{"title":"Modeling Pain Without Injury: Inherited Rodent Models as Mechanistic Windows into Chronic Pain.","authors":"Luiz F Ferrari, Norman E Taylor","doi":"10.1093/function/zqaf043","DOIUrl":null,"url":null,"abstract":"<p><p>Chronic pain is a multifactorial condition often accompanied by comorbidities such as anxiety, depression, and cardiovascular dysfunction. Traditional injury-based models have provided valuable mechanistic insights but are limited in their ability to capture the spontaneous, polygenic, and systemic nature of human chronic pain. Inherited pain models, such as consomic rat strains, transgenic mice, and recombinant inbred panels, offer a unique advantage towards bridging this translational gap: they enable the study of pain-related mechanisms in the absence of experimental injury, reducing confounding effects and better reflecting clinical complexity. These models serve as powerful platforms to investigate neuroimmune signaling, oxidative stress, and epigenetic regulation, and to explore how these pathways interact with sex, stress, and systemic comorbidities. Importantly, while referred to as \"inherited pain models\", these systems are not designed to model pain transmission across generations, but rather to uncover genetically-driven susceptibility to pain and its mechanistic basis. Many of the mechanisms identified in these models overlap with findings from human genome-wide association studies (GWAS), reinforcing their translational relevance. Beyond mechanistic discovery, inherited pain models can be used for the identification of biomarkers, the study of gene-environment interactions, and the development of mechanism-based therapies. Integration with multi-omics technologies and patient-derived systems further enhance their utility. This review highlights how these models are reshaping the field by enabling biologically-informed approaches to diagnosis, prevention, and treatment, thus laying the foundations for a more precise and proactive era in pain medicine.</p>","PeriodicalId":73119,"journal":{"name":"Function (Oxford, England)","volume":" ","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Function (Oxford, England)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/function/zqaf043","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Chronic pain is a multifactorial condition often accompanied by comorbidities such as anxiety, depression, and cardiovascular dysfunction. Traditional injury-based models have provided valuable mechanistic insights but are limited in their ability to capture the spontaneous, polygenic, and systemic nature of human chronic pain. Inherited pain models, such as consomic rat strains, transgenic mice, and recombinant inbred panels, offer a unique advantage towards bridging this translational gap: they enable the study of pain-related mechanisms in the absence of experimental injury, reducing confounding effects and better reflecting clinical complexity. These models serve as powerful platforms to investigate neuroimmune signaling, oxidative stress, and epigenetic regulation, and to explore how these pathways interact with sex, stress, and systemic comorbidities. Importantly, while referred to as "inherited pain models", these systems are not designed to model pain transmission across generations, but rather to uncover genetically-driven susceptibility to pain and its mechanistic basis. Many of the mechanisms identified in these models overlap with findings from human genome-wide association studies (GWAS), reinforcing their translational relevance. Beyond mechanistic discovery, inherited pain models can be used for the identification of biomarkers, the study of gene-environment interactions, and the development of mechanism-based therapies. Integration with multi-omics technologies and patient-derived systems further enhance their utility. This review highlights how these models are reshaping the field by enabling biologically-informed approaches to diagnosis, prevention, and treatment, thus laying the foundations for a more precise and proactive era in pain medicine.