Genome-targeting strategies to address NaV1.7-mediated signaling in nociceptive afferents are of great clinical interest given its high selectivity and persistent analgesic outcomes. In the present work, we analyze concentration-dependent effects of suppressing primary afferent NaV1.7 using the intrathecal delivery of an antisense oligonucleotide (ASO) on pain behaviors and demonstrate that NaV1.7 ASOs are likely to modulate pain traffic by blocking afferent signaling at the dorsal root ganglion (DRG) level. Intrathecal NaV1.7 ASOs induced a concentration-dependent gradient of knockdown in DRGs (lumbar to cervical) of Scn9a mRNA and ATTO488-ProTx-II binding in small DRG neurons, and a suppression of pain behaviors initiated by mechanical compression, inflammation, and the NaV1.7 agonist OD-1. The rostro-caudal reduction in mRNA correlated with ASO distribution, with implications for dose-related analgesic profiles. Marked reduction in DRG NaV1.7 binding was seen after intrathecal delivery of an ASO optimal dose, with high selectivity for small DRG neurons. Changes in sciatic nerve NaV1.7 binding were not detected, indicating a pain traffic modulation likely happening due to a block of afferent signaling at the DRG level.
Kaue Malange, Julia Borges Paes Lemes, Briana Noble, Yuvicza Anchondo, Carlos E. Morado-Urbina, Saee Jadhav, Saurabh Yadav, Jingrui Ma, Vineet Augustine, Sara A. Dochnal, Chiraag Kambalimath, Marie Duong, Pedro Alvarez, Bethany Fitzsimmons, Curt Mazur, Holly B. Kordasiewicz, Kim Dore, Hien T. Zhao, Tony Yaksh
Usage data is cumulative from October 2026 through October 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 158 | 0 |
| 66 | 0 | |
| Figure | 104 | 0 |
| Supplemental data | 28 | 0 |
| Citation downloads | 40 | 0 |
| Totals | 396 | 0 |
| Total Views | 396 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.