It’s official: May is Cystic Fibrosis Awareness Month! So myself, and the Patient Worthy team, are excited to bring you some stories to help build your awareness and increase patient advocacy. At the end of April, researchers from Vanderbilt University Medical Center found a novel way to determine misdiagnosed or undiagnosed cases of cystic fibrosis in medical records.
Cystic Fibrosis
Cystic fibrosis (CF) is a genetic disorder which causes thick, sticky mucus to accumulate in the lungs. This mucus allows for the build-up of potentially dangerous bacteria. In addition, it may lead to breathing difficulties, problems with nutrient absorption, and lung damage that worsens over time.
The disorder stems from a mutated CFTR gene. In fact, it is considered a Mendelian condition, or one caused by single-gene mutations. Basically, people with CF receives one mutated gene from each parent.
Symptoms include shortness of breath, frequent lung and sinus infections, a chronic cough, infertility in males, digestive issues, problems with weight gain, and male infertility. However, these vary in severity. Patients can take antibiotics to mitigate the symptoms, or partake in other therapies to help maintain lung function. Lung transplants are needed when lung function severely declines.
Other conditions that mimic symptoms of CF include asthma, primary ciliary dyskinesia, or bronchiolitis. Because cystic fibrosis presents in different ways, especially depending on patient, it is sometimes difficult to diagnose using current diagnostic systems. Find out more on cystic fibrosis.
The New Approach
Researchers wanted to create a more effective way to diagnose cases of cystic fibrosis. Additionally, they hoped this strategy would allow them to better research other Mendelian conditions (or Mendelian diseases) in the future. To start, researchers decided to study electronic health records (EHRs) within a biobank.
The National Institute of Health (NIH) defines biobanks as:
respositor[ies] that store and manage biological samples known as biospecimens for use in research.
In this case, researchers used BioVU, or “Vanderbilt’s collection…of de-identified DNA samples.” The samples were sourced from 9142 patients.
Researchers then created genetically regulated models of cystic fibrosis transmembrane conductance regulator (CFTR), normally expressed via the CFTR gene. Using this expression, they marked down phenotypes, or observable traits, associated with cystic fibrosis.
Next, they created a phenotype risk score (PheRS). This was applied to EHRs from an additional 2.8 million VUMC patients, and 125,305 other patients. As a result, researchers were able to identify CF diagnoses missed in previous diagnostic testing.
This new strategy can help identify undiagnosed cases of cystic fibrosis, allowing for patients to receive better education and care.
Find their full study in Genetics in Medicine.
