eQTLs) as instrumental variables can detect potential causal genes. However, existing MR approaches are not well suited to handle the complexity of eQTL GWAS data structure and so they are subject to bias, inflation, and incorrect inference.

We present a whole-genome regulatory network analysis tool (HORNET), which is a comprehensive set of statistical and computational tools to perform genome-wide searches for causal genes using summary level GWAS data, i.e. robust to biases from multiple sources. Applying HORNET to schizophrenia, eQTL effects in the cerebellum were spread throughout the genome, and in the cortex were more localized to select loci.

Freely available at https://github.com/noahlorinczcomi/HORNET or Mac, Windows, and Linux users.

The neural extracellular matrix (ECM) accumulates in the form of perineuronal nets (PNNs), particularly around fast-spiking GABAergic interneurons in the cortex and hippocampus, but also around synapses and in association with the axon initial segments (AIS) and nodes of Ranvier. Increasing evidence highlights the role of Neurocan (Ncan), a brain-specific component of ECM, in the pathophysiology of neuropsychiatric disorders like bipolar disorder and schizophrenia. Ncan localizes at PNNs, perisynaptically, and at the nodes of Ranvier and the AIS, highlighting its potential role in regulating axonal excitability. Here, we used knockdown and knockout approaches in mouse primary cortical neurons in combination with immunocytochemistry, Western blotting and electrophysiological techniques to characterize the role of Ncan in the organization of PNNs and AISs and regulation of neuronal activity. We found that reduced Ncan levels led to remodeling of PNNs around neurons via upregulation of aggrecan mRNA and protein levels, increased expression of activity-dependent c-Fos and FosB genes and elevated spontaneous synaptic activity. The latter correlated with increased levels of ankyrin-G in the AIS, particularly in excitatory neurons, and with the elevated expression of Nav1.6 channels. Our results suggest that Ncan regulates the expression of key proteins in PNNs and AISs and provide new insights into its role in fine-tuning neuronal functions.

At the simplest level, neurons are structured to integrate synaptic input and perform computational transforms on that input, converting it into an action potential (AP) code. This process, converting synaptic input into AP output, typically occurs in a specialized region of the axon termed the axon initial segment (AIS). The AIS, as its name implies, is often contained to the first section of axon abutted to the soma and is home to a dizzying array of ion channels, attendant scaffolding proteins, intracellular organelles, extracellular proteins, and, in some cases, synapses. The AIS serves multiple roles as the final arbiter for determining if inputs are sufficient to evoke APs, as a gatekeeper that physically separates the somatodendritic domain from the axon proper, and as a regulator of overall neuronal excitability, dynamically tuning its size to best suit the needs of parent neurons. These complex roles have received considerable attention from experimentalists and theoreticians alike. Here, we review recent advances in our understanding of the AIS and its role in neuronal integration and polarity in health and disease.

Psychiatric disorders are highly comorbid, heritable, and genetically correlated [1-4]. The primary objective of cross-disorder psychiatric genetics research is to identify and characterize both the shared genetic factors that contribute to convergent disease etiologies and the unique genetic factors that distinguish between disorders [4, 5]. This information can illuminate the biological mechanisms underlying comorbid presentations of psychopathology, improve nosology and prediction of illness risk and trajectories, and aid the development of more effective and targeted interventions. In this review we discuss how estimates of comorbidity and identification of shared genetic loci between disorders can be influenced by how disorders are measured (phenotypic assessment) and the inclusion or exclusion criteria in individual genetic studies (sample ascertainment). Specifically, the depth of measurement, source of diagnosis, and time frame of disease trajectory have major implications for the clinical validity of the assessed phenotypes. Further, biases introduced in the ascertainment of both cases and controls can inflate or reduce estimates of genetic correlations. The impact of these design choices may have important implications for large meta-analyses of cohorts from diverse populations that use different forms of assessment and inclusion criteria, and subsequent cross-disorder analyses thereof. We review how assessment and ascertainment affect genetic findings in both univariate and multivariate analyses and conclude with recommendations for addressing them in future research.

CUB and sushi multiple domains 1 (CSMD1) is predominantly expressed in brain and robustly associated with schizophrenia risk; however, understanding of which cells express CSMD1 in brain and how it impacts risk is lacking. CSMD1 encodes a large transmembrane protein including fifteen tandem short consensus repeats (SCRs), resembling complement C3 convertase regulators. CSMD1 complement regulatory activity has been reported and mapped to SCR17-21. We expressed two SCR domains of CSMD1, SCR17-21 and SCR23-26, and characterised their complement regulatory activity using a panel of functional assays testing convertase and terminal pathway inhibition. Both domains inhibited the classical pathway C3 convertase by acting as factor I cofactors; neither domain caused any inhibition in alternative or terminal pathway assays. Novel anti-CSMD1 monoclonal antibodies cross-reactive with human and mouse CSMD1 were generated that detected endogenous CSMD1 in human and rodent brain; immunostaining showed predominantly astrocyte and synaptic localisation of CSMD1, the latter confirmed using isolated synapses. Using iPSC-derived cells, astrocyte expression was confirmed and expression on cortical neurons demonstrated. We show that CSMD1 is a classical pathway-specific complement regulator expressed predominantly on astrocytes, neurons, and synapses in human and mouse brain. These findings will help reveal the mechanism by which CSMD1 impacts schizophrenia risk.

The challenges in identifying functional variants from genome-wide association studies (GWAS) and unraveling regulatory mechanisms in schizophrenia research persist, particularly in intronic regions. A non-coding regulatory variant, rs1399178, associated with schizophrenia risk, is identified and its impact on NRF1 binding is investigated.

This study focuses on schizophrenia GWAS risk loci, using functional genomics, expression analyses and structural analysis to identify 736 schizophrenia risk single-nucleotide polymorphisms (SNPs) that disrupt transcription factor (TF) binding.

Among these SNPs, rs1399178 stands out as a bifunctional intergenic SNP that can switch between acting as a promoter and an enhancer, potentially influencing MLH1 and LRRFIP2 expression via expression quantitative trait loci analysis. Importantly, mutation of the G allele of rs1399178 to A significantly diminishes its binding affinity to nuclear respiratory factor 1 (NRF1). Structural analysis provides further insight into this alteration in the protein-nucleic acid complex formation.

Based on our data, a model is proposed in which rs1399178 confers schizophrenia risk by modifying NRF1 binding profiles, thereby regulating the abundance of target genes through promoter-enhancer switching. This study provides novel insights into the regulatory mechanisms of schizophrenia risk variants, highlighting the intricate nature of genetic interactions and potential therapeutic targets.

Genome-wide association studies (GWASs) have reported multiple risk loci for schizophrenia (SCZ). However, the majority of the associations were from populations of European ancestry. Here we conducted a large-scale GWAS in Eastern Asian populations (29,519 cases and 44,392 controls) and identified ten Eastern Asian-specific risk loci, two of which have not been previously reported. A further cross-ancestry GWAS meta-analysis (96,806 cases and 492,818 controls) including populations from diverse ancestries identified 61 previously unreported risk loci. Systematic variant-level analysis, including fine mapping, functional genomics and expression quantitative trait loci, prioritized potential causal variants. Gene-level analyses, including transcriptome-wide association study, proteome-wide association study and Mendelian randomization, nominated the potential causal genes. By integrating evidence from layers of different analyses, we prioritized the most plausible causal genes for SCZ, such as ACE, CNNM2, SNAP91, ABCB9 and GATAD2A. Finally, drug repurposing showed that ACE, CA14, MAPK3 and MAPT are potential therapeutic targets for SCZ. Our study not only showed the power of cross-ancestry GWAS in deciphering the genetic aetiology of SCZ, but also uncovered new genetic risk loci, potential causal variants and genes and therapeutic targets for SCZ.

Given the increasingly large number of loci discovered by psychiatric genome-wide association studies (GWASs), specification of the key biological pathways that underlie these loci has become a priority for the field. We have previously leveraged the pleiotropic genetic relationships between schizophrenia (SCZ) and 2 cognitive phenotypes (educational attainment and cognitive task performance) to differentiate 2 subsets of illness-relevant single nucleotide polymorphisms (SNPs): 1) those with concordant alleles, which are associated with reduced cognitive performance and educational attainment and increased SCZ risk, and 2) those with discordant alleles, which are linked to reduced educational and/or cognitive levels but lower SCZ susceptibility.

In the current study, we extended 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 SCZ and the 2 cognitive phenotypes revealed 768 significant pleiotropic loci (166 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 linked 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 messenger RNA translation initiation, which represents a novel finding in the SCZ literature.

Pleiotropic analysis permits not only enhanced statistical power for locus discovery but also the ability to parse distinct biological processes associated with endophenotypes.

Methamphetamine use disorder is a pressing global health issue, often accompanied by significant cognitive deficits that impair daily functioning and quality of life and complicate treatment. Emerging evidence highlights the potential role of genetic factors in methamphetamine use disorder, particularly in association with cognitive function. This review examines the key genetic and cognitive dimensions and their interplay in methamphetamine use disorder. There is converging evidence from several studies that genetic polymorphisms in BDNF, FAAH, SLC18A1, and SLC18A2 are associated with protection against or susceptibility to the disorder. In addition, people with methamphetamine use disorder consistently displayed impairments in cognitive flexibility and inhibitory control compared with people without the disorder. These cognitive domains were associated with reactivity to methamphetamine cues that were positively correlated with total years of methamphetamine use history. Emerging research also suggests that inhibitory control is negatively correlated with lower blood FAAH mRNA levels, while cognitive flexibility positively correlates with higher blood SLC18A2 mRNA levels, highlighting how genetic and cognitive dimensions interact in methamphetamine use disorder. We also include some future directions, emphasizing potential personalized therapeutic strategies that integrate genetic and cognitive insights. By drawing attention to the interplay between genes and cognition, we hope to advance our understanding of methamphetamine use disorder and inform the development of targeted interventions.

In studies of individuals of primarily European genetic ancestry, common and low-frequency variants and rare coding variants have been found to be associated with the risk of bipolar disorder (BD) and schizophrenia (SZ). However, less is known for individuals of other genetic ancestries or the role of rare non-coding variants in BD and SZ risk. We performed whole genome sequencing of African American individuals: 1,598 with BD, 3,295 with SZ, and 2,651 unaffected controls (InPSYght study). We increased power by incorporating 14,812 jointly called psychiatrically unscreened ancestry-matched controls from the Trans-Omics for Precision Medicine (TOPMed) Program for a total of 17,463 controls. To identify variants and sets of variants associated with BD and/or SZ, we performed single-variant tests, gene-based tests for singleton protein truncating variants, and rare and low-frequency variant annotation-based tests with conservation and universal chromatin states and sliding windows. We found suggestive evidence of BD association with single-variants on chromosome 18 and of lower BD risk associated with rare and low-frequency variants on chromosome 11 in a region with multiple BD GWAS loci, using a sliding window approach. We also found that chromatin and conservation state tests can be used to detect differential calling of variants in controls sequenced at different centers and to assess the effectiveness of sequencing metric covariate adjustments. Our findings reinforce the need for continued whole genome sequencing in additional samples of African American individuals and more comprehensive functional annotation of non-coding variants.

Despite hundreds of genetic risk loci identified for neuropsychiatric disorders (NPD), most causal variants/genes remain unknown. A major hurdle is that disease risk variants may act in specific biological contexts, e.g., during neuronal activation, which is difficult to study in vivo at the population level. Here, we conducted a single-cell multiomics study of neuronal activation (stimulation) in human iPSC-induced excitatory and inhibitory neurons from 100 donors, and uncovered abundant neuronal stimulation-specific causal variants/genes for NPD. We surveyed NPD-relevant transcriptomic and epigenomic landscape of neuronal activation and identified thousands of genetic variants associated with activity-dependent gene expression (i.e., eQTL) and chromatin accessibility (i.e., caQTL). These caQTL explained considerably larger proportions of NPD heritability than the eQTL. Integrating the multiomic data with GWAS further revealed NPD risk variants/genes whose effects were only detected upon stimulation. Interestingly, multiple lines of evidence support a role of activity-dependent cholesterol metabolism in NPD. Our work highlights the power of cell stimulation to reveal context-dependent "hidden" genetic effects.

Psychiatric disorders are multifactorial and effective treatments are lacking. Probable contributing factors to the challenges in therapeutic development include the complexity of the human brain and the high polygenicity of psychiatric disorders. Combining well-powered genome-wide and brain-wide genetics and transcriptomics analyses can deepen our understanding of the etiology of psychiatric disorders. Here, we leverage two landmark resources to infer the cell types involved in the etiology of schizophrenia, other psychiatric disorders and informative comparison of brain phenotypes. We found both cortical and subcortical neuronal associations for schizophrenia, bipolar disorder and depression. These cell types included somatostatin interneurons, excitatory neurons from the retrosplenial cortex and eccentric medium spiny-like neurons from the amygdala. In contrast we found T cell and B cell associations with multiple sclerosis and microglial associations with Alzheimer's disease. We provide a framework for a cell-type-based classification system that can lead to drug repurposing or development opportunities and personalized treatments. This work formalizes a data-driven, cellular and molecular model of complex brain disorders.

Strabismus is the most common ocular disorder of childhood. Three rare, recurrent genetic duplications have been associated with both esotropia and exotropia, but the mechanisms by which they contribute to strabismus are unknown. This work aims to investigate the mechanisms of the smallest of the three, a 23 kb duplication on chromosome 4 (hg38|4:25,554,985-25,578,843).

Using CRISPR and bridging oligos, we introduced the duplication into the Kolf2.1J iPSC line. We differentiated the parent line and the line with the duplication into cortical neurons using a three-dimensional differentiation protocol, and performed bulk RNASeq on neural progenitors (day 14) and differentiated neurons (day 63).

We successfully introduced the duplication into Kolf2.1J iPSCs by nucleofecting a bridging oligo for the newly formed junction along with cas9 ribonucleoparticles. We confirmed that the cells had a tandem duplication without inversion or deletion. The parent line and the line with the duplication both differentiated into neurons reliably. There were a total of 37 differentially expressed genes (DEGs) at day 63, 25 downregulated and 12 upregulated. There were 55 DEGs at day 14, 18 of which were also DEGs at day 63. The DEGs included a number of protocadherins, several genes involved in neuronal development, including SLITRK2, CSMD1, and VGF, and several genes of unknown function.

A copy number variant (CNV) that confers risk for strabismus affects gene expression of several genes involved in neural development, highlighting that strabismus most likely results from abnormal neural development, and identifying several new genes and pathways for further research into the pathophysiology of strabismus.

Deficits in neurogenesis markers in the subependymal zone (SEZ) are associated with elevated inflammation in schizophrenia and bipolar disorder. However, the extent to which complement factors are also changed in the SEZ of these major psychiatric disorders and their impact on neurogenesis remains poorly understood. We extracted RNA from the SEZ of 93 brains, including controls (n = 32), schizophrenia (n = 32), and bipolar disorder (n = 29) cases. Quantitative RT-PCR measured 13 complement transcripts encoding initiators, convertases, effectors or inhibitors. Differences in abundance were analysed by diagnosis and inflammatory subgroups (high- or low-inflammation), which were previously defined by SEZ cytokine and inflammation marker expression. Complement mRNAs C1QA (p = 0.011), C1QB (p < 0.001), C1R (p = 0.027), and Factor B (p = 0.025) were increased in high-inflammation schizophrenia versus low-inflammation controls. Conversely, high-inflammation bipolar cases had decreased C1QC (p = 0.011) and C3 (p = 0.003). Complement mRNAs C1R (SCZ, p = 0.010; BD, p = 0.047), C1S (SCZ, p = 0.026; BD, p = 0.017), and Factor B (BD, p = 0.025) were decreased in low-inflammation schizophrenia and bipolar subgroups versus low-inflammation controls. Complement inhibitors varied by subgroup: Factor H was increased in high-inflammation schizophrenia (p < 0.001), and CD59 in high-inflammation bipolar disorder (p = 0.020). Complement activator and inhibitor mRNAs were positively correlated with quiescent neural stem cell marker GFAPD (q < 0.05) but negatively with immature neuron markers DLX6-AS1 (q < 0.05) and DCX (q < 0.05). These findings suggest altered complement cascade expression in the SEZ in high- and low-inflammation schizophrenia and bipolar disorder, with opposite directional changes suggesting distinct molecular pathology. Complement activation may promote stem cell quiescence and reduce differentiation or survival of newborn neurons.

The bipolar disorder (BD) risk gene ANK3 encodes the scaffolding protein AnkyrinG (AnkG). In neurons, AnkG regulates polarity and ion channel clustering at axon initial segments and nodes of Ranvier. Disruption of neuronal AnkG causes BD-like phenotypes in mice. During development, AnkG is also expressed at comparable levels in oligodendrocytes and facilitates the efficient assembly of paranodal junctions. However, the physiological roles of glial AnkG in the mature nervous system, and its contributions to BD-like phenotypes, remain unexplored. Here, we show that oligodendroglia-specific AnkG conditional knockout results in destabilization of axoglial interactions in aged but not young adult mice. In addition, these mice exhibit significant histological, electrophysiological, and behavioral pathophysiologies. Unbiased translatomic profiling reveals potential compensatory machineries. These results highlight the functions of glial AnkG in maintaining proper axoglial interactions throughout aging and suggest a contribution of glial AnkG to neuropsychiatric disorders.

Constitutional delay of puberty (CDP) is highly heritable, but the genetic basis for CDP is largely unknown. Idiopathic hypogonadotropic hypogonadism (IHH) can be caused by rare genetic variants, but in about half of cases, no rare-variant cause is found.

To determine whether common genetic variants that influence pubertal timing contribute to CDP and IHH.

Case-control study.

80 individuals with CDP; 301 with normosmic IHH, and 348 with Kallmann syndrome (KS); control genotyping data from unrelated studies.

Polygenic scores (PGS) based on genome-wide association studies for timing of male pubertal hallmarks and age at menarche (AAM).

The CDP cohort had higher PGS for male pubertal hallmarks and for AAM compared to controls (for male hallmarks, Cohen's d = 0.67, P = 1 × 10-10; for AAM, d = 0.85, P = 1 × 10-16). The normosmic IHH cohort also had higher PGS for male hallmarks compared to controls, but the difference was smaller (male hallmarks d = 0.20, P = .003; AAM d = 0.10, P = .055). No differences were seen for the KS cohort compared to controls (male hallmarks d = 0.05, P = .45; AAM d = 0.03, P = .56).

Common genetic variants that influence pubertal timing in the general population contribute strongly to the genetics of CDP, weakly to normosmic IHH, and potentially not at all to KS. These findings demonstrate that the common-variant genetics of CDP and normosmic IHH are largely but not entirely distinct.

Schizophrenia (SCZ) is among the most persistent and devastating psychological problems. Different genetic polymorphisms are responsible for the predisposition of SCZ, and we screened NOTCH4 (rs2071287, rs204993) and CYP2E1 (rs2070673) polymorphisms in this study to find the connection with SCZ development.

We investigated a total of 420 samples (210 patients and 210 controls) and used the PCR-RFLP technique to genotype all SNPs. For statistical analyses, SPSS (version 25.0) was applied.

In the case of NOTCH4 rs2071287, no evidence of a link was found in any genetic models, whereas NOTCH4 rs204993 and CYP2E1 rs2070673 showed a significant linkage in four genetic models with SCZ risk (for NOTCH4 rs204993, additive model 2: OR = 3.39, CI = 1.84-6.23, p = 0.0001; dominant: OR = 1.84, CI = 1.22-2.76, p = 0.0032; recessive: OR = 2.67, CI = 1.53-4.64, p = 0.0005; allelic: OR = 1.75, CI = 1.32-2.30, p = 0.0001 and for CYP2E1 rs2070673, additive model 2: OR = 0.39, CI = 0.22-0.69, p = 0.0013; recessive: OR = 0.45, CI = 0.29-0.68, p = 0.0002; overdominant: OR = 1.49, CI = 1.02-2.19, p = 0.0408; allelic: OR = 0.61, CI = 0.46-0.80, p = 0.0004).

The findings of our study suggest that the polymorphisms NOTCH4 rs204993 and CYP2E1 rs2070673 in the Bangladeshi ethnicity are connected to the risk of SCZ.

Striatal cholinergic interneurons (ChIs) provide acetylcholine tone to the striatum and govern motor functions. Nicotine withdrawal elicits physical symptoms that dysregulate motor behavior. Here, the role of striatal ChIs in physical nicotine withdrawal is investigated. Mice under RNAi-dependent genetic inhibition of striatal ChIs (ChIGI) by suppressing the sodium channel subunit NaV1.1, lessening action potential generation and activity-dependent acetylcholine release is first generated. ChIGI markedly reduced the somatic signs of nicotine withdrawal without affecting other nicotine-dependent or striatum-associated behaviors. Multielectrode array (MEA) recording revealed that ChIGI reversed ex vivo nicotine-induced alterations in the number of neural population spikes in the dorsal striatum. Notably, the drug repurposing strategy revealed that a clinically-approved antimuscarinic drug, procyclidine, fully mimicked the therapeutic electrophysiological effects of ChIGI. Furthermore, both ChIGI and procyclidine prevented the nicotine withdrawal-induced reduction in striatal dopamine release in vivo. Lastly, therapeutic intervention with procyclidine dose-dependently diminished the physical signs of nicotine withdrawal. The data demonstrated that the striatal ChIs are a critical substrate of physical nicotine withdrawal and that muscarinic antagonism holds therapeutic potential against nicotine withdrawal.

Synaptic development and functions have been hypothesized as crucial mechanisms of diverse neuropsychiatric disorders. Studies in past years suggest that mutations in the fragile X mental retardation 1 (FMR1) are associated with diverse mental disorders including intellectual disability, autistic spectrum disorder, and schizophrenia. In this study, we have examined genetical interactions between a select set of risk factor genes using fruit flies to find that dfmr1, the Drosophila homolog of the human FMR1 gene, exhibits functional interactions with DISC1 in synaptic development. We show that DISC1 overexpression in the dfmr1null heterozygous background causes synaptic alterations at the larval neuromuscular junctions that are distinct from those in the wild-type background. Loss of dfmr1 modifies the DISC1 overexpression phenotype in synaptic formation, suppressing the formation of synapse boutons. Interaction between the two genes was further supported molecularly by the results that dfmr1 mutations suppress the DISC1-mediated upregulations of the postsynaptic expression of a glutamate receptor and the expression of ELKS/CAST protein, Bruchpilot, in presynaptic motoneurons. Moreover, DISC1 overexpression in the dfmr1null heterozygous background causes downregulation of a MAP1 family protein, Futsch. These results thus suggest an intriguing converging mechanism controlled by FMR1 and DISC1 in the developing glutamatergic synapses.

Key mechanisms underlying chronic pain occur within the dorsal horn. Genome-wide association studies (GWASs) have identified genetic variants predisposed to chronic pain. However, most of these variants lie within regulatory non-coding regions that have not been linked to spinal cord biology. Here, we take a multi-species approach to determine whether chronic pain variants impact the regulatory genomics of dorsal horn neurons. First, we generate a large rhesus macaque single-nucleus RNA sequencing (snRNA-seq) atlas and integrate it with available human and mouse datasets to produce a single unified, species-conserved atlas of neuron subtypes. Cellular-resolution spatial transcriptomics in mouse shows the precise laminar location of these neuron subtypes, consistent with our analysis of neuron-subtype-selective markers in macaque. Using this cross-species framework, we generate a mouse single-nucleus open chromatin atlas of regulatory elements that shows strong and selective relationships between the neuron-subtype-specific chromatin regions and variants from major chronic pain GWASs.

Maternal education was strongly correlated with adolescent brain morphology, cognitive performances, and mental health. However, the molecular basis for the effects of maternal education on the structural neurodevelopment remains unknown. Here, we conducted gene-environment-wide interaction study using the Adolescent Brain Cognitive Development cohort. Seven genomic loci with significant gene-environment interactions (G×E) on regional gray matter volumes were identified, with enriched biological functions related to metabolic process, inflammatory process, and synaptic plasticity. Additionally, genetic overlapping results with behavioral and disease-related phenotypes indicated shared biological mechanism between maternal education modified neurodevelopment and related behavioral traits. Finally, by decomposing the multidimensional components of maternal education, we found that socioeconomic status, rather than family environment, played a more important role in modifying the genetic effects on neurodevelopment. In summary, our study provided analytical evidence for G×E effects regarding adolescent neurodevelopment and explored potential biological mechanisms as well as social mechanisms through which maternal education could modify the genetic effects on regional brain development.

Common variants in the MicroRNA 137 host gene MIR137HG and its adjacent gene DPYD have been associated with schizophrenia risk and the latest Psychiatric Genomics Consortium (PGC). Genome-Wide Association Study on schizophrenia has confirmed and extended these findings. To elucidate the association of schizophrenia risk-associated SNPs in this genomic region, we examined the expression of both mature and immature transcripts of the miR-137 host gene (MIR137HG) in the dorsolateral prefrontal cortex (DLPFC) and subgenual anterior cingulate cortex (sgACC) of postmortem brain samples of donors with schizophrenia and psychiatrically-unaffected controls using qPCR and RNA-Seq approaches. No differential expression of miR-137, MIR137HG, or its transcripts was observed. Two schizophrenia risk-associated SNPs identified in the PGC study, rs11165917 (DLPFC: P = 2.0e-16; sgACC: P = 6.4e-10) and rs4274102 (DLPFC: P = 0.036; sgACC: P = 0.002), were associated with expression of the MIR137HG long non-coding RNA transcript MIR137HG-203 (ENST00000602672.2) in individuals of European ancestry. Carriers of the minor (risk) allele of rs11165917 had significantly lower expression of MIR137HG-203 compared with those carrying the major allele. However, we were unable to validate this result by short-read sequencing of RNA extracted from DLPFC or sgACC tissue. This finding suggests that immature transcripts of MIR137HG may contribute to genetic risk for schizophrenia.

Our understanding of human genes - particularly their structure, functions, and regulatory mechanisms - is still limited. The biological role of approximately 20 % of human proteins has not been established yet, and the molecular functions of the known part of the proteome remain poorly understood. This hinders progress in basic and applied biological and medical sciences, especially in treating hereditary diseases, which are caused by mutations and polymorphic variants in individual genes. Therefore, it is crucial to comprehend the mechanisms of protein functioning to address this problem. This further emphasizes the importance of investigating gene functions and molecular pathogenetic pathways associated with single-gene inherited diseases. This review focuses on the TCF4 gene that encodes a transcription factor crucial for nervous system development and functioning. Pathogenic variants in this gene have been linked to a rare genetic disorder, Pitt-Hopkins syndrome, and TCF4 polymorphic variants are associated with several socially significant diseases, including various psychiatric disorders. The pathogenetic mechanisms of these conditions remain unexplored, and the knowledge about TCF4 upregulation and its target genes is limited. TCF4 can be expressed in various isoforms due to the complex structure and regulation of its gene, which complicates the investigation of the protein's functions. Here, we consider the structure and functions of the TCF4 transcription factor. We discuss its potential target genes and the possible loss-of-function pathogenetic mechanisms identified in animal and cellular models of Pitt-Hopkins syndrome. The review also examines the advantages and limitations of potential therapies for Pitt-Hopkins syndrome that are based on TCF4 dosage compensation or altering the activity of TCF4 target genes.

Schizophrenia (SCZ) is a complex, heritable and polygenic neuropsychiatric disease, which disables the patients as well as decreases their life expectancy and quality of life. Common and rare variants studies on SCZ subjects have provided >100 genomic loci that hold importance in the context of SCZ pathophysiology. Transcriptomic studies from clinical samples have informed about the differentially expressed genes (DEGs) and non-coding RNAs in SCZ patients. Despite these advancements, no causative genes for SCZ were found and hence SCZ is difficult to recapitulate in animal models. In the last decade, induced Pluripotent Stem Cells (iPSCs)-based models have helped in understanding the neural phenotypes of SCZ by studying patient iPSC-derived 2D neuronal cultures and 3D brain organoids. Here, we have aimed to provide a simplistic overview of the current progress and advancements after synthesizing the enormous literature on SCZ genetics and SCZ iPSC-based models. Although further understanding of SCZ genetics and pathophysiological mechanisms using these technological advancements is required, the recent approaches have allowed to delineate important cellular mechanisms and biological pathways affected in SCZ.

Recent genome-wide association studies (GWAS) and whole-exome sequencing of neuropsychiatric disorders, especially schizophrenia, have identified a plethora of common and rare disease risk variants/genes. Translating the mounting human genetic discoveries into novel disease biology and more tailored clinical treatments is tied to our ability to causally connect genetic risk variants to molecular and cellular phenotypes. When combined with the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated (Cas) nuclease-mediated genome editing system, human induced pluripotent stem cell (hiPSC)-derived neural cultures (both 2D and 3D organoids) provide a promising tractable cellular model for bridging the gap between genetic findings and disease biology. In this review, we first conceptualize the advances in understanding the disease polygenicity and convergence from the past decade of iPSC modeling of different types of genetic risk factors of neuropsychiatric disorders. We then discuss the major cell types and cellular phenotypes that are most relevant to neuropsychiatric disorders in iPSC modeling. Finally, we critically review the limitations of iPSC modeling of neuropsychiatric disorders and outline the need for implementing and developing novel methods to scale up the number of iPSC lines and disease risk variants in a systematic manner. Sufficiently scaled-up iPSC modeling and a better functional interpretation of genetic risk variants, in combination with cutting-edge CRISPR/Cas9 gene editing and single-cell multi-omics methods, will enable the field to identify the specific and convergent molecular and cellular phenotypes in precision for neuropsychiatric disorders.

Cognitive impairment is the strongest predictor of functional outcomes in schizophrenia and is hypothesized to result from synaptic dysfunction. However, targeting synaptic plasticity and cognitive deficits in patients remains a significant clinical challenge. A comprehensive understanding of synaptic plasticity and the molecular basis of learning and memory in a disease context can provide specific targets for the development of novel therapeutics targeting cognitive impairments in schizophrenia. Here, we describe the role of synaptic plasticity in cognition, summarize evidence for synaptic dysfunction in schizophrenia and demonstrate the use of patient derived induced-pluripotent stem cells for studying synaptic plasticity in vitro. Lastly, we discuss current advances and future technologies for bridging basic science research of synaptic dysfunction with clinical and translational research that can be used to predict treatment response and develop novel therapeutics.

Schizophrenia (SCZ) is a complex psychiatric disorder that involves an inflammatory response thought to be characterized by microglial activation. The inflammasome complex may play critical roles in the pathomechanism of neuroinflammation but how this relates to SCZ remains unclear. In this study, we performed an immunohistochemical (IHC) analysis to compare the expression of inflammasome proteins in brain tissue from donors with SCZ (n = 16) and non-psychiatric donors (NP; n = 13) isolated from the superior frontal cortex (SFC), superior temporal cortex, and anterior cingulate cortex brain regions. To assess changes in the cell populations that express key inflammasome proteins, we performed IHC analyses of apoptosis-associated speck-like protein containing a CARD (ASC), nod-like receptor protein 3 (NLRP3), and interleukin (IL)-18 to determine if these proteins are expressed in microglia, astrocytes, oligodendrocytes, or neurons. Inflammasome proteins were expressed mainly in microglia from SCZ and NP brains. Increased numbers of microglia were present in the SFC of SCZ brains and exhibited higher inflammasome protein expression of ASC, NLRP3, and IL-18 compared to NPs. These findings suggest that increased inflammasome signaling may contribute to the pathology underlying SCZ.

MicroRNAs (miRNAs) are emerging as crucial elements in the regulation of gene expression, playing a significant role in the underlying neurobiology of a wide range of neuropsychiatric disorders. This review examines the intricate involvement of miRNAs in neuropsychiatric disorders, such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), Fragile X syndrome (FXS), autism spectrum disorder (ASD), attention-deficit hyperactivity disorder (ADHD), Tourette syndrome (TS), schizophrenia (SCZ), and mood disorders. This review highlights how miRNA dysregulation can illuminate the molecular pathways of these diseases and potentially serve as biomarkers for early diagnosis and prognosis. Specifically, miRNAs' ability to target genes critical to the pathology of neurodegenerative diseases, their role in the development of trinucleotide repeat and neurodevelopmental disorders, and their distinctive patterns in SCZ and mood disorders are discussed. The review also stresses the value of miRNAs in precision neuropsychiatry, where they could predict treatment outcomes and aid in disease management. Furthermore, the study of conserved miRNAs in model organisms like Drosophila underscores their broad utility and provides deeper mechanistic insights into their biological functions. This comprehensive examination of miRNAs across various conditions advocates for their integration into clinical practice, promising advancements in personalized healthcare for neurological and psychiatric conditions.

Nearly two decades of genome-wide association studies (GWAS) have identify thousands of disease-associated genetic variants, but very few genes with evidence of causality. Recent methodological advances demonstrate that Mendelian Randomization (MR) using expression quantitative loci (eQTLs) as instrumental variables can detect potential causal genes. However, existing MR approaches are not well suited to handle the complexity of eQTL GWAS data structure and so they are subject to bias, inflation, and incorrect inference.

We present a whole-genome regulatory network analysis tool (HORNET), which is a comprehensive set of statistical and computational tools to perform genome-wide searches for causal genes using summary level GWAS data that is robust to biases from multiple sources. Applying HORNET to schizophrenia, we identified differential magnitudes of gene expression causality. Applying HORNET to schizophrenia, we identified differential magnitudes of gene expression causality across different brain tissues.

Freely available at https://github.com/noahlorinczcomi/HORNETor Mac, Windows, and Linux users.

njl96@case.edu .