Background: Mounting evidence suggests that mitochondria respond to psychosocial stress. Recent studies suggest mitochondrial DNA (mtDNA) deletions may be increased in some psychiatric disorders, but no studies have examined early-life stress (ELS) and mtDNA deletions. In this study, we assessed mtDNA deletions in peripheral blood mononuclear cells of medically healthy young adults with and without ELS. Methods: Participants (n = 181; 69% female), ages 18 to 40 years, were recruited from the community. Participants with ELS (n = 108) had moderate to severe childhood maltreatment; 83 also had parental loss, and 59 had psychiatric disorders. Participants in the control group (n = 73) had no maltreatment, parental loss, or psychiatric disorders. Standardized interviews and self-report measures assessed demographic variables, stress, and mental health. mtDNA from peripheral blood mononuclear cells was amplified via long-range polymerase chain reaction; mtDNA deletions were quantified via Seq-Well, next-generation sequencing, and the Splice-Break pipeline. Linear regression models were used to assess relationships of mtDNA deletion metrics with ELS, adult stressors, psychiatric disorders, and demographics. Results: Participants with ELS had significantly greater rates of unique mtDNA deletion breakpoints per 10,000 coverage than participants without ELS (p < .001), correcting for age, sex, and sequencing depth. Cumulative mtDNA deletion read percentage was not significantly different between groups. Psychiatric disorders and adult stressors were associated with greater unique mtDNA deletion breakpoints (ps < .05) but did not account for associations of ELS with mtDNA deletions. Conclusions: The increased number of unique mtDNA deletion breakpoints in participants with ELS suggests that mitochondrial genomes undergo observable alterations in the context of early stress. Future studies will examine mtDNA deletions with metabolic health measures.

Rare copy number variants (CNVs) are a key component of the genetic basis of psychiatric conditions, but have not been well characterized for most. We conducted a genome-wide CNV analysis across six diagnostic categories (N = 574,965): autism (ASD), ADHD, bipolar disorder (BD), major depressive disorder (MDD), PTSD, and schizophrenia (SCZ). We identified 35 genome-wide significant associations at 18 loci, including novel associations in SCZ ( SMYD3, USP7 - HAPSTR1 ) and in the combined cross-disorder analysis ( ASTN2 ). Rare CNVs accounted for 1-3% of heritability across diagnoses. In ASD, associations were uniformly positive, consistent with autism having diverse etiologies and clinical presentations. By contrast, CNVs showed a dose-dependent relationship for other diagnoses, including SCZ and PTSD, with reciprocal deletions and duplications having inversely correlated effects and distinct genotype-phenotype relationships. Our findings suggest that genes have effects that are both dose-dependent and pleiotropic, such that a positive influence on one dimension of psychopathology may be accompanied by positive or negative effects on others.

Bipolar disorder is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 bipolar disorder risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci and prioritized 17 likely causal SNPs for bipolar disorder. We mapped these SNPs to genes and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci and results from rare variant exome sequencing in bipolar disorder. Convergent lines of evidence supported the roles of genes involved in neurotransmission and neurodevelopment, including SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, FKBP2, RASGRP1, FURIN, FES, MED24 and THRA among others in bipolar disorder. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance of bipolar disorder polygenic risk scores across diverse populations and present a high-throughput fine-mapping pipeline.

Background Early life stress (ELS) is a well-established risk factor for psychiatric conditions across the lifespan. A growing body of evidence indicates that alterations to mitochondrial DNA may result from chronic activation of physiological stress responses in ELS and may be associated with psychiatric outcomes. Several studies have found relationships between a number of psychiatric conditions and mtDNA copy number (mtDNAcn), with emerging evidence for a role of early life stress in these associations. This study examined mtDNAcn in physically healthy young adults with and without ELS and a broad range of psychiatric conditions. Methods Participants (N = 181; 69.1 % female) included those with ELS and psychiatric conditions (n = 59; ELS+Psych), ELS and no psychiatric conditions (n = 49; ELS-Psych), and with neither ELS nor psychiatric conditions (n = 73; Controls). Standardized interviews and self-reports assessed demographics, stress, and mental health. DNA from PBMCs was used as input for ultra-low coverage whole genome sequencing (ULC-WGS); mtDNAcn was quantified using the fastMitoCalc tool. ANOVAs were used to examine group differences and negative binomial regression models assessed ELS, psychopathology and mtDNAcn relationships with covariates age and sex. Results ELS+Psych individuals had significantly greater mtDNAcn compared to Control participants (p < .05), even after adjusting for relevant covariates. There was no difference between ELS-Psych individuals and Control participants. Conclusions Increased rates of mtDNAcn among individuals with ELS+Psych, but not among those with ELS-Psych, compared to Controls indicates that observable effects of ELS may only occur in the presence of psychiatric symptomatology. Findings and future directions are discussed.

Bipolar disorder is a leading contributor to the global burden of disease1. Despite high heritability (60-80%), the majority of the underlying genetic determinants remain unknown2. We analysed data from participants of European, East Asian, African American and Latino ancestries (n = 158,036 cases with bipolar disorder, 2.8 million controls), combining clinical, community and self-reported samples. We identified 298 genome-wide significant loci in the multi-ancestry meta-analysis, a fourfold increase over previous findings3, and identified an ancestry-specific association in the East Asian cohort. Integrating results from fine-mapping and other variant-to-gene mapping approaches identified 36 credible genes in the aetiology of bipolar disorder. Genes prioritized through fine-mapping were enriched for ultra-rare damaging missense and protein-truncating variations in cases with bipolar disorder4, highlighting convergence of common and rare variant signals. We report differences in the genetic architecture of bipolar disorder depending on the source of patient ascertainment and on bipolar disorder subtype (type I or type II). Several analyses implicate specific cell types in the pathophysiology of bipolar disorder, including GABAergic interneurons and medium spiny neurons. Together, these analyses provide additional insights into the genetic architecture and biological underpinnings of bipolar disorder.

Schizophrenia (SCZ) is a complex psychiatric disorder with unclear biological mechanisms. Spectrins, cytoskeletal proteins linked to neurodevelopmental disorders, are regulated by the AKT/GSK3 pathway, which is implicated in SCZ. However, the impact of SCZ-related dysregulation of this pathway on spectrin expression and distribution remains unexplored. Here, we show that βIV spectrin protein levels were reduced in neurons of the dorsolateral prefrontal cortex in SCZ postmortem samples compared to healthy control (HC) from the Human Brain Collection Core (HBCC). To investigate potential links between βIV spectrin and the AKT/GSK3 pathway, we analyzed the PsychEncode dataset, revealing elevated SPTBN4 and AKT2 mRNA levels with correlated gene transcription in both HCs and individuals with SCZ. Next, computational tools were employed to identify potential AKT and GSK3 phosphorylation sites on βIV spectrin, and two GSK3 sites were validated through in vitro assays. To assess whether βIV spectrin distribution and sensitivity to AKT/GSK3 are altered in SCZ, we used iPSC-derived neurons from two independent cohorts of patients with significantly increased familial genetic risk for the disorder. Alteration in βIV spectrin levels and sensitivity to AKT/GSK3 inhibitors were consistently observed across both cohorts. Importantly, a Random Forest classifier applied to βIV spectrin imaging achieved up to 98% accuracy in classifying cells by diagnosis in postmortem samples, and by diagnosis or diagnosis × perturbation in iPSC samples. These findings reveal altered βIV spectrin levels and AKT/GSK3 sensitivity in SCZ, identifying βIV spectrin image-based endophenotypes as robust, generalizable predictive biomarkers of SCZ, with the potential for scalable clinical applications.

Common mitochondrial DNA (mtDNA) deletions are large structural variants in the mitochondrial genome that accumulate in metabolically active tissues with age and have been investigated in various diseases. We applied the Splice-Break2 pipeline (designed for high-throughput quantification of mtDNA deletions) to human RNA-Seq datasets and describe the methodological considerations for evaluating common deletions in bulk, single-cell, and spatial transcriptomics datasets. A robust evaluation of 1570 samples from 14 RNA-Seq studies showed: (i) the abundance of some common deletions detected in PCR-amplified mtDNA correlates with levels observed in RNA-Seq data; (ii) RNA-Seq library preparation method has a strong effect on deletion detection; (iii) deletions had a significant, positive correlation with age in brain and muscle; (iv) deletions were enriched in cortical grey matter, specifically in layers 3 and 5; and (v) brain regions with dopaminergic neurons (i.e., substantia nigra, ventral tegmental area, and caudate nucleus) had remarkable enrichment of common mtDNA deletions.

Background In cellular bioenergetics, mitochondria play a central role, serving as the primary site for ATP synthesis and have central role on neuronal network dynamics, thereby governing vital neuronal processes and underpinning bioenergetics. Recent molecular studies have demonstrated that mitochondrial dysfunction in the pathophysiology of multiple psychiatric disorders such as bipolar disorder (BD), schizophrenia (SCZ), and major depressive disorder (MDD). We investigated the association of variants in the nuclear-encoded mitochondrial genes (NEMG) with the risks of BD, SCZ, and MDD, and modeled mitochondrial polygenic risk scores (mitoPRS). Methods We performed a random-effects meta-analysis of single nucleotide polymorphisms (SNPs) of NEMG based on MitoCarta v3.0 on SCZ Psychiatric Genomics Consortium wave 3 (PGCw3; 27835 SCZ, 35273 controls), BD-PGCw3 (25047 BD, 40740 controls) and MDD-PGCw2 (18494 MDD, 21864 controls) to characterize nuclear-encoded mitochondrial SNP association with each disorder. Furthermore, we performed a mega-analysis using 70% of the datasets to generate mitoPRS for nuclear-mitochondrial encoding SNVs via PRSice-2 and characterized phenotypic variance explained by mitochondrial genes in the held-out test set. Results The meta-analyses of BD and SCZ demonstrated positive associations of NEMG with deviation of the P values from the theoretical distribution, but not in MDD. The mitoPRS for BD and SCZ were strongly associated with each disorder in the held-out cohort (Nagelkerke's pseudo-R2 BD-mitoPRS = 0.032, Nagelkerke's pseudo-R2 SCZ-mitoPRS = 0.034). Discussion The results suggest the evidence for the involvement of nuclear-encoded mitochondrial genetics in susceptibility of BD and SCZ. In the next steps, we aim to generate a next-generation mitoPRS using deep convolutional neural network, and to investigate the association of mitoPRS with clinical characteristics and metabolism in patients with BD and SCZ.

Suicide is a condition resulting from complex environmental and genetic risks that affect millions of people globally. Both structural and functional studies identified the hippocampus as one of the vulnerable brain regions contributing to suicide risk. Here, we have identified the hippocampal transcriptomes, gene ontology, cell type proportions, dendritic spine morphology, and transcriptomic signature in iPSC-derived neuronal precursor cells (NPCs) and neurons in postmortem brain tissue from suicide deaths. The hippocampal tissue transcriptomic data revealed that NPAS4 gene expression was downregulated while ALDH1A2, NAAA, and MLXIPL gene expressions were upregulated in tissue from suicide deaths. The gene ontology identified 29 significant pathways including NPAS4-associated gene ontology terms "excitatory post-synaptic potential", "regulation of postsynaptic membrane potential" and "long-term memory" indicating alteration of glutamatergic synapses in the hippocampus of suicide deaths. The cell type deconvolution identified decreased excitatory neuron proportion and an increased inhibitory neuron proportion providing evidence of excitation/inhibition imbalance in the hippocampus of suicide deaths. In addition, suicide deaths had increased dendric spine density, due to an increase of thin (relatively unstable) dendritic spines, compared to controls. The transcriptomes of iPSC-derived hippocampal-like NPCs and neurons revealed 31 and 33 differentially expressed genes in NPC and neurons, respectively, of suicide deaths. The suicide-associated differentially expressed genes in NPCs were RELN, CRH, EMX2, OXTR, PARM1 and IFITM2 which overlapped with previously published results. The previously-known suicide-associated differentially expressed genes in differentiated neurons were COL1A1, THBS1, IFITM2, AQP1, and NLRP2. Together, these findings would help better understand the hippocampal neurobiology of suicide for identifying therapeutic targets to prevent suicide.

Large numbers of genetic loci have been identified that are known to contain common risk alleles for schizophrenia, but linking associated alleles to specific risk genes remains challenging. Given that most alleles that influence liability to schizophrenia are thought to do so by altered gene expression, intuitively, case-control differential gene expression studies should highlight genes with a higher probability of being associated with schizophrenia and could help identify the most likely causal genes within associated loci. Here, we test this hypothesis by comparing transcriptome analysis of the dorsolateral prefrontal cortex from 563 schizophrenia cases and 802 controls with genome-wide association study (GWAS) data from the third wave study of the Psychiatric Genomics Consortium. Genes differentially expressed in schizophrenia were not enriched for common allelic association statistics compared with other brain-expressed genes, nor were they enriched for genes within associated loci previously reported to be prioritized by genetic fine-mapping. Genes prioritized by Summary-based Mendelian Randomization were underexpressed in cases compared to other genes in the same GWAS loci. However, the overall strength and direction of expression change predicted by SMR were not related to that observed in the differential expression data. Overall, this study does not support the hypothesis that genes identified as differentially expressed from RNA sequencing of bulk brain tissue are enriched for those that show evidence for genetic associations. Such data have limited utility for prioritizing genes in currently associated loci in schizophrenia.

Recent postmortem transcriptomic studies of schizophrenia (SCZ) have shown hundreds of differentially expressed genes. However, the extent to which these gene expression changes reflect antipsychotic drug (APD) exposure remains uncertain. We compared differential gene expression in the prefrontal cortex of SCZ patients who tested positive for APDs at the time of death with SCZ patients who did not. APD exposure was associated with numerous changes in the brain transcriptome, especially among SCZ patients on atypical APDs. Brain transcriptome data from macaques chronically treated with APDs showed that APDs affect the expression of many functionally relevant genes, some of which show expression changes in the same directions as those observed in SCZ. Co-expression modules enriched for synaptic function showed convergent patterns between SCZ and some of the APD effects, while those associated with inflammation and glucose metabolism exhibited predominantly divergent patterns between SCZ and APD effects. In contrast, major cell-type shifts inferred in SCZ were primarily unaffected by APD use. These results show that APDs may confound SCZ-associated gene expression changes in postmortem brain tissue. Disentangling these effects will help identify causal genes and improve our neurobiological understanding of SCZ.

The frontal pole (Brodmann area 10, BA10) is the largest cytoarchitectonic region of the human cortex, performing complex integrative functions. BA10 undergoes intensive adolescent grey matter pruning prior to the age of onset for bipolar disorder (BP) and schizophrenia (SCHIZ), and its dysfunction is likely to underly aspects of their shared symptomology. In this study, we investigated the role of BA10 neurotransmission-related gene expression in BP and SCHIZ. We performed qPCR to measure the expression of 115 neurotransmission-related targets in control, BP, and SCHIZ postmortem samples ( n = 72). We chose this method for its high sensitivity to detect low-level expression. We then strengthened our findings by performing a meta-analysis of publicly released BA10 microarray data ( n = 101) and identified sources of convergence with our qPCR results. To improve interpretation, we leveraged the unusually large database of clinical metadata accompanying our samples to explore the relationship between BA10 gene expression, therapeutics, substances of abuse, and symptom profiles, and validated these findings with publicly available datasets. Using these convergent sources of evidence, we identified 20 neurotransmission-related genes that were differentially expressed in BP and SCHIZ in BA10. These results included a large diagnosis-related decrease in two important therapeutic targets with low levels of expression, HTR2B and DRD4, as well as other findings related to dopaminergic, GABAergic and astrocytic function. We also observed that therapeutics may produce a differential expression that opposes diagnosis effects. In contrast, substances of abuse showed similar effects on BA10 gene expression as BP and SCHIZ, potentially amplifying diagnosis-related dysregulation.

Mitochondrial dysfunction is a neurobiological phenomenon implicated in the pathophysiology of schizophrenia and bipolar disorder that can synergistically affect synaptic neurotransmission. We hypothesized that schizophrenia and bipolar disorder share molecular alterations at the mitochondrial and synaptic levels. Mitochondria DNA (mtDNA) copy number (CN), mtDNA common deletion (CD), mtDNA total deletion, complex I activity, synapse number, and synaptic mitochondria number were studied in the postmortem human dorsolateral prefrontal cortex (DLPFC), superior temporal gyrus (STG), primary visual cortex (V1), and nucleus accumbens (NAc) of controls (CON), and subjects with schizophrenia (SZ), and bipolar disorder (BD). The results showed (i) the mtDNA CN is significantly higher in DLPFC of both SZ and BD, decreased in the STG of BD, and unaltered in V1 and NAc of both SZ and BD; (ii) the mtDNA CD is significantly higher in DLPFC of BD while unaltered in STG, V1, and NAc of both SZ and BD; (iii) The total deletion burden is significantly higher in DLPFC in both SZ and BD while unaltered in STG, V1, and NAc of SZ and BD; (iv) Complex I activity is significantly lower in DLPFC of both SZ and BD, which is driven by the presence of medications, with no alteration in STG, V1, and NAc. In addition, complex I protein concentration, by ELISA, was decreased across three cortical regions of SZ and BD subjects; (v) The number of synapses is decreased in DLPFC of both SZ and BD, while the synaptic mitochondria number was significantly lower in female SZ and female BD compared to female controls. Overall, these findings will pave the way to understand better the pathophysiology of schizophrenia and bipolar disorder for therapeutic interventions.

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, P < 2.14 × 10-6) and 32 genes at a false discovery rate of <5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure and function of the synapse. The associations of the NMDA (N-methyl-D-aspartate) receptor subunit GRIN2A and AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptor subunit GRIA3 provide support for dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We observe an overlap of rare variant risk among schizophrenia, autism spectrum disorders1, epilepsy and severe neurodevelopmental disorders2, although different mutation types are implicated in some shared genes. Most genes described here, however, are not implicated in neurodevelopment. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk3, suggesting that common and rare genetic risk factors converge at least partially on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, which indicates that more risk genes await discovery using this approach.

BACKGROUND:Mitochondria are multifunctional energy-producing and signaling organelles that support life and contribute to stress adaptation. There is a growing understanding of the dynamic relationship between stress exposure and mitochondrial biology; however, the influence of stress on key domains of mitochondrial biology during early-life, particularly the earliest phases of intra-uterine/prenatal period remains largely unknown. Thus, the goal of this study was to examine the impact of fetal exposure to stress (modeled as the biological construct allostatic load) upon mitochondrial biology in early childhood. METHODS:In n = 30 children (range: 3.5-6 years, 53% male), we quantified mitochondrial content via citrate synthase (CS) activity and mtDNA copy number (mtDNAcn), and measured mitochondrial bioenergetic capacity via respiratory chain enzyme activities (complexes I (CI), II (CII), and IV (CIV)) in platelet-depleted peripheral blood mononuclear cells (PBMCs). In a cohort of healthy pregnant women, maternal allostatic load was operationalized as a latent variable (sum of z-scores) representing an aggregation of early-, mid- and late-gestation measures of neuroendocrine (cortisol), immune (interleukin-6, C-reactive protein), metabolic (homeostasis model assessment of insulin resistance, free fatty acids), and cardiovascular (aggregate systolic and diastolic blood pressure) systems, as well as an anthropometric indicator (pre-pregnancy body mass index [BMI]). RESULTS:An interquartile increase in maternal allostatic load during pregnancy was associated with higher mitochondrial content (24% and 15% higher CS and mtDNAcn), and a higher mitochondrial bioenergetic capacity (16%, 23%, and 25% higher CI, CII and CIV enzymatic activities) in child leukocytes. The positive association between maternal allostatic load during pregnancy and child mitochondrial content and bioenergetic capacity remained significant after accounting for the effects of key pre- and post-natal maternal and child covariates (p's < 0.05, except CI p = 0.073). CONCLUSION:We report evidence that prenatal biological stress exposure, modeled as allostatic load, was associated with elevated child mitochondrial content and bioenergetic capacity in early childhood. This higher mitochondrial content and bioenergetic capacity (per leukocyte) may reflect increased energetic demands at the immune or organism level, and thus contribute to wear-and-tear and pathophysiology, and/or programmed pro-inflammatory phenotypes. These findings provide potential mechanistic insight into the cellular processes underlying developmental programming, and support the potential role that changes in mitochondrial content and bioenergetic functional capacity may play in altering life-long susceptibility for health and disease.

Increasing evidence indicates that mitochondria respond to psychosocial stress and psychiatric illness. One recent study found elevated mitochondrial DNA (mtDNA) deletions in the brains of individuals with psychiatric disorders, but no prior work has examined the relationship of mtDNA deletions and early life stress (ELS). This study assessed mtDNA deletions in peripheral blood mononuclear cells (PBMCs) in healthy young adults, with or without ELS.

Suicides have increased to over 48,000 deaths yearly in the United States. Major depressive disorder (MDD) is the most common diagnosis among suicides, and identifying those at the highest risk for suicide is a pressing challenge. The objective of this study is to identify changes in gene expression associated with suicide in brain and blood for the development of biomarkers for suicide. Blood and brain were available for 45 subjects (53 blood samples and 69 dorsolateral prefrontal cortex (DLPFC) samples in total). Samples were collected from MDD patients who died by suicide (MDD-S), MDDs who died by other means (MDD-NS) and non-psychiatric controls. We analyzed gene expression using RNA and the NanoString platform. In blood, we identified 14 genes which significantly differentiated MDD-S versus MDD-NS. The top six genes differentially expressed in blood were: PER3, MTPAP, SLC25A26, CD19, SOX9, and GAR1. Additionally, four genes showed significant changes in brain and blood between MDD-S and MDD-NS; SOX9 was decreased and PER3 was increased in MDD-S in both tissues, while CD19 and TERF1 were increased in blood but decreased in DLPFC. To our knowledge, this is the first study to analyze matched blood and brain samples in a well-defined population of MDDs demonstrating significant differences in gene expression associated with completed suicide. Our results strongly suggest that blood gene expression is highly informative to understand molecular changes in suicide. Developing a suicide biomarker signature in blood could help health care professionals to identify subjects at high risk for suicide.

Introduction: Large somatic deletions of mitochondrial DNA (mtDNA) accumulate with aging in metabolically active tissues such as the brain. We have cataloged the breakpoints and frequencies of large mtDNA deletions in the human brain. Methods: We quantified 112 high-frequency mtDNA somatic deletions across four human brain regions with the Splice-Break2 pipeline. In addition, we utilized PLINK/Seq to test the association of mitochondrial genotypes with the abundance of these high-frequency mtDNA deletions. A conservative p value threshold of 5E−08 was used to find the significant loci. Results: One mtDNA SNP (T14798C) was significantly associated with mtDNA deletions in two brain regions, the dorsolateral prefrontal cortex (DLPFC) and the superior temporal gyrus. Since the DLPFC showed the most robust association between T14798C and two deletion breakpoints (7816–14807 and 5462–14807), this association was tested in the DLPFC of a replication sample and validated the first results. Incorporating the C allele at 14,798 bp increased the perfect/imperfect length of the repeat at the 3′ breakpoint of the two associated deletions. Conclusion: This is the first study to identify the association of mtDNA SNP with large mtDNA deletions in the human brain. The T14798C allele located in the MT-CYB gene is a common polymorphism that occurs in several mitochondrial haplogroups. We hypothesize that the T14798C association with two deletions occurs by extending the repeat length around the 3′ deletion breakpoints. This simple mechanism suggests that mtDNA SNPs can affect the mitochondrial genome structure, especially in brain where high levels of reactive oxygen species lead to deletion accumulation with aging.

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.