Publicly Available hiPSC Lines with Extreme Polygenic Risk Scores for Modeling Schizophrenia

Insights for disease modeling from single-cell transcriptomics of iPSC-derived Ngn2-induced neurons and astrocytes across differentiation time and co-culture

BACKGROUND

Trans-differentiation of human-induced pluripotent stem cells into neurons via Ngn2-induction (hiPSC-N) has become an efficient system to quickly generate neurons a likely significant advance for disease modeling and in vitro assay development. Recent single-cell interrogation of Ngn2-induced neurons, however, has revealed some similarities to unexpected neuronal lineages. Similarly, a straightforward method to generate hiPSC-derived astrocytes (hiPSC-A) for the study of neuropsychiatric disorders has also been described.

RESULTS

Here, we examine the homogeneity and similarity of hiPSC-N and hiPSC-A to their in vivo counterparts, the impact of different lengths of time post Ngn2 induction on hiPSC-N (15 or 21 days), and the impact of hiPSC-N/hiPSC-A co-culture. Leveraging the wealth of existing public single-cell RNA-seq (scRNA-seq) data in Ngn2-induced neurons and in vivo data from the developing brain, we provide perspectives on the lineage origins and maturation of hiPSC-N and hiPSC-A. While induction protocols in different labs produce consistent cell type profiles, both hiPSC-N and hiPSC-A show significant heterogeneity and similarity to multiple in vivo cell fates, and both more precisely approximate their in vivo counterparts when co-cultured. Gene expression data from the hiPSC-N show enrichment of genes linked to schizophrenia (SZ) and autism spectrum disorders (ASD) as has been previously shown for neural stem cells and neurons. These overrepresentations of disease genes are strongest in our system at early times (day 15) in Ngn2-induction/maturation of neurons, when we also observe the greatest similarity to early in vivo excitatory neurons. We have assembled this new scRNA-seq data along with the public data explored here as an integrated biologist-friendly web-resource for researchers seeking to understand this system more deeply: https://nemoanalytics.org/p?l=DasEtAlNGN2&g=NES .

CONCLUSIONS

While overall we support the use of the investigated cellular models for the study of neuropsychiatric disease, we also identify important limitations. We hope that this work will contribute to understanding and optimizing cellular modeling for complex brain disorders.

A Functional Single-Nucleotide Polymorphism Upstream of the Collagen Type III Gene Is Associated with Catastrophic Fracture Risk in Thoroughbred Horses

Fractures caused by bone overloading are a leading cause of euthanasia in Thoroughbred racehorses. The risk of fatal fracture has been shown to be influenced by both environmental and genetic factors but, to date, no specific genetic mechanisms underpinning fractures have been identified. In this study, we utilised a genome-wide polygenic risk score to establish an in vitro cell system to study bone gene regulation in horses at high and low genetic risk of fracture. Candidate gene expression analysis revealed differential expression of COL3A1 and STAT1 genes in osteoblasts derived from high- and low-risk horses. Whole-genome sequencing of two fracture cases and two control horses revealed a single-nucleotide polymorphism (SNP) upstream of COL3A1 that was confirmed in a larger cohort to be significantly associated with fractures. Bioinformatics tools predicted that this SNP may impact the binding of the transcription factor SOX11. Gene modulation demonstrated SOX11 is upstream of COL3A1, and the region binds to nuclear proteins. Furthermore, luciferase assays demonstrated that the region containing the SNP has promoter activity. However, the specific effect of the SNP depends on the broader genetic background of the cells and suggests other factors may also be involved in regulating COL3A1 expression. In conclusion, we have identified a novel SNP that is significantly associated with fracture risk and provide new insights into the regulation of the COL3A1 gene.

DPYSL2/CRMP2 isoform B knockout in human iPSC-derived glutamatergic neurons confirms its role in mTOR signaling and neurodevelopmental disorders

The DPYSL2/CRMP2 gene encodes a microtubule-stabilizing protein crucial for neurogenesis and is associated with numerous psychiatric and neurodegenerative disorders including schizophrenia, bipolar disorder, and Alzheimer's disease. DPYSL2 generates multiple RNA and protein isoforms, but few studies have differentiated between them. We previously reported an association of a functional variant in the DPYSL2-B isoform with schizophrenia (SCZ) and demonstrated in HEK293 cells that this variant reduced the length of cellular projections and created transcriptomic changes that captured schizophrenia etiology by disrupting mTOR signaling-mediated regulation. In the present study, we follow up on these results by creating, to our knowledge, the first models of endogenous DPYSL2-B knockout in human induced pluripotent stem cells (iPSCs) and neurons. CRISPR/Cas9-faciliated knockout of DPYSL2-B in iPSCs followed by Ngn2-induced differentiation to glutamatergic neurons showed a reduction in DPYSL2-B/CRMP2-B RNA and protein with no observable impact on DPYSL2-A/CRMP2-A. The average length of dendrites in knockout neurons was reduced up to 58% compared to controls. Transcriptome analysis revealed disruptions in pathways highly relevant to psychiatric disease including mTOR signaling, cytoskeletal dynamics, immune function, calcium signaling, and cholesterol biosynthesis. We also observed a significant enrichment of the differentially expressed genes in SCZ-associated loci from genome-wide association studies (GWAS). Our findings expand our previous results to neuronal cells, clarify the functions of the human DPYSL2-B isoform and confirm its involvement in molecular pathologies shared between many psychiatric diseases.

Cell-type-specific regulation of APOE and CLU levels in human neurons by the Alzheimer's disease risk gene SORL1

SORL1 is implicated in the pathogenesis of Alzheimer's disease (AD) through genetic studies. To interrogate the roles of SORL1 in human brain cells, SORL1-null induced pluripotent stem cells (iPSCs) were differentiated to neuron, astrocyte, microglial, and endothelial cell fates. Loss of SORL1 leads to alterations in both overlapping and distinct pathways across cell types, with the greatest effects in neurons and astrocytes. SORL1 loss induces a neuron-specific reduction in apolipoprotein E (APOE) and clusterin (CLU) and altered lipid profiles. Analyses of iPSCs derived from a large cohort reveal a neuron-specific association between SORL1, APOE, and CLU levels, a finding validated in postmortem brain. Enhancement of retromer-mediated trafficking rescues tau phenotypes observed in SORL1-null neurons but does not rescue APOE levels. Pathway analyses implicate transforming growth factor β (TGF-β)/SMAD signaling in SORL1 function, and modulating SMAD signaling in neurons alters APOE RNA levels in a SORL1-dependent manner. Taken together, these data provide a mechanistic link between strong genetic risk factors for AD.

In vitro modeling of the neurobiological effects of glucocorticoids: A review

Hypothalamic-pituitary adrenal (HPA)axis dysregulation has long been implicated in stress-related disorders such as major depression and post-traumatic stress disorder. Glucocorticoids (GCs) are released from the adrenal glands as a result of HPA-axis activation. The release of GCs is implicated with several neurobiological changes that are associated with negative consequences of chronic stress and the onset and course of psychiatric disorders. Investigating the underlying neurobiological effects of GCs may help to better understand the pathophysiology of stress-related psychiatric disorders. GCs impact a plethora of neuronal processes at the genetic, epigenetic, cellular, and molecular levels. Given the scarcity and difficulty in accessing human brain samples, 2D and 3D in vitro neuronal cultures are becoming increasingly useful in studying GC effects. In this review, we provide an overview of in vitro studies investigating the effects of GCs on key neuronal processes such as proliferation and survival of progenitor cells, neurogenesis, synaptic plasticity, neuronal activity, inflammation, genetic vulnerability, and epigenetic alterations. Finally, we discuss the challenges in the field and offer suggestions for improving the use of in vitro models to investigate GC effects.

Cell-type-specific regulation of APOE levels in human neurons by the Alzheimer's disease risk gene SORL1

SORL1 is strongly implicated in the pathogenesis of Alzheimer's disease (AD) through human genetic studies that point to an association of reduced SORL1 levels with higher risk for AD. To interrogate the role(s) of SORL1 in human brain cells, SORL1 null iPSCs were generated, followed by differentiation to neuron, astrocyte, microglia, and endothelial cell fates. Loss of SORL1 led to alterations in both overlapping and distinct pathways across cell types, with the greatest effects in neurons and astrocytes. Intriguingly, SORL1 loss led to a dramatic neuron-specific reduction in APOE levels. Further, analyses of iPSCs derived from a human aging cohort revealed a neuron-specific linear correlation between SORL1 and APOE RNA and protein levels, a finding validated in human post-mortem brain. Pathway analysis implicated intracellular transport pathways and TGF- β/SMAD signaling in the function of SORL1 in neurons. In accord, enhancement of retromer-mediated trafficking and autophagy rescued elevated phospho-tau observed in SORL1 null neurons but did not rescue APOE levels, suggesting that these phenotypes are separable. Stimulation and inhibition of SMAD signaling modulated APOE RNA levels in a SORL1-dependent manner. These studies provide a mechanistic link between two of the strongest genetic risk factors for AD.

PRSet: Pathway-based polygenic risk score analyses and software

Polygenic risk scores (PRSs) have been among the leading advances in biomedicine in recent years. As a proxy of genetic liability, PRSs are utilised across multiple fields and applications. While numerous statistical and machine learning methods have been developed to optimise their predictive accuracy, these typically distil genetic liability to a single number based on aggregation of an individual's genome-wide risk alleles. This results in a key loss of information about an individual's genetic profile, which could be critical given the functional sub-structure of the genome and the heterogeneity of complex disease. In this manuscript, we introduce a 'pathway polygenic' paradigm of disease risk, in which multiple genetic liabilities underlie complex diseases, rather than a single genome-wide liability. We describe a method and accompanying software, PRSet, for computing and analysing pathway-based PRSs, in which polygenic scores are calculated across genomic pathways for each individual. We evaluate the potential of pathway PRSs in two distinct ways, creating two major sections: (1) In the first section, we benchmark PRSet as a pathway enrichment tool, evaluating its capacity to capture GWAS signal in pathways. We find that for target sample sizes of >10,000 individuals, pathway PRSs have similar power for evaluating pathway enrichment as leading methods MAGMA and LD score regression, with the distinct advantage of providing individual-level estimates of genetic liability for each pathway -opening up a range of pathway-based PRS applications, (2) In the second section, we evaluate the performance of pathway PRSs for disease stratification. We show that using a supervised disease stratification approach, pathway PRSs (computed by PRSet) outperform two standard genome-wide PRSs (computed by C+T and lassosum) for classifying disease subtypes in 20 of 21 scenarios tested. As the definition and functional annotation of pathways becomes increasingly refined, we expect pathway PRSs to offer key insights into the heterogeneity of complex disease and treatment response, to generate biologically tractable therapeutic targets from polygenic signal, and, ultimately, to provide a powerful path to precision medicine.

Use of in vitro derived human neuronal models to study host-parasite interactions of Toxoplasma gondii in neurons and neuropathogenesis of chronic toxoplasmosis

Toxoplasma gondii infects approximately one-third of the world's population resulting in a chronic infection with the parasite located in cysts in neurons in the brain. In most immunocompetent hosts the chronic infection is asymptomatic, but several studies have found correlations between Toxoplasma seropositivity and neuropsychiatric disorders, including Schizophrenia, and some other neurological disorders. Host-parasite interactions of bradyzoites in cysts in neurons is not well understood due in part to the lack of suitable in vitro human neuronal models. The advent of stem cell technologies in which human neurons can be derived in vitro from human induced pluripotent stem cells (hiPSCs) or direct conversion of somatic cells generating induced neurons (iNs), affords the opportunity to develop in vitro human neuronal culture systems to advance the understanding of T. gondii in human neurons. Human neurons derived from hiPSCs or iNs, generate pure human neuron monolayers that express differentiated neuronal characteristics. hiPSCs also generate 3D neuronal models that better recapitulate the cytoarchitecture of the human brain. In this review, an overview of iPSC-derived neurons and iN protocols leading to 2D human neuron cultures and hiPSC-derived 3D cerebral organoids will be given. The potential applications of these 2D and 3D human neuronal models to address questions about host-parasite interactions of T. gondii in neurons and the parasite in the CNS, will be discussed. These human neuronal in vitro models hold the promise to advance the understanding of T. gondii in human neurons and to improve the understanding of neuropathogenesis of chronic toxoplasmosis.

Reduced LYNX1 expression in transcriptome of human iPSC-derived neural progenitors modeling fragile X syndrome

Lack of FMR1 protein results in fragile X syndrome (FXS), which is the most common inherited intellectual disability syndrome and serves as an excellent model disease to study molecular mechanisms resulting in neuropsychiatric comorbidities. We compared the transcriptomes of human neural progenitors (NPCs) generated from patient-derived induced pluripotent stem cells (iPSCs) of three FXS and three control male donors. Altered expression of RAD51C, PPIL3, GUCY1A2, MYD88, TRAPPC4, LYNX1, and GTF2A1L in FXS NPCs suggested changes related to triplet repeat instability, RNA splicing, testes development, and pathways previously shown to be affected in FXS. LYNX1 is a cholinergic brake of tissue plasminogen activator (tPA)-dependent plasticity, and its reduced expression was consistent with augmented tPA-dependent radial glial process growth in NPCs derived from FXS iPSC lines. There was evidence of human iPSC line donor-dependent variation reflecting potentially phenotypic variation. NPCs derived from an FXS male with concomitant epilepsy expressed differently several epilepsy-related genes, including genes shown to cause the auditory epilepsy phenotype in the murine model of FXS. Functional enrichment analysis highlighted regulation of insulin-like growth factor pathway in NPCs modeling FXS with epilepsy. Our results demonstrated potential of human iPSCs in disease modeling for discovery and development of therapeutic interventions by showing early gene expression changes in FXS iPSC-derived NPCs consistent with the known pathophysiological changes in FXS and by revealing disturbed FXS progenitor growth linked to reduced expression of LYNX1, suggesting dysregulated cholinergic system.

Probing the molecular and cellular pathological mechanisms of schizophrenia using human induced pluripotent stem cell models

With recent advancements in psychiatric genomics, as a field, "stem cell-based disease modelers" were given the exciting yet daunting task of translating the extensive list of disease-associated risks into biologically and clinically relevant information in order to deliver therapeutically meaningful leads and insights. Despite their limitations, human induced pluripotent stem cell (iPSCs) based models have greatly aided our understanding of the molecular and cellular mechanisms underlying the complex etiology of brain disorders including schizophrenia (SCZ). In this review, we summarize the major findings from studies in the past decade which utilized iPSC models to investigate cell type-specific phenotypes relevant to idiopathic SCZ and disease penetrant alleles. Across cell type differences, several biological themes emerged, serving as potential neurodevelopmental mechanisms of SCZ, including oxidative stress and mitochondrial dysfunction, depletion of progenitor pools and insufficient differentiation potential of these progenitors, and structural and functional deficits of neurons and other supporting cells. Here, we discuss both the recent progress as well as challenges and improvements needed for future studies utilizing iPSCs as a model for SCZ and other neuropsychiatric disorders.

Modeling common and rare genetic risk factors of neuropsychiatric disorders in human induced pluripotent stem cells

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.

Bench Research Informed by GWAS Results

Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually 'highly polygenic'. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise 'wet biologists' with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.

A Comparison of Ten Polygenic Score Methods for Psychiatric Disorders Applied Across Multiple Cohorts

BACKGROUND

Polygenic scores (PGSs), which assess the genetic risk of individuals for a disease, are calculated as a weighted count of risk alleles identified in genome-wide association studies. PGS methods differ in which DNA variants are included and the weights assigned to them; some require an independent tuning sample to help inform these choices. PGSs are evaluated in independent target cohorts with known disease status. Variability between target cohorts is observed in applications to real data sets, which could reflect a number of factors, e.g., phenotype definition or technical factors.

METHODS

The Psychiatric Genomics Consortium Working Groups for schizophrenia and major depressive disorder bring together many independently collected case-control cohorts. We used these resources (31,328 schizophrenia cases, 41,191 controls; 248,750 major depressive disorder cases, 563,184 controls) in repeated application of leave-one-cohort-out meta-analyses, each used to calculate and evaluate PGS in the left-out (target) cohort. Ten PGS methods (the baseline PC+T method and 9 methods that model genetic architecture more formally: SBLUP, LDpred2-Inf, LDpred-funct, LDpred2, Lassosum, PRS-CS, PRS-CS-auto, SBayesR, MegaPRS) were compared.

RESULTS

Compared with PC+T, the other 9 methods gave higher prediction statistics, MegaPRS, LDPred2, and SBayesR significantly so, explaining up to 9.2% variance in liability for schizophrenia across 30 target cohorts, an increase of 44%. For major depressive disorder across 26 target cohorts, these statistics were 3.5% and 59%, respectively.

CONCLUSIONS

Although the methods that more formally model genetic architecture have similar performance, MegaPRS, LDpred2, and SBayesR rank highest in most comparisons and are recommended in applications to psychiatric disorders.

Common Genetic Variation in Humans Impacts In Vitro Susceptibility to SARS-CoV-2 Infection

The host response to SARS-CoV-2, the etiologic agent of the COVID-19 pandemic, demonstrates significant interindividual variability. In addition to showing more disease in males, the elderly, and individuals with underlying comorbidities, SARS-CoV-2 can seemingly afflict healthy individuals with profound clinical complications. We hypothesize that, in addition to viral load and host antibody repertoire, host genetic variants influence vulnerability to infection. Here we apply human induced pluripotent stem cell (hiPSC)-based models and CRISPR engineering to explore the host genetics of SARS-CoV-2. We demonstrate that a single-nucleotide polymorphism (rs4702), common in the population and located in the 3' UTR of the protease FURIN, influences alveolar and neuron infection by SARS-CoV-2 in vitro. Thus, we provide a proof-of-principle finding that common genetic variation can have an impact on viral infection and thus contribute to clinical heterogeneity in COVID-19. Ongoing genetic studies will help to identify high-risk individuals, predict clinical complications, and facilitate the discovery of drugs.