Stem Cell Models for Context-Specific Modeling in Psychiatric Disorders

Genetic Liability to Posttraumatic Stress Disorder Symptoms and Its Association With Cardiometabolic and Respiratory Outcomes

Importance

Posttraumatic stress disorder (PTSD) has been reported to be a risk factor for several physical and somatic symptoms. However, the genetics of PTSD and its potential association with medical outcomes remain unclear.

Objective

To examine disease categories and laboratory tests from electronic health records (EHRs) that are associated with PTSD polygenic scores.

Design, Setting, and Participants

This genetic association study was conducted from July 15, 2021, to January 24, 2023, using EHR data from participants across 4 biobanks. The polygenic scores of PTSD symptom severity (PGS-PTSD) were tested with all available phecodes in Vanderbilt University Medical Center's biobank (BioVU), Mass General Brigham (MGB), Michigan Genomics Initiative (MGI), and UK Biobank (UKBB). The significant medical outcomes were tested for overrepresented disease categories and subsequently tested for genetic correlation and 2-sample mendelian randomization (MR) to determine genetically informed associations. Multivariable MR was conducted to assess whether PTSD associations with health outcomes were independent of the genetic effect of body mass index and tobacco smoking.

Exposures

Polygenic score of PTSD symptom severity.

Main Outcomes and Measures

A total of 1680 phecodes (ie, International Classification of Diseases, Ninth Revision- and Tenth Revision-based phenotypic definitions of health outcomes) across 4 biobanks and 490 laboratory tests across 2 biobanks (BioVU and MGB).

Results

In this study including a total of 496 317 individuals (mean [SD] age, 56.8 [8.0] years; 263 048 female [53%]) across the 4 EHR sites, meta-analyzing associations of PGS-PTSD with 1680 phecodes from 496 317 individuals showed significant associations to be overrepresented from mental health disorders (fold enrichment = 3.15; P = 5.81 × 10-6), circulatory system (fold enrichment = 3.32; P = 6.39 × 10-12), digestive (fold enrichment = 2.42; P = 2.16 × 10-7), and respiratory outcomes (fold enrichment = 2.51; P = 8.28 × 10-5). The laboratory measures scan with PGS-PTSD in BioVU and MGB biobanks revealed top associations in metabolic and immune domains. MR identified genetic liability to PTSD symptom severity as an associated risk factor for 12 health outcomes, including alcoholism (β = 0.023; P = 1.49 × 10-4), tachycardia (β = 0.045; P = 8.30 × 10-5), cardiac dysrhythmias (β = 0.016, P = 3.09 × 10-5), and acute pancreatitis (β = 0.049, P = 4.48 × 10-4). Several of these associations were robust to genetic effects of body mass index and smoking. We observed a bidirectional association between PTSD symptoms and nonspecific chest pain and C-reactive protein.

Conclusions and Relevance

Results of this study suggest the broad health repercussions associated with the genetic liability to PTSD across 4 biobanks. The circulatory and respiratory systems association was observed to be overrepresented in all 4 biobanks.

Genetics of human brain development

Brain development in humans is achieved through precise spatiotemporal genetic control, the mechanisms of which remain largely elusive. Recently, integration of technological advances in human stem cell-based modelling with genome editing has emerged as a powerful platform to establish causative links between genotypes and phenotypes directly in the human system. Here, we review our current knowledge of complex genetic regulation of each key step of human brain development through the lens of evolutionary specialization and neurodevelopmental disorders and highlight the use of human stem cell-derived 2D cultures and 3D brain organoids to investigate human-enriched features and disease mechanisms. We also discuss opportunities and challenges of integrating new technologies to reveal the genetic architecture of human brain development and disorders.

Common genetic variation impacts stress response in the brain

To explain why individuals exposed to identical stressors experience divergent clinical outcomes, we determine how molecular encoding of stress modifies genetic risk for brain disorders. Analysis of post-mortem brain (n=304) revealed 8557 stress-interactive expression quantitative trait loci (eQTLs) that dysregulate expression of 915 eGenes in response to stress, and lie in stress-related transcription factor binding sites. Response to stress is robust across experimental paradigms: up to 50% of stress-interactive eGenes validate in glucocorticoid treated hiPSC-derived neurons (n=39 donors). Stress-interactive eGenes show brain region- and cell type-specificity, and, in post-mortem brain, implicate glial and endothelial mechanisms. Stress dysregulates long-term expression of disorder risk genes in a genotype-dependent manner; stress-interactive transcriptomic imputation uncovered 139 novel genes conferring brain disorder risk only in the context of traumatic stress. Molecular stress-encoding explains individualized responses to traumatic stress; incorporating trauma into genomic studies of brain disorders is likely to improve diagnosis, prognosis, and drug discovery.

Microglial contribution to the pathology of neurodevelopmental disorders in humans

Microglia are the brain's resident macrophages, which guide various developmental processes crucial for brain maturation, activity, and plasticity. Microglial progenitors enter the telencephalic wall by the 4th postconceptional week and colonise the fetal brain in a manner that spatiotemporally tracks key neurodevelopmental processes in humans. However, much of what we know about how microglia shape neurodevelopment comes from rodent studies. Multiple differences exist between human and rodent microglia warranting further focus on the human condition, particularly as microglia are emerging as critically involved in the pathological signature of various cognitive and neurodevelopmental disorders. In this article, we review the evidence supporting microglial involvement in basic neurodevelopmental processes by focusing on the human species. We next concur on the neuropathological evidence demonstrating whether and how microglia contribute to the aetiology of two neurodevelopmental disorders: autism spectrum conditions and schizophrenia. Next, we highlight how recent technologies have revolutionised our understanding of microglial biology with a focus on how these tools can help us elucidate at unprecedented resolution the links between microglia and neurodevelopmental disorders. We conclude by reviewing which current treatment approaches have shown most promise towards targeting microglia in neurodevelopmental disorders and suggest novel avenues for future consideration.

Modeling psychotic disorders: Environment x environment interaction

Schizophrenia is a major psychotic disorder with multifactorial etiology that includes interactions between genetic vulnerability and environmental risk factors. In addition, interplay of multiple environmental adversities affects neurodevelopment and may increase the individual risk of developing schizophrenia. Consistent with the two-hit hypothesis of schizophrenia, we review rodent models that combine maternal immune activation as the first hit with other adverse environmental exposures as the second hit. We discuss the strengths and pitfalls of the current animal models of environment x environment interplay and propose some future directions to advance the field.

Bridging the translational gap: what can synaptopathies tell us about autism?

Multiple molecular pathways and cellular processes have been implicated in the neurobiology of autism and other neurodevelopmental conditions. There is a current focus on synaptic gene conditions, or synaptopathies, which refer to clinical conditions associated with rare genetic variants disrupting genes involved in synaptic biology. Synaptopathies are commonly associated with autism and developmental delay and may be associated with a range of other neuropsychiatric outcomes. Altered synaptic biology is suggested by both preclinical and clinical studies in autism based on evidence of differences in early brain structural development and altered glutamatergic and GABAergic neurotransmission potentially perturbing excitatory and inhibitory balance. This review focusses on the NRXN-NLGN-SHANK pathway, which is implicated in the synaptic assembly, trans-synaptic signalling, and synaptic functioning. We provide an overview of the insights from preclinical molecular studies of the pathway. Concentrating on NRXN1 deletion and SHANK3 mutations, we discuss emerging understanding of cellular processes and electrophysiology from induced pluripotent stem cells (iPSC) models derived from individuals with synaptopathies, neuroimaging and behavioural findings in animal models of Nrxn1 and Shank3 synaptic gene conditions, and key findings regarding autism features, brain and behavioural phenotypes from human clinical studies of synaptopathies. The identification of molecular-based biomarkers from preclinical models aims to advance the development of targeted therapeutic treatments. However, it remains challenging to translate preclinical animal models and iPSC studies to interpret human brain development and autism features. We discuss the existing challenges in preclinical and clinical synaptopathy research, and potential solutions to align methodologies across preclinical and clinical research. Bridging the translational gap between preclinical and clinical studies will be necessary to understand biological mechanisms, to identify targeted therapies, and ultimately to progress towards personalised approaches for complex neurodevelopmental conditions such as autism.

Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings

Major depressive disorder (MDD) is a complex and heterogeneous psychiatric syndrome with genetic and environmental influences. In addition to neuroanatomical and circuit-level disturbances, dysregulation of the brain transcriptome is a key phenotypic signature of MDD. Postmortem brain gene expression data are uniquely valuable resources for identifying this signature and key genomic drivers in human depression; however, the scarcity of brain tissue limits our capacity to observe the dynamic transcriptional landscape of MDD. It is therefore crucial to explore and integrate depression and stress transcriptomic data from numerous, complementary perspectives to construct a richer understanding of the pathophysiology of depression. In this review, we discuss multiple approaches for exploring the brain transcriptome reflecting dynamic stages of MDD: predisposition, onset, and illness. We next highlight bioinformatic approaches for hypothesis-free, genome-wide analyses of genomic and transcriptomic data and their integration. Last, we summarize the findings of recent genetic and transcriptomic studies within this conceptual framework.