Longitudinal Transcriptomic Analysis of Human Cortical Spheroids Identifies Axonal Dysregulation in the Prenatal Brain as a Mediator of Genetic Risk for Schizophrenia

BACKGROUND: Schizophrenia (SCZ) has a known neurodevelopmental etiology, but limited access to human prenatal brain tissue hampers the investigation of basic disease mechanisms in early brain development. Here, we elucidate the molecular mechanisms contributing to SCZ risk in a disease-relevant model of the prenatal human brain. METHODS: We generated induced pluripotent stem cell–derived organoids, termed human cortical spheroids (hCSs), from a large, genetically stratified sample of 14 SCZ cases and 14 age- and sex-matched controls. The hCSs were differentiated for 150 days, and comprehensive molecular characterization across 4 time points was carried out. RESULTS: The transcriptional and cellular architecture of hCSs closely resembled that of fetal brain tissue at 10 to 24 postconception weeks, showing strongest spatial overlap with frontal regions of the cerebral cortex. A total of 3520 genes were differentially modulated between SCZ and control hCSs across organoid maturation, displaying a significant contribution of genetic loading, an overrepresentation of risk genes for autism spectrum disorder and SCZ, and the strongest enrichment for axonal processes in all hCS stages. The two axon guidance genes SEMA7A and SEMA5A, the first a promoter of synaptic functions and the second a repressor, were downregulated and upregulated, respectively, in SCZ hCSs. This expression pattern was confirmed at the protein level and replicated in a large postmortem sample. CONCLUSIONS: Applying a disease-relevant model of the developing fetal brain, we identified consistent dysregulation of axonal genes as an early risk factor for SCZ, providing novel insights into the effects of genetic predisposition on the neurodevelopmental origins of the disorder

Bivariate causal mixture model quantifies polygenic overlap between complex traits beyond genetic correlation.

Accumulating evidence from genome wide association studies (GWAS) suggests an abundance of shared genetic influences among complex human traits and disorders, such as mental disorders. Here we introduce a statistical tool, MiXeR, which quantifies polygenic overlap irrespective of genetic correlation, using GWAS summary statistics. MiXeR results are presented as a Venn diagram of unique and shared polygenic components across traits. At 90% of SNP-heritability explained for each phenotype, MiXeR estimates that 8.3 K variants causally influence schizophrenia and 6.4 K influence bipolar disorder. Among these variants, 6.2 K are shared between the disorders, which have a high genetic correlation. Further, MiXeR uncovers polygenic overlap between schizophrenia and educational attainment. Despite a genetic correlation close to zero, the phenotypes share 8.3 K causal variants, while 2.5 K additional variants influence only educational attainment. By considering the polygenicity, discoverability and heritability of complex phenotypes, MiXeR analysis may improve our understanding of cross-trait genetic architectures

Cross-tissue eQTL enrichment of associations in schizophrenia.

The genome-wide association study of the Psychiatric Genomics Consortium identified over one hundred schizophrenia susceptibility loci. The number of non-coding variants discovered suggests that gene regulation could mediate the effect of these variants on disease. Expression quantitative trait loci (eQTLs) contribute to variation in levels of mRNA. Given the co-occurrence of schizophrenia and several traits not involving the central nervous system (CNS), we investigated the enrichment of schizophrenia associations among eQTLs for four non-CNS tissues: adipose tissue, epidermal tissue, lymphoblastoid cells and blood. Significant enrichment was seen in eQTLs of all tissues: adipose (β = 0.18, p = 8.8 × 10−06), epidermal (β = 0.12, p = 3.1 × 10−04), lymphoblastoid (β = 0.19, p = 6.2 × 10−08) and blood (β = 0.19, p = 6.4 × 10−06). For comparison, we looked for enrichment of association with traits of known relevance to one or more of these tissues (body mass index, height, rheumatoid arthritis, systolic blood pressure and type-II diabetes) and found that schizophrenia enrichment was of similar scale to that observed when studying diseases in the context of a more likely causal tissue. To further investigate tissue specificity, we looked for differential enrichment of eQTLs with relevant Roadmap affiliation (enhancers and promoters) and varying distance from the transcription start site. Neither factor significantly contributed to the enrichment, suggesting that this is equally distributed in tissue-specific and cross-tissue regulatory elements. Our analyses suggest that functional correlates of schizophrenia risk are prevalent in non-CNS tissues. This could be because of pleiotropy or the effectiveness of variants affecting expression in different contexts. This suggests the utility of large, single-tissue eQTL experiments to increase eQTL discovery power in the study of schizophrenia, in addition to smaller, multiple-tissue approaches. Our results conform to the notion that schizophrenia is a systemic disorder involving many tissues

Dose-dependent transcriptional effects of lithium and adverse effect burden in a psychiatric cohort

Lithium is the first-line treatment for bipolar disorder (BD), but there is a large variation in response rate and adverse effects. Although the molecular effects of lithium have been studied extensively, the specific mechanisms of action remain unclear. In particular, the molecular changes underlying lithium adverse effects are little known. Multiple linear regression analyses of lithium serum concentrations and global gene expression levels in whole blood were carried out using a large case-control sample (n = 1450). Self-reported adverse effects of lithium were assessed with the “Udvalg for Kliniske Undersøgelser” (UKU) adverse effect rating scale, and regression analysis was used to identify significant associations between lithium-related genes and six of the most common adverse effects. Serum concentrations of lithium were significantly associated with the expression levels of 52 genes (FDR < 0.01), largely replicating previous results. We found 32 up-regulated genes and 20 down-regulated genes in lithium users compared to non-users. The down-regulated gene set was enriched for several processes related to the translational machinery. Two adverse effects were significantly associated (p < 0.01) with three or more lithium-associated genes: tremor (FAM13A-AS1, FAR2, ITGAX, RWDD1, and STARD10) and xerostomia (ANKRD13A, FAR2, RPS8, and RWDD1). The adverse effect association with the largest effect was between CAMK1D expression and nausea/vomiting. These results suggest putative transcriptional mechanisms that may predict lithium adverse effects, and could thus have a large potential for informing clinical practice.publishedVersio

Shared genetic loci between depression and cardiometabolic traits

Epidemiological and clinical studies have found associations between depression and cardiovascular disease risk factors, and coronary artery disease patients with depression have worse prognosis. The genetic relationship between depression and these cardiovascular phenotypes is not known. We here investigated overlap at the genome-wide level and in individual loci between depression, coronary artery disease and cardiovascular risk factors. We used the bivariate causal mixture model (MiXeR) to quantify genome-wide polygenic overlap and the conditional/conjunctional false discovery rate (pleioFDR) method to identify shared loci, based on genome-wide association study summary statistics on depression (n = 450,619), coronary artery disease (n = 502,713) and nine cardiovascular risk factors (n = 204,402–776,078). Genetic loci were functionally annotated using FUnctional Mapping and Annotation (FUMA). Of 13.9K variants influencing depression, 9.5K (SD 1.0K) were shared with body-mass index. Of 4.4K variants influencing systolic blood pressure, 2K were shared with depression. ConjFDR identified 79 unique loci associated with depression and coronary artery disease or cardiovascular risk factors. Six genomic loci were associated jointly with depression and coronary artery disease, 69 with blood pressure, 49 with lipids, 9 with type 2 diabetes and 8 with c-reactive protein at conjFDR < 0.05. Loci associated with increased risk for depression were also associated with increased risk of coronary artery disease and higher total cholesterol, low-density lipoprotein and c-reactive protein levels, while there was a mixed pattern of effect direction for the other risk factors. Functional analyses of the shared loci implicated metabolism of alpha-linolenic acid pathway for type 2 diabetes. Our results showed polygenic overlap between depression, coronary artery disease and several cardiovascular risk factors and suggest molecular mechanisms underlying the association between depression and increased cardiovascular disease risk.publishedVersio

Transcriptional and functional effects of lithium in bipolar disorder iPSC-derived cortical spheroids

Lithium (Li) is recommended for long-term treatment of bipolar disorder (BD). However, its mechanism of action is still poorly understood. Induced pluripotent stem cell (iPSC)-derived brain organoids have emerged as a powerful tool for modeling BD-related disease mechanisms. We studied the effects of 1 mM Li treatment for 1 month in iPSC-derived human cortical spheroids (hCS) from 10 healthy controls (CTRL) and 11 BD patients (6 Li-responders, Li-R, and 5 Li non-treated, Li-N). At day 180 of differentiation, BD hCS showed smaller size, reduced proportion of neurons, decreased neuronal excitability and reduced neural network activity compared to CTRL hCS. Li rescued excitability of BD hCS neurons by exerting an opposite effect in the two diagnostic groups, increasing excitability in BD hCS and decreasing it in CTRL hCS. We identified 132 Li-associated differentially expressed genes (DEGs), which were overrepresented in sodium ion homeostasis and kidney-related pathways. Moreover, Li regulated secretion of pro-inflammatory cytokines and increased mitochondrial reserve capacity in BD hCS. Through long-term Li treatment of a human 3D brain model, this study partly elucidates the functional and transcriptional mechanisms underlying the clinical effects of Li, such as rescue of neuronal excitability and neuroprotection. Our results also underscore the substantial influence of treatment duration in Li studies. Lastly, this study illustrates the potential of patient iPSC-derived 3D brain models for precision medicine in psychiatry.publishedVersio

Characterizing the Genetic Overlap Between Psychiatric Disorders and Sleep-Related Phenotypes

Background: A range of sleep disturbances are commonly experienced by patients with psychiatric disorders, and genome-wide genetic analyses have shown some significant genetic correlations between these traits. Here, we applied novel statistical genetic methodologies to better characterize the potential shared genetic architecture between sleep-related phenotypes and psychiatric disorders. Methods: Using the MiXeR method, which can estimate polygenic overlap beyond genetic correlation, the shared genetic architecture between major psychiatric disorders (bipolar disorder [N = 51,710], depression [N = 480,359], and schizophrenia [N = 77,096]) and sleep-related phenotypes (chronotype [N = 449,734], insomnia [N = 386,533] and sleep duration [N = 446,118]) were quantified on the basis of genetic summary statistics. Furthermore, the conditional/conjunctional false discovery rate framework was used to identify specific shared loci between these phenotypes, for which positional and functional annotation were conducted with FUMA. Results: Extensive genetic overlap between the sleep-related phenotypes and bipolar disorder (63%–77%), depression (76%–79%), and schizophrenia (64%–79%) was identified, with moderate levels of congruence between most investigated traits (47%–58%). Specific shared loci were identified for all bivariate analyses, and a subset of 70 credible genes were mapped to these shared loci. Conclusions: The current results provide evidence for substantial polygenic overlap between psychiatric disorders and sleep-related phenotypes, beyond genetic correlation (|rg| = 0.02 to 0.42). Moderate congruency within the shared genetic components suggests a complex genetic relationship and potential subgroups with higher or lower genetic concordance. This work provides new insights and understanding of the shared genetic etiology of sleep-related phenotypes and psychiatric disorders and highlights new opportunities and avenues for future investigation.publishedVersio

Shared genetic architecture between irritable bowel syndrome and psychiatric disorders reveals molecular pathways of the gut-brain axis

Background: Irritable bowel syndrome (IBS) often co-occurs with psychiatric and gastrointestinal disorders. A recent genome-wide association study (GWAS) identified several genetic risk variants for IBS. However, most of the heritability remains unidentified, and the genetic overlap with psychiatric and somatic disorders is not quantified beyond genome-wide genetic correlations. Here, we characterize the genetic architecture of IBS, further, investigate its genetic overlap with psychiatric and gastrointestinal phenotypes, and identify novel genomic risk loci. Methods: Using GWAS summary statistics of IBS (53,400 cases and 433,201 controls), and psychiatric and gastrointestinal phenotypes, we performed bivariate casual mixture model analysis to characterize the genetic architecture and genetic overlap between these phenotypes. We leveraged identified genetic overlap to boost the discovery of genomic loci associated with IBS, and to identify specific shared loci associated with both IBS and psychiatric and gastrointestinal phenotypes, using the conditional/conjunctional false discovery rate (condFDR/conjFDR) framework. We used functional mapping and gene annotation (FUMA) for functional analyses. Results: IBS was highly polygenic with 12k trait-influencing variants. We found extensive polygenic overlap between IBS and psychiatric disorders and to a lesser extent with gastrointestinal diseases. We identified 132 independent IBS-associated loci (condFDR < 0.05) by conditioning on psychiatric disorders (n = 127) and gastrointestinal diseases (n = 24). Using conjFDR, 70 unique loci were shared between IBS and psychiatric disorders. Functional analyses of shared loci revealed enrichment for biological pathways of the nervous and immune systems. Genetic correlations and shared loci between psychiatric disorders and IBS subtypes were different. Conclusions: We found extensive polygenic overlap of IBS and psychiatric and gastrointestinal phenotypes beyond what was revealed with genetic correlations. Leveraging the overlap, we discovered genetic loci associated with IBS which implicate a wide range of biological pathways beyond the gut-brain axis. Genetic differences may underlie the clinical subtype of IBS. These results increase our understanding of the pathophysiology of IBS which may form the basis for the development of individualized interventions.publishedVersio

Prognostic influence of macrophages in patients with diffuse large B-cell lymphoma : a correlative study from a Nordic phase II trial

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