# Multipronged approach to diminish sympathetic hyperreflexia and ensuing cardiovascular and immune dysfunction after spinal cord injury

> **NIH NIH R01** · DREXEL UNIVERSITY · 2022 · $441,416

## Abstract

PROJECT SUMMARY
Spinal cord injury (SCI) is a devastating event sustained by as many as 1.3 million Americans. While not often
appreciated, cardiovascular disease and susceptibility to infection are leading causes of mortality and morbidity
in individuals living with SCI. One major reason thought to underlie these issues is SCI-induced dysregulation
of the sympathetic nervous system. In this proposal, we will use a clinically-relevant contusion rodent SCI model
to test the hypothesis that intracellular sigma peptide (ISP) will promote sufficient sprouting of serotonergic
axons onto neurons in the spinal sympathetic circuit below the SCI to normalize sympathetic activity after injury.
Furthermore, we hypothesize that administering a combining ISP and inhibition of soluble tumor necrosis factor
alpha (sTNFα) with XPro1595 – which target different root causes of sympathetic hyperreflexia after SCI (i.e.,
interrupted supraspinal input the spinal sympathetic circuit and sTNFα-induced maladaptive plasticity of the
spinal sympathetic circuit, respectively) – will have synergistic effects on improving cardiovascular and immune
function after SCI.

## Key facts

- **NIH application ID:** 10387726
- **Project number:** 1R01NS122371-01A1
- **Recipient organization:** DREXEL UNIVERSITY
- **Principal Investigator:** Veronica Jean Tom
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $441,416
- **Award type:** 1
- **Project period:** 2022-04-01 → 2027-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10387726

## Citation

> US National Institutes of Health, RePORTER application 10387726, Multipronged approach to diminish sympathetic hyperreflexia and ensuing cardiovascular and immune dysfunction after spinal cord injury (1R01NS122371-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10387726. Licensed CC0.

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