Sana Syed, MD, is a gastroenterologist and physician-scientist at UVA Health Children’s. Her research, while greatly varied, is all focused on improving outcomes for children worldwide. For her, research is about health equity.
Syed’s NIH-funded research uses state-of-the-art molecular and data science techniques to characterize the metabolic shifts, genetic signatures, and tissue features associated with pediatric inflammatory bowel diseases. Using cutting-edge molecular and computational image analysis techniques, the Syed Lab studies intestinal structure and function in patients with inflammatory diseases of the gastrointestinal tract.
Syed’s global health research is primarily centered on identifying early signatures of environmental enteric dysfunction, considered the primary driver for stunting in many low- and middle-income countries, while her research in the U.S. centers on leading collaborations to better diagnose inflammatory bowel diseases and predict patient-specific future outcomes of disease. Syed’s research aims to improve diagnostics, outcome predictions, and personalized medical care for children all around the world.
See Syed's selected publications. Below, Syed discusses the applications of her research and answers our Researcher Highlight questions:
What are you working on right now?
Right now, my research is focused on three core themes:
- Using computational image analysis to explore key features of luminal inflammatory enteropathies, like celiac disease, environmental enteric dysfunction, and Crohn’s disease, to predict patient-specific outcomes.
- Pinpointing specific metabolic signatures of luminal inflammatory enteropathies and using these signatures to classify disease subtypes, predict disease progression, and identify biomarkers and therapeutic targets.
- Mapping the early (0-5 year) gut development at a single-cell resolution, and linking these cellular maps with contextual data on tissue morphology, genetic background, social determinants of health, and environmental exposures.
Through these efforts, we aim to better understand the person-to-person variation in the healthy gut and use this information to improve studies into various gastrointestinal diseases. This will not only help enhance our scientific knowledge of various diseases and development states, but it will also derive new clinical paradigms to provide precision medicine designed for an individual patient’s genes, environment, and lifestyle.
What are the most intriguing potential clinical applications of your work?
Artificial intelligence offers healthcare researchers an increasing number of potential avenues to improve patient care. Along with a multidisciplinary team of physicians, data scientists, and engineers, we have been working together to build new tools to better care for our pediatric gastroenterology patients.
Our team has recently harnessed our increased computational capacity to process data, recognize patterns, and accurately assess complex medical issues to identify promising advancements in treating children with celiac disease and inflammatory bowel disease. The most intriguing application of this research is that we’ll better understand the tissue changes associated with disease, as well as the changes in gene expression, proteins, and lipids that go hand-in-hand with these tissue features.
By illuminating these “fingerprints” of disease, we can provide a bench-to-bedside platform that leverages information obtained as part of a patient’s standard clinical visits to provide patient-specific care and improve health outcomes for all.
What made you choose UVA Health as the place to do your research?
When I completed my training in clinical pediatrics and gastroenterology, my career goal was to pursue research in undernutrition, with a focus on global health. I was interested in coming to UVA Health because of numerous faculty who have successful careers combining their passion for global health, research, and clinical medicine. I was fortunate to find a home in pediatrics and supportive mentors in our department and across the School of Medicine.
What do you wish more people knew about your area of research?
As a pediatrician, research is – at its very core – about equity and justice. When I take care of children in my clinical practice, we see all these gaps where we don’t yet understand why something is happening or don’t have a tool needed to provide better care.
As a researcher, I can then go back and help try and find answers to these challenges and improve our patient outcomes. By doing so, you create a new future and opportunities for the patients that we're seeing today. So, I really think science is about developing the next generation.
I hope my career will be about supporting and developing the next generation with a focus on women and underrepresented minorities. I think it will be such a huge contribution if we, in any small way, reduce the burden of childhood undernutrition and understand what causes it and how to solve it.
Machine learning is one way we can contribute to our understanding and treatment of childhood undernutrition. Our clinics collect so much research, but the volume of this data and the different forms the data comes in make it extraordinarily challenging for humans to identify relationships between this information. AI tools allow us to process and synthesize larger and larger volumes of data or recognize changes beyond the ability of our senses. The ultimate goal of using AI in medicine is to optimize support tools to help physicians make more informed clinical decisions.
How did you become interested in your area of research?
I really love children. I love them in all their shapes and sizes. I love tiny babies. I love grumpy teenagers who won't tell you anything that's going on in their lives. I love the 5-year-olds who will tell you every single thing. On a global scale, any society's most vulnerable members are often its women and children. So knowing this was a need and knowing I loved children is really what drove me into pediatrics.
Although fortunate to grow up in a healthy environment, I have seen firsthand the impacts of undernutrition on childhood growth. Globally, we know ~45 million children under 5 years of age suffer from wasting, and nearly 150 million experience stunted growth due to chronic undernutrition and disease. My passion for helping all children live happy, healthy lives has centered my research on studying intestinal structure and function in the context of luminal inflammatory diseases.
When I joined UVA Health, I knew I wanted to study undernutrition and global health with a focus on children, yet exactly how I could best distinguish myself was undetermined. Around this time, I knew little about data science except that the field of data science had already developed incredibly useful tools and technologies for probing molecular causes of disease from the extraordinary amounts of data collected during clinical care. As I explored and learned more, I was driven by a desire to use big data to improve human health.