Abstract
Joint pain is an increasing concern for our aging population, as current therapies to slow joint disease progression or reduce pain are largely ineffective and often carry significant health and dependency risks. Age and joint disease induce changes to all tissues that make up the joint, including the dense neural network that innervates the joint. Several studies have correlated joint innervation changes in diseases such as osteoarthritis or rheumatoid arthritis, but little is known about their respective functional consequences. How subtypes of knee-innervating neurons affect pain experience remains relatively uncharacterized. A few studies focused on a single neural subtype due to the limited availability of validated tools to study joint innervation. To better understand the relationship between aging, joint disease, and pain, systematic characterization of nociceptors and other neural subtypes regulating joint homeostasis and pain is urgently needed. This study’s objective was to establish a validated molecular and genetic toolbox for accurate mapping of the neuro-architecture in the murine knee. We screened genetic reporter mice, containing different combinations of Cre and Flp recombinase alleles along with recombinase responsive reporter alleles to either highlight peripheral nociceptors or post-ganglionic sympathetic neurons for their specificity and accuracy in labeling specific neural subtypes in the dorsal root ganglia, sympathetic ganglia, and the knee joint. Additionally, we compared the performance of a series of conventional retrograde tracers for effective labelling of sensory and sympathetic neurons innervating the knee joint. The validated molecular and genetic tools identified in this study will facilitate the creation of comprehensive joint innervation maps in physiological and pathological contexts, setting the stage for identifying the cellular and molecular changes responsible for mediating joint pain, a necessary goal for improved therapeutic interventions. Lay summary Joint diseases, such as Rheumatoid Arthritis and Osteoarthritis significantly affect the neural landscape in joints, impacting pain, balance, and joint health. Understanding these nerve changes can provide insights into the drivers of joint pain and potential treatments. Our study evaluated genetic and conventional neural tracer tools to visualize and track knee innervating nerve fibers. We found two genetic mouse lines that specifically highlight sensory and sympathetic nerves, making them suitable models for knee joint studies. Additionally, the fluorescent tracer True Blue, effectively marks cell bodies of knee-innervating neurons. These tools will help researchers better understand nerve changes in painful joint pathologies.
Full text
3,309 characters
· extracted from
oa-doi-fallback
· click to expand
Abstract
Joint pain is an increasing concern for our aging population, as current therapies to slow joint disease progression or reduce pain are largely ineffective and often carry significant health and dependency risks. Age and joint disease induce changes to all tissues that make up the joint, including the dense neural network that innervates the joint. Several studies have correlated joint innervation changes in diseases such as osteoarthritis or rheumatoid arthritis, but little is known about their respective functional consequences. How subtypes of knee-innervating neurons affect pain experience remains relatively uncharacterized. A few studies focused on a single neural subtype due to the limited availability of validated tools to study joint innervation. To better understand the relationship between aging, joint disease, and pain, systematic characterization of nociceptors and other neural subtypes regulating joint homeostasis and pain is urgently needed. This study’s objective was to establish a validated molecular and genetic toolbox for accurate mapping of the neuro-architecture in the murine knee. We screened genetic reporter mice, containing different combinations of Cre and Flp recombinase alleles along with recombinase responsive reporter alleles to either highlight peripheral nociceptors or post-ganglionic sympathetic neurons for their specificity and accuracy in labeling specific neural subtypes in the dorsal root ganglia, sympathetic ganglia, and the knee joint. Additionally, we compared the performance of a series of conventional retrograde tracers for effective labelling of sensory and sympathetic neurons innervating the knee joint. The validated molecular and genetic tools identified in this study will facilitate the creation of comprehensive joint innervation maps in physiological and pathological contexts, setting the stage for identifying the cellular and molecular changes responsible for mediating joint pain, a necessary goal for improved therapeutic interventions.
Lay summary Joint diseases, such as Rheumatoid Arthritis and Osteoarthritis significantly affect the neural landscape in joints, impacting pain, balance, and joint health. Understanding these nerve changes can provide insights into the drivers of joint pain and potential treatments. Our study evaluated genetic and conventional neural tracer tools to visualize and track knee innervating nerve fibers. We found two genetic mouse lines that specifically highlight sensory and sympathetic nerves, making them suitable models for knee joint studies. Additionally, the fluorescent tracer True Blue, effectively marks cell bodies of knee-innervating neurons. These tools will help researchers better understand nerve changes in painful joint pathologies.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Updates to this new version were minor and mainly to the text in the manuscript. These updates include changes to: Purpose statement in abstract; Background on RE-JOIN in intro; sample size in Methods; image analysis in Methods; Discussion statements in knee results, clarity in discussion on absence of DBH-reporter signal in knee sections. The updates in the new version did not change the results or conclusions from the original manuscript.
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.