Quantitative sensory testing–based sensory phenotypes align with measures of peripheral nerve damage in patients with painful polyneuropathies

: Quantitative sensory testing (QST) is increasingly used to stratify patients with peripheral neuropathic pain into sensory phenotypes that may reflect distinct underlying pain mechanisms. Yet, their correspondence with objective measures of peripheral nerve damage remains unclear. This study investigated whether QST-based phenotypes are associated with objective measures of peripheral nerve damage in patients with painful polyneuropathy. We retrospectively analyzed data from 130 patients with painful polyneuropathy, who underwent nerve conduction studies, distal leg skin biopsy, and QST at the foot dorsum. Using an established algorithm, patients were classified into 4 QST sensory phenotypes: Sensory Loss, Mechanical Hyperalgesia, Thermal Hyperalgesia, and Healthy. We assessed sural sensory nerve action potential (SNAP) amplitude, intraepidermal nerve fiber density using PGP9.5, TRPV1, and GAP43 immunostaining, as well as TRPV1 and GAP43/PGP9.5 ratios. These parameters were compared across QST phenotypes. Associations were analyzed using multinomial logistic regression models. Patients with the Sensory Loss phenotype-the most prevalent subgroup-had significantly lower sural SNAP amplitudes and intraepidermal nerve fiber densities of PGP9.5, TRPV1, and GAP43, compared with the other phenotypes. Compared with Sensory Loss, Mechanical Hyperalgesia demonstrated higher sural SNAP amplitudes (P < 0.0001), TRPV1/PGP9.5 (P = 0.018), and GAP43/PGP9.5 ratios (P = 0.011), whereas Thermal Hyperalgesia was associated with higher sural SNAP amplitudes (P = 0.041) and PGP9.5 intraepidermal nerve fiber density (P = 0.025). Our study demonstrates that QST-based phenotypes are associated with distinctive patterns of peripheral nerve damage in patients with painful polyneuropathy. These findings suggest that QST phenotyping may capture different aspects of underlying pain mechanisms, supporting its value for mechanism-based patient stratification.