# Influence of inflammation-related genetic variants on PT treatment response in a population affected by CLBP

> **NIH NIH U19** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $100,000

## Abstract

Project Summary
Chronic Low Back Pain (CLBP) is a complex multi-factorial condition, as well as the most prevalent painful
musculoskeletal disorder worldwide. Its causes and mechanisms are numerous and still poorly understood,
which leads to common failure in its clinical treatment (e.g. physical therapy - PT). Systemic inflammation has
been gaining attention in the literature as a likely contributing aspect to CLBP, but its causes are diverse and still
lack thorough insight. One of these causes seems to be the presence of specific SNPs (Single Nucleotide
Polymorphism, the simplest and most common variation in human DNA) in certain genes that are known to be
related to both inflammation and pain. It is unclear how these variations may affect the outcomes of different
types of PT treatment for CLBP, which is an innovative aspect of the proposed research project. Overall, the
main objective is to be able to better tailor specific PT treatment to each patient. More specifically, this research
aims to understand if there is an association between gene variations and outcomes of PT treatment; it also
intends to better understand the mechanisms behind how gene variations affect inflammation, to support the
formation of novel research questions in the area of pain. Furthermore, it seeks to determine clinical sub-
phenotypes of CLBP using machine learning (Network Phenotyping Strategy - NPS) based on patients’
responsiveness to PT treatment. From a career standpoint, it aims at supporting my professional development
for a future in pain research and academia.
The project will use genetic and clinical data from 200-250 patients, gathered from the 1000 patients’ cohort that
the Pitt LB3P Mechanistic Research Center will collect; it will include all the patients with CLBP and no diagnosis
of inflammatory or auto-immune disease who will undergo PT treatment as part of their standard of care within
the University of Pittsburgh Medical Center (UPMC). The data that will be used for this study includes the
variations for selected genes, PT treatment (to be collected as a novel aspect facilitated by this proposed
supplement), the outcomes variables (disability and pain scores, pain interference, the impression of change),
as well as other clinically relevant information (e.g. age, sex, comorbidities). The analysis will be performed with
two different approaches: first, it will be analyzed with the traditional statistical testing for genetic variations, to
look for associations between SNPs and PT treatment outcomes. The analysis will include Logistic regression
analysis for the association between genetic variations and outcome measures, Fisher's exact test for proper
group determination, Cochran’s Q test for multiple groups if a non-paired assumption will be found to be more
clinically relevant. Subsequently, the dataset will be analyzed using the NPS approach, which will help delineate
clinical outcome-based phenotypes based on clinical response to PT treatment...

## Key facts

- **NIH application ID:** 10208162
- **Project number:** 3U19AR076725-01S1
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Gwendolyn A Sowa
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $100,000
- **Award type:** 3
- **Project period:** 2019-09-26 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10208162

## Citation

> US National Institutes of Health, RePORTER application 10208162, Influence of inflammation-related genetic variants on PT treatment response in a population affected by CLBP (3U19AR076725-01S1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10208162. Licensed CC0.

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