Next generation behavioral sequencing for advancing pain quantification

A Systematic Review and Meta-Analysis of Anxiety- and Depressive-Like Behaviors in Rodent Models of Neuropathic Pain

Background

Epidemiological studies have frequently shown the concurrence of chronic pain with symptoms of anxiety and depression, particularly in women. Animal models are useful to understand the complex mechanisms underlying comorbidities, but the wide range of methods employed and the wealth of evidence sometimes impedes effective translation and reproducibility. In this systematic review and meta-analysis, we aimed to synthesize the evidence regarding the influence of variables such as sex and species on anxiety- and depressive-like behaviors in rodent models of neuropathic pain.

Methods

Following PROSPERO registration, we searched EMBASE, Scopus, and the Web of Science from their inception to November 24, 2023, identifying 126 studies that met the inclusion criteria. The Hedges' g value for each experiment and study was calculated, and further subgroup and meta-regression analyses were performed.

Results

Neuropathic pain significantly reduced the time that rats and mice spent in the open arms of the elevated plus and zero mazes (g = -1.14), time spent in the center of the open field (g = -1.12), sucrose consumption in the sucrose preference test (g = -1.43), and grooming time in the splash test (g = -1.37) while increasing latency to feed in the novelty-suppressed feeding test (g = 1.59) and immobility in the forced swimming (g = 1.85) and tail suspension (g = 1.91) tests. Sex differences were observed, with weaker effects in female than in male rodents for several behavioral paradigms, and funnel plots identified positive publication bias in the literature.

Conclusions

This meta-analysis emphasizes the effect of neuropathic pain on anxiety- and depressive-like behaviors in rodents, highlighting the importance of investigating sex differences in future experimental studies.

Deep sequencing of Phox2a nuclei reveals five classes of anterolateral system neurons

The anterolateral system (ALS) is a major ascending pathway from the spinal cord that projects to multiple brain areas and underlies the perception of pain, itch, and skin temperature. Despite its importance, our understanding of this system has been hampered by the considerable functional and molecular diversity of its constituent cells. Here, we use fluorescence-activated cell sorting to isolate ALS neurons belonging to the Phox2a-lineage for single-nucleus RNA sequencing. We reveal five distinct clusters of ALS neurons (ALS1-5) and document their laminar distribution in the spinal cord using in situ hybridization. We identify three clusters of neurons located predominantly in laminae I-III of the dorsal horn (ALS1-3) and two clusters with cell bodies located in deeper laminae (ALS4 and ALS5). Our findings reveal the transcriptional logic that underlies ALS neuronal diversity in the adult mouse and uncover the molecular identity of two previously identified classes of projection neurons. We also show that these molecular signatures can be used to target groups of ALS neurons using retrograde viral tracing. Overall, our findings provide a valuable resource for studying somatosensory biology and targeting subclasses of ALS neurons.

Finding new analgesics: Computational pharmacology faces drug discovery challenges

Despite the worldwide prevalence and huge burden of pain, pain is an undertreated phenomenon. Currently used analgesics have several limitations regarding their efficacy and safety. The discovery of analgesics possessing a novel mechanism of action has faced multiple challenges, including a limited understanding of biological processes underpinning pain and analgesia and poor animal-to-human translation. Computational pharmacology is currently employed to face these challenges. In this review, we discuss the theory, methods, and applications of computational pharmacology in pain research. Computational pharmacology encompasses a wide variety of theoretical concepts and practical methodological approaches, with the overall aim of gaining biological insight through data acquisition and analysis. Data are acquired from patients or animal models with pain or analgesic treatment, at different levels of biological organization (molecular, cellular, physiological, and behavioral). Distinct methodological algorithms can then be used to analyze and integrate data. This helps to facilitate the identification of biological molecules and processes associated with pain phenotype, build quantitative models of pain signaling, and extract translatable features between humans and animals. However, computational pharmacology has several limitations, and its predictions can provide false positive and negative findings. Therefore, computational predictions are required to be validated experimentally before drawing solid conclusions. In this review, we discuss several case study examples of combining and integrating computational tools with experimental pain research tools to meet drug discovery challenges.

A parabrachial hub for the prioritization of survival behavior

Long-term sustained pain in the absence of acute physical injury is a prominent feature of chronic pain conditions. While neurons responding to noxious stimuli have been identified, understanding the signals that persist without ongoing painful stimuli remains a challenge. Using an ethological approach based on the prioritization of adaptive survival behaviors, we determined that neuropeptide Y (NPY) signaling from multiple sources converges on parabrachial neurons expressing the NPY Y1 receptor to reduce sustained pain responses. Neural activity recordings and computational modeling demonstrate that activity in Y1R parabrachial neurons is elevated following injury, predicts functional coping behavior, and is inhibited by competing survival needs. Taken together, our findings suggest that parabrachial Y1 receptor-expressing neurons are a critical hub for endogenous analgesic pathways that suppress sustained pain states.

Deep sequencing of Phox2a nuclei reveals five classes of anterolateral system neurons

The anterolateral system (ALS) is a major ascending pathway from the spinal cord that projects to multiple brain areas and underlies the perception of pain, itch and skin temperature. Despite its importance, our understanding of this system has been hampered by the considerable functional and molecular diversity of its constituent cells. Here we use fluorescence-activated cell sorting to isolate ALS neurons belonging to the Phox2a-lineage for single-nucleus RNA sequencing. We reveal five distinct clusters of ALS neurons (ALS1-5) and document their laminar distribution in the spinal cord using in situ hybridization. We identify 3 clusters of neurons located predominantly in laminae I-III of the dorsal horn (ALS1-3) and two clusters with cell bodies located in deeper laminae (ALS4 & ALS5). Our findings reveal the transcriptional logic that underlies ALS neuronal diversity in the adult mouse and uncover the molecular identity of two previously identified classes of projection neurons. We also show that these molecular signatures can be used to target groups of ALS neurons using retrograde viral tracing. Overall, our findings provide a valuable resource for studying somatosensory biology and targeting subclasses of ALS neurons.