REVIEW article

Front. Synaptic Neurosci., 10 August 2026

Volume 18 - 2026 | https://doi.org/10.3389/fnsyn.2026.1845252

Zebrafish as a translational model for peptide-mediated synaptic dysfunction related to obesity

  • 1. S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande, Brazil

  • 2. Centro de Análises Proteômicas e Bioquímicas, Universidade Católica de Brasília, Brasília, Brazil

Abstract

Obesity-driven synaptic dysfunction is increasingly recognized as a key mechanism linking metabolic disorders to neurodegenerative diseases. This review aims to explore the utility of zebrafish (Danio rerio) as a translational model to investigate these mechanisms and screen peptide-based therapeutic strategies. Owing to their optical transparency, genetic tractability, and suitability for high-throughput screening, zebrafish provide a powerful platform for studying neuronal circuitry and evaluating bioactive peptides in vivo. Current evidence on pathophysiological processes underlying obesity-related synaptic impairment, including central resistance to metabolic hormones, oxidative stress, and the chronic inflammatory state, which promotes persistent immune activation and neuroinflammation. In addition, the persistence of these disturbances in the organism can lead to dysfunctions and pathologies, such as Parkinson’s and Alzheimer’s diseases, both of which are discussed in more detail in this review. Also, particular emphasis is placed on the roles of glial cells and the gut–brain axis in modulating synaptic integrity. We highlight how cutting-edge technologies, such as live neural imaging and single-cell transcriptomics, are accelerating peptide discovery and mechanism-of-action studies in zebrafish. Furthermore, we discuss emerging therapeutic peptides such as GLP-1 analogs and BDNF-based molecules that modulate inflammatory pathways, restore insulin signaling, and enhance neuronal resilience. Collectively, the evidence positions zebrafish as a robust model not only for elucidating disease mechanisms but also for advancing peptide-based interventions targeting synaptic dysfunction in obesity.

1 Introduction

Obesity is a metabolic disorder whose prevalence has been increasing exponentially, emerging as one of the major public health challenges of the twenty-first century (Tremmel et al., 2017). Fat accumulation is closely associated with the onset of other chronic diseases, such as cardiovascular disorders and endocrine conditions like type 2 diabetes mellitus (DM2), however, growing evidence points to an intrinsic relationship between obesity and a range of brain dysfunctions, including cognitive decline and the development of neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease (Anstey et al., 2011; Piché et al., 2020). Despite the existence of other diabetic conditions, such as type 1 diabetes mellitus and gestational diabetes, DM2 accounts for 60 to 70% of cases and is strongly associated with the aging process (Szablewski, 2025). In this context, most studies investigating the interface between diabetes and dementia focus predominantly on DM2, particularly in the context of obesity, in which chronic low-grade inflammation, insulin resistance, and oxidative stress create a hostile cerebral environment that compromises synaptic integrity and function (Crispino et al., 2020).

The study of synaptic dynamics in response to systemic metabolic alterations is limited in traditional mammalian models due to high costs, long experimental durations, and difficulties in real-time visualization. In this context, the zebrafish (Danio rerio) emerges as a promising experimental model (Ghaddar and Diotel, 2022). Zebrafish combines conserved neuro-metabolic pathways with in vivo imaging capabilities and high-throughput screening, making it a powerful model for investigating obesity-associated neurodegenerative disorders (Santoro, 2014). These features position zebrafish as a valuable tool to investigate the interactions between obesity and synaptic health, as well as potential diagnostic strategies and novel therapeutic approaches (Phillips and Westerfield, 2014).

Given the advantages of zebrafish in therapeutic efficacy testing, its use becomes feasible for the identification of novel effective therapies, among which therapeutic peptides emerge as a promising class of drugs in neuroscience (Fernández et al., 2025). Peptides such as incretin analogs, exemplified by glucagon-like peptide-1 (GLP-1), and neuropeptides like brain-derived neurotrophic factor (BDNF) stand out for their high specificity and ability to act on multiple fronts of the pathophysiology of obesity and its neurological comorbidities (Cohen-Cory et al., 2010; Nauck et al., 2021). GLP-1 also exerts direct neuroprotective effects by modulating inflammation and oxidative stress, thereby supporting cerebral homeostasis (Lv et al., 2024).

In this context, the present review aims to examine the complex interplay between obesity and neurological dysfunctions, highlighting the study of underlying mechanisms and evaluating therapeutic interventions. Furthermore, the potential of therapeutic peptides to mitigate synaptic damage associated with obesity is discussed, emphasizing the value of this model as a strategic tool for developing diagnostic and therapeutic approaches to address the neurological consequences of this condition.

2 An integrative model: zebrafish in neuro-metabolic research

Neurological changes resulting from metabolic disorders have been extensively investigated using different animal models, including non-human primates, pigs, rodents, and, more recently, zebrafish, which has been gaining prominence in research aimed at understanding the effects of obesity (Kleinert et al., 2018). As an excellent tool in the field of neuroscience, zebrafish provide a better understanding of the mechanisms involved in plasticity, degeneration, and regeneration of brain tissue (Ghaddar and Diotel, 2022). Considered a translational model, in addition to a comprehensive analysis of the target disease, D. rerio also allows for the analysis of diagnoses and possible treatments (Phillips and Westerfield, 2014). To emphasize the relevance of zebrafish in global research, a bibliometric analysis using established databases identified 93,381 studies involving zebrafish, of which 20,291 were classified as relevant to toxicological research (Lima et al., 2026).

In fact, zebrafish is particularly well designed for large-scale genetic modifications due to its ex-uterine development, short generation time, and efficient transposon-based transgenesis systems (Moran et al., 2023). One of the main factors that motivates the use of zebrafish is their significant similarity to the human genome and its organization, especially in terms of the genetic pathways responsible for transduction (Postlethwait et al., 2000; Becker and Rinkwitz, 2012). In terms of physiology, zebrafish have the same metabolic organs as humans, reflecting a similarity in energy homeostasis, lipid storage, insulin secretion, and feeding-related behaviors (Zang et al., 2018). For this reason, when induced in D. rerio, obesity-related disorders are analogous to those observed in humans (Ghaddar and Diotel, 2022), driving the development of genetic models, with transgenic lines with obesogenic genes, or with obesity induced by high-fat diets (Zang et al., 2018).

Fluorescent reporter lines enable real-time visualization of developmental processes and obesity progression in transgenic zebrafish, supporting longitudinal in vivo studies (Driever and Fishman, 1996). Because of this peculiarity, fluorescent protein expression allows the monitoring of obesity in transgenic animals, from their development to progression (Faillaci et al., 2018). Despite their outstanding optical transparency, the neural circuits of zebrafish in the larval stages are still developing and do not yet function fully, as observed in adult fish (Shen et al., 2025). However, although they are not typically chosen for optical tests, adult fish possess anatomical regions similar in structure and function to the hippocampus (Zupanc et al., 2005) and amygdala of mammals (Perathoner et al., 2016), allowing for the introduction of behavioral tests in this model. Following this, we provide an example of the influence of the zebrafish’s developmental stages (larval and adult) on scientific research regarding neurological disorder (Figure 1).

Figure 1

Another relevant aspect is that, from a metabolic point of view, zebrafish express functional orthologs of genes involved in energy regulation, including Peroxisome Proliferator-Activated Receptors-γ (PPARγ), in addition to leptin and insulin receptors (Seth et al., 2013). Due to these factors intrinsic to zebrafish, this animal has also come to be used in the field of neuroscience, exploring the consequences of obesity and other metabolic disorders on brain homeostasis (Tonon and Grassi, 2023). These analogous disorders, such as genetic mutant lines like leptin receptor (lepa or lepr) knockouts are widely deployed to isolate endogenous neuroendocrine signaling pathways, consistently resulting in marked hyperphagia and automated adipose accumulation (Oka et al., 2010; Del Vecchio et al., 2021). Complementing these genetic frameworks, diet-induced obesity (DIO) paradigms utilizing high-fat diets or overfeeding with live prey (Artemia salina) successfully mimic the polygenic and environmental complexities of human metabolic syndrome, including systemic lipid shifts and severe hepatic steatosis (Oka et al., 2010; Fowler et al., 2021). Taken together, both modeling strategies establish a reliable dual-experimental baseline for investigating downstream neurobiological comorbidities, such as blood–brain barrier (BBB) disruption and localized synaptic dysfunction (Oka et al., 2010; Del Vecchio et al., 2021).

The observation of the translational boundaries of these models requires careful consideration of distinct technical and biological constraints. The ancestral genome duplication in teleost fish represents a major confounding factor, as targeted disruptions in specific genes like lepa can induce functional compensation by its paralog lepb, yielding divergent and context-dependent phenotypes across laboratory strains (Del Vecchio et al., 2021). Additionally, the regulatory feedback loops differ from mammalian systems, as zebrafish leptin is predominantly synthesized in the liver rather than acting as a classic adipocyte-derived signaling molecule (Michel et al., 2016; Del Vecchio et al., 2021). For dietary approaches, standardizing high-fat formulations remains challenging, and the associated hyper-alimentation often degrades tank water quality, introducing confounding environmental stress that shifts baseline cortisol levels (Smith et al., 2013; Michel et al., 2016). These challenges are continuously offset by the physical advantages of the model during imaging.

In fact, a variety of studies warn about the relationship between increased body fat and the emergence of other chronic degenerative diseases, such as dementia (Hayden et al., 2006). In this context, other unique characteristics of zebrafish have emerged, such as the ability to regenerate the brain after major injuries without cell loss (Ghaddar et al., 2021), allowing for the exploration of neuroprotection and neurogenesis mechanisms (Dorsemans et al., 2017). Although the distribution of neurogenic niches in zebrafish is different when compared to humans (Grandel and Brand, 2013), generating a neuroanatomical distinction, studies point to homologous functions in several areas, such as those responsible for memory processes and fear responses (Fontana et al., 2018), making it an excellent model for studying diseases such as Alzheimer’s (Newman et al., 2014). Above, the image illustrates the comparative anatomy of the functional regions of the brains of an adult human and an adult zebrafish (Figure 2).

Figure 2

This animal model expresses glutamate and gamma-aminobutyric acid (GABA) receptors, with GABA acting as an inhibitory neurotransmitter in adults and as a neurotrophic factor during embryonic neuronal development (Kim et al., 2004). In this species, it is possible to observe in more detail the processes of synaptic plasticity, synaptic contact stabilization, and synaptic maturation due to the presence of Postsynaptic Density Protein 95 (PSD-95) (Meyer et al., 2005). Furthermore, susceptibility genes related to highly prevalent neurodegenerative diseases, including Amyloid Precursor Protein (APP) and presenilins (PSEN1/2), are conserved and functionally active (Joshi et al., 2009; Newman et al., 2009).

The preservation of endocrine and neurological pathways has turned zebrafish into an excellent integrated neuro-metabolic model, generating a better understanding of the pathophysiology of diseases correlated with these disorders (Yashaswini et al., 2025), also allowing for the possibility of new approaches to diagnosis and therapeutic treatments (Ochenkowska et al., 2022). One of the most unique contributions of the zebrafish model to translational neuroscience is the ability to perform dynamic and non-invasive imaging of biological processes in real time using an optical microscope (Ma et al., 2012). Among the various applications, imaging in studies such as the following can be highlighted: (i) Synapse dynamics: through complete visualization of the brain, it is possible to better understand the neural activity of cells and networks; (ii) Neuronal activity: through genetically modified calcium indicators, revealing subcellular changes in Ca2+ based on fluorescence intensity; (iii) Inflammatory response, cellular behavior during microglia recruitment; (iv) Cerebral blood flow and adequate oxygen transport to tissues (Schwerte et al., 2003; Leung et al., 2013; Hamilton et al., 2016).

Although rodents have been considered for a long time as the best animal model for testing new therapeutic approaches, zebrafish are gradually being introduced as a candidate for testing new drugs in the neuroscience field (Pound et al., 2004; Ibhazehiebo et al., 2020). In addition to being easy to maintain and low-cost, D. rerio can be used to perform in vivo toxicity and safety tests, reducing potential drug failures and allowing for faster evaluation of new compounds (Ochenkowska et al., 2022). As mentioned above, zebrafish are commonly used not only as a metabolic model, but also as a model that exhibits neurological comorbidities along with markers of neuroinflammation, oxidative stress, and reduced neurotrophic factors, establishing an experimental platform conducive to testing multifunctional therapies, such as peptides (Zhou et al., 2014; Shang et al., 2025). The versatility offered by this model is advantageous for the development of therapeutic peptides, since these bioactives require a better understanding of their pharmacokinetic and pharmacodynamic properties (Yang et al., 2016; Singh et al., 2024).

Recently, in vivo experiments have begun to use zebrafish in their studies to determine the efficacy and specificity of their therapeutic peptides (Shull et al., 2017). A study using zebrafish and peptide-based nanocomplexes proved that these bioactive compounds can be easily internalized in zebrafish embryos, do not cause harmful or toxic effects, and do not affect the normal development of the fish (Faria et al., 2024). Therefore, zebrafish transcend their role as a disease model to become an indispensable tool for therapeutic development, providing functional in vivo evidence acting on the obesity-synaptic dysfunction axis.

3 Obesity-induced synaptic dysfunction

Complex multifactorial metabolic condition that transcends the mere accumulation of adipose tissue to establish itself as a significant risk factor for the development of dysfunctions in the central nervous system (CNS) (Golkar et al., 2026). The deterioration of cognitive function, synaptic plasticity, and neuronal integrity represents one of the most concerning links between obesity and brain health (Crispino et al., 2020).

Synaptic dysfunction represents a key pathogenic event that precedes both cognitive decline and neurodegeneration and can be marked by alterations in synaptic structure and function, impaired neuronal communication, and synaptic loss, in advanced stages (Valcarcel-Ares et al., 2019; Golkar et al., 2026). A deep understanding of the pathophysiological mechanisms underlying this dysfunction is essential for developing effective therapeutic and preventive strategies, particularly given that one of the major pillars of obesity-induced neurotoxicity lies in hormonal dysregulation, chronic inflammation (both systemic and neuroinflammation), and oxidative stress (Ghaddar and Diotel, 2022), as shown in the following schematic illustration (Figure 3).

Figure 3

Beyond hormonal dysregulation, disruption of redox homeostasis and activation of chronic inflammatory cascades are central events in obesity-associated neurotoxicity (Vuković et al., 2026). Among the mechanisms involved, the Nrf2 (nuclear factor erythroid 2-related factor 2) signaling pathway constitutes a major cellular defense against oxidative stress by regulating the expression of antioxidant enzymes (He et al., 2020). In zebrafish models of diet-induced obesity, excessive lipid intake has been associated with reduced Nrf2 expression in the telencephalon, accompanied by downregulation of key antioxidant genes, including superoxide dismutase 1 (sod1) and catalase (cat) (Weydert and Cullen, 2010; Meguro et al., 2019). Consequently, impaired antioxidant defenses favor reactive oxygen species (ROS) accumulation, which contributes to oxidative damage and compromises synaptic integrity (Beckhauser et al., 2016; Liu et al., 2025).

In parallel, obesity promotes activation of the Toll-like receptor 4 (TLR4)/nuclear factor kappa B (NF-κB) signaling axis. In zebrafish, activation of TLR4 by saturated fatty acids and systemic inflammatory mediators induces NF-κB nuclear translocation, leading to increased expression of pro-inflammatory cytokines such as interleukin-1β (IL-1β) and interleukin-6 (IL-6) (Campos-Bayardo et al., 2025). Sustained activation of these inflammatory pathways contributes to neuroinflammation and exacerbates synaptic dysfunction. Furthermore, stress-responsive mitogen-activated protein kinase (MAPK) pathways, particularly p38 MAPK and c-Jun N-terminal kinase (JNK), are activated in response to oxidative and inflammatory stimuli and have been implicated in neuronal damage and neurodegenerative conditions (Kim and Choi, 2015). Although these pathways have been extensively characterized in mammalian obesity models, their high degree of conservation in zebrafish highlights the utility of this model for investigating molecular mechanisms underlying obesity-induced neurodegeneration (Ghaddar and Diotel, 2022).

Starting with insulin and leptin, two crucial peptide hormones that regulate not only peripheral energy homeostasis but also brain function, acting as essential neuromodulators in the (Chang et al., 2019). Insulin crosses the BBB, and its receptors are abundantly expressed in brain regions involved in complex cognitive processes, such as the hippocampus and prefrontal cortex. In the brain, insulin signaling holds significant importance in modulating synaptic plasticity, directly influencing long-term potentiation (LTP) and long-term depression (LTD), which are fundamental cellular mechanisms for learning and memory formation (Chang et al., 2019; Crispino et al., 2020). Inflammation and oxidative stress contribute to increased BBB permeability by downregulating tight junction proteins in brain regions such as the hippocampus, thereby compromising barrier integrity (Davidson et al., 2014; Ghaddar et al., 2020). In mammalian models of diet-induced obesity, similar mechanisms have been associated with BBB disruption, neuroinflammation, and cognitive impairment, further supporting the translational relevance of these findings. Chronic metabolic inflammation associated with obesity is closely linked to activation of NF-κB signaling, which functions as a central regulator of pro-inflammatory cytokine expression and oxidative stress in the central nervous system. In rodent models of HFD-induced obesity, NF-κB activation in brain regions such as the hippocampus and hypothalamus has been associated with increased expression of pro-inflammatory mediators (TNF-α, IL-1β, and IL-6), leading to synaptic dysfunction, impaired neuroplasticity, and cognitive deficits (Davidson et al., 2014; Meguro et al., 2019).

In parallel, HFD exposure contributes to disruption of BBB integrity through downregulation of tight junction proteins, including claudin-5 and occludin, thereby increasing barrier permeability and facilitating peripheral inflammatory signaling into the brain. Comparable effects have been reported in zebrafish models of diet-induced obesity, in which increased oxidative stress, BBB leakage, and neuroinflammatory responses were observed (Ghaddar et al., 2020). Altogether, these data indicate that NF-κB-mediated inflammatory signaling represents a conserved mechanism linking metabolic dysfunction to BBB disruption and neurobehavioral impairment across vertebrate models, thereby supporting the translational relevance of zebrafish findings in the context of established mammalian evidence.

Similarly, leptin is an anorexigenic hormone produced by adipocytes which signals the state of energy reserves to the hypothalamus but also exerts direct effects on synaptic structure and function in several brain areas, including the hippocampus (Harvey et al., 2006). Leptin resistance, characterized by elevated hormone levels in the bloodstream without a corresponding cellular response in target tissues, impairs synaptic plasticity, neurogenesis, and contributes to cognitive and behavioral decline (Harvey et al., 2006; Ghaddar and Diotel, 2022). This failure in leptin signaling also promotes increased food intake and perpetuates the cycle of obesity and its neurological comorbidities.

Animal models, such as D. rerio, have proven valuable for investigating hormonal dysregulation and its effects on synaptic dysfunction. Studies in zebrafish subjected to high-fat diets (HFD) or overfeeding induce an obese state that mimics many aspects of the human condition, including insulin and leptin resistance (Godino-Gimeno et al., 2023; Al Jaberi et al., 2025). These models exhibit behavioral alterations, such as increased anxiety and deficits in memory and learning, which correlate with synaptic dysfunction and changes in the expression of genes related to plasticity (Picolo et al., 2021; Al Jaberi et al., 2025).

Also, obesity is intrinsically linked to low-grade chronic inflammation, which originates primarily from expanded and dysfunctional adipose tissue. This tissue, particularly visceral fat, releases a myriad of pro-inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and interleukin-1 beta (IL-1β), in addition to chemokines and adipokines, into the systemic circulation (Salas-Venegas et al., 2022). The persistence of these inflammatory mediators compromises the integrity of the BBB, making it more permeable and allowing their translocation into the brain parenchyma. This invasion and the subsequent activation of glial cells, astrocytes, and microglia, initiate neuroinflammation, a pathological process that carries a substantial and deleterious role in synaptic dysfunction (Valcarcel-Ares et al., 2019; Salas-Venegas et al., 2022).

Chronic activation of microglia by peripheral inflammation or DAMPs drives their shift from a neuroprotective (M2) to a pro-inflammatory (M1) state, promoting the release of ROS and cytokines that impair neurogenesis, LTP, and synaptic integrity (Valcarcel-Ares et al., 2019; Crispino et al., 2020). Thus, the zebrafish model offers significant advantages for studying neuroinflammation and its impact on synaptic dysfunction, particularly because their larvae can be subjected to in vivo and real-time visualization of microglial activation, cell migration, and neuroimmune interactions using advanced imaging techniques (Ghaddar and Diotel, 2022). Also, the ability to trace individual neurons and synapses in larvae and adult fish enables detailed analysis of neuroinflammation effects on neural connectivity and function, providing valuable insights into the pathogenesis of obesity-induced synaptic dysfunction (Wanner and Vishwanathan, 2018).

The accumulation of ROS in the brain leads to oxidative damage to essential macromolecules, including lipids (lipid peroxidation), proteins (protein carbonylation), and DNA, thereby compromising neuronal structure and function and directly affecting synaptic integrity and communication (Crispino et al., 2020). In obesity, mitochondria are the main organelles responsible for cellular energy production (ATP) via oxidative phosphorylation, acting as a central pathological feature that manifests as reduced ATP production efficiency, increased ROS generation, and impaired mitochondrial dynamics and biogenesis (Crispino et al., 2020).

Recent studies have pointed to the dysregulation of specific pathways, such as that of cofilin-1, a protein that regulates actin cytoskeleton dynamics in dendritic spines, as a critical molecular link between obesity and synaptic loss (Alsegiani et al., 2025). Zebrafish, with its high metabolic rate and sensitivity to nutritional alterations, serves as an effective model for investigating oxidative stress and mitochondrial dysfunction in the brain. Obesity models in zebrafish demonstrate increased oxidative stress markers and changes in brain mitochondrial function, which correlate with observed cognitive and behavioral deficits (Picolo et al., 2021; Ghaddar and Diotel, 2022).

Indeed, in vivo models enable the investigation of obesity-induced synaptic dysfunction and its functional consequences, particularly through alterations in cognitive and behavioral performance. In zebrafish, these outcomes can be assessed using behavioral paradigms analogous to those employed in mammalian models, thereby facilitating translational comparisons. For example, adult zebrafish exposed to a long-term HFD exhibit significant impairments in learning, associative memory, and executive function, closely paralleling findings reported in rodent models (Meguro et al., 2019).

Beyond neuroinflammation, obesity-associated metabolic stress has also been linked to increased anxiety-like behaviors, which can be evaluated using the Novel Tank Diving Test (Picolo et al., 2021). These alterations are commonly characterized by increased thigmotaxis, heightened agitation, and reduced locomotor activity and exploration of the upper water column, collectively reflecting an anxiogenic phenotype (Borba et al., 2025). Additional behavioral paradigms, including the T- and Y-maze tests for spatial memory and the Novel Object Recognition test for recognition memory, provide complementary functional readouts for identifying cognitive deficits associated with obesity (Luo et al., 2024).

Taken together, these behavioral assays establish an important link between molecular alterations, such as obesity-associated synaptic dysfunction, and clinically relevant phenotypes, thereby strengthening the translational value of zebrafish models for investigating neurocognitive complications associated with obesity. Accordingly, Table 1 lists behavioral tests commonly employed in zebrafish and their mammalian counterparts.

Table 1

Functional domainZebrafish assayMammalian equivalentPrimary outcome and translational readoutRelevance to synaptic dysfunction
Anxiety-like behaviorNovel Tank TestOpen Field TestThigmotaxis and vertical exploration; reflects acute stress response (Johnson et al., 2023)Linked to GABAergic/Glutamatergic imbalance in the pallium (Martins et al., 2024)
Light/Dark PreferenceLight–Dark BoxScototaxis (dark preference); measures risk assessment and conflict (Johnson et al., 2023)Reflects altered synaptic transmission in the ventral telencephalon (War et al., 2022)
Learning and memoryY-Maze / T-MazeY-Maze / T-MazeSpatial working memory and spontaneous alternation
(Cleal et al., 2021)
Long-term memory formation depends on glutamatergic activation of plastic synapses (Blank et al., 2009)
Conditioned Place PreferenceConditioned Place PreferenceAssociative learning and reward-seeking behavior (Yashina et al., 2019)Dopamine receptor manipulations alter acquisition, consolidation, and probe performance in associative and latent learning tasks (Naderi et al., 2016)
Motor and sensorimotorVisual Motor ResponseOpen Field / Activity MonitoringInteraction between visual and motor centers (Bollmann, 2019)These behaviors depend on distributed functional connectivity and circuit architecture, supporting their use as readouts of sensorimotor network integrity (Liu et al., 2025)
Swimming Activity AnalysisRotarod TestSwimming speed, endurance-like output, and coordination patterns are common locomotor phenotypes in zebrafish behavioral analysis (Johnson et al., 2025)Reflects motor neuron integrity and cerebellar-like synaptic coordination (Najac et al., 2023)
Social behaviorShoaling TestThree-Chamber Social TestShoaling quantifies social cohesion and group structure, including spacing and collective organization (Galstyan et al., 2022)Oxytocin receptor loss increases group spacing and reduces polarization, linking shoaling phenotypes to oxytocinergic control of social circuit function (Gemmer et al., 2022)
Mirror TestResident–Intruder ParadigmMirror-induced display assays quantify aggression and social reactivity in zebrafish (Pham et al., 2012)Serotonergic signaling alters mirror-test behavior, supporting a link between aggression-like reactivity and serotonergic modulation of social circuit excitability (de Moura et al., 2023)

Translational behavioral approaches in zebrafish for the evaluation of synaptic dysfunction. The table summarizes behavioral tests used in zebrafish and their mammalian counterparts, highlighting the functional domains assessed, primary behavioral outcomes, and their relevance to synaptic function.

4 Dysfunction of non-neuronal cells in metabolic disorders

Astrocytes provide critical support in the energy metabolism of the CNS providing structural support and regulating the extracellular environment, such as ion balance and neurotransmitter removal, which are essential for synaptic function (Lopategui Cabezas et al., 2014; Chen et al., 2023). These cells modulate neuronal activity through the release of gliotransmitters, such as glutamate, adenosine triphosphate (ATP), and cytokines, and convert glucose into lactate, providing energy to neurons and supporting synaptic plasticity and memory (Bélanger et al., 2011; Beard et al., 2022; Chamaa et al., 2024). Metabolic disorders, such as obesity, can dysregulate this pathway, impair lipid supply, and affect synaptic function in the hippocampus (Suzuki et al., 2010). In this context, astrocytes are essential for lipid synthesis and cholesterol homeostasis, as they supply cholesterol to neurons through Apolipoprotein E (APOE), which is responsible for fat transport in the brain (Valenza et al., 2015).

Despite the physiological function of APOE in the brain, another gene expression, APOE4, alters the normal function of glial cells, potentially contributing to the risk of Alzheimer’s disease through protein aggregation and mitochondrial dysfunction (Fernandez et al., 2019). Overall, the presence of the APOE4 variant alters brain lipid metabolism, reducing the cholesterol available to neurons and leading to the loss of synaptic vesicles and a decrease in SNAP-25 protein, compromising the plasticity and functioning of the hippocampus in vivo (Jeong et al., 2019). According to studies, processes that affect lipid metabolism, such as those observed in metabolic disorders, contribute significantly to synaptic dysfunction and cognitive impairment (Yang et al., 2024).

Transgenic zebrafish models have been employed to study glial cells dynamically, allowing real-time observation of their development, regeneration, and response to nervous system injury (Lyons and Talbot, 2015). In a transgenic zebrafish model, the expression of the multifunctional protein DJ-1 in astrocytes protected against oxidative stress, being associated with the regulation of antioxidant and inflammatory proteins and the activation of the Nrf2-ARE transcriptional pathway, highlighting the crucial role of astrocytes in neuronal defense and preservation (Frøyset et al., 2018). Another transgenic model developed with green fluorescent protein (GFP) linked to glial fibrillary acidic protein (GFAP) enabled the visualization of astrocytes and other glial cells at different developmental stages and under pathological conditions (Bernardos and Raymond, 2006). These experimental models represent a valuable tool to investigate how metabolic alterations affect not only neurons but also other cell types, such as astrocytes, leading to secondary neuronal dysfunction and synaptic impairments (Chen et al., 2020).

Among the various cell types affected by metabolic alterations, microglia stand out for their immunological role and their close relationship between metabolism and neuroinflammation (Wake et al., 2011). Microglia not only detect and respond to pathogens or injuries but also regulate the synaptic microenvironment by controlling the availability of metabolites and influencing neurotransmitter uptake and recycling, thereby contributing to synaptic remodeling (Crapser et al., 2021). In this way, microglia maintain a balance between neuronal activity and inflammatory signaling, being essential for the preservation of synaptic plasticity (Deczkowska et al., 2018). Studies have shown HFD induce microglial activation in the hypothalamus, a critical region for the regulation of food intake and energy expenditure through the TLR4/NF-κB pathway, leading to the release of pro-inflammatory cytokines such as TNF-α and IL-1β, which are closely associated with the onset of neurodegenerative diseases (Stathori et al., 2025).

Another indicator of microglial activation is ghrelin (Ghre) signaling, a 28-amino-acid peptide that directly influences microglial activity in the context of obesity and type 2 diabetes mellitus (Pereira et al., 2017). Ghrelin modulates inflammatory and neurometabolic responses during states of peripheral insulin resistance and hyperphagia, leading to the presence of reactive microglial cells with reduced homeostatic efficiency, thereby promoting neuroinflammation and synaptic dysfunction (Kojima and Kangawa, 2005). Thus, dysregulation of the ghrelin–microglia axis links obesity, insulin resistance, and metabolic disturbances to cognitive impairment and the progression of neurodegenerative diseases (Russo et al., 2022). Excessive microglial activation is associated with the release of pro-inflammatory cytokines, which can induce synaptotoxicity and disrupt neural circuits involved in learning and memory (Wellen and Hotamisligil, 2005).

In adult zebrafish subjected to overfeeding, microglial activation is accompanied by increased levels of pro-inflammatory cytokines, oxidative stress, and reduced neurogenesis, with specific microglial subpopulations either modulating synaptic activity or phagocytosing apoptotic neurons, indicating the presence of distinct molecular programs that regulate adaptive and inflammatory responses in the brain (Ghaddar and Diotel, 2022). Consequently, obesity in zebrafish has been shown to impair short-term memory, while long-term memory remains relatively preserved (Godino-Gimeno et al., 2023). Moreover, metabolic disorders commonly associated with obesity, such as hyperglycemia and overnutrition, trigger a neuroinflammatory state characterized by intense glial activation, compromising the integrity of the blood–brain barrier and impairing neurogenesis, suggesting that the metabolic impacts on the brain are highly conserved across species (Ghaddar and Diotel, 2022). Despite these detrimental effects, the brain also activates endogenous regenerative mechanisms, implying that compensatory responses attempt to repair the damage induced by high-fat diets (Azbazdar et al., 2023; Sadeghdoust et al., 2024).

Oligodendrocytes also stand out as glial cells highly sensitive to metabolic alterations, and their dysfunction, often associated with myelin loss under neurodegenerative conditions, may precede and contribute to neuronal degeneration (Griffiths et al., 1998). Metabolic disturbances in oligodendrocytes, including reduced glycolysis, insufficient lactate transport, and impaired lipid synthesis, particularly cholesterol, compromise energy supply to axons and the maintenance of myelin, thereby impairing efficient neuronal conduction (Saher et al., 2005). In obesity, these effects are exacerbated by decreased cerebral blood flow and reduced oxygen and nutrient availability, which enhance oxidative stress and render oligodendrocytes even more vulnerable (Langley et al., 2020). Such processes lead to diminished mitochondrial function, impaired differentiation, and activation of apoptotic markers, hindering remyelination, aggravating neuroaxonal deficits, and contributing to long-term neurodegeneration (Neto et al., 2023). Overall, microglia, astrocytes, and oligodendrocytes can shift from an oxidative to a more glycolytic metabolic profile, promoting cytokine production, oxidative stress, and neuronal impairment; these metabolic alterations directly disrupt neuron–glia communication and drive the progression of neurodegenerative diseases (Afridi et al., 2020).

Therefore, these glial cells undergo a Warburg-like metabolic reprogramming characterized by an increased dependence on aerobic glycolysis and reduced mitochondrial oxidative metabolism (Vizuete et al., 2024). In the context of obesity, elevated levels of circulating saturated fatty acids and systemic inflammation act as key drivers of this metabolic shift, promoting glial dysfunction in the central nervous system (Guo et al., 2026). This process is mediated by the upregulation of hypoxia-inducible factor 1-alpha (HIF-1α) and glucose transporter 1 (GLUT1), leading to increased glycolytic flux and intracellular accumulation of lactate and reactive oxygen species (ROS) (Corcoran and O’Neill, 2016). These metabolic byproducts function as signaling molecules that promote activation of the NLRP3 inflammasome complex (Ralston et al., 2017). Upon assembly, the NLRP3 inflammasome activates caspase-1, resulting in the maturation and secretion of IL-1β and IL-18, which are central mediators of obesity-associated neuroinflammation.

In zebrafish models of diet-induced obesity, similar inflammatory and metabolic signatures have been reported, including increased oxidative stress and activation of conserved inflammatory pathways, supporting the translational relevance of these mechanisms across vertebrates (Wang et al., 2025). Importantly, this glial metabolic dysregulation contributes to impairment of the astrocyte–neuron lactate shuttle (ANLS), reducing metabolic support to neurons and leading to ATP depletion and structural instability (García-Domínguez, 2026). At the synaptic level, these alterations are associated with disrupted synaptic homeostasis, impaired neurotransmission, and synaptotoxicity (Hasan et al., 2026). In this context, peptide-based interventions emerge as promising modulators of obesity-induced neuroinflammatory and metabolic dysfunction. Bioinspired and rationally designed peptides have been reported to modulate key upstream regulators of this cascade, including HIF-1α signaling, GLUT1-mediated metabolic flux, and NLRP3 inflammasome activation, thereby attenuating IL-1β/IL-18 release and restoring glial metabolic balance (Wu et al., 2025, 2026). In addition, certain neuroactive peptides may directly influence synaptic stability by modulating neurotransmitter systems and promoting synaptic plasticity. Collectively, these peptide-mediated effects suggest a potential strategy to counteract obesity-driven glial dysfunction and synaptic impairment, with zebrafish providing a valuable translational platform for screening and functional validation of these compounds (Muraleedharan et al., 2020; Sun et al., 2020).

In this context, therapeutic strategies aimed at modulating neuroinflammation have garnered significant interest, with anti-inflammatory peptides emerging as promising candidates due to their ability to regulate the release of inflammatory mediators, modulate pattern recognition receptors, and inhibit pro-inflammatory signaling pathways (Liu et al., 2024). Moreover, zebrafish represent a valuable model for investigating the role of intracellular peptides in cell–cell communication, enabling studies on mechanisms underlying neurological disorders and neurodegenerative diseases (Teixeira et al., 2019). Evidence suggests that certain bioactive peptides can modulate the release of inflammatory mediators, regulate the expression of pattern recognition receptors, inhibit pro-inflammatory signaling pathways, and promote the resolution of inflammation, thereby restoring homeostatic balance in the central nervous system (Giri and Chandra, 2025).

5 Microbiota–gut–brain–synapse axis: insights from zebrafish models

The gut microbiota is increasingly recognized as a critical regulator of host metabolism, immune homeostasis, and bidirectional communication with the central nervous system through the microbiota–gut–brain axis (Weiss and Hennet, 2017; Moszak et al., 2020). Alterations in microbial composition associated with obesity promote intestinal dysbiosis, systemic inflammation, and metabolic dysfunction, ultimately contributing to neuroinflammation and synaptic impairment. Under normal conditions, the gut microbiota maintains host homeostasis and mitigates adverse physiological effects. However, factors such as dietary habits, medication use, alterations in the intestinal mucosa, immune dysregulation, and changes in microbial composition can disrupt this balance, promoting dysbiosis and metabolic disorders (Weiss and Hennet, 2017; Moszak et al., 2020).

In fact, individuals with reduced gut microbial diversity exhibit higher body mass index, adiposity, dyslipidemia, brain insulin resistance, and a more pronounced inflammatory state (Liu et al., 2017). Alterations in bacterial metabolism influence host biochemical diversity and metabolic activity, thereby affecting multiple physiological processes. Consequently, obesity-associated dysbiosis contributes to excessive adipose tissue accumulation and the exacerbation of inflammatory responses (Smith et al., 2007; Gomes et al., 2018).

Over the past decade, gut dysbiosis has been associated with numerous disorders, including obesity, diabetes, cardiovascular disease, autoimmune diseases, and neurological disorders (Martin-Gallausiaux et al., 2021). Increasing evidence indicates that specific microorganisms, their metabolites, and structural components modulate the pathophysiology of neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease (Vogt et al., 2017). Although the precise mechanisms underlying these interactions remain incompletely understood, increasing evidence supports a central role for the microbiota–gut–brain axis in obesity-associated neurodegeneration (Zang et al., 2018; Zhong et al., 2022). Through in vivo studies, communication within the microbiota–gut–brain axis has been shown to occur through a complex bidirectional network in which the central nervous system regulates the enteric nervous system, autonomic nervous system, and microbial activity, while signals originating from the gut and its microbiota influence CNS development and function (Lynch and Pedersen, 2016; Socała et al., 2021).

One of the principal communication pathways within the microbiota–gut–brain axis is the vagus nerve, which transmits intestinal signals to the central nervous system (Bonaz et al., 2018; Ahmed et al., 2022). Microbial metabolites constitute another major route of gut–brain communication. These metabolites are end products of bacterial metabolism and profoundly influence brain function through interactions with the autonomic nervous system and synaptic signaling (Cryan et al., 2019; Kasarello et al., 2023; Miri et al., 2023). Among them, short-chain fatty acids stimulate the secretion of insulin, ghrelin, leptin, and amylin, thereby slowing gastric emptying, prolonging intestinal transit, and enhancing glucose-dependent insulin release (Koh et al., 2016; Martin-Gallausiaux et al., 2021).

Furthermore, the gut microbiota produces neurotransmitters and neuromodulators, including catecholamines, GABA, and tryptophan-derived metabolites, which influence hypothalamic activity, neuroendocrine signaling, and neurodevelopment (Cussotto et al., 2018; Wang et al., 2023). Another important communication route is the neuroendocrine pathway, in which enteroendocrine cells release hormones and neurotransmitters, including GLP-1, PYY, cholecystokinin, substance P, and serotonin, playing an essential role in communication between the intestine and the central nervous system (5-HT) (Wang et al., 2023). Therefore, tryptophan, metabolized by the microbiota into serotonin and kynurenine pathway compounds, may, under inflammatory conditions, be redirected to the production of quinolinic acid, a neurotoxic metabolite associated with neuronal death in neurodegenerative diseases (O’Mahony et al., 2015; Agus et al., 2018). Thus, studies with gnotobiotic zebrafish have been essential for mapping how the presence or absence of specific microorganisms alters the metabolite profile and, consequently, neuronal development and function (Rea et al., 2022).

An increasing number of studies have examined the bidirectional signaling within the brain–gut–microbiome (BGM) axis in the pathophysiology of obesity, mediated by metabolic, endocrine, neural, and immune mechanisms (Osadchiy et al., 2019). In this context, although structural differences exist between the zebrafish and human intestines, D. rerio shares conserved molecular mechanisms related to intestinal structure and function (Lieschke and Currie, 2007). Accordingly, several obesity models have been developed in zebrafish through dietary and genetic manipulations (Zang et al., 2018), enabling the comparison of metabolic phenotypes in DIO, such as overfeeding with a normal-fat diet (Landgraf et al., 2017).

Recently, several studies, many of which employ zebrafish, have elucidated molecular mechanisms by which the gut microbiota influences neurodegeneration (Wang et al., 2022). Molecular mimicry involves bacterial amyloids, such as the Curli protein from Escherichia coli, which are structurally analogous to human Aβ and α-synuclein and can trigger exaggerated immune responses, accelerating protein aggregation linked to neurodegeneration (Friedland, 2015). During dysbiosis, lipopolysaccharide from Gram-negative bacteria can cross the intestinal and blood–brain barriers, activating glial Toll-like receptors and promoting neuroinflammation via TNF-α and IL-1β, thereby contributing to neuronal damage in Alzheimer’s and Parkinson’s diseases (Sampson et al., 2016; Adedara et al., 2024). Zebrafish models are particularly advantageous for visualizing these processes in real time, enabling the observation of immune cell infiltration into the brain and microglial activation following systemic lipopolysaccharide exposure (Mohanta et al., 2020).

Given the complexity of these microbiota–gut–brain interactions, robust experimental models are required to investigate these pathways under controlled conditions. The zebrafish is a model organism known for its use in the field of translational neuroscience and has also been used in studies addressing the gut microbiome (Gerlai, 2014; Borrelli et al., 2016; Lu et al., 2021). The zebrafish provides insights into the causative role of certain microorganisms in neuroinflammation, BBB dysfunction, and the aggregation of pathological proteins such as beta-amyloid (Aβ) and alpha-synuclein (α-syn) (Lee et al., 2021; Zhang et al., 2022). Nevertheless, their capacity to create gnotobiotic models revolutionizes their use in studying the gut-brain axis, and, unlike mice, breeding germ-free zebrafish requires a rapid and low-cost process, achieved through surface sterilization of the eggs (Xia et al., 2022). Based on this approach, the correlation between the direct function of microbial components and brain health can be investigated, an advancement that was difficult to achieve with more complex models (Stagaman et al., 2024).

6 Technologies applied to zebrafish

The zebrafish model allows biological processes to be observed in real time, offering significant advantages over in vitro models or other opaque animal models, enabling imaging at the systemic, cellular, and subcellular levels (Ahrens et al., 2013; Antinucci and Hindges, 2016; Ahrens et al., 2013; Antinucci and Hindges, 2016). In models with induced obesity, for example, imaging tests can be used to measure the amount of fat mass gained from different diets, such as a high-fat diet (Landgraf et al., 2017; Landgraf et al., 2017). It can be performed on the same individual using different approaches, such as analyzing neural development. The use of two-photon microscopy enables visualization of biological structures and processes, allowing imaging of synapses, dendrites, and entire neuronal populations in in vivo assays with high resolution and complexity (Griffiths et al., 2020; de Vito et al., 2022; Griffiths et al., 2020; de Vito et al., 2022).

Two-photon excitation uses infrared light, promising less aggression and allowing greater tissue penetration without causing significant damage. It is invisible to fish, minimizing interference with natural behavior (Hasani et al., 2023). This methodology was applied to observe the process of adipogenesis in zebrafish, since the lipid metabolism pathways are the same in mammals (den Broeder et al., 2017). Thus, this method has also helped to investigate disease progression and synaptic changes in zebrafish models, similar to Alzheimer’s and Parkinson’s (Muto and Kawakami, 2016; de Vito et al., 2022). The application of the two-photon technique during pathological processes is ideal for observing morphological and functional changes, as well as the body’s response to potential treatments (Turrini et al., 2024). During the administration of peptide-based drug therapies, whose biodistribution still requires investigation, this technique allows direct visualization of peptide biodistribution and treatment responses in vivo (Turrini et al., 2023). Furthermore, as a translational animal model, using zebrafish, it is possible to observe whether a specific peptide can prevent synaptic degeneration or restore compromised neuronal function (Fiametti et al., 2025). The assessment of improvement in rapid axonal transport, a process that is also often dysfunctional in neurodegeneration, can also be monitored with two-photon after peptide administration (Grimaud et al., 2022).

Other methodologies have also been employed to investigate both disease mechanisms and treatment effects, including optogenetic analyses, which allow precise control of neuronal activity using light beams (Simmich et al., 2012). By expressing light-sensitive proteins, such as opsins, in specific neurons, it is possible to selectively activate or inhibit these neurons with light pulses, enabling the manipulation of neural circuits and the study of their functions (Zhu et al., 2009). Zebrafish represent an ideal model for optogenetics due to the ease of genetic manipulation, allowing the control of specific neuronal populations (Portugues et al., 2013; Chia et al., 2022). This approach provides insights into disease mechanisms and, when applied in therapeutic protocols, enables the evaluation of peptide efficacy in restoring circuit function or mitigating the effects of induced dysfunction (Zhang et al., 2024).

In addition to imaging approaches, biomolecular analysis methodologies, particularly gene expression profiling, allow for the understanding of the function and dysfunction of neural populations, complementing imaging by revealing the molecular mechanisms underlying disease and treatment effects (Denninger et al., 2022). Single-cell RNA sequencing (scRNA-seq) enables the analysis of gene expression profiles at the individual cellular level, uncovering cellular heterogeneity and transcriptional states that would be masked in bulk RNA analyses (Farnsworth et al., 2020). In zebrafish, scRNA-seq has been instrumental in mapping cellular development, identifying rare cell types, and understanding molecular changes that occur across different developmental stages and in response to stimuli (Pandey et al., 2023; Sur et al., 2023).

Studies in zebrafish have employed scRNA-seq to compare transcriptomic profiles in Alzheimer’s and Parkinson’s disease models with human tissues, revealing both shared and distinct molecular responses (Cosacak et al., 2022; Lau et al., 2025). This technique can identify early disease biomarkers, elucidate mechanisms of neuroinflammation and neurodegeneration, and guide the development of therapies targeting specific cell types (Cosacak et al., 2019). By analyzing the transcriptomic profiles of individual cells in neurodegenerative disease models treated with peptides, it is possible to identify the genetic pathways and cell types that respond to the intervention (Cosacak et al., 2019). This can reveal new therapeutic targets, treatment response biomarkers, and the heterogeneity of cellular responses to peptides, providing a detailed understanding of their molecular mechanisms of action (Cosacak et al., 2019).

Behavioral assays have been extensively used in zebrafish over the past decade to monitor performance alterations ranging from metabolic disorders to their neurodegenerative consequences (Godino-Gimeno et al., 2023). Recently, with advances in artificial intelligence (AI), its application has been further enhanced in vivo behavioral analyses, including the use of machine learning and computer vision, transforming the analysis of complex datasets generated in zebrafish studies (Fan et al., 2023). Additionally, AI algorithms are employed to process and interpret large volumes of imaging data, identifying subtle morphological and functional features that may be overlooked by conventional behavioral tests (Yang et al., 2021).

AI is particularly valuable for drug screening and disease model phenotyping, such as in Parkinson’s disease, where it has been employed to discriminate movement disorders, enabling the identification of novel therapeutic compounds (Gendelev et al., 2024). AI can also be used to assess the impact of genetic mutations or toxin exposures on behavior and neural morphology, providing a powerful tool for biomarker discovery and understanding disease pathogenesis (Bozhko et al., 2022; Del Rosario Hernández et al., 2024). In this context, AI can predict peptide efficacy based on their structure and interactions with biological targets, optimizing the drug discovery process and allowing a more precise evaluation of peptides’ ability to reverse or mitigate behavioral and morphological deficits associated with neurodegeneration (Del Rosario Hernández et al., 2024).

7 Therapeutic strategies assessed using zebrafish

Biomedical research heavily relies upon in vivo models for the evaluation and validation of new therapeutic strategies (Domínguez-Oliva et al., 2023). Such models, which include a variety of living organisms, allow the study of diseases in a complex biological context, providing crucial insights into the efficacy, safety and mechanisms of action of potential treatments (Lange and Inal, 2023). The application of animal models in biological studies and drug development has long been established, owing to the remarkable anatomical and physiological parallels between humans and mammals (Barré-Sinoussi and Montagutelli, 2015). The zebrafish has been deployed to investigate such effects, providing insights into how those peptides may influence brain function (Yan et al., 2024), simplified in Table 2.

Table 2

Molecule (therapeutic group)Mechanism of actionObserved effectsAdvantagesLimitationsReferences
Protein-based drugs
Liraglutide (GLP-1 agonist receptor)Activation of GLP-1 receptors; modulation of neuronal excitability and inflammation; improvement of glucose metabolismPromoted neuronal viability, reduced apoptosis, regulated neuroinflammatory responses, and exhibited anxiolytic and antidepressant-like effectsClinically approved; demonstrated neuroprotective efficacy in multiple models; translational potential to humansRequires parenteral administration; possible desensitization of GLP-1R with chronic useCandeias et al. (2015), Abd el-Rady et al. (2021), Bertelli et al. (2021), and Urkon et al. (2025)
Tirzepatide (GIP and GLP-1 receptor agonist)Dual activation of GIP and GLP-1 receptors; AMPK activation; antioxidant, anti-inflammatory, and anti-apoptotic actionsImproved cognitive performance, restored antioxidant and anti-inflammatory markers in DM2 zebrafish modelsEnhanced efficacy via dual incretin signaling; broader metabolic and neuroprotective coverageLimited long-term data on CNS effects; potential gastrointestinal adverse eventsHristov et al. (2025) and Misra et al. (2025)
BDNF (neurotrophin)Activation of TrkB receptors; modulation of synaptic plasticity and neuronal survivalEnhanced learning, memory, and synaptic connectivity; conserved function between zebrafish and humansHigh translational relevance; potent modulator of synaptic function.Poor pharmacokinetic stability; limited ability to cross the BBBCohen-Cory et al. (2010), De Felice et al. (2014), Lucini et al. (2018), and Lucon-Xiccato et al. (2022)
PACAP38 (neuropeptide)Modulation of cAMP/PKA pathways; antioxidant, anti-apoptotic, and anti-inflammatory effectsProtected neurons and sensory cells from oxidative stress; mitigated apoptosis in neurotoxic modelsBroad neuroprotective spectrum; highly conserved peptideShort half-life; poor stability; complex receptor signaling networkKasica et al. (2016), Kasica-Jarosz et al. (2018), Ghanizada et al. (2019), and Cherait et al. (2025)
NGF (neurotrophin)Activation of TrkA receptors; regulation of neuronal differentiation, repair, and maintenancePromoted neuronal survival, cholinergic protection, and synaptic repairCentral for neuronal development; strong neuroregenerative propertiesLimited BBB permeability; potential pro-nociceptive and inflammatory effectsBathina and Das (2015), Xiao and Le (2016), and Gu et al. (2025)
Non-protein drugs
Metformin (biguanide)AMPK pathway activation; regulation of mitochondrial respiration and insulin sensitivityExhibited neuroprotective effects, reduced oxidative stress, improved mitochondrial function and neuronal survivalSafe, inexpensive, and well-characterized; multi-targeted cellular benefitsLimited brain penetration; variable efficacy in advanced neurodegenerative stagesSportelli et al. (2020) and Reed et al. (2025)
Vildagliptin (DPP-4 inhibitor)Inhibition of dipeptidyl peptidase-4 enzyme; prolongation of endogenous GLP-1 activityEnhanced neuronal survival, reduced oxidative damage, and improved behavioral parameters in DM2 modelsOral drug with good safety profile; indirectly promotes neurotrophic effectsModerate CNS activity; limited experimental evidence in zebrafishPariyar et al. (2022)
Sitagliptin (DPP-4 inhibitor)Inhibition of DPP-4, increasing levels of active incretins and insulin sensitivityReduced brain inflammation and oxidative stress; improved cognition in Parkinson-like zebrafish.Neuroprotective potential through indirect incretin pathway activationMechanistic specificity in CNS remains unclear; moderate efficacyMani and Arfeen (2024)
Pioglitazone (thiazolidinediones)PPAR-γ activation; regulation of mitochondrial and insulin signaling pathways; reduction of neuroinflammationImproved cognitive and behavioral outcomes; decreased inflammatory cytokines and oxidative damage.Well-known anti-inflammatory profile; promising in metabolic and neurodegenerative contextsAssociated with weight gain and cardiovascular side effectsHu et al. (2024)
Rosiglitazone (thiazolidinediones)PPAR-γ agonist; promotes mitochondrial biogenesis and glucose utilization in neuronsEnhanced learning performance; mitigated oxidative stress and synaptic dysfunction in zebrafish CNS modelsRestores mitochondrial activity and synaptic plasticitySafety concerns regarding cardiac effects; limited CNS selectivityCai et al. (2025)

Therapeutic strategies evaluated in zebrafish models and their main effects, featuring different classes of molecules with neuroprotective and metabolic potential describing their mechanisms of action, observed effects, advantages, and limitation.

These studies highlight the use of zebrafish as a translational model to investigate the relationship between metabolism, inflammation, and synaptic dysfunction.

Although zebrafish represent an attractive model for studies involving peptide-based therapeutic interventions, the route of administration and its influence on pharmacokinetics must be carefully considered when interpreting experimental outcomes. In larval models, immersion is the most commonly employed method; however, this approach relies on passive absorption through the skin and gills, which may not accurately reproduce systemic distribution and limits precise tracking of peptide uptake and biodistribution (Cocchiaro and Rawls, 2013). Moreover, peptide administration by immersion may increase susceptibility to degradation and instability, posing an additional challenge for therapeutic investigations (Lee et al., 2025).

In contrast, adult zebrafish allow more controlled delivery approaches, including intravenous and intraperitoneal microinjection as well as oral gavage, enabling better characterization of absorption, distribution, metabolism, and excretion (ADME) processes (Chaoul et al., 2023). In neurological studies, another important consideration is the developmental status of BBB. In larval zebrafish, BBB maturation is still ongoing, and the extent to which its permeability and functional properties resemble those of the mammalian BBB remains incompletely understood (Fleming et al., 2013). Consequently, BBB permeability may influence peptide exposure within the central nervous system and should be considered when extrapolating findings to mammalian models.

Furthermore, several studies have demonstrated that pharmacokinetic parameters obtained in zebrafish correlate with those observed in mammals, including humans. In particular, Kulkarni et al. highlighted the translational value of zebrafish for pharmacokinetic studies, supporting their use as a complementary model for predicting mammalian ADME profiles (Kulkarni et al., 2017). Therefore, differences in developmental stage and administration route should be taken into account when comparing peptide efficacy and pharmacokinetic profiles between zebrafish and mammalian models.

Due to its well-established central nervous system and ability to model a wide range of pathological conditions, from stress to DM2 and neurodegenerative diseases, zebrafish provide an efficient platform for screening and validating peptide compounds (Lucini et al., 2018). In vivo models have thus become crucial for elucidating metabolic dysfunction, such as that observed in DM2, accelerating neurodegenerative processes, including amyloid aggregation, mitochondrial impairment, and synaptic loss (Athauda and Foltynie, 2016; de Bem et al., 2021).

As previously mentioned, the association with metabolic disorders, such as DM2 and neurodegenerative diseases, has been increasingly recognized (Procaccini et al., 2016) and consequently, the number of studies focused on treating these diseases has also increased. Several studies have shown that certain classes of antidiabetic drugs can attenuate neuroinflammation, oxidative stress, mitochondrial dysfunction, and neuronal apoptosis, which are common pathological mechanisms in diseases such as Alzheimer’s and Parkinson’s (Nowell et al., 2023). The GLP-1, a derivative of proglucagon generated via post-translational processing, is primarily produced by enteroendocrine L cells in the intestine and can also be secreted by some neurons in the hindbrain, linking peripheral and central mechanisms of energy regulation (Nauck et al., 2021; Monti et al., 2022).

The GLP-1 and gastric inhibitory polypeptide (GIP) analogs, originally developed for the treatment of DM2, have shown promising neuroprotective effects, extending their therapeutic potential beyond glycemic regulation (Hristov et al., 2025). Moreover, Liraglutide, a GLP-1 receptor agonist, has been shown to promote neuronal viability and regulate neuroinflammatory processes in several in vivo models (Candeias et al., 2015; Urkon et al., 2025). Upon binding to GLP-1 receptors, Liraglutide activates intracellular signaling cascades, including the PI3K/Akt and MAPK/ERK pathways, which contribute to neuronal survival, attenuation of excitotoxicity, and enhancement of antioxidant defenses (Li et al., 2015). In particular, activation of these pathways has been associated with reduced oxidative stress and preservation of synaptic function. Notably, Bertelli et al. demonstrated that short-term liraglutide treatment exerts anxiolytic-like effects in zebrafish, whereas long-term administration mitigates the behavioral and physiological consequences of chronic unpredictable stress (Bertelli et al., 2021). Therefore, Liraglutide improves brain oxidative status and reduces oxidative damage, further supporting its neuroprotective properties (Bertelli et al., 2021; Lv et al., 2024), as can be seen below (Figure 4).

Figure 4

Beyond Liraglutide, another GLP-1 receptor agonist antidiabetic drug, Tirzepatide, a dual agonist of GIP and GLP-1 receptors, represents a potential neuroprotective drug (Hristov et al., 2025). Recently, a study in zebrafish with a high-fat diet induced by DM2 investigated the effects of Tirzepatide (10 nM/kg, i.p.), which improved cognitive performance and restored levels of GSH, catalase, and IL-10, effects attributed to its antioxidant, anti-inflammatory, anti-apoptotic, and AMPK-activating neuroprotective actions (Misra et al., 2025). The dual effects of Tirzepatide may provide a more robust and effective pharmacological profile compared to selective agonists, addressing the complex pathophysiology of diabetes-related cognitive impairment more comprehensively (Hristov et al., 2025; Misra et al., 2025).

Beyond hormonal peptides, such as Liraglutide and Tirzepatide, certain molecules may exert neuroprotective effects, including neurotrophic factors. Neurotrophic factors are proteins that regulate neuronal growth, differentiation, repair, and survival, playing a central role in synaptic transmission and neuronal plasticity (Mitre et al., 2016). Their effects are essential for neural integrity and plasticity, and the absence or dysfunction of these factors may lead to degeneration and apoptosis of neurons (Capossela et al., 2024). Synaptic modulation by those factors is crucial for the development and healthy functioning of the CNS (Durán Laforet and Schafer, 2024). In vivo studies have investigated the therapeutic potential of neurotrophic factors and synaptic modulators to restore neuronal function and connectivity in different neurological conditions (Numakawa and Kajihara, 2025).

BDNF is one of the most studied neurotrophic factors, known for its ability to modify synaptic strength and to act as a mediator, modulator, or instructor of synaptic plasticity (Cohen-Cory et al., 2010; Colucci-D’amato et al., 2020). Another important neuroprotective pathway involves brain-derived neurotrophic factor (BDNF) and its receptor TrkB. Activation of BDNF/TrkB signaling stimulates downstream PI3K/Akt and MAPK pathways (Teng et al., 2026), promoting neuronal survival, synaptic plasticity, and memory-related processes. Therefore, modulation of BDNF/TrkB signaling represents a promising strategy for counteracting obesity-associated synaptic dysfunction and cognitive impairment (Lee and Lim, 2025). Overall, these findings suggest that therapeutic peptides exert their beneficial effects through specific receptor-mediated signaling pathways that converge on antioxidant and pro-survival mechanisms, ultimately contributing to the preservation of synaptic plasticity and neuronal function.

Next, to neurotropic factors contributing to neuronal pathways, the pituitary adenylate cyclase-activating polypeptide (PACAP) is a neuropeptide with potential neuroprotective, anti-inflammatory, and antioxidant effects (Lucon-Xiccato et al., 2022). This neuropeptide is a highly conserved molecule, present mainly as PACAP38, its major isoform, and as the amidated isoform PACAP27 (Ghanizada et al., 2019). However, in zebrafish, only PACAP38 demonstrated protecting inner ear hair cells from oxidative stress, mitigating stress-induced apoptosis (Kasica et al., 2016). The distribution of peptides and their receptors in the zebrafish brain strongly suggests their involvement in cognitive and neuroprotective functions (Wu et al., 2006; Nakamachi et al., 2019).

The neuroprotective aspects of PACAP are attributed to its ability to modulate the inflammatory response, reduce oxidative stress, and promote cell survival, and in brain damage models, it can attenuate neuronal death while preserving neural function (Kasica-Jarosz et al., 2018; Cherait et al., 2025). Further neurotrophins, such as Nerve Growth Factor (NGF), are known due to their role in neuronal development and involvement in pain modulation and the inflammatory process (Bathina and Das, 2015). The NGF was the first neurotrophic factor discovered and is fundamental for the survival, differentiation, and maintenance of sensory and sympathetic neurons (Gu et al., 2025). NGF is abundant in the brain, especially in the hippocampus, contributing to neural development and helping to protect cholinergic neurons from degeneration (Xiao and Le, 2016). Therefore, developing humanized zebrafish models, where human genes are expressed in fish, promises to further refine the translational relevance of these studies (Moran et al., 2023). Additionally, understanding the three-dimensional molecular structures of drugs is fundamental to uncovering their mechanisms of action and optimizing therapeutic approaches, particularly when examining the complex interaction between obesity and metabolic and neurological dysfunctions (Lin et al., 2025). Protein-based therapeutics, particularly bioactive peptides, have gained increasing attention because they target conserved signaling pathways involved in obesity-associated synaptic dysfunction (Figure 5).

Figure 5

Among protein-based drugs, some display helical structure, namely Liraglutide, Tirzepatide, and PACAP38. These structural arrangements are often seen in hormone derived glucagon/secretin family, whose conformations adopt a helical structure when interacting with G protein-coupled receptors (Inooka et al., 2001). The prevalence of helixes within these drugs is closely associated with receptor-ligand binding affinity, whereby the C-terminal helix attaches to the extracellular domain of the receptor, allowing activation by the N-terminal (Runge et al., 2008). Meanwhile, BDNF and NGF belong to the neurotrophin family as opposed to helical peptides, which are characterized by their “cystine-knot” folding, featuring antiparallel β-sheets and dimeric structures (Robinson et al., 1999). These structural arrangements are typical for the neurotrophin family and allow for a specific binding surface for Trk receptors, responsible for activating survival and neuronal differentiation pathways (Robinson et al., 1999).

Apart from hormonal peptides, antidiabetic drugs also perform an essential part in regulating metabolic disorders. Metformin, a drug widely used for DM2, for example, has shown neuroprotective properties in animal models of neurodegenerative diseases, targeting various cellular pathways implicated in the progression of these conditions (Sportelli et al., 2020; Reed et al., 2025). Moreover, dipeptidyl peptidase-4 (DPP-4) inhibitors such as Vildagliptin and Sitagliptin have also exhibited neuroprotective effects in DM2 and Parkinson’s models, through mechanisms that are still being extensively investigated (Pariyar et al., 2022; Mani and Arfeen, 2024). Likewise, thiazolidinediones such as Pioglitazone and Rosiglitazone have demonstrated neuroprotective properties in animal models of diseases such as Parkinson’s and Alzheimer’s, resulting in improved behavioral performance and cognitive function (Hu et al., 2024). Furthermore, these findings highlight the potential for repositioning antidiabetic drugs for the treatment of neurological disorders, taking advantage of shared pathophysiological mechanisms such as insulin resistance and cerebral metabolic dysfunction (Cai et al., 2025). Non-protein drugs have also demonstrated promising therapeutic potential in zebrafish models of metabolic disorders (Figure 6).

Figure 6

These non-protein drugs present low-molecular-weight structures with different three-dimensional arrangements. Both Sitagliptin and Vildagliptin are DPP-4 inhibitors, an enzyme responsible for degrading incretins such as GLP-1 and GIP, hormones involved in regulating insulin secretion (Berger et al., 2018). Structurally, DPP-4 inhibitors present nitrogen heteroatoms, thereby constituting amide and nitrile groups, as well as hydrophobic aromatic rings (Lamos et al., 2019). The thiazolidinedione group, represented by Pioglitazone and Rosiglitazone, are characterized by the thiazolidinedione ring, which assists interaction with peroxisome proliferator-activated receptor gamma via hydrogen bonding, as well as a hydrophobic aromatic region that forms a cavity within the receptor, eventually, this process alters the gene expression related to lipid metabolism and insulin sensitivity (Ranjan et al., 2025). Metformin exhibits the simplest arrangement, a highly polar structure, as well as the presence of multiple amine groups (Rena et al., 2017). The simplicity of its structure is directly related to its mechanism of action, as it does not depend on specific binding to a particular receptor; thus, it acts primarily by activating AMP-activated protein kinase, leading to a reduction in hepatic glucose production and an increase in insulin sensitivity (Rena et al., 2017).

8 Translational limitations of zebrafish models

Despite the numerous advantages of the zebrafish model, there are limitations in usage, particularly regarding pharmacokinetics and peptide delivery (Kale et al., 2026). Although there is significant genomic and physiological similarity between zebrafish and humans, certain neuroanatomical differences may be a point of contention. For example, the zebrafish brain, particularly in the larval stage, lacks a laminated cerebral cortex, a structure essential for complex cognitive functions in mammals (Vohra et al., 2024). Furthermore, although zebrafish exhibit obesity induced by a high-fat diet, their short lifespan may differ in the temporal progression (Faillaci et al., 2018), meaning that scaling to a human lifetime is only approximate, not one-to-one. Thus, it is observed that, although the zebrafish serves as a noteworthy platform, research involving synaptic restoration and the efficacy of peptides must be validated through rigorous clinical trials to guarantee translational applicability.

Administration of therapeutic peptides using the water immersion method often results in unpredictable bioavailability, since absorption through the gills and skin differs substantially from mammalian routes of administration, thereby limiting the translational relevance of pharmacokinetic findings (Vyavahare et al., 2026). Consequently, researchers frequently employ parenteral routes, such as intraperitoneal, intravenous, or cerebroventricular administration, particularly in adult zebrafish when precise dosing and improved bioavailability are required. In contrast, larval zebrafish are generally exposed to compounds through water immersion, owing to their suitability for high-throughput screening. However, the use of parenteral administration in adults requires considerable technical expertise and reduces the efficiency of large-scale screening approaches (Kale et al., 2026; Vyavahare et al., 2026). Furthermore, the pharmacokinetics of mammalian peptides in zebrafish remain poorly characterized; differences in BBB permeability, rapid enzymatic degradation by piscine proteases (hydrolases), and altered clearance rates can significantly hinder the translation of effective therapeutic dosages from fish to mammalian systems (Fleming et al., 2013; Gupta et al., 2025). In fact, BBB permeability and the expression of drug transporters can vary among different in vivo model species, potentially leading to different pharmacokinetic responses (Liu et al., 2005).

About the pharmacokinetic constraints, notable divergences exist in metabolism, anatomical structures, and obesity phenotypes between zebrafish and mammals. While zebrafish possess conserved neuroendocrine pathways for appetite regulation, they lack encapsulated adipose depots equivalent to mammalian visceral and subcutaneous fat, storing lipids instead in pancreatic, dermal, and visceral regions without the same architectural complexity (Kulkarni et al., 2017; Zang et al., 2018). Brain anatomy also presents challenges; zebrafish lack a multi-layered neocortex, a region heavily implicated in the cognitive decline associated with metabolic syndrome in humans. This structural divergence complicates the direct translation of synaptic pathology, as the zebrafish telencephalon relies on different organizational principles to process spatial and emotional memory compared to the mammalian hippocampus and cortex (Picolo et al., 2021; Ghaddar and Diotel, 2022).

Finally, evaluating cognitive and behavioral deficits related to obesity-induced synaptic dysfunction in zebrafish carries inherent methodological limitations (Picolo et al., 2021). Although paradigms such as novel object recognition, Y-maze, and inhibitory avoidance tests are widely used to assess learning and memory, they are highly sensitive to confounding factors like altered locomotor activity or visual acuity, both of which can be perturbed by high-fat diets (Meguro et al., 2019; Picolo et al., 2021). Zebrafish behavior is heavily influenced by environmental stressors (e.g., water temperature, pH, and handling), which can increase inter-individual variability and obscure subtle cognitive rescues afforded by peptide interventions. Also, it has been observed that metabolic rates in ectothermic teleosts differ significantly from those of endothermic mammals, primarily because they do not possess brown adipose tissue (Zang et al., 2018), which may influence the presence of obesity-induced neuroinflammation. These constraints underscore the fact that while zebrafish are an exceptional screening tool for uncovering core molecular mechanisms, they must be viewed as a complementary model that requires subsequent validation in mammalian systems (Tao et al., 2022; Li et al., 2025).

9 Conclusion

This review establishes the zebrafish as a unique translational model, whose combination of neuro-metabolic conservation and advanced diagnostic technologies positions it as an ideal platform for elucidating the pathophysiology of obesity-induced synaptic dysfunction. Overall, it represents a balanced experimental system, being more cost-effective than mouse models while retaining greater biological complexity than in vitro approaches. As the field advances toward more complex peptide-based interventions, the zebrafish is increasingly integrated into the drug discovery pipeline, with growing acceptance in the pharmaceutical sector. Thus, its role is no longer a distant prospect but a consolidating reality, supporting the transition from molecular discovery to clinically relevant metabolic neurotherapies.

Statements

Author contributions

AR: Writing – original draft, Writing – review & editing, Conceptualization. AL: Writing – original draft. LiM: Writing – original draft. GC: Writing – original draft. JM: Writing – original draft. DB: Writing – original draft. OF: Writing – review & editing. LuM: Writing – review & editing.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Acknowledgments

The authors would like to thank CAPES, CNPq, and FUNDECT for the support and fellowships that made this research possible.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that Generative AI was not used in the creation of this manuscript.

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References

  • 1

    Abd el-RadyN. M.AhmedA.Abdel-RadyM. M.IsmailO. I. (2021). Glucagon-like peptide-1 analog improves neuronal and behavioral impairment and promotes neuroprotection in a rat model of aluminum-induced dementia. Physiol. Rep.8:e14651. doi: 10.14814/phy2.14651,

  • 2

    AdedaraI. A.MohammedK. A.CanzianJ.AjayiB. O.FarombiE. O.EmanuelliT.et al. (2024). “Chapter five – utility of zebrafish-based models in understanding molecular mechanisms of neurotoxicity mediated by the gut–brain axis,” in Advances in Neurotoxicology, eds. TinkovA. A.AschnerM.CostaL. G. (Cambridge, MA, USA: Academic Press), 177209.

  • 3

    AfridiR.KimJ. H.RahmanM. H.SukK. (2020). Metabolic regulation of glial phenotypes: implications in neuron–glia interactions and neurological disorders. Front. Cell. Neurosci.14:20. doi: 10.3389/fncel.2020.00020,

  • 4

    AgusA.PlanchaisJ.SokolH. (2018). Gut microbiota regulation of tryptophan metabolism in health and disease. Cell Host Microbe23, 716724. doi: 10.1016/j.chom.2018.05.003,

  • 5

    AhmedH.LeyrolleQ.KoistinenV.KärkkäinenO.LayéS.DelzenneN.et al. (2022). Microbiota-derived metabolites as drivers of gut–brain communication. Gut Microbes14:2102878. doi: 10.1080/19490976.2022.2102878,

  • 6

    AhrensM. B.OrgerM. B.RobsonD. N.LiJ. M.KellerP. J. (2013). Whole-brain functional imaging at cellular resolution using light-sheet microscopy. Nat. Methods10, 413420. doi: 10.1038/nmeth.2434

  • 7

    Al JaberiF. M.AlzarzourR.DewaA.MuhamadA.ZakariaF. (2025). Metabolic clues to memory loss: high-fat diets and brain-adipose crosstalk in zebrafish. Behav. Brain Res.486:115559. doi: 10.1016/j.bbr.2025.115559,

  • 8

    AlsegianiA. S.AlshalawiB.AlzahraniS.AlzomanN. Z.AlmomenA. (2025). Obesity-induced cofilin1 pathway dysregulation: possible molecular links between neuroinflammation, cognitive decline, and Alzheimer’s disease biomarkers. IBRO Neurosci. Rep.19, 699708. doi: 10.1016/j.ibneur.2025.10.001,

  • 9

    AnsteyK. J.CherbuinN.BudgeM.YoungJ. (2011). Body mass index in midlife and late-life as a risk factor for dementia: a meta-analysis of prospective studies. Obes. Rev.12, e426e437. doi: 10.1111/j.1467-789X.2010.00825.x,

  • 10

    AntinucciP.HindgesR. (2016). A crystal-clear zebrafish for in vivo imaging. Sci. Rep.6:29490. doi: 10.1038/srep29490,

  • 11

    AthaudaD.FoltynieT. (2016). The glucagon-like peptide 1 (GLP) receptor as a therapeutic target in Parkinson’s disease: mechanisms of action. Drug Discov. Today21, 802818. doi: 10.1016/j.drudis.2016.01.013,

  • 12

    AzbazdarY.PoyrazY. K.OzalpO.NazliD.IpekgilD.CucunG.et al. (2023). High-fat diet feeding triggers a regenerative response in the adult zebrafish brain. Mol. Neurobiol.60, 24862506. doi: 10.1007/s12035-023-03210-4,

  • 13

    Barré-SinoussiF.MontagutelliX. (2015). Animal models are essential to biological research: issues and perspectives. Future Sci. OA1:FSO63. doi: 10.4155/fso.15.63,

  • 14

    BathinaS.DasU. N. (2015). Brain-derived neurotrophic factor and its clinical implications. Arch. Med. Sci.6, 11641178. doi: 10.5114/aoms.2015.56342,

  • 15

    BeardE.LengacherS.DiasS.MagistrettiP. J.FinsterwaldC. (2022). Astrocytes as key regulators of brain energy metabolism: new therapeutic perspectives. Front. Physiol.12:825816. doi: 10.3389/fphys.2021.825816,

  • 16

    BeckerT. S.RinkwitzS. (2012). Zebrafish as a genomics model for human neurological and polygenic disorders. Dev. Neurobiol.72, 415428. doi: 10.1002/dneu.20888,

  • 17

    BeckhauserT. F.Francis-OliveiraJ.De PasqualeR. (2016). Reactive oxygen species: physiological and physiopathological effects on synaptic plasticity. J. Exp. Neurosci.10, 2348. doi: 10.4137/JEN.S39887,

  • 18

    BélangerM.AllamanI.MagistrettiP. J. (2011). Brain energy metabolism: focus on astrocyte-neuron metabolic cooperation. Cell Metab.14, 724738. doi: 10.1016/j.cmet.2011.08.016,

  • 19

    BergerJ. P.SinhaRoyR.PocaiA.KellyT. M.ScapinG.GaoY.-D.et al. (2018). A comparative study of the binding properties, dipeptidyl peptidase-4 (DPP-4) inhibitory activity and glucose-lowering efficacy of the DPP-4 inhibitors alogliptin, linagliptin, saxagliptin, sitagliptin and vildagliptin in mice. Endocrinol. Diabetes Metab.1:e00002. doi: 10.1002/edm2.2,

  • 20

    BernardosR. L.RaymondP. A. (2006). GFAP transgenic zebrafish. Gene Expr. Patterns6, 10071013. doi: 10.1016/j.modgep.2006.04.006,

  • 21

    BertelliP. R.MocelinR.MarconM.SachettA.GomezR.RosaA. R.et al. (2021). Anti-stress effects of the glucagon-like peptide-1 receptor agonist liraglutide in zebrafish. Prog. Neuro-Psychopharmacol. Biol. Psychiatry111:110388. doi: 10.1016/j.pnpbp.2021.110388,

  • 22

    BlankM.GuerimL. D.CordeiroR. F.ViannaM. R. M. (2009). A one-trial inhibitory avoidance task to zebrafish: rapid acquisition of an NMDA-dependent long-term memory. Neurobiol. Learn. Mem.92, 529534. doi: 10.1016/j.nlm.2009.07.001,

  • 23

    BollmannJ. H. (2019). The zebrafish visual system: from circuits to behavior. On: Fri13:52. doi: 10.1146/annurev-vision-091718

  • 24

    BonazB.BazinT.PellissierS. (2018). The vagus nerve at the interface of the microbiota-gut-brain axis. Front. Neurosci.12:49. doi: 10.3389/fnins.2018.00049,

  • 25

    BorbaJ. V.ResmimC. M.FontanaB. D.MoraesH. S.MüllerM. L.BlancoL.et al. (2025). Anxiogenic and anxiolytic modulators differentially affect thigmotaxis and thrashing behavior in adult zebrafish during habituation to the open field test. Behav. Process.228:105199. doi: 10.1016/j.beproc.2025.105199,

  • 26

    BorrelliL.AcetoS.AgnisolaC.De PaoloS.DipinetoL.StillingR. M.et al. (2016). Probiotic modulation of the microbiota-gut-brain axis and behaviour in zebrafish. Sci. Rep.6:30046. doi: 10.1038/srep30046,

  • 27

    BozhkoD. V.MyrovV. O.KolchanovaS. M.PolovianA. I.GalumovG. K.DeminK. A.et al. (2022). Artificial intelligence-driven phenotyping of zebrafish psychoactive drug responses. Prog. Neuro-Psychopharmacol. Biol. Psychiatry112:110405. doi: 10.1016/j.pnpbp.2021.110405,

  • 28

    CaiZ.ZhongJ.ZhuG.ZhangJ. (2025). Comparative efficacy and safety of antidiabetic agents in Alzheimer’s disease: a network meta-analysis of randomized controlled trials. J. Prev Alzheimers Dis.12:100111. doi: 10.1016/j.tjpad.2025.100111,

  • 29

    Campos-BayardoT. I.Román-RojasD.García-SánchezA.Cardona-MuñozE. G.Sánchez-LozanoD. I.Totsuka-SuttoS.et al. (2025). The role of TLRs in obesity and its related metabolic disorders. Int. J. Mol. Sci.26, 22292256. doi: 10.3390/ijms26052229,

  • 30

    CandeiasE.SebastiãoI.CardosoS.CorreiaS.CarvalhoC.PlácidoA.et al. (2015). Gut-brain connection: the neuroprotective effects of the anti-diabetic drug liraglutide. World J. Diabetes6, 807827. doi: 10.4239/wjd.v6.i6.807

  • 31

    CaposselaL.GattoA.FerrettiS.Di SarnoL.GragliaB.MasseseM.et al. (2024). Multifaceted roles of nerve growth factor: a comprehensive review with a special insight into pediatric perspectives. Biology (Basel).13, 546572. doi: 10.3390/biology13070546,

  • 32

    ChamaaF.MagistrettiP. J.FiumelliH. (2024). Astrocyte-derived lactate in stress disorders. Neurobiol. Dis.192:106417. doi: 10.1016/j.nbd.2024.106417,

  • 33

    ChangE. H.ChavanS. S.PavlovV. A. (2019). Cholinergic control of inflammation, metabolic dysfunction, and cognitive impairment in obesity-associated disorders: mechanisms and novel therapeutic opportunities. Front. Neurosci.13:263. doi: 10.3389/fnins.2019.00263,

  • 34

    ChaoulV.DibE. Y.BedranJ.KhouryC.ShmouryO.HarbF.et al. (2023). Assessing drug administration techniques in zebrafish models of neurological disease. Int. J. Mol. Sci.24, 1489814927. doi: 10.3390/ijms241914898,

  • 35

    ChenJ.PoskanzerK. E.FreemanM. R.MonkK. R. (2020). Live-imaging of astrocyte morphogenesis and function in zebrafish neural circuits. Nat. Neurosci.23, 12971306. doi: 10.1038/s41593-020-0703-x,

  • 36

    ChenZ.YuanZ.YangS.ZhuY.XueM.ZhangJ.et al. (2023). Brain energy metabolism: astrocytes in neurodegenerative diseases. CNS Neurosci. Ther.29, 2436. doi: 10.1111/cns.13982,

  • 37

    CheraitA.XifróX.ReglodiD.VaudryD. (2025). More than three decades after discovery of the neuroprotective effect of PACAP, what is still preventing its clinical use?J. Mol. Neurosci.75:80. doi: 10.1007/s12031-025-02366-z,

  • 38

    ChiaK.KlingseisenA.SiegerD.PrillerJ. (2022). Zebrafish as a model organism for neurodegenerative disease. Front. Mol. Neurosci.15:940484. doi: 10.3389/fnmol.2022.940484,

  • 39

    ClealM.FontanaB. D.RansonD. C.McBrideS. D.SwinnyJ. D.RedheadE. S.et al. (2021). The free-movement pattern Y-maze: a cross-species measure of working memory and executive function. Behav. Res. Methods53, 536557. doi: 10.3758/s13428-020-01452-x,

  • 40

    CocchiaroJ. L.RawlsJ. F. (2013). Microgavage of zebrafish larvae. JoVEe4434:e4434. doi: 10.3791/4434,

  • 41

    Cohen-CoryS.KidaneA. H.ShirkeyN. J.MarshakS. (2010). Brain-derived neurotrophic factor and the development of structural neuronal connectivity. Dev. Neurobiol.70, 271288. doi: 10.1002/dneu.20774,

  • 42

    Colucci-D’amatoL.SperanzaL.VolpicelliF. (2020). Neurotrophic factor bdnf, physiological functions and therapeutic potential in depression, neurodegeneration and brain cancer. Int. J. Mol. Sci.21, 129. doi: 10.3390/ijms21207777,

  • 43

    CorcoranS. E.O’NeillL. A. J. (2016). HIF1α and metabolic reprogramming in inflammation. J. Clin. Invest.126, 36993707. doi: 10.1172/JCI84431,

  • 44

    CosacakM. I.BhattaraiP.De JagerP. L.MenonV.TostoG.KizilC. (2022). Single cell/nucleus transcriptomics comparison in zebrafish and humans reveals common and distinct molecular responses to Alzheimer’s disease. Cells11, 18071827. doi: 10.3390/cells11111807,

  • 45

    CosacakM. I.BhattaraiP.ReinhardtS.PetzoldA.DahlA.ZhangY.et al. (2019). Single-cell transcriptomics analyses of neural stem cell heterogeneity and contextual plasticity in a zebrafish brain model of amyloid toxicity. Cell Rep.27, 13071318.e3. doi: 10.1016/j.celrep.2019.03.090,

  • 46

    CrapserJ. D.ArreolaM. A.TsourmasK. I.GreenK. N. (2021). Microglia as hackers of the matrix: sculpting synapses and the extracellular space. Cell. Mol. Immunol.18, 24722488. doi: 10.1038/s41423-021-00751-3,

  • 47

    CrispinoM.TrincheseG.PennaE.CimminoF.CatapanoA.VillanoI.et al. (2020). Interplay between peripheral and central inflammation in obesity-promoted disorders: the impact on synaptic mitochondrial functions. Int. J. Mol. Sci.21, 122. doi: 10.3390/ijms21175964,

  • 48

    CryanJ. F.O’RiordanK. J.CowanC. S. M.SandhuK. V.BastiaanssenT. F. S.BoehmeM.et al. (2019). The microbiota-gut-brain axis. Physiol. Rev.99, 18772013. doi: 10.1152/physrev.00018.2018

  • 49

    CussottoS.SandhuK. V.DinanT. G.CryanJ. F. (2018). The neuroendocrinology of the microbiota-gut-brain Axis: a behavioural perspective. Front. Neuroendocrinol.51, 80101. doi: 10.1016/j.yfrne.2018.04.002,

  • 50

    DavidsonT. L.TracyA. L.SchierL. A.SwithersS. E. (2014). A view of obesity as a learning and memory disorder. J. Exp. Psychol. Anim. Behav. Process.40, 261279. doi: 10.1037/xan0000029,

  • 51

    de BemA. F.KrolowR.FariasH. R.de RezendeV. L.GelainD. P.MoreiraJ. C. F.et al. (2021). Animal models of metabolic disorders in the study of neurodegenerative diseases: an overview. Front. Neurosci.14:604150. doi: 10.3389/fnins.2020.604150,

  • 52

    De FeliceE.PorrecaI.AllevaE.De GirolamoP.AmbrosinoC.CiriacoE.et al. (2014). Localization of BDNF expression in the developing brain of zebrafish. J. Anat.224, 564574. doi: 10.1111/joa.12168,

  • 53

    de MouraL. A.PytersonM. P.PimentelA. F. N.AraújoF.de SouzaL. V. X. B.MendesC. H. M.et al. (2023). Roles of the 5-HT2C receptor on zebrafish sociality. Prog. Neuro-Psychopharmacol. Biol. Psychiatry125:110769. doi: 10.1016/j.pnpbp.2023.110769

  • 54

    de VitoG.TurriniL.MüllenbroichC.RicciP.SancataldoG.MazzamutoG.et al. (2022). Fast whole-brain imaging of seizures in zebrafish larvae by two-photon light-sheet microscopy. Biomed. Opt. Express13, 15161536. doi: 10.1364/BOE.434146

  • 55

    DeczkowskaA.Keren-ShaulH.WeinerA.ColonnaM.SchwartzM.AmitI. (2018). Disease-associated microglia: a universal immune sensor of neurodegeneration. Cell173, 10731081. doi: 10.1016/j.cell.2018.05.003,

  • 56

    Del Rosario HernándezT.GoreS. V.KreilingJ. A.CretonR. (2024). Drug repurposing for neurodegenerative diseases using zebrafish behavioral profiles. Biomed. Pharmacother.171:116096. doi: 10.1016/j.biopha.2023.116096,

  • 57

    Del VecchioG.MurashitaK.VerriT.GomesA. S.RønnestadI. (2021). Leptin receptor-deficient (knockout) zebrafish: effects on nutrient acquisition. Gen. Comp. Endocrinol.310:113832. doi: 10.1016/j.ygcen.2021.113832,

  • 58

    den BroederM. J.MoesterM. J. B.KamstraJ. H.CenijnP. H.DavidoiuV.KammingaL. M.et al. (2017). Altered adipogenesis in zebrafish larvae following high fat diet and chemical exposure is visualised by stimulated raman scattering microscopy. Int. J. Mol. Sci.18, 894915. doi: 10.3390/ijms18040894

  • 59

    DenningerJ. K.WalkerL. A.ChenX.TurkogluA.PanA.TappZ.et al. (2022). Robust transcriptional profiling and identification of differentially expressed genes with low input RNA sequencing of adult hippocampal neural stem and progenitor populations. Front. Mol. Neurosci.15:810722. doi: 10.3389/fnmol.2022.810722,

  • 60

    Domínguez-OlivaA.Hernández-ÁvalosI.Martínez-BurnesJ.Olmos-HernándezA.Verduzco-MendozaA.Mota-RojasD. (2023). The importance of animal models in biomedical research: current insights and applications. Animals13, 12231247. doi: 10.3390/ani13071223,

  • 61

    DorsemansA.-C.SouléS.WegerM.BourdonE.Lefebvre d’HellencourtC.MeilhacO.et al. (2017). Impaired constitutive and regenerative neurogenesis in adult hyperglycemic zebrafish. J. Comp. Neurol.525, 442458. doi: 10.1002/cne.24065

  • 62

    DrieverW.FishmanM. C. (1996). The zebrafish: heritable disorders in transparent embryos. J. Clin. Invest.97, 17881794. doi: 10.1172/JCI118608,

  • 63

    Durán LaforetV.SchaferD. P. (2024). Microglia: activity-dependent regulators of neural circuits. Ann. N. Y. Acad. Sci.1533, 3850. doi: 10.1111/nyas.15105,

  • 64

    FaillaciF.MilosaF.CritelliR. M.TurolaE.SchepisF.VillaE. (2018). Obese zebrafish: a small fish for a major human health condition. Animal Model. Exp. Med.1, 255265. doi: 10.1002/ame2.12042,

  • 65

    FanY.-L.HsuF.-R.WangY.LiaoL.-D. (2023). Unlocking the potential of zebrafish research with artificial intelligence: advancements in tracking, processing, and visualization. Med. Biol. Eng. Comput.61, 27972814. doi: 10.1007/s11517-023-02903-1,

  • 66

    FariaR.VivèsE.BoisguérinP.DescampsS.SousaÂ.CostaD. (2024). Upgrading mitochondria-targeting peptide-based nanocomplexes for zebrafish in vivo compatibility assays. Pharmaceutics16, 961983. doi: 10.3390/pharmaceutics16070961,

  • 67

    FarnsworthD. R.SaundersL. M.MillerA. C. (2020). A single-cell transcriptome atlas for zebrafish development. Dev. Biol.459, 100108. doi: 10.1016/j.ydbio.2019.11.008,

  • 68

    FernándezJ. A. A.de MouraT. C.VilaS. F.GaytánJ. A. R.López-DíazI.Learte-AymamíS.et al. (2025). Effects of two different peptides on pentylenetetrazole-induced seizures in larval zebrafish. PLoS One20:e0308581. Available at:. doi: 10.1371/journal.pone.0308581,

  • 69

    FernandezC. G.HambyM. E.McReynoldsM. L.RayW. J. (2019). The role of apoE4 in disrupting the homeostatic functions of astrocytes and microglia in aging and Alzheimer’s disease. Front. Aging Neurosci.11:14. doi: 10.3389/fnagi.2019.00014,

  • 70

    FiamettiL. O.FrancoC. A.NunesL. O. C.de CastroL. M.Santos-FilhoN. A. (2025). Study of intracellular peptides of the central nervous system of zebrafish (Danio rerio) in a Parkinson’s disease model. Int. J. Mol. Sci.26, 20172029. doi: 10.3390/ijms26052017,

  • 71

    FlemingA.DiekmannH.GoldsmithP. (2013). Functional characterisation of the maturation of the blood-brain barrier in larval zebrafish. PLoS One8:e77548. Available at:. doi: 10.1371/journal.pone.0077548,

  • 72

    FontanaB. D.MezzomoN. J.KalueffA. V.RosembergD. B. (2018). The developing utility of zebrafish models of neurological and neuropsychiatric disorders: a critical review. Exp. Neurol.299, 157171. doi: 10.1016/j.expneurol.2017.10.004,

  • 73

    FowlerL. A.PowersA. D.WilliamsM. B.DavisJ. L.BarryR. J.D’AbramoL. R.et al. (2021). The effects of dietary saturated fat source on weight gain and adiposity are influenced by both sex and total dietary lipid intake in zebrafish. PLoS One16:e0257914. Available at:. doi: 10.1371/journal.pone.0257914,

  • 74

    FriedlandR. P. (2015). Mechanisms of molecular mimicry involving the microbiota in neurodegeneration. J. Alzheimer's Dis45, 349362. doi: 10.3233/JAD-142841,

  • 75

    FrøysetA. K.EdsonA. J.GharbiN.KhanE. A.DondorpD.BaiQ.et al. (2018). Astroglial DJ-1 over-expression up-regulates proteins involved in redox regulation and is neuroprotective in vivo. Redox Biol.16, 237247. doi: 10.1016/j.redox.2018.02.010,

  • 76

    GalstyanD. S.KolesnikovaT. O.KositsynY. M.ZabegalovK. N.GubaidullinaM. A.MaslovG. O.et al. (2022). Studying social behavior in zebrafish (Danio rerioo) in the tests of social interaction, social preference, behavior in the shoaling and aggression tasks. Rev. Clin. Pharmacol. Drug Ther.20, 135147. doi: 10.17816/RCF202135-147

  • 77

    García-DomínguezM. (2026). Glial cell dynamics in neuroinflammation: mechanisms, interactions, and therapeutic implications. Biomedicine14:115. doi: 10.3390/biomedicines14010115,

  • 78

    GemmerA.MirkesK.AnneserL.EilersT.KibatC.MathuruA.et al. (2022). Oxytocin receptors influence the development and maintenance of social behavior in zebrafish (Danio rerio). Sci. Rep.12:4322. doi: 10.1038/s41598-022-07990-y,

  • 79

    GendelevL.TaylorJ.Myers-TurnbullD.ChenS.McCarrollM. N.ArkinM. R.et al. (2024). Deep phenotypic profiling of neuroactive drugs in larval zebrafish. Nat. Commun.15:9955. doi: 10.1038/s41467-024-54375-y,

  • 80

    GerlaiR. (2014). Social behavior of zebrafish: from synthetic images to biological mechanisms of shoaling. J. Neurosci. Methods234, 5965. doi: 10.1016/j.jneumeth.2014.04.028,

  • 81

    GhaddarB.DiotelN. (2022). Zebrafish: a new promise to study the impact of metabolic disorders on the brain. Int. J. Mol. Sci.23, 53725395. doi: 10.3390/ijms23105372,

  • 82

    GhaddarB.LübkeL.CouretD.RastegarS.DiotelN. (2021). Cellular mechanisms participating in brain repair of adultzebrafish and mammals after injury. Cells10, 124. doi: 10.3390/cells10020391,

  • 83

    GhaddarB.VeerenB.RondeauP.BringartM.Lefebvre d’HellencourtC.MeilhacO.et al. (2020). Impaired brain homeostasis and neurogenesis in diet-induced overweight zebrafish: a preventive role from A. borbonica extract. Sci. Rep.10:14496. doi: 10.1038/s41598-020-71402-2,

  • 84

    GhanizadaH.Al-KaragholiM. A.-M.ArngrimN.OlesenJ.AshinaM. (2019). PACAP27 induces migraine-like attacks in migraine patients. Cephalalgia40, 5767. doi: 10.1177/0333102419864507,

  • 85

    GiriS.ChandraP. (2025). Modulation of neuropathological pathways by bioactive peptides and proteins/polypeptides: targeting oxidative stress in neurodegenerative diseases. Neuropeptides114:102563. doi: 10.1016/j.npep.2025.102563,

  • 86

    Godino-GimenoA.ThörnqvistP. O.ChiviteM.MíguezJ. M.WinbergS.Cerdá-ReverterJ. M. (2023). Obesity impairs cognitive function with no effects on anxiety-like behaviour in zebrafish. Int. J. Mol. Sci.24, 231612330. doi: 10.3390/ijms241512316,

  • 87

    GolkarA.RazazpourF.DalfardiM.BaghcheghiY. (2026). Molecular mechanisms underlying obesity-induced memory dysfunction: a comprehensive narrative review. Physiol. Behav.303:115119. doi: 10.1016/j.physbeh.2025.115119,

  • 88

    GomesA. C.HoffmannC.MotaJ. F. (2018). The human gut microbiota: metabolism and perspective in obesity. Gut Microbes9, 118. doi: 10.1080/19490976.2018.1465157,

  • 89

    GrandelH.BrandM. (2013). Comparative aspects of adult neural stem cell activity in vertebrates. Dev. Genes Evol.223, 131147. doi: 10.1007/s00427-012-0425-5,

  • 90

    GriffithsI.KlugmannM.AndersonT.YoolD.ThomsonC.SchwabM. H.et al. (1998). Axonal swellings and degeneration in mice lacking the major proteolipid of myelin. Science280, 16101613. doi: 10.1126/science.280.5369.1610

  • 91

    GriffithsV. A.ValeraA. M.LauJ. Y. N.RošH.YountsT. J.MarinB.et al. (2020). Real-time 3D movement correction for two-photon imaging in behaving animals. Nat. Methods17, 741748. doi: 10.1038/s41592-020-0851-7,

  • 92

    GrimaudB.FrétaudM.TerrasF.BénassyA.DuroureK.BercierV.et al. (2022). In vivo fast nonlinear microscopy reveals impairment of fast axonal transport induced by molecular motor imbalances in the brain of zebrafish larvae. ACS Nano16, 2047020487. doi: 10.1021/acsnano.2c06799,

  • 93

    GuC.-L.ZhangL.ZhuY.BaoT.-Y.ZhuY.-T.ChenY.-T.et al. (2025). Exploring the cellular and molecular basis of nerve growth factor in cerebral ischemia recovery. Neuroscience566, 190197. doi: 10.1016/j.neuroscience.2024.12.049,

  • 94

    GuoY.LuanH.LinJ. (2026). Obesity is the culprit behind fatty acid-induced inflammation. Nutr. Metab. (Lond.)23:35. doi: 10.1186/s12986-026-01076-6

  • 95

    GuptaA.ShawP.SharmaS. N.GuptaS.SinhaS. (2025). Site-specific chemical modulation of a flexible azaproline transporter to enhance epirubicin accumulation in drug-resistant human glioblastoma cells and blood–brain barrier penetration in adult zebrafish. Mol. Pharm.22, 24132430. doi: 10.1021/acs.molpharmaceut.4c01029

  • 96

    HamiltonL.AstellK. R.VelikovaG.SiegerD. (2016). A zebrafish live imaging model reveals differential responses of microglia toward glioblastoma cells in vivo. Zebrafish13, 523534. doi: 10.1089/zeb.2016.1339,

  • 97

    HarveyJ.SolovyovaN.IrvingA. (2006). Leptin and its role in hippocampal synaptic plasticity. Prog. Lipid Res.45, 369378. doi: 10.1016/j.plipres.2006.03.001,

  • 98

    HasanI.TangX.XuJ. (2026). Glial cells in behavioral and psychological symptoms of Alzheimer’s disease. Int. J. Mol. Sci.27, 46214662. doi: 10.3390/ijms27104621,

  • 99

    HasaniH.SunJ.ZhuS. I.RongQ.WillomitzerF.AmorR.et al. (2023). Whole-brain imaging of freely-moving zebrafish. Front. Neurosci.17:1127574. doi: 10.3389/fnins.2023.1127574,

  • 100

    HaydenK. M.ZandiP. P.LyketsosC. G.KhachaturianA. S.BastianL. A.CharoonrukG.et al. (2006). Vascular risk factors for incident Alzheimer disease and vascular dementia: the Cache County study. Alzheimer Dis. Assoc. Disord.20, 93100. doi: 10.1097/01.wad.0000213814.43047.86

  • 101

    HeF.RuX.WenT. (2020). NRF2, a transcription factor for stress response and beyond. Int. J. Mol. Sci.21, 47774723. doi: 10.3390/ijms21134777,

  • 102

    HristovM.CheemaG.AliH.Andreeva-GatevaP. (2025). Beyond glycemic control: the neuroprotective potential of tirzepatide. Pharmacia72, 110. doi: 10.3897/pharmacia.72.e155150

  • 103

    HuL.WangW.ChenX.BaiG.MaL.YangX.et al. (2024). Prospects of antidiabetic drugs in the treatment of neurodegenerative disease. Brain-X2:e52. doi: 10.1002/brx2.52

  • 104

    IbhazehieboK.RhoJ. M.KurraschD. M. (2020). Metabolism-based drug discovery in zebrafish: an emerging strategy to uncover new anti-seizure therapies. Neuropharmacology167:107988. doi: 10.1016/j.neuropharm.2020.107988

  • 105

    InookaH.OhtakiT.KitaharaO.IkegamiT.EndoS.KitadaC.et al. (2001). Conformation of a peptide ligand bound to its G-protein coupled receptor. Nat. Struct. Biol.8, 161165. doi: 10.1038/84159

  • 106

    JeongW.LeeH.ChoS.SeoJ. (2019). ApoE4-induced cholesterol dysregulation and its brain cell type-specific implications in the pathogenesis of Alzheimer’s disease. Mol. Cells42, 739746. doi: 10.14348/molcells.2019.0200,

  • 107

    JohnsonA. L.HurdP. L.MathotK. J.HamiltonT. J. (2025). Behavioural variability and repeatability in adult zebrafish (Danio rerio) using the novel tank dive test. PLoS One20:e0335308. Available at:. doi: 10.1371/journal.pone.0335308,

  • 108

    JohnsonA.LohE.VerbitskyR.SlessorJ.FranczakB. C.SchalomonM.et al. (2023). Examining behavioural test sensitivity and locomotor proxies of anxiety-like behaviour in zebrafish. Sci. Rep.13:3768. doi: 10.1038/s41598-023-29668-9,

  • 109

    JoshiP.LiangJ. O.DiMonteK.SullivanJ.PimplikarS. W. (2009). Amyloid precursor protein is required for convergent-extension movements during zebrafish development. Dev. Biol.335, 111. doi: 10.1016/j.ydbio.2009.07.041,

  • 110

    KaleA.RandhaveN. V.PatilD.WaghB.SetiaA.MalikA. K.et al. (2026). Nanotheranostics in zebrafish cancer models: insights into targeting, biodistribution, and systemic drug delivery. Mol. Pharm.23, 639661. doi: 10.1021/acs.molpharmaceut.5c01185,

  • 111

    KasarelloK.Cudnoch-JedrzejewskaA.CzarzastaK. (2023). Communication of gut microbiota and brain via immune and neuroendocrine signaling. Front. Microbiol.14:1118529. doi: 10.3389/fmicb.2023.1118529,

  • 112

    KasicaN.PodlaszP.SundvikM.TamasA.ReglodiD.KaleczycJ. (2016). Protective effects of pituitary adenylate cyclase-activating polypeptide (PACAP) against oxidative stress in zebrafish hair cells. Neurotox. Res.30, 633647. doi: 10.1007/s12640-016-9659-8,

  • 113

    Kasica-JaroszN.PodlaszP.KaleczycJ. (2018). Pituitary adenylate cyclase–activating polypeptide (PACAP-38) plays an inhibitory role against inflammation induced by chemical damage to zebrafish hair cells. PLoS One13:e0198180. Available at:. doi: 10.1371/journal.pone.0198180,

  • 114

    KimE. K.ChoiE.-J. (2015). Compromised MAPK signaling in human diseases: an update. Arch. Toxicol.89, 867882. doi: 10.1007/s00204-015-1472-2

  • 115

    KimY.-J.NamR.-H.YooY. M.LeeC.-J. (2004). Identification and functional evidence of GABAergic neurons in parts of the brain of adult zebrafish (Danio rerio). Neurosci. Lett.355, 2932. doi: 10.1016/j.neulet.2003.10.024,

  • 116

    KleinertM.ClemmensenC.HofmannS. M.MooreM. C.RennerS.WoodsS. C.et al. (2018). Animal models of obesity and diabetes mellitus. Nat. Rev. Endocrinol.14, 140162. doi: 10.1038/nrendo.2017.161,

  • 117

    KohA.De VadderF.Kovatcheva-DatcharyP.BäckhedF. (2016). From dietary fiber to host physiology: short-chain fatty acids as key bacterial metabolites. Cell165, 13321345. doi: 10.1016/j.cell.2016.05.041,

  • 118

    KojimaM.KangawaK. (2005). Ghrelin: structure and function. Physiol. Rev.85, 495522. doi: 10.1152/physrev.00012.2004

  • 119

    KulkarniP.MedishettiR.NuneN.YellankiS.SripuramV.RaoP.et al. (2017). Correlation of pharmacokinetics and brain penetration data of adult zebrafish with higher mammals including humans. J. Pharmacol. Toxicol. Methods88, 147152. doi: 10.1016/j.vascn.2017.09.258,

  • 120

    LamosE. M.HedringtonM.DavisS. N. (2019). An update on the safety and efficacy of oral antidiabetic drugs: DPP-4 inhibitors and SGLT-2 inhibitors. Expert Opin. Drug Saf.18, 691701. doi: 10.1080/14740338.2019.1626823,

  • 121

    LandgrafK.SchusterS.MeuselA.GartenA.RiemerT.SchleinitzD.et al. (2017). Short-term overfeeding of zebrafish with normal or high-fat diet as a model for the development of metabolically healthy versus unhealthy obesity. BMC Physiol.17:4. doi: 10.1186/s12899-017-0031-x,

  • 122

    LangeS.InalJ. M. (2023). Animal models of human disease. Int. J. Mol. Sci.24, 1582115835. doi: 10.3390/ijms242115821,

  • 123

    LangleyM. R.YoonH.KimH. N.ChoiC.-I.SimonW.KleppeL.et al. (2020). High fat diet consumption results in mitochondrial dysfunction, oxidative stress, and oligodendrocyte loss in the central nervous system. Biochim. Biophys. Acta1866:165630. doi: 10.1016/j.bbadis.2019.165630,

  • 124

    LauF.BinacchiR.BrugnaraS.Cumplido-MayoralA.Di SavinoS.KhanI.et al. (2025). Using single-cell RNA sequencing with Drosophila, zebrafish, and mouse models for studying Alzheimer’s and Parkinson’s disease. Neuroscience573, 505517. doi: 10.1016/j.neuroscience.2025.03.042

  • 125

    LeeY.ChaY. m.YangJ. (2025). Screening and evaluation of therapeutic candidates with vascular protective effects in zebrafish models of diabetic retinopathy. Sci. Rep.15:35946. doi: 10.1038/s41598-025-20272-7,

  • 126

    LeeJ. G.ChoH. J.JeongY. M.LeeJ. S. (2021). Genetic approaches using zebrafish to study the microbiota–gut–brain axis in neurological disorders. Cells10, 566525. doi: 10.3390/cells10030566,

  • 127

    LeeH.LimY. (2025). Can myokines serve as supporters of muscle–brain connectivity in obesity and type 2 diabetes? Potential of exercise and nutrition interventions. Nutrients17, 36153636. doi: 10.3390/nu17223615,

  • 128

    LeungL. C.WangG. X.MourrainP. (2013). Imaging zebrafish neural circuitry from whole brain to synapse. Front. Neural Circuits.76. doi: 10.3389/fncir.2013.00076

  • 129

    LiY.BaderM.TamargoI.RubovitchV.TweedieD.PickC. G.et al. (2015). Liraglutide is neurotrophic and neuroprotective in neuronal cultures and mitigates mild traumatic brain injury in mice. J. Neurochem.135, 12031217. doi: 10.1111/jnc.13169,

  • 130

    LiX.FuC.TanX.FuS. (2025). Responses of zebrafish to chronic environmental stressors: anxiety-like behavior and its persistence. Front. Mar. Sci.12:1551595. doi: 10.3389/fmars.2025.1551595

  • 131

    LieschkeG. J.CurrieP. D. (2007). Animal models of human disease: zebrafish swim into view. Nat. Rev. Genet.8, 353367. doi: 10.1038/nrg2091,

  • 132

    LimaC.GussoD.DisnerG. R.PintoF. J.FalcãoM. A. P.RosaJ. G. S.et al. (2026). The zebrafish in toxicology: a bibliometric analysis reveals current trends and future avenues for predictive safety assessment. Front. Toxicol.7:1700031. doi: 10.3389/ftox.2025.1700031,

  • 133

    LinA.CheC.JiangA.QiC.GlavianoA.ZhaoZ.et al. (2025). Protein spatial structure meets artificial intelligence: revolutionizing drug synergy–antagonism in precision medicine. Adv. Sci.12:e07764. doi: 10.1002/advs.202507764,

  • 134

    LiuR.HongJ.XuX.FengQ.ZhangD.GuY.et al. (2017). Gut microbiome and serum metabolome alterations in obesity and after weight-loss intervention. Nat. Med.23, 859868. doi: 10.1038/nm.4358,

  • 135

    LiuS.LiuJ.WangY.DengF.DengZ. (2025). Oxidative stress: signaling pathways, biological functions, and disease. MedComm (Beijing)6:e70268. doi: 10.1002/mco2.70268,

  • 136

    LiuX.LoringM. D.ZuninoL.FoukeK. E.LongchampF. A.BernardinoA.et al. (2025). Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors. Sci. Robot.10:eadv4408. doi: 10.1126/scirobotics.adv4408,

  • 137

    LiuX.SmithB. J.ChenC.CallegariE.BeckerS. L.ChenX.et al. (2005). Use of a physiologically based pharmacokinetic model to study the time to reach brain equilibrium: an experimental analysis of the role of blood-brain barrier permeability, plasma protein binding, and brain tissue binding. J. Pharmacol. Exp. Ther.313, 12541262. doi: 10.1124/jpet.104.079319,

  • 138

    LiuH.ZhangL.YuJ.ShaoS. (2024). Advances in the application and mechanism of bioactive peptides in the treatment of inflammation. Front. Immunol.15:1413179. doi: 10.3389/fimmu.2024.1413179,

  • 139

    Lopategui CabezasI.Herrera BatistaA.Pentón RolG. (2014). The role of glial cells in Alzheimer disease: potential therapeutic implications. Neurología (English Edition)29, 305309. doi: 10.1016/j.nrleng.2012.10.009,

  • 140

    LuH.LiP.HuangX.WangC. H.LiM.XuZ. Z. (2021). Zebrafish model for human gut microbiome-related studies: advantages and limitations. Medicine in Microecology8:100042. doi: 10.1016/j.medmic.2021.100042

  • 141

    LuciniC.D’angeloL.CacialliP.PalladinoA.de GirolamoP. (2018). BDNF, brain, and regeneration: insights from zebrafish. Int. J. Mol. Sci.19, 31553171. doi: 10.3390/ijms19103155,

  • 142

    Lucon-XiccatoT.MontalbanoG.GattoE.FrigatoE.D’AnielloS.BertolucciC. (2022). Individual differences and knockout in zebrafish reveal similar cognitive effects of BDNF between teleosts and mammals. Proc. R. Soc. B Biol. Sci.289:2036. doi: 10.1098/rspb.2022.2036

  • 143

    LuoL.YanT.YangL.ZhaoM. (2024). Aluminum chloride and D-galactose induced a zebrafish model of Alzheimer’s disease with cognitive deficits and aging. Comput. Struct. Biotechnol. J.23, 22302239. doi: 10.1016/j.csbj.2024.05.036,

  • 144

    LvR.ZhaoY.WangX.HeY.DongN.MinX.et al. (2024). GLP-1 analogue liraglutide attenuates CIH-induced cognitive deficits by inhibiting oxidative stress, neuroinflammation, and apoptosis via the Nrf2/HO-1 and MAPK/NF-κB signaling pathways. Int. Immunopharmacol.142:113222. doi: 10.1016/j.intimp.2024.113222,

  • 145

    LynchS. V.PedersenO. (2016). The human intestinal microbiome in health and disease. N. Engl. J. Med.375, 23692379. doi: 10.1056/nejmra1600266,

  • 146

    LyonsD. A.TalbotW. S. (2015). Glial cell development and function in zebrafish. Cold Spring Harb. Perspect. Biol.7:020526. doi: 10.1101/cshperspect.a020586,

  • 147

    MaR.DistelM.Deán-BenX. L.NtziachristosV.RazanskyD. (2012). Non-invasive whole-body imaging of adult zebrafish with optoacoustic tomography. Phys. Med. Biol.57, 72277237. doi: 10.1088/0031-9155/57/22/7227,

  • 148

    ManiV.ArfeenM. (2024). In vivo and computational studies on sitagliptin’s neuroprotective role in type 2 diabetes mellitus: implications for Alzheimer’s disease. Brain Sci.14, 11911211. doi: 10.3390/brainsci14121191,

  • 149

    Martin-GallausiauxC.MarinelliL.BlottièreH. M.LarraufieP.LapaqueN. (2021). SCFA: mechanisms and functional importance in the gut. Proc. Nutr. Soc.80, 3749. doi: 10.1017/S0029665120006916

  • 150

    MartinsM. L.PinheiroE. F.SaitoG. A.De LimaC. A. C.LeãoL. K. R.BatistaE. d. J. O.et al. (2024). Distinct acute stressors produce different intensity of anxiety-like behavior and differential glutamate release in zebrafish brain. Front. Behav. Neurosci.18:1464992. doi: 10.3389/fnbeh.2024.1464992

  • 151

    MeguroS.HosoiS.HasumuraT. (2019). High-fat diet impairs cognitive function of zebrafish. Sci. Rep.9:17063. doi: 10.1038/s41598-019-53634-z,

  • 152

    MeyerM. P.TrimmerJ. S.GilthorpeJ. D.SmithS. J. (2005). Characterization of zebrafish PSD-95 gene family members. J. Neurobiol.63, 91105. doi: 10.1002/neu.20118,

  • 153

    MichelM.Page-McCawP. S.ChenW.ConeR. D. (2016). Leptin signaling regulates glucose homeostasis, but not adipostasis, in the zebrafish. Proc. Natl. Acad. Sci.113, 30843089. doi: 10.1073/pnas.1513212113,

  • 154

    MiriS.YeoJ. D.AbubakerS.HammamiR. (2023). Neuromicrobiology, an emerging neurometabolic facet of the gut microbiome?Front. Microbiol.14:1098412. doi: 10.3389/fmicb.2023.1098412,

  • 155

    MisraS.RajputP.KaurA. (2025). Tirzepatide mitigates cognitive decline in zebrafish model of type 2 diabetes mellitus induced by high-fat diet. Naunyn Schmiedeberg's Arch. Pharmacol.398, 88618883. doi: 10.1007/s00210-025-03827-3,

  • 156

    MitreM.MarigaA.ChaoM. V. (2016). Neurotrophin signalling: novel insights into mechanisms and pathophysiology. Clin. Sci.131, 1323. doi: 10.1042/CS20160044,

  • 157

    MohantaL.DasB. C.PatriM. (2020). Microbial communities modulating brain functioning and behaviors in zebrafish: a mechanistic approach. Microb. Pathog.145:104251. doi: 10.1016/j.micpath.2020.104251,

  • 158

    MontiG.Gomes MoreiraD.RichnerM.MutsaersH. A. M.FerreiraN.JanA. (2022). GLP-1-receptor agonists in neurodegeneration: neurovascular unit in the spotlight. Cells11, 20232052. doi: 10.3390/cells11132023,

  • 159

    MoranA. L.FehillyJ. D.BlacqueO.KennedyB. N. (2023). Gene therapy for RAB28: what can we learn from zebrafish?Vis. Res.210:108270. doi: 10.1016/j.visres.2023.108270,

  • 160

    MoszakM.SzulińskaM.BogdańskiP. (2020). You are what you eat—the relationship between diet, microbiota, and metabolic disorders— a review. Nutrients12, 10961126. doi: 10.3390/nu12041096,

  • 161

    MuraleedharanR.GawaliM. V.TiwariD.SukumaranA.OatmanN.AndersonJ.et al. (2020). AMPK-regulated astrocytic lactate shuttle plays a non-cell-autonomous role in neuronal survival. Cell Rep.32:108092. doi: 10.1016/j.celrep.2020.108092,

  • 162

    MutoA.KawakamiK. (2016). “Calcium imaging of neuronal activity in free-swimming larval zebrafish,” in Zebrafish: Methods and Protocols, eds. KawakamiK.PattonE. E.OrgerM. (New York, NY: Springer New York), 333341.

  • 163

    NaderiM.JamwalA.FerrariM. C. O.NiyogiS.ChiversD. P. (2016). Dopamine receptors participate in acquisition and consolidation of latent learning of spatial information in zebrafish (Danio rerio). Prog. Neuro-Psychopharmacol. Biol. Psychiatry67, 2130. doi: 10.1016/j.pnpbp.2016.01.002,

  • 164

    NajacM.McLeanD. L.RamanI. M. (2023). Synaptic variance and action potential firing of cerebellar output neurons during motor learning in larval zebrafish. Curr. Biol.33, 32993311.e3. doi: 10.1016/j.cub.2023.06.045,

  • 165

    NakamachiT.TanigawaA.KonnoN.ShiodaS.MatsudaK. (2019). Expression patterns of PACAP and PAC1R genes and anorexigenic action of PACAP1 and PACAP2 in zebrafish. Front. Endocrinol.10:227. doi: 10.3389/fendo.2019.00227,

  • 166

    NauckM. A.QuastD. R.WefersJ.PfeifferA. F. H. (2021). The evolving story of incretins (GIP and GLP-1) in metabolic and cardiovascular disease: a pathophysiological update. Diabetes Obes. Metab.23, 529. doi: 10.1111/dom.14496,

  • 167

    NetoA.FernandesA.BarateiroA. (2023). The complex relationship between obesity and neurodegenerative diseases: an updated review. Front. Cell. Neurosci.17:1294420. doi: 10.3389/fncel.2023.1294420,

  • 168

    NewmanM.EbrahimieE.LardelliM. (2014). Using the zebrafish model for Alzheimer’s disease research. Front. Genet.5:189. doi: 10.3389/fgene.2014.00189,

  • 169

    NewmanM.TuckerB.NornesS.WardA.LardelliM. (2009). Altering presenilin gene activity in zebrafish embryos causes changes in expression of genes with potential involvement in Alzheimer’s disease pathogenesis. J. Alzheimer's Dis16, 133147. doi: 10.3233/JAD-2009-0945,

  • 170

    NowellJ.BluntE.GuptaD.EdisonP. (2023). Antidiabetic agents as a novel treatment for Alzheimer’s and Parkinson’s disease. Ageing Res. Rev.89:101979. doi: 10.1016/j.arr.2023.101979,

  • 171

    NumakawaT.KajiharaR. (2025). The role of brain-derived neurotrophic factor as an essential mediator in neuronal functions and the therapeutic potential of its mimetics for neuroprotection in neurologic and psychiatric disorders. Molecules30, 848872. doi: 10.3390/molecules30040848,

  • 172

    O’MahonyS. M.ClarkeG.BorreY. E.DinanT. G.CryanJ. F. (2015). Serotonin, tryptophan metabolism and the brain-gut-microbiome axis. Behav. Brain Res.277, 3248. doi: 10.1016/j.bbr.2014.07.027,

  • 173

    OchenkowskaK.HeroldA.SamarutÉ. (2022). Zebrafish is a powerful tool for precision medicine approaches to neurological disorders. Front. Mol. Neurosci.15:944693. doi: 10.3389/fnmol.2022.944693,

  • 174

    OkaT.NishimuraY.ZangL.HiranoM.ShimadaY.WangZ.et al. (2010). Diet-induced obesity in zebrafish shares common pathophysiological pathways with mammalian obesity. BMC Physiol.10:21. doi: 10.1186/1472-6793-10-21,

  • 175

    OsadchiyV.MartinC. R.MayerE. A. (2019). The Gut–Brain Axis and the Microbiome: Mechanisms and Clinical Implications. Clin. Gastroenterol. Hepatol.17, 322332. doi:10.1016/j.cgh.2018.10.002, The gut-brain Axis and the microbiome: mechanisms and clinical implications,

  • 176

    PandeyS.MoyerA. J.ThymeS. B. (2023). A single-cell transcriptome atlas of the maturing zebrafish telencephalon. Genome Res.33, 658671. doi: 10.1101/gr.277278.122,

  • 177

    PariyarR.BastolaT.LeeD. H.SeoJ. (2022). Neuroprotective effects of the DPP4 inhibitor vildagliptin in in vivo and in vitro models of Parkinson’s disease. Int. J. Mol. Sci.23, 23882407. doi: 10.3390/ijms23042388,

  • 178

    PerathonerS.Cordero-MaldonadoM. L.CrawfordA. D. (2016). Potential of zebrafish as a model for exploring the role of the amygdala in emotional memory and motivational behavior. J. Neurosci. Res.94, 445462. doi: 10.1002/jnr.23712,

  • 179

    PereiraJ. A. da S.SilvaF. C.dade Moraes-VieiraP. M. M. (2017). The impact of ghrelin in metabolic diseases: an immune perspective. J. Diabetes Res. 2017,:4527980. doi: 10.1155/2017/4527980

  • 180

    PhamM.RaymondJ.HesterJ.KyzarE.GaikwadS.BruceI.et al. (2012). “Assessing social behavior phenotypes in adult zebrafish: shoaling, social preference, and Mirror biting tests,” in Zebrafish Protocols for Neurobehavioral Research, eds. KalueffA. V.StewartA. M. (Totowa, NJ: Humana Press), 231246.

  • 181

    PhillipsJ. B.WesterfieldM. (2014). Zebrafish models in translational research: tipping the scales toward advancements in human health. Dis. Model. Mech.7, 739743. doi: 10.1242/dmm.015545,

  • 182

    PichéM. E.TchernofA.DesprésJ. P. (2020). Obesity phenotypes, diabetes, and cardiovascular diseases. Circ. Res.126, 14771500. doi: 10.1161/CIRCRESAHA.120.316101,

  • 183

    PicoloV. L.QuadrosV. A.CanzianJ.GrisoliaC. K.GoulartJ. T.PantojaC.et al. (2021). Short-term high-fat diet induces cognitive decline, aggression, and anxiety-like behavior in adult zebrafish. Prog. Neuro-Psychopharmacol. Biol. Psychiatry110:110288. doi: 10.1016/j.pnpbp.2021.110288

  • 184

    PortuguesR.SeveriK. E.WyartC.AhrensM. B. (2013). Optogenetics in a transparent animal: circuit function in the larval zebrafish. Curr. Opin. Neurobiol.23, 119126. doi: 10.1016/j.conb.2012.11.001,

  • 185

    PostlethwaitJ. H.WoodsI. G.Ngo-HazelettP.YanY. L.KellyP. D.ChuF.et al. (2000). Zebrafish comparative genomics and the origins of vertebrate chromosomes. Genome Res.10, 18901902. doi: 10.1101/gr.164800,

  • 186

    PoundP.EbrahimS.SandercockP.BrackenM. B.RobertsI. (2004). Where is the evidence that animal research benefits humans?BMJ328, 514517. doi: 10.1136/bmj.328.7438.514,

  • 187

    ProcacciniC.SantopaoloM.FaicchiaD.ColamatteoA.FormisanoL.de CandiaP.et al. (2016). Role of metabolism in neurodegenerative disorders. Metabolism65, 13761390. doi: 10.1016/j.metabol.2016.05.018,

  • 188

    RalstonJ. C.LyonsC. L.KennedyE. B.KirwanA. M.RocheH. M. (2017). Annual review of nutrition fatty acids and NLRP3 inflammasome-mediated inflammation in metabolic tissues. Annu. Rev. Nutr.25:42. doi: 10.1146/annurev-nutr-071816

  • 189

    RanjanG.RanjanS.SunitaP.PattanayakS. P. (2025). Thiazolidinedione derivatives in cancer therapy: exploring novel mechanisms, therapeutic potentials, and future horizons in oncology. Naunyn Schmiedeberg's Arch. Pharmacol.398, 47054725. doi: 10.1007/s00210-024-03661-z,

  • 190

    ReaV.BellI.BallT.Van RaayT. (2022). Gut-derived metabolites influence neurodevelopmental gene expression and Wnt signaling events in a germ-free zebrafish model. Microbiome10:132. doi: 10.1186/s40168-022-01302-2,

  • 191

    ReedS.TakaE.Darling-ReedS.SolimanK. F. A. (2025). Neuroprotective effects of metformin through the modulation of neuroinflammation and oxidative stress. Cells14, 10641103. doi: 10.3390/cells14141064,

  • 192

    RenaG.HardieD. G.PearsonE. R. (2017). The mechanisms of action of metformin. Diabetologia60, 15771585. doi: 10.1007/s00125-017-4342-z,

  • 193

    RobinsonR. C.RadziejewskiC.SpraggonG.GreenwaldJ.KosturaM. R.BurtnickL. D.et al. (1999). The structures of the neurotrophin 4 homodimer and the brain-derived neurotrophic factor/neurotrophin 4 heterodimer reveal a common Trk-binding site. Protein Sci.8, 25892597. doi: 10.1110/ps.8.12.2589,

  • 194

    RungeS.ThøgersenH.MadsenK.LauJ.RudolphR. (2008). Crystal structure of the ligand-bound glucagon-like Peptide-1 receptor extracellular domain*. J. Biol. Chem.283, 1134011347. doi: 10.1074/jbc.M708740200,

  • 195

    RussoC.ValleM. S.RussoA.MalaguarneraL. (2022). The interplay between ghrelin and microglia in neuroinflammation: implications for obesity and neurodegenerative diseases. Int. J. Mol. Sci.23, 1343213452. doi: 10.3390/ijms232113432,

  • 196

    SadeghdoustM.DasA.KaushikD. K. (2024). Fueling neurodegeneration: metabolic insights into microglia functions. J. Neuroinflammation21:300. doi: 10.1186/s12974-024-03296-0,

  • 197

    SaherG.BrüggerB.Lappe-SiefkeC.MöbiusW.TozawaR.WehrM. C.et al. (2005). High cholesterol level is essential for myelin membrane growth. Nat. Neurosci.8, 468475. doi: 10.1038/nn1426,

  • 198

    Salas-VenegasV.Flores-TorresR. P.Rodríguez-CortésY. M.Rodríguez-RetanaD.Ramírez-CarretoR. J.Concepción-CarrilloL. E.et al. (2022). The obese brain: mechanisms of systemic and local inflammation, and interventions to reverse the cognitive deficit. Front. Integr. Neurosci.16:798995. doi: 10.3389/fnint.2022.798995,

  • 199

    SampsonT. R.DebeliusJ. W.ThronT.JanssenS.ShastriG. G.IlhanZ. E.et al. (2016). Gut microbiota regulate motor deficits and neuroinflammation in a model of Parkinson’s disease. Cell167, 14691480.e12. doi: 10.1016/j.cell.2016.11.018

  • 200

    SantoroM. M. (2014). Zebrafish as a model to explore cell metabolism. Trends Endocrinol. Metab.25, 546554. doi: 10.1016/j.tem.2014.06.003,

  • 201

    SchwerteT.ÜberbacherD.PelsterB. (2003). Non-invasive imaging of blood cell concentration and blood distribution in zebrafish Danio rerio incubated in hypoxic conditions in vivo. J. Exp. Biol.206, 12991307. doi: 10.1242/jeb.00249,

  • 202

    SethA.StempleD. L.BarrosoI. (2013). The emerging use of zebrafish to model metabolic disease. Dis. Model. Mech.6, 10801088. doi: 10.1242/dmm.011346,

  • 203

    ShangY.HuX.RenM.MaL.ZhaoX.GaoC.et al. (2025). Understanding the toxicity induced by radiation-triggered neuroinflammation and the on-demand design of targeted peptide nanodrugs. Signal Transduct. Target. Ther.10:286. doi: 10.1038/s41392-025-02375-9,

  • 204

    ShenB.WeiH.WenY.GengY.YangT.ChenZ.et al. (2025). Optimized in vivo two-photon imaging reveals the essential role of the contralateral eye in functional optic nerve regeneration in zebrafish larvae. Eye Vision12:34. doi: 10.1186/s40662-025-00447-z,

  • 205

    ShullA. Y.HuC.-A. A.TengY. (2017). Zebrafish as a model to evaluate peptide-related cancer therapies. Amino Acids49, 19071913. doi: 10.1007/s00726-017-2388-3

  • 206

    SimmichJ.StaykovE.ScottE. (2012). “Chapter 8 – zebrafish as an appealing model for optogenetic studies,” in Progress in Brain Research, eds. KnöpfelT.BoydenE. S. (Amsterdam, NLD: Elsevier), 145162.

  • 207

    SinghK.GuptaJ. K.KumarS.SoniU. (2024). A review of the common neurodegenerative disorders: current therapeutic approaches and the potential role of bioactive peptides. Curr. Protein Pept. Sci.25, 507526. doi: 10.2174/0113892037275221240327042353,

  • 208

    SmithD. L.BarryR. J.PowellM. L.NagyT. R.D’AbramoL. R.WattsS. A. (2013). Dietary protein source influence on body size and composition in growing zebrafish. Zebrafish10, 439446. doi: 10.1089/zeb.2012.0864

  • 209

    SmithK.McCoyK. D.MacphersonA. J. (2007). Use of axenic animals in studying the adaptation of mammals to their commensal intestinal microbiota. Semin. Immunol.19, 5969. doi: 10.1016/j.smim.2006.10.002,

  • 210

    SocałaK.DoboszewskaU.SzopaA.SerefkoA.WłodarczykM.ZielińskaA.et al. (2021). The role of microbiota-gut-brain axis in neuropsychiatric and neurological disorders. Pharmacol. Res.172:105840. doi: 10.1016/j.phrs.2021.105840,

  • 211

    SportelliC.UrsoD.JennerP.ChaudhuriK. R. (2020). Metformin as a potential neuroprotective agent in prodromal Parkinson’s disease—viewpoint. Front. Neurol.11:556. doi: 10.3389/fneur.2020.00556,

  • 212

    StagamanK.AlexievA.SielerM. J.HammerA.KasschauK. D.TruongL.et al. (2024). The zebrafish gut microbiome influences benzo[a]pyrene developmental neurobehavioral toxicity. Sci. Rep.14:14618. doi: 10.1038/s41598-024-65610-3,

  • 213

    StathoriG.VlahosN. F.CharmandariE.ValsamakisG. (2025). Obesity- and high-fat-diet-induced neuroinflammation: implications for autonomic nervous system dysfunction and endothelial disorders. Int. J. Mol. Sci.26, 40474060. doi: 10.3390/ijms26094047,

  • 214

    SunY.WangY.ChenS. T.ChenY. J.ShenJ.YaoW. B.et al. (2020). Modulation of the astrocyte-neuron lactate shuttle system contributes to neuroprotective action of fibroblast growth factor 21. Theranostics10, 84308445. doi: 10.7150/thno.44370,

  • 215

    SurA.WangY.CaparP.MargolinG.ProchaskaM. K.FarrellJ. A. (2023). Single-cell analysis of shared signatures and transcriptional diversity during zebrafish development. Dev. Cell58, 30283047.e12. doi: 10.1016/j.devcel.2023.11.001,

  • 216

    SuzukiR.LeeK.JingE.BiddingerS. B.McDonaldJ. G.MontineT. J.et al. (2010). Diabetes and insulin in regulation of brain cholesterol metabolism. Cell Metab.12, 567579. doi: 10.1016/j.cmet.2010.11.006,

  • 217

    SzablewskiL. (2025). Associations between diabetes mellitus and neurodegenerative diseases. Int. J. Mol. Sci.26, 542592. doi: 10.3390/ijms26020542,

  • 218

    TaoY.LiZ.YangY.JiaoY.QuJ.WangY.et al. (2022). Effects of common environmental endocrine-disrupting chemicals on zebrafish behavior. Water Res.208:117826. doi: 10.1016/j.watres.2021.117826,

  • 219

    TeixeiraC. M. M.CorreaC. N.IwaiL. K.FerroE. S., and Castro, L. M. de (2019). Characterization of intracellular peptides from zebrafish (Danio rerio) brain. Zebrafish16, 240251. doi:10.1089/zeb.2018.1718,

  • 220

    TengS.-W.ChenX.-L.ChenZ.-Y. (2026). Molecular architects of memory: BDNF/TrkB signaling and trafficking in neuronal plasticity and memory. Mol. Psychiatry31, 43864401. doi: 10.1038/s41380-026-03552-0,

  • 221

    TononF.GrassiG. (2023). Zebrafish as an experimental model for human disease. Int. J. Mol. Sci.24, 87718777. doi: 10.3390/ijms24108771,

  • 222

    TremmelM.GerdthamU. G.NilssonP. M.SahaS. (2017). Economic burden of obesity: a systematic literature review. Int. J. Environ. Res. Public Health14, 435452. doi: 10.3390/ijerph14040435,

  • 223

    TurriniL.RicciP.SorelliM.de VitoG.MarchettiM.VanziF.et al. (2024). Two-photon all-optical neurophysiology for the dissection of larval zebrafish brain functional and effective connectivity. Commun. Biol.7:1261. doi: 10.1038/s42003-024-06731-3,

  • 224

    TurriniL.RoschiL.de VitoG.PavoneF. S.VanziF. (2023). Imaging approaches to investigate pathophysiological mechanisms of brain disease in zebrafish. Int. J. Mol. Sci.24, 98339856. doi: 10.3390/ijms24129833,

  • 225

    UrkonM.FerenczE.SzászJ. A.SzaboM. I. M.Orbán-KisK.SzatmáriS.et al. (2025). Antidiabetic GLP-1 receptor agonists have neuroprotective properties in experimental animal models of Alzheimer’s disease. Pharmaceuticals18, 614650. doi: 10.3390/ph18050614,

  • 226

    Valcarcel-AresM. N.TucsekZ.KissT.GilesC. B.TarantiniS.YabluchanskiyA.et al. (2019). Obesity in aging exacerbates neuroinflammation, dysregulating synaptic function-related genes and altering eicosanoid synthesis in the mouse hippocampus: potential role in impaired synaptic plasticity and cognitive decline. J. Gerontol. Ser. A74, 290298. doi: 10.1093/gerona/gly127,

  • 227

    ValenzaM.MarulloM.Di PaoloE.CesanaE.ZuccatoC.BiellaG.et al. (2015). Disruption of astrocyte-neuron cholesterol cross talk affects neuronal function in Huntington’s disease. Cell Death Differ.22, 690702. doi: 10.1038/cdd.2014.162,

  • 228

    VizueteA. F. K.FróesF.SeadyM.CaurioA. C.Ramires JuniorO. V.LeiteA. K. O.et al. (2024). Targeting glycolysis for neuroprotection in early LPS-induced neuroinflammation. Brain Behav. Immun. Health42:100901. doi: 10.1016/j.bbih.2024.100901,

  • 229

    VogtN. M.KerbyR. L.Dill-McFarlandK. A.HardingS. J.MerluzziA. P.JohnsonS. C.et al. (2017). Gut microbiome alterations in Alzheimer’s disease. Sci. Rep.7:13537. doi: 10.1038/s41598-017-13601-y,

  • 230

    VohraS.HerreraK.Tavhelidse-SuckT.WittbrodtJ.KnoblichS.SeleitA.et al. (2024). Multi-species community platform for comparative neuroscience in teleost fish. BioRxiv. doi: 10.1101/2024.02.14.580400

  • 231

    VukovićM.NosekI.Medić StojanoskaM.KozićD. (2026). Neurometabolic and neuroinflammatory consequences of obesity: insights into brain vulnerability and imaging-based biomarkers. Int. J. Mol. Sci.27:958. doi: 10.3390/ijms27020958,

  • 232

    VyavahareS.PawarA.SayyedS. A.ShegarN.RaykarS.DokeR.et al. (2026). Zebrafish as a versatile screening model for neurological diseases: insights into biology, drug delivery and therapeutic discovery. J. Biochem. Mol. Toxicol.40:e70750. doi: 10.1002/jbt.70750,

  • 233

    WakeH.MoorhouseA. J.NabekuraJ. (2011). Functions of microglia in the central nervous system – beyond the immune response. Neuron Glia Biol.7, 4753. doi: 10.1017/S1740925X12000063

  • 234

    WangW.GaoX.LiuL.GuoS.DuanJ.XiaoP. (2025). Zebrafish as a vertebrate model for high-throughput drug toxicity screening: mechanisms, novel techniques, and future perspectives. J. Pharm. Anal.15:101195. doi: 10.1016/j.jpha.2025.101195,

  • 235

    WangY.SongJ.WangX.QianQ.WangH. (2022). Study on the toxic-mechanism of triclosan chronic exposure to zebrafish (Danio rerio) based on gut-brain axis. Sci. Total Environ.844:156936. doi: 10.1016/j.scitotenv.2022.156936,

  • 236

    WangQ.YangQ.LiuX. (2023). The microbiota–gut–brain axis and neurodevelopmental disorders. Protein Cell14, 762775. doi: 10.1093/procel/pwad026,

  • 237

    WannerA. A.VishwanathanA. (2018). Methods for mapping neuronal activity to synaptic connectivity: lessons from larval zebrafish. Front. Neural Circuits12:89. doi: 10.3389/fncir.2018.00089,

  • 238

    WarR. V. S.PaulS.SharmaU. R.PmM. (2022). Zebrafish as an emerging alternative tool for studying anxiety disorders. J. Adv. Sci. Res.13, 1320. doi: 10.55218/jasr.2022131103

  • 239

    WeissG. A.HennetT. (2017). Mechanisms and consequences of intestinal dysbiosis. Cell. Mol. Life Sci.74, 29592977. doi: 10.1007/s00018-017-2509-x,

  • 240

    WellenK. E.HotamisligilG. S. (2005). Inflammation, stress, and diabetes. J. Clin. Invest.115, 11111119. doi: 10.1172/jci25102,

  • 241

    WeydertC. J.CullenJ. J. (2010). Measurement of superoxide dismutase, catalase and glutathione peroxidase in cultured cells and tissue. Nat. Protoc.5, 5166. doi: 10.1038/nprot.2009.197,

  • 242

    WuS.AdamsB. A.FradingerE. A.SherwoodN. M. (2006). Role of two genes encoding PACAP in early brain development in zebrafish. Ann. N. Y. Acad. Sci.1070, 602621. doi: 10.1196/annals.1317.091

  • 243

    WuQ.TianJ.GuY.BiX.ZhangH. (2026). Metabolic reprogramming of microglia in neuroinflammation and depression. Int. J. Mol. Sci.27, 3984015. doi: 10.3390/ijms27093984,

  • 244

    WuY.ZhaoL.ZhangX.LiuR.GaoD.SuJ.et al. (2025). Mechanism of biphasic activation of NLRP3 inflammasome in the fat greenling (Hexagrammos otakii) under hypoxic stress: from inflammatory defense to pyroptosis execution. Fishes10, 542562. doi: 10.3390/fishes10110542

  • 245

    XiaH.ChenH.ChengX.YinM.YaoX.MaJ.et al. (2022). Zebrafish: an efficient vertebrate model for understanding role of gut microbiota. Mol. Med.28:161. doi: 10.1186/s10020-022-00579-1,

  • 246

    XiaoN.LeQ.-T. (2016). Neurotrophic factors and their potential applications in tissue regeneration. Arch. Immunol. Ther. Exp.64, 8999. doi: 10.1007/s00005-015-0376-4,

  • 247

    YanF.HaoZ.ZengJ.LiuY.DaiQ.ZhuY.et al. (2024). Identification of a neuropeptide in suppressing food intake in zebrafish. Biochem. Biophys. Res. Commun.734:150752. doi: 10.1016/j.bbrc.2024.150752,

  • 248

    YangX.ChenY.-H.LiuL.GuZ.YouY.HaoJ.-R.et al. (2024). Regulation of glycolysis-derived L-lactate production in astrocytes rescues the memory deficits and aβ burden in early Alzheimer’s disease models. Pharmacol. Res.208:107357. doi: 10.1016/j.phrs.2024.107357,

  • 249

    YangJ.ShimadaY.OlsthoornR. C. L.Snaar-JagalskaB. E.SpainkH. P.KrosA. (2016). Application of coiled coil peptides in liposomal anticancer drug delivery using a zebrafish xenograft model. ACS Nano10, 74287435. doi: 10.1021/acsnano.6b01410,

  • 250

    YangP.TakahashiH.MuraseM.ItohM. (2021). Zebrafish behavior feature recognition using three-dimensional tracking and machine learning. Sci. Rep.11:13492. doi: 10.1038/s41598-021-92854-0,

  • 251

    YashaswiniC.KiranN. S.ChatterjeeA. (2025). Zebrafish navigating the metabolic maze: insights into human disease – assets, challenges and future implications. J. Diabetes Metab. Disord.24:3. doi: 10.1007/s40200-024-01539-8,

  • 252

    YashinaK.Tejero-CanteroÁ.HerzA.BaierH. (2019). Zebrafish exploit visual cues and geometric relationships to form a spatial memory. iScience19, 119134. doi: 10.1016/j.isci.2019.07.013,

  • 253

    ZangL.MaddisonL. A.ChenW. (2018). Zebrafish as a model for obesity and diabetes. Front. Cell Dev. Biol.6:91. doi: 10.3389/fcell.2018.00091,

  • 254

    ZhangH.ChenY.WangZ.XieG.LiuM.YuanB.et al. (2022). Implications of gut microbiota in neurodegenerative diseases. Front. Immunol.13:785644. doi: 10.3389/fimmu.2022.785644,

  • 255

    ZhangQ.LiT.XuM.IslamB.WangJ. (2024). Application of optogenetics in neurodegenerative diseases. Cell. Mol. Neurobiol.44:57. doi: 10.1007/s10571-024-01486-1,

  • 256

    ZhongX.LiJ.LuF.ZhangJ.GuoL. (2022). Application of zebrafish in the study of the gut microbiome. Animal Model. Exp. Med.5, 323336. doi: 10.1002/ame2.12227,

  • 257

    ZhouW.LuS.SuY.XueD.YuX.WangS.et al. (2014). Decreasing oxidative stress and neuroinflammation with a multifunctional peptide rescues memory deficits in mice with Alzheimer disease. Free Radic. Biol. Med.74, 5063. doi: 10.1016/j.freeradbiomed.2014.06.013,

  • 258

    ZhuP.NaritaY.BundschuhS. T.FajardoO.SchärerY. P. Z.ChattopadhyayaB.et al. (2009). Optogenetic dissection of neuronal circuits in zebrafish using viral gene transfer and the tet system. Front. Neural Circuits3:21. doi: 10.3389/neuro.04.021.2009,

  • 259

    ZupancG. K. H.HinschK.GageF. H. (2005). Proliferation, migration, neuronal differentiation, and long-term survival of new cells in the adult zebrafish brain. J. Comp. Neurol.488, 290319. doi: 10.1002/cne.20571,

Summary

Keywords

gut–brain axis, metabolic syndrome, neuroinflammation, obesity, synaptic plasticity, therapeutic peptides, zebrafish

Citation

Rodrigues AC, Lacerda AP, Mukoyama LTH, de Carvalho GB, da Mata JAL, Buccini DF, Franco OL and Migliolo L (2026) Zebrafish as a translational model for peptide-mediated synaptic dysfunction related to obesity. Front. Synaptic Neurosci. 18:1845252. doi: 10.3389/fnsyn.2026.1845252

Received

01 April 2026

Revised

01 July 2026

Accepted

20 July 2026

Published

10 August 2026

Volume

18 - 2026

Edited by

Mayank Gautam, University of Pennsylvania, United States

Reviewed by

Jihane Soueid, American University of Beirut, Lebanon

Anamica Chauhan, Shoolini University, India

Updates

Copyright

*Correspondence: Ludovico Migliolo,

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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