Dec. 17, 2025
Demystifying Chronic Low Back Pain
Researchers from across Pitt Health Sciences are examining patterns of low back pain to find the best treatment options based on individuals’ experiences.
Unprecedented collaboration. Groundbreaking research.
By MCRE and Gwendolyn Sowa
Imagine an auditorium filled with individuals of varying ages, genders and races. They have different medical histories, educational backgrounds and incomes. But they have one thing in common—chronic lower back pain (cLBP).
How do you treat these individuals?
Clinicians agree that there is no single answer.
Despite the fact that lower back pain affects an estimated 619 million people and is a leading cause of disability worldwide, the chronic nature of the disease and the changing course of an individual’s experience of pain over time are poorly understood. Not all lower back pain has the same intensity and duration. And the pain may be caused by a wide range of factors and respond to different treatments with unpredictable varied efficacies.
The multifaceted nature of the disease requires multifaceted approaches, with experts from diverse fields viewing the disease through different lens.
What they have learned is different from any research they could possibly conduct if they stayed in their own silos.
Do phenotypes hold the key to treatment options?
For more than five years, researchers from various departments within the University of Pittsburgh School of Health and Rehabilitation Sciences (SHRS) have been collaborating with colleagues from the School of Medicine (SOM) and the Swanson School of Engineering (SSOES) to examine various phenotypes, or patterns, that contribute to an individual’s experience of low back pain in the hopes of being able to predict the best treatment options.
The word “phenotype” is a scientific term for a cluster of characteristics that suggest a clinical pattern or profile. Saying that someone simply has chronic low back pain is not helpful for determining which treatment is best for that patient. This research is designed to find specific clinical patterns or profiles (phenotypes) that will help inform decision-making about which treatment or treatments work best for which phenotype.
While collaboration between different Pitt Health Sciences departments and schools is not unusual, the scope and longevity of this particular project is.
Starting in 2019, an interdisciplinary team of medical doctors, surgeons, physical therapists, chiropractors, engineers, psychologists, biologists and data scientists began following 1,007 participants enrolled in the Lower Back Pain: Biological, Biomechanical, Behavioral Phenotypes (LB3P) observational study, part of the National Institutes of Health (NIH) Back Pain Consortium (BACPAC).
Researchers were divided into core groups that approached cLBP from different perspectives, comprehensively amassing an unprecedented amount data. They collected biosamples and biomarkers, examined movement, behavioral experiences and social determinants of health before categorizing the results into clusters of phenotypes.
According to Gwendolyn Sowa, chair, Department of Physical Medicine and Rehabilitation in the School of Medicine and coprincipal investigator (PI), “It’s all about finding the right treatment for the right patient at the right time.”
Today, thanks to a new $20 million grant from the National Institute of Arthritis and Musculoskeletal and Skin Diseases, the same team of researchers is building on their past work in a new study known as the Holistic Pain Phenotyping (H2P) that will bring them even closer to understanding the whole patient experience of pain.
“This team is committed to working together without barriers to find the most effective non-opioid treatments for pain,” continues Sowa.
Michael Schneider, professor of community health and rehabilitation science and director of the Doctor of Chiropractic program within SHRS, has joined forces with Sowa on a number of other studies in years prior to the LB3P project. He believes this type of interprofessional collaboration could only happen at Pitt.
“Pitt has extraordinary people with extensive experience who are willing to put their personal interests aside and come together to tackle a problem that each of us sees in our individual practices. It’s very unique,” says Schneider.
“I have not seen this level of professional respect and enthusiasm around collaboration anywhere else,” adds Sowa.
Core groups meet several times each month, either in-person or virtually, to discuss strategies, analyze data and share insights. They have come to trust one another implicitly and see each other’s contributions in a new light. What they have learned is different from any research they could possibly conduct if they stayed in their own silos.
For example, Carol Greco, emeritus associate professor of psychiatry in the SOM and internationally renowned researcher, is part of the behavioral core, along with Schneider. She weighs in on psychosocial factors that improve pain and functioning in persons with chronic disease. In the biomechanical core, Kevin Bell, assistant professor of bioengineering in SSOE, brings his knowledge of wearable devices that measure joint motions and activity of individuals with cLBP to complement his colleague Assistant Professor William Anderst’s novel kinematics assessments from the SOM’s Department of Orthopaedic Surgery.
Charity Patterson, director of the SHRS Data Center, serves as codirector of the informatics core for both cLBP studies, along with Gina Pugliano McKernan, assistant professor of physical medicine and rehabilitation, SOM. Together they oversee data governance, monitoring, sharing and statistical analysis.
“Pitt fosters interdisciplinary collaboration through a culture that actively encourages and celebrates crossdisciplinary work,” says Bell. “But what stands out most is the shared commitment of my colleagues. Each brings world-class expertise and a genuine openness to learning from one another. That spirit of collaboration is what makes this work possible and what will ultimately lead to breakthroughs in care.”
The results are (almost) in!
Data from the LB3P study is currently being analyzed even as the new H2P study begins.
Patterson, McKernan and Leming Zhou, associate professor of health information management, SHRS, are using artificial intelligence and machine learning models to analyze thousands of variables. “We are using both traditional clustering methods and novel methods to best understand the diverse sample of our low back pain participants,” explains McKernan.
“In addition to identifying phenotypes, we are looking into identifying novel biomarkers that relate to the person's experience of pain and functional outcomes in response to treatments. It’s a very exciting time for us,” says Sowa.
Nam Vo, professor of orthopaedic surgery, SOM, and the study’s coPI, says LB3P was a landmark study in terms of data collection. “Never before has anyone phenotyped such a large group of participants. And now we have the opportunity to let that data inform us in a new study that follows those same participants for another five years,” explains Vo.
Professor and Department of Physical Therapy Chair Sara Piva, who led a team that recruited and retained participants for both studies, says this is significant.
“The data will be especially valuable because every one of the 1,007 original participants has agreed to come back for the H2P study,” says Piva. ”The first five years of observation allowed us to group people into clusters by phenotypes, but during the next five years we will see how their pain has evolved—with or without various types of treatment—as well as how it relates to other painful conditions.”
“All of this is leading up to precision medicine—the ability to use a person’s unique biological and physical makeup, as well as their psychological dispositions,” notes Schneider. “It will eventually allow us to prescribe the most effective treatment for different individuals. And that’s what every one of us is hoping to do.”