Anxiety Cell Models for Research

Anxiety disorders are the most common mental disorders worldwide. According to the World Health Organization (WHO), an estimated 301 million people lived with an anxiety disorder in 2019, including 58 million children and adolescents. The prevalence is higher in females (4.6%) than males (2.6%). Anxiety disorders are often underdiagnosed and undertreated, leading to significant disability and economic burden. The global burden of anxiety disorders has increased during the COVID-19 pandemic, with a rise of 25% in 2020. The 5-year survival is not applicable as anxiety is not a fatal condition, but it significantly reduces quality of life and increases the risk of suicide and comorbid conditions like depression.

Anxiety disorders are complex and heterogeneous, involving genetic, epigenetic, and environmental factors. They are ideal for mechanistic studies because of the availability of well-characterized animal models and human cell lines. Public datasets such as the Psychiatric Genomics Consortium (PGC) provide genome-wide association study (GWAS) data, and the NCBI Gene database lists numerous anxiety-related genes. Open questions include the precise neural circuits, the role of neuroinflammation, and the identification of novel therapeutic targets. Gene-edited cell models allow researchers to dissect the function of specific genes in relevant cell types, such as neurons and glial cells.

Anxiety is not a cancer, but it involves dysregulation of stress response pathways. The major pathways include:

• • Hypothalamic-Pituitary-Adrenal (HPA) Axis: Chronic stress leads to overactivation of the HPA axis, resulting in elevated cortisol levels, which can affect neuronal function.
• • Serotonergic System: Dysregulation of serotonin (5-HT) signaling, including alterations in the serotonin transporter (SLC6A4) and receptors (HTR1A, HTR2A), is implicated.
• • GABAergic System: Reduced GABAergic inhibition, involving GABA-A receptor subunits (GABRA1, GABRG2), contributes to hyperexcitability.
• • Glutamatergic System: Excitatory/inhibitory imbalance, with NMDA and AMPA receptor dysfunction (GRIN1, GRIA1), is involved.
• • Neurotrophin Signaling: Brain-derived neurotrophic factor (BDNF) and its receptor NTRK2 are critical for neuronal survival and plasticity.

Unlike cancer, anxiety disorders are not characterized by somatic mutations but by common genetic variants and epigenetic changes. The following table lists key genes with associated variants and their functional effects, based on data from GWAS and ClinVar.

Anxiety involves complex interactions between multiple signaling networks:

• • Serotonergic signaling: Key nodes include TPH2 (tryptophan hydroxylase), SLC6A4 (serotonin transporter), HTR1A (5-HT1A receptor), and HTR2A (5-HT2A receptor).
• • GABAergic signaling: GAD1 (glutamate decarboxylase), GABRA1, GABRG2, and GABBR1 (GABA-B receptor).
• • Glutamatergic signaling: GRIN1 (NMDA receptor subunit), GRIA1 (AMPA receptor subunit), and GRM5 (metabotropic glutamate receptor 5).
• • HPA axis: CRH (corticotropin-releasing hormone), CRHR1, POMC, and NR3C1 (glucocorticoid receptor).
• • Neurotrophin signaling: BDNF, NTRK2, and downstream MAPK/ERK and PI3K/AKT pathways.

Common cell lines used in anxiety research include:

Organoids, such as brain organoids derived from induced pluripotent stem cells (iPSCs), offer a more physiologically relevant 3D model that recapitulates neuronal development and network activity. They are particularly useful for studying genetic variants associated with anxiety.

Animal models are essential for studying anxiety-like behavior. Common models include:

• • Chronic mild stress (CMS) models: Mice or rats subjected to unpredictable mild stressors for weeks.
• • Elevated plus maze (EPM) and open field test: Behavioral tests to assess anxiety-like behavior.
• • Genetic models: Knockout mice for genes like SLC6A4, BDNF, and CRHR1.
• • Chemogenetic models: Using DREADDs to modulate neuronal activity.
• • Optogenetic models: To control specific neural circuits.
• • PDX (patient-derived xenografts) are not applicable for anxiety, but humanized mouse models with human immune cells are used to study neuroinflammation.

CRISPR-based gene editing enables the creation of isogenic cell lines with precise modifications in anxiety-related genes. These models are invaluable for studying gene function and drug responses. Examples include:

• • SLC6A4 knockout SH-SY5Y cells: To study serotonin reuptake and the effects of SSRIs.
• • BDNF Val66Met knock-in SH-SY5Y cells: To investigate the impact on BDNF secretion and neuronal survival.
• • GRIN1 knockout cells: To study NMDA receptor function and glutamatergic signaling.
• • HTR1A knockout cells: To examine serotonin receptor signaling.

These gene-edited cell lines are commercially available from various sources, ensuring sequence verification and quality. They accelerate research by providing consistent and reproducible models for target validation and drug screening.

Gene-edited cell lines are used to validate the function of genes implicated in anxiety. For example, knocking out SLC6A4 in SH-SY5Y cells allows researchers to study the effects on serotonin uptake and downstream signaling. Knock-in of the BDNF Val66Met variant helps dissect the molecular consequences of this common polymorphism. These models enable high-throughput screening to identify genetic modifiers and novel therapeutic targets.

Isogenic pairs (wild-type vs. gene-edited) are used in drug screening to identify compounds that specifically target the mutated pathway. For instance, screening for compounds that rescue the phenotype of SLC6A4 knockout cells may reveal new anxiolytics. Additionally, gene-edited cells can be used to study drug resistance, such as the development of tolerance to benzodiazepines in GABA receptor mutant cells.

CRISPR-based synthetic lethality screens can identify genes that, when knocked out, are lethal only in the context of a specific anxiety-related mutation. This approach can uncover novel biomarkers and therapeutic targets. For example, in cells with a BDNF Val66Met mutation, knocking out a gene that compensates for the deficit may lead to cell death, highlighting a potential target for intervention.