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Neuropathic pain arises from dysfunction of the peripheral or central nervous system and affects up to 10% of the population worldwide. Aberrant activity in injured sensory nerve fibers, particularly spontaneous firing and altered conduction properties of nociceptors, is tightly linked to pain, yet its molecular underpinnings in humans have long remained elusive. Over recent years, major technological advances have transformed both functional and molecular analyses of sensory neurons. High-resolution single-cell and spatial transcriptomics have produced detailed atlases of sensory neuron diversity, while traditional electrophysiological approaches such as patch-clamp and microneurography have provided unparalleled insight into nerve fiber properties. Despite their individual strengths, molecular and functional classifications of sensory neurons have largely evolved in parallel. This review focuses on emerging strategies that bridge these approaches to achieve an integrated, mechanistic understanding of neuropathic pain. We discuss how microneurography-defined biophysical hallmarks, such as activity-dependent slowing, recovery cycle signatures, and following frequency, can be transferred into in vitro patch-clamp paradigms, enabling direct functional comparison with dissociated human and large-animal sensory neurons. The incorporation of Patch-seq approaches has further enabled the assignment of molecular identity to functionally defined nociceptor subtypes, exemplified by the characterization of the mechano-insensitive "sleeping" nociceptors. Finally, we highlight how multimodal datasets combining electrophysiology, transcriptomics, and computational modeling provide new opportunities to unravel the ion channel mechanisms, particularly sodium channel subtypes, that shape pathological firing states. By directly linking human nerve fiber function to molecular programs, this integrative framework paves the way toward stratified, mechanism-based therapies for neuropathic pain.
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Lampert et al. (2026) studied this question.
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