Diabetes is the most common cause of peripheral neuropathy (DPN). Clinical practice is focused on screening for loss of sensation to touch, mediated by myelinated Aß fibers. These ‘large’ fibers are affected later in the course of disease than ‘small’ thinly or unmyelinated Ad and C-fibers. These fibers transmit sensations of thermal and painful stimuli. Early detection and diagnosis of small fiber neuropathy in DPN would help alleviate comorbidities associated with DPN. To address this need, we propose to validate diagnostic procedures including laser evoked potentials (LEPs) in a population of non-Hispanic Black (NHB) and non-Hispanic White (NHW) patients with painful and painless DPN. Our goal is to develop neural network models comprised of noninvasive assessments of symptoms, signs, and EEG features that successfully diagnose patients with DPN. The secondary goal is to develop neural network models to separate patients with painful DPN from those with the painless DPN. We hypothesize that the inclusion of highly disease-sensitive LEP data will enable the model to effectively separate diagnostic groups irrespective of racialized group with superior accuracy compared to one variable models or standard diagnostic algorithms. This hypothesis will be tested through the following aims: SA1: Develop and standardize painful and warm laser stimuli and LEPs to diagnose small fiber DPN in NHBs and NHWs. We aim to determine a) detection thresholds for warm and painful laser stimuli, and pain intensity curves for painful heat in NHBs and NHWs with and without DPN; b) LEPs for warm and painful stimuli in NHBs and NHWs with and without DPN and c) relationships between quantitative measures of skin pigmentation and LEPs. SA2: Diagnose small fiber neuropathy in patients with painful and painless DPN using a set of measurements and neural network models and identify specific neurophysiologic features underlying diagnosis. Previous development of LEPs for diagnosis of DPN have excluded NHBs. Our preliminary success evoking LEPs in NHBs supports feasibility and safety. Completion of this work will establish diagnostic algorithms to be tested in future studies. Determining the characteristics of laser-evoked potentials in NHB participants will add a tool to investigate racialized group differences in pain processing to make our understanding of pain processing representative of the US population. One undergraduate student’s summer pay is included in the grant to engage in a 2-month research experience. Students from Morgan State University undergraduate research programs will be recruited to assist with this study. The principal investigator has published 5 abstracts in local and national venues and two manuscripts in peer-reviewed journals since 2020 with 5 undergraduates from MSU and 4 undergraduates from Johns Hopkins University.

ASCEND@MSU Pilot

2024-06-01

2025-06-01