Splenic Ultrasound to Treat Rheumatoid Arthritis
Splenic ultrasound (SUS) is an emerging noninvasive immunomodulatory therapy in which ultrasound at diagnostic intensities is applied to the spleen, causing a reduction in pro-inflammatory cytokine production through activation of the cholinergic anti-inflammatory pathway. One promising application of this therapy is in the treatment of rheumatoid arthritis (RA), an autoimmune disease in which excess cytokines drive chronic inflammation and joint destruction.
The lab of MSI PI Hubert Lim (Professor, Otolaryngology – Head and Neck Surgery) has promising animal data, including demonstration of SUS-mediated reductions in joint swelling in a mouse model of RA, which led to initiation of a human trial in participants with RA (ClinicalTrials.gov: NCT03690466). Up to 20 participants with RA will have received either a two-week course of daily SUS or sham therapy, and blood draws are being performed at three time points to assess levels of RA biomarkers. In samples from a subset of treatment and control/sham participants, peripheral blood mononuclear cells (PBMCs) were isolated and processed for single cell RNA-sequencing. Analyses of these sequencing data, which will elucidate how SUS affects gene expression in PBMCs, will be performed by Dr. Marissa Macchietto of the Research Informatics Group at MSI. Knowledge gained will yield new insights into SUS’s mode of efficacy and inform new avenues of basic and clinical research in the use of SUS to treat inflammatory diseases.
This project recently received a UMII Seed Grant. UMII Seed Grant funds are intended to promote, catalyze, accelerate and advance UMN-based informatics research in areas related to the MnDRIVE initiative, so that UMN faculty and staff are well prepared to compete for longer term external funding opportunities. This project falls under the Discoveries and Treatments for Brain Conditions research area of the MnDRIVE initiative.
The Lim group also uses MSI to perform large-scale neural data analyses, create and run computation modeling for characterizing energy stimulation fields (e.g., electrical, ultrasound), use NEURON/neural modeling programs, and perform large-scale genomic/RNA-seq analyses.