This story was originally published in the March 2025 issue of the Breakthroughs newsletter.
Investigators are advancing research to support proactive responses in diagnosing and preventing chronic diseases. Across departments, scientists at Feinberg are pursuing new ways of testing to determine a person’s risk of developing chronic conditions. From genetic testing to blood tests, there are new innovations that could help prevent disease and empower people to stay healthier longer.
One such study has been led by Rex L. Chisholm, PhD, vice dean for scientific affairs and graduate education and the Adam and Richard T. Lind Professor of Medical Genetics, for nearly two decades. The Emerge Network, funded by the National Human Genome Research Institute (NHGRI), is a collection of 10 sites across the country that study how collected genetic data merged with electronic medical records can help to detect a patient’s susceptibility to a particular condition and if someone would be better suited for a certain medication.
Beginning in 2007, the project has evolved over the years from first looking at how the team could utilize existing patient samples to provide a genetic risk assessment, to now being able to share clinical recommendations that are informed by an individual’s genome. Today, 25,000 people have been enrolled in the study.
Chisholm said the study has prevented disease and saved lives since it first began. Preliminary results from the current study has shown that as high as 50 percent of participants have followed their tailored clinical recommendations.
Further research is needed to follow up with folks within the study deemed “high-risk” and to determine if the information shared has reduced incidence of disease.
Chisholm believes studies like the Emerge Network will have an important impact on healthcare costs and preventive care.
“It is expensive to treat chronic disease,” Chisholm said. “While gene sequencing is also expensive, it should be demonstrated that sequencing is cheaper than treating a chronic health condition. A cost-benefit analysis could show that intervening earlier results in healthier people.”
Laura Rasmussen-Torvik, PhD, chief of Epidemiology in the Department of Preventive Medicine, and Elizabeth McNally, MD, PhD, Elizabeth J. Ward Professor of Genetic Medicine, are also PIs on the national study.
Developing Blood Tests for Respiratory Illness
Research coming out of the Department of Medicine’s Division of Pulmonary and Critical Care outlined a new blood test that could be used to identify adults at risk of developing severe respiratory illnesses, including chronic obstructive pulmonary disease (COPD).
The recent study published in the American Journal of Respiratory and Critical Care Medicine was led by Ravi Kalhan, MD, ‘06 MS, the Louis A. Simpson Professor of Pulmonary Medicine and associate dean of faculty affairs.
While COPD isn’t curable, treatments may help improve quality of life, however there are no established methods for detecting lung function decline early to prevent potential severe disease, according to Kalhan, was senior author of the study.
Using blood sample data from more than 2,400 participants enrolled in the Coronary Artery Risk Development in Young Adults (CARDIA) study, the team used a technique called discovery proteomics to identify 32 unique protein expression levels in the blood samples from individuals with lung function decline compared to those without.
These 32 proteins were then compiled into a proteomic risk score created by Kalhan’s team. The scientists then tested this risk score in two other patient cohorts, one from the COPDGene Study and the other from the U.K. Biobank, to examine associations with future respiratory morbidity and mortality.
“We think this is step one to finding out what causes COPD in the long run. It’s innovative in the sense that it takes a super-important clinical measure that no one can actually determine easily and synthesizes it into a blood test that now we know predicts bad outcomes,” said Kalhan, who is also co-director of the Northwestern University Clinical and Translational Sciences (NUCATS) Institute’s Center for Education and Career Development.
Kalhan said his team is currently validating their method to better identify patients at risk for COPD and medically attended respiratory illnesses that require healthcare contact or intervention.
“If we can do the hard work of figuring out what the causal roles of those proteins are and how they function and how this risk is conveyed, we can actually think about targets for interception of chronic lung disease before it becomes a problem,” Kalhan said.
Identifying Genetic Causes in Neurodegeneration
Within the Ken and Ruth Davee Department of Neurology, research continues to identify genetic causes of neurodegenerative diseases. A recent study published in Brain demonstrated a novel approach that can better identify and characterize genetic variant interactions associated with increased risk of Parkinson’s disease. This research improves the current understanding of the genetic heritability of the disease.
Identifying genetic drivers of the disease has long been a priority of the field: several genes are currently known to cause Parkinson’s disease, and 94 genetic risk variants have been identified from previous genome-wide association studies. Despite this progress, previous studies have only been able to identify approximately one-third of genetic drivers of Parkinson’s disease, said Bernabe Ignacio Bustos, PhD, a postdoctoral fellow in the laboratory of Dimitri Krainc, MD, PhD, and a co-first author of the study.
In the study, the team designed and used the genome approach VARI3 with a combined dataset consisting of 14 patient cohorts of European ancestry in collaboration with members of the International Parkinson’s Disease Genomics Consortium and identified 14 genetic variant interactions associated with a significant increase in Parkinson’s disease risk.
Next, using four independent Parkinson’s disease datasets, the investigators identified genotype combination risk profiles that are associated with overlapping genotype combination specific expression patterns.
Further analysis also demonstrated that the epistatic effect on Parkinson’s disease of those variants was observed in both patients with European ancestry and with Native American ancestry.
“This is exciting as, not only are we seeing that variants do work together to increase Parkinson’s disease risk, but we’re also beginning to see that different genotype combinations within an epistatic association are influencing how genes are expressed,” Bustos said.
The findings demonstrate how genetic variants work both alone and together to influence Parkinson’s disease risk, which may inform the development of novel therapeutic targets or biomarkers for determining disease risk.
According to Bustos, his team aims to confirm their findings in a laboratory to understand exactly how these interactions impact cells and contribute to disease risk and how these genetic interactions affect people from diverse racial and ethnic backgrounds.
“Our goal is to use this information to build a risk prediction tool that combine these genetic findings with other known risk factors, which could help physicians more accurately predict an individual’s risk for Parkinson’s disease and provide personalized advice or care,” Bustos said.
Overall, scientists at Feinberg are working toward prevention and risk prediction techniques that could impact human health.
“In all the work that we do, we are trying to improve health for the next generation,” Chisholm said. “The work being done across departments on risk prediction is a testament to that.”
Melissa Rohman contributed to this story.
